diff --git a/README.md b/README.md
index d3ed4936..df98850e 100644
--- a/README.md
+++ b/README.md
@@ -3,7 +3,7 @@
 [![Build Status](https://travis-ci.org/justadudewhohacks/face-api.js.svg?branch=master)](https://travis-ci.org/justadudewhohacks/face-api.js)
 [![Slack](https://slack.bri.im/badge.svg)](https://slack.bri.im)
 
-**JavaScript face recognition API for the browser and nodejs implemented on top of tensorflow.js core ([tensorflow/tfjs-core](https://github.com/tensorflow/tfjs-core))**
+**JavaScript face recognition API for the browser and nodejs implemented on top of tensorflow.js core ([tensorflow/tfjs-core](https://github.com/tensorflow/tfjs))**
 
 ![faceapi](https://user-images.githubusercontent.com/31125521/57224752-ad3dc080-700a-11e9-85b9-1357b9f9bca4.gif)
 
@@ -16,6 +16,7 @@
 * **[Realtime Webcam Face Detection And Emotion Recognition - Video](https://youtu.be/CVClHLwv-4I)**
 * **[Easy Face Recognition Tutorial With JavaScript - Video](https://youtu.be/AZ4PdALMqx0)**
 * **[Using face-api.js with Vue.js and Electron](https://medium.com/@andreas.schallwig/do-not-laugh-a-simple-ai-powered-game-3e22ad0f8166)**
+* **[Add Masks to People - Gant Laborde on Learn with Jason](https://www.learnwithjason.dev/fun-with-machine-learning-pt-2)**
 
 ## Table of Contents
 
diff --git a/dist/face-api.js b/dist/face-api.js
index dfdc420a..a4373418 100644
--- a/dist/face-api.js
+++ b/dist/face-api.js
@@ -6,7 +6,7 @@
 
   /**
    * @license
-   * Copyright 2019 Google LLC. All Rights Reserved.
+   * Copyright 2020 Google LLC. All Rights Reserved.
    * Licensed under the Apache License, Version 2.0 (the "License");
    * you may not use this file except in compliance with the License.
    * You may obtain a copy of the License at
@@ -20,285 +20,291 @@
    * limitations under the License.
    * =============================================================================
    */
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match");ht().disposeTensor(this),this.dataId=t.dataId,ht().incRef(this,null);},n.prototype.dispose=function(){ht().disposeVariable(this),this.isDisposedInternal=!0;},n}(dt);Object.defineProperty(bt,Symbol.hasInstance,{value:function(t){return t instanceof dt&&null!=t.assign&&t.assign instanceof Function}}),function(t){t.R0="R0",t.R1="R1",t.R2="R2",t.R3="R3",t.R4="R4",t.R5="R5",t.R6="R6";}(vt||(vt={})),function(t){t.float32="float32",t.int32="int32",t.bool="int32",t.complex64="complex64";}(mt||(mt={})),function(t){t.float32="float32",t.int32="int32",t.bool="bool",t.complex64="complex64";}(gt||(gt={})),function(t){t.float32="float32",t.int32="float32",t.bool="float32",t.complex64="complex64";}(yt||(yt={})),function(t){t.float32="complex64",t.int32="complex64",t.bool="complex64",t.complex64="complex64";}(xt||(xt={}));var wt={float32:yt,int32:mt,bool:gt,complex64:xt};function Ct(t,e){if("string"===t||"string"===e){if("string"===t&&"string"===e)return "string";throw new Error("Can not upcast "+t+" with "+e)}return wt[t][e]}function Et(t){return Ct(t,"int32")}function Rt(t,e){if(t.dtype===e.dtype)return [t,e];var n=Ct(t.dtype,e.dtype);return [t.cast(n),e.cast(n)]}function It(t,e){g(t.dtype===e.dtype,function(){return "The dtypes of the first("+t.dtype+") and second("+e.dtype+") input must match"});}function kt(t){var e=[];return function t(e,n,r){if(null==e)return;if(e instanceof dt)return void n.push(e);if(o=e,!Array.isArray(o)&&"object"!=typeof o)return;var o;var a=e;for(var i in a){var u=a[i];r.has(u)||(r.add(u),t(u,n,r));}}(t,e,new Set),e}var St,At=Object.freeze({makeTypesMatch:Rt,assertTypesMatch:It,isTensorInList:function(t,e){for(var n=0;n<e.length;n++)if(e[n].id===t.id)return !0;return !1},getTensorsInContainer:kt}),Dt=function(){function t(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null};}return t.prototype.dispose=function(){for(var t in this.registeredVariables)this.registeredVariables[t].dispose();},t}(),Tt=function(){function t(t){this.ENV=t,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Dt;}return t.prototype.ready=function(){return n(this,void 0,void 0,function(){var t,e,n;return r(this,function(r){switch(r.label){case 0:if(null!=this.pendingBackendInit)return [2,this.pendingBackendInit.then(function(){})];if(null!=this.backendInstance)return [2];t=this.getSortedBackends(),e=0,r.label=1;case 1:return e<t.length?(n=t[e],[4,this.initializeBackend(n).success]):[3,5];case 2:return r.sent()?[4,this.setBackend(n)]:[3,4];case 3:return r.sent(),[2];case 4:return e++,[3,1];case 5:throw new Error("Could not initialize any backends, all backend initializations failed.")}})})},Object.defineProperty(t.prototype,"backend",{get:function(){if(null!=this.pendingBackendInit)throw new Error("Backend '"+this.backendName+"' has not yet been initialized. Make sure to await tf.ready() before calling other methods");if(null==this.backendInstance){var t=this.initializeBackendsAndReturnBest(),e=t.name;if(t.asyncInit)throw new Error("The highest priority backend '"+e+"' has not yet been initialized. Make sure to await tf.ready() before calling other methods");this.setBackend(e);}return this.backendInstance},enumerable:!0,configurable:!0}),t.prototype.backendNames=function(){return Object.keys(this.registryFactory)},t.prototype.findBackend=function(t){if(!(t in this.registry)){if(!(t in this.registryFactory))return null;if(this.initializeBackend(t).asyncInit)return null}return this.registry[t]},t.prototype.findBackendFactory=function(t){return t in this.registryFactory?this.registryFactory[t].factory:null},t.prototype.registerBackend=function(t,e,n){return void 0===n&&(n=1),t in this.registryFactory?(console.warn(t+" backend was already registered. Reusing existing backend factory."),!1):(this.registryFactory[t]={factory:e,priority:n},!0)},t.prototype.setBackend=function(t){return n(this,void 0,void 0,function(){var e,n,o;return r(this,function(r){switch(r.label){case 0:if(null==this.registryFactory[t])throw new Error("Backend name '"+t+"' not found in registry");return this.backendName=t,null!=this.registry[t]?[3,4]:(this.backendInstance=null,e=this.initializeBackend(t),n=e.success,e.asyncInit?[4,n]:[3,2]);case 1:return o=r.sent(),[3,3];case 2:o=n,r.label=3;case 3:if(!o)return [2,!1];r.label=4;case 4:return this.backendInstance=this.registry[t],this.setupRegisteredKernels(),this.profiler=new et(this.backendInstance),[2,!0]}})})},t.prototype.setupRegisteredKernels=function(){var t=this;c(this.backendName).forEach(function(e){null!=e.setupFunc&&e.setupFunc(t.backendInstance);});},t.prototype.disposeRegisteredKernels=function(t){var e=this;c(t).forEach(function(n){null!=n.disposeFunc&&n.disposeFunc(e.registry[t]);});},t.prototype.initializeBackend=function(t){var e=this,n=this.registryFactory[t];if(null==n)throw new Error("Cannot initialize backend "+t+", no registration found.");try{var r=n.factory();if(Promise.resolve(r)===r){var o=++this.pendingBackendInitId,a=r.then(function(n){return !(o<e.pendingBackendInitId)&&(e.registry[t]=n,e.pendingBackendInit=null,!0)}).catch(function(n){return !(o<e.pendingBackendInitId)&&(e.pendingBackendInit=null,console.warn("Initialization of backend "+t+" failed"),console.warn(n.stack||n.message),!1)});return this.pendingBackendInit=a,{success:a,asyncInit:!0}}return this.registry[t]=r,{success:!0,asyncInit:!1}}catch(e){return console.warn("Initialization of backend "+t+" failed"),console.warn(e.stack||e.message),{success:!1,asyncInit:!1}}},t.prototype.removeBackend=function(t){if(!(t in this.registryFactory))throw new Error(t+" backend not found in registry");this.backendName===t&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null);},t.prototype.getSortedBackends=function(){var t=this;if(0===Object.keys(this.registryFactory).length)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort(function(e,n){return t.registryFactory[n].priority-t.registryFactory[e].priority})},t.prototype.initializeBackendsAndReturnBest=function(){for(var t=this.getSortedBackends(),e=0;e<t.length;e++){var n=t[e],r=this.initializeBackend(n),o=r.success,a=r.asyncInit;if(a||o)return {name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")},t.prototype.moveData=function(t,e){var n=this.state.tensorInfo.get(e),r=n.backend,o=this.readSync(e);r.disposeData(e),n.backend=t,t.move(e,o,n.shape,n.dtype),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++;},t.prototype.tidy=function(t,e){var n,r=this,o=null;if(null==e){if("function"!=typeof t)throw new Error("Please provide a function to tidy()");e=t;}else{if("string"!=typeof t&&!(t instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if("function"!=typeof e)throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");o=t;}return this.scopedRun(function(){return r.startScope(o)},function(){return r.endScope(n)},function(){return (n=e())instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n})},t.prototype.scopedRun=function(t,e,n){t();try{var r=n();return e(),r}catch(t){throw e(),t}},t.prototype.nextTensorId=function(){return t.nextTensorId++},t.prototype.nextVariableId=function(){return t.nextVariableId++},t.prototype.clone=function(t){var e=this.makeTensorFromDataId(t.dataId,t.shape,t.dtype),n={x:t};return this.addTapeNode(this.state.activeScope.name,n,[e],function(t){return {x:function(){return t.toFloat()}}},[]),e},t.prototype.runKernel=function(t,e,n,r,o){return this.runKernelFunc(null,e,null,t,n,r,o)},t.prototype.shouldCheckForMemLeaks=function(){return this.ENV.getBool("IS_TEST")},t.prototype.checkKernelForMemLeak=function(t,e,n){var r=this.backend.numDataIds(),o=0;n.forEach(function(t){o+="complex64"===t.dtype?3:1;});var a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-e-o-a;if(i>0)throw new Error("Backend '"+this.backendName+"' has an internal memory leak ("+i+" data ids) after running '"+t+"'")},t.prototype.runKernelFunc=function(t,e,n,r,o,a,i){var u,c=this;void 0===a&&(a=[]),void 0===i&&(i=[]);var l,h=[],f=this.isTapeOn(),p=null!=this.state.activeScope?this.state.activeScope.name:"",d=function(t){f&&(h=t.map(function(t){return c.keep(c.clone(t))}));},v=this.state.numBytes,m=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);var g,y=s(r,this.backendName);return l=null!=y?function(){var t=c.backend.numDataIds();g=y.kernelFunc({inputs:e,attrs:o,backend:c.backend});var n=Array.isArray(g)?g:[g];c.shouldCheckForMemLeaks()&&c.checkKernelForMemLeak(p,t,n);var r=n.map(function(t){var e=t.dataId,n=t.shape,r=t.dtype;return c.makeTensorFromDataId(e,n,r)}),u=r.filter(function(t,e){return i[e]});return d(a.slice().concat(u)),r}:function(){var e=c.backend.numDataIds();g=c.tidy(function(){return t(c.backend,d)});var n=Array.isArray(g)?g:[g];return c.shouldCheckForMemLeaks()&&c.checkKernelForMemLeak(p,e,n),n},this.scopedRun(function(){return c.state.kernelDepth++},function(){return c.state.kernelDepth--},function(){u=c.ENV.getBool("DEBUG")?c.profiler.profileKernel(p,e,function(){return l()}):l();}),f&&this.addTapeNode(p,e,u,n,h),this.state.profiling&&this.state.activeProfile.kernels.push({name:p,bytesAdded:this.state.numBytes-v,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-m,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(e).map(function(t){return e[t].shape}),outputShapes:u.map(function(t){return t.shape})}),Array.isArray(g)?u:u[0]},t.prototype.makeTensor=function(t,e,n,r){if(null==t)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;var o=t;"string"===n&&W(t[0])&&(o=t.map(function(t){return J(t)}));var a=r.write(o,e,n),i=new dt(e,n,a,this.nextTensorId());if(this.incRef(i,r),"string"===n){var u=this.state.tensorInfo.get(a),s=L(o);this.state.numBytes+=s-u.bytes,u.bytes=s;}return i},t.prototype.makeTensorFromDataId=function(t,e,n,r){var o=new dt(e,n=n||"float32",t,this.nextTensorId());return this.incRef(o,r),o},t.prototype.makeVariable=function(t,e,n,r){void 0===e&&(e=!0),n=n||this.nextVariableId().toString(),null!=r&&r!==t.dtype&&(t=t.asType(r));var o=new bt(t,e,n,this.nextTensorId());if(null!=this.state.registeredVariables[o.name])throw new Error("Variable with name "+o.name+" was already registered");return this.state.registeredVariables[o.name]=o,this.incRef(o,this.backend),o},t.prototype.incRef=function(t,e){var n=this.state.tensorInfo.has(t.dataId)?this.state.tensorInfo.get(t.dataId).refCount:0;if(this.state.numTensors++,"string"===t.dtype&&this.state.numStringTensors++,0===n){this.state.numDataBuffers++;var r=0;"complex64"!==t.dtype&&"string"!==t.dtype&&(r=t.size*P(t.dtype)),this.state.tensorInfo.set(t.dataId,{backend:e||this.backend,dtype:t.dtype,shape:t.shape,bytes:r,refCount:0}),this.state.numBytes+=r;}this.state.tensorInfo.get(t.dataId).refCount++,t instanceof bt||this.track(t);},t.prototype.disposeTensor=function(t){if(this.state.tensorInfo.has(t.dataId)){this.state.numTensors--,"string"===t.dtype&&this.state.numStringTensors--;var e=this.state.tensorInfo.get(t.dataId);e.refCount<=1?("complex64"!==t.dtype&&(this.state.numBytes-=e.bytes),this.state.numDataBuffers--,e.backend.disposeData(t.dataId),this.state.tensorInfo.delete(t.dataId)):this.state.tensorInfo.get(t.dataId).refCount--;}},t.prototype.disposeVariables=function(){for(var t in this.state.registeredVariables){var e=this.state.registeredVariables[t];this.disposeVariable(e);}},t.prototype.disposeVariable=function(t){this.disposeTensor(t),null!=this.state.registeredVariables[t.name]&&delete this.state.registeredVariables[t.name];},t.prototype.memory=function(){var t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(t.unreliable=!0,null==t.reasons&&(t.reasons=[]),t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),t},t.prototype.profile=function(t){return n(this,void 0,void 0,function(){var e,n;return r(this,function(r){return this.state.profiling=!0,e=this.state.numBytes,n=this.state.numTensors,this.state.activeProfile.kernels=[],this.state.activeProfile.result=t(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max.apply(Math,this.state.activeProfile.kernels.map(function(t){return t.totalBytesSnapshot})),this.state.activeProfile.newBytes=this.state.numBytes-e,this.state.activeProfile.newTensors=this.state.numTensors-n,[2,this.state.activeProfile]})})},t.prototype.isTapeOn=function(){return this.state.gradientDepth>0&&0===this.state.kernelDepth},t.prototype.addTapeNode=function(t,e,n,r,o){var a=this,i={id:this.state.nextTapeNodeId++,name:t,inputs:e,outputs:n,saved:o};null!=r&&(i.gradient=function(t){return t=t.map(function(t,e){if(null==t){var r=n[e],o=$(r.size,r.dtype);return a.makeTensor(o,r.shape,r.dtype)}return t}),r(t.length>1?t:t[0],o)}),this.state.activeTape.push(i);},t.prototype.keep=function(t){return t.kept=!0,t},t.prototype.startTape=function(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++;},t.prototype.endTape=function(){this.state.gradientDepth--;},t.prototype.startScope=function(t){var e={track:[],name:"unnamed scope",id:this.state.nextScopeId++};t&&(e.name=t),this.state.scopeStack.push(e),this.state.activeScope=e;},t.prototype.endScope=function(t){for(var e=this,n=kt(t),r=new Set(n.map(function(t){return t.id})),o=0;o<this.state.activeScope.track.length;o++){var a=this.state.activeScope.track[o];a.kept||r.has(a.id)||a.dispose();}var i=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],n.forEach(function(t){t.kept||t.scopeId!==i.id||e.track(t);});},t.prototype.gradients=function(t,e,n,r){var o=this;if(void 0===r&&(r=!1),g(e.length>0,function(){return "gradients() received an empty list of xs."}),null!=n&&"float32"!==n.dtype)throw new Error("dy must have 'float32' dtype, but has '"+n.dtype+"'");var a=this.scopedRun(function(){return o.startTape()},function(){return o.endTape()},function(){return o.tidy("forward",t)});g(a instanceof dt,function(){return "The result y returned by f() must be a tensor."});var i=function(t,e,n){for(var r={},o={},a=0;a<e.length;a++)r[e[a].id]=!0;for(a=0;a<t.length;a++){var i=(d=t[a]).inputs;for(var u in i){for(var s=i[u],c=!1,l=0;l<e.length;l++)if(r[s.id]){d.outputs.forEach(function(t){return r[t.id]=!0}),c=!0,o[d.id]=!0;break}if(c)break}}var h={};h[n.id]=!0;var f={};for(a=t.length-1;a>=0;a--)for(i=(d=t[a]).inputs,l=0;l<d.outputs.length;l++)if(h[d.outputs[l].id]){for(var u in i)h[i[u].id]=!0,f[d.id]=!0;break}var p=[];for(a=0;a<t.length;a++){var d;if(o[(d=t[a]).id]&&f[d.id]){var v={};for(var u in d.inputs){var m=d.inputs[u];r[m.id]&&(v[u]=m);}var g=Object.assign({},d);g.inputs=v,g.outputs=d.outputs,p.push(g);}}return p}(this.state.activeTape,e,a);if(!r&&0===i.length&&e.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",function(){var t,r,u={};u[a.id]=null==n?(t=a.shape,r=X(w(t),"float32"),Nt.makeTensor(r,t,"float32")):n,function(t,e,n){for(var r=function(r){var o=e[r],a=[];if(o.outputs.forEach(function(e){var n=t[e.id];null!=n?a.push(n):a.push(null);}),null==o.gradient)throw new Error("Cannot compute gradient: gradient function not found for "+o.name+".");var i=o.gradient(a),u=function(e){if(!(e in i))throw new Error("Cannot backprop through input "+e+". Available gradients found: "+Object.keys(i)+".");var r=n(function(){return i[e]()});if("float32"!==r.dtype)throw new Error("Error in gradient for op "+o.name+". The gradient of input "+e+" must have 'float32' dtype, but has '"+r.dtype+"'");var a=o.inputs[e];if(!C(r.shape,a.shape))throw new Error("Error in gradient for op "+o.name+". The gradient of input '"+e+"' has shape '"+r.shape+"', which does not match the shape of the input '"+a.shape+"'");if(null==t[a.id])t[a.id]=r;else{var u=t[a.id];t[a.id]=u.add(r),u.dispose();}};for(var s in o.inputs)u(s);},o=e.length-1;o>=0;o--)r(o);}(u,i,function(t){return o.tidy(t)});var s=e.map(function(t){return u[t.id]});return 0===o.state.gradientDepth&&(o.state.activeTape.forEach(function(t){for(var e=0,n=t.saved;e<n.length;e++){n[e].dispose();}}),o.state.activeTape=null),{value:a,grads:s}})},t.prototype.customGrad=function(t){var e=this;return g(G(t),function(){return "The f passed in customGrad(f) must be a function."}),function(){for(var n,r=[],o=0;o<arguments.length;o++)r[o]=arguments[o];g(r.every(function(t){return t instanceof dt}),function(){return "The args passed in customGrad(f)(x1, x2,...) must all be tensors"});var a={};return r.forEach(function(t,e){a[e]=t;}),e.runKernelFunc(function(e,o){return g((n=t.apply(void 0,r.concat([o]))).value instanceof dt,function(){return "The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"}),g(G(n.gradFunc),function(){return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."}),n.value},a,function(t,e){var o=n.gradFunc(t,e),a=Array.isArray(o)?o:[o];g(a.length===r.length,function(){return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."}),g(a.every(function(t){return t instanceof dt}),function(){return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors."});var i={};return a.forEach(function(t,e){i[e]=function(){return t};}),i})}},t.prototype.readSync=function(t){return this.state.tensorInfo.get(t).backend.readSync(t)},t.prototype.read=function(t){return this.state.tensorInfo.get(t).backend.read(t)},t.prototype.time=function(t){return n(this,void 0,void 0,function(){var e,n;return r(this,function(r){switch(r.label){case 0:return e=Y(),[4,this.backend.time(t)];case 1:return (n=r.sent()).wallMs=Y()-e,[2,n]}})})},t.prototype.track=function(t){return null!=this.state.activeScope&&(t.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(t)),t},Object.defineProperty(t.prototype,"registeredVariables",{get:function(){return this.state.registeredVariables},enumerable:!0,configurable:!0}),t.prototype.reset=function(){for(var t in this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new Dt,this.registry)this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null;},t.nextTensorId=0,t.nextVariableId=0,t}();var Nt=function(){var t=function(){if(null==St){var t=void 0;if("undefined"!=typeof window)t=window;else if("undefined"!=typeof global)t=global;else if("undefined"!=typeof process)t=process;else{if("undefined"==typeof self)throw new Error("Could not find a global object");t=self;}St=t;}return St}();if(null==t._tfengine){var e=new o(t);t._tfengine=new Tt(e);}return function(t){i=t;}(t._tfengine.ENV),ht=function(){return t._tfengine},t._tfengine}();function Ft(){return "undefined"!=typeof window&&null!=window.document||"undefined"!=typeof WorkerGlobalScope}var _t=a();_t.registerFlag("DEBUG",function(){return !1},function(t){t&&console.warn("Debugging mode is ON. 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Yo(t,e,n,r){var o=[];t.forEach(function(t){var e=w(t.shapeInfo.logicalShape);t.shapeInfo.isUniform?o.push("uniform float "+t.name+(e>1?"["+e+"]":"")+";"):(o.push("uniform sampler2D "+t.name+";"),o.push("uniform int offset"+t.name+";"));});var a,i,u=o.join("\n"),s=t.map(function(t){return function(t,e,n){void 0===n&&(n=!1);var r="";r+=n?Jo(t):Qo(t);var o=t.shapeInfo.logicalShape,a=e.logicalShape;o.length<=a.length&&(r+=n?function(t,e){var n,r=t.name,o=r.charAt(0).toUpperCase()+r.slice(1),a="get"+o+"AtOutCoords",i=t.shapeInfo.logicalShape.length,u=e.logicalShape.length,s=ho(t.shapeInfo.logicalShape,e.logicalShape),c=aa(u),l=u-i,h=["x","y","z","w","u","v"];n=0===i?"":u<2&&s.length>=1?"coords = 0;":s.map(function(t){return "coords."+h[t+l]+" = 0;"}).join("\n");var f="";f=u<2&&i>0?"coords":t.shapeInfo.logicalShape.map(function(t,e){return "coords."+h[e+l]}).join(", ");var p="return outputValue;",d=1===w(t.shapeInfo.logicalShape),v=1===w(e.logicalShape);if(1!==i||d||v){if(d&&!v)p=1===u?"\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\n      ":"\n        return vec4(outputValue.x);\n      ";else if(s.length){var m=i-2,g=i-1;s.indexOf(m)>-1&&s.indexOf(g)>-1?p="return vec4(outputValue.x);":s.indexOf(m)>-1?p="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":s.indexOf(g)>-1&&(p="return vec4(outputValue.xx, outputValue.zz);");}}else p="\n      return vec4(outputValue.xy, outputValue.xy);\n    ";return "\n    vec4 "+a+"() {\n      "+c+" coords = getOutputCoords();\n      "+n+"\n      vec4 outputValue = get"+o+"("+f+");\n      "+p+"\n    }\n  "}(t,e):function(t,e){var n=t.name,r=n.charAt(0).toUpperCase()+n.slice(1),o="get"+r+"AtOutCoords",a=e.texShape,i=t.shapeInfo.texShape,u=t.shapeInfo.logicalShape.length,s=e.logicalShape.length;if(!t.shapeInfo.isUniform&&u===s&&null==t.shapeInfo.flatOffset&&C(i,a))return "\n      float "+o+"() {\n        return sampleTexture("+n+", resultUV);\n      }\n    ";var c,l=aa(s),h=ho(t.shapeInfo.logicalShape,e.logicalShape),f=s-u,p=["x","y","z","w","u","v"];c=0===u?"":s<2&&h.length>=1?"coords = 0;":h.map(function(t){return "coords."+p[t+f]+" = 0;"}).join("\n");var d="";d=s<2&&u>0?"coords":t.shapeInfo.logicalShape.map(function(t,e){return "coords."+p[e+f]}).join(", ");return "\n    float "+o+"() {\n      "+l+" coords = getOutputCoords();\n      "+c+"\n      return get"+r+"("+d+");\n    }\n  "}(t,e));return r}(t,e,r)}).join("\n"),c=e.texShape,l=Ko(),h=function(t){return "\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return "+t.texture2D+"(textureSampler, uv).r;\n    }\n  "}(l),f=function(t){return t.version+"\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    "+t.varyingFs+" vec2 resultUV;\n    "+t.defineOutput+"\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    uniform float NAN;\n    "+t.defineSpecialNaN+"\n    "+t.defineSpecialInf+"\n    "+t.defineRound+"\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    int idiv(int a, int b, float sign) {\n      int res = a / b;\n      int mod = imod(a, b);\n      if (sign < 0. && mod != 0) {\n        res -= 1;\n      }\n      return res;\n    }\n\n    //Based on the work of Dave Hoskins\n    //https://www.shadertoy.com/view/4djSRW\n    #define HASHSCALE1 443.8975\n    float random(float seed){\n      vec2 p = resultUV * seed;\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n      p3 += dot(p3, p3.yzx + 19.19);\n      return fract((p3.x + p3.y) * p3.z);\n    }\n\n    "+Zo+"\n    "+ta+"\n    "+ea+"\n  "}(l);return e.isPacked?(a=function(t,e){switch(t.length){case 0:return "\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(1===n[0])return "\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * "+n[1]+".0);\n      }\n    ";if(1===n[1])return "\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * "+n[0]+".0);\n      }\n    ";return "\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      return 2 * (resTexRC.x * "+n[1]+" + resTexRC.y);\n    }\n  "}(0,e);case 2:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(C(t,e))return "\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2("+n[0]+", "+n[1]+"));\n      }\n    ";var r=Math.ceil(t[1]/2);return "\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec2(r, c);\n    }\n  "}(t,e);case 3:return n=t,r=e,o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=Math.ceil(n[2]/2),i=a*Math.ceil(n[1]/2),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+o[0]+", "+o[1]+"));\n      int index = resTexRC.x * "+o[1]+" + resTexRC.y;\n\n      int b = index / "+i+";\n      index -= b * "+i+";\n\n      int r = 2 * (index / "+a+");\n      int c = imod(index, "+a+") * 2;\n\n      return ivec3(b, r, c);\n    }\n  ";default:return function(t,e){for(var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],r=Math.ceil(t[t.length-1]/2),o=r*Math.ceil(t[t.length-2]/2),a=o,i="",u="b, r, c",s=2;s<t.length-1;s++)a*=t[t.length-s-1],i="\n      int b"+s+" = index / "+a+";\n      index -= b"+s+" * "+a+";\n    "+i,u="b"+s+", "+u;return "\n    ivec"+t.length+" getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n\n      "+i+"\n\n      int b = index / "+o+";\n      index -= b * "+o+";\n\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec"+t.length+"("+u+");\n    }\n  "}(t,e)}var n,r,o,a,i;}(e.logicalShape,c),i=function(t){return "\n    void setOutput(vec4 val) {\n      "+t.output+" = val;\n    }\n  "}(l)):(a=function(t,e){switch(t.length){case 0:return "\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return function(t,e){if(1===e[0])return "\n      int getOutputCoords() {\n        return int(resultUV.x * "+e[1]+".0);\n      }\n    ";if(1===e[1])return "\n      int getOutputCoords() {\n        return int(resultUV.y * "+e[0]+".0);\n      }\n    ";return "\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+e[0]+", "+e[1]+"));\n      return resTexRC.x * "+e[1]+" + resTexRC.y;\n    }\n  "}(0,e);case 2:return function(t,e){if(C(t,e))return "\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2("+e[0]+", "+e[1]+"));\n      }\n    ";if(1===t[1])return "\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+e[0]+", "+e[1]+"));\n        int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ";if(1===t[0])return "\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+e[0]+", "+e[1]+"));\n        int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ";return "\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+e[0]+", "+e[1]+"));\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n      int r = index / "+t[1]+";\n      int c = index - r * "+t[1]+";\n      return ivec2(r, c);\n    }\n  "}(t,e);case 3:return n=e,r=jo(["r","c","d"],t),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n      "+r+"\n      return ivec3(r, c, d);\n    }\n  ";case 4:return function(t,e){var n=jo(["r","c","d","d2"],t);return "\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+e[0]+", "+e[1]+"));\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n      "+n+"\n      return ivec4(r, c, d, d2);\n    }\n  "}(t,e);case 5:return function(t,e){var n=jo(["r","c","d","d2","d3"],t);return "\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2("+e[0]+",\n                             "+e[1]+"));\n\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n\n      "+n+"\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  "}(t,e);case 6:return function(t,e){var n=jo(["r","c","d","d2","d3","d4"],t);return "\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+e[0]+", "+e[1]+"));\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n\n      "+n+"\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  "}(t,e);default:throw new Error(t.length+"-D output sampling is not yet supported")}var n,r;}(e.logicalShape,c),i=function(t){return "\n    void setOutput(float val) {\n      "+t.output+" = vec4(val, 0, 0, 0);\n    }\n  "}(l)),r&&(f+=na),[f,h,i,u,a,s,n].join("\n")}function Qo(t){var e=t.shapeInfo.logicalShape;switch(e.length){case 0:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return "float "+n+"() {return "+e+";}";var r=t.shapeInfo.texShape,o=r[0],a=r[1];if(1===o&&1===a)return "\n      float "+n+"() {\n        return sampleTexture("+e+", halfCR);\n      }\n    ";var i=t.shapeInfo.texShape,u=i[0],s=i[1],c=ra(e);return "\n    float "+n+"() {\n      vec2 uv = uvFromFlat("+u+", "+s+", "+c+");\n      return sampleTexture("+e+", uv);\n    }\n  "}(t);case 1:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return "\n      float "+n+"(int index) {\n        "+oa(t)+"\n      }\n    ";var r=t.shapeInfo.texShape,o=r[0],a=r[1];if(1===a&&1===o)return "\n      float "+n+"(int index) {\n        return sampleTexture("+e+", halfCR);\n      }\n    ";var i=ra(e);if(1===a)return "\n      float "+n+"(int index) {\n        vec2 uv = vec2(0.5, (float(index + "+i+") + 0.5) / "+o+".0);\n        return sampleTexture("+e+", uv);\n      }\n    ";if(1===o)return "\n      float "+n+"(int index) {\n        vec2 uv = vec2((float(index + "+i+") + 0.5) / "+a+".0, 0.5);\n        return sampleTexture("+e+", uv);\n      }\n    ";return "\n    float "+n+"(int index) {\n      vec2 uv = uvFromFlat("+o+", "+a+", index + "+i+");\n      return sampleTexture("+e+", uv);\n    }\n  "}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape;if(null!=o&&C(e,o)){var a=o[0],i=o[1];return "\n    float "+r+"(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2("+i+".0, "+a+".0);\n      return sampleTexture("+n+", uv);\n    }\n  "}var u=T(e),s=u.newShape,c=u.keptDims,l=s;if(l.length<e.length){var h=ia(t,l);return "\n      "+Qo(h)+"\n      float "+r+"(int row, int col) {\n        return "+r+"("+ua(["row","col"],c)+");\n      }\n    "}if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col) {\n        int index = round(dot(vec2(row, col), vec2("+e[1]+", 1)));\n        "+oa(t)+"\n      }\n    ";var f=o[0],p=o[1],d=ra(n);if(1===p)return "\n    float "+r+"(int row, int col) {\n      float index = dot(vec3(row, col, "+d+"), vec3("+e[1]+", 1, 1));\n      vec2 uv = vec2(0.5, (index + 0.5) / "+f+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ";if(1===f)return "\n    float "+r+"(int row, int col) {\n      float index = dot(vec3(row, col, "+d+"), vec3("+e[1]+", 1, 1));\n      vec2 uv = vec2((index + 0.5) / "+p+".0, 0.5);\n      return sampleTexture("+n+", uv);\n    }\n  ";return "\n  float "+r+"(int row, int col) {\n    // Explicitly use integer operations as dot() only works on floats.\n    int index = row * "+e[1]+" + col + "+d+";\n    vec2 uv = uvFromFlat("+f+", "+p+", index);\n    return sampleTexture("+n+", uv);\n  }\n"}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[1]*e[2],a=e[2],i=T(e),u=i.newShape,s=i.keptDims,c=u;if(c.length<e.length){var l=ia(t,c);return "\n        "+Qo(l)+"\n        float "+r+"(int row, int col, int depth) {\n          return "+r+"("+ua(["row","col","depth"],s)+");\n        }\n      "}if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col, int depth) {\n        int index = round(dot(vec3(row, col, depth),\n                          vec3("+o+", "+a+", 1)));\n        "+oa(t)+"\n      }\n    ";var h=t.shapeInfo.texShape,f=h[0],p=h[1],d=t.shapeInfo.flatOffset;if(p===o&&null==d)return "\n        float "+r+"(int row, int col, int depth) {\n          float texR = float(row);\n          float texC = dot(vec2(col, depth), vec2("+a+", 1));\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2("+p+".0, "+f+".0);\n          return sampleTexture("+n+", uv);\n        }\n      ";if(p===a&&null==d)return "\n    float "+r+"(int row, int col, int depth) {\n      float texR = dot(vec2(row, col), vec2("+e[1]+", 1));\n      float texC = float(depth);\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+p+".0, "+f+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ";var v=ra(n);return "\n      float "+r+"(int row, int col, int depth) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * "+o+" + col * "+a+" + depth + "+v+";\n        vec2 uv = uvFromFlat("+f+", "+p+", index);\n        return sampleTexture("+n+", uv);\n      }\n  "}(t);case 4:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[3],a=e[2]*o,i=e[1]*a,u=T(e),s=u.newShape,c=u.keptDims;if(s.length<e.length){var l=ia(t,s);return "\n      "+Qo(l)+"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        return "+r+"("+ua(["row","col","depth","depth2"],c)+");\n      }\n    "}if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col, int depth, int depth2) {\n        int index = round(dot(vec4(row, col, depth, depth2),\n                          vec4("+i+", "+a+", "+o+", 1)));\n        "+oa(t)+"\n      }\n    ";var h=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,p=f[0],d=f[1];if(d===i&&null==h)return "\n      float "+r+"(int row, int col, int depth, int depth2) {\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3("+a+", "+o+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+d+".0, "+p+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(d===o&&null==h)return "\n      float "+r+"(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3("+e[1]*e[2]+", "+e[2]+", 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+d+".0, "+p+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var v=ra(n);return "\n    float "+r+"(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+i+" + col * "+a+" +\n          depth * "+o+" + depth2;\n      vec2 uv = uvFromFlat("+p+", "+d+", index + "+v+");\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);case 5:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[4],a=e[3]*o,i=e[2]*a,u=e[1]*i,s=T(e),c=s.newShape,l=s.keptDims;if(c.length<e.length){var h=ia(t,c);return "\n      "+Qo(h)+"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        return "+r+"("+ua(["row","col","depth","depth2","depth3"],l)+");\n      }\n    "}if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        float index = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+u+", "+i+", "+a+", "+o+")) +\n          depth3;\n        "+oa(t)+"\n      }\n    ";var f=t.shapeInfo.flatOffset,p=t.shapeInfo.texShape,d=p[0],v=p[1];if(v===u&&null==f)return "\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n                         vec4("+i+", "+a+", "+o+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+v+".0, "+d+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(v===o&&null==f)return "\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        float texR = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+e[1]*e[2]*e[3]+",\n               "+e[2]*e[3]+", "+e[3]+", 1));\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+v+".0, "+d+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var m=ra(n);return "\n    float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+u+" + col * "+i+" + depth * "+a+" +\n          depth2 * "+o+" + depth3 + "+m+";\n      vec2 uv = uvFromFlat("+d+", "+v+", index);\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);case 6:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=T(e),a=o.newShape,i=o.keptDims;if(a.length<e.length){var u=ia(t,a);return "\n      "+Qo(u)+"\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        return "+r+"("+ua(["row","col","depth","depth2","depth3","depth4"],i)+");\n      }\n    "}var s=e[5],c=e[4]*s,l=e[3]*c,h=e[2]*l,f=e[1]*h;if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n        int index = round(dot(\n          vec4(row, col, depth, depth2),\n          vec4("+f+", "+h+", "+l+", "+c+")) +\n          dot(\n            vec2(depth3, depth4),\n            vec2("+s+", 1)));\n        "+oa(t)+"\n      }\n    ";var p=t.shapeInfo.flatOffset,d=t.shapeInfo.texShape,v=d[0],m=d[1];if(m===f&&null==p)return "\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n          vec4("+h+", "+l+", "+c+", "+s+")) +\n               float(depth4);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+m+".0, "+v+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(m===s&&null==p)return "\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        float texR = dot(vec4(row, col, depth, depth2),\n          vec4("+e[1]*e[2]*e[3]*e[4]+",\n               "+e[2]*e[3]*e[4]+",\n               "+e[3]*e[4]+",\n               "+e[4]+")) + float(depth3);\n        int texC = depth4;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+m+".0, "+v+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var g=ra(n);return "\n    float "+r+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+f+" + col * "+h+" + depth * "+l+" +\n          depth2 * "+c+" + depth3 * "+s+" + depth4 + "+g+";\n      vec2 uv = uvFromFlat("+v+", "+m+", index);\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);default:throw new Error(e.length+"-D input sampling is not yet supported")}}function Jo(t){var e,n,r;switch(t.shapeInfo.logicalShape.length){case 0:return e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),r=Ko(),"\n    vec4 "+n+"() {\n      return "+r.texture2D+"("+e+", halfCR);\n    }\n  ";case 1:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),r=t.shapeInfo.texShape,o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=Ko();return "\n    vec4 "+n+"(int index) {\n      vec2 uv = packedUVfrom1D(\n        "+o[0]+", "+o[1]+", index);\n      return "+a.texture2D+"("+e+", uv);\n    }\n  "}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,a=o[0],i=o[1],u=Ko();if(null!=o&&C(e,o))return "\n      vec4 "+r+"(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2("+i+".0, "+a+".0);\n\n        return "+u.texture2D+"("+n+", uv);\n      }\n    ";var s=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],c=Math.ceil(e[1]/2);return "\n    vec4 "+r+"(int row, int col) {\n      vec2 uv = packedUVfrom2D("+c+", "+s[0]+", "+s[1]+", row, col);\n      return "+u.texture2D+"("+n+", uv);\n    }\n  "}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,a=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];if(1===e[0]){var i=e.slice(1),u=ia(t,i);return "\n        "+Jo(u)+"\n        vec4 "+r+"(int b, int row, int col) {\n          return "+r+"("+ua(["b","row","col"],[1,2])+");\n        }\n      "}var s=a[0],c=a[1],l=Math.ceil(e[2]/2),h=l*Math.ceil(e[1]/2),f=Ko();return "\n    vec4 "+r+"(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        "+s+", "+c+", "+h+", "+l+", b, row, col);\n      return "+f.texture2D+"("+n+", uv);\n    }\n  "}(t);default:return function(t){for(var e=t.shapeInfo.logicalShape,n=e.length,r=t.name,o="get"+r.charAt(0).toUpperCase()+r.slice(1),a=t.shapeInfo.texShape,i=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],u=i[0],s=i[1],c=Math.ceil(e[n-1]/2),l=c*Math.ceil(e[n-2]/2),h="int b, int row, int col",f="b * "+l+" + (row / 2) * "+c+" + (col / 2)",p=2;p<n-1;p++)h="int b"+p+", "+h,l*=e[n-p-1],f="b"+p+" * "+l+" + "+f;var d=Ko();return "\n    vec4 "+o+"("+h+") {\n      int index = "+f+";\n      int texR = index / "+s+";\n      int texC = index - texR * "+s+";\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+s+", "+u+");\n      return "+d.texture2D+"("+r+", uv);\n    }\n  "}(t)}}var Zo="\nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",ta="\nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",ea="\nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",na="\n  float getChannel(vec4 frag, vec2 innerDims) {\n    vec2 modCoord = mod(innerDims, 2.);\n    return modCoord.x == 0. ?\n      (modCoord.y == 0. ? frag.r : frag.g) :\n      (modCoord.y == 0. ? frag.b : frag.a);\n  }\n  float getChannel(vec4 frag, int dim) {\n    float modCoord = mod(float(dim), 2.);\n    return modCoord == 0. ? frag.r : frag.g;\n  }\n";function ra(t){return "offset"+t}function oa(t){var e=t.name,n=w(t.shapeInfo.logicalShape);return n<2?"return "+e+";":"\n    for (int i = 0; i < "+n+"; i++) {\n      if (i == index) {\n        return "+e+"[i];\n      }\n    }\n  "}function aa(t){if(t<=1)return "int";if(2===t)return "ivec2";if(3===t)return "ivec3";if(4===t)return "ivec4";if(5===t)return "ivec5";if(6===t)return "ivec6";throw Error("GPU for rank "+t+" is not yet supported")}function ia(t,e){var n=JSON.parse(JSON.stringify(t));return n.shapeInfo.logicalShape=e,n}function ua(t,e){return e.map(function(e){return t[e]}).join(", ")}var sa=function(){return function(t,e,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,g(t.length>2,function(){return "Packed arg"+(n.charAt(0).toUpperCase()+n.slice(1))+" supports only inputs with rank above 2."});var o=t[t.length-1],a=Math.ceil(o/e);this.outputShape=t.slice(0,-1),a>1&&this.outputShape.push(a),r||this.variableNames.push("bestIndicesA");var i,u,s=this.outputShape,c=s.length,l=aa(c),h=qo("coords",c);if(1===a){var f=aa(u=c+1);i="\n        "+f+" sourceLocR = "+f+"("+h.join()+", 0);\n        ++"+h[c-1]+";\n        "+f+" sourceLocG = "+f+"("+h.join()+", 0);\n        ++"+h[c-2]+";\n        "+f+" sourceLocA = "+f+"("+h.join()+", 0);\n        --"+h[c-1]+";\n        "+f+" sourceLocB = "+f+"("+h.join()+", 0);\n        --"+h[c-2]+";";}else u=c,i="\n        "+l+" sourceLocR = coords;\n        ++"+h[c-1]+";\n        "+l+" sourceLocG = coords;\n        ++"+h[c-2]+";\n        "+l+" sourceLocA = coords;\n        --"+h[c-1]+";\n        "+l+" sourceLocB = coords;\n        --"+h[c-2]+";";var p=["x","y","z","w","u","v"].slice(0,u),d="."+p[u-1],v=p.map(function(t){return "int "+t}),m=qo("sourceLocR",u-1).concat("inIdx.r"),y=qo("sourceLocG",u-1).concat("inIdx.g"),x=qo("sourceLocB",u-1).concat("inIdx.b"),b=qo("sourceLocA",u-1).concat("inIdx.a"),w="max"===n?"greaterThan":"lessThan",C=r?"":"\n          inIdx = round(vec4(getBestIndicesAChannel("+m.join()+"),\n                             getBestIndicesAChannel("+y.join()+"),\n                             getBestIndicesAChannel("+x.join()+"),\n                             getBestIndicesAChannel("+b.join()+")));",E="vec4(\n            getAChannel("+m.join()+"),\n            hasNextCol ? getAChannel("+y.join()+") : 0.,\n            hasNextRow ? getAChannel("+x.join()+") : 0.,\n            hasNextRow && hasNextCol ? getAChannel("+b.join()+") : 0.)",R=r?"":"\n      float getBestIndicesAChannel("+v.join()+") {\n        return getChannel(getBestIndicesA("+p.join()+"),\n                                          vec2("+p.slice(-2).join()+"));\n      }";this.userCode="\n      float getAChannel("+v.join()+") {\n        return getChannel(getA("+p.join()+"),\n                               vec2("+p.slice(-2).join()+"));\n      }\n      "+R+"\n      void main() {\n        "+l+" coords = getOutputCoords();\n        bool hasNextCol = "+h[c-1]+" < "+(s[c-1]-1)+";\n        bool hasNextRow = "+h[c-2]+" < "+(s[c-2]-1)+";\n        "+i+"\n        ivec4 srcIdx = ivec4(sourceLocR"+d+", sourceLocG"+d+",\n          sourceLocB"+d+", sourceLocA"+d+") * "+e+";\n        ivec4 inIdx = srcIdx;\n        vec4 bestIndex = vec4(inIdx);\n        vec4 bestValue = "+E+";\n\n        for (int i = 0; i < "+e+"; i++) {\n          inIdx = srcIdx;\n          "+C+"\n          vec4 candidate = "+E+";\n          bvec4 nan = isnan(candidate);\n          bvec4 replace = bvec4(\n            vec4("+w+"(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\n                           replace.y  ? candidate.y : bestValue.y,\n                           replace.z  ? candidate.z : bestValue.z,\n                           replace.w  ? candidate.w : bestValue.w);\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n          srcIdx++;\n        }\n        setOutput(bestIndex);\n      }\n    ";}}(),ca=function(){return function(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=t.dilationHeight,i=t.dilationWidth,u=t.effectiveFilterHeight,s=t.effectiveFilterWidth,c=u-1-t.padInfo.top,l=s-1-t.padInfo.left,h=1/(e*n);this.userCode="\n      const ivec2 pads = ivec2("+c+", "+l+");\n      const float avgMultiplier = float("+h+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+u+";\n            wR += "+a+") {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+s+";\n            wC+= "+i+") {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),la=function(){return function(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,u=t.dilationDepth,s=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,p=l-1-t.padInfo.front,d=h-1-t.padInfo.top,v=f-1-t.padInfo.left,m=1/(e*n*r);this.userCode="\n      const ivec3 pads = ivec3("+p+", "+d+", "+v+");\n      const float avgMultiplier = float("+m+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+l+";\n            wD += "+u+") {\n          float dyD = float(dyDCorner + wD) / "+o+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+h+";\n              wR += "+s+") {\n            float dyR = float(dyRCorner + wR) / "+a+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+f+";\n                wC += "+c+") {\n              float dyC = float(dyCCorner + wC) / "+i+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),ha=function(){return function(t,e,n,r,o,a){this.outputShape=[],this.variableNames=["x","mean","variance"],po(t,e),po(t,n);var i="0.0";null!=r&&(po(t,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");var u="1.0";null!=o&&(po(t,o),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = "+i+";\n        float scale = "+u+";\n        float inv = scale * inversesqrt(variance + float("+a+"));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    ";}}(),fa=function(){return function(t,e,n,r,o,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],po(t,e),po(t,n);var i="vec4(0.0)";null!=r&&(po(t,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");var u="vec4(1.0)";null!=o&&(po(t,o),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        vec4 offset = "+i+";\n        vec4 scale = "+u+";\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4("+a+"));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    ";}}(),pa="return areal * breal - aimag * bimag;",da="return areal * bimag + aimag * breal;",va=function(){return function(t,e,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=po(e,n),this.userCode="\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        "+t+"\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    ";}}(),ma="return a + b;",ga="return a - b;",ya="return a * b;",xa="return (a < 0.) ? b * a : a;",ba=function(){return function(t,e,n){this.variableNames=["A","B"],this.outputShape=po(e,n),this.userCode="\n      float binaryOperation(float a, float b) {\n        "+t+"\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    ";}}(),wa="\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n",Ca=function(){return function(t,e,n,r){void 0===r&&(r=!1),this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=po(e,n);var o=this.outputShape.length,a="";if(r)if(0===o||1===w(this.outputShape))a="\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        ";else if(a="\n          "+aa(o)+" coords = getOutputCoords();\n        ",1===o)a+="\n            result.y = (coords + 1) >= "+this.outputShape[0]+" ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          ";else{var i=qo("coords",o);a+="\n            bool nextRowOutOfBounds =\n              ("+i[o-2]+" + 1) >= "+this.outputShape[o-2]+";\n            bool nextColOutOfBounds =\n              ("+i[o-1]+" + 1) >= "+this.outputShape[o-1]+";\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          ";}this.userCode="\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        "+t+"\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        "+a+"\n\n        setOutput(result);\n      }\n    ";}}(),Ea=function(){function t(t){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,o){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(o,"minVal"),n.maxLoc=r.getUniformLocationNoThrow(o,"maxVal")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e);}},t}(),Ra=function(){function t(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        vec4 value = getAAtOutCoords();\n\n        if (any(isnan(value))) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,o){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(o,"minVal"),n.maxLoc=r.getUniformLocationNoThrow(o,"maxVal")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e);}},t}(),Ia=function(){return function(t){this.variableNames=["real","imag"],this.outputShape=t,this.userCode="\n      void main() {\n        float re = abs(getRealAtOutCoords());\n        float im = abs(getImagAtOutCoords());\n        float mx = max(re, im);\n\n        // sadly the length function in glsl is not underflow-safe\n        // (at least not on Intel GPUs). So the safe solution is\n        // to ensure underflow-safety in all cases.\n        setOutput(\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\n        );\n      }\n    ";}}(),ka=function(){return function(t){this.outputShape=[],this.outputShape=bn(t,1),this.variableNames=t.map(function(t,e){return "T"+e});var e=new Array(t.length-1);e[0]=t[0][1];for(var n=1;n<e.length;n++)e[n]=e[n-1]+t[n][1];var r=["if (yC < "+e[0]+") setOutput(getT0(yR, yC));"];for(n=1;n<e.length;n++){var o=e[n-1];r.push("else if (yC < "+e[n]+") setOutput(getT"+n+"(yR, yC-"+o+"));");}var a=e.length,i=e[e.length-1];r.push("else setOutput(getT"+a+"(yR, yC-"+i+"));"),this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        "+r.join("\n        ")+"\n      }\n    ";}}(),Sa=function(){return function(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=bn(t,e);var n=this.outputShape,r=n.length,o=aa(r),a=qo("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=t.map(function(t,e){return "T"+e});var u=new Array(t.length-1);u[0]=t[0][e];for(var s=1;s<u.length;s++)u[s]=u[s-1]+t[s][e];var c=i[e],l=i.slice(-2),h=i.join(),f="if ("+c+" < "+u[0]+") {\n        return getChannel(\n            getT0("+h+"), vec2("+l.join()+"));\n        }";for(s=1;s<u.length;s++){var p=u[s-1];f+="\n        if ("+c+" < "+u[s]+"  && "+c+" >= "+u[s-1]+") {\n          return getChannel(\n            getT"+s+"("+Aa(i,c,p)+"),\n            vec2("+Aa(l,c,p)+"));\n        }";}var d=u.length,v=u[u.length-1];f+="\n        return getChannel(\n          getT"+d+"("+Aa(i,c,v)+"),\n          vec2("+Aa(l,c,v)+"));",this.userCode="\n      float getValue("+i.map(function(t){return "int "+t})+") {\n        "+f+"\n      }\n\n      void main() {\n        "+o+" coords = getOutputCoords();\n        vec4 result = vec4(getValue("+a+"), 0., 0., 0.);\n\n        "+a[r-1]+" = "+a[r-1]+" + 1;\n        if ("+a[r-1]+" < "+n[r-1]+") {\n          result.g = getValue("+a+");\n        }\n\n        "+a[r-2]+" = "+a[r-2]+" + 1;\n        if ("+a[r-2]+" < "+n[r-2]+") {\n          result.a = getValue("+a+");\n        }\n\n        "+a[r-1]+" = "+a[r-1]+" - 1;\n        if ("+a[r-2]+" < "+n[r-2]+" &&\n            "+a[r-1]+" < "+n[r-1]+") {\n          result.b = getValue("+a+");\n        }\n        setOutput(result);\n      }\n    ";}}();function Aa(t,e,n){var r=t.indexOf(e);return t.map(function(t,e){return e===r?t+" - "+n:t}).join()}var Da=function(){return function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,a="channelsLast"===t.dataFormat;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+o+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              if ("+a+") {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),Ta=function(){return function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a="channelsLast"===t.dataFormat,i=e-1-t.padInfo.top,u=n-1-t.padInfo.left,s=a?1:2,c=a?2:3,l=a?3:1;this.userCode="\n      const ivec2 pads = ivec2("+i+", "+u+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords["+l+"];\n\n        ivec2 dyCorner = ivec2(coords["+s+"], coords["+c+"]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n\n              if ("+a+") {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),Na=function(){return function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.padInfo.front,a=t.padInfo.top,i=t.padInfo.left;this.userCode="\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yF = 0; yF < "+t.outDepth+"; yF++) {\n            int xF = wF + yF * "+e+" - "+o+";\n\n            if (xF < 0 || xF >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n              int xR = wR + yR * "+n+" - "+a+";\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n                int xC = wC + yC * "+r+" - "+i+";\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),Fa=function(){return function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,u=e-1-t.padInfo.front,s=n-1-t.padInfo.top,c=r-1-t.padInfo.left;this.userCode="\n      const ivec3 pads = ivec3("+u+", "+s+", "+c+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+e+"; wF++) {\n          float dyF = float(dyFCorner + wF) / "+o+".0;\n\n          if (dyF < 0.0 || dyF >= "+t.outDepth+".0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = "+e+" - 1 - wF;\n\n          for (int wR = 0; wR < "+n+"; wR++) {\n            float dyR = float(dyRCorner + wR) / "+a+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = "+n+" - 1 - wR;\n\n            for (int wC = 0; wC < "+r+"; wC++) {\n              float dyC = float(dyCCorner + wC) / "+i+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = "+r+" - 1 - wC;\n\n              for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),_a=function(){return function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,a=t.outChannels/t.inChannels;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * "+a+" + dm;\n\n        float dotProd = 0.0;\n\n        // TO DO: Vec4 over the batch size\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+o+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),Oa=function(){return function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=e-1-t.padInfo.top,i=n-1-t.padInfo.left,u=t.outChannels/t.inChannels;this.userCode="\n      const ivec2 pads = ivec2("+a+", "+i+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < "+u+"; dm++) {\n              int d2 = d1 * "+u+" + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),Ma=function(){return function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.outputShape=t.outShape;var o=t.padInfo.top,a=t.padInfo.left,i=t.strideHeight,u=t.strideWidth,s=t.dilationHeight,c=t.dilationWidth,l=t.filterHeight,h=t.filterWidth,f=4*Math.floor(t.inChannels/4),p=t.inChannels%4,d="channelsLast"===t.dataFormat,v=d?1:2,m=d?2:3,g=d?3:1,y="",x="";n&&(y=r?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"\n          float activation(float x) {\n            "+n+"\n          }\n        ",x="result = activation(result);");var b=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+y+"\n\n      const ivec2 strides = ivec2("+i+", "+u+");\n      const ivec2 pads = ivec2("+o+", "+a+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords["+g+"];\n\n        ivec2 xRCCorner =\n            ivec2(coords["+v+"], coords["+m+"]) * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+l+"; wR++) {\n          int xR = xRCorner + wR * "+s+";\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+h+"; wC++) {\n            int xC = xCCorner + wC * "+c+";\n\n            if (xC < 0 || xC >= "+t.inWidth+") {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < "+f+"; d1 += 4) {\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              if ("+d+") {\n                vec4 xValues = vec4(\n                  getX(batch, xR, xC, d1),\n                  getX(batch, xR, xC, d1 + 1),\n                  getX(batch, xR, xC, d1 + 2),\n                  getX(batch, xR, xC, d1 + 3)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec4 xValues = vec4(\n                  getX(batch, d1, xR, xC),\n                  getX(batch, d1 + 1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if ("+(1===p)+") {\n\n              if ("+d+") {\n                dotProd +=\n                    getX(batch, xR, xC, "+f+") *\n                    getW(wR, wC, "+f+", d2);\n              } else {\n                dotProd +=\n                    getX(batch, "+f+", xR, xC) *\n                    getW(wR, wC, "+f+", d2);\n              }\n\n            } else if ("+(2===p)+") {\n              vec2 wValues = vec2(\n                getW(wR, wC, "+f+", d2),\n                getW(wR, wC, "+f+" + 1, d2)\n              );\n\n              if ("+d+") {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, "+f+"),\n                  getX(batch, xR, xC, "+f+" + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, "+f+", xR, xC),\n                  getX(batch, "+f+" + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if ("+(3===p)+") {\n              vec3 wValues = vec3(\n                getW(wR, wC, "+f+", d2),\n                getW(wR, wC, "+f+" + 1, d2),\n                getW(wR, wC, "+f+" + 2, d2)\n              );\n\n              if ("+d+") {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, "+f+"),\n                  getX(batch, xR, xC, "+f+" + 1),\n                  getX(batch, xR, xC, "+f+" + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, "+f+", xR, xC),\n                  getX(batch, "+f+" + 1, xR, xC),\n                  getX(batch, "+f+" + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        "+b+"\n        "+x+"\n        setOutput(result);\n      }\n    ";}}(),Ba=function(){return function(t){this.variableNames=["x","W"],this.outputShape=t.outShape;var e=t.padInfo.front,n=t.padInfo.top,r=t.padInfo.left,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,u=t.dilationDepth,s=t.dilationHeight,c=t.dilationWidth,l=t.filterDepth,h=t.filterHeight,f=t.filterWidth,p=4*Math.floor(t.inChannels/4),d=t.inChannels%4;this.userCode="\n      const ivec3 strides = ivec3("+o+", "+a+", "+i+");\n      const ivec3 pads = ivec3("+e+", "+n+", "+r+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+l+"; wF++) {\n          int xF = xFCorner + wF * "+u+";\n\n          if (xF < 0 || xF >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+h+"; wR++) {\n            int xR = xRCorner + wR * "+s+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+f+"; wC++) {\n              int xC = xCCorner + wC * "+c+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < "+p+"; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if ("+(1===d)+") {\n                dotProd +=\n                  getX(batch, xF, xR, xC, "+p+") *\n                  getW(wF, wR, wC, "+p+", d2);\n              } else if ("+(2===d)+") {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, "+p+"),\n                  getX(batch, xF, xR, xC, "+p+" + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, "+p+", d2),\n                  getW(wF, wR, wC, "+p+" + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if ("+(3===d)+") {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, "+p+"),\n                  getX(batch, xF, xR, xC, "+p+" + 1),\n                  getX(batch, xF, xR, xC, "+p+" + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, "+p+", d2),\n                  getW(wF, wR, wC, "+p+" + 1, d2),\n                  getW(wF, wR, wC, "+p+" + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),Pa=function(){return function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.outputShape=t.outShape;var o=t.inHeight,a=t.inWidth,i=t.padInfo.top,u=t.padInfo.left,s=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,p=t.filterWidth,d=t.outChannels/t.inChannels,v="",m="";n&&(v=r?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"\n          float activation(float x) {\n            "+n+"\n          }\n        ",m="result = activation(result);");var g=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+v+"\n\n      const ivec2 strides = ivec2("+s+", "+c+");\n      const ivec2 pads = ivec2("+i+", "+u+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / "+d+";\n        int q = d2 - d1 * "+d+";\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < "+f+"; wR++) {\n          int xR = xRCorner + wR * "+l+";\n\n          if (xR < 0 || xR >= "+o+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+p+"; wC++) {\n            int xC = xCCorner + wC * "+h+";\n\n            if (xC < 0 || xC >= "+a+") {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n\n        float result = dotProd;\n        "+g+"\n        "+m+"\n        setOutput(result);\n      }\n    ";}}(),La=function(){return function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.outShape;for(var o=t.inHeight,a=t.inWidth,i=t.padInfo.top,u=t.padInfo.left,s=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,p=t.filterWidth,d=p,m="int xR; int xC; int xCOffset;",g=0;g<f;g++)for(var y=0;y<p;y++)m+="\n          vec4 xTexelR"+g+"C"+2*y+" = vec4(0.);\n          vec4 wR"+g+"C"+y+" = vec4(0.);\n          vec4 xR"+g+"C"+y+" = vec4(0.);";for(g=0;g<f;g++)for(var x=0;x<d;x++){if(m+="\n          xR = xRCorner + "+g*l+";\n          xC = xCCorner + "+(y=2*x)*h+";\n        ",1===c){if(y<p&&(m+=u%2==1?"\n                xCOffset = xC + 1;\n                if(xR >= 0 && xR < "+o+" && xCOffset >= 0 && xCOffset < "+a+") {\n                  xTexelR"+g+"C"+y+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+g+"C"+y+" = vec4(0.);\n                }\n\n                xCOffset = xC + 1 - 2;\n                if(xR >= 0 && xR < "+o+" && xCOffset >= 0 && xCOffset < "+a+") {\n                  vec4 previous = getX(batch, xR, xCOffset, d1);\n                  xR"+g+"C"+y+" = vec4(previous.zw, xTexelR"+g+"C"+y+".xy);\n                } else {\n                  xR"+g+"C"+y+" = vec4(0, 0, xTexelR"+g+"C"+y+".xy);\n                }\n              ":"\n                if(xR >= 0 && xR < "+o+" && xC >= 0 && xC < "+a+") {\n                  xTexelR"+g+"C"+y+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+g+"C"+y+" = vec4(0.);\n                }\n\n                xR"+g+"C"+y+" = xTexelR"+g+"C"+y+";\n              ",y+1<p)){var b=u%2==0?v(h):h;h%2==0&&u%2==1||h%2!=0&&u%2!=1?(m+="\n                  xCOffset = xC + "+u%2+" + "+b+";\n\n                  if(xR >= 0 && xR < "+o+" &&\n                    xCOffset >= 0 && xCOffset < "+a+") {\n                    xTexelR"+g+"C"+(y+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n                ",h>1&&(m+="\n                    xCOffset -= 2;\n                    if(xR >= 0 && xR < "+o+" &&\n                      xCOffset >= 0 && xCOffset < "+a+") {\n                      xTexelR"+g+"C"+y+" = getX(batch, xR, xCOffset, d1);\n                    } else {\n                      xTexelR"+g+"C"+y+" = vec4(0.);\n                    }\n                  "),m+="\n                  xR"+g+"C"+(y+1)+" = vec4(\n                    xTexelR"+g+"C"+y+".zw, xTexelR"+g+"C"+(y+2)+".xy);\n                "):m+="\n                  xCOffset = xC + "+b+";\n\n                  if(xR >= 0 && xR < "+o+" &&\n                    xCOffset >= 0 && xCOffset < "+a+") {\n                    xTexelR"+g+"C"+(y+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n\n                  xR"+g+"C"+(y+1)+" = xTexelR"+g+"C"+(y+2)+";\n                ";}}else y<p&&(m+="\n              if(xR >= 0 && xR < "+o+") {\n            ",u%2==1?(m+="\n                xCOffset = xC + 1 - "+c+";\n                if(xCOffset >= 0 && xCOffset < "+a+") {\n                  xTexelR"+g+"C"+y+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+g+"C"+y+" = vec4(0.);\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < "+a+") {\n                  xTexelR"+g+"C"+(y+2)+" = getX(batch, xR, xC + 1, d1);\n                } else {\n                  xTexelR"+g+"C"+(y+2)+" = vec4(0.);\n                }\n\n                xR"+g+"C"+y+" = vec4(\n                  xTexelR"+g+"C"+y+".zw, xTexelR"+g+"C"+(y+2)+".zw);\n              ",y+1<p&&(m+="\n                  vec4 final = vec4(0.);\n                  xCOffset = xC + 1 + "+c+";\n                  if(xCOffset >= 0 && xCOffset < "+a+") {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xR"+g+"C"+(y+1)+" = vec4(xTexelR"+g+"C"+(y+2)+".xy, final.xy);\n                ")):(m+="\n                if(xC >= 0 && xC < "+a+") {\n                  xTexelR"+g+"C"+y+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+g+"C"+y+" = vec4(0.);\n                }\n\n                xCOffset = xC + "+c+";\n                if(xCOffset >= 0 && xCOffset < "+a+") {\n                  xTexelR"+g+"C"+(y+2)+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+g+"C"+(y+2)+" = vec4(0.);\n                }\n\n                xR"+g+"C"+y+" = vec4(\n                  xTexelR"+g+"C"+y+".xy, xTexelR"+g+"C"+(y+2)+".xy);\n              ",y+1<p&&(m+="\n                  xR"+g+"C"+(y+1)+" = vec4(\n                    xTexelR"+g+"C"+y+".zw, xTexelR"+g+"C"+(y+2)+".zw);\n                ")),m+="}");y<p&&(m+="\n            vec4 wTexelR"+g+"C"+y+" = getW("+g+", "+y+", d1, q);\n            wR"+g+"C"+y+" = vec4(wTexelR"+g+"C"+y+".xz, wTexelR"+g+"C"+y+".xz);\n          ",y+1<p&&(m+="\n              vec4 wTexelR"+g+"C"+(y+1)+" = getW("+g+", "+(y+1)+", d1, q);\n              wR"+g+"C"+(y+1)+" =\n                vec4(wTexelR"+g+"C"+(y+1)+".xz, wTexelR"+g+"C"+(y+1)+".xz);"));}for(g=0;g<f;g++)for(y=0;y<p;y++)m+="dotProd += xR"+g+"C"+y+" * wR"+g+"C"+y+";";var w="",C="";n&&(w=r?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"vec4 activation(vec4 x) {\n          "+n+"\n        }",C="result = activation(result);");var E=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+w+"\n\n      const ivec2 strides = ivec2("+s+", "+c+");\n      const ivec2 pads = ivec2("+i+", "+u+");\n\n      void main() {\n\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2;\n        int q = 0;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        vec4 dotProd = vec4(0.);\n\n        "+m+"\n\n        vec4 result = dotProd;\n        "+E+"\n        "+C+"\n        setOutput(result);\n      }\n    ";}}(),Wa=function(){return function(t,e,n,r,o){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];var a=t[0],i=t[1],u=t[2],s=t[3],c=e[0],l=n[0],h=n[1];this.outputShape=[c,l,h,s];var f="bilinear"===r?1:0,p=[i-1+".0",u-1+".0"],d=p[0],v=p[1],m=l>1?[""+(i-1)/(l-1),"(y2-y1) * height_ratio","y1*"+d+" + float(y)*(height_scale)"]:["0.0","0.0","0.5 * (y1+y2) * "+d],g=m[0],y=m[1],x=m[2],b=h>1?[""+(u-1)/(h-1),"(x2-x1) * width_ratio","x1*"+v+" + float(x)*(width_scale)"]:["0.0","0.0","0.5 * (x1+x2) * "+v],w=b[0],C=b[1],E=b[2];this.userCode="\n      const float height_ratio = float("+g+");\n      const float width_ratio = float("+w+");\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n        float x2 = getBoxes(b,3);\n\n        // get image in batch index\n        int bInd = round(getBoxInd(b));\n        if(bInd < 0 || bInd >= "+a+") {\n          return;\n        }\n\n        float height_scale = "+y+";\n        float width_scale = "+C+";\n\n        float in_y = "+x+";\n        if( in_y < 0.0 || in_y > "+d+" ) {\n          setOutput(float("+o+"));\n          return;\n        }\n        float in_x = "+E+";\n        if( in_x < 0.0 || in_x > "+v+" ) {\n          setOutput(float("+o+"));\n          return;\n        }\n\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\n        if("+f+" == 1) {\n          // Compute the four integer indices.\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    ";}}(),Ua=function(){return function(t,e,n){this.variableNames=["x"],this.outputShape=t;var r=t.length,o=t[t.length-1],a=n?"<":">";this.userCode="\n      int getIndex(int i) {\n        "+(n?"return "+o+" -i - 1;":"return i;")+"\n      }\n\n      void main() {\n        "+aa(r)+" coords = getOutputCoords();\n        int end = "+Va(r,"coords")+";\n        float val = 0.0;\n        for (int i = "+o+" - 1; i >= 0; i -= 1) {\n          int idx = getIndex(i);\n          if (idx "+a+" end) {\n            continue;\n          }\n          if (idx == end && "+e+") {\n            continue;\n          }\n          "+Va(r,"coords")+" = idx;\n          val += getX("+function(t,e){if(1===t)return ""+e;if(2===t)return e+".x, "+e+".y";if(3===t)return e+".x, "+e+".y, "+e+".z";if(4===t)return e+".x, "+e+".y, "+e+".z, "+e+".w";throw Error("Cumulative sum for rank "+t+" is not yet supported")}(r,"coords")+");\n        }\n        setOutput(val);\n      }\n    ";}}();function Va(t,e){if(1===t)return ""+e;if(2===t)return e+".y";if(3===t)return e+".z";if(4===t)return e+".w";throw Error("Cumulative sum for rank "+t+" is not yet supported")}var za=function(){return function(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Ot.DENSE;var e=zt(t),n=Ko();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+jo(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getA(rc.x, rc.y, rc.z);\n        }\n\n        "+n.output+" = result;\n      }\n    ";}}(),Ga=function(){return function(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Ot.DENSE;var e=zt(t),n=Ko();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+jo(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\n        }\n\n        "+n.output+" = result;\n      }\n    ";}}(),Ha=function(){function t(t,e,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=t,this.blockSize=e,this.dataFormat=n,this.userCode="\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = "+this.getHeightCoordString()+";\n      int w = "+this.getWidthCoordString()+";\n      int d = "+this.getDepthCoordString()+";\n\n      int in_h = h / "+e+";\n      int offset_h = imod(h, "+e+");\n      int in_w = w / "+e+";\n      int offset_w = imod(w, "+e+");\n      int offset_d = (offset_h * "+e+" + offset_w) *\n        "+this.getOutputDepthSize()+";\n      int in_d = d + offset_d;\n\n      float result = "+this.getInputSamplingString()+";\n      setOutput(result);\n    }\n  ";}return t.prototype.getHeightCoordString=function(){return "NHWC"===this.dataFormat?"coords[1]":"coords[2]"},t.prototype.getWidthCoordString=function(){return "NHWC"===this.dataFormat?"coords[2]":"coords[3]"},t.prototype.getDepthCoordString=function(){return "NHWC"===this.dataFormat?"coords[3]":"coords[1]"},t.prototype.getOutputDepthSize=function(){return "NHWC"===this.dataFormat?this.outputShape[3]:this.outputShape[1]},t.prototype.getInputSamplingString=function(){return "NHWC"===this.dataFormat?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"},t}(),qa=function(){return function(t){this.variableNames=["X"],this.outputShape=[t,t],this.userCode="\n      void main() {\n          ivec2 coords = getOutputCoords();\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\n          setOutput(val);\n      }\n    ";}}(),Ka=function(){return function(t){this.variableNames=["A"],this.outTexUsage=Mt.DOWNLOAD;var e=Ko();this.outputShape=t,this.userCode="\n      "+$o+"\n\n      void main() {\n        float x = getAAtOutCoords();\n        "+e.output+" = encode_float(x);\n      }\n    ";}}(),ja=function(){return function(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Mt.DOWNLOAD;var e=Ko();this.outputShape=t,this.userCode="\n      "+$o+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n        "+e.output+" = encode_float(x);\n      }\n    ";}}(),Xa=function(){return function(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"];var r=Ko(),o=e[0],a=e[1];this.outputShape=t;var i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode="\n      "+Xo(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        int flatIndex = getFlatIndex(coords);\n        int offset = imod(flatIndex, 4);\n\n        flatIndex = idiv(flatIndex, 4, 1.);\n        \n        int r = flatIndex / "+a+";\n        int c = imod(flatIndex, "+a+");\n        vec2 uv = (vec2(c, r) + halfCR) / vec2("+a+".0, "+o+".0);\n        vec4 values = "+r.texture2D+"(A, uv);\n\n        float result;\n\n        if(offset == 0) {\n          result = values[0];\n        } else if(offset == 1) {\n          result = values[1];\n        } else if(offset == 2) {\n          result = values[2];\n        } else {\n          result = values[3];\n        }\n\n        "+r.output+" = vec4("+i+", 0., 0., 0.);\n      }\n    ";}}(),$a=function(){return function(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var r=Ko(),o=e[0],a=e[1];this.outputShape=t;var i="",u="result";n&&(u="floor(result * 255. + 0.5)");for(var s=0;s<=1;s++)for(var c=0;c<=1;c++){var l=2*s+c;i+="\n          localCoords = coords;\n          if(localCoords[2] + "+c+" < "+t[2]+") {\n            localCoords[2] += "+c+";\n            if(localCoords[1] + "+s+" < "+t[1]+") {\n              localCoords[1] += "+s+";\n\n              flatIndex = getFlatIndex(localCoords);\n              offset = imod(flatIndex, 4);\n\n              flatIndex = idiv(flatIndex, 4, 1.);\n\n              r = flatIndex / "+a+";\n              c = imod(flatIndex, "+a+");\n              uv = (vec2(c, r) + halfCR) / vec2("+a+".0, "+o+".0);\n              values = "+r.texture2D+"(A, uv);\n\n              if(offset == 0) {\n                result["+l+"] = values[0];\n              } else if(offset == 1) {\n                result["+l+"] = values[1];\n              } else if(offset == 2) {\n                result["+l+"] = values[2];\n              } else {\n                result["+l+"] = values[3];\n              }\n            }\n          }\n        ";}this.userCode="\n      "+Xo(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        vec4 result = vec4(0.);\n        int flatIndex, r, c, offset;\n        ivec3 localCoords;\n        vec2 uv;\n        vec4 values;\n\n        "+i+"\n\n        "+r.output+" = "+u+";\n      }\n    ";}}(),Ya="return real * expR - imag * expI;",Qa="return real * expI + imag * expR;",Ja=function(){return function(t,e,n){this.variableNames=["real","imag"];var r=e[1];this.outputShape=e;var o=n?"2.0 * "+Math.PI:"-2.0 * "+Math.PI,a=n?r+".0":"1.0";this.userCode="\n      const float exponentMultiplier = "+o+";\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        "+t+"\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float("+r+");\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < "+r+"; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / "+a+";\n        }\n\n        return result;\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        setOutput(mulMatDFT(coords[0], coords[1]));\n      }\n    ";}}(),Za=function(){function t(t,e){this.outputShape=[],this.variableNames=["x"],this.outputShape=t,this.userCode="\n      uniform float value;\n      void main() {\n        // Input can be obtained from uniform value.\n        setOutput(value);\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.valueLoc&&(e.valueLoc=n.getUniformLocationNoThrow(r,"value")),n.gl.uniform1f(e.valueLoc,t);}},t}(),ti=function(){return function(t,e,n){this.variableNames=["A","indices"];var r=t.slice();r[n]=e,this.outputShape=r,this.rank=r.length;var o=aa(this.rank),a=function(t,e){var n=t.length;if(n>4)throw Error("Gather for rank "+n+" is not yet supported");if(1===n)return "int(getIndices(resRC))";for(var r=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],a=0;a<t.length;a++)a===e?o.push("int(getIndices("+r[a]+"))"):o.push(""+r[a]);return o.join()}(t,n);this.userCode="\n      void main() {\n        "+o+" resRC = getOutputCoords();\n        setOutput(getA("+a+"));\n      }\n    ";}}();var ei=function(){return function(t,e,n){this.sliceDim=t,this.strides=e,this.variableNames=["x","indices"],this.outputShape=n;var r=aa(e.length),o=aa(n.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode="\n        "+r+" strides = "+r+"("+this.strides+");\n         void main() {\n          "+o+" coords = getOutputCoords();\n          int flattenIndex = 0;\n          for (int j = 0; j < "+this.sliceDim+"; j++) {\n            int index = round(getIndices(coords[0], j));\n            flattenIndex += index * "+a+";\n          }\n          setOutput(getX(flattenIndex, coords[1]));\n        }\n      ";}}();function ni(t,e){var n=Ko();return Qt(t,e,n.version+"\n    precision highp float;\n    "+n.attribute+" vec3 clipSpacePos;\n    "+n.attribute+" vec2 uv;\n    "+n.varyingVs+" vec2 resultUV;\n\n    void main() {\n      gl_Position = vec4(clipSpacePos, 1);\n      resultUV = uv;\n    }")}function ri(t,e){return ae(t,e,new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]))}function oi(t,e){return ie(t,e,new Uint16Array([0,1,2,2,1,3]))}function ai(t,e,n,r,o,a,i){se(n,r);var u=ue(t,e),s=t.TEXTURE_2D;return qt(t,e,function(){return t.bindTexture(s,u)}),qt(t,e,function(){return t.texParameteri(s,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE)}),qt(t,e,function(){return t.texParameteri(s,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE)}),qt(t,e,function(){return t.texParameteri(s,t.TEXTURE_MIN_FILTER,t.NEAREST)}),qt(t,e,function(){return t.texParameteri(s,t.TEXTURE_MAG_FILTER,t.NEAREST)}),qt(t,e,function(){return t.texImage2D(s,0,o,n,r,0,a,i,null)}),qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)}),u}function ii(t,e,n,r,o){var a=Vt(n,r);return ai(t,e,a[0],a[1],o.internalFormatFloat,o.textureFormatFloat,t.FLOAT)}function ui(t,e,n,r,o){var a=Vt(n,r);return ai(t,e,a[0],a[1],o.internalFormatHalfFloat,o.textureFormatFloat,o.textureTypeHalfFloat)}function si(t,e,n,r,o){var a=Vt(n,r);return ai(t,e,a[0],a[1],t.RGBA,t.RGBA,t.UNSIGNED_BYTE)}function ci(t,e,n,r,o){var a=Gt(n,r);return ai(t,e,a[0],a[1],o.internalFormatPackedFloat,t.RGBA,t.FLOAT)}function li(t,e,n,r,o){var a=Gt(n,r);return ai(t,e,a[0],a[1],o.internalFormatPackedHalfFloat,t.RGBA,o.textureTypeHalfFloat)}function hi(t,e,n,r){return qt(t,e,function(){return t.bindBuffer(t.ARRAY_BUFFER,r)}),le(t,e,n,"clipSpacePos",r,3,20,0)&&le(t,e,n,"uv",r,2,20,12)}function fi(t,e,n,r,o,a,i){var u,s,c;qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),a instanceof Uint8Array?(u=new Uint8Array(r*o*4),s=t.UNSIGNED_BYTE,c=t.RGBA):(u=new Float32Array(r*o*4),s=t.FLOAT,c=i.internalFormatPackedFloat),u.set(a),qt(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,c,r,o,0,t.RGBA,s,u)}),qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)});}function pi(t,e,n,r){qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),r.data instanceof Uint8Array?qt(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,r.width,r.height,0,t.RGBA,t.UNSIGNED_BYTE,r.data)}):qt(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,r)}),qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)});}function di(t,e,n,r,o){var a=t.createBuffer();qt(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,a)});var i=16*n*r;return qt(t,e,function(){return t.bufferData(t.PIXEL_PACK_BUFFER,i,t.STREAM_READ)}),qt(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,0)}),qt(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,null)}),a}function vi(t,e,n){var r=t,o=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,e),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,o),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),o}function mi(t,e,n,r,o){var a=Vt(n,r),i=a[0],u=a[1],s=new Uint8Array(n*r*4);return qt(t,e,function(){return t.readPixels(0,0,i,u,o.downloadTextureFormat,t.UNSIGNED_BYTE,s)}),new Float32Array(s.buffer)}function gi(t,e,n,r,o,a,i,u){var s=t,c=new Float32Array(function(t,e){var n=Gt(t,e);return n[0]*n[1]*4}(a,i));return s.bindBuffer(s.PIXEL_PACK_BUFFER,e),s.getBufferSubData(s.PIXEL_PACK_BUFFER,0,c),s.bindBuffer(s.PIXEL_PACK_BUFFER,null),c}function yi(t,e,n,r){var o=new Float32Array(n*r*4);return qt(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,o)}),o}var xi=Object.freeze({createVertexShader:ni,createVertexBuffer:ri,createIndexBuffer:oi,createFloat32MatrixTexture:ii,createFloat16MatrixTexture:ui,createUnsignedBytesMatrixTexture:si,createPackedMatrixTexture:ci,createFloat16PackedMatrixTexture:li,bindVertexProgramAttributeStreams:hi,uploadDenseMatrixToTexture:fi,uploadPixelDataToTexture:pi,createBufferFromOutputTexture:di,downloadFloat32MatrixFromBuffer:vi,downloadByteEncodedFloatMatrixFromOutputTexture:mi,downloadPackedMatrixFromBuffer:gi,downloadMatrixFromPackedOutputTexture:yi}),bi=function(){function t(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];var e=a().getNumber("WEBGL_VERSION");null!=t?(this.gl=t,Wt(e,t)):this.gl=Ut(e);var n="WEBGL_color_buffer_float";if(1===a().getNumber("WEBGL_VERSION")){if(this.textureFloatExtension=Yt(this.gl,this.debug,"OES_texture_float"),Te(this.gl,"OES_texture_half_float"))this.textureHalfFloatExtension=Yt(this.gl,this.debug,"OES_texture_half_float");else if(a().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Te(this.gl,"EXT_color_buffer_half_float"))this.colorBufferHalfFloatExtension=Yt(this.gl,this.debug,"EXT_color_buffer_half_float");else if(a().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Te(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else{if(!Te(this.gl,"EXT_color_buffer_half_float"))throw new Error("GL context does not support color renderable floats");this.colorBufferHalfFloatExtension=this.gl.getExtension("EXT_color_buffer_half_float");}this.vertexBuffer=ri(this.gl,this.debug),this.indexBuffer=oi(this.gl,this.debug),this.framebuffer=ce(this.gl,this.debug),this.textureConfig=Ht(this.gl,this.textureHalfFloatExtension);}return Object.defineProperty(t.prototype,"debug",{get:function(){return a().getBool("DEBUG")},enumerable:!0,configurable:!0}),t.prototype.dispose=function(){var t=this;if(!this.disposed){null!=this.program&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),null!=this.outputTexture&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");var e=this.gl;qt(e,this.debug,function(){return e.finish()}),qt(e,this.debug,function(){return e.bindFramebuffer(e.FRAMEBUFFER,null)}),qt(e,this.debug,function(){return e.deleteFramebuffer(t.framebuffer)}),qt(e,this.debug,function(){return e.bindBuffer(e.ARRAY_BUFFER,null)}),qt(e,this.debug,function(){return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)}),qt(e,this.debug,function(){return e.deleteBuffer(t.indexBuffer)}),this.disposed=!0;}},t.prototype.createFloat32MatrixTexture=function(t,e){return this.throwIfDisposed(),ii(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createFloat16MatrixTexture=function(t,e){return this.throwIfDisposed(),ui(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createUnsignedBytesMatrixTexture=function(t,e){return this.throwIfDisposed(),si(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.uploadPixelDataToTexture=function(t,e){this.throwIfDisposed(),pi(this.gl,this.debug,t,e);},t.prototype.uploadDenseMatrixToTexture=function(t,e,n,r){this.throwIfDisposed(),fi(this.gl,this.debug,t,e,n,r,this.textureConfig);},t.prototype.createFloat16PackedMatrixTexture=function(t,e){return this.throwIfDisposed(),li(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createPackedMatrixTexture=function(t,e){return this.throwIfDisposed(),ci(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.deleteMatrixTexture=function(t){var e=this;this.throwIfDisposed(),this.outputTexture===t&&(me(this.gl,this.debug,this.framebuffer),this.outputTexture=null),qt(this.gl,this.debug,function(){return e.gl.deleteTexture(t)});},t.prototype.downloadByteEncodedFloatMatrixFromOutputTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return mi(r.gl,r.debug,e,n,r.textureConfig)})},t.prototype.downloadPackedMatrixFromBuffer=function(t,e,n,r,o,a){return gi(this.gl,t,0,0,0,o,a,this.textureConfig)},t.prototype.downloadFloat32MatrixFromBuffer=function(t,e){return vi(this.gl,t,e)},t.prototype.createBufferFromTexture=function(t,e,n){this.bindTextureToFrameBuffer(t);var r=di(this.gl,this.debug,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r},t.prototype.createAndWaitForFence=function(){var t=this.createFence(this.gl);return this.pollFence(t)},t.prototype.createFence=function(t){var e,n,r=this;if(a().getBool("WEBGL_FENCE_API_ENABLED")){var o=t,i=o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE,0);t.flush(),n=function(){var t=o.clientWaitSync(i,0,0);return t===o.ALREADY_SIGNALED||t===o.CONDITION_SATISFIED},e=i;}else a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(e=this.beginQuery(),this.endQuery(),n=function(){return r.isQueryAvailable(e,a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}):n=function(){return !0};return {query:e,isFencePassed:n}},t.prototype.downloadMatrixFromPackedTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return yi(r.gl,r.debug,e,n)})},t.prototype.createProgram=function(t){this.throwIfDisposed();var e=this.gl,n=Jt(e,this.debug,t),r=ni(e,this.debug),o=ne(e,this.debug);return qt(e,this.debug,function(){return e.attachShader(o,r)}),qt(e,this.debug,function(){return e.attachShader(o,n)}),re(e,this.debug,o),this.debug&&oe(e,this.debug,o),this.vertexAttrsAreBound||(this.setProgram(o),this.vertexAttrsAreBound=hi(e,this.debug,this.program,this.vertexBuffer)),o},t.prototype.deleteProgram=function(t){var e=this;this.throwIfDisposed(),t===this.program&&(this.program=null),null!=t&&qt(this.gl,this.debug,function(){return e.gl.deleteProgram(t)});},t.prototype.setProgram=function(t){var e=this;this.throwIfDisposed(),this.program=t,null!=this.program&&this.debug&&oe(this.gl,this.debug,this.program),qt(this.gl,this.debug,function(){return e.gl.useProgram(t)});},t.prototype.getUniformLocation=function(t,e,n){return void 0===n&&(n=!0),this.throwIfDisposed(),n?fe(this.gl,this.debug,t,e):pe(this.gl,t,e)},t.prototype.getAttributeLocation=function(t,e){var n=this;return this.throwIfDisposed(),qt(this.gl,this.debug,function(){return n.gl.getAttribLocation(t,e)})},t.prototype.getUniformLocationNoThrow=function(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)},t.prototype.setInputMatrixTexture=function(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),de(this.gl,this.debug,this.program,t,e,n);},t.prototype.setOutputMatrixTexture=function(t,e,n){this.setOutputMatrixTextureDriver(t,n,e);},t.prototype.setOutputPackedMatrixTexture=function(t,e,n){this.throwIfDisposed();var r=Gt(e,n),o=r[0],a=r[1];this.setOutputMatrixTextureDriver(t,o,a);},t.prototype.setOutputMatrixWriteRegion=function(t,e,n,r){this.setOutputMatrixWriteRegionDriver(n,t,r,e);},t.prototype.setOutputPackedMatrixWriteRegion=function(t,e,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")},t.prototype.debugValidate=function(){null!=this.program&&oe(this.gl,this.debug,this.program),ge(this.gl);},t.prototype.executeProgram=function(){this.throwIfDisposed(),this.throwIfNoProgram();var t=this.gl;this.debug&&this.debugValidate(),qt(t,this.debug,function(){return t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0)});},t.prototype.blockUntilAllProgramsCompleted=function(){var t=this;this.throwIfDisposed(),qt(this.gl,this.debug,function(){return t.gl.finish()});},t.prototype.getQueryTimerExtension=function(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=Yt(this.gl,this.debug,2===a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension},t.prototype.getQueryTimerExtensionWebGL2=function(){return this.getQueryTimerExtension()},t.prototype.getQueryTimerExtensionWebGL1=function(){return this.getQueryTimerExtension()},t.prototype.beginQuery=function(){if(2===a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var t=this.gl,e=this.getQueryTimerExtensionWebGL2(),n=t.createQuery();return t.beginQuery(e.TIME_ELAPSED_EXT,n),n}var r=this.getQueryTimerExtensionWebGL1(),o=r.createQueryEXT();return r.beginQueryEXT(r.TIME_ELAPSED_EXT,o),o},t.prototype.endQuery=function(){if(2!==a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var t=this.getQueryTimerExtensionWebGL1();t.endQueryEXT(t.TIME_ELAPSED_EXT);}else{var e=this.gl,n=this.getQueryTimerExtensionWebGL2();e.endQuery(n.TIME_ELAPSED_EXT);}},t.prototype.waitForQueryAndGetTime=function(t){return n(this,void 0,void 0,function(){var e=this;return r(this,function(n){switch(n.label){case 0:return [4,S(function(){return e.disposed||e.isQueryAvailable(t,a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))})];case 1:return n.sent(),[2,this.getQueryTime(t,a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))]}})})},t.prototype.getQueryTime=function(t,e){if(0===e)return null;if(2===e){var n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}var r=this.getQueryTimerExtensionWebGL1();return r.getQueryObjectEXT(t,r.QUERY_RESULT_EXT)/1e6},t.prototype.isQueryAvailable=function(t,e){if(0===e)return !0;if(2===e){var n=this.gl,r=this.getQueryTimerExtensionWebGL2(),o=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint}o=(r=this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(t,r.QUERY_RESULT_AVAILABLE_EXT);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint},t.prototype.pollFence=function(t){var e=this;return new Promise(function(n){e.addItemToPoll(function(){return t.isFencePassed()},function(){return n()});})},t.prototype.pollItems=function(){for(var t=function(t){for(var e=0;e<t.length;++e){var n=t[e]();if(!n)break}return e-1}(this.itemsToPoll.map(function(t){return t.isDoneFn})),e=0;e<=t;++e){(0, this.itemsToPoll[e].resolveFn)();}this.itemsToPoll=this.itemsToPoll.slice(t+1);},t.prototype.addItemToPoll=function(t,e){var n=this;this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),this.itemsToPoll.length>1||S(function(){return n.pollItems(),0===n.itemsToPoll.length});},t.prototype.bindTextureToFrameBuffer=function(t){this.throwIfDisposed(),ve(this.gl,this.debug,t,this.framebuffer),this.debug&&ge(this.gl);},t.prototype.unbindTextureToFrameBuffer=function(){null!=this.outputTexture?(ve(this.gl,this.debug,this.outputTexture,this.framebuffer),this.debug&&ge(this.gl)):me(this.gl,this.debug,this.framebuffer);},t.prototype.downloadMatrixDriver=function(t,e){this.bindTextureToFrameBuffer(t);var n=e();return this.unbindTextureToFrameBuffer(),n},t.prototype.setOutputMatrixTextureDriver=function(t,e,n){this.throwIfDisposed();var r=this.gl;ve(r,this.debug,t,this.framebuffer),this.debug&&ge(r),this.outputTexture=t,qt(r,this.debug,function(){return r.viewport(0,0,e,n)}),qt(r,this.debug,function(){return r.scissor(0,0,e,n)});},t.prototype.setOutputMatrixWriteRegionDriver=function(t,e,n,r){var o=this;this.throwIfDisposed(),qt(this.gl,this.debug,function(){return o.gl.scissor(t,e,n,r)});},t.prototype.throwIfDisposed=function(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")},t.prototype.throwIfNoProgram=function(){if(null==this.program)throw new Error("No GPU program is currently set.")},t}();function wi(t,e){if(t.length!==e.length)throw Error("Binary was compiled with "+t.length+" inputs, but was executed with "+e.length+" inputs");t.forEach(function(t,n){var r=t.logicalShape,o=e[n],a=o.shape;if(!C(r,a))throw Error("Binary was compiled with different shapes than the current args. Shapes "+r+" and "+a+" must match");if(!t.isUniform||!o.isUniform){var i=t.texShape,u=o.isUniform?null:o.texData.texShape;if(!C(i,u))throw Error("Binary was compiled with different texture shapes than the current args. Shape "+i+" and "+u+" must match")}});}var Ci=function(){return function(t,e,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var r=n.filterWidth,o=n.inChannels,a=n.strideWidth,i=n.strideHeight,u=n.padInfo,s=n.outWidth,c=n.dilationWidth,l=n.dilationHeight,h=n.dataFormat,f=u.left,p=u.top,d=o*r,v=Ko(),m="channelsLast"===h,g=m?0:1,y=m?1:2,x="",b=0;b<=1;b++)for(var w=0;w<=1;w++)x+="\n          blockIndex = rc.y + "+w+";\n          pos = rc.x + "+b+";\n\n          if(blockIndex < "+t[1]+" && pos < "+t[0]+") {\n            offsetY = int(blockIndex / ("+s+")) * "+i+" - "+p+";\n            d0 = offsetY + "+l+" * (pos / "+d+");\n\n            if(d0 < "+e[g]+" && d0 >= 0) {\n\n              offsetX = int(mod(float(blockIndex), "+s+".) * "+a+". - "+f+".);\n              d1 = offsetX + "+c+" * (int(mod(float(pos), "+d+".) / "+o+".));\n\n              if(d1 < "+e[y]+" && d1 >= 0) {\n\n                ch = int(mod(float(pos), "+o+".));\n\n                if ("+m+") {\n                  innerDims = vec2(d1, ch);\n                  result["+(2*b+w)+"] = getChannel(\n                    getA(d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result["+(2*b+w)+"] = getChannel(\n                    getA(ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        ";this.userCode="\n      void main() {\n        ivec2 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        "+x+"\n\n        "+v.output+" = result;\n      }\n    ";}}(),Ei=function(){return function(t,e,n,r,o){this.variableNames=["x"],this.outputShape=[];var a,i=e,u=t[3]-1;this.outputShape=t;var s="float("+n+") + float("+r+") * sum";a=.5===o?"inversesqrt("+s+")":1===o?"1.0/("+s+")":"exp(log("+s+") * float(-"+o+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -"+i+"; j <= "+i+"; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  "+u+") {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * "+a+";\n        setOutput(val);\n      }\n    ";}}(),Ri=function(){return function(t,e,n,r,o){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=r,this.beta=o,this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < "+this.depth+"; ++d) {\n          int depthBegin = int(max(0.0, float(d - "+e+")));\n          int depthEnd = int(min(float("+this.depth+"),\n              float(d + "+e+" + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = "+this.depth+";\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float("+r+") * norm + float("+n+");\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float("+r+")\n                * float("+o+")\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * "+o+");\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    ";}}(),Ii=function(){return function(t,e,n,r,o){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;var a,i=e,u=t[3]-1;this.outputShape=t;var s="float("+n+") + float("+r+") * sum";a=.5===o?"inversesqrt("+s+")":1===o?"1.0/("+s+")":"exp(log("+s+") * float(-"+o+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < "+this.outputShape[3]+";\n        bool hasNextRow = c < "+this.outputShape[2]+";\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - "+i+";\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - "+i+"; j <= "+i+"; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2("+u+"));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * "+a+";\n        setOutput(result);\n      }\n    ";}}(),ki=function(){return function(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideHeight,n=t.strideWidth,r=t.dilationHeight,o=t.effectiveFilterHeight,a=t.effectiveFilterWidth,i=o-1-t.padInfo.top,u=a-1-t.padInfo.left,s=o*a-1;this.userCode="\n      const ivec2 pads = ivec2("+i+", "+u+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+o+";\n          wR += "+r+") {\n          float dyR = float(dyRCorner + wR) / "+e+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+a+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+n+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = "+s+" - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * "+a+" + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),Si=function(){return function(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.dilationDepth,a=t.dilationHeight,i=t.dilationWidth,u=t.effectiveFilterDepth,s=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=u-1-t.padInfo.front,h=s-1-t.padInfo.top,f=c-1-t.padInfo.left,p=u*s*c-1;this.userCode="\n      const ivec3 pads = ivec3("+l+", "+h+", "+f+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+u+";\n           wD += "+o+") {\n          float dyD = float(dyDCorner + wD) / "+e+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+s+";\n              wR += "+a+") {\n            float dyR = float(dyRCorner + wR) / "+n+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+c+";\n                wC += "+i+") {\n              float dyC = float(dyCCorner + wC) / "+r+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = "+p+" -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * "+s+" * "+c+" +\n                  wR * "+c+" + wC;\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n              dotProd += dyValue * mask;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";}}(),Ai=function(){return function(t,e,n,r,o,a,i){void 0===n&&(n=!1),void 0===r&&(r=!1),void 0===o&&(o=!1),void 0===a&&(a=null),void 0===i&&(i=!1),this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;var u=n?t[1]:t[2],s=Math.ceil(u/2),c=n?"i * 2, rc.y":"rc.y, i * 2",l=r?"rc.z, i * 2":"i * 2, rc.z",h=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],p="",d="";a&&(p=i?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          "+a+"\n        }":"vec4 activation(vec4 x) {\n          "+a+"\n        }",d="result = activation(result);");var v=o?"result += getBiasAtOutCoords();":"";o&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+p+"\n\n      const float sharedDimension = "+s+".0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < "+s+"; i++) {\n          vec4 a = getMatrixA(rc.x, "+c+");\n          vec4 b = getMatrixB(rc.x, "+l+");\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += ("+h[0]+" * "+f[0]+");\n          result += ("+h[1]+" * "+f[1]+");\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        "+v+"\n\n        "+d+"\n\n        setOutput(result);\n      }\n    ";}}(),Di=function(){function t(t,e,n){this.variableNames=["probs"],this.outputShape=[t,n],this.userCode="\n      uniform float seed;\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < "+(e-1)+"; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float("+(e-1)+"));\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.seedLoc&&(e.seedLoc=n.getUniformLocation(r,"seed")),n.gl.uniform1f(e.seedLoc,t);}},t}(),Ti=function(){return function(t,e,n,r){this.variableNames=["indices"],this.outputShape=[t,e],this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float("+r+"), float("+n+"),\n                      float(index == coords.y)));\n      }\n    ";}}(),Ni=function(){return function(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=t;var e=t.length;if(0===e)this.userCode="\n        void main() {\n          setOutput(vec4(getA(), 0., 0., 0.));\n        }\n      ";else{var n=qo("rc",e),r=aa(e),o=function(t,e,n){if(1===t)return "rc > "+e[0];for(var r="",o=t-2;o<t;o++)r+=n[o]+" >= "+e[o],o<t-1&&(r+="||");return r}(e,t,n),a=function(t,e,n,r){if(1===t)return "";var o=r.slice(-2);return "\n    int r = "+o[0]+";\n    int c = "+o[1]+";\n    int rp1 = r + 1;\n    int cp1 = c + 1;\n\n    bool cEdge = cp1 >= "+e+";\n    bool rEdge = rp1 >= "+n+";\n  "}(e,t[t.length-1],t[t.length-2],n),i=function(t,e){var n=t.length,r=function(t,e){for(var n=[],r=0;r<=1;r++)for(var o=0;o<=1;o++){for(var a=(0===r?"r":"rp1")+", "+(0===o?"c":"cp1"),i=2;i<t;i++)a=e[e.length-1-i]+","+a;n.push(a);}return n}(n,e);return 1===n?"getA(rc),\n            rc + 1 >= "+t[0]+" ? 0. : getA(rc + 1),\n            0, 0":"getA("+r[0]+"),\n          cEdge ? 0. : getA("+r[1]+"),\n          rEdge ? 0. : getA("+r[2]+"),\n          rEdge || cEdge ? 0. : getA("+r[3]+")"}(t,n);this.userCode="\n        void main() {\n          "+r+" rc = getOutputCoords();\n\n          if("+o+") {\n            setOutput(vec4(0));\n          } else {\n            "+a+"\n\n            setOutput(vec4("+i+"));\n          }\n        }\n      ";}}}();var Fi=function(){return function(t,e,n){this.variableNames=["x"],this.outputShape=e.map(function(e,n){return e[0]+t[n]+e[1]});var r=t.length,o=aa(r),a=e.map(function(t){return t[0]}).join(","),i=e.map(function(e,n){return e[0]+t[n]}).join(","),u=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);this.userCode=1!==r?"\n      "+o+" start = "+o+"("+a+");\n      "+o+" end = "+o+"("+i+");\n\n      void main() {\n        "+o+" outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(float("+n+"));\n        } else {\n          "+o+" coords = outC - start;\n          setOutput(getX("+u+"));\n        }\n      }\n    ":"\n        int start = "+a+";\n        int end = "+i+";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(float("+n+"));\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      ";}}(),_i=function(){return function(t,e,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.map(function(e,n){return e[0]+t[n]+e[1]});for(var r=t.length,o=aa(r),a=e.map(function(t){return t[0]}).join(","),i=e.map(function(e,n){return e[0]+t[n]}).join(","),u=qo("rc",r),s=qo("source",r),c=u[r-1]+" < "+this.outputShape[r-1],l=1===r?"source":"vec2("+s.slice(-2).join()+")",h=[o+" rc = outputLoc;",u[r-1]+" += 1;\n       if("+c+") {\n      ",1===r?"":"}\n       rc = outputLoc;\n       "+u[r-2]+" += 1;\n       if("+u[r-2]+" < "+this.outputShape[r-2]+") {",1===r?"":"  "+u[r-1]+" += 1;\n         if("+c+") {"],f=1===r?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="",d=0,v=1===r?2:4;d<v;d++)p+="\n        "+h[d]+"\n        if ("+f+") {\n          result["+d+"] = float("+n+");\n        } else {\n          "+o+" source = rc - start;\n          result["+d+"] = getChannel(getX("+s.join()+"), "+l+");\n        }\n      ";p+=1===r?"} ":"}}",this.userCode="\n      const "+o+" start = "+o+"("+a+");\n      const "+o+" end = "+o+"("+i+");\n\n      void main() {\n        "+o+" outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        "+p+"\n        setOutput(result);\n      }\n    ";}}(),Oi=function(){return function(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,o=t.strideHeight,a=t.strideWidth,i=t.dilationHeight,u=t.dilationWidth,s=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=t.padInfo.top,h=t.padInfo.left;this.outputShape=t.outShape;var f="avg"===e,p="0.0";if(f||(p="-1.0 / 1e-20"),n)this.userCode="\n        const ivec2 strides = ivec2("+o+", "+a+");\n        const ivec2 pads = ivec2("+l+", "+h+");\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < "+s+";\n              wR += "+i+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+c+";\n                wC += "+u+") {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value >= currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = wR * "+c+" + wC;\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else{var d=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(d="avgValue / count");var v=4*Math.floor(r/4),m=r%4,g="\n      if ("+f+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec2 strides = ivec2("+o+", "+a+");\n      const ivec2 pads = ivec2("+l+", "+h+");\n      const float initializationValue = "+p+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+p+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < "+s+";\n            wR += "+i+") {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+v+"; wC += 4) {\n            int xC = xCCorner + wC * "+u+";\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+u+", d),\n              getValue(batch, xR, xC + 2 * "+u+", d),\n              getValue(batch, xR, xC + 3 * "+u+", d)\n            );\n\n            "+g+"\n          }\n\n          int xC = xCCorner + "+v+";\n          if ("+(1===m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            "+g+"\n          } else if ("+(2===m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+u+", d),\n              initializationValue,\n              initializationValue\n            );\n\n            "+g+"\n          } else if ("+(3===m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+u+", d),\n              getValue(batch, xR, xC + 2 * "+u+", d),\n              initializationValue\n            );\n\n            "+g+"\n          }\n        }\n        setOutput("+d+");\n      }\n    ";}}}(),Mi=function(){return function(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,u=t.dilationDepth,s=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,p=t.padInfo.front,d=t.padInfo.top,v=t.padInfo.left;this.outputShape=t.outShape;var m="avg"===e,g="0.0";if(m||(g="-1.0 / 1e-20"),n)this.userCode="\n        const ivec3 strides =\n            ivec3("+o+", "+a+", "+i+");\n        const ivec3 pads = ivec3("+p+", "+d+", "+v+");\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < "+l+";\n              wD += "+u+") {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int wR = 0; wR < "+h+";\n                wR += "+s+") {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int wC = 0; wC < "+f+";\n                  wC += "+c+") {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value >= currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;\n                  minMaxPosition =\n                      wD * "+h+" * "+f+" +\n                      wR * "+f+" + wC;;\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else{var y=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(y="avgValue / count");var x=4*Math.floor(r/4),b=r%4,w="\n      if ("+m+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec3 strides =\n        ivec3("+o+", "+a+", "+i+");\n      const ivec3 pads = ivec3("+p+", "+d+", "+v+");\n      const float initializationValue = "+g+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+g+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < "+l+";\n            wD += "+u+") {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+h+";\n            wR += "+s+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+x+"; wC += 4) {\n              int xC = xCCorner + wC * "+c+";\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+c+", ch),\n                getValue(batch, xD, xR, xC + 3 * "+c+", ch)\n              );\n\n              "+w+"\n            }\n\n            int xC = xCCorner + "+x+";\n            if ("+(1===b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(2===b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(3===b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+c+", ch),\n                initializationValue\n              );\n\n              "+w+"\n            }\n          }\n          setOutput("+y+");\n        }\n      }\n    ";}}}(),Bi=function(){return function(t,e){this.variableNames=["x"];var n=t.windowSize,r=t.batchSize,o=t.inSize,a=Math.ceil(o/n);this.outputShape=[r,a];var i="0.0",u="";"prod"===e?i="1.0":"min"===e?(i="1.0 / 1e-20",u="min"):"max"===e&&(i="-1.0 / 1e-20",u="max");var s=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"sum"===e?s="sumValue":"prod"===e?s="prodValue":"all"===e?s="allValue":"any"===e&&(s="anyValue");var c=4*Math.floor(n/4),l=n%4,h="\n      if ("+("sum"===e)+") {\n        sumValue += dot(values, ones);\n      } else if ("+("prod"===e)+") {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = "+u+"(values, minMaxValue);\n      }\n    ",f="vec4";"all"===e?(i="1.0",h="\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      ",f="bvec4"):"any"===e&&(i="0.0",h="\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      ",f="bvec4");var p="";o%n>0&&(p="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return initializationValue;\n        }\n      "),this.userCode="\n      const float initializationValue = "+i+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        "+p+"\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * "+n+";\n\n        vec4 minMaxValue = vec4("+i+");\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < "+c+"; i += 4) {\n          int inIdx = inOffset + i;\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          "+h+"\n        }\n\n        int inIdx = inOffset + "+c+";\n        if ("+(1===l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          "+h+"\n        } else if ("+(2===l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          "+h+"\n        } else if ("+(3===l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          "+h+"\n        }\n        setOutput("+s+");\n      }\n    ";}}(),Pi=function(){return function(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var n="",r=0;r<4;r++){var o="thisRC = rc;";r%2==1&&(o+="thisRC.z += 1;"),r>1&&(o+="thisRC.y += 1;"),n+="\n        "+o+"\n        "+(r>0?"if(thisRC.y < rows && thisRC.z < cols){":"")+"\n          int flatIndex = getFlatIndex(thisRC);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result["+r+"] =\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n        "+(r>0?"}":"")+"\n      ";}this.userCode="\n      \n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      "+jo(["r","c","d"],e)+"\n      return ivec3(r, c, d);\n    }\n  \n      "+Xo(t)+"\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.);\n\n        ivec3 thisRC;\n        int rows = "+t[1]+";\n        int cols = "+t[2]+";\n\n        "+n+"\n\n        setOutput(result);\n      }\n    ";}}();var Li=function(){return function(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],a=r[2],i=t.shape,u=i[1],s=i[2],c=[n&&u>1?o-1:o,n&&s>1?a-1:a],l=[n&&u>1?u-1:u,n&&s>1?s-1:s],h=c[0]/l[0],f=c[1]/l[1],p=1/h,d=1/f,v=2*Math.ceil(p)+2,m=2*Math.ceil(d)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+h+");\n        const float widthScale = float("+f+");\n\n        const float invHeightScale = float("+p+");\n        const float invWidthScale = float("+d+");\n\n        const int winHeight = int("+v+");\n        const int winWidth = int("+m+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+u+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+s+") {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), "+(o-1)+".0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), "+(a-1)+".0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    ";}}(),Wi=function(){return function(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var o=t[0],a=t[1],i=t[2],u=t[3];this.outputShape=[o,e,n,u];var s=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+s[0]/c[0]+",\n          "+s[1]/c[1]+");\n      const vec2 inputShapeRC = vec2("+a+".0, "+i+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    ";}}(),Ui=function(){return function(t,e,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var o=t[0],a=t[1],i=t[2],u=t[3];this.outputShape=[o,e,n,u];var s=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode="\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          "+s[0]/c[0]+",\n          "+s[1]/c[1]+",\n          "+s[1]/c[1]+");\n      const vec3 inputShapeRC = vec3("+a+".0, "+i+".0,\n                                     "+i+".0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < "+(u-1)+";\n        bool hasNextRow = coords.z < "+(n-1)+";\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    ";}}(),Vi=function(){return function(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],a=r[2],i=t.shape,u=i[1],s=i[2],c=[n&&u>1?o-1:o,n&&s>1?a-1:a],l=[n&&u>1?u-1:u,n&&s>1?s-1:s],h=c[0]/l[0],f=c[1]/l[1],p=1/h,d=1/f,v=2*Math.ceil(p)+2,m=2*Math.ceil(d)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+h+");\n        const float widthScale = float("+f+");\n\n        const float invHeightScale = float("+p+");\n        const float invWidthScale = float("+d+");\n\n        const int winHeight = int("+v+");\n        const int winWidth = int("+m+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+u+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+s+") {\n              continue;\n            }\n\n            float sourceFracRow =\n              float("+c[0]+") *\n                (float(dyR) / float("+l[0]+"));\n\n            float sourceFracCol =\n                float("+c[1]+") *\n                  (float(dyC) / float("+l[1]+"));\n\n            int sourceNearestRow = int(min(\n                float(int("+o+") - 1),\n                "+n+" ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int("+a+") - 1),\n                "+n+" ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    ";}}(),zi=function(){return function(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var o=t[0],a=t[1],i=t[2],u=t[3];this.outputShape=[o,e,n,u];var s=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n],l=r?"0.5":"0.0";this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+s[0]/c[0]+",\n          "+s[1]/c[1]+");\n      const vec2 inputShapeRC = vec2("+a+".0, "+i+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + "+l+")));\n\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    ";}}(),Gi=function(){return function(t,e){this.variableNames=["x"];var n=t.length;if(n>4)throw new Error("WebGL backend: Reverse of rank-"+n+" tensor is not yet supported");if(this.outputShape=t,1!==n){var r=t.map(function(n,r){return function(n){return -1!==e.indexOf(n)&&1!==t[n]?t[n]+" - coords["+n+"] - 1":"coords["+n+"]"}(r)}).join(","),o=aa(n);this.userCode="\n      void main() {\n        "+o+" coords = getOutputCoords();\n        setOutput(getX("+r+"));\n      }\n    ";}else this.userCode="\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX("+t[0]+" - coord - 1));\n        }\n      ";}}(),Hi=function(){return function(t,e){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;var n=t.length;if(n>4)throw new Error("WebGL backend: Reverse of rank-"+n+" tensor is not yet supported");this.outputShape=t;var r=qo("rc",n),o=r[n-1]+" + 1 < "+this.outputShape[n-1],a=r[n-2]+" + 1 < "+this.outputShape[n-2],i=aa(n);function u(n){var r=t.map(function(r,o){return function(n,r){return -1!==e.indexOf(n)&&1!==t[n]?t[n]+" - "+r[n]+" - 1":""+r[n]}(o,n)});return "getChannel(getX("+r.join(",")+"), vec2("+r.slice(-2).join(",")+"))"}this.userCode=1===n?"\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX("+t[0]+" - rc - 1),\n            "+t[0]+" - rc - 1);\n          if("+o+"){\n              result.g = getChannel(getX("+t[0]+" - (rc  + 1) - 1),\n                "+t[0]+" - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      ":"\n        void main() {\n          "+i+" rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = "+function(t){return u(t)}(r.slice())+";\n          if("+o+"){\n            result.g = "+function(t){return t[n-1]="("+t[n-1]+" + 1)",u(t)}(r.slice())+";\n          }\n          if("+a+") {\n            result.b = "+function(t){return t[n-2]="("+t[n-2]+" + 1)",u(t)}(r.slice())+";\n            if("+o+") {\n              result.a = "+function(t){return t[n-1]="("+t[n-1]+" + 1)",t[n-2]="("+t[n-2]+" + 1)",u(t)}(r.slice())+";\n            }\n          }\n          setOutput(result);\n        }\n    ";}}(),qi=function(){return function(t,e,n,r,o,a,i){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;var u=aa(o.length),s=aa(a.length),c="";1===n?c="i":2===n&&(c="i, j");var l="getIndices("+c+")",h="";1===r?h="i":2===r&&(h="i, coords[1]");var f="getUpdates("+h+")",p=e>1?"strides[j]":"strides";this.userCode="\n        "+u+" strides = "+u+"("+o+");\n\n        void main() {\n          "+s+" coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < "+t+"; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < "+e+"; j++) {\n              int index = round("+l+");\n              flattenedIndex += index * "+p+";\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += "+f+";\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      ";}}(),Ki=function(){return function(t,e){this.variableNames=["x","segmentIds"];var n=t.windowSize,r=t.batchSize,o=t.inSize,a=t.numSegments,i=a*Math.ceil(o/n);this.outputShape=[r,i];var u=4*Math.floor(n/4),s=n%4,c="\n        sumValue += dot(values, segFilter);\n    ",l="";o%n>0&&(l="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return initializationValue;\n        }\n      ");var h="";o%n>0&&(h="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return -1.0;\n        }\n      "),this.userCode="\n      const float initializationValue = 0.0;\n\n      float getValue(int batch, int inIdx) {\n        "+l+"\n        return getX(batch, inIdx);\n      }\n\n      float getSegmentIdAtIndex(int inIdx) {\n        "+h+"\n        return getSegmentIds(inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = int(floor(float(outIdx) / float(\n          "+a+")) * float("+n+"));\n        int currentSeg = int(mod(float(outIdx), float("+a+")));\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < "+u+"; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n          );\n\n          "+c+"\n        }\n\n        int inIdx = inOffset + "+u+";\n        if ("+(1===s)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            0,\n            0,\n            0\n          );\n\n          "+c+"\n        } else if ("+(2===s)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n              0,\n              0\n          );\n\n          "+c+"\n        } else if ("+(3===s)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            0\n          );\n\n          "+c+"\n        }\n        setOutput(sumValue);\n      }\n    ";}}(),ji=function(){return function(t,e,n){var r,o;if(this.variableNames=["c","a","b"],this.outputShape=e,n>4)throw Error("Where for rank "+n+" is not yet supported");if(1===n)o="resRC",r="resRC";else{for(var a=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],u=[],s=0;s<e.length;s++)u.push(""+a[s]),s<t&&i.push(""+a[s]);r=i.join(),o=u.join();}var c=aa(n);this.userCode="\n      void main() {\n        "+c+" resRC = getOutputCoords();\n        float cVal = getC("+r+");\n        if (cVal >= 1.0) {\n          setOutput(getA("+o+"));\n        } else {\n          setOutput(getB("+o+"));\n        }\n      }\n    ";}}(),Xi=function(){function t(t){this.variableNames=["source"],this.outputShape=t,this.rank=t.length;var e,n=aa(this.rank),r="uniform int start["+this.rank+"];",o=function(t){if(1===t)return "sourceLoc";if(t<=6)return $i.slice(0,t).map(function(t){return "sourceLoc."+t}).join(",");throw Error("Slicing for rank "+t+" is not yet supported")}(this.rank);e="\n        "+n+" sourceLoc;\n        "+n+" coords = getOutputCoords();\n        "+t.map(function(t,e){return "sourceLoc."+$i[e]+" = start["+e+"] + coords."+$i[e]+";"}).join("\n")+"\n      ",this.userCode="\n      "+r+"\n      void main() {\n        "+e+"\n        setOutput(getSource("+o+"));\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+t.length+")");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,"start"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t);}},t}(),$i=["x","y","z","w","u","v"];var Yi=function(){function t(t){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length;var e=aa(this.rank),n=qo("coords",this.rank),r=qo("sourceLoc",this.rank),o=1===this.rank?"sourceLoc":"vec2("+r.slice(-2).join()+")",a="getChannel(getSource("+r.join()+"), "+o+")",i="\n      result.x = "+a+";\n      if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n        ++"+r[this.rank-1]+";\n        result.y = "+a+";\n        --"+r[this.rank-1]+";\n      }\n    ",u=1===this.rank?"":"\n      --"+n[this.rank-1]+";\n      if (++"+n[this.rank-2]+" < "+t[this.rank-2]+") {\n        ++"+r[this.rank-2]+";\n        result.z = "+a+";\n        if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n          ++"+r[this.rank-1]+";\n          result.w = "+a+";\n        }\n      }\n    ",s=this.rank<=4?"sourceLoc = coords +\n            "+e+"("+t.map(function(t,e){return "start["+e+"]"}).join()+");":t.map(function(t,e){return r[e]+" = "+n[e]+" + start["+e+"];"}).join("\n");this.userCode="\n      uniform int start["+this.rank+"];\n      void main() {\n        "+e+" coords = getOutputCoords();\n        "+e+" sourceLoc;\n        "+s+"\n        vec4 result = vec4(0.);\n        "+i+"\n        "+u+"\n        setOutput(result);\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+t.length+")");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,"start"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t);}},t}(),Qi=function(){return function(t,e,n){this.variableNames=["x"],this.outputShape=n;var r=n.length,o=aa(n.length),a=aa(n.length),i="";if(1===r)i="coords * strides + begin";else{var u=0;i=n.map(function(t,e){return u++,1===n.length?"coords * strides["+e+"] + begin["+e+"]":"coords["+(u-1)+"] * strides["+e+"] + begin["+e+"]"}).join(",");}this.userCode="\n      "+o+" begin = "+o+"("+t+");\n      "+o+" strides = "+o+"("+e+");\n\n      void main() {\n        "+a+" coords = getOutputCoords();\n        setOutput(getX("+i+"));\n      }\n    ";}}(),Ji=function(){function t(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={};}return t.prototype.acquireTexture=function(t,e,n){var r,o=Zi(e,n),a=tu(t,o,n);if(a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]),this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this.log();var i=this.freeTextures[a].shift();return this.usedTextures[a].push(i),i}return this.numUsedTextures++,this.log(),o===Bt.PACKED_2X2_FLOAT32?r=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Bt.PACKED_2X2_FLOAT16?r=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Bt.UNPACKED_FLOAT32?r=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Bt.UNPACKED_FLOAT16?r=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Bt.PACKED_4X1_UNSIGNED_BYTE&&(r=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[a].push(r),r},t.prototype.releaseTexture=function(t,e,n,r){if(null!=this.freeTextures){var o=tu(e,Zi(n,r),r);o in this.freeTextures||(this.freeTextures[o]=[]),this.freeTextures[o].push(t),this.numFreeTextures++,this.numUsedTextures--;var a=this.usedTextures[o],i=a.indexOf(t);if(i<0)throw new Error("Cannot release a texture that was never provided by this texture manager");a.splice(i,1),this.log();}},t.prototype.log=function(){if(this.logEnabled){var t=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",this.numFreeTextures+" / "+this.numUsedTextures,"("+t+")");}},t.prototype.getNumUsedTextures=function(){return this.numUsedTextures},t.prototype.getNumFreeTextures=function(){return this.numFreeTextures},t.prototype.dispose=function(){var t=this;if(null!=this.freeTextures){for(var e in this.freeTextures)this.freeTextures[e].forEach(function(e){t.gpgpu.deleteMatrixTexture(e);});for(var e in this.usedTextures)this.usedTextures[e].forEach(function(e){t.gpgpu.deleteMatrixTexture(e);});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0;}},t}();function Zi(t,e){if(t===Mt.UPLOAD)return Bt.PACKED_2X2_FLOAT32;if(t===Mt.RENDER||null==t)return function(t){return a().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?t?Bt.PACKED_2X2_FLOAT32:Bt.UNPACKED_FLOAT32:t?Bt.PACKED_2X2_FLOAT16:Bt.UNPACKED_FLOAT16}(e);if(t===Mt.DOWNLOAD||t===Mt.PIXELS)return Bt.PACKED_4X1_UNSIGNED_BYTE;throw new Error("Unknown logical texture type "+t)}function tu(t,e,n){return t[0]+"_"+t[1]+"_"+e+"_"+n}var eu=function(){return function(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[r]*e[r];this.outputShape=n,this.rank=n.length;var o=aa(this.rank),a=function(t){var e=t.length;if(e>5)throw Error("Tile for rank "+e+" is not yet supported");if(1===e)return "imod(resRC, "+t[0]+")";for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[],o=0;o<t.length;o++)r.push("imod("+n[o]+", "+t[o]+")");return r.join()}(t);this.userCode="\n      void main() {\n        "+o+" resRC = getOutputCoords();\n        setOutput(getA("+a+"));\n      }\n    ";}}();var nu=function(){return function(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];this.outputShape=n,this.rank=n.length;var o=aa(this.rank),a=function(t){var e=t.length;if(e>6)throw Error("Transpose for rank "+e+" is not yet supported");for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(e),o=0;o<t.length;o++)r[t[o]]=n[o];return r.join()}(e);this.userCode="\n    void main() {\n      "+o+" resRC = getOutputCoords();\n      setOutput(getA("+a+"));\n    }\n    ";}}();var ru=function(){return function(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error("Packed transpose for rank "+this.rank+" is not yet supported.");var o=aa(this.rank),a=Ho("rc",this.rank),i=new Array(this.rank);for(r=0;r<e.length;r++)i[e[r]]=a[r];var u="vec2("+i.slice(-2).join()+")",s="++"+a[this.rank-1]+" < "+n[this.rank-1],c="getChannel(getA("+i.join()+"), "+u+")";this.userCode="\n    void main() {\n      "+o+" rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = "+c+";\n      if("+s+") {\n        result[1] = "+c+";\n      }\n      --"+a[this.rank-1]+";\n      if(++"+a[this.rank-2]+" < "+n[this.rank-2]+") {\n        result[2] = "+c+";\n        if("+s+") {\n          result[3] = "+c+";\n        }\n      }\n      setOutput(result);\n    }\n    ";}}(),ou=1.7580993408473768,au=1.0507009873554805,iu=function(){return function(t,e){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      float unaryOperation(float x) {\n        "+e+"\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    ";}}(),uu="if (isnan(x)) return x;",su="return x;",cu="return abs(x);",lu=uu+"\n  return (x < 0.0) ? 0.0 : x;\n",hu=uu+"\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n",fu="return (x >= 0.0) ? x : (exp(x) - 1.0);",pu="\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = "+ou+";\n  float scale = "+au+";\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n";var du="return -x;",vu="return ceil(x);",mu="return floor(x);",gu="return exp(x);",yu="return exp(x) - 1.0;",xu=uu+"\n  return sin(x);\n",bu=uu+"\n  return cos(x);\n",wu=uu+"\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return asin(x);\n",Cu=uu+"\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return acos(x);\n",Eu=uu+"\n  return atan(x);\n",Ru=uu+"return log(x + sqrt(x * x + 1.0));",Iu=uu+"\n  if (x < 1.0) return NAN;\n  return log(x + sqrt(x * x - 1.0));",ku=uu+"\n  if ((x < -1.0) || (x > 1.0)) return NAN;\n  return (log(1.0 + x) - log(1.0 - x)) / 2.0;",Su="return x;",Au="return x;",Du="\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",Tu="\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",Nu="\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n",Fu=function(){return function(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode="\n      vec4 unaryOperation(vec4 x) {\n        "+e+"\n      }\n\n      void main() {\n        vec4 x = getAAtOutCoords();\n        vec4 y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    ";}}(),_u=function(){return function(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=t;var e=t.length,n=qo("rc",e),r=aa(e),o=function(t,e){if(1===t)return "rc";for(var n="",r=0;r<t;r++)n+=e[r],r<t-1&&(n+=",");return n}(e,n),a=n.slice(-2),i=e<=1?"rc":"vec2("+a.join(",")+")";this.userCode="\n      void main() {\n        "+r+" rc = getOutputCoords();\n        vec4 packedInput = getA("+o+");\n\n        setOutput(getChannel(packedInput, "+i+"));\n      }\n    ";}}(),Ou={};function Mu(t,e){if(void 0===e&&(e=!1),"linear"===t)return e?Au:su;if("relu"===t)return e?Du:lu;if("elu"===t)return e?Nu:fu;if("relu6"===t)return e?Tu:hu;if("prelu"===t)return e?wa:xa;throw new Error("Activation "+t+" has not been implemented for the WebGL backend.")}var Bu=600;var Pu=function(t){function o(e){var n,r=t.call(this)||this;if(r.pendingRead=new WeakMap,r.pendingDisposal=new WeakSet,r.dataRefCount=new WeakMap,r.numBytesInGPU=0,r.uploadWaitMs=0,r.downloadWaitMs=0,r.warnedAboutMemory=!1,r.pendingDeletes=0,r.disposed=!1,!a().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(null==e){var o=Ut(a().getNumber("WEBGL_VERSION"));r.binaryCache=(n=a().getNumber("WEBGL_VERSION"))in Ou?Ou[n]:(Ou[n]={},Ou[n]),r.gpgpu=new bi(o),r.canvas=o.canvas,r.gpgpuCreatedLocally=!0;}else r.gpgpu=e,r.binaryCache={},r.gpgpuCreatedLocally=!1,r.canvas=e.gl.canvas;return r.textureManager=new Ji(r.gpgpu),r.numMBBeforeWarning=null==a().global.screen?1024:a().global.screen.height*a().global.screen.width*window.devicePixelRatio*Bu/1024/1024,r.texData=new so(r,Nt),r}return e(o,t),o.prototype.numDataIds=function(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes},o.prototype.write=function(t,e,n){if(a().getBool("DEBUG")&&this.checkNumericalProblems(t),"complex64"===n&&null!=t)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");var r={};return this.texData.set(r,{shape:e,dtype:n,values:t,usage:Mt.UPLOAD}),r},o.prototype.move=function(t,e,n,r){if(a().getBool("DEBUG")&&this.checkNumericalProblems(e),"complex64"===r)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:r,values:e,usage:Mt.UPLOAD});},o.prototype.readSync=function(t){var e=this.texData.get(t),n=e.values,r=e.dtype,o=e.complexTensors,a=e.slice,i=e.shape,u=e.isPacked;if(null!=a){var s=void 0;s=u?new Fu(i,Su):new iu(i,Su);var c=this.runWebGLProgram(s,[{dataId:t,shape:i,dtype:r}],r),l=this.readSync(c.dataId);return this.disposeData(c.dataId),l}if(null!=n)return this.convertAndCacheOnCPU(t);if("string"===r)return n;var h,f,p=null!=this.activeTimers;(p&&(h=Y()),"complex64"===r)?f=No(o.real.dataSync(),o.imag.dataSync()):f=this.getValuesFromTexture(t);return p&&(this.downloadWaitMs+=Y()-h),this.convertAndCacheOnCPU(t,f)},o.prototype.read=function(t){return n(this,void 0,void 0,function(){var e,n,o,i,u,s,c,l,h,f,p,d,v,m,g,y,x,b,C,E,R,I;return r(this,function(r){switch(r.label){case 0:if(this.pendingRead.has(t))return e=this.pendingRead.get(t),[2,new Promise(function(t){return e.push(t)})];if(n=this.texData.get(t),o=n.values,i=n.shape,u=n.slice,s=n.dtype,c=n.complexTensors,l=n.isPacked,null!=u)return h=void 0,h=l?new Fu(i,Su):new iu(i,Su),f=this.runWebGLProgram(h,[{dataId:t,shape:i,dtype:s}],s),p=this.read(f.dataId),this.disposeData(f.dataId),[2,p];if(null!=o)return [2,this.convertAndCacheOnCPU(t)];if(!a().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&2===a().getNumber("WEBGL_VERSION"))throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");return d=null,"complex64"!==s&&a().get("WEBGL_BUFFER_SUPPORTED")&&(v=this.decode(t),m=this.texData.get(v.dataId),d=(I=this.gpgpu).createBufferFromTexture.apply(I,[m.texture].concat(zt(i)))),this.pendingRead.set(t,[]),"complex64"===s?[3,2]:[4,this.gpgpu.createAndWaitForFence()];case 1:r.sent(),r.label=2;case 2:return "complex64"!==s?[3,4]:[4,Promise.all([c.real.data(),c.imag.data()])];case 3:return y=r.sent(),x=y[0],b=y[1],g=No(x,b),[3,5];case 4:null==d?g=this.getValuesFromTexture(t):(C=w(i),g=this.gpgpu.downloadFloat32MatrixFromBuffer(d,C)),r.label=5;case 5:return null!=v&&this.disposeData(v.dataId),E=this.convertAndCacheOnCPU(t,g),R=this.pendingRead.get(t),this.pendingRead.delete(t),R.forEach(function(t){return t(E)}),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t),this.pendingDeletes--),[2,E]}})})},o.prototype.checkNumericalProblems=function(t){if(null!=t)for(var e=0;e<t.length;e++){var n=t[e];if(!Xt(n)){if(a().getBool("WEBGL_RENDER_FLOAT32_CAPABLE"))throw Error("The value "+n+" cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'");throw Error("The value "+n+" cannot be represented on this device.")}}},o.prototype.getValuesFromTexture=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,i=n.isPacked,u=w(r);if(a().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){var s=this.decode(t),c=this.texData.get(s.dataId),l=(e=this.gpgpu).downloadMatrixFromPackedTexture.apply(e,[c.texture].concat(zt(r))).subarray(0,u);return this.disposeData(s.dataId),l}var h=a().getBool("WEBGL_PACK")&&!0===i,f=h?Ee(r):r,p=h?new ja(f):new Ka(f),d=this.runWebGLProgram(p,[{shape:f,dtype:o,dataId:t}],"float32"),v=this.texData.get(d.dataId),m=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(v.texture,v.texShape[0],v.texShape[1]).subarray(0,u);return this.disposeData(d.dataId),m},o.prototype.time=function(t){return n(this,void 0,void 0,function(){var e,n,o,a,i,u,s;return r(this,function(r){switch(r.label){case 0:return e=this.activeTimers,n=[],o=!1,null==this.programTimersStack?(this.programTimersStack=n,o=!0):this.activeTimers.push(n),this.activeTimers=n,t(),a=b(this.activeTimers.map(function(t){return t.query})).filter(function(t){return null!=t}),i=b(this.activeTimers.map(function(t){return t.name})).filter(function(t){return null!=t}),this.activeTimers=e,o&&(this.programTimersStack=null),[4,Promise.all(a)];case 1:return u=r.sent(),s={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:m(u),getExtraProfileInfo:function(){return u.map(function(t,e){return {name:i[e],ms:t}}).map(function(t){return t.name+": "+t.ms}).join(", ")},wallMs:null},this.uploadWaitMs=0,this.downloadWaitMs=0,[2,s]}})})},o.prototype.memory=function(){return {unreliable:!1,numBytesInGPU:this.numBytesInGPU}},o.prototype.startTimer=function(){return a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?this.gpgpu.beginQuery():{startMs:Y(),endMs:null}},o.prototype.endTimer=function(t){return a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(this.gpgpu.endQuery(),t):(t.endMs=Y(),t)},o.prototype.getQueryTime=function(t){return n(this,void 0,void 0,function(){var e;return r(this,function(n){return a().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?[2,this.gpgpu.waitForQueryAndGetTime(t)]:[2,(e=t).endMs-e.startMs]})})},o.prototype.disposeData=function(t){if(!this.pendingDisposal.has(t)){if(this.pendingRead.has(t))return this.pendingDisposal.add(t),void this.pendingDeletes++;if(this.texData.has(t)){this.releaseGPUData(t);var e=this.texData.get(t).complexTensors;null!=e&&(e.real.dispose(),e.imag.dispose()),this.texData.delete(t);}}},o.prototype.releaseGPUData=function(t){var e=this.texData.get(t),n=e.texture,r=e.dtype,o=e.texShape,a=e.usage,i=e.isPacked,u=e.slice,s=u&&u.origDataId||t,c=this.dataRefCount.get(s);c>1?this.dataRefCount.set(s,c-1):(this.dataRefCount.delete(s),null!=n&&(this.numBytesInGPU-=this.computeBytes(o,r),this.textureManager.releaseTexture(n,o,a,i)));var l=this.texData.get(t);l.texture=null,l.texShape=null,l.isPacked=!1,l.slice=null;},o.prototype.getTexture=function(t){return this.uploadToGPU(t),this.texData.get(t).texture},o.prototype.getDataInfo=function(t){return this.texData.get(t)},o.prototype.getCPUBackend=function(){return a().getBool("WEBGL_CPU_FORWARD")?(null==this.cpuBackend&&(this.cpuBackend=Nt.findBackend("cpu")),this.cpuBackend):null},o.prototype.shouldExecuteOnCPU=function(t,e){var n=this;return void 0===e&&(e=128),null!=this.getCPUBackend()&&t.every(function(t){return null==n.texData.get(t.dataId).texture&&t.size<e})},o.prototype.getGPGPUContext=function(){return this.gpgpu},o.prototype.complex=function(t,e){var n=this.makeOutput(t.shape,"complex64");return this.texData.get(n.dataId).complexTensors={real:Nt.keep(t.clone()),imag:Nt.keep(e.clone())},n},o.prototype.real=function(t){return this.texData.get(t.dataId).complexTensors.real.clone()},o.prototype.imag=function(t){return this.texData.get(t.dataId).complexTensors.imag.clone()},o.prototype.slice=function(t,e,n){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.slice(t,e,n);if(0===w(n))return In([],n,t.dtype);var r=this.texData.get(t.dataId).isPacked,o=Yr(t.shape,e,n);if(r||!o){var i=a().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Yi(n):new Xi(n),u=i.getCustomSetupFunc(e);return this.compileAndRun(i,[t],null,u)}return this.uploadToGPU(t.dataId),this.shallowSlice(t,e,n)},o.prototype.shallowSlice=function(t,e,n){var r=this.texData.get(t.dataId),o=this.makeOutput(n,t.dtype),a=this.texData.get(o.dataId);Object.assign(a,r),a.shape=n,a.dtype=t.dtype;var i=Qr(e,t.strides);r.slice&&(i+=r.slice.flatOffset),a.slice={flatOffset:i,origDataId:r.slice&&r.slice.origDataId||t.dataId};var u=this.dataRefCount.get(a.slice.origDataId)||1;return this.dataRefCount.set(a.slice.origDataId,u+1),o},o.prototype.stridedSlice=function(t,e,n,r){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.stridedSlice(t,e,n,r);var o=jr(e,n,r);if(o.some(function(t){return 0===t}))return In([],o);var a=new Qi(e,r,o);return this.compileAndRun(a,[t])},o.prototype.reverse=function(t,e){var n=a().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Hi(t.shape,e):new Gi(t.shape,e);return this.compileAndRun(n,[t])},o.prototype.concat=function(t,e){if("complex64"===t[0].dtype){var n=t.map(function(t){return En(t)}),r=t.map(function(t){return Rn(t)});return Cn(this.concat(n,e),this.concat(r,e))}if(this.shouldExecuteOnCPU(t))return this.cpuBackend.concat(t,e);if(1===t.length)return t[0];if(t.length>a().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){var o=Math.floor(t.length/2),i=this.concat(t.slice(0,o),e),u=this.concat(t.slice(o),e);return this.concat([i,u],e)}if(a().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&t[0].rank>1){var s=new Sa(t.map(function(t){return t.shape}),e);return this.compileAndRun(s,t)}var c=bn(t.map(function(t){return t.shape}),e),l=t.map(function(t){return t.as2D(-1,w(t.shape.slice(e)))}),h=new ka(l.map(function(t){return t.shape}));return this.compileAndRun(h,l).reshape(c)},o.prototype.neg=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.neg(t);if(a().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,du,t.dtype);var e=new iu(t.shape,du);return this.compileAndRun(e,[t])},o.prototype.batchMatMul=function(t,e,n,r){var o=n?t.shape[2]:t.shape[1],a=r?e.shape[1]:e.shape[2],i=n?t.shape[1]:t.shape[2],u=t.shape[0];if((1===o||1===a)&&i>1e3){n&&(t=t.transpose([0,2,1])),r&&(e=e.transpose([0,2,1]));var s=1===a?t:t.as3D(u,i,1),c=1===a?2:1,l=1===a?e.as3D(u,1,i):e;return this.multiply(s,l).sum(c,!0)}var h=Ct(t.dtype,e.dtype),f=new Ai(t.shape,[u,o,a],n,r);return this.compileAndRun(f,[t,e],h)},o.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,a=t.bias,i=t.activation,u=t.preluActivationWeights,s=r?e.shape[2]:e.shape[1],c=o?n.shape[1]:n.shape[2],l=e.shape[0],h=Ct(e.dtype,n.dtype),f=null!=a,p=null!=u,d=i?Mu(i,!0):null,v=new Ai(e.shape,[l,s,c],r,o,f,d,p),m=[e,n];return a&&m.push(a),u&&m.push(u),this.compileAndRun(v,m,h)},o.prototype.multiply=function(t,e){if("complex64"===t.dtype){var n=this.texData.get(t.dataId),r=this.texData.get(e.dataId),o=new va(pa,t.shape,e.shape),i=new va(da,t.shape,e.shape),u=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag),this.makeComplexComponentTensorInfo(e,r.complexTensors.real),this.makeComplexComponentTensorInfo(e,r.complexTensors.imag)],s=this.compileAndRun(o,u),c=this.compileAndRun(i,u),l=this.complex(s,c);return s.dispose(),c.dispose(),l}if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.multiply(t,e);if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,ya,t.dtype);var h=new ba(ya,t.shape,e.shape);return this.compileAndRun(h,[t,e],t.dtype)},o.prototype.batchNormalization=function(t,e,n,r,o,i){var u=[t,e,n],s=null;null!=i&&(s=i.shape,u.push(i));var c=null;if(null!=o&&(c=o.shape,u.push(o)),a().getBool("WEBGL_PACK_NORMALIZATION")){var l=new fa(t.shape,e.shape,n.shape,s,c,r);return this.compileAndRun(l,u)}var h=new ha(t.shape,e.shape,n.shape,s,c,r);return this.compileAndRun(h,u)},o.prototype.localResponseNormalization4D=function(t,e,n,r,o){var i=a().getBool("WEBGL_PACK_NORMALIZATION")?new Ii(t.shape,e,n,r,o):new Ei(t.shape,e,n,r,o);return this.compileAndRun(i,[t])},o.prototype.LRNGrad=function(t,e,n,r,o,a,i){var u=new Ri(e.shape,r,o,a,i);return this.compileAndRun(u,[e,n,t])},o.prototype.tile=function(t,e){if("string"===t.dtype){var n=this.readSync(t.dataId).map(function(t){return Z(t)});return Lo(ir(t.shape,t.dtype,n),e)}var r=new eu(t.shape,e);return this.compileAndRun(r,[t])},o.prototype.pad=function(t,e,n){var r=a().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new _i(t.shape,e,n):new Fi(t.shape,e,n);return this.compileAndRun(r,[t])},o.prototype.transpose=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.transpose(t,e);var n=a().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new ru(t.shape,e):new nu(t.shape,e);return this.compileAndRun(n,[t])},o.prototype.gather=function(t,e,n){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.gather(t,e,n);var r=new ti(t.shape,e.size,n);return this.compileAndRun(r,[t,e])},o.prototype.batchToSpaceND=function(t,e,n){g(t.rank<=4,function(){return "batchToSpaceND for rank > 4 with a WebGL backend not implemented yet"});var r=e.reduce(function(t,e){return t*e}),o=Mr(t.shape,e,r),a=Br(o.length,e.length),i=Pr(t.shape,e,r),u=Lr(n,e.length),s=Wr(i,n,e.length);return t.reshape(o).transpose(a).reshape(i).slice(u,s)},o.prototype.spaceToBatchND=function(t,e,n){g(t.rank<=4,function(){return "spaceToBatchND for rank > 4 with a WebGL backend not implemented yet"});var r=e.reduce(function(t,e){return t*e}),o=[[0,0]];o.push.apply(o,n);for(var a=1+e.length;a<t.shape.length;++a)o.push([0,0]);var i=t.pad(o),u=Mr(i.shape,e,r,!1),s=Br(u.length,e.length,!1),c=Pr(i.shape,e,r,!1);return i.reshape(u).transpose(s).reshape(c)},o.prototype.reduce=function(t,e,n){var r=t.shape[0],o=t.shape[1],a=zr(o),i=new Bi({windowSize:a,inSize:o,batchSize:r},e),u=this.compileAndRun(i,[t],n);return 1===u.shape[1]?u:this.reduce(u,e,n)},o.prototype.argReduce=function(t,e,n){void 0===n&&(n=null);var r=t.shape[0],o=t.shape[1];null!=n&&(r=n.shape[0],o=n.shape[1]);var a=zr(o),i=new Go({windowSize:a,inSize:o,batchSize:r},e,null==n),u=[t];null!=n&&u.push(n);var s=this.compileAndRun(i,u,"int32");return 1===s.shape[1]?s:this.argReduce(t,e,s)},o.prototype.argReducePacked=function(t,e,n){void 0===n&&(n=null);var r=null!=n?n.shape:t.shape,o=zr(r[r.length-1]),a=new sa(r,o,e,null==n),i=null==n?[t]:[t,n],u=this.compileAndRun(a,i,"int32");return u.rank===t.rank?this.argReducePacked(t,e,u):u},o.prototype.sum=function(t,e){vn("sum",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o),i=Et(t.dtype);return this.reduce(a,"sum",i).reshape(r)},o.prototype.prod=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.prod(t,e);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o),i=Et(t.dtype);return this.reduce(a,"prod",i).reshape(r)},o.prototype.unsortedSegmentSum=function(t,e,n){var r=0,o=mn([r],t.rank),a=t;null!=o&&(a=t.transpose(o),r=yn(1,t.rank)[0]);var i=function(t,e,n){for(var r=[],o=t.length,a=0;a<o;a++)a!==e?r.push(t[a]):r.push(n);return r}(a.shape,r,n),u=w([a.shape[r]]),s=a.as2D(-1,u),c=Et(t.dtype),l=this.segOpCompute(s,"unsortedSegmentSum",e,c,n).reshape(i);return null!=o&&(l=l.transpose(gn(o))),l},o.prototype.segOpCompute=function(t,e,n,r,o){var a=t.shape[0],i=t.shape[1],u=function(t,e){var n,r=!1;for(t<=Vr?(n=t,r=!0):n=H(t,Math.floor(Math.sqrt(t)));!r;)n>e||n===t?r=!0:n=H(t,n+1);return n}(i,o),s=new Ki({windowSize:u,inSize:i,batchSize:a,numSegments:o},e),c=this.compileAndRun(s,[t,n],r);return c.shape[1]===o?c:(n=Wn(0,o).tile([i/u]),this.segOpCompute(c,e,n,r,o))},o.prototype.argMinMaxReduce=function(t,e,n){var r=[e];if(vn("arg"+n.charAt(0).toUpperCase()+n.slice(1),r,t.rank),!a().getBool("WEBGL_PACK_REDUCE")||t.rank<=2){var o=pn(t.shape,r),i=o[0],u=w(o[1]),s=t.as2D(-1,u);return this.argReduce(s,n).reshape(i)}return this.argReducePacked(t,n)},o.prototype.argMin=function(t,e){return this.argMinMaxReduce(t,e,"min")},o.prototype.argMax=function(t,e){return this.argMinMaxReduce(t,e,"max")},o.prototype.cumsum=function(t,e,n,r){if(e!==t.rank-1)throw new Error("WebGL cumsum shader expects an inner-most axis="+(t.rank-1)+" but got axis="+e);var o=new Ua(t.shape,n,r);return this.compileAndRun(o,[t])},o.prototype.equal=function(t,e){if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(equal(a, b));\n","bool");var n=new ba("return float(a == b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.notEqual=function(t,e){if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(notEqual(a, b));\n","bool");var n=new ba("return float(a != b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.less=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.less(t,e);if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(lessThan(a, b));\n","bool");var n=new ba("return float(a < b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.lessEqual=function(t,e){if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(lessThanEqual(a, b));\n","bool");var n=new ba("return float(a <= b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.greater=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.greater(t,e);if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(greaterThan(a, b));\n","bool");var n=new ba("return float(a > b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.greaterEqual=function(t,e){if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(greaterThanEqual(a, b));\n","bool");var n=new ba("return float(a >= b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.logicalNot=function(t){var e=new iu(t.shape,"return float(!(x >= 1.0));");return this.compileAndRun(e,[t])},o.prototype.logicalAnd=function(t,e){if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n","bool");var n=new ba("return float(a >= 1.0 && b >= 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.logicalOr=function(t,e){if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n","bool");var n=new ba("return float(a >= 1.0 || b >= 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.select=function(t,e,n){var r=new ji(t.rank,e.shape,e.rank);return this.compileAndRun(r,[t,e,n],Ct(e.dtype,n.dtype))},o.prototype.where=function(t){an("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");var e=t.dataSync();return Uo(t.shape,e)},o.prototype.topk=function(t,e,n){return Wo(t.dataSync(),t.shape,t.dtype,e)},o.prototype.min=function(t,e){vn("min",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o);return this.reduce(a,"min",a.dtype).reshape(r)},o.prototype.minimum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.minimum(t,e);var n=a().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ca("\n  vec4 result = vec4(min(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new ba("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return min(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.mod=function(t,e){var n=a().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ca("\n  vec4 result = mod(a, b);\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new ba("if (b == 0.0) return NAN;\n  return mod(a, b);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.max=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.max(t,e);vn("max",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o);return this.reduce(a,"max",a.dtype).reshape(r)},o.prototype.maximum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.maximum(t,e);var n=a().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ca("\n  vec4 result = vec4(max(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new ba("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return max(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.all=function(t,e){vn("all",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o);return this.reduce(a,"all",a.dtype).reshape(r)},o.prototype.any=function(t,e){vn("any",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o);return this.reduce(a,"any",a.dtype).reshape(r)},o.prototype.squaredDifference=function(t,e){var n=a().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ca("return (a - b) * (a - b);",t.shape,e.shape):new ba("return (a - b) * (a - b);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.realDivide=function(t,e){if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS")){return this.packedBinaryOp(t,e,"\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n","float32",!0)}var n=new ba("\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;",t.shape,e.shape);return this.compileAndRun(n,[t,e],"float32")},o.prototype.floorDiv=function(t,e){if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    result[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    result[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    result[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    result[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4(result);\n","int32");var n=new ba("\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n",t.shape,e.shape);return this.compileAndRun(n,[t,e],"int32")},o.prototype.add=function(t,e){if("complex64"===t.dtype&&"complex64"===e.dtype)return this.complexSeparableBinaryOp(t,e,ma);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.add(t,e);var n=Ct(t.dtype,e.dtype);if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,ma,n);var r=new ba(ma,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},o.prototype.packedUnaryOp=function(t,e,n){var r=new Fu(t.shape,e);return this.compileAndRun(r,[t],n)},o.prototype.packedBinaryOp=function(t,e,n,r,o){void 0===o&&(o=!1);var a=new Ca(n,t.shape,e.shape,o);return this.compileAndRun(a,[t,e],r)},o.prototype.complexSeparableBinaryOp=function(t,e,n){var r=this,o=this.texData.get(t.dataId),a=this.texData.get(e.dataId),i=[[o.complexTensors.real,a.complexTensors.real],[o.complexTensors.imag,a.complexTensors.imag]].map(function(o){var a=o[0],i=o[1],u=r.makeComplexComponentTensorInfo(t,a),s=r.makeComplexComponentTensorInfo(e,i),c=new ba(n,t.shape,e.shape);return r.compileAndRun(c,[u,s],Ct(a.dtype,i.dtype))}),u=i[0],s=i[1],c=this.complex(u,s);return u.dispose(),s.dispose(),c},o.prototype.makeComplexComponentTensorInfo=function(t,e){return {dataId:e.dataId,dtype:e.dtype,shape:t.shape}},o.prototype.addN=function(t){if(1===t.length)return t[0];if(t.length>a().get("WEBGL_MAX_TEXTURES_IN_SHADER")){var e=Math.floor(t.length/2),n=this.addN(t.slice(0,e)),r=this.addN(t.slice(e));return this.addN([n,r])}var o=t.map(function(t){return t.dtype}).reduce(function(t,e){return Ct(t,e)}),i=t.map(function(t){return t.shape}),u=a().getBool("WEBGL_PACK")?new zo(t[0].shape,i):new Vo(t[0].shape,i);return this.compileAndRun(u,t,o)},o.prototype.subtract=function(t,e){if("complex64"===t.dtype&&"complex64"===e.dtype)return this.complexSeparableBinaryOp(t,e,ga);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.subtract(t,e);var n=Ct(t.dtype,e.dtype);if(a().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,ga,t.dtype);var r=new ba(ga,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},o.prototype.pow=function(t,e){var n=a().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ca("\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new ba("\nif(a < 0.0 && floor(b) < b){\n  return NAN;\n}\nif (b == 0.0) {\n  return 1.0;\n}\nreturn (round(mod(b, 2.0)) != 1) ?\n    pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",t.shape,e.shape),r=Ct(t.dtype,e.dtype);return this.compileAndRun(n,[t,e],r)},o.prototype.ceil=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.ceil(t);if(a().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,vu,t.dtype);var e=new iu(t.shape,vu);return this.compileAndRun(e,[t])},o.prototype.floor=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.floor(t);if(a().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,mu,t.dtype);var e=new iu(t.shape,mu);return this.compileAndRun(e,[t])},o.prototype.sign=function(t){var e=new iu(t.shape,"\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n");return this.compileAndRun(e,[t])},o.prototype.isNaN=function(t){var e=new iu(t.shape,"return float(isnan(x));");return this.compileAndRun(e,[t],"bool")},o.prototype.isInf=function(t){var e=new iu(t.shape,"return float(isinf(x));");return this.compileAndRun(e,[t],"bool")},o.prototype.isFinite=function(t){var e=new iu(t.shape,"return float(!isnan(x) && !isinf(x));");return this.compileAndRun(e,[t],"bool")},o.prototype.round=function(t){var e=new iu(t.shape,"\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n");return this.compileAndRun(e,[t])},o.prototype.exp=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.exp(t);if(a().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,gu,t.dtype);var e=new iu(t.shape,gu);return this.compileAndRun(e,[t])},o.prototype.expm1=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.expm1(t);if(a().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,yu,t.dtype);var e=new iu(t.shape,yu);return this.compileAndRun(e,[t])},o.prototype.log=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.log(t);if(a().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,"\n  vec4 result = log(x);\n  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\n\n  return result;\n",t.dtype);var e=new iu(t.shape,"if (x < 0.0) return NAN;\n  return log(x);");return this.compileAndRun(e,[t])},o.prototype.log1p=function(t){var e=new iu(t.shape,"return log(1.0 + x);");return this.compileAndRun(e,[t])},o.prototype.sqrt=function(t){var e=new iu(t.shape,"return sqrt(x);");return this.compileAndRun(e,[t])},o.prototype.rsqrt=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.rsqrt(t);var e=new iu(t.shape,"return inversesqrt(x);");return this.compileAndRun(e,[t])},o.prototype.reciprocal=function(t){var e=new iu(t.shape,"return 1.0 / x;");return this.compileAndRun(e,[t])},o.prototype.relu=function(t){var e;return e=a().getBool("WEBGL_PACK")?new Fu(t.shape,Du):new iu(t.shape,lu),this.compileAndRun(e,[t])},o.prototype.relu6=function(t){var e;return e=a().getBool("WEBGL_PACK")?new Fu(t.shape,Tu):new iu(t.shape,hu),this.compileAndRun(e,[t])},o.prototype.prelu=function(t,e){var n=a().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ca(wa,t.shape,e.shape):new ba(xa,t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.elu=function(t){if(a().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Nu,t.dtype);var e=new iu(t.shape,fu);return this.compileAndRun(e,[t])},o.prototype.eluDer=function(t,e){var n=a().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ca("\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\n",t.shape,e.shape):new ba("return (b >= 1.0) ? a : a * (b + 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.selu=function(t){var e=new iu(t.shape,pu);return this.compileAndRun(e,[t])},o.prototype.int=function(t){var e=new iu(t.shape,"return float(int(x));");return this.compileAndRun(e,[t],"int32")},o.prototype.clip=function(t,e,n){var r,o=(r=a().getBool("WEBGL_PACK_CLIP")?new Ra(t.shape):new Ea(t.shape)).getCustomSetupFunc(e,n);return this.compileAndRun(r,[t],null,o)},o.prototype.abs=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.abs(t);if(a().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,cu,t.dtype);var e=new iu(t.shape,cu);return this.compileAndRun(e,[t])},o.prototype.complexAbs=function(t){var e=this.texData.get(t.dataId),n=new Ia(t.shape),r=[this.makeComplexComponentTensorInfo(t,e.complexTensors.real),this.makeComplexComponentTensorInfo(t,e.complexTensors.imag)];return this.compileAndRun(n,r)},o.prototype.sigmoid=function(t){var e=new iu(t.shape,"return 1.0 / (1.0 + exp(-1.0 * x));");return this.compileAndRun(e,[t])},o.prototype.softplus=function(t){var e=new iu(t.shape,"\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n");return this.compileAndRun(e,[t])},o.prototype.sin=function(t){var e=new iu(t.shape,xu);return this.compileAndRun(e,[t])},o.prototype.cos=function(t){var e=new iu(t.shape,bu);return this.compileAndRun(e,[t])},o.prototype.tan=function(t){var e=new iu(t.shape,"return tan(x);");return this.compileAndRun(e,[t])},o.prototype.asin=function(t){var e=new iu(t.shape,wu);return this.compileAndRun(e,[t])},o.prototype.acos=function(t){var e=new iu(t.shape,Cu);return this.compileAndRun(e,[t])},o.prototype.atan=function(t){var e=new iu(t.shape,Eu);return this.compileAndRun(e,[t])},o.prototype.atan2=function(t,e){var n=a().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ca("\n  vec4 result = atan(a, b);\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new ba("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return atan(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.sinh=function(t){var e=new iu(t.shape,"\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},o.prototype.cosh=function(t){var e=new iu(t.shape,"\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},o.prototype.tanh=function(t){var e=new iu(t.shape,"\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n");return this.compileAndRun(e,[t])},o.prototype.asinh=function(t){var e=new iu(t.shape,Ru);return this.compileAndRun(e,[t])},o.prototype.acosh=function(t){var e=new iu(t.shape,Iu);return this.compileAndRun(e,[t])},o.prototype.atanh=function(t){var e=new iu(t.shape,ku);return this.compileAndRun(e,[t])},o.prototype.erf=function(t){var e=new iu(t.shape,'\n  // Error function is calculated approximately with elementary function.\n  // See "Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables", Abramowitz and Stegun.\n  float p = 0.3275911;\n  float a1 = 0.254829592;\n  float a2 = -0.284496736;\n  float a3 = 1.421413741;\n  float a4 = -1.453152027;\n  float a5 = 1.061405429;\n\n  float sign = sign(x);\n  x = abs(x);\n  float t = 1.0 / (1.0 + p * x);\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\n');return this.compileAndRun(e,[t])},o.prototype.step=function(t,e){var n=new iu(t.shape,function(t){return void 0===t&&(t=0),uu+"\n    return x > 0.0 ? 1.0 : float("+t+");\n  "}(e));return this.compileAndRun(n,[t])},o.prototype.conv2dByMatMul=function(t,e,n,r,o,i){var u=t.shape,s=this.texData.get(t.dataId),c=n.inChannels,l=u[0]*u[1]*u[2],h=n.outChannels,f="channelsLast"===n.dataFormat,p=(1===l||1===h)&&c>1e3,d=u[2]%2!=0&&!!s.isPacked;if(p||!a().getBool("WEBGL_LAZILY_UNPACK")||!a().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!d){var v=f?u[0]*u[1]*u[2]:u[0]*u[2]*u[3],m=this.reshape(t,[1,v,n.inChannels]),y=this.reshape(e,[1,n.inChannels,n.outChannels]);return this.reshape(this.fusedBatchMatMul({a:m,b:y,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:i}),n.outShape)}var x=f?u[0]*u[1]*(u[2]+1):u[0]*u[2]*(u[3]+1),b={dataId:t.dataId,shape:[1,x,n.inChannels],dtype:t.dtype},w=s.shape;s.shape=s.shape.slice(),s.shape[s.shape.length-2]++,g(ke(s.shape,b.shape),function(){return "packed reshape "+s.shape+" to "+b.shape+" isn't free"});var C=this.reshape(e,[1,n.inChannels,n.outChannels]),E=this.fusedBatchMatMul({a:b,b:C,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:i}),R=this.texData.get(E.dataId);return g(R.isPacked,function(){return "batchMatMul result is expected to be packed"}),s.shape=w,R.shape=n.outShape,Nt.makeTensorFromDataId(E.dataId,n.outShape,E.dtype)},o.prototype.conv2dWithIm2Row=function(t,e,n,r,o,a){var i=n.filterWidth,u=n.filterHeight,s=n.inChannels,c=n.outWidth,l=n.outHeight,h="channelsLast"===n.dataFormat,f=i*u*s,p=l*c,d=[f,p],v=t.squeeze([0]),m=e.reshape([1,f,-1]),g=new Ci(d,v.shape,n),y=this.compileAndRun(g,[v]).reshape([1,d[0],d[1]]),x=null!=r,b=null!=a,w=o?Mu(o,!0):null,C=new Ai(y.shape,[1,p,n.outChannels],!0,!1,x,w,b),E=[y,m];r&&E.push(r),b&&E.push(a);var R=this.compileAndRun(C,E);return h?R.reshape([1,l,c,n.outChannels]):R.reshape([1,n.outChannels,l,c])},o.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,i=t.activation,u=t.preluActivationWeights;if(1===r.filterHeight&&1===r.filterWidth&&1===r.dilationHeight&&1===r.dilationWidth&&1===r.strideHeight&&1===r.strideWidth&&("SAME"===r.padInfo.type||"VALID"===r.padInfo.type))return this.conv2dByMatMul(e,n,r,o,i,u);if(a().getBool("WEBGL_CONV_IM2COL")&&1===e.shape[0])return this.conv2dWithIm2Row(e,n,r,o,i,u);var s=null!=o,c=null!=u,l=i?Mu(i,!1):null,h=new Ma(r,s,l,c),f=[e,n];return o&&f.push(o),u&&f.push(u),this.compileAndRun(h,f)},o.prototype.conv2d=function(t,e,n){if(1===n.filterHeight&&1===n.filterWidth&&1===n.dilationHeight&&1===n.dilationWidth&&1===n.strideHeight&&1===n.strideWidth&&("SAME"===n.padInfo.type||"VALID"===n.padInfo.type))return this.conv2dByMatMul(t,e,n);if(a().getBool("WEBGL_CONV_IM2COL")&&1===t.shape[0])return this.conv2dWithIm2Row(t,e,n);var r=new Ma(n);return this.compileAndRun(r,[t,e])},o.prototype.conv2dDerInput=function(t,e,n){var r=new Ta(n);return this.compileAndRun(r,[t,e])},o.prototype.conv2dDerFilter=function(t,e,n){var r=new Da(n);return this.compileAndRun(r,[t,e])},o.prototype.fusedDepthwiseConv2D=function(t){var e,n=t.input,r=t.filter,o=t.convInfo,i=t.bias,u=t.activation,s=t.preluActivationWeights,c=a().getBool("WEBGL_PACK_DEPTHWISECONV")&&o.strideWidth<=2&&o.outChannels/o.inChannels==1,l=u?Mu(u,c):null,h=[n,r],f=null!=i,p=null!=s;return f&&h.push(i),p&&h.push(s),c?(e=new La(o,f,l,p),this.compileAndRun(e,h)):(e=new Pa(o,f,l,p),this.compileAndRun(e,h))},o.prototype.depthwiseConv2D=function(t,e,n){var r;return a().getBool("WEBGL_PACK_DEPTHWISECONV")&&n.strideWidth<=2&&n.outChannels/n.inChannels==1?(r=new La(n),this.compileAndRun(r,[t,e])):(r=new Pa(n),this.compileAndRun(r,[t,e]))},o.prototype.depthwiseConv2DDerInput=function(t,e,n){var r=new Oa(n);return this.compileAndRun(r,[t,e])},o.prototype.depthwiseConv2DDerFilter=function(t,e,n){var r=new _a(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3d=function(t,e,n){var r=new Ba(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3dDerInput=function(t,e,n){var r=new Fa(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3dDerFilter=function(t,e,n){var r=new Na(n);return this.compileAndRun(r,[t,e])},o.prototype.maxPool=function(t,e){var n=new Oi(e,"max",!1);return this.compileAndRun(n,[t])},o.prototype.avgPool=function(t,e){var n=new Oi(e,"avg",!1);return this.compileAndRun(n,[t],"float32")},o.prototype.maxPoolBackprop=function(t,e,n,r){var o=new Oi(r,"max",!0),a=this.compileAndRun(o,[e]),i=new ki(r),u=this.compileAndRun(i,[t,a],e.dtype);return a.dispose(),u},o.prototype.avgPoolBackprop=function(t,e,n){var r=new ca(n);return this.compileAndRun(r,[t],e.dtype)},o.prototype.cast=function(t,e){return So(t,e,this)},o.prototype.unstack=function(t,e){for(var n=t.shape[e],r=new Array(t.rank-1),o=0,a=0;a<t.rank;a++)a!==e&&(r[o++]=t.shape[a]);var i=new Array(t.rank).fill(0),u=t.shape.slice();u[e]=1;var s=new Array(n);for(a=0;a<s.length;a++)i[e]=a,s[a]=this.slice(t,i,u).reshape(r);return s},o.prototype.avgPool3d=function(t,e){var n=new Mi(e,"avg",!1);return this.compileAndRun(n,[t],"float32")},o.prototype.avgPool3dBackprop=function(t,e,n){var r=new la(n);return this.compileAndRun(r,[t],e.dtype)},o.prototype.maxPool3d=function(t,e){var n=new Mi(e,"max",!1);return this.compileAndRun(n,[t],"float32")},o.prototype.maxPool3dBackprop=function(t,e,n,r){var o=new Mi(r,"max",!0),a=this.compileAndRun(o,[e]),i=new Si(r),u=this.compileAndRun(i,[t,a],e.dtype);return a.dispose(),u},o.prototype.reshape=function(t,e){var n=this.texData.get(t.dataId);if(n.isPacked&&!ke(t.shape,e)&&(null===n.texture||!ke(n.shape,e))){var r=this.packedReshape(t,e);return Nt.makeTensorFromDataId(r.dataId,r.shape,r.dtype)}return Ao(t,e)},o.prototype.resizeBilinear=function(t,e,n,r){var o=a().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Ui(t.shape,e,n,r):new Wi(t.shape,e,n,r);return this.compileAndRun(o,[t],"float32")},o.prototype.resizeBilinearBackprop=function(t,e,n){var r=new Li(t,e,n);return this.compileAndRun(r,[t])},o.prototype.resizeNearestNeighbor=function(t,e,n,r){var o=new zi(t.shape,e,n,r);return this.compileAndRun(o,[t])},o.prototype.resizeNearestNeighborBackprop=function(t,e,n){var r=new Vi(t,e,n);return this.compileAndRun(r,[t])},o.prototype.multinomial=function(t,e,n,r){var o=e?t:io(t),a=o.shape[0],i=o.shape[1],u=new Di(a,i,n),s=u.getCustomSetupFunc(r);return this.compileAndRun(u,[o],"int32",s)},o.prototype.oneHot=function(t,e,n,r){var o=new Ti(t.size,e,n,r);return this.compileAndRun(o,[t])},o.prototype.diag=function(t){var e=new qa(t.size);return this.compileAndRun(e,[t])},o.prototype.nonMaxSuppression=function(t,e,n,r,o){return an("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead"),Mo(t.dataSync(),e.dataSync(),n,r,o)},o.prototype.cropAndResize=function(t,e,n,r,o,a){var i=new Wa(t.shape,e.shape,r,o,a);return this.compileAndRun(i,[t,e,n],"float32")},o.prototype.depthToSpace=function(t,e,n){g(e>1,function(){return "blockSize should be > 1 for depthToSpace, but was: "+e});var r=t.shape[0],o="NHWC"===n?t.shape[1]:t.shape[2],a="NHWC"===n?t.shape[2]:t.shape[3],i="NHWC"===n?t.shape[3]:t.shape[1],u=o*e,s=a*e,c=i/(e*e),l=new Ha("NHWC"===n?[r,u,s,c]:[r,c,u,s],e,n);return this.compileAndRun(l,[t])},o.prototype.split=function(t,e,n){return Po(t,e,n)},o.prototype.scatterND=function(t,e,n){var r=Hr(0,t,n),o=r.sliceRank,a=r.numUpdates,i=r.sliceSize,u=r.strides,s=r.outputSize,c=[s/i,i],l=t.reshape([a,o]),h=e.reshape([a,i]);if(0===s)return Ao(In([]),n);var f=Sn(0),p=new qi(a,o,l.rank,h.rank,u,c);return this.compileAndRun(p,[h,l,f]).reshape(n)},o.prototype.sparseToDense=function(t,e,n,r){var o=Hr(0,t,n),a=o.sliceRank,i=o.numUpdates,u=o.strides,s=o.outputSize,c=new qi(i,a,t.rank,e.rank,u,[s,1],!1);return this.compileAndRun(c,[e,t,r]).reshape(n)},o.prototype.fft=function(t){return this.fftImpl(t,!1)},o.prototype.ifft=function(t){return this.fftImpl(t,!0)},o.prototype.fftImpl=function(t,e){var n=this.texData.get(t.dataId),r=new Ja(Ya,t.shape,e),o=new Ja(Qa,t.shape,e),a=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag)],i=this.compileAndRun(r,a),u=this.compileAndRun(o,a),s=this.complex(i,u).as2D(t.shape[0],t.shape[1]);return i.dispose(),u.dispose(),s},o.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=Ur(t,e),a=o[0],i=o[1],u=o[2],s=o[3],c=e.reshape([i,r]),l=t.reshape([t.size/u,u]),h=new ei(r,s,[i,u]);return this.compileAndRun(h,[l,c]).reshape(a)},o.prototype.fill=function(t,e,n){if("string"===(n=n||z(e))){var r=F(n,w(t));return r.fill(e),Nt.makeTensor(r,t,n,this)}var o=new Za(t,e),a=o.getCustomSetupFunc(e);return this.compileAndRun(o,[],n,a)},o.prototype.onesLike=function(t){if("string"===t.dtype)throw new Error("onesLike is not supported under string dtype");return this.fill(t.shape,1,t.dtype)},o.prototype.zerosLike=function(t){return this.fill(t.shape,"string"===t.dtype?"":0,t.dtype)},o.prototype.linspace=function(t,e,n){return Do(t,e,n)},o.prototype.makeTensorInfo=function(t,e){var n=this.write(null,t,e);return this.texData.get(n).usage=null,{dataId:n,shape:t,dtype:e}},o.prototype.makeOutput=function(t,e){var n=this.makeTensorInfo(t,e).dataId;return Nt.makeTensorFromDataId(n,t,e,this)},o.prototype.unpackTensor=function(t){var e=new _u(t.shape);return this.runWebGLProgram(e,[t],t.dtype)},o.prototype.packTensor=function(t){var e=new Ni(t.shape);return this.runWebGLProgram(e,[t],t.dtype,null,!0)},o.prototype.packedReshape=function(t,e){var n=[we(t.shape)].concat(Ce(t.shape)),r={dtype:t.dtype,shape:n,dataId:t.dataId},o=[we(e)].concat(Ce(e)),a=new Pi(o,n),i=this.runWebGLProgram(a,[r],t.dtype,null,!0);return {dataId:i.dataId,shape:e,dtype:i.dtype}},o.prototype.decode=function(t){var e,n=this.texData.get(t),r=n.isPacked,o=n.shape,a=n.dtype,i=Ee(o);e=r?new Ga(i):new za(i);return {dtype:a,shape:o,dataId:this.runWebGLProgram(e,[{shape:i,dtype:a,dataId:t}],a,null,!0).dataId}},o.prototype.runWebGLProgram=function(t,e,n,r,o){var i=this;void 0===o&&(o=!1);var u=this.makeTensorInfo(t.outputShape,n),s=this.texData.get(u.dataId);if(t.packedOutput&&(s.isPacked=!0),t.outPackingScheme===Ot.DENSE){var c=zt(t.outputShape);s.texShape=c.map(function(t){return 2*t});}if(null!=t.outTexUsage&&(s.usage=t.outTexUsage),0===w(u.shape))return s.values=N(u.dtype,0),u;var l=[],h=e.map(function(e){if("complex64"===e.dtype)throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");var n=i.texData.get(e.dataId);if(null==n.texture){if(!t.packedInputs&&w(e.shape)<=a().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return {shape:e.shape,texData:null,isUniform:!0,uniformValues:n.values};t.packedInputs&&(n.isPacked=!0,n.shape=e.shape);}else if(!!n.isPacked!=!!t.packedInputs)e=n.isPacked?i.unpackTensor(e):i.packTensor(e),l.push(e),n=i.texData.get(e.dataId);else if(n.isPacked&&!ke(n.shape,e.shape)){var r=e,o=e.shape;e.shape=n.shape,e=i.packedReshape(e,o),l.push(e),n=i.texData.get(e.dataId),r.shape=o;}return i.uploadToGPU(e.dataId),{shape:e.shape,texData:n,isUniform:!1}});this.uploadToGPU(u.dataId);var f,p={shape:u.shape,texData:s,isUniform:!1},d=function(t,e,n){var r="";e.concat(n).forEach(function(t){var e=null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0,n=t.isUniform?"uniform":t.texData.texShape;r+=t.shape+"_"+n+"_"+e;});var o=t.userCode,a=t.constructor.name;return 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{program:e,source:c,webGLProgram:l,uniformLocations:p,inShapeInfos:u,outShapeInfo:s,infLoc:h,nanLoc:f}}(i.gpgpu,t,h,p)}),m=null!=this.activeTimers;if(m&&(f=this.startTimer()),function(t,e,n,r,o){wi(e.inShapeInfos,n),wi([e.outShapeInfo],[r]);var i=r.texData.texture,u=r.texData.texShape;r.texData.isPacked?t.setOutputPackedMatrixTexture(i,u[0],u[1]):t.setOutputMatrixTexture(i,u[0],u[1]),t.setProgram(e.webGLProgram),1===a().getNumber("WEBGL_VERSION")&&null!==e.infLoc&&t.gl.uniform1f(e.infLoc,1/0),null!==e.nanLoc&&t.gl.uniform1f(e.nanLoc,NaN),n.forEach(function(n,r){var o=e.program.variableNames[r],a=e.uniformLocations[o],i=e.uniformLocations["offset"+o];if(null!=a)if(n.isUniform)if(w(n.shape)<2)t.gl.uniform1f(a,n.uniformValues[0]);else{var u=n.uniformValues;u instanceof Float32Array||(u=new Float32Array(u)),t.gl.uniform1fv(a,u);}else 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g=this.makeTensorInfo([v,d],o);this.texData.get(g.dataId).usage=m?Mt.PIXELS:Mt.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId),d,v,a);var y=this.runWebGLProgram(p,[g],o,null,!0),x=this.texData.get(y.dataId);n.texture=x.texture,n.texShape=x.texShape,n.isPacked=x.isPacked,n.usage=x.usage,this.disposeData(g.dataId),this.texData.delete(y.dataId),n.values=null,l&&(this.uploadWaitMs+=Y()-c);}else{var b=this.acquireTexture(h,u,o,s);n.texture=b;}}},o.prototype.convertAndCacheOnCPU=function(t,e){var n=this.texData.get(t),r=n.dtype;return this.releaseGPUData(t),null!=e&&(n.values=function(t,e){if("float32"===e||"complex64"===e)return t;if("int32"===e||"bool"===e){for(var n="int32"===e?new Int32Array(t.length):new Uint8Array(t.length),r=0;r<n.length;++r)n[r]=Math.round(t[r]);return n}throw new Error("Unknown dtype 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l=yo(a,n.shape,r,1,o),h=Nt.runKernelFunc(function(t){return t.conv3dDerInput(i,n,l)},{dy5D:i});return u?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}var Sc=wn({conv1d_:function(t,e,n,r,o,a,i){void 0===o&&(o="NWC"),void 0===a&&(a=1);var u=cn(t,"x","conv1d"),s=cn(e,"filter","conv1d"),c=u,l=!1;2===u.rank&&(l=!0,c=u.as3D(1,u.shape[0],u.shape[1])),g(3===c.rank,function(){return "Error in conv1d: input must be rank 3, but got rank "+c.rank+"."}),g(3===s.rank,function(){return "Error in conv1d: filter must be rank 3, but got rank "+s.rank+"."}),null!=i&&g(E(r),function(){return "Error in conv1d: pad must be an integer when using, dimRoundingMode "+i+" but got pad "+r+"."}),g(c.shape[2]===s.shape[1],function(){return "Error in conv1d: depth of input ("+c.shape[2]+") must match input depth for filter "+s.shape[1]+"."}),g(Io(n,a),function(){return "Error in conv1D: Either stride or dilation must be 1. 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Got dilations '"+a+"'"});var n=e[0],r=e[1];return {x:function(){return _c(n.shape,t,r,h)},filter:function(){return Oc(n,t,r.shape,h)}}},"DepthwiseConv2dNative",h,f);return l?p.as3D(p.shape[1],p.shape[2],p.shape[3]):p}}),_c=wn({depthwiseConv2dDerInput_:function(t,e,n,r){var o=e,a=!1;3===e.rank&&(a=!0,o=e.as4D(1,e.shape[0],e.shape[1],e.shape[2]));var i=Nt.runKernelFunc(function(t){return t.depthwiseConv2DDerInput(o,n,r)},{dy4D:o});return a?i.as3D(i.shape[1],i.shape[2],i.shape[3]):i}}),Oc=wn({depthwiseConv2dDerFilter_:function(t,e,n,r){var o=t;3===t.rank&&(o=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var a=e;return 3===a.rank&&(a=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),Nt.runKernelFunc(function(t){return t.depthwiseConv2DDerFilter(o,a,r)},{x4D:o,dy4D:a})}}),Mc=wn({separableConv2d_:function(t,e,n,r,o,a,i){void 0===a&&(a=[1,1]),void 0===i&&(i="NHWC");var u=cn(t,"x","separableConv2d"),s=cn(e,"depthwiseFilter","separableConv2d"),c=cn(n,"pointwiseFilter","separableConv2d"),l=u,h=!1;if(3===u.rank&&(h=!0,l=u.as4D(1,u.shape[0],u.shape[1],u.shape[2])),"NCHW"===i)throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");g(4===l.rank,function(){return "Error in separableConv2d: input must be rank 4, but got rank "+l.rank+"."}),g(4===s.rank,function(){return "Error in separableConv2d: depthwise filter must be rank 4, but got rank "+s.rank+"."}),g(4===c.rank,function(){return "Error in separableConv2d: pointwise filter must be rank 4, but got rank "+s.rank+"."}),g(1===c.shape[0],function(){return "Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got "+c.shape[0]+"."}),g(1===c.shape[1],function(){return "Error in separableConv2d: the second dimension of pointwise filter must be 1, but got "+c.shape[1]+"."});var f=s.shape[2],p=s.shape[3];g(c.shape[2]===f*p,function(){return "Error in separableConv2d: the third dimension of pointwise filter must be "+f*p+", but got "+c.shape[2]+"."});var d=Fc(l,s,r,o,i,a),v=Ac(d,c,1,"valid",i);return h?v.as3D(v.shape[1],v.shape[2],v.shape[3]):v}}),Bc=wn({conv2dTranspose_:function(t,e,n,r,o,a){return Rc(n,cn(t,"x","conv2dTranspose"),cn(e,"filter","conv2dTranspose"),r,o,"NHWC",a)}}),Pc=wn({conv3dTranspose_:function(t,e,n,r,o){return kc(n,cn(t,"x","conv3dTranspose"),cn(e,"filter","conv3dTranspose"),r,o)}});var Lc=wn({matMul_:function(t,e,n,r){var o;void 0===n&&(n=!1),void 0===r&&(r=!1);var a=cn(t,"a","matMul"),i=cn(e,"b","matMul");o=Rt(a,i),a=o[0],i=o[1];var u=n?a.shape[a.rank-2]:a.shape[a.rank-1],s=r?i.shape[i.rank-1]:i.shape[i.rank-2],c=n?a.shape[a.rank-1]:a.shape[a.rank-2],l=r?i.shape[i.rank-2]:i.shape[i.rank-1],h=a.shape.slice(0,-2),f=i.shape.slice(0,-2),p=w(h),d=w(f);g(a.rank>=2&&i.rank>=2&&a.rank===i.rank,function(){return "Error in matMul: inputs must have the same rank of at least 2, got ranks "+a.rank+" and "+i.rank+"."}),g(C(h,f),function(){return "Error in matMul: outer dimensions ("+h+") and ("+f+") of Tensors with shapes "+a.shape+" and "+i.shape+" must match."}),g(u===s,function(){return "Error in matMul: inner shapes ("+u+") and ("+s+") of Tensors with shapes "+a.shape+" and "+i.shape+" and transposeA="+n+" and transposeB="+r+" must match."});var v=a.shape.slice(0,-2).concat([c,l]),m=n?a.as3D(p,u,c):a.as3D(p,c,u),y=r?i.as3D(d,l,s):i.as3D(d,s,l),x={transposeA:n,transposeB:r};return Nt.runKernelFunc(function(t,e){var o=t.batchMatMul(m,y,n,r);return e([m,y]),o},{a:m,b:y},function(t,e){var o=e,a=o[0],i=o[1];return n||r?!n&&r?{a:function(){return t.matMul(i,!1,!1)},b:function(){return t.matMul(a,!0,!1)}}:n&&!r?{a:function(){return i.matMul(t,!1,!0)},b:function(){return a.matMul(t,!1,!1)}}:{a:function(){return i.matMul(t,!0,!0)},b:function(){return t.matMul(a,!0,!0)}}:{a:function(){return t.matMul(i,!1,!0)},b:function(){return a.matMul(t,!0,!1)}}},"BatchMatMul",x).reshape(v)}}),Wc=wn({dot_:function(t,e){var n=cn(t,"t1","dot"),r=cn(e,"t2","dot");g(!(1!==n.rank&&2!==n.rank||1!==r.rank&&2!==r.rank),function(){return "Error in dot: inputs must all be rank 1 or 2, but got ranks "+n.rank+" and "+r.rank+"."});var o=1===n.rank?n.size:n.shape[1],a=1===r.rank?r.size:r.shape[0];return g(o===a,function(){return "Error in dot: inner dimensions of inputs must match, but got "+o+" and "+a+"."}),1===n.rank&&1===r.rank?n.as2D(1,-1).matMul(r.as2D(-1,1)).asScalar():1===n.rank&&2===r.rank?n.as2D(1,-1).matMul(r.as2D(r.shape[0],r.shape[1])).as1D():2===n.rank&&1===r.rank?n.matMul(r.as2D(-1,1)).as1D():n.matMul(r.as2D(r.shape[0],r.shape[1]))}}),Uc=wn({outerProduct_:function(t,e){var n=cn(t,"v1","outerProduct"),r=cn(e,"v2","outerProduct");return g(1===n.rank&&1===r.rank,function(){return "Error in outerProduct: inputs must be rank 1, but got ranks "+n.rank+" and "+r.rank+"."}),n.as2D(-1,1).matMul(r.as2D(1,-1))}});var Vc=wn({reverse_:function(t,e){var n=cn(t,"x","reverse");if(0===n.rank)return n.clone();var r=D(e,n.shape);return Nt.runKernelFunc(function(t){return t.reverse(n,r)},{$x:n},function(t){return {$x:function(){return t.reverse(r)}}}).reshapeAs(n)}}),zc=wn({reverse1d_:function(t){var e=cn(t,"x","reverse");return g(1===e.rank,function(){return "Error in reverse1D: x must be rank 1 but got rank "+e.rank+"."}),Vc(e,0)}}),Gc=wn({reverse2d_:function(t,e){var n=cn(t,"x","reverse");return g(2===n.rank,function(){return "Error in reverse2D: x must be rank 2 but got rank "+n.rank+"."}),Vc(n,e)}}),Hc=wn({reverse3d_:function(t,e){var n=cn(t,"x","reverse");return g(3===n.rank,function(){return "Error in reverse3D: x must be rank 3 but got rank "+n.rank+"."}),Vc(n,e)}}),qc=wn({reverse4d_:function(t,e){var n=cn(t,"x","reverse");return g(4===n.rank,function(){return "Error in reverse4D: x must be rank 4 but got rank "+n.rank+"."}),Vc(n,e)}});function Kc(t,e,n,r,o,a){var i=cn(t,"x","maxPool"),u=i,s=!1;3===i.rank&&(s=!0,u=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),null==r&&(r=[1,1]),g(4===u.rank,function(){return "Error in maxPool: input must be rank 4 but got rank "+u.rank+"."}),g(Io(n,r),function(){return "Error in maxPool: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+r+"'"}),null!=a&&g(E(o),function(){return "Error in maxPool: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+o+"."});var c=vo(u.shape,e,n,r,o,a);if(1===c.filterWidth&&1===c.filterHeight&&C(c.inShape,c.outShape))return i.clone();var l=[u],h=Nt.runKernelFunc(function(t,e){var n=t.maxPool(u,c);return e([u,n]),n},{x:u},function(t,a){var i=a[0],u=a[1];return {x:function(){return function(t,e,n,r,o,a,i,u){var s=cn(t,"dy","maxPoolBackprop"),c=cn(e,"input","maxPoolBackprop"),l=cn(n,"output","maxPoolBackprop");g(c.rank===s.rank,function(){return "Rank of input ("+c.rank+") does not match rank of dy ("+s.rank+")"}),null==a&&(a=[1,1]),g(Io(o,a),function(){return "Error in maxPoolBackProp: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+a+"'"}),g(4===s.rank,function(){return "Error in maxPoolBackprop: dy must be rank 4 but got rank "+s.rank+"."}),g(4===c.rank,function(){return "Error in maxPoolBackprop: input must be rank 4 but got rank "+c.rank+"."}),null!=u&&g(E(i),function(){return "Error in maxPoolBackprop: pad must be an integer when using, dimRoundingMode "+u+" but got pad "+i+"."});var h=vo(c.shape,r,o,a,i,u);return Nt.runKernelFunc(function(t){return t.maxPoolBackprop(s,c,l,h)},{$dy:s,$input:c})}(t,i,u,e,n,r,o)}}},"MaxPool",c,l);return s?h.as3D(h.shape[1],h.shape[2],h.shape[3]):h}function jc(t,e,n,r,o,a){var i=cn(t,"x","avgPool","float32");null==r&&(r=[1,1]),g(Io(n,r),function(){return "Error in avgPool: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+r+"'"});var u=i,s=!1;3===i.rank&&(s=!0,u=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),g(4===u.rank,function(){return "Error in avgPool: x must be rank 4 but got rank "+u.rank+"."}),null!=a&&g(E(o),function(){return "Error in avgPool: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+o+"."});var c=vo(u.shape,e,n,r,o,a);if(1===c.filterWidth&&1===c.filterHeight&&C(c.inShape,c.outShape))return i.clone();var l=Nt.runKernelFunc(function(t){return t.avgPool(u,c)},{x:u},function(t){return {x:function(){return function(t,e,n,r,o,a){var i=cn(t,"dy","avgPoolBackprop"),u=cn(e,"input","avgPoolBackprop");g(u.rank===i.rank,function(){return "Rank of input ("+u.rank+") does not match rank of dy ("+i.rank+")"}),null==o&&(o=[1,1]),g(Io(r,o),function(){return "Error in avgPoolBackprop: Either strides or dilations must be 1. Got strides "+r+" and dilations '"+o+"'"});var s=u,c=i,l=!1;3===u.rank&&(l=!0,s=u.as4D(1,u.shape[0],u.shape[1],u.shape[2]),c=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),g(4===c.rank,function(){return "Error in avgPoolBackprop: dy must be rank 4 but got rank "+c.rank+"."}),g(4===s.rank,function(){return "Error in avgPoolBackprop: input must be rank 4 but got rank "+s.rank+"."});var h=vo(s.shape,n,r,o,a),f=Nt.runKernelFunc(function(t){return t.avgPoolBackprop(c,s,h)},{dy4D:c,input4D:s});return l?f.as3D(f.shape[1],f.shape[2],f.shape[3]):f}(t,u,e,n,r,o)}}},"AvgPool",c);return l=l.cast(i.dtype),s?l.as3D(l.shape[1],l.shape[2],l.shape[3]):l}var Xc=wn({maxPool_:function(t,e,n,r,o){return Kc(t,e,n,1,r,o)}}),$c=wn({avgPool_:function(t,e,n,r,o){return jc(t,e,n,1,r,o)}}),Yc=wn({pool_:function(t,e,n,r,o,a){null==o&&(o=[1,1]),null==a&&(a=1),0===r&&(r="valid");var i=cn(t,"x","maxPool"),u=i,s=!1;3===i.rank&&(s=!0,u=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),g(Io(a,o),function(){return "Error in pool: Either strides or dilations must be 1. Got strides "+a+" and dilations '"+o+"'"});var c,l=vo(u.shape,e,a,o,r),h=[l.dilationHeight,l.dilationWidth];c="same"===r?function(t,e){var n=t.map(function(t,n){return t+(t-1)*(e[n]-1)}).map(function(t){return t-1}),r=n.map(function(t){return Math.floor(t/2)}),o=n.map(function(t,e){return t-r[e]});return n.map(function(t,e){return [r[e],o[e]]})}([l.filterHeight,l.filterWidth],h):[[0,0],[0,0]];var f=1===h[0]&&1===h[1],p=function(t,e,n){var r=n.map(function(t){return t[0]}),o=n.map(function(t){return t[1]}),a=t.concat(r,o),i=e.map(function(t,e){return (t-a[e]%t)%t}),u=o.map(function(t,e){return t+i[e]}),s=e.map(function(t,e){return [r[e],u[e]]}),c=e.map(function(t,e){return [0,i[e]]});return [s,c]}([l.inHeight,l.inWidth],h,c),d=p[0],v=p[1],m=f?r:"valid",y=f?u:Ar(u,h,d),x=("avg"===n?function(){return jc(y,e,a,1,m)}:function(){return Kc(y,e,a,1,m)})(),b=f?x:sr(x,h,v);return s?b.as3D(b.shape[1],b.shape[2],b.shape[3]):b}}),Qc=wn({maxPool3d_:function(t,e,n,r,o,a,i){void 0===a&&(a="NDHWC");var u=cn(t,"x","maxPool3d"),s=u,c=!1;4===u.rank&&(c=!0,s=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3])),null==i&&(i=[1,1,1]),g(5===s.rank,function(){return "Error in maxPool3d: x must be rank 5 but got rank "+s.rank+"."}),g("NDHWC"===a,function(){return "Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of "+a}),g(Io(n,i),function(){return "Error in maxPool3d: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+i+"'"}),null!=o&&g(E(r),function(){return "Error in maxPool3d: pad must be an integer when using, dimRoundingMode "+o+" but got pad "+r+"."});var l=mo(s.shape,e,n,i,r,o,a),h=Nt.runKernelFunc(function(t,e){var n=t.maxPool3d(s,l);return e([s,n]),n},{x:s},function(t,a){var u=a[0],s=a[1];return {x:function(){return function(t,e,n,r,o,a,i,u){var s=cn(t,"dy","maxPool3dBackprop"),c=cn(e,"input","maxPool3dBackprop"),l=cn(n,"output","maxPool3dBackprop"),h=s,f=c,p=l,d=!1;4===c.rank&&(d=!0,h=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3]),f=c.as5D(1,c.shape[0],c.shape[1],c.shape[2],c.shape[3]),p=l.as5D(1,l.shape[0],l.shape[1],l.shape[2],l.shape[3])),g(5===h.rank,function(){return "Error in maxPool3dBackprop: dy must be rank 5 but got rank "+h.rank+"."}),g(5===f.rank,function(){return "Error in maxPool3dBackprop: input must be rank 5 but got rank "+f.rank+"."}),g(5===p.rank,function(){return "Error in maxPool3dBackprop: output must be rank 5 but got rank "+p.rank+"."}),null==a&&(a=[1,1,1]),g(Io(o,a),function(){return "Error in maxPool3dBackprop: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+a+"'"}),null!=u&&g(E(i),function(){return "Error in maxPool3dBackprop: pad must be an integer when using, dimRoundingMode "+u+" but got pad "+i+"."});var v=mo(f.shape,r,o,a,i,u),m=Nt.runKernelFunc(function(t){return t.maxPool3dBackprop(h,f,p,v)},{dy5D:h,input5D:f});return d?m.as4D(m.shape[1],m.shape[2],m.shape[3],m.shape[4]):m}(t,u,s,e,n,i,r,o)}}});return c?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}}),Jc=wn({avgPool3d_:function(t,e,n,r,o,a,i){void 0===a&&(a="NDHWC");var u=cn(t,"x","avgPool3d","float32"),s=u,c=!1;4===u.rank&&(c=!0,s=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3])),null==i&&(i=[1,1,1]),g(5===s.rank,function(){return "Error in avgPool3d: x must be rank 5 but got rank "+s.rank+"."}),g("NDHWC"===a,function(){return "Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of "+a}),g(Io(n,i),function(){return "Error in avgPool3d: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+i+"'"}),null!=o&&g(E(r),function(){return "Error in avgPool3d: pad must be an integer when using, dimRoundingMode "+o+" but got pad "+r+"."});var l=mo(s.shape,e,n,i,r,o,a),h=Nt.runKernelFunc(function(t){return t.avgPool3d(s,l)},{x:s},function(t){return {x:function(){return function(t,e,n,r,o,a,i){var u=cn(t,"dy","avgPool3dBackprop"),s=cn(e,"input","avgPool3dBackprop"),c=u,l=s,h=!1;4===s.rank&&(h=!0,c=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]),l=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3])),g(5===c.rank,function(){return "Error in avgPool3dBackprop: dy must be rank 5 but got rank "+c.rank+"."}),g(5===l.rank,function(){return "Error in avgPool3dBackprop: input must be rank 5 but got rank "+l.rank+"."}),null==o&&(o=[1,1,1]),g(Io(r,o),function(){return "Error in avgPool3dBackprop: Either strides or dilations must be 1. Got strides "+r+" and dilations '"+o+"'"}),null!=i&&g(E(a),function(){return "Error in maxPool3dBackprop: pad must be an integer when using, dimRoundingMode "+i+" but got pad "+a+"."});var f=mo(l.shape,n,r,o,a,i),p=Nt.runKernelFunc(function(t){return t.avgPool3dBackprop(c,l,f)},{dy5D:c,input5D:l});return h?p.as4D(p.shape[1],p.shape[2],p.shape[3],p.shape[4]):p}(t,s,e,n,i,r,o)}}});return h=h.cast(s.dtype),c?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}});var Zc=wn({slice_:function(t,e,n){var r,o,a=cn(t,"x","slice");if(0===a.rank)throw new Error("Slicing scalar is not possible");(r="number"==typeof e?[e].concat(new Array(a.rank-1).fill(0)):e.length<a.rank?e.concat(new Array(a.rank-e.length).fill(0)):e.slice()).forEach(function(t){g(-1!==t,function(){return "slice() does not support negative begin indexing."});}),o=(o=null==n?new Array(a.rank).fill(-1):"number"==typeof n?[n].concat(new Array(a.rank-1).fill(-1)):n.length<a.rank?n.concat(new 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h=function(t,e){var n=cn(t,"labels","sigmoidCrossEntropyWithLogits"),r=cn(e,"logits","sigmoidCrossEntropyWithLogits");y(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");var o=r.relu(),a=r.mul(n),i=r.abs().neg().exp().log1p();return o.sub(a).add(i)}(a,i);return $l(h,u,o)}}),nh=wn({softmaxCrossEntropy_:function(t,e,n,r,o){void 0===r&&(r=0),void 0===o&&(o=Kl.SUM_BY_NONZERO_WEIGHTS);var a=cn(t,"onehotLabels","softmaxCrossEntropy"),i=cn(e,"logits","softmaxCrossEntropy"),u=null;if(null!=n&&(u=cn(n,"weights","softmaxCrossEntropy")),y(a.shape,i.shape,"Error in softmaxCrossEntropy: "),r>0){var s=Sn(r),c=Sn(1),l=Sn(a.shape[1]);a=a.mul(c.sub(s)).add(s.div(l));}var h=function(t,e,n){if(void 0===n&&(n=-1),-1===n&&(n=e.rank-1),n!==e.rank-1)throw Error("Softmax cross entropy along a non-last dimension is not yet supported. 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resizeNearestNeighbor: x must be rank 3 or 4, but got rank "+r.rank+"."}),g(2===e.length,function(){return "Error in resizeNearestNeighbor: new shape must 2D, but got shape "+e+"."}),g("float32"===r.dtype||"int32"===r.dtype,function(){return "`images` must have `int32` or `float32` as dtype"});var o=r,a=!1;3===r.rank&&(a=!0,o=r.as4D(1,r.shape[0],r.shape[1],r.shape[2]));var i=e[0],u=e[1],s=Nt.runKernelFunc(function(t,e){return e([o]),t.resizeNearestNeighbor(o,i,u,n)},{batchImages:o},function(t,e){return {batchImages:function(){return Nt.runKernelFunc(function(r){return r.resizeNearestNeighborBackprop(t,e[0],n)},{})}}});return a?s.as3D(s.shape[1],s.shape[2],s.shape[3]):s}}),fh=wn({nonMaxSuppression_:function(t,e,n,r,o){void 0===r&&(r=.5),void 0===o&&(o=Number.NEGATIVE_INFINITY);var a=cn(t,"boxes","nonMaxSuppression"),i=cn(e,"scores","nonMaxSuppression"),u=ch(a,i,n,r,o);n=u.maxOutputSize,r=u.iouThreshold,o=u.scoreThreshold;var s={maxOutputSize:n,iouThreshold:r,scoreThreshold:o};return Nt.runKernelFunc(function(t){return t.nonMaxSuppression(a,i,n,r,o)},{boxes:a,scores:i},null,"NonMaxSuppressionV3",s)}}),ph=function(t,e,o,a,i){return void 0===a&&(a=.5),void 0===i&&(i=Number.NEGATIVE_INFINITY),n(this,void 0,void 0,function(){var n,u,s,c,l,h,f;return r(this,function(r){switch(r.label){case 0:return n=cn(t,"boxes","nonMaxSuppressionAsync"),u=cn(e,"scores","nonMaxSuppressionAsync"),s=ch(n,u,o,a,i),o=s.maxOutputSize,a=s.iouThreshold,i=s.scoreThreshold,[4,Promise.all([n.data(),u.data()])];case 1:return c=r.sent(),l=c[0],h=c[1],f=Mo(l,h,o,a,i),n!==t&&n.dispose(),u!==e&&u.dispose(),[2,f]}})})},dh=wn({cropAndResize_:function(t,e,n,r,o,a){var i=cn(t,"image","cropAndResize"),u=cn(e,"boxes","cropAndResize","float32"),s=cn(n,"boxInd","cropAndResize","int32");o=o||"bilinear",a=a||0;var c=u.shape[0];return g(4===i.rank,function(){return "Error in cropAndResize: image must be rank 4,but got rank "+i.rank+"."}),g(2===u.rank&&4===u.shape[1],function(){return "Error in cropAndResize: boxes must be have size ["+c+",4] but had shape "+u.shape+"."}),g(1===s.rank&&s.shape[0]===c,function(){return "Error in cropAndResize: boxInd must be have size ["+c+"] but had shape "+u.shape+"."}),g(2===r.length,function(){return "Error in cropAndResize: cropSize must be of length 2, but got length "+r.length+"."}),g(r[0]>=1&&r[1]>=1,function(){return "cropSize must be atleast [1,1], but was "+r}),g("bilinear"===o||"nearest"===o,function(){return "method must be bilinear or nearest, but was "+o}),Nt.runKernelFunc(function(t,e){return t.cropAndResize(i,u,s,r,o,a)},{images:i,boxes:u,boxInd:s},null,"CropAndResize",{method:o,extrapolationValue:a,cropSize:r})}}),vh=Object.freeze({resizeBilinear:lh,resizeNearestNeighbor:hh,nonMaxSuppression:fh,nonMaxSuppressionAsync:ph,cropAndResize:dh}),mh=function(t,e){return !(t>0)||"linear"===e},gh=function(t,e,n){if(null==n||"linear"===n)return t;if("relu"===n)return t.mul(e.step());throw new Error("Gradient for activation "+n+" has not been implemented yet.")},yh=function(t,e){var n=e,r=fo(t.shape,e.shape);return r.length>0&&(n=n.sum(r)),n.reshape(t.shape)},xh=function(t,e,n){if("linear"===e)return t;if("relu"===e)return xl(t);if("elu"===e)return ml(t);if("relu6"===e)return bl(t);if("prelu"===e)return yl(t,n);throw new Error("Unknown fused activation "+e+".")};var bh=wn({fusedMatMul_:function(t){var e,n=t.a,r=t.b,o=t.transposeA,a=void 0!==o&&o,i=t.transposeB,u=void 0!==i&&i,s=t.bias,c=t.activation,l=void 0===c?"linear":c,h=t.preluActivationWeights;if(!1===mh(Nt.state.gradientDepth,l)){var f=Lc(n,r,a,u);return null!=s&&(f=Ws(f,s)),xh(f,l,h)}var p=cn(n,"a","fused matMul"),d=cn(r,"b","fused matMul");e=Rt(p,d),p=e[0],d=e[1];var v=a?p.shape[p.rank-2]:p.shape[p.rank-1],m=u?d.shape[d.rank-1]:d.shape[d.rank-2],y=a?p.shape[p.rank-1]:p.shape[p.rank-2],x=u?d.shape[d.rank-2]:d.shape[d.rank-1],b=p.shape.slice(0,-2),E=d.shape.slice(0,-2),R=w(b),I=w(E);g(p.rank>=2&&d.rank>=2&&p.rank===d.rank,function(){return "Error in fused matMul: 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e.readSync(t.dataId)}),r=ir(t[0].shape,t[0].dtype),o=r.values,a=0;a<t.length;a++)for(var i=n[a],u=0;u<o.length;u++)o[u]+=i[u];return r.toTensor()},o.prototype.subtract=function(t,e){return "complex64"===t.dtype||"complex64"===e.dtype?this.broadcastedBinaryComplexOp(t.cast("complex64"),e.cast("complex64"),function(t,e,n,r){return {real:t-n,imag:e-r}}):this.broadcastedBinaryOp(t,e,Ct(t.dtype,e.dtype),function(t,e){return t-e})},o.prototype.pow=function(t,e){return Ih([t,e],"pow"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.pow(t,e)})},o.prototype.batchMatMul=function(t,e,n,r){Ih([t,e],"matMul");for(var o=n?t.shape[1]:t.shape[2],a=n?t.shape[2]:t.shape[1],i=r?e.shape[1]:e.shape[2],u=t.shape[0],s=this.readSync(t.dataId),c=this.readSync(e.dataId),l=n?[t.strides[0],1,t.strides[1]]:[t.strides[0],t.strides[1],1],h=l[0],f=l[1],p=l[2],d=r?[1,e.strides[1],e.strides[0]]:[e.strides[1],1,e.strides[0]],v=d[0],m=d[1],g=d[2],y=a*i,x=ir([u,a,i],t.dtype),b=x.values,w=this.blockSize,C=0;C<u;C++)for(var E=0;E<a;E+=w)for(var R=0;R<i;R+=w)for(var I=0;I<o;I+=w)for(var k=Math.min(E+w,a),S=Math.min(R+w,i),A=Math.min(I+w,o),D=E;D<k;D++)for(var T=R;T<S;T++){for(var N=0,F=I;F<A;F++)N+=s[C*h+D*f+F*p]*c[F*v+T*m+C*g];b[C*y+(D*i+T)]+=N;}return x.toTensor()},o.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,a=t.bias,i=t.activation,u=t.preluActivationWeights,s=this.batchMatMul(e,n,r,o);return a&&(s=this.add(s,a)),i&&(s=kh(this,s,i,u)),s},o.prototype.multiply=function(t,e){return "complex64"===t.dtype||"complex64"===e.dtype?this.broadcastedBinaryComplexOp(t.cast("complex64"),e.cast("complex64"),function(t,e,n,r){return {real:t*n-e*r,imag:t*r+e*n}}):this.broadcastedBinaryOp(t,e,Ct(t.dtype,e.dtype),function(t,e){return t*e})},o.prototype.realDivide=function(t,e){Ih([t,e],"realDivide");return this.broadcastedBinaryOp(t,e,"float32",function(t,e){return t/e})},o.prototype.floorDiv=function(t,e){Ih([t,e],"floorDiv");return this.broadcastedBinaryOp(t,e,"int32",function(t,e){return Math.floor(t/e)})},o.prototype.sum=function(t,e){Ih(t,"sum"),vn("sum",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,Ct(t.dtype,"int32")),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=0,f=0;f<i;++f)h+=s[l+f];u[c]=h;}return a},o.prototype.prod=function(t,e){Ih(t,"sum");for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,Ct(t.dtype,"int32")),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=1,f=0;f<i;++f)h*=s[l+f];u[c]=h;}return a},o.prototype.unsortedSegmentSum=function(t,e,n){Ih(t,"unsortedSegmentSum");for(var r=[],o=t.rank-e.rank,a=0;a<o;++a)e=e.expandDims(a+1);for(a=0;a<n;++a){var i=Sn(a,"int32"),u=uc(i,e).asType("float32").mul(t).sum(0);r.push(u);}return Tr(r)},o.prototype.argMin=function(t,e){Ih(t,"argMin");var n=[e];vn("argMin",n,t.rank);for(var r=pn(t.shape,n),o=r[0],a=r[1],i=Bn(o,"int32"),u=w(a),s=this.readSync(i.dataId),c=this.readSync(t.dataId),l=0;l<s.length;++l){for(var h=l*u,f=c[h],p=0,d=0;d<u;++d){var v=c[h+d];v<f&&(f=v,p=d);}s[l]=p;}return i},o.prototype.argMax=function(t,e){Ih(t,"argMax");var n=[e];vn("argMax",n,t.rank);for(var r=pn(t.shape,n),o=r[0],a=r[1],i=Bn(o,"int32"),u=w(a),s=this.readSync(i.dataId),c=this.readSync(t.dataId),l=0;l<s.length;++l){for(var h=l*u,f=c[h],p=0,d=0;d<u;++d){var v=c[h+d];v>f&&(f=v,p=d);}s[l]=p;}return i},o.prototype.cumsum=function(t,e,n,r){if(Ih(t,"cumsum"),e!==t.rank-1)throw new Error("backend.cumsum in CPU expects an inner-most axis="+(t.rank-1)+" but got axis="+e);for(var o=Ct(t.dtype,"int32"),a=Bn(t.shape,o),i=this.readSync(a.dataId),u=this.readSync(t.dataId),s=t.shape[t.rank-1],c=r?function(t,e){return t+s-e-1}:function(t,e){return t+e},l=0;l<u.length;l+=s)for(var h=0;h<s;h++){var f=c(l,h);if(0===h)i[f]=n?0:u[f];else{var p=c(l,h-1);i[f]=n?u[p]+i[p]:u[f]+i[p];}}return a},o.prototype.equal=function(t,e){return Ih([t,e],"equal"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t===e?1:0})},o.prototype.notEqual=function(t,e){return Ih([t,e],"notEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t!==e?1:0})},o.prototype.less=function(t,e){return Ih([t,e],"less"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t<e?1:0})},o.prototype.lessEqual=function(t,e){return Ih([t,e],"lessEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t<=e?1:0})},o.prototype.greater=function(t,e){return Ih([t,e],"greater"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t>e?1:0})},o.prototype.greaterEqual=function(t,e){return Ih([t,e],"greaterEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t>=e?1:0})},o.prototype.logicalNot=function(t){Ih(t,"logicalNot");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)n[r]=e[r]?0:1;return this.makeOutput(n,t.shape,"bool")},o.prototype.logicalAnd=function(t,e){return Ih([t,e],"logicalAnd"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t&&e})},o.prototype.logicalOr=function(t,e){return Ih([t,e],"logicalOr"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t||e})},o.prototype.select=function(t,e,n){Ih([t,e,n],"select");for(var r=this.readSync(t.dataId),o=this.readSync(e.dataId),a=this.readSync(n.dataId),i=Bn(e.shape,Ct(e.dtype,n.dtype)),u=this.readSync(i.dataId),s=0,c=0===t.rank||t.rank>1||1===e.rank?1:w(e.shape.slice(1)),l=0;l<r.length;l++)for(var h=0;h<c;h++)1===r[l]?u[s++]=o[l]:u[s++]=a[l];return i},o.prototype.where=function(t){Ih([t],"where");var e=this.readSync(t.dataId);return Uo(t.shape,e)},o.prototype.topk=function(t,e,n){return Ih(t,"topk"),Wo(this.readSync(t.dataId),t.shape,t.dtype,e)},o.prototype.min=function(t,e){Ih(t,"min"),vn("min",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,t.dtype),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=s[l],f=0;f<i;++f){var p=s[l+f];p<h&&(h=p);}u[c]=h;}return a},o.prototype.minimum=function(t,e){return Ih([t,e],"minimum"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.min(t,e)})},o.prototype.mod=function(t,e){return Ih([t,e],"mod"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var n=t%e;return t<0&&e<0||t>=0&&e>=0?n:(n+e)%e})},o.prototype.max=function(t,e){Ih(t,"max"),vn("max",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,t.dtype),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=s[l],f=0;f<i;++f){var p=s[l+f];p>h&&(h=p);}u[c]=h;}return a},o.prototype.maximum=function(t,e){return Ih([t,e],"maximum"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.max(t,e)})},o.prototype.all=function(t,e){Ih(t,"all"),vn("all",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,t.dtype),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=s[l],f=0;f<i;++f){var p=s[l+f];h=h&&p;}u[c]=h;}return a},o.prototype.any=function(t,e){Ih(t,"any"),vn("any",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,t.dtype),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=s[l],f=0;f<i;++f){var p=s[l+f];h=h||p;}u[c]=h;}return a},o.prototype.squaredDifference=function(t,e){return Ih([t,e],"squaredDifference"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var n=t-e;return n*n})},o.prototype.ceil=function(t){Ih(t,"ceil");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.ceil(e[r]);return this.makeOutput(n,t.shape,"float32")},o.prototype.floor=function(t){Ih(t,"floor");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.floor(e[r]);return this.makeOutput(n,t.shape,"float32")},o.prototype.sign=function(t){Ih(t,"x");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)e[r]<0?n[r]=-1:e[r]>0?n[r]=1:n[r]=0;return this.makeOutput(n,t.shape,"float32")},o.prototype.isNaN=function(t){Ih(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isNaN(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},o.prototype.isInf=function(t){Ih(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Math.abs(e[r])===1/0&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},o.prototype.isFinite=function(t){Ih(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isFinite(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},o.prototype.round=function(t){Ih(t,"round");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=Math.floor(e[r]);e[r]-o<.5?n[r]=Math.floor(e[r]):e[r]-o>.5?n[r]=Math.ceil(e[r]):n[r]=o%2==0?o:o+1;}return this.makeOutput(n,t.shape,"float32")},o.prototype.exp=function(t){Ih(t,"exp");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.exp(e[r]);return this.makeOutput(n,t.shape,"float32")},o.prototype.expm1=function(t){Ih(t,"expm1");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.expm1(e[r]);return this.makeOutput(n,t.shape,"float32")},o.prototype.log=function(t){Ih(t,"log");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log(o);}return this.makeOutput(n,t.shape,"float32")},o.prototype.log1p=function(t){Ih(t,"log1p");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log1p(o);}return this.makeOutput(n,t.shape,"float32")},o.prototype.sqrt=function(t){Ih(t,"sqrt");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.sqrt(o);}return this.makeOutput(n,t.shape,"float32")},o.prototype.rsqrt=function(t){Ih(t,"rsqrt");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=1/Math.sqrt(o);}return this.makeOutput(n,t.shape,"float32")},o.prototype.reciprocal=function(t){Ih(t,"reciprocal");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=1/e[r];return this.makeOutput(n,t.shape,"float32")},o.prototype.linear=function(t){return t},o.prototype.relu=function(t){Ih(t,"relu");for(var e=Bn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.max(0,r[o]);return e},o.prototype.relu6=function(t){Ih(t,"relu");for(var e=Bn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.min(Math.max(0,r[o]),6);return e},o.prototype.prelu=function(t,e){return Ih([t,e],"prelu"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return t<0?e*t:t})},o.prototype.elu=function(t){Ih(t,"elu");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=n[r];e[r]=o>=0?o:Math.exp(o)-1;}return this.makeOutput(e,t.shape,"float32")},o.prototype.eluDer=function(t,e){Ih([t,e],"eluDer");for(var n=new Float32Array(e.size),r=this.readSync(e.dataId),o=this.readSync(t.dataId),a=0;a<r.length;++a){var i=r[a];n[a]=i>=1?o[a]:o[a]*(i+1);}return this.makeOutput(n,e.shape,"float32")},o.prototype.selu=function(t){Ih(t,"selu");for(var e=ou,n=au,r=new Float32Array(t.size),o=this.readSync(t.dataId),a=0;a<o.length;++a){var i=o[a];r[a]=i>=0?n*i:e*(Math.exp(i)-1);}return this.makeOutput(r,t.shape,"float32")},o.prototype.clip=function(t,e,n){Ih(t,"clip");for(var r=new Float32Array(t.size),o=this.readSync(t.dataId),a=0;a<o.length;++a){var i=o[a];r[a]=i>n?n:i<e?e:i;}return this.makeOutput(r,t.shape,"float32")},o.prototype.abs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.abs(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.complexAbs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<t.size;++r){var o=n[2*r],a=n[2*r+1];e[r]=Math.hypot(o,a);}return this.makeOutput(e,t.shape,"float32")},o.prototype.int=function(t){Ih(t,"int");for(var e=new Int32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=n[r];return this.makeOutput(e,t.shape,"int32")},o.prototype.sigmoid=function(t){Ih(t,"sigmoid");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=1/(1+Math.exp(-n[r]));return this.makeOutput(e,t.shape,"float32")},o.prototype.softplus=function(t){Ih(t,"softplus");for(var e=Math.log(1.1920928955078125e-7)+2,n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var a=r[o]>-e,i=r[o]<e,u=Math.exp(r[o]),s=void 0;s=i?u:a?r[o]:Math.log(1+u),n[o]=s;}return this.makeOutput(n,t.shape,"float32")},o.prototype.sin=function(t){Ih(t,"sin");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sin(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.cos=function(t){Ih(t,"cos");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cos(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.tan=function(t){Ih(t,"tan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.tan(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.asin=function(t){Ih(t,"asin");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asin(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.acos=function(t){Ih(t,"acos");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acos(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.atan=function(t){Ih(t,"atan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atan(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.atan2=function(t,e){return Ih([t,e],"atan2"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.atan2(t,e)})},o.prototype.sinh=function(t){Ih(t,"sinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sinh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.cosh=function(t){Ih(t,"cosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cosh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.tanh=function(t){Ih(t,"tanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=R(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.asinh=function(t){Ih(t,"asinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asinh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.acosh=function(t){Ih(t,"acosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acosh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.atanh=function(t){Ih(t,"atanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atanh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.erf=function(t){Ih(t,"erf");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=Math.sign(n[r]),a=Math.abs(n[r]),i=1/(1+.3275911*a);e[r]=o*(1-((((1.061405429*i-1.453152027)*i+1.421413741)*i-.284496736)*i+.254829592)*i*Math.exp(-a*a));}return this.makeOutput(e,t.shape,"float32")},o.prototype.step=function(t,e){void 0===e&&(e=0),Ih(t,"step");for(var n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var a=r[o];isNaN(a)?n[o]=NaN:n[o]=a>0?1:e;}return this.makeOutput(n,t.shape,"float32")},o.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,i=t.preluActivationWeights,u=this.conv2d(e,n,r);return o&&(u=this.add(u,o)),a&&(u=kh(this,u,a,i)),u},o.prototype.conv2d=function(t,e,n){Ih([t,e],"conv2d");for(var r=n.filterHeight,o=n.filterWidth,a=n.dilationHeight,i=n.dilationWidth,u=n.padInfo.left,s=n.padInfo.top,c="channelsLast"===n.dataFormat,l=ir(n.outShape,t.dtype),h=t.strides[0],f=c?t.strides[1]:t.strides[2],p=c?t.strides[2]:1,d=c?1:t.strides[1],v=l.strides[0],m=c?l.strides[1]:l.strides[2],g=c?l.strides[2]:1,y=c?1:l.strides[1],x=this.readSync(t.dataId),b=this.readSync(e.dataId),w=l.values,C=0;C<n.batchSize;++C)for(var E=C*h,R=C*v,I=0;I<n.outHeight;++I)for(var k=R+I*m,S=I*n.strideHeight-s,A=0;A<r;A++){var D=S+A*a;if(!(D<0||D>=n.inHeight))for(var T=A*e.strides[0],N=E+D*f,F=0;F<n.outWidth;++F)for(var _=k+F*g,O=F*n.strideWidth-u,M=0;M<o;M++){var B=O+M*i;if(!(B<0||B>=n.inWidth))for(var P=N+B*p,L=T+M*e.strides[1],W=0;W<n.inChannels;++W){for(var U=x[P+W*d],V=0;V<n.outChannels;++V)w[_+V*y]+=U*b[L+V];L+=n.outChannels;}}}return l.toTensor()},o.prototype.conv3d=function(t,e,n){for(var r=n.filterDepth,o=n.filterHeight,a=n.filterWidth,i=n.dilationDepth,u=n.dilationHeight,s=n.dilationWidth,c=n.padInfo.front,l=n.padInfo.left,h=n.padInfo.top,f=ir(n.outShape,t.dtype),p=this.readSync(t.dataId),d=this.readSync(e.dataId),v=f.values,m=0;m<n.batchSize;++m)for(var g=m*t.strides[0],y=m*f.strides[0],x=0;x<n.outDepth;++x)for(var b=y+x*f.strides[1],w=x*n.strideDepth-c,C=0;C<r;C++){var E=w+C*i;if(!(E<0||E>=n.inDepth))for(var R=C*e.strides[0],I=g+E*t.strides[1],k=0;k<n.outHeight;++k)for(var S=b+k*f.strides[2],A=k*n.strideHeight-h,D=0;D<o;D++){var T=A+D*u;if(!(T<0||T>=n.inHeight))for(var N=R+D*e.strides[1],F=I+T*t.strides[2],_=0;_<n.outWidth;++_)for(var O=S+_*n.outChannels,M=_*n.strideWidth-l,B=0;B<a;B++){var P=M+B*s;if(!(P<0||P>=n.inWidth))for(var L=N+B*e.strides[2],W=F+P*n.inChannels,U=L,V=0;V<n.inChannels;++V){for(var z=p[W+V],G=0;G<n.outChannels;++G)v[O+G]+=z*d[U+G];U+=n.outChannels;}}}}return f.toTensor()},o.prototype.conv2dDerInput=function(t,e,n){Ih([t,e],"conv2dDerInput");for(var r=ir(n.inShape,"float32"),o=r.values,a=this.readSync(t.dataId),i=this.readSync(e.dataId),u=e.strides,s=u[0],c=u[1],l=u[2],h=n.batchSize,f=n.filterHeight,p=n.filterWidth,d=n.inChannels,v=n.inHeight,m=n.inWidth,g=n.outChannels,y=n.outHeight,x=n.outWidth,b=n.strideHeight,w=n.strideWidth,C=n.dataFormat,E=f-1-n.padInfo.top,R=p-1-n.padInfo.left,I="channelsLast"===C,k=r.strides[0],S=I?r.strides[1]:r.strides[2],A=I?r.strides[2]:1,D=I?1:r.strides[1],T=t.strides[0],N=I?t.strides[1]:t.strides[2],F=I?t.strides[2]:1,_=I?1:t.strides[1],O=0;O<h;++O)for(var M=0;M<d;++M)for(var B=0;B<v;++B)for(var P=B-E,L=Math.max(0,Math.ceil(P/b)),W=Math.min(y,(f+P)/b),U=0;U<m;++U){for(var V=U-R,z=Math.max(0,Math.ceil(V/w)),G=Math.min(x,(p+V)/w),H=0,q=L;q<W;++q)for(var K=q*b-P,j=z;j<G;++j)for(var X=T*O+N*q+F*j,$=s*(f-1-K)+c*(p-1-(j*w-V))+l*M,Y=0;Y<g;++Y){H+=a[X+_*Y]*i[$+Y];}o[k*O+S*B+A*U+D*M]=H;}return r.toTensor()},o.prototype.conv3dDerInput=function(t,e,n){for(var r=ir(n.inShape,"float32"),o=r.values,a=r.strides,i=a[0],u=a[1],s=a[2],c=a[3],l=this.readSync(t.dataId),h=t.strides,f=h[0],p=h[1],d=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=n.batchSize,E=n.filterDepth,R=n.filterHeight,I=n.filterWidth,k=n.inChannels,S=n.inDepth,A=n.inHeight,D=n.inWidth,T=n.outChannels,N=n.outDepth,F=n.outHeight,_=n.outWidth,O=n.strideDepth,M=n.strideHeight,B=n.strideWidth,P=E-1-n.padInfo.front,L=R-1-n.padInfo.top,W=I-1-n.padInfo.left,U=0;U<C;++U)for(var V=0;V<k;++V)for(var z=0;z<S;++z)for(var G=z-P,H=Math.max(0,Math.ceil(G/O)),q=Math.min(N,(E+G)/O),K=0;K<A;++K)for(var j=K-L,X=Math.max(0,Math.ceil(j/M)),$=Math.min(F,(R+j)/M),Y=0;Y<D;++Y){for(var Q=Y-W,J=Math.max(0,Math.ceil(Q/B)),Z=Math.min(_,(I+Q)/B),tt=0,et=H;et<q;++et)for(var nt=et*O-G,rt=X;rt<$;++rt)for(var ot=rt*M-j,at=J;at<Z;++at)for(var it=f*U+p*et+d*rt+v*at,ut=y*(E-1-nt)+x*(R-1-ot)+b*(I-1-(at*B-Q))+w*V,st=0;st<T;++st){tt+=l[it+st]*m[ut+st];}o[i*U+u*z+s*K+c*Y+V]=tt;}return r.toTensor()},o.prototype.conv2dDerFilter=function(t,e,n){Ih([t,e],"conv2dDerFilter");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,u="channelsLast"===n.dataFormat,s=ir(n.filterShape,"float32"),c=n.padInfo.left,l=n.padInfo.top,h=this.bufferSync(t),f=this.bufferSync(e),p=0;p<a;++p)for(var d=Math.max(0,Math.ceil((l-p)/r)),v=Math.min(n.outHeight,(n.inHeight+l-p)/r),m=0;m<i;++m)for(var g=Math.max(0,Math.ceil((c-m)/o)),y=Math.min(n.outWidth,(n.inWidth+c-m)/o),x=0;x<n.inChannels;++x)for(var b=0;b<n.outChannels;++b){for(var w=0,C=0;C<n.batchSize;++C)for(var E=d;E<v;++E)for(var R=p+E*r-l,I=g;I<y;++I){var k=m+I*o-c;w+=u?h.get(C,R,k,x)*f.get(C,E,I,b):h.get(C,x,R,k)*f.get(C,b,E,I);}s.set(w,p,m,x,b);}return s.toTensor()},o.prototype.conv3dDerFilter=function(t,e,n){for(var r=n.strideDepth,o=n.strideHeight,a=n.strideWidth,i=n.filterDepth,u=n.filterHeight,s=n.filterWidth,c=ir(n.filterShape,"float32"),l=c.values,h=c.strides,f=h[0],p=h[1],d=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=this.readSync(t.dataId),E=t.strides,R=E[0],I=E[1],k=E[2],S=E[3],A=n.padInfo.front,D=n.padInfo.left,T=n.padInfo.top,N=0;N<i;++N)for(var F=Math.max(0,Math.ceil((A-N)/r)),_=Math.min(n.outDepth,(n.inDepth+A-N)/r),O=N*f,M=0;M<u;++M)for(var B=Math.max(0,Math.ceil((T-M)/o)),P=Math.min(n.outHeight,(n.inHeight+T-M)/o),L=M*p+O,W=0;W<s;++W)for(var U=Math.max(0,Math.ceil((D-W)/a)),V=Math.min(n.outWidth,(n.inWidth+D-W)/a),z=W*d+L,G=0;G<n.inChannels;++G)for(var H=G*v+z,q=0;q<n.outChannels;++q){for(var K=0,j=0;j<n.batchSize;++j)for(var X=j*R,$=j*y,Y=F;Y<_;++Y)for(var Q=(N+Y*r-A)*I+X,J=Y*x+$,Z=B;Z<P;++Z)for(var tt=(M+Z*o-T)*k+Q,et=Z*b+J,nt=U;nt<V;++nt){var rt=nt*w+et;K+=C[(W+nt*a-D)*S+tt+G]*m[rt+q];}l[H+q]=K;}return c.toTensor()},o.prototype.fusedDepthwiseConv2D=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,i=t.preluActivationWeights,u=this.depthwiseConv2D(e,n,r);return o&&(u=this.add(u,o)),a&&(u=kh(this,u,a,i)),u},o.prototype.depthwiseConv2D=function(t,e,n){Ih([t,e],"depthwiseConv2D");for(var r=n.filterHeight,o=n.filterWidth,a=n.dilationHeight,i=n.dilationWidth,u=n.padInfo.left,s=n.padInfo.top,c=n.outChannels/n.inChannels,l=ir(n.outShape,t.dtype),h=this.readSync(t.dataId),f=this.readSync(e.dataId),p=l.values,d=0;d<n.batchSize;++d)for(var v=d*t.strides[0],m=d*l.strides[0],g=0;g<n.outHeight;++g)for(var y=m+g*l.strides[1],x=g*n.strideHeight-u,b=0;b<r;++b){var w=x+b*a;if(!(w<0||w>=n.inHeight))for(var C=b*e.strides[0],E=v+w*t.strides[1],R=0;R<n.outWidth;++R)for(var I=y+R*l.strides[2],k=R*n.strideWidth-s,S=0;S<o;++S){var A=k+S*i;if(!(A<0||A>=n.inWidth))for(var D=C+S*e.strides[1],T=E+A*n.inChannels,N=I,F=D,_=0;_<n.inChannels;++_){for(var O=h[T+_],M=0;M<c;++M)p[N+M]+=O*f[F+M];N+=c,F+=c;}}}return l.toTensor()},o.prototype.depthwiseConv2DDerInput=function(t,e,n){Ih([t,e],"depthwiseConv2DDerInput");for(var r=ir(n.inShape,"float32"),o=r.values,a=r.strides,i=a[0],u=a[1],s=a[2],c=this.readSync(t.dataId),l=t.strides,h=l[0],f=l[1],p=l[2],d=this.readSync(e.dataId),v=e.strides,m=v[0],g=v[1],y=v[2],x=n.batchSize,b=n.filterHeight,w=n.filterWidth,C=n.inChannels,E=n.inHeight,R=n.inWidth,I=n.outChannels,k=n.outHeight,S=n.outWidth,A=n.strideHeight,D=n.strideWidth,T=b-1-n.padInfo.top,N=w-1-n.padInfo.left,F=I/C,_=0;_<x;++_)for(var O=0;O<C;++O)for(var M=0;M<E;++M)for(var B=M-T,P=Math.max(0,Math.ceil(B/A)),L=Math.min(k,(b+B)/A),W=0;W<R;++W){for(var U=W-N,V=Math.max(0,Math.ceil(U/D)),z=Math.min(S,(w+U)/D),G=0,H=P;H<L;++H)for(var q=H*A-B,K=V;K<z;++K)for(var j=h*_+f*H+p*K,X=m*(b-1-q)+g*(w-1-(K*D-U))+y*O,$=0;$<F;++$){G+=c[j+(O*F+$)]*d[X+$];}o[i*_+u*M+s*W+O]=G;}return r.toTensor()},o.prototype.depthwiseConv2DDerFilter=function(t,e,n){Ih([t,e],"depthwiseConv2DDerFilter");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,u=ir(n.filterShape,"float32"),s=n.padInfo.left,c=n.padInfo.top,l=n.outChannels/n.inChannels,h=this.bufferSync(t),f=this.bufferSync(e),p=0;p<a;++p)for(var d=Math.max(0,Math.ceil((c-p)/r)),v=Math.min(n.outHeight,(n.inHeight+c-p)/r),m=0;m<i;++m)for(var g=Math.max(0,Math.ceil((s-m)/o)),y=Math.min(n.outWidth,(n.inWidth+s-m)/o),x=0;x<n.outChannels;++x){for(var b=Math.trunc(x/l),w=x%l,C=0,E=0;E<n.batchSize;++E)for(var R=d;R<v;++R)for(var I=p+R*r-c,k=g;k<y;++k){var S=m+k*o-s;C+=h.get(E,I,S,b)*f.get(E,R,k,x);}u.set(C,p,m,b,w);}return u.toTensor()},o.prototype.tile=function(t,e){return Ih(t,"tile"),Lo(this.bufferSync(t),e)},o.prototype.pad=function(t,e,n){Ih(t,"pad");var r=e.map(function(e,n){return e[0]+t.shape[n]+e[1]}),o=e.map(function(t){return t[0]}),a=this.bufferSync(t),i=ir(r,t.dtype);0!==n&&i.values.fill(n);for(var u=0;u<t.size;u++){var s=a.indexToLoc(u),c=s.map(function(t,e){return t+o[e]});i.set.apply(i,[a.get.apply(a,s)].concat(c));}return i.toTensor()},o.prototype.transpose=function(t,e){Ih(t,"transpose");for(var n=new Array(t.rank),r=0;r<n.length;r++)n[r]=t.shape[e[r]];var o=this.readSync(t.dataId),a=ir(n,t.dtype),i=this.bufferSync(t);for(r=0;r<t.size;++r){for(var u=i.indexToLoc(r),s=new Array(u.length),c=0;c<s.length;c++)s[c]=u[e[c]];var l=a.locToIndex(s);a.values[l]=o[r];}return a.toTensor()},o.prototype.gather=function(t,e,n){Ih([t,e],"gather");var r=t.shape.slice(),o=this.readSync(e.dataId);r[n]=o.length;for(var a=ir(r,t.dtype),i=this.bufferSync(t),u=0;u<a.size;++u){var s=a.indexToLoc(u),c=s.slice();c[n]=o[s[n]];var l=i.locToIndex(c);a.values[u]=i.values[l];}return a.toTensor()},o.prototype.batchToSpaceND=function(t,e,n){Ih([t],"batchToSpaceND");var r=e.reduce(function(t,e){return t*e}),o=Mr(t.shape,e,r),a=Br(o.length,e.length),i=Pr(t.shape,e,r),u=Lr(n,e.length),s=Wr(i,n,e.length);return t.reshape(o).transpose(a).reshape(i).slice(u,s)},o.prototype.spaceToBatchND=function(t,e,n){Ih([t],"spaceToBatchND");var r=e.reduce(function(t,e){return t*e}),o=[[0,0]];o.push.apply(o,n);for(var a=1+e.length;a<t.shape.length;++a)o.push([0,0]);var i=t.pad(o),u=Mr(i.shape,e,r,!1),s=Br(u.length,e.length,!1),c=Pr(i.shape,e,r,!1);return i.reshape(u).transpose(s).reshape(c)},o.prototype.pool=function(t,e,n){Ih(t,"pool");for(var r=e.strideHeight,o=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,u=e.effectiveFilterHeight,s=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=this.readSync(t.dataId),p=ir(e.outShape,t.dtype),d=p.values,v=e.outShape[1]*e.outShape[2]*e.outShape[3],m=e.outShape[2]*e.outShape[3],g=e.outShape[3],y=0;y<e.batchSize;++y)for(var x=y*v,b=y*t.strides[0],w=0;w<e.inChannels;++w)for(var C=0;C<e.outHeight;++C)for(var E=C*r-c,R=Math.max(0,E),I=Math.min(e.inHeight,u+E),k=x+C*m,S=0;S<e.outWidth;++S){for(var A=S*o-l,D=Math.max(0,A),T=Math.min(e.inWidth,s+A),N=h,F=0,_=0,O=R;O<I;O+=a){for(var M=b+O*t.strides[1],B=D;B<T;B+=i){var P=f[M+B*t.strides[2]+w];"max"===n&&P>N?N=P:"avg"===n&&(F+=P,_++);}if(isNaN(N))break}d[k+S*g+w]="avg"===n?F/_:N;}return p.toTensor()},o.prototype.maxPool=function(t,e){return this.pool(t,e,"max")},o.prototype.maxPoolPositions=function(t,e){for(var n=ir(e.outShape,"int32"),r=e.strideHeight,o=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,u=e.effectiveFilterHeight,s=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h=this.bufferSync(t),f=0;f<e.batchSize;++f)for(var p=0;p<e.inChannels;++p)for(var d=0;d<e.outHeight;++d){for(var v=d*r-c,m=v;m<0;)m+=a;for(var g=Math.min(e.inHeight,u+v),y=0;y<e.outWidth;++y){for(var x=y*o-l,b=x;b<0;)b+=i;for(var w=Math.min(e.inWidth,s+x),C=Number.NEGATIVE_INFINITY,E=-1,R=m;R<g;R+=a)for(var I=R-v,k=b;k<w;k+=i){var S=k-x,A=h.get(f,R,k,p);A>C&&(C=A,E=I*s+S);}n.set(E,f,d,y,p);}}return n.toTensor()},o.prototype.maxPoolBackprop=function(t,e,n,r){Ih([e,n],"maxPoolBackprop");for(var o=this.maxPoolPositions(e,r),a=r.strideHeight,i=r.strideWidth,u=r.dilationHeight,s=r.dilationWidth,c=r.effectiveFilterHeight,l=r.effectiveFilterWidth,h=l-1-r.padInfo.left,f=c-1-r.padInfo.top,p=ir(e.shape,"float32"),d=this.bufferSync(o),v=this.bufferSync(t),m=0;m<r.batchSize;++m)for(var g=0;g<r.inChannels;++g)for(var y=0;y<r.inHeight;++y)for(var x=0;x<r.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=u){var R=(b+E)/a;if(!(R<0||R>=r.outHeight||Math.floor(R)!==R))for(var I=0;I<l;I+=s){var k=(w+I)/i;if(!(k<0||k>=r.outWidth||Math.floor(k)!==k)){var S=c*l-1-d.get(m,R,k,g)===E*l+I?1:0;if(0!==S)C+=v.get(m,R,k,g)*S;}}}p.set(C,m,y,x,g);}return p.toTensor()},o.prototype.avgPoolBackprop=function(t,e,n){Ih([t,e],"avgPoolBackprop");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,u=n.dilationHeight,s=n.dilationWidth,c=n.effectiveFilterHeight,l=n.effectiveFilterWidth,h=l-1-n.padInfo.left,f=c-1-n.padInfo.top,p=ir(e.shape,"float32"),d=1/(a*i),v=this.bufferSync(t),m=0;m<n.batchSize;++m)for(var g=0;g<n.inChannels;++g)for(var y=0;y<n.inHeight;++y)for(var x=0;x<n.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=u){var R=(b+E)/r;if(!(R<0||R>=n.outHeight||Math.floor(R)!==R))for(var I=0;I<l;I+=s){var k=(w+I)/o;if(!(k<0||k>=n.outWidth||Math.floor(k)!==k))C+=v.get(m,R,k,g);}}p.set(C*d,m,y,x,g);}return p.toTensor()},o.prototype.pool3d=function(t,e,n){Ih(t,"pool3d");for(var r=e.strideDepth,o=e.strideHeight,a=e.strideWidth,i=e.dilationDepth,u=e.dilationHeight,s=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,p=e.padInfo.top,d=e.padInfo.left,v="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=this.readSync(t.dataId),g=ir(e.outShape,t.dtype),y=g.values,x=e.outShape[1]*e.outShape[2]*e.outShape[3]*e.outShape[4],b=e.outShape[2]*e.outShape[3]*e.outShape[4],w=e.outShape[3]*e.outShape[4],C=e.outShape[4],E=0;E<e.batchSize;++E)for(var R=E*x,I=E*t.strides[0],k=0;k<e.inChannels;++k)for(var S=0;S<e.outDepth;++S){for(var A=S*r-f,D=A;D<0;)D+=i;for(var T=Math.min(e.inDepth,c+A),N=R+S*b,F=0;F<e.outHeight;++F){for(var _=F*o-p,O=_;O<0;)O+=u;for(var M=Math.min(e.inHeight,l+_),B=N+F*w,P=0;P<e.outWidth;++P){for(var L=P*a-d,W=L;W<0;)W+=s;for(var U=Math.min(e.inWidth,h+L),V=B+P*C,z=v,G=0,H=0,q=D;q<T;q+=i){for(var K=I+q*t.strides[1],j=O;j<M;j+=u){for(var X=K+j*t.strides[2],$=W;$<U;$+=s){var Y=m[X+$*t.strides[3]+k];if("max"===n&&Y>z?z=Y:"avg"===n&&(G+=Y,H++),isNaN(z))break}if(isNaN(z))break}if(isNaN(z))break}y[V+k]="avg"===n?G/H:z;}}}return g.toTensor()},o.prototype.avgPool3d=function(t,e){return Ih(t,"avgPool3d"),this.pool3d(t,e,"avg").toFloat()},o.prototype.avgPool3dBackprop=function(t,e,n){Ih([t,e],"avgPool3dBackprop");for(var r=n.strideDepth,o=n.strideHeight,a=n.strideWidth,i=n.filterDepth,u=n.filterHeight,s=n.filterWidth,c=n.dilationDepth,l=n.dilationHeight,h=n.dilationWidth,f=n.effectiveFilterDepth,p=n.effectiveFilterHeight,d=n.effectiveFilterWidth,v=f-1-n.padInfo.front,m=d-1-n.padInfo.left,g=p-1-n.padInfo.top,y=ir(e.shape,"float32"),x=1/(i*u*s),b=this.bufferSync(t),w=0;w<n.batchSize;++w)for(var C=0;C<n.inChannels;++C)for(var E=0;E<n.inDepth;++E)for(var R=0;R<n.inHeight;++R)for(var I=0;I<n.inWidth;++I){for(var k=E-v,S=R-g,A=I-m,D=0,T=0;T<f;T+=c){var N=(k+T)/r;if(!(N<0||N>=n.outDepth||Math.floor(N)!==N))for(var F=0;F<p;F+=l){var _=(S+F)/o;if(!(_<0||_>=n.outHeight||Math.floor(_)!==_))for(var O=0;O<d;O+=h){var M=(A+O)/a;if(!(M<0||M>=n.outWidth||Math.floor(M)!==M))D+=b.get(w,N,_,M,C);}}}y.set(D*x,w,E,R,I,C);}return y.toTensor()},o.prototype.maxPool3d=function(t,e){return Ih(t,"maxPool3d"),this.pool3d(t,e,"max").toFloat()},o.prototype.maxPool3dPositions=function(t,e){for(var n=ir(e.outShape,"int32"),r=e.strideDepth,o=e.strideHeight,a=e.strideWidth,i=e.dilationDepth,u=e.dilationHeight,s=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,p=e.padInfo.top,d=e.padInfo.left,v=this.bufferSync(t),m=0;m<e.batchSize;++m)for(var g=0;g<e.inChannels;++g)for(var y=0;y<e.outDepth;++y){for(var x=y*r-f,b=x;b<0;)b+=i;for(var w=Math.min(e.inDepth,c+x),C=0;C<e.outHeight;++C){for(var E=C*o-p,R=E;R<0;)R+=u;for(var I=Math.min(e.inHeight,l+E),k=0;k<e.outWidth;++k){for(var S=k*a-d,A=S;A<0;)A+=s;for(var D=Math.min(e.inWidth,h+S),T=Number.NEGATIVE_INFINITY,N=-1,F=b;F<w;F+=i)for(var _=F-x,O=R;O<I;O+=u)for(var M=O-E,B=A;B<D;B+=s){var P=B-S,L=v.get(m,F,O,B,g);L>=T&&(T=L,N=_*l*h+M*l+P);}n.set(N,m,y,C,k,g);}}}return n.toTensor()},o.prototype.maxPool3dBackprop=function(t,e,n,r){Ih([e,n],"maxPool3dBackprop");for(var o=this.maxPool3dPositions(e,r),a=r.strideDepth,i=r.strideHeight,u=r.strideWidth,s=r.dilationDepth,c=r.dilationHeight,l=r.dilationWidth,h=r.effectiveFilterDepth,f=r.effectiveFilterHeight,p=r.effectiveFilterWidth,d=h-1-r.padInfo.front,v=p-1-r.padInfo.left,m=f-1-r.padInfo.top,g=ir(e.shape,"float32"),y=this.bufferSync(o),x=this.bufferSync(t),b=0;b<r.batchSize;++b)for(var w=0;w<r.inChannels;++w)for(var C=0;C<r.inDepth;++C)for(var E=0;E<r.inHeight;++E)for(var R=0;R<r.inWidth;++R){for(var I=C-d,k=E-m,S=R-v,A=0,D=0;D<h;D+=s){var T=(I+D)/a;if(!(T<0||T>=r.outDepth||Math.floor(T)!==T))for(var N=0;N<f;N+=c){var F=(k+N)/i;if(!(F<0||F>=r.outHeight||Math.floor(F)!==F))for(var _=0;_<p;_+=l){var O=(S+_)/u;if(!(O<0||O>=r.outWidth||Math.floor(O)!==O)){var M=h*f*p-1-y.get(b,T,F,O,w)===D*f*p+N*p+_?1:0;if(0!==M)A+=x.get(b,T,F,O,w)*M;}}}}g.set(A,b,C,E,R,w);}return g.toTensor()},o.prototype.cast=function(t,e){return So(t,e,this)},o.prototype.reshape=function(t,e){return Ao(t,e)},o.prototype.avgPool=function(t,e){return Ih(t,"avgPool"),this.pool(t,e,"avg").toFloat()},o.prototype.resizeBilinear=function(t,e,n,r){Ih(t,"resizeBilinear");for(var o=t.shape,a=o[0],i=o[1],u=o[2],s=o[3],c=this.readSync(t.dataId),l=new Float32Array(w([a,e,n,s])),h=[r&&e>1?i-1:i,r&&n>1?u-1:u],f=[r&&e>1?e-1:e,r&&n>1?n-1:n],p=0,d=h[0]/f[0],v=h[1]/f[1],m=0;m<a;m++)for(var g=0;g<e;g++)for(var y=d*g,x=Math.floor(y),b=y-x,C=Math.min(i-1,Math.ceil(y)),E=m*t.strides[0]+x*t.strides[1],R=m*t.strides[0]+C*t.strides[1],I=0;I<n;I++)for(var k=v*I,S=Math.floor(k),A=k-S,D=Math.min(u-1,Math.ceil(k)),T=E+S*t.strides[2],N=R+S*t.strides[2],F=E+D*t.strides[2],_=R+D*t.strides[2],O=0;O<s;O++){var M=c[T+O],B=c[N+O],P=M+(c[F+O]-M)*A,L=P+(B+(c[_+O]-B)*A-P)*b;l[p++]=L;}return In(l,[a,e,n,s])},o.prototype.resizeBilinearBackprop=function(t,e,n){Ih([t,e],"resizeBilinearBackprop");for(var r=e.shape,o=r[0],a=r[1],i=r[2],u=r[3],s=t.shape,c=s[1],l=s[2],h=new Float32Array(o*a*i*u),f=[n&&c>1?a-1:a,n&&l>1?i-1:i],p=[n&&c>1?c-1:c,n&&l>1?l-1:l],d=f[0]/p[0],v=f[1]/p[1],m=this.readSync(t.dataId),g=0,y=0;y<o;y++)for(var x=y*e.strides[0],b=0;b<c;b++)for(var w=b*d,C=Math.floor(w),E=Math.min(Math.ceil(w),a-1),R=x+C*e.strides[1],I=x+E*e.strides[1],k=w-C,S=1-k,A=0;A<l;A++)for(var D=A*v,T=Math.floor(D),N=Math.min(Math.ceil(D),i-1),F=D-T,_=1-F,O=R+T*e.strides[2],M=R+N*e.strides[2],B=I+T*e.strides[2],P=I+N*e.strides[2],L=S*_,W=S*F,U=k*_,V=k*F,z=0;z<u;z++){var G=m[g++];h[O+z]+=G*L,h[M+z]+=G*W,h[B+z]+=G*U,h[P+z]+=G*V;}return Nn(h,[o,i,a,u],e.dtype)},o.prototype.resizeNearestNeighbor=function(t,e,n,r){Ih(t,"resizeNearestNeighbor");for(var o=t.shape,a=o[0],i=o[1],u=o[2],s=o[3],c=this.readSync(t.dataId),l=new Float32Array(a*e*n*s),h=[r&&e>1?i-1:i,r&&n>1?u-1:u],f=[r&&e>1?e-1:e,r&&n>1?n-1:n],p=h[0]/f[0],d=h[1]/f[1],v=0,m=0;m<a;m++)for(var g=m*t.strides[0],y=0;y<e;y++)for(var x=p*y,b=g+Math.min(i-1,r?Math.round(x):Math.floor(x))*t.strides[1],w=0;w<n;w++)for(var C=d*w,E=b+Math.min(u-1,r?Math.round(C):Math.floor(C))*t.strides[2],R=0;R<s;R++){var I=c[E+R];l[v++]=I;}return In(l,[a,e,n,s],t.dtype)},o.prototype.resizeNearestNeighborBackprop=function(t,e,n){Ih([t,e],"resizeNearestNeighborBackprop");for(var r=e.shape,o=r[0],a=r[1],i=r[2],u=r[3],s=t.shape,c=s[1],l=s[2],h=new Float32Array(o*a*i*u),f=this.readSync(t.dataId),p=[n&&c>1?a-1:a,n&&l>1?i-1:i],d=[n&&c>1?c-1:c,n&&l>1?l-1:l],v=p[0]/d[0],m=p[1]/d[1],g=1/v,y=1/m,x=2*Math.ceil(g)+2,b=2*Math.ceil(y)+2,w=0;w<o;w++)for(var C=w*e.strides[0],E=0;E<a;E++)for(var R=C+E*e.strides[1],I=Math.floor(E*g),k=Math.floor(I-x/2),S=0;S<i;S++)for(var A=R+S*e.strides[2],D=Math.floor(S*y),T=Math.floor(D-b/2),N=0;N<u;N++){for(var F=0,_=0;_<x;_++){var O=_+k;if(!(O<0||O>=c)){var M=C+O*t.strides[1],B=O*v;if(E===Math.min(a-1,n?Math.round(B):Math.floor(B)))for(var P=0;P<b;P++){var L=P+T;if(!(L<0||L>=l)){var W=M+L*t.strides[2],U=L*m;S===Math.min(i-1,n?Math.round(U):Math.floor(U))&&(F+=f[W+N]);}}}}h[A+N]=F;}return Nn(h,e.shape,e.dtype)},o.prototype.batchNormalization=function(t,e,n,r,o,a){Ih([t,e,n,o,a],"batchNorm");for(var i=this.readSync(t.dataId),u=this.readSync(e.dataId),s=this.readSync(n.dataId),c=o?this.readSync(o.dataId):new Float32Array([1]),l=a?this.readSync(a.dataId):new Float32Array([0]),h=new Float32Array(i.length),f=l.length,p=c.length,d=s.length,v=u.length,m=0,g=0,y=0,x=0,b=0;b<i.length;++b)h[b]=l[m++]+(i[b]-u[g++])*c[y++]/Math.sqrt(s[x++]+r),m>=f&&(m=0),g>=v&&(g=0),y>=p&&(y=0),x>=d&&(x=0);return Nn(h,t.shape)},o.prototype.localResponseNormalization4D=function(t,e,n,r,o){Ih(t,"localResponseNormalization4D");var a=t.shape[3],i=a-1,u=this.readSync(t.dataId),s=t.size,c=new Float32Array(s);function l(t){for(var n=t%a,r=t-n+Math.max(0,n-e),o=t-n+Math.min(n+e,i),s=0;r<=o;r++){var c=u[r];s+=c*c;}return s}for(var h=0;h<s;h++){var f=l(h),p=u[h]*Math.pow(n+r*f,-o);c[h]=p;}return Nn(c,t.shape)},o.prototype.LRNGrad=function(t,e,n,r,o,a,i){Ih(t,"LRNGrad");for(var u=t.shape[3],s=this.readSync(t.dataId),c=this.readSync(e.dataId),l=this.readSync(n.dataId),h=new Float32Array(t.size),f=t.size,p=0;p<f;p++){for(var d=p%u,v=p-d+Math.max(0,d-r),m=p-d+Math.min(u,d+r+1),g=0,y=v;y<m;y++)g+=Math.pow(c[y],2);g=a*g+o;for(y=v;y<m;y++){var x=-2*a*i*c[y]*l[p]/g;p===y&&(x+=Math.pow(g,-i)),x*=s[p],h[y]+=x;}}return Nn(h,t.shape)},o.prototype.multinomial=function(t,e,n,r){Ih(t,"multinomial");for(var o=e?t:io(t),a=o.shape[0],i=o.shape[1],u=Bn([a,n],"int32"),s=this.readSync(u.dataId),c=this.readSync(o.dataId),l=0;l<a;++l){var h=l*i,f=new Float32Array(i-1);f[0]=c[h];for(var p=1;p<f.length;++p)f[p]=f[p-1]+c[h+p];for(var d=nr(r.toString()),v=l*n,m=0;m<n;++m){var g=d();s[v+m]=f.length;for(var y=0;y<f.length;y++)if(g<f[y]){s[v+m]=y;break}}}return u},o.prototype.oneHot=function(t,e,n,r){Ih(t,"oneHot");var o=new Float32Array(t.size*e);o.fill(r);for(var a=this.readSync(t.dataId),i=0;i<t.size;++i)a[i]>=0&&a[i]<e&&(o[i*e+a[i]]=n);return Dn(o,[t.size,e],"int32")},o.prototype.nonMaxSuppression=function(t,e,n,r,o){return Ih(t,"nonMaxSuppression"),Mo(this.readSync(t.dataId),this.readSync(e.dataId),n,r,o)},o.prototype.fft=function(t){return this.fftBatch(t,!1)},o.prototype.ifft=function(t){return this.fftBatch(t,!0)},o.prototype.fftBatch=function(t,e){for(var n=t.shape[0],r=t.shape[1],o=ir(t.shape,"float32"),a=ir(t.shape,"float32"),i=En(t).as2D(n,r),u=Rn(t).as2D(n,r),s=0;s<n;s++)for(var c=i.slice([s,0],[1,r]),l=u.slice([s,0],[1,r]),h=Cn(c,l),f=this.readSync(this.fftImpl(h,e).dataId),p=0;p<r;p++){var d=Fo(f,p);o.values[s*r+p]=d.real,a.values[s*r+p]=d.imag;}return Cn(o.toTensor(),a.toTensor()).as2D(n,r)},o.prototype.fftImpl=function(t,e){var n=t.as1D(),r=n.size;if(this.isExponentOf2(r)){var o=this.fftRadix2(n,r,e).as2D(t.shape[0],t.shape[1]);return e&&(o=Cn(En(o).div(Sn(r)),Rn(o).div(Sn(r)))),o}var a=this.readSync(t.dataId),i=function(t){for(var e=new Float32Array(t.length/2),n=new Float32Array(t.length/2),r=0;r<t.length;r+=2)e[r/2]=t[r],n[r/2]=t[r+1];return {real:e,imag:n}}(this.fourierTransformByMatmul(a,r,e));return Cn(i.real,i.imag).as2D(t.shape[0],t.shape[1])},o.prototype.isExponentOf2=function(t){return 0==(t&t-1)},o.prototype.fftRadix2=function(t,e,n){if(1===e)return t;var r=this.readSync(t.dataId),o=e/2,a=function(t){for(var e=Math.ceil(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=0;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return {real:n,imag:r}}(r),i=Cn(a.real,a.imag).as1D(),u=function(t){for(var e=Math.floor(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=2;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return {real:n,imag:r}}(r),s=Cn(u.real,u.imag).as1D();i=this.fftRadix2(i,o,n),s=this.fftRadix2(s,o,n);var c=function(t,e){for(var n=new Float32Array(t/2),r=new Float32Array(t/2),o=0;o<Math.ceil(t/2);o++){var a=(e?2:-2)*Math.PI*(o/t);n[o]=Math.cos(a),r[o]=Math.sin(a);}return {real:n,imag:r}}(e,n),l=Cn(c.real,c.imag).mul(s),h=i.add(l),f=i.sub(l),p=En(h).concat(En(f)),d=Rn(h).concat(Rn(f));return Cn(p,d).as1D()},o.prototype.fourierTransformByMatmul=function(t,e,n){for(var r=new Float32Array(2*e),o=0;o<e;o++){for(var a=0,i=0,u=0;u<e;u++){var s=Oo(o*u,e,n),c=Fo(t,u);a+=c.real*s.real-c.imag*s.imag,i+=c.real*s.imag+c.imag*s.real;}n&&(a/=e,i/=e),_o(r,a,i,o);}return r},o.prototype.depthToSpace=function(t,e,n){g("NHWC"===n,function(){return "Only NHWC dataFormat supported on CPU for depthToSpace. Got "+n}),g(e>1,function(){return "blockSize should be > 1 for depthToSpace, but was: "+e});for(var r=t.shape[0],o=t.shape[1],a=t.shape[2],i=t.shape[3],u=o*e,s=a*e,c=i/(e*e),l=this.readSync(t.dataId),h=new Float32Array(r*u*s*c),f=0,p=0;p<r;++p)for(var d=0;d<u;++d)for(var v=Math.floor(d/e),m=d%e,y=0;y<s;++y)for(var x=Math.floor(y/e),b=(m*e+y%e)*c,w=0;w<c;++w){var C=w+b+i*(x+a*(v+o*p));h[f++]=l[C];}return Nn(h,[r,u,s,c])},o.prototype.broadcastedBinaryOp=function(t,e,n,r){var o=po(t.shape,e.shape),a=ir(o,n),i=this.readSync(t.dataId),u=this.readSync(e.dataId),s=ho(t.shape,o),c=ho(e.shape,o),l=a.values;if(s.length+c.length===0)for(var h=0;h<l.length;++h)l[h]=r(i[h%i.length],u[h%u.length]);else{var f=this.bufferSync(t),p=this.bufferSync(e),d=function(n){var o=a.indexToLoc(n),h=o.slice(-t.rank);s.forEach(function(t){return h[t]=0});var d=f.locToIndex(h),v=o.slice(-e.rank);c.forEach(function(t){return v[t]=0});var m=p.locToIndex(v);l[n]=r(i[d],u[m]);};for(h=0;h<l.length;++h)d(h);}return a.toTensor()},o.prototype.broadcastedBinaryComplexOp=function(t,e,n){var r=po(t.shape,e.shape),o=ir(r,"float32"),a=ir(r,"float32"),i=this.readSync(t.dataId),u=this.readSync(e.dataId),s=ho(t.shape,r),c=ho(e.shape,r),l=o.values,h=a.values;if(s.length+c.length===0)for(var f=0;f<l.length;f++){var p=f%i.length,d=f%u.length,v=n(i[2*p],i[2*p+1],u[2*d],u[2*d+1]);l[f]=v.real,h[f]=v.imag;}else{var m=this.bufferSync(this.data.get(t.dataId).complexTensors.real),g=this.bufferSync(this.data.get(e.dataId).complexTensors.real),y=function(r){var a=o.indexToLoc(r),f=a.slice(-t.rank);s.forEach(function(t){return f[t]=0});var p=m.locToIndex(f),d=a.slice(-e.rank);c.forEach(function(t){return d[t]=0});var v=g.locToIndex(d),y=n(i[2*p],i[2*p+1],u[2*v],u[2*v+1]);l[r]=y.real,h[r]=y.imag;};for(f=0;f<l.length;f++)y(f);}return this.complex(o.toTensor(),a.toTensor())},o.prototype.split=function(t,e,n){return Po(t,e,n)},o.prototype.dispose=function(){},o.prototype.floatPrecision=function(){return 32},o.prototype.epsilon=function(){return 1e-7},o.prototype.cropAndResize=function(t,e,n,r,o,a){for(var i=t.shape,u=i[0],s=i[1],c=i[2],l=i[3],h=e.shape[0],f=r[0],p=r[1],d=ir([h,f,p,l],"float32"),v=this.readSync(e.dataId),m=this.readSync(n.dataId),g=this.readSync(t.dataId),y=t.strides,x=d.strides,b=0;b<h;b++){var w=4*b,C=v[w],E=v[w+1],R=v[w+2],I=v[w+3],k=m[b];if(!(k>=u))for(var S=f>1?(R-C)*(s-1)/(f-1):0,A=p>1?(I-E)*(c-1)/(p-1):0,D=0;D<f;D++){var T=f>1?C*(s-1)+D*S:.5*(C+R)*(s-1);if(T<0||T>s-1)for(var N=0;N<p;N++)for(var F=0;F<l;F++){var _=F+N*x[2]+D*x[1]+b*x[0];d.values[_]=a;}else if("bilinear"===o){var O=Math.floor(T),M=Math.ceil(T),B=T-O;for(N=0;N<p;N++){if((q=p>1?E*(c-1)+N*A:.5*(E+I)*(c-1))<0||q>c-1)for(F=0;F<l;F++){_=F+N*x[2]+D*x[1]+b*x[0];d.values[_]=a;}else{var P=Math.floor(q),L=Math.ceil(q),W=q-P;for(F=0;F<l;F++){var U=g[_=F+P*y[2]+O*y[1]+k*y[0]],V=g[_=F+L*y[2]+O*y[1]+k*y[0]],z=g[_=F+P*y[2]+M*y[1]+k*y[0]],G=U+(V-U)*W,H=z+(g[_=F+L*y[2]+M*y[1]+k*y[0]]-z)*W;_=F+N*x[2]+D*x[1]+b*x[0],d.values[_]=G+(H-G)*B;}}}}else for(N=0;N<p;++N){var q;if((q=p>1?E*(c-1)+N*A:.5*(E+I)*(c-1))<0||q>c-1)for(F=0;F<l;F++){_=F+N*x[2]+D*x[1]+b*x[0];d.values[_]=a;}else{var K=Math.round(q),j=Math.round(T);for(F=0;F<l;F++){var X=F+K*y[2]+j*y[1]+k*y[0],$=F+N*x[2]+D*x[1]+b*x[0];d.values[$]=g[X];}}}}}return d.toTensor()},o.prototype.sparseToDense=function(t,e,n,r){var o=Hr(0,t,n),a=o.sliceRank,i=o.numUpdates,u=o.sliceSize,s=o.strides,c=o.outputSize;return this.scatter(t,e,n,c,u,i,a,s,r,!1)},o.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=Ur(t,e),a=o[0],i=o[1],u=o[2],s=o[3];if(0===i)return In([],a,t.dtype);for(var c=new lt([i,u],t.dtype),l=this.readSync(e.dataId),h=this.readSync(t.dataId),f=0;f<i;f++){for(var p=[],d=0,v=0;v<r;v++){var m=l[f*r+v];d+=m*s[v],p.push(m);}if(d<0||d>=t.size/u)throw new Error("Invalid indices: "+p+" does not index into "+t.shape);for(var g=0;g<u;g++)c.values[f*u+g]=h[d*u+g];}return c.toTensor().reshape(a)},o.prototype.scatterND=function(t,e,n){var r=Hr(0,t,n),o=r.sliceRank,a=r.numUpdates,i=r.sliceSize,u=r.strides,s=r.outputSize,c=Sn(0);return this.scatter(t,e,n,s,i,a,o,u,c,!0)},o.prototype.fill=function(t,e,n){var r=F(n=n||z(e),w(t));return r.fill(e),Nt.makeTensor(r,t,n,this)},o.prototype.onesLike=function(t){if("string"===t.dtype)throw new Error("onesLike is not supported for string tensors");return this.fill(t.shape,1,t.dtype)},o.prototype.zerosLike=function(t){var e=F(t.dtype,w(t.shape));return this.makeOutput(e,t.shape,t.dtype)},o.prototype.linspace=function(t,e,n){return Do(t,e,n)},o.prototype.scatter=function(t,e,n,r,o,a,i,u,s,c){var l=[r/o,o],h=this.readSync(t.dataId),f=this.readSync(e.dataId);if(0===r)return In([],n,e.dtype);var p=new lt(l,e.dtype);p.values.fill(this.readSync(s.dataId)[0]);for(var d=0;d<a;d++){for(var v=[],m=0,g=0;g<i;g++){var y=h[d*i+g];v.push(y),m+=y*u[g];}if(m<0||m>=r/o)throw new Error("Invalid indices: "+v+" does not index into "+n);for(var x=0;x<o;x++)c?p.values[m*o+x]+=f[d*o+x]:p.values[m*o+x]=0===e.rank?f[0]:f[d*o+x];}return p.toTensor().reshape(n)},o}(co);Nt.registerBackend("cpu",function(){return new Sh},1),l({kernelName:"Square",backendName:"cpu",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e.x,o=n;Ih(r,"square");for(var a=o.data.get(r.dataId).values,i=new Float32Array(a.length),u=0;u<a.length;++u){var s=a[u];i[u]=s*s;}return {dataId:o.write(i,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}}),l({kernelName:"Square",backendName:"webgl",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e.x,o=n,a=new iu(r.shape,"return x * x;");return o.runWebGLProgram(a,[r],r.dtype)}});var Ah,Dh=function(){return function(t){this.variableNames=["A"];var e=Ko(),n=t[0],r=t[1];this.outputShape=t,this.userCode="\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+r+".0, "+n+".0);\n\n        vec4 values = "+e.texture2D+"(A, uv);\n        float value;\n        if (depth == 0) {\n          value = values.r;\n        } else if (depth == 1) {\n          value = values.g;\n        } else if (depth == 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    ";}}(),Th=function(){return function(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var e=Ko(),n=t[0],r=t[1];this.outputShape=t,this.userCode="\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n\n        vec4 result = vec4(0.);\n\n        for(int row=0; row<=1; row++) {\n          for(int col=0; col<=1; col++) {\n            texC = coords[1] + row;\n            depth = coords[2] + col;\n\n            vec2 uv = (vec2(texC, texR) + halfCR) /\n                       vec2("+r+".0, "+n+".0);\n            vec4 values = "+e.texture2D+"(A, uv);\n            float value;\n            if (depth == 0) {\n              value = values.r;\n            } else if (depth == 1) {\n              value = values.g;\n            } else if (depth == 2) {\n              value = values.b;\n            } else if (depth == 3) {\n              value = values.a;\n            }\n\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\n          }\n        }\n\n        "+e.output+" = result;\n      }\n    ";}}();l({kernelName:"FromPixels",backendName:"webgl",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=t.attrs,o=e.pixels,i=r.numChannels,u="undefined"!=typeof HTMLVideoElement&&o instanceof HTMLVideoElement,s="undefined"!=typeof HTMLImageElement&&o instanceof HTMLImageElement,c=u?[o.videoWidth,o.videoHeight]:[o.width,o.height],l=c[0],h=c[1],f=[h,l],p=[h,l,i];(s||u)&&(null==Ah&&(Ah=document.createElement("canvas").getContext("2d")),Ah.canvas.width=l,Ah.canvas.height=h,Ah.drawImage(o,0,0,l,h),o=Ah.canvas);var d=n.makeTensorInfo(f,"int32");n.texData.get(d.dataId).usage=Mt.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),o);var v=a().getBool("WEBGL_PACK")?new Th(p):new Dh(p),m=n.runWebGLProgram(v,[d],"int32");return n.disposeData(d.dataId),m}});var Nh=function(){function t(){}return t.prototype.fetch=function(t,e){return fetch(t,e)},t.prototype.now=function(){return performance.now()},t.prototype.encode=function(t,e){if("utf-8"!==e&&"utf8"!==e)throw new Error("Browser's encoder only supports utf-8, but got "+e);return null==this.textEncoder&&(this.textEncoder=new TextEncoder),this.textEncoder.encode(t)},t.prototype.decode=function(t,e){return new TextDecoder(e).decode(t)},t}();a().get("IS_BROWSER")&&a().setPlatform("browser",new 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s,c=Gh(e),l=a.transaction(Yh,"readwrite"),h=l.objectStore(Yh),f=h.put({modelPath:n.modelPath,modelArtifactsInfo:c});f.onsuccess=function(){var o=(s=a.transaction($h,"readwrite")).objectStore($h).put({modelPath:n.modelPath,modelArtifacts:e,modelArtifactsInfo:c});o.onsuccess=function(){return t({modelArtifactsInfo:c})},o.onerror=function(t){var e=(h=l.objectStore(Yh)).delete(n.modelPath);e.onsuccess=function(){return a.close(),r(o.error)},e.onerror=function(t){return a.close(),r(o.error)};};},f.onerror=function(t){return a.close(),r(f.error)},l.oncomplete=function(){null==s?a.close():s.oncomplete=function(){return a.close()};};}},o.onerror=function(t){return r(o.error)};})},t.URL_SCHEME="indexeddb://",t}(),tf=function(t){return a().getBool("IS_BROWSER")&&!Array.isArray(t)&&t.startsWith(Zh.URL_SCHEME)?(e=t.slice(Zh.URL_SCHEME.length),new Zh(e)):null;var e;};Hh.registerSaveRouter(tf),Hh.registerLoadRouter(tf);var ef=function(){function t(){this.indexedDB=Qh();}return t.prototype.listModels=function(){return n(this,void 0,void 0,function(){var t=this;return r(this,function(e){return [2,new Promise(function(e,n){var r=t.indexedDB.open("tensorflowjs",1);r.onupgradeneeded=function(){return Jh(r)},r.onsuccess=function(){var t=r.result,o=t.transaction(Yh,"readonly"),a=o.objectStore(Yh).getAll();a.onsuccess=function(){for(var t={},n=0,r=a.result;n<r.length;n++){var o=r[n];t[o.modelPath]=o.modelArtifactsInfo;}e(t);},a.onerror=function(e){return t.close(),n(a.error)},o.oncomplete=function(){return t.close()};},r.onerror=function(t){return n(r.error)};})]})})},t.prototype.removeModel=function(t){return n(this,void 0,void 0,function(){var e=this;return r(this,function(n){var r;return t=(r=t).startsWith(Zh.URL_SCHEME)?r.slice(Zh.URL_SCHEME.length):r,[2,new Promise(function(n,r){var o=e.indexedDB.open("tensorflowjs",1);o.onupgradeneeded=function(){return Jh(o)},o.onsuccess=function(){var e,a=o.result,i=a.transaction(Yh,"readwrite"),u=i.objectStore(Yh),s=u.get(t);s.onsuccess=function(){if(null==s.result)return a.close(),r(new Error("Cannot find model with path '"+t+"' in IndexedDB."));var o=u.delete(t),i=function(){var o=(e=a.transaction($h,"readwrite")).objectStore($h).delete(t);o.onsuccess=function(){return n(s.result.modelArtifactsInfo)},o.onerror=function(t){return r(s.error)};};o.onsuccess=i,o.onerror=function(t){return i(),a.close(),r(s.error)};},s.onerror=function(t){return a.close(),r(s.error)},i.oncomplete=function(){null==e?a.close():e.oncomplete=function(){return a.close()};};},o.onerror=function(t){return r(o.error)};})]})})},t}();if(a().getBool("IS_BROWSER"))try{Kh.registerManager(Zh.URL_SCHEME,new ef);}catch(t){}var nf="/",rf="tensorflowjs_models",of="info",af="model_topology",uf="weight_specs",sf="weight_data",cf="model_metadata";function lf(t){return {info:[rf,t,of].join(nf),topology:[rf,t,af].join(nf),weightSpecs:[rf,t,uf].join(nf),weightData:[rf,t,sf].join(nf),modelMetadata:[rf,t,cf].join(nf)}}function hf(t){var e=t.split(nf);if(e.length<3)throw new Error("Invalid key format: "+t);return e.slice(1,e.length-1).join(nf)}var ff=function(){function t(t){if(!a().getBool("IS_BROWSER")||void 0===window.localStorage)throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,null==t||!t)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=t,this.keys=lf(this.modelPath);}return t.prototype.save=function(t){return n(this,void 0,void 0,function(){var e,n,o;return r(this,function(r){if(t.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");e=JSON.stringify(t.modelTopology),n=JSON.stringify(t.weightSpecs),o=Gh(t);try{return this.LS.setItem(this.keys.info,JSON.stringify(o)),this.LS.setItem(this.keys.topology,e),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,(a=t.weightData,Wh?Buffer.from(a).toString("base64"):btoa(String.fromCharCode.apply(null,new Uint8Array(a))))),this.LS.setItem(this.keys.modelMetadata,JSON.stringify({format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,userDefinedMetadata:t.userDefinedMetadata})),[2,{modelArtifactsInfo:o}]}catch(t){throw this.LS.removeItem(this.keys.info),this.LS.removeItem(this.keys.topology),this.LS.removeItem(this.keys.weightSpecs),this.LS.removeItem(this.keys.weightData),this.LS.removeItem(this.keys.modelMetadata),new Error("Failed to save model '"+this.modelPath+"' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes="+o.modelTopologyBytes+", weightSpecsBytes="+o.weightSpecsBytes+", weightDataBytes="+o.weightDataBytes+".")}var a;return [2]})})},t.prototype.load=function(){return n(this,void 0,void 0,function(){var t,e,n,o,a,i,u;return r(this,function(r){if(null==(t=JSON.parse(this.LS.getItem(this.keys.info))))throw new Error("In local storage, there is no model with name '"+this.modelPath+"'");if("JSON"!==t.modelTopologyType)throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");if(e={},null==(n=JSON.parse(this.LS.getItem(this.keys.topology))))throw new Error("In local storage, the topology of model '"+this.modelPath+"' is missing.");if(e.modelTopology=n,null==(o=JSON.parse(this.LS.getItem(this.keys.weightSpecs))))throw new Error("In local storage, the weight specs of model '"+this.modelPath+"' are missing.");if(e.weightSpecs=o,null!=(a=this.LS.getItem(this.keys.modelMetadata))&&(i=JSON.parse(a),e.format=i.format,e.generatedBy=i.generatedBy,e.convertedBy=i.convertedBy,e.userDefinedMetadata=i.userDefinedMetadata),null==(u=this.LS.getItem(this.keys.weightData)))throw new Error("In local storage, the binary weight values of model '"+this.modelPath+"' are missing.");return e.weightData=function(t){if(Wh){var e=Buffer.from(t,"base64");return e.buffer.slice(e.byteOffset,e.byteOffset+e.byteLength)}for(var n=atob(t),r=new Uint8Array(n.length),o=0;o<n.length;++o)r.set([n.charCodeAt(o)],o);return r.buffer}(u),[2,e]})})},t.URL_SCHEME="localstorage://",t}(),pf=function(t){return a().getBool("IS_BROWSER")&&!Array.isArray(t)&&t.startsWith(ff.URL_SCHEME)?(e=t.slice(ff.URL_SCHEME.length),new ff(e)):null;var e;};Hh.registerSaveRouter(pf),Hh.registerLoadRouter(pf);var df=function(){function t(){g(a().getBool("IS_BROWSER"),function(){return "Current environment is not a web browser"}),g(void 0!==window.localStorage,function(){return "Current browser does not appear to support localStorage"}),this.LS=window.localStorage;}return t.prototype.listModels=function(){return n(this,void 0,void 0,function(){var t,e,n,o,a,i;return r(this,function(r){for(t={},e=rf+nf,n=nf+of,o=0;o<this.LS.length;++o)(a=this.LS.key(o)).startsWith(e)&&a.endsWith(n)&&(i=hf(a),t[i]=JSON.parse(this.LS.getItem(a)));return [2,t]})})},t.prototype.removeModel=function(t){return n(this,void 0,void 0,function(){var e,n;return r(this,function(r){var o;if(t=(o=t).startsWith(ff.URL_SCHEME)?o.slice(ff.URL_SCHEME.length):o,e=lf(t),null==this.LS.getItem(e.info))throw new Error("Cannot find model at path '"+t+"'");return n=JSON.parse(this.LS.getItem(e.info)),this.LS.removeItem(e.info),this.LS.removeItem(e.topology),this.LS.removeItem(e.weightSpecs),this.LS.removeItem(e.weightData),[2,n]})})},t}();if(a().getBool("IS_BROWSER"))try{Kh.registerManager(ff.URL_SCHEME,new df);}catch(t){}var vf="model",mf=".json",gf=".weights.bin";function yf(t){return new Promise(function(t){return setTimeout(t)}).then(t)}var xf=function(){function t(e){if(!a().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(t.URL_SCHEME)&&(e=e.slice(t.URL_SCHEME.length)),null!=e&&0!==e.length||(e=vf),this.modelTopologyFileName=e+mf,this.weightDataFileName=e+gf;}return t.prototype.save=function(t){return n(this,void 0,void 0,function(){var e,n,o,a,i,u;return r(this,function(r){switch(r.label){case 0:if("undefined"==typeof document)throw new Error("Browser downloads are not supported in this environment since `document` is not present");if(e=window.URL.createObjectURL(new Blob([t.weightData],{type:"application/octet-stream"})),!(t.modelTopology instanceof ArrayBuffer))return [3,1];throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");case 1:return n=[{paths:["./"+this.weightDataFileName],weights:t.weightSpecs}],o={modelTopology:t.modelTopology,format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,weightsManifest:n},a=window.URL.createObjectURL(new Blob([JSON.stringify(o)],{type:"application/json"})),(i=null==this.jsonAnchor?document.createElement("a"):this.jsonAnchor).download=this.modelTopologyFileName,i.href=a,[4,yf(function(){return i.dispatchEvent(new MouseEvent("click"))})];case 2:return r.sent(),null==t.weightData?[3,4]:((u=null==this.weightDataAnchor?document.createElement("a"):this.weightDataAnchor).download=this.weightDataFileName,u.href=e,[4,yf(function(){return u.dispatchEvent(new MouseEvent("click"))})]);case 3:r.sent(),r.label=4;case 4:return [2,{modelArtifactsInfo:Gh(t)}]}})})},t.URL_SCHEME="downloads://",t}(),bf=function(){function t(t){if(null==t||t.length<1)throw new Error("When calling browserFiles, at least 1 file is required, but received "+t);this.files=t;}return t.prototype.load=function(){return n(this,void 0,void 0,function(){var t,e,n=this;return r(this,function(r){return t=this.files[0],e=this.files.slice(1),[2,new Promise(function(r,o){var a=new FileReader;a.onload=function(a){var i=JSON.parse(a.target.result),u=i.modelTopology;if(null!=u){0===e.length&&r({modelTopology:u});var s=i.weightsManifest;if(null!=s){var c;try{c=n.checkManifestAndWeightFiles(s,e);}catch(t){return void o(t)}var l=[],h=[],f=[];s.forEach(function(t){t.paths.forEach(function(t){h.push(t),f.push(null);}),l.push.apply(l,t.weights);}),s.forEach(function(t){t.paths.forEach(function(t){var e=new FileReader;e.onload=function(e){var n=e.target.result,o=h.indexOf(t);f[o]=n,-1===f.indexOf(null)&&r({modelTopology:u,weightSpecs:l,weightData:Vh(f),format:i.format,generatedBy:i.generatedBy,convertedBy:i.convertedBy,userDefinedMetadata:i.userDefinedMetadata});},e.onerror=function(e){return o("Failed to weights data from file of path '"+t+"'.")},e.readAsArrayBuffer(c[t]);});});}else o(new Error("weightManifest field is missing from file "+t.name));}else o(new Error("modelTopology field is missing from file "+t.name));},a.onerror=function(e){return o("Failed to read model topology and weights manifest JSON from file '"+t.name+"'. BrowserFiles supports loading Keras-style tf.Model artifacts only.")},a.readAsText(t);})]})})},t.prototype.checkManifestAndWeightFiles=function(t,e){for(var n=[],r=e.map(function(t){return zh(t.name)}),o={},a=0,i=t;a<i.length;a++){i[a].paths.forEach(function(t){var a=zh(t);if(-1!==n.indexOf(a))throw new Error("Duplicate file basename found in weights manifest: '"+a+"'");if(n.push(a),-1===r.indexOf(a))throw new Error("Weight file with basename '"+a+"' is not provided.");o[t]=e[r.indexOf(a)];});}if(n.length!==e.length)throw new Error("Mismatch in the number of files in weights manifest ("+n.length+") and the number of weight files provided ("+e.length+").");return o},t}();function wf(t,e,n,r){!function(t){g(null!=t&&Array.isArray(t)&&t.length>0,function(){return "promises must be a none empty array"});}(t),function(t,e){g(t>=0&&t<=1,function(){return "Progress fraction must be in range [0, 1], but got startFraction "+t}),g(e>=0&&e<=1,function(){return "Progress fraction must be in range 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function(o,a,i){return void 0===a&&(a=""),n(e,void 0,void 0,function(){var e,n,u,s,c,l,h,f,p,d;return r(this,function(r){switch(r.label){case 0:if(e=o.map(function(){return !1}),n={},u=null!=i?i.map(function(){return !1}):[],s=[],o.forEach(function(t,r){var o=0;t.weights.forEach(function(t){var a="quantization"in t?t.quantization.dtype:t.dtype,c=Mh[a]*w(t.shape),l=function(){e[r]=!0,null==n[r]&&(n[r]=[]),n[r].push({manifestEntry:t,groupOffset:o,sizeBytes:c});};null!=i?i.forEach(function(e,n){e===t.name&&(l(),u[n]=!0);}):l(),s.push(t.name),o+=c;});}),!u.every(function(t){return t}))throw c=i.filter(function(t,e){return !u[e]}),new Error("Could not find weights in manifest with names: "+c.join(", ")+". \nManifest JSON has weights with names: "+s.join(", ")+".");return l=e.reduce(function(t,e,n){return e&&t.push(n),t},[]),h=[],l.forEach(function(t){o[t].paths.forEach(function(t){var e=a+(a.endsWith("/")?"":"/")+t;h.push(e);});}),[4,t(h)];case 1:return f=r.sent(),p={},d=0,l.forEach(function(t){for(var e=o[t].paths.length,r=0,a=0;a<e;a++)r+=f[d+a].byteLength;for(var i=new ArrayBuffer(r),u=new Uint8Array(i),s=0,c=0;c<e;c++){var l=new Uint8Array(f[d+c]);u.set(l,s),s+=l.byteLength;}n[t].forEach(function(t){var e=Ph(i.slice(t.groupOffset,t.groupOffset+t.sizeBytes),[t.manifestEntry]);for(var n in e)p[n]=e[n];}),d+=e;}),[2,p]}})})}}Hh.registerSaveRouter(function(t){return a().getBool("IS_BROWSER")&&!Array.isArray(t)&&t.startsWith(xf.URL_SCHEME)?(e=t.slice(xf.URL_SCHEME.length),void 0===e&&(e="model"),new xf(e)):null;var e;});var Rf=function(){function t(t,e){if(this.DEFAULT_METHOD="POST",null==e&&(e={}),this.weightPathPrefix=e.weightPathPrefix,this.onProgress=e.onProgress,null!=e.fetchFunc?(g("function"==typeof e.fetchFunc,function(){return "Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"}),this.fetch=e.fetchFunc):this.fetch=a().platform.fetch,g(null!=t&&t.length>0,function(){return "URL path for http must not be null, undefined or empty."}),Array.isArray(t)&&g(2===t.length,function(){return "URL paths for http must have a length of 2, (actual length is "+t.length+")."}),this.path=t,null!=e.requestInit&&null!=e.requestInit.body)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=e.requestInit||{};}return t.prototype.save=function(t){return n(this,void 0,void 0,function(){var e,n,o,a;return r(this,function(r){switch(r.label){case 0:if(t.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");return (e=Object.assign({method:this.DEFAULT_METHOD},this.requestInit)).body=new FormData,n=[{paths:["./model.weights.bin"],weights:t.weightSpecs}],o={modelTopology:t.modelTopology,format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,userDefinedMetadata:t.userDefinedMetadata,weightsManifest:n},e.body.append("model.json",new Blob([JSON.stringify(o)],{type:"application/json"}),"model.json"),null!=t.weightData&&e.body.append("model.weights.bin",new Blob([t.weightData],{type:"application/octet-stream"}),"model.weights.bin"),[4,this.fetch(this.path,e)];case 1:if((a=r.sent()).ok)return [2,{modelArtifactsInfo:Gh(t),responses:[a]}];throw new Error("BrowserHTTPRequest.save() failed due to HTTP response status "+a.status+".")}})})},t.prototype.load=function(){return n(this,void 0,void 0,function(){var t,e,n,o,a,i,u,s,c,l,h,f;return r(this,function(r){switch(r.label){case 0:return [4,this.fetch(this.path,this.requestInit)];case 1:if(!(t=r.sent()).ok)throw new Error("Request to "+this.path+" failed with status code "+t.status+". Please verify this URL points to the model JSON of the model to load.");r.label=2;case 2:return r.trys.push([2,4,,5]),[4,t.json()];case 3:return e=r.sent(),[3,5];case 4:throw r.sent(),n="Failed to parse model JSON of response from "+this.path+".",this.path.endsWith(".pb")?n+=" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.":n+=" Please make sure the server is serving valid JSON for this request.",new Error(n);case 5:if(o=e.modelTopology,a=e.weightsManifest,i=e.generatedBy,u=e.convertedBy,s=e.format,c=e.userDefinedMetadata,null==o&&null==a)throw new Error("The JSON from HTTP path "+this.path+" contains neither model topology or manifest for weights.");return null==a?[3,7]:[4,this.loadWeights(a)];case 6:f=r.sent(),l=f[0],h=f[1],r.label=7;case 7:return [2,{modelTopology:o,weightSpecs:l,weightData:h,userDefinedMetadata:c,generatedBy:i,convertedBy:u,format:s}]}})})},t.prototype.loadWeights=function(t){return n(this,void 0,void 0,function(){var e,n,o,a,i,u,s,c,l,h,f;return r(this,function(r){switch(r.label){case 0:for(e=Array.isArray(this.path)?this.path[1]:this.path,n=function(t){var e=t.lastIndexOf("/"),n=t.lastIndexOf("?"),r=t.substring(0,e),o=n>e?t.substring(n):"";return [r+"/",o]}(e),o=n[0],a=n[1],i=this.weightPathPrefix||o,u=[],s=0,c=t;s<c.length;s++)l=c[s],u.push.apply(u,l.weights);return h=[],t.forEach(function(t){t.paths.forEach(function(t){h.push(i+t+a);});}),[4,Cf(h,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress})];case 1:return f=r.sent(),[2,[u,Vh(f)]]}})})},t.URL_SCHEME_REGEX=/^https?:\/\//,t}();function If(t){return null!=t.match(Rf.URL_SCHEME_REGEX)}var kf=function(t,e){if("undefined"==typeof fetch)return null;return (Array.isArray(t)?t.every(function(t){return If(t)}):If(t))?Sf(t,{onProgress:e}):null};function Sf(t,e){return new Rf(t,e)}Hh.registerSaveRouter(kf),Hh.registerLoadRouter(kf);var Af=function(){function t(t){this.modelArtifacts=t;}return t.prototype.load=function(){return n(this,void 0,void 0,function(){return r(this,function(t){return [2,this.modelArtifacts]})})},t}(),Df=function(){function t(t){this.saveHandler=t;}return t.prototype.save=function(t){return n(this,void 0,void 0,function(){return r(this,function(e){return [2,this.saveHandler(t)]})})},t}();var Tf=Object.freeze({browserFiles:function(t){return new bf(t)},browserHTTPRequest:function(t,e){return Sf(t,e)},concatenateArrayBuffers:Vh,decodeWeights:Ph,encodeWeights:function(t,e){return n(this,void 0,void 0,function(){var o,a,i,u,s,c=this;return r(this,function(l){switch(l.label){case 0:for(o=[],a=[],i=Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t),u=function(u){var s=i[u],l=Array.isArray(t)?t[u].tensor:t[s];if("float32"!==l.dtype&&"int32"!==l.dtype&&"bool"!==l.dtype&&"string"!==l.dtype)throw new Error("Unsupported dtype in weight '"+s+"': "+l.dtype);var h={name:s,shape:l.shape,dtype:l.dtype};if("string"===l.dtype){var f=new Promise(function(t){return n(c,void 0,void 0,function(){var e,n,o,a,i,u,s;return r(this,function(r){switch(r.label){case 0:return [4,l.bytes()];case 1:for(e=r.sent(),n=e.reduce(function(t,e){return t+e.length},0)+Bh*e.length,o=new Uint8Array(n),a=0,i=0;i<e.length;i++)u=e[i],s=new Uint8Array(new Uint32Array([u.length]).buffer),o.set(s,a),a+=Bh,o.set(u,a),a+=u.length;return t(o),[2]}})})});a.push(f);}else a.push(l.data());null!=e&&(h.group=e),o.push(h);},s=0;s<i.length;++s)u(s);return [4,Promise.all(a)];case 1:return [2,{data:Lh(l.sent()),specs:o}]}})})},fromMemory:function(t,e,n,r){return 1===arguments.length?null!=t.modelTopology||null!=t.weightSpecs?new Af(t):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new Af({modelTopology:t})):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. 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d=f.div(p.sqrt().add(e.epsilon)).mul(-e.learningRate).add(i);i.assign(d);}}),e.accBeta1.assign(e.accBeta1.mul(e.beta1)),e.accBeta2.assign(e.accBeta2.mul(e.beta2));}),this.incrementIterations();},o.prototype.dispose=function(){this.accBeta1.dispose(),this.accBeta2.dispose(),null!=this.accumulatedFirstMoment&&je(this.accumulatedFirstMoment.map(function(t){return t.variable})),null!=this.accumulatedSecondMoment&&je(this.accumulatedSecondMoment.map(function(t){return t.variable}));},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){var t;return r(this,function(e){switch(e.label){case 0:return t=this.accumulatedFirstMoment.concat(this.accumulatedSecondMoment),[4,this.saveIterations()];case 1:return [2,[e.sent()].concat(t.map(function(t){return {name:t.originalName,tensor:t.variable}}))]}})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){var e,n=this;return r(this,function(r){switch(r.label){case 0:return [4,this.extractIterations(t)];case 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e(o,t),o.prototype.applyGradients=function(t){var e=this,n=Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t);Ke(function(){var r=ac(1,e.accBeta1),o=Gs(-e.learningRate,e.iteration.mul(e.decay).add(1));n.forEach(function(n,a){var i=Nt.registeredVariables[n];null==e.accumulatedFirstMoment[a]&&(e.accumulatedFirstMoment[a]={originalName:n+"/m",variable:Vn(i).variable(!1)}),null==e.accumulatedWeightedInfNorm[a]&&(e.accumulatedWeightedInfNorm[a]={originalName:n+"/v",variable:Vn(i).variable(!1)});var u=Array.isArray(t)?t[a].tensor:t[n];if(null!=u){var s=e.accumulatedFirstMoment[a].variable,c=e.accumulatedWeightedInfNorm[a].variable,l=s.mul(e.beta1).add(u.mul(1-e.beta1)),h=c.mul(e.beta2),f=u.abs(),p=h.maximum(f);s.assign(l),c.assign(p);var d=o.div(r).mul(l.div(p.add(e.epsilon))).add(i);i.assign(d);}}),e.iteration.assign(e.iteration.add(1)),e.accBeta1.assign(e.accBeta1.mul(e.beta1));}),this.incrementIterations();},o.prototype.dispose=function(){this.accBeta1.dispose(),this.iteration.dispose(),null!=this.accumulatedFirstMoment&&je(this.accumulatedFirstMoment.map(function(t){return t.variable})),null!=this.accumulatedWeightedInfNorm&&je(this.accumulatedWeightedInfNorm.map(function(t){return t.variable}));},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){return r(this,function(t){throw new Error("getWeights() is not implemented for Adamax yet.")})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){return r(this,function(t){throw new Error("setWeights() is not implemented for Adamax yet.")})})},o.prototype.getConfig=function(){return {learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}},o.fromConfig=function(t,e){return new t(e.learningRate,e.beta1,e.beta2,e.epsilon,e.decay)},o.className="Adamax",o}(Xf);Lf(Jf);var Zf=function(t){function o(e){var n=t.call(this)||this;return n.learningRate=e,n.setLearningRate(e),n}return e(o,t),o.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var o=Array.isArray(t)?t[r].tensor:t[n];if(null!=o){var a=Nt.registeredVariables[n];Ke(function(){var t=e.c.mul(o).add(a);a.assign(t);});}}),this.incrementIterations();},o.prototype.setLearningRate=function(t){this.learningRate=t,null!=this.c&&this.c.dispose(),this.c=Xe(Sn(-t));},o.prototype.dispose=function(){this.c.dispose();},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){return r(this,function(t){switch(t.label){case 0:return [4,this.saveIterations()];case 1:return [2,[t.sent()]]}})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){return r(this,function(e){switch(e.label){case 0:return 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{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}},o.fromConfig=function(t,e){return new t(e.learningRate,e.momentum,e.useNesterov)},o.className="Momentum",o}(Zf);Lf(tp);var ep=function(t){function o(e,n,r,o,a){void 0===n&&(n=.9),void 0===r&&(r=0),void 0===o&&(o=null),void 0===a&&(a=!1);var i=t.call(this)||this;return i.learningRate=e,i.decay=n,i.momentum=r,i.epsilon=o,i.accumulatedMeanSquares=[],i.accumulatedMoments=[],i.accumulatedMeanGrads=[],i.centered=a,null==o&&(i.epsilon=Nt.backend.epsilon()),i}return e(o,t),o.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var o=Nt.registeredVariables[n];null==e.accumulatedMeanSquares[r]&&(e.accumulatedMeanSquares[r]={originalName:n+"/rms",variable:Ke(function(){return Vn(o).variable(!1)})}),null==e.accumulatedMoments[r]&&(e.accumulatedMoments[r]={originalName:n+"/momentum",variable:Ke(function(){return Vn(o).variable(!1)})}),null==e.accumulatedMeanGrads[r]&&e.centered&&(e.accumulatedMeanGrads[r]={originalName:n+"/mg",variable:Ke(function(){return Vn(o).variable(!1)})});var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var i=e.accumulatedMeanSquares[r].variable,u=e.accumulatedMoments[r].variable;Ke(function(){var t=i.mul(e.decay).add(a.square().mul(1-e.decay));if(e.centered){var n=e.accumulatedMeanGrads[r].variable,s=n.mul(e.decay).add(a.mul(1-e.decay)),c=u.mul(e.momentum).add(a.mul(e.learningRate).div(t.sub(s.square().add(e.epsilon)).sqrt()));i.assign(t),n.assign(s),u.assign(c);var l=o.sub(c);o.assign(l);}else{var h=i.mul(e.decay).add(a.square().mul(1-e.decay));c=u.mul(e.momentum).add(a.mul(e.learningRate).div(h.add(e.epsilon).sqrt()));i.assign(h),u.assign(c);l=o.sub(c);o.assign(l);}});}}),this.incrementIterations();},o.prototype.dispose=function(){null!=this.accumulatedMeanSquares&&je(this.accumulatedMeanSquares.map(function(t){return 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this.throwIfDisposed(),xt.subStrict(this,t)},t.prototype.pow=function(t){return this.throwIfDisposed(),xt.pow(this,t)},t.prototype.powStrict=function(t){return this.throwIfDisposed(),xt.powStrict(this,t)},t.prototype.mul=function(t){return this.throwIfDisposed(),xt.mul(this,t)},t.prototype.mulStrict=function(t){return this.throwIfDisposed(),xt.mulStrict(this,t)},t.prototype.div=function(t){return this.throwIfDisposed(),xt.div(this,t)},t.prototype.divNoNan=function(t){return this.throwIfDisposed(),xt.divNoNan(this,t)},t.prototype.floorDiv=function(t){return this.throwIfDisposed(),xt.floorDiv(this,t)},t.prototype.divStrict=function(t){return this.throwIfDisposed(),xt.divStrict(this,t)},t.prototype.minimum=function(t){return this.throwIfDisposed(),xt.minimum(this,t)},t.prototype.minimumStrict=function(t){return this.throwIfDisposed(),xt.minimumStrict(this,t)},t.prototype.maximum=function(t){return this.throwIfDisposed(),xt.maximum(this,t)},t.prototype.maximumStrict=function(t){return this.throwIfDisposed(),xt.maximumStrict(this,t)},t.prototype.mod=function(t){return this.throwIfDisposed(),xt.mod(this,t)},t.prototype.modStrict=function(t){return this.throwIfDisposed(),xt.modStrict(this,t)},t.prototype.squaredDifferenceStrict=function(t){return this.throwIfDisposed(),xt.squaredDifferenceStrict(this,t)},t.prototype.transpose=function(t){return this.throwIfDisposed(),xt.transpose(this,t)},t.prototype.notEqual=function(t){return this.throwIfDisposed(),xt.notEqual(this,t)},t.prototype.notEqualStrict=function(t){return this.throwIfDisposed(),xt.notEqualStrict(this,t)},t.prototype.less=function(t){return this.throwIfDisposed(),xt.less(this,t)},t.prototype.lessStrict=function(t){return this.throwIfDisposed(),xt.lessStrict(this,t)},t.prototype.equal=function(t){return this.throwIfDisposed(),xt.equal(this,t)},t.prototype.equalStrict=function(t){return this.throwIfDisposed(),xt.equalStrict(this,t)},t.prototype.lessEqual=function(t){return this.throwIfDisposed(),xt.lessEqual(this,t)},t.prototype.lessEqualStrict=function(t){return this.throwIfDisposed(),xt.lessEqualStrict(this,t)},t.prototype.greater=function(t){return this.throwIfDisposed(),xt.greater(this,t)},t.prototype.greaterStrict=function(t){return this.throwIfDisposed(),xt.greaterStrict(this,t)},t.prototype.greaterEqual=function(t){return this.throwIfDisposed(),xt.greaterEqual(this,t)},t.prototype.greaterEqualStrict=function(t){return this.throwIfDisposed(),xt.greaterEqualStrict(this,t)},t.prototype.logicalAnd=function(t){return this.throwIfDisposed(),xt.logicalAnd(this,t)},t.prototype.logicalOr=function(t){return this.throwIfDisposed(),xt.logicalOr(this,t)},t.prototype.logicalNot=function(){return this.throwIfDisposed(),xt.logicalNot(this)},t.prototype.logicalXor=function(t){return this.throwIfDisposed(),xt.logicalXor(this,t)},t.prototype.where=function(t,e){return this.throwIfDisposed(),xt.where(t,this,e)},t.prototype.neg=function(){return this.throwIfDisposed(),xt.neg(this)},t.prototype.ceil=function(){return this.throwIfDisposed(),xt.ceil(this)},t.prototype.floor=function(){return this.throwIfDisposed(),xt.floor(this)},t.prototype.sign=function(){return this.throwIfDisposed(),xt.sign(this)},t.prototype.isNaN=function(){return this.throwIfDisposed(),xt.isNaN(this)},t.prototype.isInf=function(){return this.throwIfDisposed(),xt.isInf(this)},t.prototype.isFinite=function(){return this.throwIfDisposed(),xt.isFinite(this)},t.prototype.exp=function(){return this.throwIfDisposed(),xt.exp(this)},t.prototype.expm1=function(){return this.throwIfDisposed(),xt.expm1(this)},t.prototype.log=function(){return this.throwIfDisposed(),xt.log(this)},t.prototype.log1p=function(){return this.throwIfDisposed(),xt.log1p(this)},t.prototype.sqrt=function(){return this.throwIfDisposed(),xt.sqrt(this)},t.prototype.rsqrt=function(){return this.throwIfDisposed(),xt.rsqrt(this)},t.prototype.square=function(){return this.throwIfDisposed(),xt.square(this)},t.prototype.reciprocal=function(){return this.throwIfDisposed(),xt.reciprocal(this)},t.prototype.abs=function(){return this.throwIfDisposed(),xt.abs(this)},t.prototype.clipByValue=function(t,e){return this.throwIfDisposed(),xt.clipByValue(this,t,e)},t.prototype.relu=function(){return this.throwIfDisposed(),xt.relu(this)},t.prototype.relu6=function(){return this.throwIfDisposed(),xt.relu6(this)},t.prototype.elu=function(){return this.throwIfDisposed(),xt.elu(this)},t.prototype.selu=function(){return this.throwIfDisposed(),xt.selu(this)},t.prototype.leakyRelu=function(t){return void 0===t&&(t=.2),this.throwIfDisposed(),xt.leakyRelu(this,t)},t.prototype.prelu=function(t){return this.throwIfDisposed(),xt.prelu(this,t)},t.prototype.sigmoid=function(){return this.throwIfDisposed(),xt.sigmoid(this)},t.prototype.logSigmoid=function(){return this.throwIfDisposed(),xt.logSigmoid(this)},t.prototype.softplus=function(){return this.throwIfDisposed(),xt.softplus(this)},t.prototype.zerosLike=function(){return this.throwIfDisposed(),xt.zerosLike(this)},t.prototype.onesLike=function(){return this.throwIfDisposed(),xt.onesLike(this)},t.prototype.sin=function(){return this.throwIfDisposed(),xt.sin(this)},t.prototype.cos=function(){return this.throwIfDisposed(),xt.cos(this)},t.prototype.tan=function(){return this.throwIfDisposed(),xt.tan(this)},t.prototype.asin=function(){return this.throwIfDisposed(),xt.asin(this)},t.prototype.acos=function(){return this.throwIfDisposed(),xt.acos(this)},t.prototype.atan=function(){return this.throwIfDisposed(),xt.atan(this)},t.prototype.sinh=function(){return this.throwIfDisposed(),xt.sinh(this)},t.prototype.cosh=function(){return this.throwIfDisposed(),xt.cosh(this)},t.prototype.tanh=function(){return this.throwIfDisposed(),xt.tanh(this)},t.prototype.asinh=function(){return this.throwIfDisposed(),xt.asinh(this)},t.prototype.acosh=function(){return this.throwIfDisposed(),xt.acosh(this)},t.prototype.atanh=function(){return this.throwIfDisposed(),xt.atanh(this)},t.prototype.erf=function(){return this.throwIfDisposed(),xt.erf(this)},t.prototype.round=function(){return this.throwIfDisposed(),xt.round(this)},t.prototype.step=function(t){return void 0===t&&(t=0),this.throwIfDisposed(),xt.step(this,t)},t.prototype.softmax=function(t){return void 0===t&&(t=-1),this.throwIfDisposed(),xt.softmax(this,t)},t.prototype.logSoftmax=function(t){return void 0===t&&(t=-1),this.throwIfDisposed(),xt.logSoftmax(this,t)},t.prototype.resizeBilinear=function(t,e){return void 0===e&&(e=!1),this.throwIfDisposed(),xt.image.resizeBilinear(this,t,e)},t.prototype.resizeNearestNeighbor=function(t,e){return void 0===e&&(e=!1),this.throwIfDisposed(),xt.image.resizeNearestNeighbor(this,t,e)},t.prototype.conv1d=function(t,e,n,r,o,a){return void 0===r&&(r="NWC"),void 0===o&&(o=1),this.throwIfDisposed(),xt.conv1d(this,t,e,n,r,o,a)},t.prototype.conv2d=function(t,e,n,r,o,a){return void 0===r&&(r="NHWC"),void 0===o&&(o=[1,1]),this.throwIfDisposed(),xt.conv2d(this,t,e,n,r,o,a)},t.prototype.conv2dTranspose=function(t,e,n,r,o){return this.throwIfDisposed(),xt.conv2dTranspose(this,t,e,n,r,o)},t.prototype.depthwiseConv2D=function(t,e,n,r,o,a){return void 0===r&&(r="NHWC"),void 0===o&&(o=[1,1]),this.throwIfDisposed(),xt.depthwiseConv2d(this,t,e,n,r,o,a)},t.prototype.separableConv2d=function(t,e,n,r,o,a){return void 0===o&&(o=[1,1]),void 0===a&&(a="NHWC"),this.throwIfDisposed(),xt.separableConv2d(this,t,e,n,r,o,a)},t.prototype.avgPool=function(t,e,n,r){return this.throwIfDisposed(),xt.avgPool(this,t,e,n,r)},t.prototype.maxPool=function(t,e,n,r){return this.throwIfDisposed(),xt.maxPool(this,t,e,n,r)},t.prototype.localResponseNormalization=function(t,e,n,r){return void 0===t&&(t=5),void 0===e&&(e=1),void 0===n&&(n=1),void 0===r&&(r=.5),xt.localResponseNormalization(this,t,e,n,r)},t.prototype.pool=function(t,e,n,r,o){return this.throwIfDisposed(),xt.pool(this,t,e,n,r,o)},t.prototype.variable=function(t,e,n){return void 0===t&&(t=!0),this.throwIfDisposed(),yt().makeVariable(this,t,e,n)},t.prototype.unsortedSegmentSum=function(t,e){return this.throwIfDisposed(),xt.unsortedSegmentSum(this,t,e)},t.prototype.batchToSpaceND=function(t,e){return this.throwIfDisposed(),xt.batchToSpaceND(this,t,e)},t.prototype.spaceToBatchND=function(t,e){return this.throwIfDisposed(),xt.spaceToBatchND(this,t,e)},t.prototype.topk=function(t,e){return void 0===t&&(t=1),void 0===e&&(e=!0),this.throwIfDisposed(),xt.topk(this,t,e)},t.prototype.stridedSlice=function(t,e,n,r,o,a,i,s){return void 0===r&&(r=0),void 0===o&&(o=0),void 0===a&&(a=0),void 0===i&&(i=0),void 0===s&&(s=0),this.throwIfDisposed(),xt.stridedSlice(this,t,e,n,r,o,a,i,s)},t.prototype.depthToSpace=function(t,e){return this.throwIfDisposed(),xt.depthToSpace(this,t,e)},t.prototype.fft=function(){return this.throwIfDisposed(),xt.spectral.fft(this)},t.prototype.ifft=function(){return this.throwIfDisposed(),xt.spectral.ifft(this)},t.prototype.rfft=function(){return this.throwIfDisposed(),xt.spectral.rfft(this)},t.prototype.irfft=function(){return this.throwIfDisposed(),xt.spectral.irfft(this)},t}();Object.defineProperty(wt,Symbol.hasInstance,{value:function(t){return !!t&&null!=t.dataId&&null!=t.shape&&null!=t.dtype}});var Ct,Et,Rt,It,kt,St=function(t){function n(e,n,r,o){var a=t.call(this,e.shape,e.dtype,e.dataId,o)||this;return a.trainable=n,a.name=r,a}return e(n,t),n.prototype.assign=function(t){if(t.dtype!==this.dtype)throw new Error("dtype of the new value ("+t.dtype+") and previous value ("+this.dtype+") must match");if(!S(t.shape,this.shape))throw new Error("shape of the new value ("+t.shape+") and previous value ("+this.shape+") must match");yt().disposeTensor(this),this.dataId=t.dataId,yt().incRef(this,null);},n.prototype.dispose=function(){yt().disposeVariable(this),this.isDisposedInternal=!0;},n}(wt);Object.defineProperty(St,Symbol.hasInstance,{value:function(t){return t instanceof wt&&null!=t.assign&&t.assign instanceof Function}}),function(t){t.R0="R0",t.R1="R1",t.R2="R2",t.R3="R3",t.R4="R4",t.R5="R5",t.R6="R6";}(Ct||(Ct={})),function(t){t.float32="float32",t.int32="int32",t.bool="int32",t.complex64="complex64";}(Et||(Et={})),function(t){t.float32="float32",t.int32="int32",t.bool="bool",t.complex64="complex64";}(Rt||(Rt={})),function(t){t.float32="float32",t.int32="float32",t.bool="float32",t.complex64="complex64";}(It||(It={})),function(t){t.float32="complex64",t.int32="complex64",t.bool="complex64",t.complex64="complex64";}(kt||(kt={}));var At={float32:It,int32:Et,bool:Rt,complex64:kt};function Dt(t,e){if("string"===t||"string"===e){if("string"===t&&"string"===e)return "string";throw new Error("Can not upcast "+t+" with "+e)}return At[t][e]}function Tt(t){return Dt(t,"int32")}function Nt(t,e){if(t.dtype===e.dtype)return [t,e];var n=Dt(t.dtype,e.dtype);return [t.cast(n),e.cast(n)]}function Ft(t,e){C(t.dtype===e.dtype,(function(){return "The dtypes of the first("+t.dtype+") and second("+e.dtype+") input must match"}));}function _t(t){var e=[];return function t(e,n,r){if(null==e)return;if(e instanceof wt)return void n.push(e);if(o=e,!Array.isArray(o)&&"object"!=typeof o)return;var o;var a=e;for(var i in a){var s=a[i];r.has(s)||(r.add(s),t(s,n,r));}}(t,e,new Set),e}var Ot,Mt=Object.freeze({makeTypesMatch:Nt,assertTypesMatch:Ft,isTensorInList:function(t,e){return e.some((function(e){return e.id===t.id}))},getTensorsInContainer:_t}),Bt=function(){function t(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null};}return t.prototype.dispose=function(){for(var t in this.registeredVariables)this.registeredVariables[t].dispose();},t}(),Pt=function(){function t(t){this.ENV=t,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Bt;}return t.prototype.ready=function(){return n(this,void 0,void 0,(function(){var t,e,n;return r(this,(function(r){switch(r.label){case 0:if(null!=this.pendingBackendInit)return [2,this.pendingBackendInit.then((function(){}))];if(null!=this.backendInstance)return [2];t=this.getSortedBackends(),e=0,r.label=1;case 1:return e<t.length?(n=t[e],[4,this.initializeBackend(n).success]):[3,5];case 2:return r.sent()?[4,this.setBackend(n)]:[3,4];case 3:return r.sent(),[2];case 4:return e++,[3,1];case 5:throw new Error("Could not initialize any backends, all backend initializations failed.")}}))}))},Object.defineProperty(t.prototype,"backend",{get:function(){if(null!=this.pendingBackendInit)throw new Error("Backend '"+this.backendName+"' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods");if(null==this.backendInstance){var t=this.initializeBackendsAndReturnBest(),e=t.name;if(t.asyncInit)throw new Error("The highest priority backend '"+e+"' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods");this.setBackend(e);}return this.backendInstance},enumerable:!0,configurable:!0}),t.prototype.backendNames=function(){return Object.keys(this.registryFactory)},t.prototype.findBackend=function(t){if(!(t in this.registry)){if(!(t in this.registryFactory))return null;if(this.initializeBackend(t).asyncInit)return null}return this.registry[t]},t.prototype.findBackendFactory=function(t){return t in this.registryFactory?this.registryFactory[t].factory:null},t.prototype.registerBackend=function(t,e,n){return void 0===n&&(n=1),t in this.registryFactory?(console.warn(t+" backend was already registered. Reusing existing backend factory."),!1):(this.registryFactory[t]={factory:e,priority:n},!0)},t.prototype.setBackend=function(t){return n(this,void 0,void 0,(function(){var e,n,o;return r(this,(function(r){switch(r.label){case 0:if(null==this.registryFactory[t])throw new Error("Backend name '"+t+"' not found in registry");return this.backendName=t,null!=this.registry[t]?[3,4]:(this.backendInstance=null,e=this.initializeBackend(t),n=e.success,e.asyncInit?[4,n]:[3,2]);case 1:return o=r.sent(),[3,3];case 2:o=n,r.label=3;case 3:if(!o)return [2,!1];r.label=4;case 4:return this.backendInstance=this.registry[t],this.setupRegisteredKernels(),this.profiler=new ut(this.backendInstance),[2,!0]}}))}))},t.prototype.setupRegisteredKernels=function(){var t=this;f(this.backendName).forEach((function(e){null!=e.setupFunc&&e.setupFunc(t.backendInstance);}));},t.prototype.disposeRegisteredKernels=function(t){var e=this;f(t).forEach((function(n){null!=n.disposeFunc&&n.disposeFunc(e.registry[t]);}));},t.prototype.initializeBackend=function(t){var e=this,n=this.registryFactory[t];if(null==n)throw new Error("Cannot initialize backend "+t+", no registration found.");try{var r=n.factory();if(Promise.resolve(r)===r){var o=++this.pendingBackendInitId,a=r.then((function(n){return !(o<e.pendingBackendInitId)&&(e.registry[t]=n,e.pendingBackendInit=null,!0)})).catch((function(n){return !(o<e.pendingBackendInitId)&&(e.pendingBackendInit=null,console.warn("Initialization of backend "+t+" failed"),console.warn(n.stack||n.message),!1)}));return this.pendingBackendInit=a,{success:a,asyncInit:!0}}return this.registry[t]=r,{success:!0,asyncInit:!1}}catch(e){return console.warn("Initialization of backend "+t+" failed"),console.warn(e.stack||e.message),{success:!1,asyncInit:!1}}},t.prototype.removeBackend=function(t){if(!(t in this.registryFactory))throw new Error(t+" backend not found in registry");this.backendName===t&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null);},t.prototype.getSortedBackends=function(){var t=this;if(0===Object.keys(this.registryFactory).length)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((function(e,n){return t.registryFactory[n].priority-t.registryFactory[e].priority}))},t.prototype.initializeBackendsAndReturnBest=function(){for(var t=this.getSortedBackends(),e=0;e<t.length;e++){var n=t[e],r=this.initializeBackend(n),o=r.success,a=r.asyncInit;if(a||o)return {name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")},t.prototype.moveData=function(t,e){var n=this.state.tensorInfo.get(e),r=n.backend,o=this.readSync(e);r.disposeData(e),n.backend=t,t.move(e,o,n.shape,n.dtype),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++;},t.prototype.tidy=function(t,e){var n,r=this,o=null;if(null==e){if("function"!=typeof t)throw new Error("Please provide a function to tidy()");e=t;}else {if("string"!=typeof t&&!(t instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if("function"!=typeof e)throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");o=t;}return this.scopedRun((function(){return r.startScope(o)}),(function(){return r.endScope(n)}),(function(){return (n=e())instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n}))},t.prototype.scopedRun=function(t,e,n){t();try{var r=n();return e(),r}catch(t){throw e(),t}},t.prototype.nextTensorId=function(){return t.nextTensorId++},t.prototype.nextVariableId=function(){return t.nextVariableId++},t.prototype.clone=function(t){var e=this.makeTensorFromDataId(t.dataId,t.shape,t.dtype),n={x:t};return this.addTapeNode(this.state.activeScope.name,n,[e],(function(t){return {x:function(){return t.toFloat()}}}),[]),e},t.prototype.runKernel=function(t,e,n,r,o){return this.runKernelFunc(null,e,null,t,n,r,o)},t.prototype.shouldCheckForMemLeaks=function(){return this.ENV.getBool("IS_TEST")},t.prototype.checkKernelForMemLeak=function(t,e,n){var r=this.backend.numDataIds(),o=0;n.forEach((function(t){o+="complex64"===t.dtype?3:1;}));var a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-e-o-a;if(i>0)throw new Error("Backend '"+this.backendName+"' has an internal memory leak ("+i+" data ids) after running '"+t+"'")},t.prototype.runKernelFunc=function(t,e,n,r,o,a,i){var s,u=this;void 0===a&&(a=[]),void 0===i&&(i=[]);var c=[],h=this.isTapeOn();null==r&&(r=null!=this.state.activeScope?this.state.activeScope.name:"");var f,d=function(t){h&&(c=t.map((function(t){return u.keep(u.clone(t))})));},p=this.state.numBytes,v=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);var m,g=l(r,this.backendName);return f=null!=g?function(){var t=u.backend.numDataIds();m=g.kernelFunc({inputs:e,attrs:o,backend:u.backend});var n=Array.isArray(m)?m:[m];u.shouldCheckForMemLeaks()&&u.checkKernelForMemLeak(r,t,n);var s=n.map((function(t){var e=t.dataId,n=t.shape,r=t.dtype;return u.makeTensorFromDataId(e,n,r)})),c=s.filter((function(t,e){return i[e]}));return d((a||[]).slice().concat(c)),s}:function(){var e=u.backend.numDataIds();m=u.tidy((function(){return t(u.backend,d)}));var n=Array.isArray(m)?m:[m];return u.shouldCheckForMemLeaks()&&u.checkKernelForMemLeak(r,e,n),n},this.scopedRun((function(){return u.state.kernelDepth++}),(function(){return u.state.kernelDepth--}),(function(){s=u.ENV.getBool("DEBUG")?u.profiler.profileKernel(r,e,(function(){return f()})):f();})),h&&this.addTapeNode(r,e,s,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:r,bytesAdded:this.state.numBytes-p,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-v,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(e).map((function(t){return e[t].shape})),outputShapes:s.map((function(t){return t.shape}))}),Array.isArray(m)?s:s[0]},t.prototype.makeTensor=function(t,e,n,r){if(null==t)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;var o=t;"string"===n&&H(t[0])&&(o=t.map((function(t){return rt(t)})));var a=r.write(o,e,n),i=new wt(e,n,a,this.nextTensorId());if(this.incRef(i,r),"string"===n){var s=this.state.tensorInfo.get(a),u=G(o);this.state.numBytes+=u-s.bytes,s.bytes=u;}return i},t.prototype.makeTensorFromDataId=function(t,e,n,r){var o=new wt(e,n=n||"float32",t,this.nextTensorId());return this.incRef(o,r),o},t.prototype.makeVariable=function(t,e,n,r){void 0===e&&(e=!0),n=n||this.nextVariableId().toString(),null!=r&&r!==t.dtype&&(t=t.asType(r));var o=new St(t,e,n,this.nextTensorId());if(null!=this.state.registeredVariables[o.name])throw new Error("Variable with name "+o.name+" was already registered");return this.state.registeredVariables[o.name]=o,this.incRef(o,this.backend),o},t.prototype.incRef=function(t,e){var n=this.state.tensorInfo.has(t.dataId)?this.state.tensorInfo.get(t.dataId).refCount:0;if(this.state.numTensors++,"string"===t.dtype&&this.state.numStringTensors++,0===n){this.state.numDataBuffers++;var r=0;"complex64"!==t.dtype&&"string"!==t.dtype&&(r=t.size*z(t.dtype)),this.state.tensorInfo.set(t.dataId,{backend:e||this.backend,dtype:t.dtype,shape:t.shape,bytes:r,refCount:0}),this.state.numBytes+=r;}this.state.tensorInfo.get(t.dataId).refCount++,t instanceof St||this.track(t);},t.prototype.disposeTensor=function(t){if(this.state.tensorInfo.has(t.dataId)){this.state.numTensors--,"string"===t.dtype&&this.state.numStringTensors--;var e=this.state.tensorInfo.get(t.dataId);e.refCount<=1?("complex64"!==t.dtype&&(this.state.numBytes-=e.bytes),this.state.numDataBuffers--,e.backend.disposeData(t.dataId),this.state.tensorInfo.delete(t.dataId)):this.state.tensorInfo.get(t.dataId).refCount--;}},t.prototype.disposeVariables=function(){for(var t in this.state.registeredVariables){var e=this.state.registeredVariables[t];this.disposeVariable(e);}},t.prototype.disposeVariable=function(t){this.disposeTensor(t),null!=this.state.registeredVariables[t.name]&&delete this.state.registeredVariables[t.name];},t.prototype.memory=function(){var t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(t.unreliable=!0,null==t.reasons&&(t.reasons=[]),t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),t},t.prototype.profile=function(t){return n(this,void 0,void 0,(function(){var e,n;return r(this,(function(r){return this.state.profiling=!0,e=this.state.numBytes,n=this.state.numTensors,this.state.activeProfile.kernels=[],this.state.activeProfile.result=t(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max.apply(Math,this.state.activeProfile.kernels.map((function(t){return t.totalBytesSnapshot}))),this.state.activeProfile.newBytes=this.state.numBytes-e,this.state.activeProfile.newTensors=this.state.numTensors-n,[2,this.state.activeProfile]}))}))},t.prototype.isTapeOn=function(){return this.state.gradientDepth>0&&0===this.state.kernelDepth},t.prototype.addTapeNode=function(t,e,n,r,o){var a=this,i={id:this.state.nextTapeNodeId++,kernelName:t,inputs:e,outputs:n,saved:o},s=h(t);null!=s&&(r=s.gradFunc),null!=r&&(i.gradient=function(t){return t=t.map((function(t,e){if(null==t){var r=n[e],o=tt(r.size,r.dtype);return a.makeTensor(o,r.shape,r.dtype)}return t})),r(t.length>1?t:t[0],o)}),this.state.activeTape.push(i);},t.prototype.keep=function(t){return t.kept=!0,t},t.prototype.startTape=function(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++;},t.prototype.endTape=function(){this.state.gradientDepth--;},t.prototype.startScope=function(t){var e={track:[],name:"unnamed scope",id:this.state.nextScopeId++};t&&(e.name=t),this.state.scopeStack.push(e),this.state.activeScope=e;},t.prototype.endScope=function(t){for(var e=this,n=_t(t),r=new Set(n.map((function(t){return t.id}))),o=0;o<this.state.activeScope.track.length;o++){var a=this.state.activeScope.track[o];a.kept||r.has(a.id)||a.dispose();}var i=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],n.forEach((function(t){t.kept||t.scopeId!==i.id||e.track(t);}));},t.prototype.gradients=function(t,e,n,r){var o=this;if(void 0===r&&(r=!1),C(e.length>0,(function(){return "gradients() received an empty list of xs."})),null!=n&&"float32"!==n.dtype)throw new Error("dy must have 'float32' dtype, but has '"+n.dtype+"'");var a=this.scopedRun((function(){return o.startTape()}),(function(){return o.endTape()}),(function(){return o.tidy("forward",t)}));C(a instanceof wt,(function(){return "The result y returned by f() must be a tensor."}));var i=function(t,e,n){for(var r={},o={},a=0;a<e.length;a++)r[e[a].id]=!0;for(a=0;a<t.length;a++){var i=(p=t[a]).inputs;for(var s in i){for(var u=i[s],c=!1,l=0;l<e.length;l++)if(r[u.id]){p.outputs.forEach((function(t){return r[t.id]=!0})),c=!0,o[p.id]=!0;break}if(c)break}}var h={};h[n.id]=!0;var f={};for(a=t.length-1;a>=0;a--)for(i=(p=t[a]).inputs,l=0;l<p.outputs.length;l++)if(h[p.outputs[l].id]){for(var s in i)h[i[s].id]=!0,f[p.id]=!0;break}var d=[];for(a=0;a<t.length;a++){var p;if(o[(p=t[a]).id]&&f[p.id]){var v={};for(var s in p.inputs){var m=p.inputs[s];r[m.id]&&(v[s]=m);}var g=Object.assign({},p);g.inputs=v,g.outputs=p.outputs,d.push(g);}}return d}(this.state.activeTape,e,a);if(!r&&0===i.length&&e.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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The gradient of input '"+e+"' has shape '"+r.shape+"', which does not match the shape of the input '"+a.shape+"'");if(null==t[a.id])t[a.id]=r;else {var s=t[a.id];t[a.id]=s.add(r),s.dispose();}};for(var u in o.inputs)s(u);},o=e.length-1;o>=0;o--)r(o);}(s,i,(function(t){return o.tidy(t)}));var u=e.map((function(t){return s[t.id]}));return 0===o.state.gradientDepth&&(o.state.activeTape.forEach((function(t){for(var e=0,n=t.saved;e<n.length;e++){n[e].dispose();}})),o.state.activeTape=null),{value:a,grads:u}}))},t.prototype.customGrad=function(t){var e=this;return C(X(t),(function(){return "The f passed in customGrad(f) must be a function."})),function(){for(var n,r=[],o=0;o<arguments.length;o++)r[o]=arguments[o];C(r.every((function(t){return t instanceof wt})),(function(){return "The args passed in customGrad(f)(x1, x2,...) must all be tensors"}));var a={};return r.forEach((function(t,e){a[e]=t;})),e.runKernelFunc((function(e,o){return C((n=t.apply(void 0,r.concat([o]))).value instanceof wt,(function(){return "The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"})),C(X(n.gradFunc),(function(){return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."})),n.value}),a,(function(t,e){var o=n.gradFunc(t,e),a=Array.isArray(o)?o:[o];C(a.length===r.length,(function(){return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."})),C(a.every((function(t){return t instanceof wt})),(function(){return "The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors."}));var i={};return a.forEach((function(t,e){i[e]=function(){return t};})),i}))}},t.prototype.readSync=function(t){return this.state.tensorInfo.get(t).backend.readSync(t)},t.prototype.read=function(t){return this.state.tensorInfo.get(t).backend.read(t)},t.prototype.time=function(t){return n(this,void 0,void 0,(function(){var e,n;return r(this,(function(r){switch(r.label){case 0:return e=et(),[4,this.backend.time(t)];case 1:return (n=r.sent()).wallMs=et()-e,[2,n]}}))}))},t.prototype.track=function(t){return null!=this.state.activeScope&&(t.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(t)),t},Object.defineProperty(t.prototype,"registeredVariables",{get:function(){return this.state.registeredVariables},enumerable:!0,configurable:!0}),t.prototype.reset=function(){for(var t in this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new Bt,this.registry)this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null;},t.nextTensorId=0,t.nextVariableId=0,t}();var Lt=function(){var t=function(){if(null==Ot){var t=void 0;if("undefined"!=typeof window)t=window;else if("undefined"!=typeof global)t=global;else if("undefined"!=typeof process)t=process;else {if("undefined"==typeof self)throw new Error("Could not find a global object");t=self;}Ot=t;}return Ot}();if(null==t._tfengine){var e=new o(t);t._tfengine=new Pt(e);}return function(t){s=t;}(t._tfengine.ENV),yt=function(){return t._tfengine},t._tfengine}();function Wt(){return "undefined"!=typeof window&&null!=window.document||"undefined"!=typeof WorkerGlobalScope}var Ut=i();Ut.registerFlag("DEBUG",(function(){return !1}),(function(t){t&&console.warn("Debugging mode is ON. 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a=1;a<t.length;++a)a<=e.length?r?o.push(e[a-1]*t[a]):o.push(t[a]/e[a-1]):o.push(t[a]);return o}function qr(t,e){for(var n=[0],r=0;r<e;++r)n.push(t[r][0]);return n}function Kr(t,e,n){for(var r=t.slice(0,1),o=0;o<n;++o)r.push(t[o+1]-e[o][0]-e[o][1]);return r}function jr(t,e){if(t.rank<1)throw new Error("tf.gatherND() expects the input to be rank 1 or higher, but the rank was "+t.rank+".");if(e.rank<1)throw new Error("tf.gatherND() expects the indices to be rank 1 or higher, but the rank was "+e.rank+".");if("int32"!==e.dtype)throw new Error("tf.gatherND() expects the indices to be int32 type, but the dtype was "+e.dtype+".");if(e.shape[e.rank-1]>t.rank)throw new Error("index innermost dimension length must be <= tensor rank; saw: "+e.shape[e.rank-1]+" vs. "+t.rank);if(0===t.size)throw new Error("Requested more than 0 entries, but input is empty. 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Uo=Object.freeze({castTensor:Po,reshapeTensor:Lo,linspaceImpl:Wo,upcastType:Dt,axesAreInnerMostDims:yn,combineLocations:xn,computeOutAndReduceShapes:bn,expandShapeToKeepDim:wn,assertAxesAreInnerMostDims:Cn,getAxesPermutation:En,getUndoAxesPermutation:Rn,getInnerMostAxes:In,getBroadcastDims:Co,getReductionAxes:Eo,assertAndGetBroadcastShape:Ro,assertParamsConsistent:kn,computeOutShape:Sn,computePool2DInfo:Io,computePool3DInfo:ko,computeConv2DInfo:So,computeConv3DInfo:Ao,computeDefaultPad:Do,tupleValuesAreOne:Oo,eitherStridesOrDilationsAreOne:Mo,convertConv2DDataFormat:Bo,PARALLELIZE_THRESHOLD:Yr,computeOptimalWindowSize:$r});function Vo(t,e){if(t.length!==e.length)throw new Error("Cannot merge real and imag arrays of different lengths. real:"+t.length+", imag: "+e.length+".");for(var n=new Float32Array(2*t.length),r=0;r<n.length;r+=2)n[r]=t[r/2],n[r+1]=e[r/2];return n}function zo(t,e){return {real:t[2*e],imag:t[2*e+1]}}function Go(t,e,n,r){t[2*r]=e,t[2*r+1]=n;}function Ho(t,e,n){var r=(n?2:-2)*Math.PI*(t/e);return {real:Math.cos(r),imag:Math.sin(r)}}function qo(t,e,n){var r=function(t,e,n){return function(t,e,n){var r=0,o=t.length,a=0,i=!1;for(;r<o;){var s=n(e,t[a=r+(o-r>>>1)]);s>0?r=a+1:(o=a,i=!s);}return i?r:-r-1}(t,e,n||Ko)}(t,e,n),o=r<0?-(r+1):r;t.splice(o,0,e);}function Ko(t,e){return t>e?1:t<e?-1:0}function jo(t,e,n,r,o){return Yo(t,e,n,r,o,0).selectedIndices}function Xo(t,e,n,r,o,a){var i=Yo(t,e,n,r,o,a);return i.numValidOutputs.dispose(),{selectedIndices:i.selectedIndices,selectedScores:i.selectedScores}}function Yo(t,e,n,r,o,a,i,s){void 0===s&&(s=!1);for(var u=Array.from(e).map((function(t,e){return {score:t,boxIndex:e,suppressBeginIndex:0}})).filter((function(t){return t.score>o})).sort(Jo),c=a>0?-.5/a:0,l=[],h=[];l.length<n&&u.length>0;){var f=u.pop(),d=f.score,p=f.boxIndex,v=f.suppressBeginIndex;if(d<o)break;for(var m=!1,g=l.length-1;g>=v;--g){var 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fa(t,e,n,r){var o=[];t.forEach((function(t){var e=k(t.shapeInfo.logicalShape);t.shapeInfo.isUniform?o.push("uniform float "+t.name+(e>1?"["+e+"]":"")+";"):(o.push("uniform sampler2D "+t.name+";"),o.push("uniform int offset"+t.name+";"));}));var a,i,s=o.join("\n"),u=t.map((function(t){return function(t,e,n){void 0===n&&(n=!1);var r="";r+=n?pa(t):da(t);var o=t.shapeInfo.logicalShape,a=e.logicalShape;o.length<=a.length&&(r+=n?function(t,e){var n,r=t.name,o=r.charAt(0).toUpperCase()+r.slice(1),a="get"+o+"AtOutCoords",i=t.shapeInfo.logicalShape.length,s=e.logicalShape.length,u=Co(t.shapeInfo.logicalShape,e.logicalShape),c=wa(s),l=s-i,h=["x","y","z","w","u","v"];n=0===i?"":s<2&&u.length>=1?"coords = 0;":u.map((function(t){return "coords."+h[t+l]+" = 0;"})).join("\n");var f="";f=s<2&&i>0?"coords":t.shapeInfo.logicalShape.map((function(t,e){return "coords."+h[e+l]})).join(", ");var d="return outputValue;",p=1===k(t.shapeInfo.logicalShape),v=1===k(e.logicalShape);if(1!==i||p||v){if(p&&!v)d=1===s?"\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\n      ":"\n        return vec4(outputValue.x);\n      ";else if(u.length){var m=i-2,g=i-1;u.indexOf(m)>-1&&u.indexOf(g)>-1?d="return vec4(outputValue.x);":u.indexOf(m)>-1?d="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":u.indexOf(g)>-1&&(d="return vec4(outputValue.xx, outputValue.zz);");}}else d="\n      return vec4(outputValue.xy, outputValue.xy);\n    ";return "\n    vec4 "+a+"() {\n      "+c+" coords = getOutputCoords();\n      "+n+"\n      vec4 outputValue = get"+o+"("+f+");\n      "+d+"\n    }\n  "}(t,e):function(t,e){var n=t.name,r=n.charAt(0).toUpperCase()+n.slice(1),o="get"+r+"AtOutCoords",a=e.texShape,i=t.shapeInfo.texShape,s=t.shapeInfo.logicalShape.length,u=e.logicalShape.length;if(!t.shapeInfo.isUniform&&s===u&&null==t.shapeInfo.flatOffset&&S(i,a))return "\n      float "+o+"() {\n        return sampleTexture("+n+", resultUV);\n      }\n    ";var c,l=wa(u),h=Co(t.shapeInfo.logicalShape,e.logicalShape),f=u-s,d=["x","y","z","w","u","v"];c=0===s?"":u<2&&h.length>=1?"coords = 0;":h.map((function(t){return "coords."+d[t+f]+" = 0;"})).join("\n");var p="";p=u<2&&s>0?"coords":t.shapeInfo.logicalShape.map((function(t,e){return "coords."+d[e+f]})).join(", ");return "\n    float "+o+"() {\n      "+l+" coords = getOutputCoords();\n      "+c+"\n      return get"+r+"("+p+");\n    }\n  "}(t,e));return r}(t,e,r)})).join("\n"),c=e.texShape,l=ua(),h=function(t){return "\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return "+t.texture2D+"(textureSampler, uv).r;\n    }\n  "}(l),f=function(t){return t.version+"\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    "+t.varyingFs+" vec2 resultUV;\n    "+t.defineOutput+"\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int 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return 0;\n    }\n  ";case 1:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(1===n[0])return "\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * "+n[1]+".0);\n      }\n    ";if(1===n[1])return "\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * "+n[0]+".0);\n      }\n    ";return "\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      return 2 * (resTexRC.x * "+n[1]+" + resTexRC.y);\n    }\n  "}(0,e);case 2:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(S(t,e))return "\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2("+n[0]+", "+n[1]+"));\n      }\n    ";var r=Math.ceil(t[1]/2);return "\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec2(r, c);\n    }\n  "}(t,e);case 3:return n=t,r=e,o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=Math.ceil(n[2]/2),i=a*Math.ceil(n[1]/2),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+o[0]+", "+o[1]+"));\n      int index = resTexRC.x * "+o[1]+" + resTexRC.y;\n\n      int b = index / "+i+";\n      index -= b * "+i+";\n\n      int r = 2 * (index / "+a+");\n      int c = imod(index, "+a+") * 2;\n\n      return ivec3(b, r, c);\n    }\n  ";default:return function(t,e){for(var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],r=Math.ceil(t[t.length-1]/2),o=r*Math.ceil(t[t.length-2]/2),a=o,i="",s="b, r, c",u=2;u<t.length-1;u++)a*=t[t.length-u-1],i="\n      int b"+u+" = index / "+a+";\n      index -= b"+u+" * "+a+";\n    "+i,s="b"+u+", "+s;return "\n    ivec"+t.length+" getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n\n      "+i+"\n\n      int b = index / "+o+";\n      index -= b * "+o+";\n\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec"+t.length+"("+s+");\n    }\n  "}(t,e)}var n,r,o,a,i;}(e.logicalShape,c),i=function(t){return "\n    void setOutput(vec4 val) {\n      "+t.output+" = val;\n    }\n  "}(l)):(a=function(t,e){switch(t.length){case 0:return "\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return function(t,e){if(1===e[0])return "\n      int getOutputCoords() {\n        return int(resultUV.x * "+e[1]+".0);\n      }\n    ";if(1===e[1])return "\n      int getOutputCoords() {\n        return int(resultUV.y * "+e[0]+".0);\n      }\n    ";return "\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+e[0]+", "+e[1]+"));\n      return resTexRC.x * "+e[1]+" + resTexRC.y;\n    }\n  "}(0,e);case 2:return function(t,e){if(S(t,e))return "\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2("+e[0]+", "+e[1]+"));\n      }\n    ";if(1===t[1])return "\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+e[0]+", "+e[1]+"));\n        int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ";if(1===t[0])return "\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+e[0]+", "+e[1]+"));\n        int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ";return "\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+e[0]+", "+e[1]+"));\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n      int r = index / "+t[1]+";\n      int c = index - r * "+t[1]+";\n      return ivec2(r, c);\n    }\n  "}(t,e);case 3:return n=e,r=ca(["r","c","d"],t),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n      "+r+"\n      return ivec3(r, c, d);\n    }\n  ";case 4:return function(t,e){var n=ca(["r","c","d","d2"],t);return "\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+e[0]+", "+e[1]+"));\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n      "+n+"\n      return ivec4(r, c, d, d2);\n    }\n  "}(t,e);case 5:return function(t,e){var n=ca(["r","c","d","d2","d3"],t);return "\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2("+e[0]+",\n                             "+e[1]+"));\n\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n\n      "+n+"\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  "}(t,e);case 6:return function(t,e){var n=ca(["r","c","d","d2","d3","d4"],t);return "\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+e[0]+", "+e[1]+"));\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n\n      "+n+"\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  "}(t,e);default:throw new Error(t.length+"-D output sampling is not yet supported")}var n,r;}(e.logicalShape,c),i=function(t){return "\n    void setOutput(float val) {\n      "+t.output+" = vec4(val, 0, 0, 0);\n    }\n  "}(l)),r&&(f+=ya),[f,h,i,s,a,u,n].join("\n")}function da(t){var e=t.shapeInfo.logicalShape;switch(e.length){case 0:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return "float "+n+"() {return "+e+";}";var r=t.shapeInfo.texShape,o=r[0],a=r[1];if(1===o&&1===a)return "\n      float "+n+"() {\n        return sampleTexture("+e+", halfCR);\n      }\n    ";var i=t.shapeInfo.texShape,s=i[0],u=i[1],c=xa(e);return "\n    float "+n+"() {\n      vec2 uv = uvFromFlat("+s+", "+u+", "+c+");\n      return sampleTexture("+e+", uv);\n    }\n  "}(t);case 1:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return "\n      float "+n+"(int index) {\n        "+ba(t)+"\n      }\n    ";var r=t.shapeInfo.texShape,o=r[0],a=r[1];if(1===a&&1===o)return "\n      float "+n+"(int index) {\n        return sampleTexture("+e+", halfCR);\n      }\n    ";var i=xa(e);if(1===a)return "\n      float "+n+"(int index) {\n        vec2 uv = vec2(0.5, (float(index + "+i+") + 0.5) / "+o+".0);\n        return sampleTexture("+e+", uv);\n      }\n    ";if(1===o)return "\n      float "+n+"(int index) {\n        vec2 uv = vec2((float(index + "+i+") + 0.5) / "+a+".0, 0.5);\n        return sampleTexture("+e+", uv);\n      }\n    ";return "\n    float "+n+"(int index) {\n      vec2 uv = uvFromFlat("+o+", "+a+", index + "+i+");\n      return sampleTexture("+e+", uv);\n    }\n  "}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape;if(null!=o&&S(e,o)){var a=o[0],i=o[1];return "\n    float "+r+"(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2("+i+".0, "+a+".0);\n      return sampleTexture("+n+", uv);\n    }\n  "}var s=M(e),u=s.newShape,c=s.keptDims,l=u;if(l.length<e.length){var h=Ca(t,l);return "\n      "+da(h)+"\n      float "+r+"(int row, int col) {\n        return "+r+"("+Ea(["row","col"],c)+");\n      }\n    "}if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col) {\n        int index = round(dot(vec2(row, col), vec2("+e[1]+", 1)));\n        "+ba(t)+"\n      }\n    ";var f=o[0],d=o[1],p=xa(n);if(1===d)return "\n    float "+r+"(int row, int col) {\n      float index = dot(vec3(row, col, "+p+"), vec3("+e[1]+", 1, 1));\n      vec2 uv = vec2(0.5, (index + 0.5) / "+f+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ";if(1===f)return "\n    float "+r+"(int row, int col) {\n      float index = dot(vec3(row, col, "+p+"), vec3("+e[1]+", 1, 1));\n      vec2 uv = vec2((index + 0.5) / "+d+".0, 0.5);\n      return sampleTexture("+n+", uv);\n    }\n  ";return "\n  float "+r+"(int row, int col) {\n    // Explicitly use integer operations as dot() only works on floats.\n    int index = row * "+e[1]+" + col + "+p+";\n    vec2 uv = uvFromFlat("+f+", "+d+", index);\n    return sampleTexture("+n+", uv);\n  }\n"}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[1]*e[2],a=e[2],i=M(e),s=i.newShape,u=i.keptDims,c=s;if(c.length<e.length){var l=Ca(t,c);return "\n        "+da(l)+"\n        float "+r+"(int row, int col, int depth) {\n          return "+r+"("+Ea(["row","col","depth"],u)+");\n        }\n      "}if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col, int depth) {\n        int index = round(dot(vec3(row, col, depth),\n                          vec3("+o+", "+a+", 1)));\n        "+ba(t)+"\n      }\n    ";var h=t.shapeInfo.texShape,f=h[0],d=h[1],p=t.shapeInfo.flatOffset;if(d===o&&null==p)return "\n        float "+r+"(int row, int col, int depth) {\n          float texR = float(row);\n          float texC = dot(vec2(col, depth), vec2("+a+", 1));\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2("+d+".0, "+f+".0);\n          return sampleTexture("+n+", uv);\n        }\n      ";if(d===a&&null==p)return "\n    float "+r+"(int row, int col, int depth) {\n      float texR = dot(vec2(row, col), vec2("+e[1]+", 1));\n      float texC = float(depth);\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+d+".0, "+f+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ";var v=xa(n);return "\n      float "+r+"(int row, int col, int depth) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * "+o+" + col * "+a+" + depth + "+v+";\n        vec2 uv = uvFromFlat("+f+", "+d+", index);\n        return sampleTexture("+n+", uv);\n      }\n  "}(t);case 4:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[3],a=e[2]*o,i=e[1]*a,s=M(e),u=s.newShape,c=s.keptDims;if(u.length<e.length){var l=Ca(t,u);return "\n      "+da(l)+"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        return "+r+"("+Ea(["row","col","depth","depth2"],c)+");\n      }\n    "}if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col, int depth, int depth2) {\n        int index = round(dot(vec4(row, col, depth, depth2),\n                          vec4("+i+", "+a+", "+o+", 1)));\n        "+ba(t)+"\n      }\n    ";var h=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,d=f[0],p=f[1];if(p===i&&null==h)return "\n      float "+r+"(int row, int col, int depth, int depth2) {\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3("+a+", "+o+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+p+".0, "+d+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(p===o&&null==h)return "\n      float "+r+"(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3("+e[1]*e[2]+", "+e[2]+", 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+p+".0, "+d+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var v=xa(n);return "\n    float "+r+"(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+i+" + col * "+a+" +\n          depth * "+o+" + depth2;\n      vec2 uv = uvFromFlat("+d+", "+p+", index + "+v+");\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);case 5:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[4],a=e[3]*o,i=e[2]*a,s=e[1]*i,u=M(e),c=u.newShape,l=u.keptDims;if(c.length<e.length){var h=Ca(t,c);return "\n      "+da(h)+"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        return "+r+"("+Ea(["row","col","depth","depth2","depth3"],l)+");\n      }\n    "}if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        float index = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+s+", "+i+", "+a+", "+o+")) +\n          depth3;\n        "+ba(t)+"\n      }\n    ";var f=t.shapeInfo.flatOffset,d=t.shapeInfo.texShape,p=d[0],v=d[1];if(v===s&&null==f)return "\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n                         vec4("+i+", "+a+", "+o+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+v+".0, "+p+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(v===o&&null==f)return "\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        float texR = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+e[1]*e[2]*e[3]+",\n               "+e[2]*e[3]+", "+e[3]+", 1));\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+v+".0, "+p+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var m=xa(n);return "\n    float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+s+" + col * "+i+" + depth * "+a+" +\n          depth2 * "+o+" + depth3 + "+m+";\n      vec2 uv = uvFromFlat("+p+", "+v+", index);\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);case 6:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=M(e),a=o.newShape,i=o.keptDims;if(a.length<e.length){var s=Ca(t,a);return "\n      "+da(s)+"\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        return "+r+"("+Ea(["row","col","depth","depth2","depth3","depth4"],i)+");\n      }\n    "}var u=e[5],c=e[4]*u,l=e[3]*c,h=e[2]*l,f=e[1]*h;if(t.shapeInfo.isUniform)return "\n      float "+r+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n        int index = round(dot(\n          vec4(row, col, depth, depth2),\n          vec4("+f+", "+h+", "+l+", "+c+")) +\n          dot(\n            vec2(depth3, depth4),\n            vec2("+u+", 1)));\n        "+ba(t)+"\n      }\n    ";var d=t.shapeInfo.flatOffset,p=t.shapeInfo.texShape,v=p[0],m=p[1];if(m===f&&null==d)return "\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n          vec4("+h+", "+l+", "+c+", "+u+")) +\n               float(depth4);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+m+".0, "+v+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(m===u&&null==d)return "\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        float texR = dot(vec4(row, col, depth, depth2),\n          vec4("+e[1]*e[2]*e[3]*e[4]+",\n               "+e[2]*e[3]*e[4]+",\n               "+e[3]*e[4]+",\n               "+e[4]+")) + float(depth3);\n        int texC = depth4;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+m+".0, "+v+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var g=xa(n);return "\n    float "+r+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+f+" + col * "+h+" + depth * "+l+" +\n          depth2 * "+c+" + depth3 * "+u+" + depth4 + "+g+";\n      vec2 uv = uvFromFlat("+v+", "+m+", index);\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);default:throw new Error(e.length+"-D input sampling is not yet supported")}}function pa(t){var e,n,r;switch(t.shapeInfo.logicalShape.length){case 0:return e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),r=ua(),"\n    vec4 "+n+"() {\n      return "+r.texture2D+"("+e+", halfCR);\n    }\n  ";case 1:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),r=t.shapeInfo.texShape,o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=ua();return "\n    vec4 "+n+"(int index) {\n      vec2 uv = packedUVfrom1D(\n        "+o[0]+", "+o[1]+", index);\n      return "+a.texture2D+"("+e+", uv);\n    }\n  "}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,a=o[0],i=o[1],s=ua();if(null!=o&&S(e,o))return "\n      vec4 "+r+"(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2("+i+".0, "+a+".0);\n\n        return "+s.texture2D+"("+n+", uv);\n      }\n    ";var u=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],c=Math.ceil(e[1]/2);return "\n    vec4 "+r+"(int row, int col) {\n      vec2 uv = packedUVfrom2D("+c+", "+u[0]+", "+u[1]+", row, col);\n      return "+s.texture2D+"("+n+", uv);\n    }\n  "}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,a=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];if(1===e[0]){var i=e.slice(1),s=Ca(t,i);return "\n        "+pa(s)+"\n        vec4 "+r+"(int b, int row, int col) {\n          return "+r+"("+Ea(["b","row","col"],[1,2])+");\n        }\n      "}var u=a[0],c=a[1],l=Math.ceil(e[2]/2),h=l*Math.ceil(e[1]/2),f=ua();return "\n    vec4 "+r+"(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        "+u+", "+c+", "+h+", "+l+", b, row, col);\n      return "+f.texture2D+"("+n+", uv);\n    }\n  "}(t);default:return function(t){for(var e=t.shapeInfo.logicalShape,n=e.length,r=t.name,o="get"+r.charAt(0).toUpperCase()+r.slice(1),a=t.shapeInfo.texShape,i=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],s=i[0],u=i[1],c=Math.ceil(e[n-1]/2),l=c*Math.ceil(e[n-2]/2),h="int b, int row, int col",f="b * "+l+" + (row / 2) * "+c+" + (col / 2)",d=2;d<n-1;d++)h="int b"+d+", "+h,l*=e[n-d-1],f="b"+d+" * "+l+" + "+f;var p=ua();return "\n    vec4 "+o+"("+h+") {\n      int index = "+f+";\n      int texR = index / "+u+";\n      int texC = index - texR * "+u+";\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+u+", "+s+");\n      return "+p.texture2D+"("+r+", uv);\n    }\n  "}(t)}}var va="\nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",ma="\nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",ga="\nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",ya="\n  float getChannel(vec4 frag, vec2 innerDims) {\n    vec2 modCoord = mod(innerDims, 2.);\n    return modCoord.x == 0. ?\n      (modCoord.y == 0. ? frag.r : frag.g) :\n      (modCoord.y == 0. ? frag.b : frag.a);\n  }\n  float getChannel(vec4 frag, int dim) {\n    float modCoord = mod(float(dim), 2.);\n    return modCoord == 0. ? frag.r : frag.g;\n  }\n";function xa(t){return "offset"+t}function ba(t){var e=t.name,n=k(t.shapeInfo.logicalShape);return n<2?"return "+e+";":"\n    for (int i = 0; i < "+n+"; i++) {\n      if (i == index) {\n        return "+e+"[i];\n      }\n    }\n  "}function wa(t){if(t<=1)return "int";if(2===t)return "ivec2";if(3===t)return "ivec3";if(4===t)return "ivec4";if(5===t)return "ivec5";if(6===t)return "ivec6";throw Error("GPU for rank "+t+" is not yet supported")}function Ca(t,e){var n=JSON.parse(JSON.stringify(t));return n.shapeInfo.logicalShape=e,n}function Ea(t,e){return e.map((function(e){return t[e]})).join(", ")}var Ra=function(t,e,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,C(t.length>2,(function(){return "Packed arg"+(n.charAt(0).toUpperCase()+n.slice(1))+" supports only inputs with rank above 2."}));var o=t[t.length-1],a=Math.ceil(o/e);this.outputShape=t.slice(0,-1),a>1&&this.outputShape.push(a),r||this.variableNames.push("bestIndicesA");var i,s,u=this.outputShape,c=u.length,l=wa(c),h=sa("coords",c);if(1===a){var f=wa(s=c+1);i="\n        "+f+" sourceLocR = "+f+"("+h.join()+", 0);\n        ++"+h[c-1]+";\n        "+f+" sourceLocG = "+f+"("+h.join()+", 0);\n        ++"+h[c-2]+";\n        "+f+" sourceLocA = "+f+"("+h.join()+", 0);\n        --"+h[c-1]+";\n        "+f+" sourceLocB = "+f+"("+h.join()+", 0);\n        --"+h[c-2]+";";}else s=c,i="\n        "+l+" sourceLocR = coords;\n        ++"+h[c-1]+";\n        "+l+" sourceLocG = coords;\n        ++"+h[c-2]+";\n        "+l+" sourceLocA = coords;\n        --"+h[c-1]+";\n        "+l+" sourceLocB = coords;\n        --"+h[c-2]+";";var d=["x","y","z","w","u","v"].slice(0,s),p="."+d[s-1],v=d.map((function(t){return "int "+t})),m=sa("sourceLocR",s-1).concat("inIdx.r"),g=sa("sourceLocG",s-1).concat("inIdx.g"),y=sa("sourceLocB",s-1).concat("inIdx.b"),x=sa("sourceLocA",s-1).concat("inIdx.a"),b="max"===n?"greaterThan":"lessThan",w=r?"":"\n          inIdx = round(vec4(getBestIndicesAChannel("+m.join()+"),\n                             getBestIndicesAChannel("+g.join()+"),\n                             getBestIndicesAChannel("+y.join()+"),\n                             getBestIndicesAChannel("+x.join()+")));",E="vec4(\n            getAChannel("+m.join()+"),\n            hasNextCol ? getAChannel("+g.join()+") : 0.,\n            hasNextRow ? getAChannel("+y.join()+") : 0.,\n            hasNextRow && hasNextCol ? getAChannel("+x.join()+") : 0.)",R=r?"":"\n      float getBestIndicesAChannel("+v.join()+") {\n        return getChannel(getBestIndicesA("+d.join()+"),\n                                          vec2("+d.slice(-2).join()+"));\n      }";this.userCode="\n      float getAChannel("+v.join()+") {\n        return getChannel(getA("+d.join()+"),\n                               vec2("+d.slice(-2).join()+"));\n      }\n      "+R+"\n      void main() {\n        "+l+" coords = getOutputCoords();\n        bool hasNextCol = "+h[c-1]+" < "+(u[c-1]-1)+";\n        bool hasNextRow = "+h[c-2]+" < "+(u[c-2]-1)+";\n        "+i+"\n        ivec4 srcIdx = ivec4(sourceLocR"+p+", sourceLocG"+p+",\n          sourceLocB"+p+", sourceLocA"+p+") * "+e+";\n        ivec4 inIdx = srcIdx;\n        vec4 bestIndex = vec4(inIdx);\n        vec4 bestValue = "+E+";\n\n        for (int i = 0; i < "+e+"; i++) {\n          inIdx = srcIdx;\n          "+w+"\n          vec4 candidate = "+E+";\n          bvec4 nan = isnan(candidate);\n          bvec4 replace = bvec4(\n            vec4("+b+"(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\n                           replace.y  ? candidate.y : bestValue.y,\n                           replace.z  ? candidate.z : bestValue.z,\n                           replace.w  ? candidate.w : bestValue.w);\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n          srcIdx++;\n        }\n        setOutput(bestIndex);\n      }\n    ";},Ia=function(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=t.dilationHeight,i=t.dilationWidth,s=t.effectiveFilterHeight,u=t.effectiveFilterWidth,c=s-1-t.padInfo.top,l=u-1-t.padInfo.left,h=1/(e*n);this.userCode="\n      const ivec2 pads = ivec2("+c+", "+l+");\n      const float avgMultiplier = float("+h+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+s+";\n            wR += "+a+") {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+u+";\n            wC+= "+i+") {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},ka=function(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,d=l-1-t.padInfo.front,p=h-1-t.padInfo.top,v=f-1-t.padInfo.left,m=1/(e*n*r);this.userCode="\n      const ivec3 pads = ivec3("+d+", "+p+", "+v+");\n      const float avgMultiplier = float("+m+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+l+";\n            wD += "+s+") {\n          float dyD = float(dyDCorner + wD) / "+o+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+h+";\n              wR += "+u+") {\n            float dyR = float(dyRCorner + wR) / "+a+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+f+";\n                wC += "+c+") {\n              float dyC = float(dyCCorner + wC) / "+i+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},Sa=function(t,e,n,r,o,a){this.outputShape=[],this.variableNames=["x","mean","variance"],Ro(t,e),Ro(t,n);var i="0.0";null!=r&&(Ro(t,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");var s="1.0";null!=o&&(Ro(t,o),this.variableNames.push("scale"),s="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = "+i+";\n        float scale = "+s+";\n        float inv = scale * inversesqrt(variance + float("+a+"));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    ";},Aa=function(t,e,n,r,o,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],Ro(t,e),Ro(t,n);var i="vec4(0.0)";null!=r&&(Ro(t,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");var s="vec4(1.0)";null!=o&&(Ro(t,o),this.variableNames.push("scale"),s="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        vec4 offset = "+i+";\n        vec4 scale = "+s+";\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4("+a+"));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    ";},Da="return areal * breal - aimag * bimag;",Ta="return areal * bimag + aimag * breal;",Na=function(t,e,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=Ro(e,n),this.userCode="\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        "+t+"\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    ";},Fa="return a + b;",_a="return a - b;",Oa="return a * b;",Ma="return (a < 0.) ? b * a : a;",Ba=function(t,e,n){this.variableNames=["A","B"],this.outputShape=Ro(e,n),this.userCode="\n      float binaryOperation(float a, float b) {\n        "+t+"\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    ";},Pa="\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n",La=function(t,e,n,r){void 0===r&&(r=!1),this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=Ro(e,n);var o=this.outputShape.length,a="";if(r)if(0===o||1===k(this.outputShape))a="\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        ";else if(a="\n          "+wa(o)+" coords = getOutputCoords();\n        ",1===o)a+="\n            result.y = (coords + 1) >= "+this.outputShape[0]+" ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          ";else {var i=sa("coords",o);a+="\n            bool nextRowOutOfBounds =\n              ("+i[o-2]+" + 1) >= "+this.outputShape[o-2]+";\n            bool nextColOutOfBounds =\n              ("+i[o-1]+" + 1) >= "+this.outputShape[o-1]+";\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          ";}this.userCode="\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        "+t+"\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        "+a+"\n\n        setOutput(result);\n      }\n    ";},Wa=function(){function t(t){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,o){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(o,"minVal"),n.maxLoc=r.getUniformLocationNoThrow(o,"maxVal")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e);}},t}(),Ua=function(){function t(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        vec4 value = getAAtOutCoords();\n\n        if (any(isnan(value))) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,o){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(o,"minVal"),n.maxLoc=r.getUniformLocationNoThrow(o,"maxVal")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e);}},t}(),Va=function(t){this.variableNames=["real","imag"],this.outputShape=t,this.userCode="\n      void main() {\n        float re = abs(getRealAtOutCoords());\n        float im = abs(getImagAtOutCoords());\n        float mx = max(re, im);\n\n        // sadly the length function in glsl is not underflow-safe\n        // (at least not on Intel GPUs). So the safe solution is\n        // to ensure underflow-safety in all cases.\n        setOutput(\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\n        );\n      }\n    ";},za=function(t){this.outputShape=[],this.outputShape=Sn(t,1),this.variableNames=t.map((function(t,e){return "T"+e}));var e=new Array(t.length-1);e[0]=t[0][1];for(var n=1;n<e.length;n++)e[n]=e[n-1]+t[n][1];var r=["if (yC < "+e[0]+") setOutput(getT0(yR, yC));"];for(n=1;n<e.length;n++){var o=e[n-1];r.push("else if (yC < "+e[n]+") setOutput(getT"+n+"(yR, yC-"+o+"));");}var a=e.length,i=e[e.length-1];r.push("else setOutput(getT"+a+"(yR, yC-"+i+"));"),this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        "+r.join("\n        ")+"\n      }\n    ";},Ga=function(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=Sn(t,e);var n=this.outputShape,r=n.length,o=wa(r),a=sa("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=t.map((function(t,e){return "T"+e}));var s=new Array(t.length-1);s[0]=t[0][e];for(var u=1;u<s.length;u++)s[u]=s[u-1]+t[u][e];var c=i[e],l=i.slice(-2),h=i.join(),f="if ("+c+" < "+s[0]+") {\n        return getChannel(\n            getT0("+h+"), vec2("+l.join()+"));\n        }";for(u=1;u<s.length;u++){var d=s[u-1];f+="\n        if ("+c+" < "+s[u]+"  && "+c+" >= "+s[u-1]+") {\n          return getChannel(\n            getT"+u+"("+Ha(i,c,d)+"),\n            vec2("+Ha(l,c,d)+"));\n        }";}var p=s.length,v=s[s.length-1];f+="\n        return getChannel(\n          getT"+p+"("+Ha(i,c,v)+"),\n          vec2("+Ha(l,c,v)+"));",this.userCode="\n      float getValue("+i.map((function(t){return "int "+t}))+") {\n        "+f+"\n      }\n\n      void main() {\n        "+o+" coords = getOutputCoords();\n        vec4 result = vec4(getValue("+a+"), 0., 0., 0.);\n\n        "+a[r-1]+" = "+a[r-1]+" + 1;\n        if ("+a[r-1]+" < "+n[r-1]+") {\n          result.g = getValue("+a+");\n        }\n\n        "+a[r-2]+" = "+a[r-2]+" + 1;\n        if ("+a[r-2]+" < "+n[r-2]+") {\n          result.a = getValue("+a+");\n        }\n\n        "+a[r-1]+" = "+a[r-1]+" - 1;\n        if ("+a[r-2]+" < "+n[r-2]+" &&\n            "+a[r-1]+" < "+n[r-1]+") {\n          result.b = getValue("+a+");\n        }\n        setOutput(result);\n      }\n    ";};function Ha(t,e,n){var r=t.indexOf(e);return t.map((function(t,e){return e===r?t+" - "+n:t})).join()}var qa=function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,a="channelsLast"===t.dataFormat;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+o+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              if ("+a+") {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},Ka=function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a="channelsLast"===t.dataFormat,i=e-1-t.padInfo.top,s=n-1-t.padInfo.left,u=a?1:2,c=a?2:3,l=a?3:1;this.userCode="\n      const ivec2 pads = ivec2("+i+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords["+l+"];\n\n        ivec2 dyCorner = ivec2(coords["+u+"], coords["+c+"]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n\n              if ("+a+") {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},ja=function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.padInfo.front,a=t.padInfo.top,i=t.padInfo.left;this.userCode="\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yF = 0; yF < "+t.outDepth+"; yF++) {\n            int xF = wF + yF * "+e+" - "+o+";\n\n            if (xF < 0 || xF >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n              int xR = wR + yR * "+n+" - "+a+";\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n                int xC = wC + yC * "+r+" - "+i+";\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},Xa=function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,s=e-1-t.padInfo.front,u=n-1-t.padInfo.top,c=r-1-t.padInfo.left;this.userCode="\n      const ivec3 pads = ivec3("+s+", "+u+", "+c+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+e+"; wF++) {\n          float dyF = float(dyFCorner + wF) / "+o+".0;\n\n          if (dyF < 0.0 || dyF >= "+t.outDepth+".0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = "+e+" - 1 - wF;\n\n          for (int wR = 0; wR < "+n+"; wR++) {\n            float dyR = float(dyRCorner + wR) / "+a+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = "+n+" - 1 - wR;\n\n            for (int wC = 0; wC < "+r+"; wC++) {\n              float dyC = float(dyCCorner + wC) / "+i+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = "+r+" - 1 - wC;\n\n              for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},Ya=function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,a=t.outChannels/t.inChannels;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * "+a+" + dm;\n\n        float dotProd = 0.0;\n\n        // TO DO: Vec4 over the batch size\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+o+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},$a=function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=e-1-t.padInfo.top,i=n-1-t.padInfo.left,s=t.outChannels/t.inChannels;this.userCode="\n      const ivec2 pads = ivec2("+a+", "+i+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < "+s+"; dm++) {\n              int d2 = d1 * "+s+" + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},Qa=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.outputShape=t.outShape;var o=t.padInfo.top,a=t.padInfo.left,i=t.strideHeight,s=t.strideWidth,u=t.dilationHeight,c=t.dilationWidth,l=t.filterHeight,h=t.filterWidth,f=4*Math.floor(t.inChannels/4),d=t.inChannels%4,p="channelsLast"===t.dataFormat,v=p?1:2,m=p?2:3,g=p?3:1,y="",x="";n&&(y=r?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"\n          float activation(float x) {\n            "+n+"\n          }\n        ",x="result = activation(result);");var b=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+y+"\n\n      const ivec2 strides = ivec2("+i+", "+s+");\n      const ivec2 pads = ivec2("+o+", "+a+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords["+g+"];\n\n        ivec2 xRCCorner =\n            ivec2(coords["+v+"], coords["+m+"]) * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+l+"; wR++) {\n          int xR = xRCorner + wR * "+u+";\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+h+"; wC++) {\n            int xC = xCCorner + wC * "+c+";\n\n            if (xC < 0 || xC >= "+t.inWidth+") {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < "+f+"; d1 += 4) {\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              if ("+p+") {\n                vec4 xValues = vec4(\n                  getX(batch, xR, xC, d1),\n                  getX(batch, xR, xC, d1 + 1),\n                  getX(batch, xR, xC, d1 + 2),\n                  getX(batch, xR, xC, d1 + 3)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec4 xValues = vec4(\n                  getX(batch, d1, xR, xC),\n                  getX(batch, d1 + 1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if ("+(1===d)+") {\n\n              if ("+p+") {\n                dotProd +=\n                    getX(batch, xR, xC, "+f+") *\n                    getW(wR, wC, "+f+", d2);\n              } else {\n                dotProd +=\n                    getX(batch, "+f+", xR, xC) *\n                    getW(wR, wC, "+f+", d2);\n              }\n\n            } else if ("+(2===d)+") {\n              vec2 wValues = vec2(\n                getW(wR, wC, "+f+", d2),\n                getW(wR, wC, "+f+" + 1, d2)\n              );\n\n              if ("+p+") {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, "+f+"),\n                  getX(batch, xR, xC, "+f+" + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, "+f+", xR, xC),\n                  getX(batch, "+f+" + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if ("+(3===d)+") {\n              vec3 wValues = vec3(\n                getW(wR, wC, "+f+", d2),\n                getW(wR, wC, "+f+" + 1, d2),\n                getW(wR, wC, "+f+" + 2, d2)\n              );\n\n              if ("+p+") {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, "+f+"),\n                  getX(batch, xR, xC, "+f+" + 1),\n                  getX(batch, xR, xC, "+f+" + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, "+f+", xR, xC),\n                  getX(batch, "+f+" + 1, xR, xC),\n                  getX(batch, "+f+" + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        "+b+"\n        "+x+"\n        setOutput(result);\n      }\n    ";},Ja=function(t){this.variableNames=["x","W"],this.outputShape=t.outShape;var e=t.padInfo.front,n=t.padInfo.top,r=t.padInfo.left,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.filterDepth,h=t.filterHeight,f=t.filterWidth,d=4*Math.floor(t.inChannels/4),p=t.inChannels%4;this.userCode="\n      const ivec3 strides = ivec3("+o+", "+a+", "+i+");\n      const ivec3 pads = ivec3("+e+", "+n+", "+r+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+l+"; wF++) {\n          int xF = xFCorner + wF * "+s+";\n\n          if (xF < 0 || xF >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+h+"; wR++) {\n            int xR = xRCorner + wR * "+u+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+f+"; wC++) {\n              int xC = xCCorner + wC * "+c+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < "+d+"; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if ("+(1===p)+") {\n                dotProd +=\n                  getX(batch, xF, xR, xC, "+d+") *\n                  getW(wF, wR, wC, "+d+", d2);\n              } else if ("+(2===p)+") {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, "+d+"),\n                  getX(batch, xF, xR, xC, "+d+" + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, "+d+", d2),\n                  getW(wF, wR, wC, "+d+" + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if ("+(3===p)+") {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, "+d+"),\n                  getX(batch, xF, xR, xC, "+d+" + 1),\n                  getX(batch, xF, xR, xC, "+d+" + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, "+d+", d2),\n                  getW(wF, wR, wC, "+d+" + 1, d2),\n                  getW(wF, wR, wC, "+d+" + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},Za=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.outputShape=t.outShape;var o=t.inHeight,a=t.inWidth,i=t.padInfo.top,s=t.padInfo.left,u=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,d=t.filterWidth,p=t.outChannels/t.inChannels,v="",m="";n&&(v=r?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"\n          float activation(float x) {\n            "+n+"\n          }\n        ",m="result = activation(result);");var g=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+v+"\n\n      const ivec2 strides = ivec2("+u+", "+c+");\n      const ivec2 pads = ivec2("+i+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / "+p+";\n        int q = d2 - d1 * "+p+";\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < "+f+"; wR++) {\n          int xR = xRCorner + wR * "+l+";\n\n          if (xR < 0 || xR >= "+o+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+d+"; wC++) {\n            int xC = xCCorner + wC * "+h+";\n\n            if (xC < 0 || xC >= "+a+") {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n\n        float result = dotProd;\n        "+g+"\n        "+m+"\n        setOutput(result);\n      }\n    ";},ti=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.outShape;for(var o=t.inHeight,a=t.inWidth,i=t.padInfo.top,s=t.padInfo.left,u=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,d=t.filterWidth,p=d,v="int xR; int xC; int xCOffset;",m=0;m<f;m++)for(var g=0;g<d;g++)v+="\n          vec4 xTexelR"+m+"C"+2*g+" = vec4(0.);\n          vec4 wR"+m+"C"+g+" = vec4(0.);\n          vec4 xR"+m+"C"+g+" = vec4(0.);";for(m=0;m<f;m++)for(var y=0;y<p;y++){if(v+="\n          xR = xRCorner + "+m*l+";\n          xC = xCCorner + "+(g=2*y)*h+";\n        ",1===c){if(g<d&&(v+=s%2==1?"\n                xCOffset = xC + 1;\n                if(xR >= 0 && xR < "+o+" && xCOffset >= 0 && xCOffset < "+a+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if(xCOffset + 1 >= "+a+") {\n                    xTexelR"+m+"C"+g+".zw = vec2(0.);\n                  }\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                xCOffset = xC + 1 - 2;\n                if(xR >= 0 && xR < "+o+" && xCOffset >= 0 && xCOffset < "+a+") {\n                  vec4 previous = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if(xCOffset + 1 >= "+a+") {\n                    previous.zw = vec2(0.);\n                  }\n\n                  xR"+m+"C"+g+" = vec4(previous.zw, xTexelR"+m+"C"+g+".xy);\n                } else {\n                  xR"+m+"C"+g+" = vec4(0, 0, xTexelR"+m+"C"+g+".xy);\n                }\n              ":"\n                if(xR >= 0 && xR < "+o+" && xC >= 0 && xC < "+a+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                xR"+m+"C"+g+" = xTexelR"+m+"C"+g+";\n              ",g+1<d)){var x=s%2==0?b(h):h;h%2==0&&s%2==1||h%2!=0&&s%2!=1?(v+="\n                  xCOffset = xC + "+s%2+" + "+x+";\n\n                  if(xR >= 0 && xR < "+o+" &&\n                    xCOffset >= 0 && xCOffset < "+a+") {\n                    xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n                ",h>1&&(v+="\n                    xCOffset -= 2;\n                    if(xR >= 0 && xR < "+o+" &&\n                      xCOffset >= 0 && xCOffset < "+a+") {\n                      xTexelR"+m+"C"+g+" = getX(batch, xR, xCOffset, d1);\n                    } else {\n                      xTexelR"+m+"C"+g+" = vec4(0.);\n                    }\n                  "),v+="\n                  xR"+m+"C"+(g+1)+" = vec4(\n                    xTexelR"+m+"C"+g+".zw, xTexelR"+m+"C"+(g+2)+".xy);\n                "):v+="\n                  xCOffset = xC + "+x+";\n\n                  if(xR >= 0 && xR < "+o+" &&\n                    xCOffset >= 0 && xCOffset < "+a+") {\n                    xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n\n                  xR"+m+"C"+(g+1)+" = xTexelR"+m+"C"+(g+2)+";\n                ";}}else g<d&&(v+="\n              if(xR >= 0 && xR < "+o+") {\n            ",s%2==1?(v+="\n                xCOffset = xC + 1 - "+c+";\n                if(xCOffset >= 0 && xCOffset < "+a+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < "+a+") {\n                  xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xC + 1, d1);\n                } else {\n                  xTexelR"+m+"C"+(g+2)+" = vec4(0.);\n                }\n\n                xR"+m+"C"+g+" = vec4(\n                  xTexelR"+m+"C"+g+".zw, xTexelR"+m+"C"+(g+2)+".zw);\n              ",g+1<d&&(v+="\n                  vec4 final = vec4(0.);\n                  xCOffset = xC + 1 + "+c+";\n                  if(xCOffset >= 0 && xCOffset < "+a+") {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xR"+m+"C"+(g+1)+" = vec4(xTexelR"+m+"C"+(g+2)+".xy, final.xy);\n                ")):(v+="\n                if(xC >= 0 && xC < "+a+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                xCOffset = xC + "+c+";\n                if(xCOffset >= 0 && xCOffset < "+a+") {\n                  xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+m+"C"+(g+2)+" = vec4(0.);\n                }\n\n                xR"+m+"C"+g+" = vec4(\n                  xTexelR"+m+"C"+g+".xy, xTexelR"+m+"C"+(g+2)+".xy);\n              ",g+1<d&&(v+="\n                  xR"+m+"C"+(g+1)+" = vec4(\n                    xTexelR"+m+"C"+g+".zw, xTexelR"+m+"C"+(g+2)+".zw);\n                ")),v+="}");g<d&&(v+="\n            vec4 wTexelR"+m+"C"+g+" = getW("+m+", "+g+", d1, q);\n            wR"+m+"C"+g+" = vec4(wTexelR"+m+"C"+g+".xz, wTexelR"+m+"C"+g+".xz);\n          ",g+1<d&&(v+="\n              vec4 wTexelR"+m+"C"+(g+1)+" = getW("+m+", "+(g+1)+", d1, q);\n              wR"+m+"C"+(g+1)+" =\n                vec4(wTexelR"+m+"C"+(g+1)+".xz, wTexelR"+m+"C"+(g+1)+".xz);"));}for(m=0;m<f;m++)for(g=0;g<d;g++)v+="dotProd += xR"+m+"C"+g+" * wR"+m+"C"+g+";";var w="",C="";n&&(w=r?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"vec4 activation(vec4 x) {\n          "+n+"\n        }",C="result = activation(result);");var E=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+w+"\n\n      const ivec2 strides = ivec2("+u+", "+c+");\n      const ivec2 pads = ivec2("+i+", "+s+");\n\n      void main() {\n\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2;\n        int q = 0;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        vec4 dotProd = vec4(0.);\n\n        "+v+"\n\n        vec4 result = dotProd;\n        "+E+"\n        "+C+"\n        setOutput(result);\n      }\n    ";},ei=function(t,e,n,r,o){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];var a=t[0],i=t[1],s=t[2],u=t[3],c=e[0],l=n[0],h=n[1];this.outputShape=[c,l,h,u];var f="bilinear"===r?1:0,d=[i-1+".0",s-1+".0"],p=d[0],v=d[1],m=l>1?[""+(i-1)/(l-1),"(y2-y1) * height_ratio","y1*"+p+" + float(y)*(height_scale)"]:["0.0","0.0","0.5 * (y1+y2) * "+p],g=m[0],y=m[1],x=m[2],b=h>1?[""+(s-1)/(h-1),"(x2-x1) * width_ratio","x1*"+v+" + float(x)*(width_scale)"]:["0.0","0.0","0.5 * (x1+x2) * "+v],w=b[0],C=b[1],E=b[2];this.userCode="\n      const float height_ratio = float("+g+");\n      const float width_ratio = float("+w+");\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n        float x2 = getBoxes(b,3);\n\n        // get image in batch index\n        int bInd = round(getBoxInd(b));\n        if(bInd < 0 || bInd >= "+a+") {\n          return;\n        }\n\n        float height_scale = "+y+";\n        float width_scale = "+C+";\n\n        float in_y = "+x+";\n        if( in_y < 0.0 || in_y > "+p+" ) {\n          setOutput(float("+o+"));\n          return;\n        }\n        float in_x = "+E+";\n        if( in_x < 0.0 || in_x > "+v+" ) {\n          setOutput(float("+o+"));\n          return;\n        }\n\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\n        if("+f+" == 1) {\n          // Compute the four integer indices.\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    ";},ni=function(t,e,n){this.variableNames=["x"],this.outputShape=t;var r=t.length,o=t[t.length-1],a=n?"<":">";this.userCode="\n      int getIndex(int i) {\n        "+(n?"return "+o+" -i - 1;":"return i;")+"\n      }\n\n      void main() {\n        "+wa(r)+" coords = getOutputCoords();\n        int end = "+ri(r,"coords")+";\n        float val = 0.0;\n        for (int i = "+o+" - 1; i >= 0; i -= 1) {\n          int idx = getIndex(i);\n          if (idx "+a+" end) {\n            continue;\n          }\n          if (idx == end && "+e+") {\n            continue;\n          }\n          "+ri(r,"coords")+" = idx;\n          val += getX("+function(t,e){if(1===t)return ""+e;if(2===t)return e+".x, "+e+".y";if(3===t)return e+".x, "+e+".y, "+e+".z";if(4===t)return e+".x, "+e+".y, "+e+".z, "+e+".w";throw Error("Cumulative sum for rank "+t+" is not yet supported")}(r,"coords")+");\n        }\n        setOutput(val);\n      }\n    ";};function ri(t,e){if(1===t)return ""+e;if(2===t)return e+".y";if(3===t)return e+".z";if(4===t)return e+".w";throw Error("Cumulative sum for rank "+t+" is not yet supported")}var oi=function(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Vt.DENSE;var e=Yt(t),n=ua();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+ca(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getA(rc.x, rc.y, rc.z);\n        }\n\n        "+n.output+" = result;\n      }\n    ";},ai=function(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Vt.DENSE;var e=Yt(t),n=ua();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+ca(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\n        }\n\n        "+n.output+" = result;\n      }\n    ";},ii=function(){function t(t,e,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=t,this.blockSize=e,this.dataFormat=n,this.userCode="\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = "+this.getHeightCoordString()+";\n      int w = "+this.getWidthCoordString()+";\n      int d = "+this.getDepthCoordString()+";\n\n      int in_h = h / "+e+";\n      int offset_h = imod(h, "+e+");\n      int in_w = w / "+e+";\n      int offset_w = imod(w, "+e+");\n      int offset_d = (offset_h * "+e+" + offset_w) *\n        "+this.getOutputDepthSize()+";\n      int in_d = d + offset_d;\n\n      float result = "+this.getInputSamplingString()+";\n      setOutput(result);\n    }\n  ";}return t.prototype.getHeightCoordString=function(){return "NHWC"===this.dataFormat?"coords[1]":"coords[2]"},t.prototype.getWidthCoordString=function(){return "NHWC"===this.dataFormat?"coords[2]":"coords[3]"},t.prototype.getDepthCoordString=function(){return "NHWC"===this.dataFormat?"coords[3]":"coords[1]"},t.prototype.getOutputDepthSize=function(){return "NHWC"===this.dataFormat?this.outputShape[3]:this.outputShape[1]},t.prototype.getInputSamplingString=function(){return "NHWC"===this.dataFormat?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"},t}(),si=function(t){this.variableNames=["X"],this.outputShape=[t,t],this.userCode="\n      void main() {\n          ivec2 coords = getOutputCoords();\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\n          setOutput(val);\n      }\n    ";},ui=function(t){this.variableNames=["A"],this.outTexUsage=zt.DOWNLOAD;var e=ua();this.outputShape=t,this.userCode="\n      "+ha+"\n\n      void main() {\n        float x = getAAtOutCoords();\n        "+e.output+" = encode_float(x);\n      }\n    ";},ci=function(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=zt.DOWNLOAD;var e=ua();this.outputShape=t,this.userCode="\n      "+ha+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n        "+e.output+" = encode_float(x);\n      }\n    ";},li=function(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"];var r=ua(),o=e[0],a=e[1];this.outputShape=t;var i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode="\n      "+la(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        int flatIndex = getFlatIndex(coords);\n        int offset = imod(flatIndex, 4);\n\n        flatIndex = idiv(flatIndex, 4, 1.);\n        \n        int r = flatIndex / "+a+";\n        int c = imod(flatIndex, "+a+");\n        vec2 uv = (vec2(c, r) + halfCR) / vec2("+a+".0, "+o+".0);\n        vec4 values = "+r.texture2D+"(A, uv);\n\n        float result;\n\n        if(offset == 0) {\n          result = values[0];\n        } else if(offset == 1) {\n          result = values[1];\n        } else if(offset == 2) {\n          result = values[2];\n        } else {\n          result = values[3];\n        }\n\n        "+r.output+" = vec4("+i+", 0., 0., 0.);\n      }\n    ";},hi=function(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var r=ua(),o=e[0],a=e[1];this.outputShape=t;var i="",s="result";n&&(s="floor(result * 255. + 0.5)");for(var u=0;u<=1;u++)for(var c=0;c<=1;c++){var l=2*u+c;i+="\n          localCoords = coords;\n          if(localCoords[2] + "+c+" < "+t[2]+") {\n            localCoords[2] += "+c+";\n            if(localCoords[1] + "+u+" < "+t[1]+") {\n              localCoords[1] += "+u+";\n\n              flatIndex = getFlatIndex(localCoords);\n              offset = imod(flatIndex, 4);\n\n              flatIndex = idiv(flatIndex, 4, 1.);\n\n              r = flatIndex / "+a+";\n              c = imod(flatIndex, "+a+");\n              uv = (vec2(c, r) + halfCR) / vec2("+a+".0, "+o+".0);\n              values = "+r.texture2D+"(A, uv);\n\n              if(offset == 0) {\n                result["+l+"] = values[0];\n              } else if(offset == 1) {\n                result["+l+"] = values[1];\n              } else if(offset == 2) {\n                result["+l+"] = values[2];\n              } else {\n                result["+l+"] = values[3];\n              }\n            }\n          }\n        ";}this.userCode="\n      "+la(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        vec4 result = vec4(0.);\n        int flatIndex, r, c, offset;\n        ivec3 localCoords;\n        vec2 uv;\n        vec4 values;\n\n        "+i+"\n\n        "+r.output+" = "+s+";\n      }\n    ";},fi="return real * expR - imag * expI;",di="return real * expI + imag * expR;",pi=function(t,e,n){this.variableNames=["real","imag"];var r=e[1];this.outputShape=e;var o=n?"2.0 * "+Math.PI:"-2.0 * "+Math.PI,a=n?r+".0":"1.0";this.userCode="\n      const float exponentMultiplier = "+o+";\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        "+t+"\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float("+r+");\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < "+r+"; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / "+a+";\n        }\n\n        return result;\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        setOutput(mulMatDFT(coords[0], coords[1]));\n      }\n    ";},vi=function(){function t(t,e){this.outputShape=[],this.variableNames=["x"],this.outputShape=t,this.userCode="\n      uniform float value;\n      void main() {\n        // Input can be obtained from uniform value.\n        setOutput(value);\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.valueLoc&&(e.valueLoc=n.getUniformLocationNoThrow(r,"value")),n.gl.uniform1f(e.valueLoc,t);}},t}(),mi=function(t,e,n){this.variableNames=["A","indices"];var r=t.slice();r[n]=e,this.outputShape=r,this.rank=r.length;var o=wa(this.rank),a=function(t,e){var n=t.length;if(n>4)throw Error("Gather for rank "+n+" is not yet supported");if(1===n)return "int(getIndices(resRC))";for(var r=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],a=0;a<t.length;a++)a===e?o.push("int(getIndices("+r[a]+"))"):o.push(""+r[a]);return o.join()}(t,n);this.userCode="\n      void main() {\n        "+o+" resRC = getOutputCoords();\n        setOutput(getA("+a+"));\n      }\n    ";};var gi=function(t,e,n){this.sliceDim=t,this.strides=e,this.variableNames=["x","indices"],this.outputShape=n;var r=wa(e.length),o=wa(n.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode="\n        "+r+" strides = "+r+"("+this.strides+");\n         void main() {\n          "+o+" coords = getOutputCoords();\n          int flattenIndex = 0;\n          for (int j = 0; j < "+this.sliceDim+"; j++) {\n            int index = round(getIndices(coords[0], j));\n            flattenIndex += index * "+a+";\n          }\n          setOutput(getX(flattenIndex, coords[1]));\n        }\n      ";};function yi(t,e){var n=ua();return oe(t,e,n.version+"\n    precision highp float;\n    "+n.attribute+" vec3 clipSpacePos;\n    "+n.attribute+" vec2 uv;\n    "+n.varyingVs+" vec2 resultUV;\n\n    void main() {\n      gl_Position = vec4(clipSpacePos, 1);\n      resultUV = uv;\n    }")}function xi(t,e){return fe(t,e,new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]))}function bi(t,e){return de(t,e,new Uint16Array([0,1,2,2,1,3]))}function wi(t,e,n,r,o,a,i){ve(n,r);var s=pe(t,e),u=t.TEXTURE_2D;return Jt(t,e,(function(){return t.bindTexture(u,s)})),Jt(t,e,(function(){return t.texParameteri(u,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE)})),Jt(t,e,(function(){return t.texParameteri(u,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE)})),Jt(t,e,(function(){return t.texParameteri(u,t.TEXTURE_MIN_FILTER,t.NEAREST)})),Jt(t,e,(function(){return t.texParameteri(u,t.TEXTURE_MAG_FILTER,t.NEAREST)})),Jt(t,e,(function(){return t.texImage2D(u,0,o,n,r,0,a,i,null)})),Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,null)})),s}function Ci(t,e,n,r,o){var a=Xt(n,r);return wi(t,e,a[0],a[1],o.internalFormatFloat,o.textureFormatFloat,t.FLOAT)}function Ei(t,e,n,r,o){var a=Xt(n,r);return wi(t,e,a[0],a[1],o.internalFormatHalfFloat,o.textureFormatFloat,o.textureTypeHalfFloat)}function Ri(t,e,n,r,o){var a=Xt(n,r);return wi(t,e,a[0],a[1],t.RGBA,t.RGBA,t.UNSIGNED_BYTE)}function Ii(t,e,n,r,o){var a=$t(n,r);return wi(t,e,a[0],a[1],o.internalFormatPackedFloat,t.RGBA,t.FLOAT)}function ki(t,e,n,r,o){var a=$t(n,r);return wi(t,e,a[0],a[1],o.internalFormatPackedHalfFloat,t.RGBA,o.textureTypeHalfFloat)}function Si(t,e,n,r){return Jt(t,e,(function(){return t.bindBuffer(t.ARRAY_BUFFER,r)})),ge(t,e,n,"clipSpacePos",r,3,20,0)&&ge(t,e,n,"uv",r,2,20,12)}function Ai(t,e,n,r,o,a,i){var s,u,c;Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,n)})),a instanceof Uint8Array?(s=new Uint8Array(r*o*4),u=t.UNSIGNED_BYTE,c=t.RGBA):(s=new Float32Array(r*o*4),u=t.FLOAT,c=i.internalFormatPackedFloat),s.set(a),Jt(t,e,(function(){return t.texImage2D(t.TEXTURE_2D,0,c,r,o,0,t.RGBA,u,s)})),Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,null)}));}function Di(t,e,n,r){Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,n)})),r.data instanceof Uint8Array?Jt(t,e,(function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,r.width,r.height,0,t.RGBA,t.UNSIGNED_BYTE,r.data)})):Jt(t,e,(function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,r)})),Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,null)}));}function Ti(t,e,n,r,o){var a=t.createBuffer();Jt(t,e,(function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,a)}));var i=16*n*r;return Jt(t,e,(function(){return t.bufferData(t.PIXEL_PACK_BUFFER,i,t.STREAM_READ)})),Jt(t,e,(function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,0)})),Jt(t,e,(function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,null)})),a}function Ni(t,e,n){var r=t,o=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,e),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,o),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),o}function Fi(t,e,n,r,o){var a=Xt(n,r),i=a[0],s=a[1],u=new Uint8Array(n*r*4);return Jt(t,e,(function(){return t.readPixels(0,0,i,s,o.downloadTextureFormat,t.UNSIGNED_BYTE,u)})),new Float32Array(u.buffer)}function _i(t,e,n,r,o,a,i,s){var u=t,c=new Float32Array(function(t,e){var n=$t(t,e);return n[0]*n[1]*4}(a,i));return u.bindBuffer(u.PIXEL_PACK_BUFFER,e),u.getBufferSubData(u.PIXEL_PACK_BUFFER,0,c),u.bindBuffer(u.PIXEL_PACK_BUFFER,null),c}function Oi(t,e,n,r){var o=new Float32Array(n*r*4);return Jt(t,e,(function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,o)})),o}var Mi=Object.freeze({createVertexShader:yi,createVertexBuffer:xi,createIndexBuffer:bi,createFloat32MatrixTexture:Ci,createFloat16MatrixTexture:Ei,createUnsignedBytesMatrixTexture:Ri,createPackedMatrixTexture:Ii,createFloat16PackedMatrixTexture:ki,bindVertexProgramAttributeStreams:Si,uploadDenseMatrixToTexture:Ai,uploadPixelDataToTexture:Di,createBufferFromOutputTexture:Ti,downloadFloat32MatrixFromBuffer:Ni,downloadByteEncodedFloatMatrixFromOutputTexture:Fi,downloadPackedMatrixFromBuffer:_i,downloadMatrixFromPackedOutputTexture:Oi}),Bi=function(){function t(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];var e=i().getNumber("WEBGL_VERSION");null!=t?(this.gl=t,Kt(e,t)):this.gl=jt(e);var n="WEBGL_color_buffer_float";if(1===i().getNumber("WEBGL_VERSION")){if(this.textureFloatExtension=re(this.gl,this.debug,"OES_texture_float"),Pe(this.gl,"OES_texture_half_float"))this.textureHalfFloatExtension=re(this.gl,this.debug,"OES_texture_half_float");else if(i().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Pe(this.gl,"EXT_color_buffer_half_float"))this.colorBufferHalfFloatExtension=re(this.gl,this.debug,"EXT_color_buffer_half_float");else if(i().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Pe(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else {if(!Pe(this.gl,"EXT_color_buffer_half_float"))throw new Error("GL context does not support color renderable floats");this.colorBufferHalfFloatExtension=this.gl.getExtension("EXT_color_buffer_half_float");}this.vertexBuffer=xi(this.gl,this.debug),this.indexBuffer=bi(this.gl,this.debug),this.framebuffer=me(this.gl,this.debug),this.textureConfig=Qt(this.gl,this.textureHalfFloatExtension);}return Object.defineProperty(t.prototype,"debug",{get:function(){return i().getBool("DEBUG")},enumerable:!0,configurable:!0}),t.prototype.dispose=function(){var t=this;if(!this.disposed){null!=this.program&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),null!=this.outputTexture&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");var e=this.gl;Jt(e,this.debug,(function(){return e.finish()})),Jt(e,this.debug,(function(){return e.bindFramebuffer(e.FRAMEBUFFER,null)})),Jt(e,this.debug,(function(){return e.deleteFramebuffer(t.framebuffer)})),Jt(e,this.debug,(function(){return e.bindBuffer(e.ARRAY_BUFFER,null)})),Jt(e,this.debug,(function(){return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)})),Jt(e,this.debug,(function(){return e.deleteBuffer(t.indexBuffer)})),this.disposed=!0;}},t.prototype.createFloat32MatrixTexture=function(t,e){return this.throwIfDisposed(),Ci(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createFloat16MatrixTexture=function(t,e){return this.throwIfDisposed(),Ei(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createUnsignedBytesMatrixTexture=function(t,e){return this.throwIfDisposed(),Ri(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.uploadPixelDataToTexture=function(t,e){this.throwIfDisposed(),Di(this.gl,this.debug,t,e);},t.prototype.uploadDenseMatrixToTexture=function(t,e,n,r){this.throwIfDisposed(),Ai(this.gl,this.debug,t,e,n,r,this.textureConfig);},t.prototype.createFloat16PackedMatrixTexture=function(t,e){return this.throwIfDisposed(),ki(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createPackedMatrixTexture=function(t,e){return this.throwIfDisposed(),Ii(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.deleteMatrixTexture=function(t){var e=this;this.throwIfDisposed(),this.outputTexture===t&&(Ee(this.gl,this.debug,this.framebuffer),this.outputTexture=null),Jt(this.gl,this.debug,(function(){return e.gl.deleteTexture(t)}));},t.prototype.downloadByteEncodedFloatMatrixFromOutputTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,(function(){return Fi(r.gl,r.debug,e,n,r.textureConfig)}))},t.prototype.downloadPackedMatrixFromBuffer=function(t,e,n,r,o,a){return _i(this.gl,t,0,0,0,o,a,this.textureConfig)},t.prototype.downloadFloat32MatrixFromBuffer=function(t,e){return Ni(this.gl,t,e)},t.prototype.createBufferFromTexture=function(t,e,n){this.bindTextureToFrameBuffer(t);var r=Ti(this.gl,this.debug,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r},t.prototype.createAndWaitForFence=function(){var t=this.createFence(this.gl);return this.pollFence(t)},t.prototype.createFence=function(t){var e,n,r=this;if(i().getBool("WEBGL_FENCE_API_ENABLED")){var o=t,a=o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE,0);t.flush(),n=function(){var t=o.clientWaitSync(a,0,0);return t===o.ALREADY_SIGNALED||t===o.CONDITION_SATISFIED},e=a;}else i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(e=this.beginQuery(),this.endQuery(),n=function(){return r.isQueryAvailable(e,i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}):n=function(){return !0};return {query:e,isFencePassed:n}},t.prototype.downloadMatrixFromPackedTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,(function(){return Oi(r.gl,r.debug,e,n)}))},t.prototype.createProgram=function(t){this.throwIfDisposed();var e=this.gl,n=ae(e,this.debug,t),r=yi(e,this.debug),o=ce(e,this.debug);return Jt(e,this.debug,(function(){return e.attachShader(o,r)})),Jt(e,this.debug,(function(){return e.attachShader(o,n)})),le(e,this.debug,o),this.debug&&he(e,this.debug,o),this.vertexAttrsAreBound||(this.setProgram(o),this.vertexAttrsAreBound=Si(e,this.debug,this.program,this.vertexBuffer)),o},t.prototype.deleteProgram=function(t){var e=this;this.throwIfDisposed(),t===this.program&&(this.program=null),null!=t&&Jt(this.gl,this.debug,(function(){return e.gl.deleteProgram(t)}));},t.prototype.setProgram=function(t){var e=this;this.throwIfDisposed(),this.program=t,null!=this.program&&this.debug&&he(this.gl,this.debug,this.program),Jt(this.gl,this.debug,(function(){return e.gl.useProgram(t)}));},t.prototype.getUniformLocation=function(t,e,n){return void 0===n&&(n=!0),this.throwIfDisposed(),n?xe(this.gl,this.debug,t,e):be(this.gl,t,e)},t.prototype.getAttributeLocation=function(t,e){var n=this;return this.throwIfDisposed(),Jt(this.gl,this.debug,(function(){return n.gl.getAttribLocation(t,e)}))},t.prototype.getUniformLocationNoThrow=function(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)},t.prototype.setInputMatrixTexture=function(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),we(this.gl,this.debug,this.program,t,e,n);},t.prototype.setOutputMatrixTexture=function(t,e,n){this.setOutputMatrixTextureDriver(t,n,e);},t.prototype.setOutputPackedMatrixTexture=function(t,e,n){this.throwIfDisposed();var r=$t(e,n),o=r[0],a=r[1];this.setOutputMatrixTextureDriver(t,o,a);},t.prototype.setOutputMatrixWriteRegion=function(t,e,n,r){this.setOutputMatrixWriteRegionDriver(n,t,r,e);},t.prototype.setOutputPackedMatrixWriteRegion=function(t,e,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")},t.prototype.debugValidate=function(){null!=this.program&&he(this.gl,this.debug,this.program),Re(this.gl);},t.prototype.executeProgram=function(){this.throwIfDisposed(),this.throwIfNoProgram();var t=this.gl;this.debug&&this.debugValidate(),Jt(t,this.debug,(function(){return t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0)}));},t.prototype.blockUntilAllProgramsCompleted=function(){var t=this;this.throwIfDisposed(),Jt(this.gl,this.debug,(function(){return t.gl.finish()}));},t.prototype.getQueryTimerExtension=function(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=re(this.gl,this.debug,2===i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension},t.prototype.getQueryTimerExtensionWebGL2=function(){return this.getQueryTimerExtension()},t.prototype.getQueryTimerExtensionWebGL1=function(){return this.getQueryTimerExtension()},t.prototype.beginQuery=function(){if(2===i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var t=this.gl,e=this.getQueryTimerExtensionWebGL2(),n=t.createQuery();return t.beginQuery(e.TIME_ELAPSED_EXT,n),n}var r=this.getQueryTimerExtensionWebGL1(),o=r.createQueryEXT();return r.beginQueryEXT(r.TIME_ELAPSED_EXT,o),o},t.prototype.endQuery=function(){if(2!==i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var t=this.getQueryTimerExtensionWebGL1();t.endQueryEXT(t.TIME_ELAPSED_EXT);}else {var e=this.gl,n=this.getQueryTimerExtensionWebGL2();e.endQuery(n.TIME_ELAPSED_EXT);}},t.prototype.waitForQueryAndGetTime=function(t){return n(this,void 0,void 0,(function(){var e=this;return r(this,(function(n){switch(n.label){case 0:return [4,F((function(){return e.disposed||e.isQueryAvailable(t,i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}))];case 1:return n.sent(),[2,this.getQueryTime(t,i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))]}}))}))},t.prototype.getQueryTime=function(t,e){if(0===e)return null;if(2===e){var n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}var r=this.getQueryTimerExtensionWebGL1();return r.getQueryObjectEXT(t,r.QUERY_RESULT_EXT)/1e6},t.prototype.isQueryAvailable=function(t,e){if(0===e)return !0;if(2===e){var n=this.gl,r=this.getQueryTimerExtensionWebGL2(),o=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint}o=(r=this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(t,r.QUERY_RESULT_AVAILABLE_EXT);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint},t.prototype.pollFence=function(t){var e=this;return new Promise((function(n){e.addItemToPoll((function(){return t.isFencePassed()}),(function(){return n()}));}))},t.prototype.pollItems=function(){for(var t=function(t){for(var e=0;e<t.length;++e){if(!t[e]())break}return e-1}(this.itemsToPoll.map((function(t){return t.isDoneFn}))),e=0;e<=t;++e){(0, this.itemsToPoll[e].resolveFn)();}this.itemsToPoll=this.itemsToPoll.slice(t+1);},t.prototype.addItemToPoll=function(t,e){var n=this;this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),this.itemsToPoll.length>1||F((function(){return n.pollItems(),0===n.itemsToPoll.length}));},t.prototype.bindTextureToFrameBuffer=function(t){this.throwIfDisposed(),Ce(this.gl,this.debug,t,this.framebuffer),this.debug&&Re(this.gl);},t.prototype.unbindTextureToFrameBuffer=function(){null!=this.outputTexture?(Ce(this.gl,this.debug,this.outputTexture,this.framebuffer),this.debug&&Re(this.gl)):Ee(this.gl,this.debug,this.framebuffer);},t.prototype.downloadMatrixDriver=function(t,e){this.bindTextureToFrameBuffer(t);var n=e();return this.unbindTextureToFrameBuffer(),n},t.prototype.setOutputMatrixTextureDriver=function(t,e,n){this.throwIfDisposed();var r=this.gl;Ce(r,this.debug,t,this.framebuffer),this.debug&&Re(r),this.outputTexture=t,Jt(r,this.debug,(function(){return r.viewport(0,0,e,n)})),Jt(r,this.debug,(function(){return r.scissor(0,0,e,n)}));},t.prototype.setOutputMatrixWriteRegionDriver=function(t,e,n,r){var o=this;this.throwIfDisposed(),Jt(this.gl,this.debug,(function(){return o.gl.scissor(t,e,n,r)}));},t.prototype.throwIfDisposed=function(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")},t.prototype.throwIfNoProgram=function(){if(null==this.program)throw new Error("No GPU program is currently set.")},t}();function Pi(t,e){if(t.length!==e.length)throw Error("Binary was compiled with "+t.length+" inputs, but was executed with "+e.length+" inputs");t.forEach((function(t,n){var r=t.logicalShape,o=e[n],a=o.shape;if(!S(r,a))throw Error("Binary was compiled with different shapes than the current args. Shapes "+r+" and "+a+" must match");if(!t.isUniform||!o.isUniform){var i=t.texShape,s=o.isUniform?null:o.texData.texShape;if(!S(i,s))throw Error("Binary was compiled with different texture shapes than the current args. Shape "+i+" and "+s+" must match")}}));}var Li=function(t,e,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var r=n.filterWidth,o=n.inChannels,a=n.strideWidth,i=n.strideHeight,s=n.padInfo,u=n.outWidth,c=n.dilationWidth,l=n.dilationHeight,h=n.dataFormat,f=s.left,d=s.top,p=o*r,v=ua(),m="channelsLast"===h,g=m?0:1,y=m?1:2,x="",b=0;b<=1;b++)for(var w=0;w<=1;w++)x+="\n          blockIndex = rc.y + "+w+";\n          pos = rc.x + "+b+";\n\n          if(blockIndex < "+t[1]+" && pos < "+t[0]+") {\n            offsetY = int(blockIndex / ("+u+")) * "+i+" - "+d+";\n            d0 = offsetY + "+l+" * (pos / "+p+");\n\n            if(d0 < "+e[g]+" && d0 >= 0) {\n\n              offsetX = int(mod(float(blockIndex), "+u+".) * "+a+". - "+f+".);\n              d1 = offsetX + "+c+" * (int(mod(float(pos), "+p+".) / "+o+".));\n\n              if(d1 < "+e[y]+" && d1 >= 0) {\n\n                ch = int(mod(float(pos), "+o+".));\n\n                if ("+m+") {\n                  innerDims = vec2(d1, ch);\n                  result["+(2*b+w)+"] = getChannel(\n                    getA(d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result["+(2*b+w)+"] = getChannel(\n                    getA(ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        ";this.userCode="\n      void main() {\n        ivec2 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        "+x+"\n\n        "+v.output+" = result;\n      }\n    ";},Wi=function(t,e,n,r,o){this.variableNames=["x"],this.outputShape=[];var a,i=e,s=t[3]-1;this.outputShape=t;var u="float("+n+") + float("+r+") * sum";a=.5===o?"inversesqrt("+u+")":1===o?"1.0/("+u+")":"exp(log("+u+") * float(-"+o+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -"+i+"; j <= "+i+"; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  "+s+") {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * "+a+";\n        setOutput(val);\n      }\n    ";},Ui=function(t,e,n,r,o){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=r,this.beta=o,this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < "+this.depth+"; ++d) {\n          int depthBegin = int(max(0.0, float(d - "+e+")));\n          int depthEnd = int(min(float("+this.depth+"),\n              float(d + "+e+" + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = "+this.depth+";\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float("+r+") * norm + float("+n+");\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float("+r+")\n                * float("+o+")\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * "+o+");\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    ";},Vi=function(t,e,n,r,o){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;var a,i=e,s=t[3]-1;this.outputShape=t;var u="float("+n+") + float("+r+") * sum";a=.5===o?"inversesqrt("+u+")":1===o?"1.0/("+u+")":"exp(log("+u+") * float(-"+o+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < "+this.outputShape[3]+";\n        bool hasNextRow = c < "+this.outputShape[2]+";\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - "+i+";\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - "+i+"; j <= "+i+"; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2("+s+"));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * "+a+";\n        setOutput(result);\n      }\n    ";},zi=function(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideHeight,n=t.strideWidth,r=t.dilationHeight,o=t.effectiveFilterHeight,a=t.effectiveFilterWidth,i=o-1-t.padInfo.top,s=a-1-t.padInfo.left,u=o*a-1;this.userCode="\n      const ivec2 pads = ivec2("+i+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+o+";\n          wR += "+r+") {\n          float dyR = float(dyRCorner + wR) / "+e+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+a+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+n+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = "+u+" - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * "+a+" + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},Gi=function(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.dilationDepth,a=t.dilationHeight,i=t.dilationWidth,s=t.effectiveFilterDepth,u=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=s-1-t.padInfo.front,h=u-1-t.padInfo.top,f=c-1-t.padInfo.left,d=s*u*c-1;this.userCode="\n      const ivec3 pads = ivec3("+l+", "+h+", "+f+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+s+";\n           wD += "+o+") {\n          float dyD = float(dyDCorner + wD) / "+e+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+u+";\n              wR += "+a+") {\n            float dyR = float(dyRCorner + wR) / "+n+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+c+";\n                wC += "+i+") {\n              float dyC = float(dyCCorner + wC) / "+r+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = "+d+" -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * "+u+" * "+c+" +\n                  wR * "+c+" + wC;\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n              dotProd += dyValue * mask;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    ";},Hi=function(t,e,n,r,o,a,i){void 0===n&&(n=!1),void 0===r&&(r=!1),void 0===o&&(o=!1),void 0===a&&(a=null),void 0===i&&(i=!1),this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;var s=n?t[1]:t[2],u=Math.ceil(s/2),c=n?"i * 2, rc.y":"rc.y, i * 2",l=r?"rc.z, i * 2":"i * 2, rc.z",h=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],d="",p="";a&&(d=i?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          "+a+"\n        }":"vec4 activation(vec4 x) {\n          "+a+"\n        }",p="result = activation(result);");var v=o?"result += getBiasAtOutCoords();":"";o&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+d+"\n\n      const float sharedDimension = "+u+".0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < "+u+"; i++) {\n          vec4 a = getMatrixA(rc.x, "+c+");\n          vec4 b = getMatrixB(rc.x, "+l+");\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += ("+h[0]+" * "+f[0]+");\n          result += ("+h[1]+" * "+f[1]+");\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        "+v+"\n\n        "+p+"\n\n        setOutput(result);\n      }\n    ";},qi=function(){function t(t,e,n){this.variableNames=["probs"],this.outputShape=[t,n],this.userCode="\n      uniform float seed;\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < "+(e-1)+"; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float("+(e-1)+"));\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.seedLoc&&(e.seedLoc=n.getUniformLocation(r,"seed")),n.gl.uniform1f(e.seedLoc,t);}},t}(),Ki=function(t,e,n,r){this.variableNames=["indices"],this.outputShape=[t,e],this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float("+r+"), float("+n+"),\n                      float(index == coords.y)));\n      }\n    ";},ji=function(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=t;var e=t.length;if(0===e)this.userCode="\n        void main() {\n          setOutput(vec4(getA(), 0., 0., 0.));\n        }\n      ";else {var n=sa("rc",e),r=wa(e),o=function(t,e,n){if(1===t)return "rc > "+e[0];for(var r="",o=t-2;o<t;o++)r+=n[o]+" >= "+e[o],o<t-1&&(r+="||");return r}(e,t,n),a=function(t,e,n,r){if(1===t)return "";var o=r.slice(-2);return "\n    int r = "+o[0]+";\n    int c = "+o[1]+";\n    int rp1 = r + 1;\n    int cp1 = c + 1;\n\n    bool cEdge = cp1 >= "+e+";\n    bool rEdge = rp1 >= "+n+";\n  "}(e,t[t.length-1],t[t.length-2],n),i=function(t,e){var n=t.length,r=function(t,e){for(var n=[],r=0;r<=1;r++)for(var o=0;o<=1;o++){for(var a=(0===r?"r":"rp1")+", "+(0===o?"c":"cp1"),i=2;i<t;i++)a=e[e.length-1-i]+","+a;n.push(a);}return n}(n,e);return 1===n?"getA(rc),\n            rc + 1 >= "+t[0]+" ? 0. : getA(rc + 1),\n            0, 0":"getA("+r[0]+"),\n          cEdge ? 0. : getA("+r[1]+"),\n          rEdge ? 0. : getA("+r[2]+"),\n          rEdge || cEdge ? 0. : getA("+r[3]+")"}(t,n);this.userCode="\n        void main() {\n          "+r+" rc = getOutputCoords();\n\n          if("+o+") {\n            setOutput(vec4(0));\n          } else {\n            "+a+"\n\n            setOutput(vec4("+i+"));\n          }\n        }\n      ";}};var Xi=function(t,e,n){this.variableNames=["x"],this.outputShape=e.map((function(e,n){return e[0]+t[n]+e[1]}));var r=t.length,o=wa(r),a=e.map((function(t){return t[0]})).join(","),i=e.map((function(e,n){return e[0]+t[n]})).join(","),s=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);this.userCode=1!==r?"\n      "+o+" start = "+o+"("+a+");\n      "+o+" end = "+o+"("+i+");\n\n      void main() {\n        "+o+" outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(float("+n+"));\n        } else {\n          "+o+" coords = outC - start;\n          setOutput(getX("+s+"));\n        }\n      }\n    ":"\n        int start = "+a+";\n        int end = "+i+";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(float("+n+"));\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      ";},Yi=function(t,e,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.map((function(e,n){return e[0]+t[n]+e[1]}));for(var r=t.length,o=wa(r),a=e.map((function(t){return t[0]})).join(","),i=e.map((function(e,n){return e[0]+t[n]})).join(","),s=sa("rc",r),u=sa("source",r),c=s[r-1]+" < "+this.outputShape[r-1],l=1===r?"source":"vec2("+u.slice(-2).join()+")",h=[o+" rc = outputLoc;",s[r-1]+" += 1;\n       if("+c+") {\n      ",1===r?"":"}\n       rc = outputLoc;\n       "+s[r-2]+" += 1;\n       if("+s[r-2]+" < "+this.outputShape[r-2]+") {",1===r?"":"  "+s[r-1]+" += 1;\n         if("+c+") {"],f=1===r?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",d="",p=0,v=1===r?2:4;p<v;p++)d+="\n        "+h[p]+"\n        if ("+f+") {\n          result["+p+"] = float("+n+");\n        } else {\n          "+o+" source = rc - start;\n          result["+p+"] = getChannel(getX("+u.join()+"), "+l+");\n        }\n      ";d+=1===r?"} ":"}}",this.userCode="\n      const "+o+" start = "+o+"("+a+");\n      const "+o+" end = "+o+"("+i+");\n\n      void main() {\n        "+o+" outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        "+d+"\n        setOutput(result);\n      }\n    ";},$i=function(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,o=t.strideHeight,a=t.strideWidth,i=t.dilationHeight,s=t.dilationWidth,u=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=t.padInfo.top,h=t.padInfo.left;this.outputShape=t.outShape;var f="avg"===e,d="0.0";if(f||(d="-1.0 / 1e-20"),n)this.userCode="\n        const ivec2 strides = ivec2("+o+", "+a+");\n        const ivec2 pads = ivec2("+l+", "+h+");\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < "+u+";\n              wR += "+i+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+c+";\n                wC += "+s+") {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value >= currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = wR * "+c+" + wC;\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else {var p=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(p="avgValue / count");var v=4*Math.floor(r/4),m=r%4,g="\n      if ("+f+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec2 strides = ivec2("+o+", "+a+");\n      const ivec2 pads = ivec2("+l+", "+h+");\n      const float initializationValue = "+d+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+d+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < "+u+";\n            wR += "+i+") {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+v+"; wC += 4) {\n            int xC = xCCorner + wC * "+s+";\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              getValue(batch, xR, xC + 2 * "+s+", d),\n              getValue(batch, xR, xC + 3 * "+s+", d)\n            );\n\n            "+g+"\n          }\n\n          int xC = xCCorner + "+v+";\n          if ("+(1===m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            "+g+"\n          } else if ("+(2===m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              initializationValue,\n              initializationValue\n            );\n\n            "+g+"\n          } else if ("+(3===m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              getValue(batch, xR, xC + 2 * "+s+", d),\n              initializationValue\n            );\n\n            "+g+"\n          }\n        }\n        setOutput("+p+");\n      }\n    ";}},Qi=function(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,d=t.padInfo.front,p=t.padInfo.top,v=t.padInfo.left;this.outputShape=t.outShape;var m="avg"===e,g="0.0";if(m||(g="-1.0 / 1e-20"),n)this.userCode="\n        const ivec3 strides =\n            ivec3("+o+", "+a+", "+i+");\n        const ivec3 pads = ivec3("+d+", "+p+", "+v+");\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < "+l+";\n              wD += "+s+") {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int wR = 0; wR < "+h+";\n                wR += "+u+") {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int wC = 0; wC < "+f+";\n                  wC += "+c+") {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value >= currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;\n                  minMaxPosition =\n                      wD * "+h+" * "+f+" +\n                      wR * "+f+" + wC;;\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else {var y=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(y="avgValue / count");var x=4*Math.floor(r/4),b=r%4,w="\n      if ("+m+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec3 strides =\n        ivec3("+o+", "+a+", "+i+");\n      const ivec3 pads = ivec3("+d+", "+p+", "+v+");\n      const float initializationValue = "+g+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+g+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < "+l+";\n            wD += "+s+") {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+h+";\n            wR += "+u+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+x+"; wC += 4) {\n              int xC = xCCorner + wC * "+c+";\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+c+", ch),\n                getValue(batch, xD, xR, xC + 3 * "+c+", ch)\n              );\n\n              "+w+"\n            }\n\n            int xC = xCCorner + "+x+";\n            if ("+(1===b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(2===b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(3===b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+c+", ch),\n                initializationValue\n              );\n\n              "+w+"\n            }\n          }\n          setOutput("+y+");\n        }\n      }\n    ";}},Ji=function(t,e){this.variableNames=["x"];var n=t.windowSize,r=t.batchSize,o=t.inSize,a=Math.ceil(o/n);this.outputShape=[r,a];var i="0.0",s="";"prod"===e?i="1.0":"min"===e?(i="1.0 / 1e-20",s="min"):"max"===e&&(i="-1.0 / 1e-20",s="max");var u=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"sum"===e?u="sumValue":"prod"===e?u="prodValue":"all"===e?u="allValue":"any"===e&&(u="anyValue");var c=4*Math.floor(n/4),l=n%4,h="\n      if ("+("sum"===e)+") {\n        sumValue += dot(values, ones);\n      } else if ("+("prod"===e)+") {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = "+s+"(values, minMaxValue);\n      }\n    ",f="vec4";"all"===e?(i="1.0",h="\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      ",f="bvec4"):"any"===e&&(i="0.0",h="\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      ",f="bvec4");var d="";o%n>0&&(d="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return initializationValue;\n        }\n      "),this.userCode="\n      const float initializationValue = "+i+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        "+d+"\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * "+n+";\n\n        vec4 minMaxValue = vec4("+i+");\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < "+c+"; i += 4) {\n          int inIdx = inOffset + i;\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          "+h+"\n        }\n\n        int inIdx = inOffset + "+c+";\n        if ("+(1===l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          "+h+"\n        } else if ("+(2===l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          "+h+"\n        } else if ("+(3===l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          "+h+"\n        }\n        setOutput("+u+");\n      }\n    ";},Zi=function(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var n="",r=0;r<4;r++){var o="thisRC = rc;";r%2==1&&(o+="thisRC.z += 1;"),r>1&&(o+="thisRC.y += 1;"),n+="\n        "+o+"\n        "+(r>0?"if(thisRC.y < rows && thisRC.z < cols){":"")+"\n          int flatIndex = getFlatIndex(thisRC);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result["+r+"] =\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n        "+(r>0?"}":"")+"\n      ";}this.userCode="\n      \n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      "+ca(["r","c","d"],e)+"\n      return ivec3(r, c, d);\n    }\n  \n      "+la(t)+"\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.);\n\n        ivec3 thisRC;\n        int rows = "+t[1]+";\n        int cols = "+t[2]+";\n\n        "+n+"\n\n        setOutput(result);\n      }\n    ";};var ts=function(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],a=r[2],i=t.shape,s=i[1],u=i[2],c=[n&&s>1?o-1:o,n&&u>1?a-1:a],l=[n&&s>1?s-1:s,n&&u>1?u-1:u],h=c[0]/l[0],f=c[1]/l[1],d=1/h,p=1/f,v=2*Math.ceil(d)+2,m=2*Math.ceil(p)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+h+");\n        const float widthScale = float("+f+");\n\n        const float invHeightScale = float("+d+");\n        const float invWidthScale = float("+p+");\n\n        const int winHeight = int("+v+");\n        const int winWidth = int("+m+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+s+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+u+") {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), "+(o-1)+".0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), "+(a-1)+".0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    ";},es=function(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var o=t[0],a=t[1],i=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/c[0]+",\n          "+u[1]/c[1]+");\n      const vec2 inputShapeRC = vec2("+a+".0, "+i+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    ";},ns=function(t,e,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var o=t[0],a=t[1],i=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode="\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          "+u[0]/c[0]+",\n          "+u[1]/c[1]+",\n          "+u[1]/c[1]+");\n      const vec3 inputShapeRC = vec3("+a+".0, "+i+".0,\n                                     "+i+".0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < "+(s-1)+";\n        bool hasNextRow = coords.z < "+(n-1)+";\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    ";},rs=function(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],a=r[2],i=t.shape,s=i[1],u=i[2],c=[n&&s>1?o-1:o,n&&u>1?a-1:a],l=[n&&s>1?s-1:s,n&&u>1?u-1:u],h=c[0]/l[0],f=c[1]/l[1],d=1/h,p=1/f,v=2*Math.ceil(d)+2,m=2*Math.ceil(p)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+h+");\n        const float widthScale = float("+f+");\n\n        const float invHeightScale = float("+d+");\n        const float invWidthScale = float("+p+");\n\n        const int winHeight = int("+v+");\n        const int winWidth = int("+m+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+s+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+u+") {\n              continue;\n            }\n\n            float sourceFracRow =\n              float("+c[0]+") *\n                (float(dyR) / float("+l[0]+"));\n\n            float sourceFracCol =\n                float("+c[1]+") *\n                  (float(dyC) / float("+l[1]+"));\n\n            int sourceNearestRow = int(min(\n                float(int("+o+") - 1),\n                "+n+" ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int("+a+") - 1),\n                "+n+" ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    ";},os=function(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var o=t[0],a=t[1],i=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n],l=r?"0.5":"0.0";this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/c[0]+",\n          "+u[1]/c[1]+");\n      const vec2 inputShapeRC = vec2("+a+".0, "+i+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + "+l+")));\n\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    ";},as=function(t,e){this.variableNames=["x"];var n=t.length;if(n>4)throw new Error("WebGL backend: Reverse of rank-"+n+" tensor is not yet supported");if(this.outputShape=t,1!==n){var r=t.map((function(n,r){return function(n){return -1!==e.indexOf(n)&&1!==t[n]?t[n]+" - coords["+n+"] - 1":"coords["+n+"]"}(r)})).join(","),o=wa(n);this.userCode="\n      void main() {\n        "+o+" coords = getOutputCoords();\n        setOutput(getX("+r+"));\n      }\n    ";}else this.userCode="\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX("+t[0]+" - coord - 1));\n        }\n      ";},is=function(t,e){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;var n=t.length;if(n>4)throw new Error("WebGL backend: Reverse of rank-"+n+" tensor is not yet supported");this.outputShape=t;var r=sa("rc",n),o=r[n-1]+" + 1 < "+this.outputShape[n-1],a=r[n-2]+" + 1 < "+this.outputShape[n-2],i=wa(n);function s(n){var r=t.map((function(r,o){return function(n,r){return -1!==e.indexOf(n)&&1!==t[n]?t[n]+" - "+r[n]+" - 1":""+r[n]}(o,n)}));return "getChannel(getX("+r.join(",")+"), vec2("+r.slice(-2).join(",")+"))"}this.userCode=1===n?"\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX("+t[0]+" - rc - 1),\n            "+t[0]+" - rc - 1);\n          if("+o+"){\n              result.g = getChannel(getX("+t[0]+" - (rc  + 1) - 1),\n                "+t[0]+" - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      ":"\n        void main() {\n          "+i+" rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = "+function(t){return s(t)}(r.slice())+";\n          if("+o+"){\n            result.g = "+function(t){return t[n-1]="("+t[n-1]+" + 1)",s(t)}(r.slice())+";\n          }\n          if("+a+") {\n            result.b = "+function(t){return t[n-2]="("+t[n-2]+" + 1)",s(t)}(r.slice())+";\n            if("+o+") {\n              result.a = "+function(t){return t[n-1]="("+t[n-1]+" + 1)",t[n-2]="("+t[n-2]+" + 1)",s(t)}(r.slice())+";\n            }\n          }\n          setOutput(result);\n        }\n    ";},ss=function(t,e,n,r,o,a,i){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;var s=wa(o.length),u=wa(a.length),c="";1===n?c="i":2===n&&(c="i, j");var l="getIndices("+c+")",h="";1===r?h="i":2===r&&(h="i, coords[1]");var f="getUpdates("+h+")",d=e>1?"strides[j]":"strides";this.userCode="\n        "+s+" strides = "+s+"("+o+");\n\n        void main() {\n          "+u+" coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < "+t+"; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < "+e+"; j++) {\n              int index = round("+l+");\n              flattenedIndex += index * "+d+";\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += "+f+";\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      ";},us=function(t,e){this.variableNames=["x","segmentIds"];var n=t.windowSize,r=t.batchSize,o=t.inSize,a=t.numSegments,i=a*Math.ceil(o/n);this.outputShape=[r,i];var s=4*Math.floor(n/4),u=n%4,c="\n        sumValue += dot(values, segFilter);\n    ",l="";o%n>0&&(l="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return initializationValue;\n        }\n      ");var h="";o%n>0&&(h="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return -1.0;\n        }\n      "),this.userCode="\n      const float initializationValue = 0.0;\n\n      float getValue(int batch, int inIdx) {\n        "+l+"\n        return getX(batch, inIdx);\n      }\n\n      float getSegmentIdAtIndex(int inIdx) {\n        "+h+"\n        return getSegmentIds(inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = int(floor(float(outIdx) / float(\n          "+a+")) * float("+n+"));\n        int currentSeg = int(mod(float(outIdx), float("+a+")));\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < "+s+"; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n          );\n\n          "+c+"\n        }\n\n        int inIdx = inOffset + "+s+";\n        if ("+(1===u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            0,\n            0,\n            0\n          );\n\n          "+c+"\n        } else if ("+(2===u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n              0,\n              0\n          );\n\n          "+c+"\n        } else if ("+(3===u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            0\n          );\n\n          "+c+"\n        }\n        setOutput(sumValue);\n      }\n    ";},cs=function(t,e,n){var r,o;if(this.variableNames=["c","a","b"],this.outputShape=e,n>4)throw Error("Where for rank "+n+" is not yet supported");if(1===n)o="resRC",r="resRC";else {for(var a=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],s=[],u=0;u<e.length;u++)s.push(""+a[u]),u<t&&i.push(""+a[u]);r=i.join(),o=s.join();}var c=wa(n);this.userCode="\n      void main() {\n        "+c+" resRC = getOutputCoords();\n        float cVal = getC("+r+");\n        if (cVal >= 1.0) {\n          setOutput(getA("+o+"));\n        } else {\n          setOutput(getB("+o+"));\n        }\n      }\n    ";},ls=function(){function t(t){this.variableNames=["source"],this.outputShape=t,this.rank=t.length;var e,n=wa(this.rank),r="uniform int start["+this.rank+"];",o=function(t){if(1===t)return "sourceLoc";if(t<=6)return hs.slice(0,t).map((function(t){return "sourceLoc."+t})).join(",");throw Error("Slicing for rank "+t+" is not yet supported")}(this.rank);e="\n        "+n+" sourceLoc;\n        "+n+" coords = getOutputCoords();\n        "+t.map((function(t,e){return "sourceLoc."+hs[e]+" = start["+e+"] + coords."+hs[e]+";"})).join("\n")+"\n      ",this.userCode="\n      "+r+"\n      void main() {\n        "+e+"\n        setOutput(getSource("+o+"));\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+t.length+")");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,"start"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t);}},t}(),hs=["x","y","z","w","u","v"];var fs=function(){function t(t){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length;var e=wa(this.rank),n=sa("coords",this.rank),r=sa("sourceLoc",this.rank),o=1===this.rank?"sourceLoc":"vec2("+r.slice(-2).join()+")",a="getChannel(getSource("+r.join()+"), "+o+")",i="\n      result.x = "+a+";\n      if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n        ++"+r[this.rank-1]+";\n        result.y = "+a+";\n        --"+r[this.rank-1]+";\n      }\n    ",s=1===this.rank?"":"\n      --"+n[this.rank-1]+";\n      if (++"+n[this.rank-2]+" < "+t[this.rank-2]+") {\n        ++"+r[this.rank-2]+";\n        result.z = "+a+";\n        if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n          ++"+r[this.rank-1]+";\n          result.w = "+a+";\n        }\n      }\n    ",u=this.rank<=4?"sourceLoc = coords +\n            "+e+"("+t.map((function(t,e){return "start["+e+"]"})).join()+");":t.map((function(t,e){return r[e]+" = "+n[e]+" + start["+e+"];"})).join("\n");this.userCode="\n      uniform int start["+this.rank+"];\n      void main() {\n        "+e+" coords = getOutputCoords();\n        "+e+" sourceLoc;\n        "+u+"\n        vec4 result = vec4(0.);\n        "+i+"\n        "+s+"\n        setOutput(result);\n      }\n    ";}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+t.length+")");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,"start"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t);}},t}(),ds=function(t,e,n){this.variableNames=["x"],this.outputShape=n;var r=n.length,o=wa(n.length),a=wa(n.length),i="";if(1===r)i="coords * strides + begin";else {var s=0;i=n.map((function(t,e){return s++,1===n.length?"coords * strides["+e+"] + begin["+e+"]":"coords["+(s-1)+"] * strides["+e+"] + begin["+e+"]"})).join(",");}this.userCode="\n      "+o+" begin = "+o+"("+t+");\n      "+o+" strides = "+o+"("+e+");\n\n      void main() {\n        "+a+" coords = getOutputCoords();\n        setOutput(getX("+i+"));\n      }\n    ";},ps=function(){function t(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={};}return t.prototype.acquireTexture=function(t,e,n){var r,o=vs(e,n),a=ms(t,o,n);if(a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]),this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this.log();var i=this.freeTextures[a].shift();return this.usedTextures[a].push(i),i}return this.numUsedTextures++,this.log(),o===Gt.PACKED_2X2_FLOAT32?r=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Gt.PACKED_2X2_FLOAT16?r=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Gt.UNPACKED_FLOAT32?r=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Gt.UNPACKED_FLOAT16?r=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Gt.PACKED_4X1_UNSIGNED_BYTE&&(r=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[a].push(r),r},t.prototype.releaseTexture=function(t,e,n,r){if(null!=this.freeTextures){var o=ms(e,vs(n,r),r);o in this.freeTextures||(this.freeTextures[o]=[]),this.freeTextures[o].push(t),this.numFreeTextures++,this.numUsedTextures--;var a=this.usedTextures[o],i=a.indexOf(t);if(i<0)throw new Error("Cannot release a texture that was never provided by this texture manager");a.splice(i,1),this.log();}},t.prototype.log=function(){if(this.logEnabled){var t=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",this.numFreeTextures+" / "+this.numUsedTextures,"("+t+")");}},t.prototype.getNumUsedTextures=function(){return this.numUsedTextures},t.prototype.getNumFreeTextures=function(){return this.numFreeTextures},t.prototype.dispose=function(){var t=this;if(null!=this.freeTextures){for(var e in this.freeTextures)this.freeTextures[e].forEach((function(e){t.gpgpu.deleteMatrixTexture(e);}));for(var e in this.usedTextures)this.usedTextures[e].forEach((function(e){t.gpgpu.deleteMatrixTexture(e);}));this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0;}},t}();function vs(t,e){if(t===zt.UPLOAD)return Gt.PACKED_2X2_FLOAT32;if(t===zt.RENDER||null==t)return function(t){return i().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?t?Gt.PACKED_2X2_FLOAT32:Gt.UNPACKED_FLOAT32:t?Gt.PACKED_2X2_FLOAT16:Gt.UNPACKED_FLOAT16}(e);if(t===zt.DOWNLOAD||t===zt.PIXELS)return Gt.PACKED_4X1_UNSIGNED_BYTE;throw new Error("Unknown logical texture type "+t)}function ms(t,e,n){return t[0]+"_"+t[1]+"_"+e+"_"+n}var gs=function(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[r]*e[r];this.outputShape=n,this.rank=n.length;var o=wa(this.rank),a=function(t){var e=t.length;if(e>5)throw Error("Tile for rank "+e+" is not yet supported");if(1===e)return "imod(resRC, "+t[0]+")";for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[],o=0;o<t.length;o++)r.push("imod("+n[o]+", "+t[o]+")");return r.join()}(t);this.userCode="\n      void main() {\n        "+o+" resRC = getOutputCoords();\n        setOutput(getA("+a+"));\n      }\n    ";};var ys=function(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];this.outputShape=n,this.rank=n.length;var o=wa(this.rank),a=function(t){var e=t.length;if(e>6)throw Error("Transpose for rank "+e+" is not yet supported");for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(e),o=0;o<t.length;o++)r[t[o]]=n[o];return r.join()}(e);this.userCode="\n    void main() {\n      "+o+" resRC = getOutputCoords();\n      setOutput(getA("+a+"));\n    }\n    ";};var xs=function(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error("Packed transpose for rank "+this.rank+" is not yet supported.");var o=wa(this.rank),a=ia("rc",this.rank),i=new Array(this.rank);for(r=0;r<e.length;r++)i[e[r]]=a[r];var s="vec2("+i.slice(-2).join()+")",u="++"+a[this.rank-1]+" < "+n[this.rank-1],c="getChannel(getA("+i.join()+"), "+s+")";this.userCode="\n    void main() {\n      "+o+" rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = "+c+";\n      if("+u+") {\n        result[1] = "+c+";\n      }\n      --"+a[this.rank-1]+";\n      if(++"+a[this.rank-2]+" < "+n[this.rank-2]+") {\n        result[2] = "+c+";\n        if("+u+") {\n          result[3] = "+c+";\n        }\n      }\n      setOutput(result);\n    }\n    ";},bs=1.7580993408473768,ws=1.0507009873554805,Cs=function(t,e){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      float unaryOperation(float x) {\n        "+e+"\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    ";},Es="if (isnan(x)) return x;",Rs="return x;",Is="return abs(x);",ks=Es+"\n  return (x < 0.0) ? 0.0 : x;\n",Ss=Es+"\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n",As="return (x >= 0.0) ? x : (exp(x) - 1.0);",Ds="\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = "+bs+";\n  float scale = "+ws+";\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n";var Ts="return -x;",Ns="return ceil(x);",Fs="return floor(x);",_s="return exp(x);",Os="return exp(x) - 1.0;",Ms=Es+"\n  return sin(x);\n",Bs=Es+"\n  return cos(x);\n",Ps=Es+"\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return asin(x);\n",Ls=Es+"\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return acos(x);\n",Ws=Es+"\n  return atan(x);\n",Us=Es+"return log(x + sqrt(x * x + 1.0));",Vs=Es+"\n  if (x < 1.0) return NAN;\n  return log(x + sqrt(x * x - 1.0));",zs=Es+"\n  if ((x < -1.0) || (x > 1.0)) return NAN;\n  return (log(1.0 + x) - log(1.0 - x)) / 2.0;",Gs="return x;",Hs="return x;",qs="\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",Ks="\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",js="\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n",Xs=function(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode="\n      vec4 unaryOperation(vec4 x) {\n        "+e+"\n      }\n\n      void main() {\n        vec4 x = getAAtOutCoords();\n        vec4 y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    ";},Ys=function(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=t;var e=t.length,n=sa("rc",e),r=wa(e),o=function(t,e){if(1===t)return "rc";for(var n="",r=0;r<t;r++)n+=e[r],r<t-1&&(n+=",");return n}(e,n),a=n.slice(-2),i=e<=1?"rc":"vec2("+a.join(",")+")";this.userCode="\n      void main() {\n        "+r+" rc = getOutputCoords();\n        vec4 packedInput = getA("+o+");\n\n        setOutput(getChannel(packedInput, "+i+"));\n      }\n    ";},$s={};function Qs(t,e){if(void 0===e&&(e=!1),"linear"===t)return e?Hs:Rs;if("relu"===t)return e?qs:ks;if("elu"===t)return e?js:As;if("relu6"===t)return e?Ks:Ss;if("prelu"===t)return e?Pa:Ma;throw new Error("Activation "+t+" has not been implemented for the WebGL backend.")}var Js=600;var Zs=function(t){function o(e){var n,r=t.call(this)||this;if(r.pendingRead=new WeakMap,r.pendingDisposal=new WeakSet,r.dataRefCount=new WeakMap,r.numBytesInGPU=0,r.uploadWaitMs=0,r.downloadWaitMs=0,r.warnedAboutMemory=!1,r.pendingDeletes=0,r.disposed=!1,!i().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(null==e){var o=jt(i().getNumber("WEBGL_VERSION"));r.binaryCache=(n=i().getNumber("WEBGL_VERSION"))in $s?$s[n]:($s[n]={},$s[n]),r.gpgpu=new Bi(o),r.canvas=o.canvas,r.gpgpuCreatedLocally=!0;}else r.gpgpu=e,r.binaryCache={},r.gpgpuCreatedLocally=!1,r.canvas=e.gl.canvas;return r.textureManager=new ps(r.gpgpu),r.numMBBeforeWarning=null==i().global.screen?1024:i().global.screen.height*i().global.screen.width*window.devicePixelRatio*Js/1024/1024,r.texData=new xo(r,Lt),r}return e(o,t),o.prototype.numDataIds=function(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes},o.prototype.write=function(t,e,n){if(i().getBool("DEBUG")&&this.checkNumericalProblems(t),"complex64"===n&&null!=t)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");var r={};return this.texData.set(r,{shape:e,dtype:n,values:t,usage:zt.UPLOAD}),r},o.prototype.move=function(t,e,n,r){if(i().getBool("DEBUG")&&this.checkNumericalProblems(e),"complex64"===r)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:r,values:e,usage:zt.UPLOAD});},o.prototype.readSync=function(t){var e=this.texData.get(t),n=e.values,r=e.dtype,o=e.complexTensors,a=e.slice,i=e.shape,s=e.isPacked;if(null!=a){var u=void 0;u=s?new Xs(i,Gs):new Cs(i,Gs);var c=this.runWebGLProgram(u,[{dataId:t,shape:i,dtype:r}],r),l=this.readSync(c.dataId);return this.disposeData(c.dataId),l}if(null!=n)return this.convertAndCacheOnCPU(t);if("string"===r)return n;var h,f,d=null!=this.activeTimers;(d&&(h=et()),"complex64"===r)?f=Vo(o.real.dataSync(),o.imag.dataSync()):f=this.getValuesFromTexture(t);return d&&(this.downloadWaitMs+=et()-h),this.convertAndCacheOnCPU(t,f)},o.prototype.read=function(t){return n(this,void 0,void 0,(function(){var e,n,o,a,s,u,c,l,h,f,d,p,v,m,g,y,x,b,w,C,E,R;return r(this,(function(r){switch(r.label){case 0:if(this.pendingRead.has(t))return e=this.pendingRead.get(t),[2,new Promise((function(t){return e.push(t)}))];if(n=this.texData.get(t),o=n.values,a=n.shape,s=n.slice,u=n.dtype,c=n.complexTensors,l=n.isPacked,null!=s)return h=void 0,h=l?new Xs(a,Gs):new Cs(a,Gs),f=this.runWebGLProgram(h,[{dataId:t,shape:a,dtype:u}],u),d=this.read(f.dataId),this.disposeData(f.dataId),[2,d];if(null!=o)return [2,this.convertAndCacheOnCPU(t)];if(!i().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&2===i().getNumber("WEBGL_VERSION"))throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");return p=null,"complex64"!==u&&i().get("WEBGL_BUFFER_SUPPORTED")&&(v=this.decode(t),m=this.texData.get(v.dataId),p=(R=this.gpgpu).createBufferFromTexture.apply(R,[m.texture].concat(Yt(a)))),this.pendingRead.set(t,[]),"complex64"===u?[3,2]:[4,this.gpgpu.createAndWaitForFence()];case 1:r.sent(),r.label=2;case 2:return "complex64"!==u?[3,4]:[4,Promise.all([c.real.data(),c.imag.data()])];case 3:return y=r.sent(),x=y[0],b=y[1],g=Vo(x,b),[3,5];case 4:null==p?g=this.getValuesFromTexture(t):(w=k(a),g=this.gpgpu.downloadFloat32MatrixFromBuffer(p,w)),r.label=5;case 5:return null!=v&&this.disposeData(v.dataId),C=this.convertAndCacheOnCPU(t,g),E=this.pendingRead.get(t),this.pendingRead.delete(t),E.forEach((function(t){return t(C)})),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t),this.pendingDeletes--),[2,C]}}))}))},o.prototype.checkNumericalProblems=function(t){if(null!=t)for(var e=0;e<t.length;e++){var n=t[e];if(!ee(n)){if(i().getBool("WEBGL_RENDER_FLOAT32_CAPABLE"))throw Error("The value "+n+" cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'");throw Error("The value "+n+" cannot be represented on this device.")}}},o.prototype.getValuesFromTexture=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,a=n.isPacked,s=k(r);if(i().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){var u=this.decode(t),c=this.texData.get(u.dataId),l=(e=this.gpgpu).downloadMatrixFromPackedTexture.apply(e,[c.texture].concat(Yt(r))).subarray(0,s);return this.disposeData(u.dataId),l}var h=i().getBool("WEBGL_PACK")&&!0===a,f=h?Te(r):r,d=h?new ci(f):new ui(f),p=this.runWebGLProgram(d,[{shape:f,dtype:o,dataId:t}],"float32"),v=this.texData.get(p.dataId),m=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(v.texture,v.texShape[0],v.texShape[1]).subarray(0,s);return this.disposeData(p.dataId),m},o.prototype.time=function(t){return n(this,void 0,void 0,(function(){var e,n,o,a,s,u,c;return r(this,(function(r){switch(r.label){case 0:return e=this.activeTimers,n=[],o=!1,null==this.programTimersStack?(this.programTimersStack=n,o=!0):this.activeTimers.push(n),this.activeTimers=n,t(),a=I(this.activeTimers.map((function(t){return t.query}))).filter((function(t){return null!=t})),s=I(this.activeTimers.map((function(t){return t.name}))).filter((function(t){return null!=t})),this.activeTimers=e,o&&(this.programTimersStack=null),u={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?[4,Promise.all(a)]:[3,2];case 1:return c=r.sent(),u.kernelMs=w(c),u.getExtraProfileInfo=function(){return c.map((function(t,e){return {name:s[e],ms:t}})).map((function(t){return t.name+": "+t.ms})).join(", ")},[3,3];case 2:u.kernelMs={error:"WebGL query timers are not supported in this environment."},r.label=3;case 3:return this.uploadWaitMs=0,this.downloadWaitMs=0,[2,u]}}))}))},o.prototype.memory=function(){return {unreliable:!1,numBytesInGPU:this.numBytesInGPU}},o.prototype.startTimer=function(){return i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:et(),endMs:null}},o.prototype.endTimer=function(t){return i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=et(),t)},o.prototype.getQueryTime=function(t){return n(this,void 0,void 0,(function(){var e;return r(this,(function(n){return i().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?[2,this.gpgpu.waitForQueryAndGetTime(t)]:[2,(e=t).endMs-e.startMs]}))}))},o.prototype.disposeData=function(t){if(!this.pendingDisposal.has(t)){if(this.pendingRead.has(t))return this.pendingDisposal.add(t),void this.pendingDeletes++;if(this.texData.has(t)){this.releaseGPUData(t);var e=this.texData.get(t).complexTensors;null!=e&&(e.real.dispose(),e.imag.dispose()),this.texData.delete(t);}}},o.prototype.releaseGPUData=function(t){var e=this.texData.get(t),n=e.texture,r=e.dtype,o=e.texShape,a=e.usage,i=e.isPacked,s=e.slice,u=s&&s.origDataId||t,c=this.dataRefCount.get(u);c>1?this.dataRefCount.set(u,c-1):(this.dataRefCount.delete(u),null!=n&&(this.numBytesInGPU-=this.computeBytes(o,r),this.textureManager.releaseTexture(n,o,a,i)));var l=this.texData.get(t);l.texture=null,l.texShape=null,l.isPacked=!1,l.slice=null;},o.prototype.getTexture=function(t){return this.uploadToGPU(t),this.texData.get(t).texture},o.prototype.getDataInfo=function(t){return this.texData.get(t)},o.prototype.getCPUBackend=function(){return i().getBool("WEBGL_CPU_FORWARD")?(null==this.cpuBackend&&(this.cpuBackend=Lt.findBackend("cpu")),this.cpuBackend):null},o.prototype.shouldExecuteOnCPU=function(t,e){var n=this;return void 0===e&&(e=128),null!=this.getCPUBackend()&&t.every((function(t){return null==n.texData.get(t.dataId).texture&&t.size<e}))},o.prototype.getGPGPUContext=function(){return this.gpgpu},o.prototype.complex=function(t,e){var n=this.makeOutput(t.shape,"complex64");return this.texData.get(n.dataId).complexTensors={real:Lt.keep(t.clone()),imag:Lt.keep(e.clone())},n},o.prototype.real=function(t){return this.texData.get(t.dataId).complexTensors.real.clone()},o.prototype.imag=function(t){return this.texData.get(t.dataId).complexTensors.imag.clone()},o.prototype.slice=function(t,e,n){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.slice(t,e,n);if(0===k(n))return Fn([],n,t.dtype);var r=this.texData.get(t.dataId).isPacked,o=io(t.shape,e,n);if(r||!o){var a=i().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new fs(n):new ls(n),s=a.getCustomSetupFunc(e);return this.compileAndRun(a,[t],null,s)}return this.uploadToGPU(t.dataId),this.shallowSlice(t,e,n)},o.prototype.shallowSlice=function(t,e,n){var r=this.texData.get(t.dataId),o=this.makeOutput(n,t.dtype),a=this.texData.get(o.dataId);Object.assign(a,r),a.shape=n,a.dtype=t.dtype;var i=so(e,t.strides);r.slice&&(i+=r.slice.flatOffset),a.slice={flatOffset:i,origDataId:r.slice&&r.slice.origDataId||t.dataId};var s=this.dataRefCount.get(a.slice.origDataId)||1;return this.dataRefCount.set(a.slice.origDataId,s+1),o},o.prototype.stridedSlice=function(t,e,n,r){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.stridedSlice(t,e,n,r);var o=ro(e,n,r);if(o.some((function(t){return 0===t})))return Fn([],o);var a=new ds(e,r,o);return this.compileAndRun(a,[t])},o.prototype.reverse=function(t,e){var n=i().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new is(t.shape,e):new as(t.shape,e);return this.compileAndRun(n,[t])},o.prototype.concat=function(t,e){if("complex64"===t[0].dtype){var n=t.map((function(t){return Tn(t)})),r=t.map((function(t){return Nn(t)}));return Dn(this.concat(n,e),this.concat(r,e))}if(this.shouldExecuteOnCPU(t))return this.cpuBackend.concat(t,e);if(1===t.length)return t[0];if(t.length>i().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){var o=Math.floor(t.length/2),a=this.concat(t.slice(0,o),e),s=this.concat(t.slice(o),e);return this.concat([a,s],e)}if(i().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&t[0].rank>1){var u=new Ga(t.map((function(t){return t.shape})),e);return this.compileAndRun(u,t)}var c=Sn(t.map((function(t){return t.shape})),e),l=t.map((function(t){return t.as2D(-1,k(t.shape.slice(e)))})),h=new za(l.map((function(t){return t.shape})));return this.compileAndRun(h,l).reshape(c)},o.prototype.neg=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.neg(t);if(i().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Ts,t.dtype);var e=new Cs(t.shape,Ts);return this.compileAndRun(e,[t])},o.prototype.batchMatMul=function(t,e,n,r){var o=n?t.shape[2]:t.shape[1],a=r?e.shape[1]:e.shape[2],i=n?t.shape[1]:t.shape[2],s=t.shape[0];if((1===o||1===a)&&i>1e3){n&&(t=t.transpose([0,2,1])),r&&(e=e.transpose([0,2,1]));var u=1===a?t:t.as3D(s,i,1),c=1===a?2:1,l=1===a?e.as3D(s,1,i):e;return this.multiply(u,l).sum(c,!0)}var h=Dt(t.dtype,e.dtype),f=new Hi(t.shape,[s,o,a],n,r);return this.compileAndRun(f,[t,e],h)},o.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,a=t.bias,i=t.activation,s=t.preluActivationWeights,u=r?e.shape[2]:e.shape[1],c=o?n.shape[1]:n.shape[2],l=e.shape[0],h=Dt(e.dtype,n.dtype),f=null!=a,d=null!=s,p=i?Qs(i,!0):null,v=new Hi(e.shape,[l,u,c],r,o,f,p,d),m=[e,n];return a&&m.push(a),s&&m.push(s),this.compileAndRun(v,m,h)},o.prototype.multiply=function(t,e){if("complex64"===t.dtype){var n=this.texData.get(t.dataId),r=this.texData.get(e.dataId),o=new Na(Da,t.shape,e.shape),a=new Na(Ta,t.shape,e.shape),s=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag),this.makeComplexComponentTensorInfo(e,r.complexTensors.real),this.makeComplexComponentTensorInfo(e,r.complexTensors.imag)],u=this.compileAndRun(o,s),c=this.compileAndRun(a,s),l=this.complex(u,c);return u.dispose(),c.dispose(),l}if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.multiply(t,e);if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,Oa,t.dtype);var h=new Ba(Oa,t.shape,e.shape);return this.compileAndRun(h,[t,e],t.dtype)},o.prototype.batchNormalization=function(t,e,n,r,o,a){var s=[t,e,n],u=null;null!=a&&(u=a.shape,s.push(a));var c=null;if(null!=o&&(c=o.shape,s.push(o)),i().getBool("WEBGL_PACK_NORMALIZATION")){var l=new Aa(t.shape,e.shape,n.shape,u,c,r);return this.compileAndRun(l,s)}var h=new Sa(t.shape,e.shape,n.shape,u,c,r);return this.compileAndRun(h,s)},o.prototype.localResponseNormalization4D=function(t,e,n,r,o){var a=i().getBool("WEBGL_PACK_NORMALIZATION")?new Vi(t.shape,e,n,r,o):new Wi(t.shape,e,n,r,o);return this.compileAndRun(a,[t])},o.prototype.LRNGrad=function(t,e,n,r,o,a,i){var s=new Ui(e.shape,r,o,a,i);return this.compileAndRun(s,[e,n,t])},o.prototype.tile=function(t,e){if("string"===t.dtype){var n=this.readSync(t.dataId).map((function(t){return ot(t)}));return ta(dr(t.shape,t.dtype,n),e)}var r=new gs(t.shape,e);return this.compileAndRun(r,[t])},o.prototype.pad=function(t,e,n){var r=i().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Yi(t.shape,e,n):new Xi(t.shape,e,n);return this.compileAndRun(r,[t])},o.prototype.transpose=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.transpose(t,e);var n=i().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new xs(t.shape,e):new ys(t.shape,e);return this.compileAndRun(n,[t])},o.prototype.gather=function(t,e,n){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.gather(t,e,n);var r=new mi(t.shape,e.size,n);return this.compileAndRun(r,[t,e])},o.prototype.batchToSpaceND=function(t,e,n){C(t.rank<=4,(function(){return "batchToSpaceND for rank > 4 with a WebGL backend not implemented yet"}));var r=e.reduce((function(t,e){return t*e})),o=zr(t.shape,e,r),a=Gr(o.length,e.length),i=Hr(t.shape,e,r),s=qr(n,e.length),u=Kr(i,n,e.length);return t.reshape(o).transpose(a).reshape(i).slice(s,u)},o.prototype.spaceToBatchND=function(t,e,n){C(t.rank<=4,(function(){return "spaceToBatchND for rank > 4 with a WebGL backend not implemented yet"}));var r=e.reduce((function(t,e){return t*e})),o=[[0,0]];o.push.apply(o,n);for(var a=1+e.length;a<t.shape.length;++a)o.push([0,0]);var i=t.pad(o),s=zr(i.shape,e,r,!1),u=Gr(s.length,e.length,!1),c=Hr(i.shape,e,r,!1);return i.reshape(s).transpose(u).reshape(c)},o.prototype.reduce=function(t,e,n){var r=t.shape[0],o=t.shape[1],a=$r(o),i=new Ji({windowSize:a,inSize:o,batchSize:r},e),s=this.compileAndRun(i,[t],n);return 1===s.shape[1]?s:this.reduce(s,e,n)},o.prototype.argReduce=function(t,e,n){void 0===n&&(n=null);var r=t.shape[0],o=t.shape[1];null!=n&&(r=n.shape[0],o=n.shape[1]);var a=$r(o),i=new aa({windowSize:a,inSize:o,batchSize:r},e,null==n),s=[t];null!=n&&s.push(n);var u=this.compileAndRun(i,s,"int32");return 1===u.shape[1]?u:this.argReduce(t,e,u)},o.prototype.argReducePacked=function(t,e,n){void 0===n&&(n=null);var r=null!=n?n.shape:t.shape,o=$r(r[r.length-1]),a=new Ra(r,o,e,null==n),i=null==n?[t]:[t,n],s=this.compileAndRun(a,i,"int32");return s.rank===t.rank?this.argReducePacked(t,e,s):s},o.prototype.sum=function(t,e){Cn("sum",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o),i=Tt(t.dtype);return this.reduce(a,"sum",i).reshape(r)},o.prototype.prod=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.prod(t,e);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o),i=Tt(t.dtype);return this.reduce(a,"prod",i).reshape(r)},o.prototype.unsortedSegmentSum=function(t,e,n){var r=0,o=En([r],t.rank),a=t;null!=o&&(a=t.transpose(o),r=In(1,t.rank)[0]);var i=function(t,e,n){for(var r=[],o=t.length,a=0;a<o;a++)a!==e?r.push(t[a]):r.push(n);return r}(a.shape,r,n),s=k([a.shape[r]]),u=a.as2D(-1,s),c=Tt(t.dtype),l=this.segOpCompute(u,"unsortedSegmentSum",e,c,n).reshape(i);return null!=o&&(l=l.transpose(Rn(o))),l},o.prototype.segOpCompute=function(t,e,n,r,o){var a=t.shape[0],i=t.shape[1],s=function(t,e){var n,r=!1;for(t<=Yr?(n=t,r=!0):n=Y(t,Math.floor(Math.sqrt(t)));!r;)n>e||n===t?r=!0:n=Y(t,n+1);return n}(i,o),u=new us({windowSize:s,inSize:i,batchSize:a,numSegments:o},e),c=this.compileAndRun(u,[t,n],r);return c.shape[1]===o?c:(n=Kn(0,o).tile([i/s]),this.segOpCompute(c,e,n,r,o))},o.prototype.argMinMaxReduce=function(t,e,n){var r=[e];if(Cn("arg"+n.charAt(0).toUpperCase()+n.slice(1),r,t.rank),!i().getBool("WEBGL_PACK_REDUCE")||t.rank<=2){var o=bn(t.shape,r),a=o[0],s=k(o[1]),u=t.as2D(-1,s);return this.argReduce(u,n).reshape(a)}return this.argReducePacked(t,n)},o.prototype.argMin=function(t,e){return this.argMinMaxReduce(t,e,"min")},o.prototype.argMax=function(t,e){return this.argMinMaxReduce(t,e,"max")},o.prototype.cumsum=function(t,e,n,r){if(e!==t.rank-1)throw new Error("WebGL cumsum shader expects an inner-most axis="+(t.rank-1)+" but got axis="+e);var o=new ni(t.shape,n,r);return this.compileAndRun(o,[t])},o.prototype.equal=function(t,e){if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(equal(a, b));\n","bool");var n=new Ba("return float(a == b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.notEqual=function(t,e){if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(notEqual(a, b));\n","bool");var n=new Ba("return float(a != b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.less=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.less(t,e);if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(lessThan(a, b));\n","bool");var n=new Ba("return float(a < b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.lessEqual=function(t,e){if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(lessThanEqual(a, b));\n","bool");var n=new Ba("return float(a <= b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.greater=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.greater(t,e);if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(greaterThan(a, b));\n","bool");var n=new Ba("return float(a > b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.greaterEqual=function(t,e){if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(greaterThanEqual(a, b));\n","bool");var n=new Ba("return float(a >= b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.logicalNot=function(t){var e=new Cs(t.shape,"return float(!(x >= 1.0));");return this.compileAndRun(e,[t])},o.prototype.logicalAnd=function(t,e){if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n","bool");var n=new Ba("return float(a >= 1.0 && b >= 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.logicalOr=function(t,e){if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n","bool");var n=new Ba("return float(a >= 1.0 || b >= 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},o.prototype.select=function(t,e,n){var r=new cs(t.rank,e.shape,e.rank);return this.compileAndRun(r,[t,e,n],Dt(e.dtype,n.dtype))},o.prototype.where=function(t){dn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");var e=t.dataSync();return na(t.shape,e)},o.prototype.topk=function(t,e,n){return ea(t.dataSync(),t.shape,t.dtype,e)},o.prototype.min=function(t,e){Cn("min",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o);return this.reduce(a,"min",a.dtype).reshape(r)},o.prototype.minimum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.minimum(t,e);var n=i().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new La("\n  vec4 result = vec4(min(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new Ba("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return min(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.mod=function(t,e){var n=i().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new La("\n  vec4 result = mod(a, b);\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new Ba("if (b == 0.0) return NAN;\n  return mod(a, b);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.max=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.max(t,e);Cn("max",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o);return this.reduce(a,"max",a.dtype).reshape(r)},o.prototype.maximum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.maximum(t,e);var n=i().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new La("\n  vec4 result = vec4(max(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new Ba("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return max(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.all=function(t,e){Cn("all",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o);return this.reduce(a,"all",a.dtype).reshape(r)},o.prototype.any=function(t,e){Cn("any",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o);return this.reduce(a,"any",a.dtype).reshape(r)},o.prototype.realDivide=function(t,e){if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS")){return this.packedBinaryOp(t,e,"\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n","float32",!0)}var n=new Ba("\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;",t.shape,e.shape);return this.compileAndRun(n,[t,e],"float32")},o.prototype.floorDiv=function(t,e){if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    result[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    result[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    result[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    result[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4(result);\n","int32");var n=new Ba("\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n",t.shape,e.shape);return this.compileAndRun(n,[t,e],"int32")},o.prototype.add=function(t,e){if("complex64"===t.dtype&&"complex64"===e.dtype)return this.complexSeparableBinaryOp(t,e,Fa);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.add(t,e);var n=Dt(t.dtype,e.dtype);if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,Fa,n);var r=new Ba(Fa,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},o.prototype.packedUnaryOp=function(t,e,n){var r=new Xs(t.shape,e);return this.compileAndRun(r,[t],n)},o.prototype.packedBinaryOp=function(t,e,n,r,o){void 0===o&&(o=!1);var a=new La(n,t.shape,e.shape,o);return this.compileAndRun(a,[t,e],r)},o.prototype.complexSeparableBinaryOp=function(t,e,n){var r=this,o=this.texData.get(t.dataId),a=this.texData.get(e.dataId),i=[[o.complexTensors.real,a.complexTensors.real],[o.complexTensors.imag,a.complexTensors.imag]].map((function(o){var a=o[0],i=o[1],s=r.makeComplexComponentTensorInfo(t,a),u=r.makeComplexComponentTensorInfo(e,i),c=new Ba(n,t.shape,e.shape);return r.compileAndRun(c,[s,u],Dt(a.dtype,i.dtype))})),s=i[0],u=i[1],c=this.complex(s,u);return s.dispose(),u.dispose(),c},o.prototype.makeComplexComponentTensorInfo=function(t,e){return {dataId:e.dataId,dtype:e.dtype,shape:t.shape}},o.prototype.addN=function(t){if(1===t.length)return t[0];if(t.length>i().get("WEBGL_MAX_TEXTURES_IN_SHADER")){var e=Math.floor(t.length/2),n=this.addN(t.slice(0,e)),r=this.addN(t.slice(e));return this.addN([n,r])}var o=t.map((function(t){return t.dtype})).reduce((function(t,e){return Dt(t,e)})),a=t.map((function(t){return t.shape})),s=i().getBool("WEBGL_PACK")?new oa(t[0].shape,a):new ra(t[0].shape,a);return this.compileAndRun(s,t,o)},o.prototype.subtract=function(t,e){if("complex64"===t.dtype&&"complex64"===e.dtype)return this.complexSeparableBinaryOp(t,e,_a);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.subtract(t,e);var n=Dt(t.dtype,e.dtype);if(i().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,_a,t.dtype);var r=new Ba(_a,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},o.prototype.pow=function(t,e){var n=i().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new La("\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new Ba("\nif(a < 0.0 && floor(b) < b){\n  return NAN;\n}\nif (b == 0.0) {\n  return 1.0;\n}\nreturn (round(mod(b, 2.0)) != 1) ?\n    pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",t.shape,e.shape),r=Dt(t.dtype,e.dtype);return this.compileAndRun(n,[t,e],r)},o.prototype.ceil=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.ceil(t);if(i().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Ns,t.dtype);var e=new Cs(t.shape,Ns);return this.compileAndRun(e,[t])},o.prototype.floor=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.floor(t);if(i().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Fs,t.dtype);var e=new Cs(t.shape,Fs);return this.compileAndRun(e,[t])},o.prototype.sign=function(t){var e=new Cs(t.shape,"\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n");return this.compileAndRun(e,[t])},o.prototype.isNaN=function(t){var e=new Cs(t.shape,"return float(isnan(x));");return this.compileAndRun(e,[t],"bool")},o.prototype.isInf=function(t){var e=new Cs(t.shape,"return float(isinf(x));");return this.compileAndRun(e,[t],"bool")},o.prototype.isFinite=function(t){var e=new Cs(t.shape,"return float(!isnan(x) && !isinf(x));");return this.compileAndRun(e,[t],"bool")},o.prototype.round=function(t){var e=new Cs(t.shape,"\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n");return this.compileAndRun(e,[t])},o.prototype.exp=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.exp(t);if(i().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,_s,t.dtype);var e=new Cs(t.shape,_s);return this.compileAndRun(e,[t])},o.prototype.expm1=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.expm1(t);if(i().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Os,t.dtype);var e=new Cs(t.shape,Os);return this.compileAndRun(e,[t])},o.prototype.softmax=function(t,e){var n=O([e],t.shape),r=this.max(t,n),o=wn(r.shape,n),a=this.subtract(t,r.reshape(o)),i=this.exp(a),s=this.sum(i,n).reshape(o);return this.realDivide(i,s)},o.prototype.log=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.log(t);if(i().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,"\n  vec4 result = log(x);\n  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\n\n  return result;\n",t.dtype);var e=new Cs(t.shape,"if (x < 0.0) return NAN;\n  return log(x);");return this.compileAndRun(e,[t])},o.prototype.log1p=function(t){var e=new Cs(t.shape,"return log(1.0 + x);");return this.compileAndRun(e,[t])},o.prototype.sqrt=function(t){var e=new Cs(t.shape,"return sqrt(x);");return this.compileAndRun(e,[t])},o.prototype.rsqrt=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.rsqrt(t);var e=new Cs(t.shape,"return inversesqrt(x);");return this.compileAndRun(e,[t])},o.prototype.reciprocal=function(t){var e=new Cs(t.shape,"return 1.0 / x;");return this.compileAndRun(e,[t])},o.prototype.relu=function(t){var e;return e=i().getBool("WEBGL_PACK")?new Xs(t.shape,qs):new Cs(t.shape,ks),this.compileAndRun(e,[t])},o.prototype.relu6=function(t){var e;return e=i().getBool("WEBGL_PACK")?new Xs(t.shape,Ks):new Cs(t.shape,Ss),this.compileAndRun(e,[t])},o.prototype.prelu=function(t,e){var n=i().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new La(Pa,t.shape,e.shape):new Ba(Ma,t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.elu=function(t){if(i().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,js,t.dtype);var e=new Cs(t.shape,As);return this.compileAndRun(e,[t])},o.prototype.eluDer=function(t,e){var n=i().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new La("\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\n",t.shape,e.shape):new Ba("return (b >= 1.0) ? a : a * (b + 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.selu=function(t){var e=new Cs(t.shape,Ds);return this.compileAndRun(e,[t])},o.prototype.int=function(t){var e=new Cs(t.shape,"return float(int(x));");return this.compileAndRun(e,[t],"int32")},o.prototype.clip=function(t,e,n){var r,o=(r=i().getBool("WEBGL_PACK_CLIP")?new Ua(t.shape):new Wa(t.shape)).getCustomSetupFunc(e,n);return this.compileAndRun(r,[t],null,o)},o.prototype.abs=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.abs(t);if(i().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Is,t.dtype);var e=new Cs(t.shape,Is);return this.compileAndRun(e,[t])},o.prototype.complexAbs=function(t){var e=this.texData.get(t.dataId),n=new Va(t.shape),r=[this.makeComplexComponentTensorInfo(t,e.complexTensors.real),this.makeComplexComponentTensorInfo(t,e.complexTensors.imag)];return this.compileAndRun(n,r)},o.prototype.sigmoid=function(t){var e=new Cs(t.shape,"return 1.0 / (1.0 + exp(-1.0 * x));");return this.compileAndRun(e,[t])},o.prototype.softplus=function(t){var e=new Cs(t.shape,"\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n");return this.compileAndRun(e,[t])},o.prototype.sin=function(t){var e=new Cs(t.shape,Ms);return this.compileAndRun(e,[t])},o.prototype.cos=function(t){var e=new Cs(t.shape,Bs);return this.compileAndRun(e,[t])},o.prototype.tan=function(t){var e=new Cs(t.shape,"return tan(x);");return this.compileAndRun(e,[t])},o.prototype.asin=function(t){var e=new Cs(t.shape,Ps);return this.compileAndRun(e,[t])},o.prototype.acos=function(t){var e=new Cs(t.shape,Ls);return this.compileAndRun(e,[t])},o.prototype.atan=function(t){var e=new Cs(t.shape,Ws);return this.compileAndRun(e,[t])},o.prototype.atan2=function(t,e){var n=i().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new La("\n  vec4 result = atan(a, b);\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new Ba("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return atan(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.sinh=function(t){var e=new Cs(t.shape,"\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},o.prototype.cosh=function(t){var e=new Cs(t.shape,"\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},o.prototype.tanh=function(t){var e=new Cs(t.shape,"\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n");return this.compileAndRun(e,[t])},o.prototype.asinh=function(t){var e=new Cs(t.shape,Us);return this.compileAndRun(e,[t])},o.prototype.acosh=function(t){var e=new Cs(t.shape,Vs);return this.compileAndRun(e,[t])},o.prototype.atanh=function(t){var e=new Cs(t.shape,zs);return this.compileAndRun(e,[t])},o.prototype.erf=function(t){var e=new Cs(t.shape,'\n  // Error function is calculated approximately with elementary function.\n  // See "Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables", Abramowitz and Stegun.\n  float p = 0.3275911;\n  float a1 = 0.254829592;\n  float a2 = -0.284496736;\n  float a3 = 1.421413741;\n  float a4 = -1.453152027;\n  float a5 = 1.061405429;\n\n  float sign = sign(x);\n  x = abs(x);\n  float t = 1.0 / (1.0 + p * x);\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\n');return this.compileAndRun(e,[t])},o.prototype.step=function(t,e){var n=new Cs(t.shape,function(t){return void 0===t&&(t=0),Es+"\n    return x > 0.0 ? 1.0 : float("+t+");\n  "}(e));return this.compileAndRun(n,[t])},o.prototype.conv2dByMatMul=function(t,e,n,r,o,a){var s=t.shape,u=this.texData.get(t.dataId),c=n.inChannels,l=s[0]*s[1]*s[2],h=n.outChannels,f="channelsLast"===n.dataFormat,d=(1===l||1===h)&&c>1e3,p=s[2]%2!=0&&!!u.isPacked;if(d||!i().getBool("WEBGL_LAZILY_UNPACK")||!i().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!p){var v=f?s[0]*s[1]*s[2]:s[0]*s[2]*s[3],m=this.reshape(t,[1,v,n.inChannels]),g=this.reshape(e,[1,n.inChannels,n.outChannels]);return this.reshape(this.fusedBatchMatMul({a:m,b:g,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:a}),n.outShape)}var y=f?s[0]*s[1]*(s[2]+1):s[0]*s[2]*(s[3]+1),x={dataId:t.dataId,shape:[1,y,n.inChannels],dtype:t.dtype},b=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,C(_e(u.shape,x.shape),(function(){return "packed reshape "+u.shape+" to "+x.shape+" isn't free"}));var w=this.reshape(e,[1,n.inChannels,n.outChannels]),E=this.fusedBatchMatMul({a:x,b:w,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:a}),R=this.texData.get(E.dataId);return C(R.isPacked,(function(){return "batchMatMul result is expected to be packed"})),u.shape=b,R.shape=n.outShape,Lt.makeTensorFromDataId(E.dataId,n.outShape,E.dtype)},o.prototype.conv2dWithIm2Row=function(t,e,n,r,o,a){var i=n.filterWidth,s=n.filterHeight,u=n.inChannels,c=n.outWidth,l=n.outHeight,h="channelsLast"===n.dataFormat,f=i*s*u,d=l*c,p=[f,d],v=t.squeeze([0]),m=e.reshape([1,f,-1]),g=new Li(p,v.shape,n),y=this.compileAndRun(g,[v]).reshape([1,p[0],p[1]]),x=null!=r,b=null!=a,w=o?Qs(o,!0):null,C=new Hi(y.shape,[1,d,n.outChannels],!0,!1,x,w,b),E=[y,m];r&&E.push(r),b&&E.push(a);var R=this.compileAndRun(C,E);return h?R.reshape([1,l,c,n.outChannels]):R.reshape([1,n.outChannels,l,c])},o.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,s=t.preluActivationWeights;if(1===r.filterHeight&&1===r.filterWidth&&1===r.dilationHeight&&1===r.dilationWidth&&1===r.strideHeight&&1===r.strideWidth&&("SAME"===r.padInfo.type||"VALID"===r.padInfo.type))return this.conv2dByMatMul(e,n,r,o,a,s);if(i().getBool("WEBGL_CONV_IM2COL")&&1===e.shape[0])return this.conv2dWithIm2Row(e,n,r,o,a,s);var u=null!=o,c=null!=s,l=a?Qs(a,!1):null,h=new Qa(r,u,l,c),f=[e,n];return o&&f.push(o),s&&f.push(s),this.compileAndRun(h,f)},o.prototype.conv2d=function(t,e,n){if(1===n.filterHeight&&1===n.filterWidth&&1===n.dilationHeight&&1===n.dilationWidth&&1===n.strideHeight&&1===n.strideWidth&&("SAME"===n.padInfo.type||"VALID"===n.padInfo.type))return this.conv2dByMatMul(t,e,n);if(i().getBool("WEBGL_CONV_IM2COL")&&1===t.shape[0])return this.conv2dWithIm2Row(t,e,n);var r=new Qa(n);return this.compileAndRun(r,[t,e])},o.prototype.conv2dDerInput=function(t,e,n){var r=new Ka(n);return this.compileAndRun(r,[t,e])},o.prototype.conv2dDerFilter=function(t,e,n){var r=new qa(n);return this.compileAndRun(r,[t,e])},o.prototype.fusedDepthwiseConv2D=function(t){var e,n=t.input,r=t.filter,o=t.convInfo,a=t.bias,s=t.activation,u=t.preluActivationWeights,c=i().getBool("WEBGL_PACK_DEPTHWISECONV")&&o.strideWidth<=2&&o.outChannels/o.inChannels==1,l=s?Qs(s,c):null,h=[n,r],f=null!=a,d=null!=u;return f&&h.push(a),d&&h.push(u),c?(e=new ti(o,f,l,d),this.compileAndRun(e,h)):(e=new Za(o,f,l,d),this.compileAndRun(e,h))},o.prototype.depthwiseConv2D=function(t,e,n){var r;return i().getBool("WEBGL_PACK_DEPTHWISECONV")&&n.strideWidth<=2&&n.outChannels/n.inChannels==1?(r=new ti(n),this.compileAndRun(r,[t,e])):(r=new Za(n),this.compileAndRun(r,[t,e]))},o.prototype.depthwiseConv2DDerInput=function(t,e,n){var r=new $a(n);return this.compileAndRun(r,[t,e])},o.prototype.depthwiseConv2DDerFilter=function(t,e,n){var r=new Ya(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3d=function(t,e,n){var r=new Ja(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3dDerInput=function(t,e,n){var r=new Xa(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3dDerFilter=function(t,e,n){var r=new ja(n);return this.compileAndRun(r,[t,e])},o.prototype.maxPool=function(t,e){var n=new $i(e,"max",!1);return this.compileAndRun(n,[t])},o.prototype.avgPool=function(t,e){var n=new $i(e,"avg",!1);return this.compileAndRun(n,[t],"float32")},o.prototype.maxPoolBackprop=function(t,e,n,r){var o=new $i(r,"max",!0),a=this.compileAndRun(o,[e]),i=new zi(r),s=this.compileAndRun(i,[t,a],e.dtype);return a.dispose(),s},o.prototype.avgPoolBackprop=function(t,e,n){var r=new Ia(n);return this.compileAndRun(r,[t],e.dtype)},o.prototype.cast=function(t,e){return Po(t,e,this)},o.prototype.unstack=function(t,e){for(var n=t.shape[e],r=new Array(t.rank-1),o=0,a=0;a<t.rank;a++)a!==e&&(r[o++]=t.shape[a]);var i=new Array(t.rank).fill(0),s=t.shape.slice();s[e]=1;var u=new Array(n);for(a=0;a<u.length;a++)i[e]=a,u[a]=this.slice(t,i,s).reshape(r);return u},o.prototype.avgPool3d=function(t,e){var n=new Qi(e,"avg",!1);return this.compileAndRun(n,[t],"float32")},o.prototype.avgPool3dBackprop=function(t,e,n){var r=new ka(n);return this.compileAndRun(r,[t],e.dtype)},o.prototype.maxPool3d=function(t,e){var n=new Qi(e,"max",!1);return this.compileAndRun(n,[t],"float32")},o.prototype.maxPool3dBackprop=function(t,e,n,r){var o=new Qi(r,"max",!0),a=this.compileAndRun(o,[e]),i=new Gi(r),s=this.compileAndRun(i,[t,a],e.dtype);return a.dispose(),s},o.prototype.reshape=function(t,e){var n=this.texData.get(t.dataId);if(n.isPacked&&!_e(t.shape,e)&&(null===n.texture||!_e(n.shape,e))){var r=this.packedReshape(t,e);return Lt.makeTensorFromDataId(r.dataId,r.shape,r.dtype)}return Lo(t,e)},o.prototype.resizeBilinear=function(t,e,n,r){var o=i().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new ns(t.shape,e,n,r):new es(t.shape,e,n,r);return this.compileAndRun(o,[t],"float32")},o.prototype.resizeBilinearBackprop=function(t,e,n){var r=new ts(t,e,n);return this.compileAndRun(r,[t])},o.prototype.resizeNearestNeighbor=function(t,e,n,r){var o=new os(t.shape,e,n,r);return this.compileAndRun(o,[t])},o.prototype.resizeNearestNeighborBackprop=function(t,e,n){var r=new rs(t,e,n);return this.compileAndRun(r,[t])},o.prototype.multinomial=function(t,e,n,r){var o=e?t:go(t),a=o.shape[0],i=o.shape[1],s=new qi(a,i,n),u=s.getCustomSetupFunc(r);return this.compileAndRun(s,[o],"int32",u)},o.prototype.oneHot=function(t,e,n,r){var o=new Ki(t.size,e,n,r);return this.compileAndRun(o,[t])},o.prototype.diag=function(t){var e=new si(t.size);return this.compileAndRun(e,[t])},o.prototype.nonMaxSuppression=function(t,e,n,r,o){return dn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead"),jo(t.dataSync(),e.dataSync(),n,r,o)},o.prototype.cropAndResize=function(t,e,n,r,o,a){var i=new ei(t.shape,e.shape,r,o,a);return this.compileAndRun(i,[t,e,n],"float32")},o.prototype.depthToSpace=function(t,e,n){C(e>1,(function(){return "blockSize should be > 1 for depthToSpace, but was: "+e}));var r=t.shape[0],o="NHWC"===n?t.shape[1]:t.shape[2],a="NHWC"===n?t.shape[2]:t.shape[3],i="NHWC"===n?t.shape[3]:t.shape[1],s=o*e,u=a*e,c=i/(e*e),l=new ii("NHWC"===n?[r,s,u,c]:[r,c,s,u],e,n);return this.compileAndRun(l,[t])},o.prototype.split=function(t,e,n){return Zo(t,e,n)},o.prototype.scatterND=function(t,e,n){var r=Zr(0,t,n),o=r.sliceRank,a=r.numUpdates,i=r.sliceSize,s=r.strides,u=r.outputSize,c=[u/i,i],l=t.reshape([a,o]),h=e.reshape([a,i]);if(0===u)return Lo(Fn([]),n);var f=On(0),d=new ss(a,o,l.rank,h.rank,s,c);return this.compileAndRun(d,[h,l,f]).reshape(n)},o.prototype.sparseToDense=function(t,e,n,r){var o=Zr(0,t,n),a=o.sliceRank,i=o.numUpdates,s=o.strides,u=o.outputSize,c=new ss(i,a,t.rank,e.rank,s,[u,1],!1);return this.compileAndRun(c,[e,t,r]).reshape(n)},o.prototype.fft=function(t){return this.fftImpl(t,!1)},o.prototype.ifft=function(t){return this.fftImpl(t,!0)},o.prototype.fftImpl=function(t,e){var n=this.texData.get(t.dataId),r=new pi(fi,t.shape,e),o=new pi(di,t.shape,e),a=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag)],i=this.compileAndRun(r,a),s=this.compileAndRun(o,a),u=this.complex(i,s).as2D(t.shape[0],t.shape[1]);return i.dispose(),s.dispose(),u},o.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=jr(t,e),a=o[0],i=o[1],s=o[2],u=o[3],c=e.reshape([i,r]),l=t.reshape([t.size/s,s]),h=new gi(r,u,[i,s]);return this.compileAndRun(h,[l,c]).reshape(a)},o.prototype.fill=function(t,e,n){if("string"===(n=n||j(e))){var r=P(n,k(t));return r.fill(e),Lt.makeTensor(r,t,n,this)}var o=new vi(t,e),a=o.getCustomSetupFunc(e);return this.compileAndRun(o,[],n,a)},o.prototype.onesLike=function(t){if("string"===t.dtype)throw new Error("onesLike is not supported under string dtype");return this.fill(t.shape,1,t.dtype)},o.prototype.zerosLike=function(t){return this.fill(t.shape,"string"===t.dtype?"":0,t.dtype)},o.prototype.linspace=function(t,e,n){return Wo(t,e,n)},o.prototype.makeTensorInfo=function(t,e){var n=this.write(null,t,e);return this.texData.get(n).usage=null,{dataId:n,shape:t,dtype:e}},o.prototype.makeOutput=function(t,e){var n=this.makeTensorInfo(t,e).dataId;return Lt.makeTensorFromDataId(n,t,e,this)},o.prototype.unpackTensor=function(t){var e=new Ys(t.shape);return this.runWebGLProgram(e,[t],t.dtype)},o.prototype.packTensor=function(t){var e=new ji(t.shape);return this.runWebGLProgram(e,[t],t.dtype,null,!0)},o.prototype.packedReshape=function(t,e){var n=[Ae(t.shape)].concat(De(t.shape)),r={dtype:t.dtype,shape:n,dataId:t.dataId},o=[Ae(e)].concat(De(e)),a=new Zi(o,n),i=this.runWebGLProgram(a,[r],t.dtype,null,!0);return {dataId:i.dataId,shape:e,dtype:i.dtype}},o.prototype.decode=function(t){var e,n=this.texData.get(t),r=n.isPacked,o=n.shape,a=n.dtype,i=Te(o);e=r?new ai(i):new oi(i);return {dtype:a,shape:o,dataId:this.runWebGLProgram(e,[{shape:i,dtype:a,dataId:t}],a,null,!0).dataId}},o.prototype.runWebGLProgram=function(t,e,n,r,o){var a=this;void 0===o&&(o=!1);var s=this.makeTensorInfo(t.outputShape,n),u=this.texData.get(s.dataId);if(t.packedOutput&&(u.isPacked=!0),t.outPackingScheme===Vt.DENSE){var c=Yt(t.outputShape);u.texShape=c.map((function(t){return 2*t}));}if(null!=t.outTexUsage&&(u.usage=t.outTexUsage),0===k(s.shape))return u.values=B(s.dtype,0),s;var l=[],h=e.map((function(e){if("complex64"===e.dtype)throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");var n=a.texData.get(e.dataId);if(null==n.texture){if(!t.packedInputs&&k(e.shape)<=i().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return {shape:e.shape,texData:null,isUniform:!0,uniformValues:n.values};t.packedInputs&&(n.isPacked=!0,n.shape=e.shape);}else if(!!n.isPacked!=!!t.packedInputs)e=n.isPacked?a.unpackTensor(e):a.packTensor(e),l.push(e),n=a.texData.get(e.dataId);else if(n.isPacked&&!_e(n.shape,e.shape)){var r=e,o=e.shape;e.shape=n.shape,e=a.packedReshape(e,o),l.push(e),n=a.texData.get(e.dataId),r.shape=o;}return a.uploadToGPU(e.dataId),{shape:e.shape,texData:n,isUniform:!1}}));this.uploadToGPU(s.dataId);var f,d={shape:s.shape,texData:u,isUniform:!1},p=function(t,e,n){var r="";e.concat(n).forEach((function(t){var e=null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0,n=t.isUniform?"uniform":t.texData.texShape;r+=t.shape+"_"+n+"_"+e;}));var o=t.userCode,a=t.constructor.name;return a+="_"+r+"_"+o}(t,h,d),v=this.getAndSaveBinary(p,(function(){return function(t,e,n,r){var o=e.userCode,a=n.map((function(t,n){var r={logicalShape:t.shape,texShape:t.isUniform?null:t.texData.texShape,isUniform:t.isUniform,isPacked:!t.isUniform&&t.texData.isPacked,flatOffset:null};return null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0&&(r.flatOffset=t.texData.slice.flatOffset),{name:e.variableNames[n],shapeInfo:r}})),s=a.map((function(t){return t.shapeInfo})),u={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},c=fa(a,u,o,e.packedInputs),l=t.createProgram(c),h=null,f=t.getUniformLocation(l,"NAN",!1);1===i().getNumber("WEBGL_VERSION")&&(h=t.getUniformLocation(l,"INFINITY",!1));for(var d={},p=0;p<e.variableNames.length;p++){var v=e.variableNames[p];d[v]=t.getUniformLocation(l,v,!1),d["offset"+v]=t.getUniformLocation(l,"offset"+v,!1);}return {program:e,source:c,webGLProgram:l,uniformLocations:d,inShapeInfos:s,outShapeInfo:u,infLoc:h,nanLoc:f}}(a.gpgpu,t,h,d)})),m=null!=this.activeTimers;if(m&&(f=this.startTimer()),function(t,e,n,r,o){Pi(e.inShapeInfos,n),Pi([e.outShapeInfo],[r]);var a=r.texData.texture,s=r.texData.texShape;r.texData.isPacked?t.setOutputPackedMatrixTexture(a,s[0],s[1]):t.setOutputMatrixTexture(a,s[0],s[1]),t.setProgram(e.webGLProgram),1===i().getNumber("WEBGL_VERSION")&&null!==e.infLoc&&t.gl.uniform1f(e.infLoc,1/0),null!==e.nanLoc&&t.gl.uniform1f(e.nanLoc,NaN),n.forEach((function(n,r){var o=e.program.variableNames[r],a=e.uniformLocations[o],i=e.uniformLocations["offset"+o];if(null!=a)if(n.isUniform)if(k(n.shape)<2)t.gl.uniform1f(a,n.uniformValues[0]);else {var s=n.uniformValues;s instanceof Float32Array||(s=new Float32Array(s)),t.gl.uniform1fv(a,s);}else null!=n.texData.slice&&null!=i&&t.gl.uniform1i(i,n.texData.slice.flatOffset),t.setInputMatrixTexture(n.texData.texture,a,r);})),null!=o&&o(t,e.webGLProgram),t.executeProgram();}(this.gpgpu,v,h,d,r),l.forEach((function(t){return a.disposeData(t.dataId)})),m&&(f=this.endTimer(f),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(f)})),!i().getBool("WEBGL_LAZILY_UNPACK")&&u.isPacked&&!1===o){var g=this.unpackTensor(s);return this.disposeData(s.dataId),g}return s},o.prototype.compileAndRun=function(t,e,n,r,o){void 0===o&&(o=!1),n=n||e[0].dtype;var a=this.runWebGLProgram(t,e,n,r,o);return Lt.makeTensorFromDataId(a.dataId,a.shape,a.dtype)},o.prototype.getAndSaveBinary=function(t,e){return t in this.binaryCache||(this.binaryCache[t]=e()),this.binaryCache[t]},o.prototype.getTextureManager=function(){return this.textureManager},o.prototype.dispose=function(){var t=this;if(!this.disposed){if(!i().getBool("IS_TEST"))Object.keys(this.binaryCache).forEach((function(e){t.gpgpu.deleteProgram(t.binaryCache[e].webGLProgram),delete t.binaryCache[e];}));this.textureManager.dispose(),null!=this.canvas&&"undefined"!=typeof HTMLCanvasElement&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0;}},o.prototype.floatPrecision=function(){var t=this;return null==this.floatPrecisionValue&&(this.floatPrecisionValue=Ze((function(){if(!i().get("WEBGL_RENDER_FLOAT32_ENABLED")){var e=i().getBool("DEBUG");i().set("DEBUG",!1);var n=t.abs(On(1e-8)).dataSync()[0];if(i().set("DEBUG",e),n>0)return 32}return 16}))),this.floatPrecisionValue},o.prototype.epsilon=function(){return 32===this.floatPrecision()?1e-7:1e-4},o.prototype.uploadToGPU=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,a=n.values,i=n.texture,s=n.usage,u=n.isPacked;if(null==i){var c,l=null!=this.activeTimers;l&&(c=et());var h=n.texShape;if(null==h&&(h=Ne(r,u),n.texShape=h),null!=a){var f=Te(r),d=void 0,p=h[1],v=h[0],m=a instanceof Uint8Array;u?(p=(e=$t(h[0],h[1]))[0],v=e[1],d=new hi(f,[v,p],m)):d=new li(f,[v,p],m);var g=this.makeTensorInfo([v,p],o);this.texData.get(g.dataId).usage=m?zt.PIXELS:zt.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId),p,v,a);var y=this.runWebGLProgram(d,[g],o,null,!0),x=this.texData.get(y.dataId);n.texture=x.texture,n.texShape=x.texShape,n.isPacked=x.isPacked,n.usage=x.usage,this.disposeData(g.dataId),this.texData.delete(y.dataId),n.values=null,l&&(this.uploadWaitMs+=et()-c);}else {var b=this.acquireTexture(h,s,o,u);n.texture=b;}}},o.prototype.convertAndCacheOnCPU=function(t,e){var n=this.texData.get(t),r=n.dtype;return this.releaseGPUData(t),null!=e&&(n.values=function(t,e){if("float32"===e||"complex64"===e)return t;if("int32"===e||"bool"===e){for(var n="int32"===e?new Int32Array(t.length):new 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Lt.runKernelFunc((function(t){return t.floor(e)}),{$x:e},(function(t){return {$x:function(){return Xn(t)}}}))}}),yu=An({log_:function(t){var e=mn(t,"x","log"),n=[e];return Lt.runKernelFunc((function(t,n){var r=t.log(e);return n([e]),r}),{x:e},(function(t,e){var n=e[0];return {x:function(){return t.div(n.toFloat())}}}),"Log",{},n)}}),xu=An({log1p_:function(t){var e=mn(t,"x","log1p");return Lt.runKernelFunc((function(t,n){var r=t.log1p(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return {$x:function(){return t.div(n.add(1))}}}))}}),bu=An({logSigmoid_:function(t){var e=mn(t,"x","logSigmoid");return Lt.runKernelFunc((function(t,n){var r=t.softplus(e.neg()).neg();return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return {$x:function(){return t.mul(n.neg().sigmoid())}}}))}}),wu=An({neg_:function(t){var e=mn(t,"x","neg"),n=[e];return Lt.runKernelFunc((function(t){return t.neg(e)}),{x:e},(function(t){return {x:function(){return 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{$x:function(){return n.toFloat().cosh().mulStrict(t)}}}))}}),Fu=An({softplus_:function(t){var e=mn(t,"x","softplus");return Lt.runKernelFunc((function(t,n){var r=t.softplus(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return {$x:function(){return t.mul(n.sigmoid())}}}))}}),_u=An({sqrt_:function(t){var e=mn(t,"x","sqrt");return Lt.runKernelFunc((function(t,n){var r=t.sqrt(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return {$x:function(){return t.div(n.toFloat().sqrt().mul(2))}}}))}}),Ou=An({step_:function(t,e){void 0===e&&(e=0);var n=mn(t,"x","step");return Lt.runKernelFunc((function(t){return t.step(n,e)}),{$x:n},(function(t){return {$x:function(){return Xn(t)}}}))}}),Mu=An({tan_:function(t){var e=mn(t,"x","tan");return Lt.runKernelFunc((function(t,n){var r=t.tan(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return {$x:function(){return t.div(n.cos().square())}}}))}}),Bu=An({tanh_:function(t){var e=mn(t,"x","tanh");return Lt.runKernelFunc((function(t,n){var r=t.tanh(e);return n([r]),r}),{x:e},(function(t,e){var n=e[0];return {x:function(){return On(1).sub(n.square()).mulStrict(t)}}}),"Tanh",{},null,[!0])}});function Pu(t,e,n,r,o,a){var i,s,u=mn(t,"x","batchNorm"),c=mn(e,"mean","batchNorm"),l=mn(n,"variance","batchNorm");return null!=o&&(i=mn(o,"scale","batchNorm")),null!=r&&(s=mn(r,"offset","batchNorm")),C(2===u.rank,(function(){return "Error in batchNorm3D: x must be rank 3 but got rank "+u.rank+"."})),C(2===c.rank||1===c.rank,(function(){return "Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank "+c.rank+"."})),C(2===l.rank||1===l.rank,(function(){return "Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank "+l.rank+"."})),null!=i&&C(2===i.rank||1===i.rank,(function(){return "Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank "+i.rank+"."})),null!=s&&C(2===s.rank||1===s.rank,(function(){return "Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank "+s.rank+"."})),Uu(u,c,l,s,i,a)}function Lu(t,e,n,r,o,a){var i,s,u=mn(t,"x","batchNorm"),c=mn(e,"mean","batchNorm"),l=mn(n,"variance","batchNorm");return null!=o&&(i=mn(o,"scale","batchNorm")),null!=r&&(s=mn(r,"offset","batchNorm")),C(3===u.rank,(function(){return "Error in batchNorm3D: x must be rank 3 but got rank "+u.rank+"."})),C(3===c.rank||1===c.rank,(function(){return "Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank "+c.rank+"."})),C(3===l.rank||1===l.rank,(function(){return "Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank "+l.rank+"."})),null!=i&&C(3===i.rank||1===i.rank,(function(){return "Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank "+i.rank+"."})),null!=s&&C(3===s.rank||1===s.rank,(function(){return "Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank "+s.rank+"."})),Uu(u,c,l,s,i,a)}function Wu(t,e,n,r,o,a){var i,s,u=mn(t,"x","batchNorm"),c=mn(e,"mean","batchNorm"),l=mn(n,"variance","batchNorm");return null!=o&&(i=mn(o,"scale","batchNorm")),null!=r&&(s=mn(r,"offset","batchNorm")),C(4===u.rank,(function(){return "Error in batchNorm4D: x must be rank 4 but got rank "+u.rank+"."})),C(4===c.rank||1===c.rank,(function(){return "Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank "+c.rank+"."})),C(4===l.rank||1===l.rank,(function(){return "Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank "+l.rank+"."})),null!=i&&C(4===i.rank||1===i.rank,(function(){return "Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank "+i.rank+"."})),null!=s&&C(4===s.rank||1===s.rank,(function(){return "Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank "+s.rank+"."})),Uu(u,c,l,s,i,a)}function Uu(t,e,n,r,o,a){null==a&&(a=.001);var i,s,u,c=mn(t,"x","batchNorm"),l=mn(e,"mean","batchNorm"),h=mn(n,"variance","batchNorm");null!=o&&(i=mn(o,"scale","batchNorm")),null!=r&&(s=mn(r,"offset","batchNorm")),C(l.rank===h.rank,(function(){return "Batch normalization 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1===o.rank?t.mul(Lr(v.as4D(1,1,1,o.shape[0]),h)).mul(c).reshape(r.shape):t.mul(v).mul(c).reshape(r.shape)},mean:function(){var t=v.mul(On(-1)).mul(p);return 1===o.rank&&(t=t.sum(l)),t.reshape(o.shape)},variance:function(){var t=m.mul(d).mul(p);return 1===o.rank&&(t=t.sum(l)),t.reshape(o.shape)},scale:function(){var e=d.mul(v),n=t.mul(e);return 1===o.rank&&(n=n.sum(l)),n.reshape(o.shape)},offset:function(){var e=t;return 1===o.rank&&(e=e.sum(l)),e.reshape(o.shape)}}}),"BatchNormalization",{varianceEpsilon:a},f).reshape(c.shape)}function Vu(t){return null==t?null:0===t.rank?t.as1D():1===t.rank?t:2===t.rank?t.as4D(1,1,t.shape[0],t.shape[1]):3===t.rank?t.as4D(1,t.shape[0],t.shape[1],t.shape[2]):t}function zu(){Xe("tf.batchNormalization() is going away. Use tf.batchNorm() instead, and note the positional argument change of scale, offset, and varianceEpsilon");}var Gu=An({batchNormalization2d_:function(t,e,n,r,o,a){return void 0===r&&(r=.001),zu(),Pu(t,e,n,a,o,r)}}),Hu=An({batchNormalization3d_:function(t,e,n,r,o,a){return void 0===r&&(r=.001),zu(),Lu(t,e,n,a,o,r)}}),qu=An({batchNormalization4d_:function(t,e,n,r,o,a){return void 0===r&&(r=.001),zu(),Wu(t,e,n,a,o,r)}}),Ku=An({batchNormalization_:function(t,e,n,r,o,a){return void 0===r&&(r=.001),zu(),Uu(t,e,n,a,o,r)}}),ju=An({batchNorm_:Uu}),Xu=An({batchNorm2d_:Pu}),Yu=An({batchNorm3d_:Lu}),$u=An({batchNorm4d_:Wu});var Qu=An({logicalAnd_:function(t,e){var n=mn(t,"a","logicalAnd","bool"),r=mn(e,"b","logicalAnd","bool");return Ro(n.shape,r.shape),Lt.runKernelFunc((function(t){return t.logicalAnd(n,r)}),{a:n,b:r},null,"LogicalAnd")}}),Ju=An({logicalNot_:function(t){var e=mn(t,"x","logicalNot","bool");return Lt.runKernelFunc((function(t){return 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Got stride "+n+" and dilation '"+a+"'"})),C("NWC"===o,(function(){return "Error in conv1d: got dataFormat of "+o+" but only NWC is currently supported."}));var h=u.as4D(1,u.shape[0],u.shape[1],u.shape[2]),f=c.as4D(c.shape[0],1,c.shape[1],c.shape[2]),d=qc(f,h,[1,n],r,"NHWC",[1,a],i);return l?d.as2D(d.shape[2],d.shape[3]):d.as3D(d.shape[0],d.shape[2],d.shape[3])}}),qc=An({conv2d_:function(t,e,n,r,o,a,i){void 0===o&&(o="NHWC"),void 0===a&&(a=[1,1]);var s=mn(t,"x","conv2d"),u=mn(e,"filter","conv2d"),c=s,l=!1;3===s.rank&&(l=!0,c=s.as4D(1,s.shape[0],s.shape[1],s.shape[2])),C(4===c.rank,(function(){return "Error in conv2d: input must be rank 4, but got rank "+c.rank+"."})),C(4===u.rank,(function(){return "Error in conv2d: filter must be rank 4, but got rank "+u.rank+"."})),null!=i&&C(A(r),(function(){return "Error in conv2d: pad must be an integer when using, dimRoundingMode "+i+" but got pad "+r+"."}));var h="NHWC"===o?c.shape[3]:c.shape[1];C(h===u.shape[2],(function(){return "Error in conv2d: depth of input ("+h+") must match input depth for filter "+u.shape[2]+"."})),C(Mo(n,a),(function(){return "Error in conv2D: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+a+"'"}));var f=Bo(o),d=So(c.shape,u.shape,n,a,r,i,!1,f),p=[u,c],v=Lt.runKernelFunc((function(t,e){var n=t.conv2d(c,u,d);return e([u,c]),n}),{x:c,filter:u},(function(t,e){var i=e,s=i[0],u=i[1];return C(Oo(a),(function(){return "Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '"+a+"'"})),{x:function(){return Xc(u.shape,t,s,n,r,o)},filter:function(){return jc(u,t,s.shape,n,r,o)}}}),"Conv2D",d,p);return l?v.as3D(v.shape[1],v.shape[2],v.shape[3]):v}}),Kc=An({conv3d_:function(t,e,n,r,o,a){void 0===o&&(o="NDHWC"),void 0===a&&(a=[1,1,1]);var i=mn(t,"x","conv3d"),s=mn(e,"filter","conv3d"),u=i,c=!1;4===i.rank&&(c=!0,u=i.as5D(1,i.shape[0],i.shape[1],i.shape[2],i.shape[3])),C(5===u.rank,(function(){return "Error in conv3d: input must be rank 5, but got rank "+u.rank+"."})),C(5===s.rank,(function(){return "Error in conv3d: filter must be rank 5, but got rank "+s.rank+"."})),C(u.shape[4]===s.shape[3],(function(){return "Error in conv3d: depth of input ("+u.shape[4]+") must match input depth for filter "+s.shape[3]+"."})),C(function(t,e){return zc(t)||zc(e)}(n,a),(function(){return "Error in conv3D: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+a+"'"})),C("NDHWC"===o,(function(){return "Error in conv3d: got dataFormat of "+o+" but only NDHWC is currently supported."}));var l=Ao(u.shape,s.shape,n,a,r),h=Lt.runKernelFunc((function(t,e){var n=t.conv3d(u,s,l);return e([u,s]),n}),{x:u,$filter:s},(function(t,e){C(zc(a),(function(){return "Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '"+a+"'"}));var o=e[0],i=e[1];return {x:function(){return Gc(o.shape,t,i,n,r)},$filter:function(){return function(t,e,n,r,o){var a=t;4===t.rank&&(a=t.as5D(1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]));var i=e;4===i.rank&&(i=e.as5D(1,e.shape[0],e.shape[1],e.shape[2],e.shape[3]));C(5===a.rank,(function(){return "Error in conv3dDerFilter: input must be rank 5, but got shape "+a.shape+"."})),C(5===i.rank,(function(){return "Error in conv3dDerFilter: dy must be rank 5, but got shape "+i.shape+"."})),C(5===n.length,(function(){return "Error in conv3dDerFilter: filterShape must be length 5, but got "+n+"."})),C(a.shape[4]===n[3],(function(){return "Error in conv3dDerFilter: depth of input "+a.shape[4]+") must match input depth in filter ("+n[3]+"."})),C(i.shape[4]===n[4],(function(){return "Error in conv3dDerFilter: depth of dy ("+i.shape[4]+") must match output depth for filter ("+n[4]+")."}));var s=Ao(a.shape,n,r,1,o);return Lt.runKernelFunc((function(t){return t.conv3dDerFilter(a,i,s)}),{x5D:a,dy5D:i})}(o,t,i.shape,n,r)}}}));return c?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}}),jc=An({conv2dDerFilter_:function(t,e,n,r,o,a,i){void 0===a&&(a="NHWC");var s=t;3===t.rank&&(s=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var u=e;3===u.rank&&(u=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),C(4===s.rank,(function(){return "Error in conv2dDerFilter: input must be rank 4, but got shape "+s.shape+"."})),C(4===u.rank,(function(){return "Error in conv2dDerFilter: dy must be rank 4, but got shape "+u.shape+"."})),C(4===n.length,(function(){return "Error in conv2dDerFilter: filterShape must be length 4, but got "+n+"."}));var c="NHWC"===a?s.shape[3]:s.shape[1],l="NHWC"===a?u.shape[3]:u.shape[1];C(c===n[2],(function(){return "Error in conv2dDerFilter: depth of input "+c+") must match input depth in filter ("+n[2]+"."})),C(l===n[3],(function(){return "Error in conv2dDerFilter: depth of dy ("+l+") must match output depth for filter ("+n[3]+")."})),null!=i&&C(A(o),(function(){return "Error in conv2dDerFilter: pad must be an integer when using, dimRoundingMode "+i+" but got pad "+o+"."}));var h=Bo(a),f=So(s.shape,n,r,1,o,i,!1,h);return Lt.runKernelFunc((function(t){return t.conv2dDerFilter(s,u,f)}),{x4D:s,dy4D:u})}}),Xc=An({conv2dDerInput_:Vc}),Yc=An({depthwiseConv2d_:function(t,e,n,r,o,a,i){void 0===a&&(a=[1,1]);var s=mn(t,"x","depthwiseConv2d"),u=mn(e,"filter","depthwiseConv2d"),c=s,l=!1;3===s.rank&&(l=!0,c=s.as4D(1,s.shape[0],s.shape[1],s.shape[2])),C(4===c.rank,(function(){return "Error in depthwiseConv2d: input must be rank 4, but got rank "+c.rank+"."})),C(4===u.rank,(function(){return "Error in depthwiseConv2d: filter must be rank 4, but got rank "+u.rank+"."})),C(c.shape[3]===u.shape[2],(function(){return "Error in depthwiseConv2d: number of input channels ("+c.shape[3]+") must match the inChannels dimension in filter "+u.shape[2]+"."})),null==a&&(a=[1,1]),C(Mo(n,a),(function(){return "Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+a+"'"})),null!=i&&C(A(r),(function(){return "Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode "+i+" but got pad "+r+"."}));var h=So(c.shape,u.shape,n,a,r,i,!0),f=[c,u],d=Lt.runKernelFunc((function(t,e){var n=t.depthwiseConv2D(c,u,h);return e([c,u]),n}),{x:c,filter:u},(function(t,e){C(Oo(a),(function(){return "Error in gradient of depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '"+a+"'"}));var n=e[0],r=e[1];return {x:function(){return $c(n.shape,t,r,h)},filter:function(){return Qc(n,t,r.shape,h)}}}),"DepthwiseConv2dNative",h,f);return l?d.as3D(d.shape[1],d.shape[2],d.shape[3]):d}}),$c=An({depthwiseConv2dDerInput_:function(t,e,n,r){var o=e,a=!1;3===e.rank&&(a=!0,o=e.as4D(1,e.shape[0],e.shape[1],e.shape[2]));var i=Lt.runKernelFunc((function(t){return t.depthwiseConv2DDerInput(o,n,r)}),{dy4D:o});return a?i.as3D(i.shape[1],i.shape[2],i.shape[3]):i}}),Qc=An({depthwiseConv2dDerFilter_:function(t,e,n,r){var o=t;3===t.rank&&(o=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var a=e;return 3===a.rank&&(a=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),Lt.runKernelFunc((function(t){return t.depthwiseConv2DDerFilter(o,a,r)}),{x4D:o,dy4D:a})}}),Jc=An({separableConv2d_:function(t,e,n,r,o,a,i){void 0===a&&(a=[1,1]),void 0===i&&(i="NHWC");var s=mn(t,"x","separableConv2d"),u=mn(e,"depthwiseFilter","separableConv2d"),c=mn(n,"pointwiseFilter","separableConv2d"),l=s,h=!1;if(3===s.rank&&(h=!0,l=s.as4D(1,s.shape[0],s.shape[1],s.shape[2])),"NCHW"===i)throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");C(4===l.rank,(function(){return "Error in separableConv2d: input must be rank 4, but got rank "+l.rank+"."})),C(4===u.rank,(function(){return "Error in separableConv2d: depthwise filter must be rank 4, but got rank "+u.rank+"."})),C(4===c.rank,(function(){return "Error in separableConv2d: pointwise filter must be rank 4, but got rank "+u.rank+"."})),C(1===c.shape[0],(function(){return "Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got "+c.shape[0]+"."})),C(1===c.shape[1],(function(){return "Error in separableConv2d: the second dimension of pointwise filter must be 1, but got "+c.shape[1]+"."}));var f=u.shape[2],d=u.shape[3];C(c.shape[2]===f*d,(function(){return "Error in separableConv2d: the third dimension of pointwise filter must be "+f*d+", but got "+c.shape[2]+"."}));var p=Yc(l,u,r,o,i,a),v=qc(p,c,1,"valid",i);return h?v.as3D(v.shape[1],v.shape[2],v.shape[3]):v}}),Zc=An({conv2dTranspose_:function(t,e,n,r,o,a){return Vc(n,mn(t,"x","conv2dTranspose"),mn(e,"filter","conv2dTranspose"),r,o,"NHWC",a)}}),tl=An({conv3dTranspose_:function(t,e,n,r,o){return Gc(n,mn(t,"x","conv3dTranspose"),mn(e,"filter","conv3dTranspose"),r,o)}});var el=An({matMul_:function(t,e,n,r){var o;void 0===n&&(n=!1),void 0===r&&(r=!1);var a=mn(t,"a","matMul"),i=mn(e,"b","matMul");o=Nt(a,i),a=o[0],i=o[1];var s=n?a.shape[a.rank-2]:a.shape[a.rank-1],u=r?i.shape[i.rank-1]:i.shape[i.rank-2],c=n?a.shape[a.rank-1]:a.shape[a.rank-2],l=r?i.shape[i.rank-2]:i.shape[i.rank-1],h=a.shape.slice(0,-2),f=i.shape.slice(0,-2),d=k(h),p=k(f);C(a.rank>=2&&i.rank>=2&&a.rank===i.rank,(function(){return "Error in matMul: inputs must have the same rank of at least 2, got ranks "+a.rank+" and "+i.rank+"."})),C(S(h,f),(function(){return "Error in matMul: outer dimensions ("+h+") and ("+f+") of Tensors with shapes "+a.shape+" and "+i.shape+" must match."})),C(s===u,(function(){return "Error in matMul: inner shapes ("+s+") and ("+u+") of Tensors with shapes "+a.shape+" and "+i.shape+" and transposeA="+n+" and transposeB="+r+" must match."}));var v=a.shape.slice(0,-2).concat([c,l]),m=n?a.as3D(d,s,c):a.as3D(d,c,s),g=r?i.as3D(p,l,u):i.as3D(p,u,l),y={transposeA:n,transposeB:r};return Lt.runKernelFunc((function(t,e){var o=t.batchMatMul(m,g,n,r);return e([m,g]),o}),{a:m,b:g},(function(t,e){var o=e,a=o[0],i=o[1];return n||r?!n&&r?{a:function(){return t.matMul(i,!1,!1)},b:function(){return t.matMul(a,!0,!1)}}:n&&!r?{a:function(){return i.matMul(t,!1,!0)},b:function(){return a.matMul(t,!1,!1)}}:{a:function(){return i.matMul(t,!0,!0)},b:function(){return t.matMul(a,!0,!0)}}:{a:function(){return t.matMul(i,!1,!0)},b:function(){return a.matMul(t,!0,!1)}}}),"BatchMatMul",y).reshape(v)}}),nl=An({dot_:function(t,e){var n=mn(t,"t1","dot"),r=mn(e,"t2","dot");C(!(1!==n.rank&&2!==n.rank||1!==r.rank&&2!==r.rank),(function(){return "Error in dot: inputs must all be rank 1 or 2, but got ranks "+n.rank+" and "+r.rank+"."}));var o=1===n.rank?n.size:n.shape[1],a=1===r.rank?r.size:r.shape[0];return C(o===a,(function(){return "Error in dot: inner dimensions of inputs must match, but got "+o+" and "+a+"."})),1===n.rank&&1===r.rank?n.as2D(1,-1).matMul(r.as2D(-1,1)).asScalar():1===n.rank&&2===r.rank?n.as2D(1,-1).matMul(r.as2D(r.shape[0],r.shape[1])).as1D():2===n.rank&&1===r.rank?n.matMul(r.as2D(-1,1)).as1D():n.matMul(r.as2D(r.shape[0],r.shape[1]))}}),rl=An({outerProduct_:function(t,e){var n=mn(t,"v1","outerProduct"),r=mn(e,"v2","outerProduct");return C(1===n.rank&&1===r.rank,(function(){return "Error in outerProduct: inputs must be rank 1, but got ranks "+n.rank+" and "+r.rank+"."})),n.as2D(-1,1).matMul(r.as2D(1,-1))}});var ol=An({reverse_:function(t,e){var n=mn(t,"x","reverse");if(0===n.rank)return n.clone();var r=O(e,n.shape);return Lt.runKernelFunc((function(t){return t.reverse(n,r)}),{$x:n},(function(t){return {$x:function(){return t.reverse(r)}}})).reshapeAs(n)}}),al=An({reverse1d_:function(t){var e=mn(t,"x","reverse");return C(1===e.rank,(function(){return "Error in reverse1D: x must be rank 1 but got rank "+e.rank+"."})),ol(e,0)}}),il=An({reverse2d_:function(t,e){var n=mn(t,"x","reverse");return C(2===n.rank,(function(){return "Error in reverse2D: x must be rank 2 but got rank "+n.rank+"."})),ol(n,e)}}),sl=An({reverse3d_:function(t,e){var n=mn(t,"x","reverse");return C(3===n.rank,(function(){return "Error in reverse3D: x must be rank 3 but got rank "+n.rank+"."})),ol(n,e)}}),ul=An({reverse4d_:function(t,e){var n=mn(t,"x","reverse");return C(4===n.rank,(function(){return "Error in reverse4D: x must be rank 4 but got rank "+n.rank+"."})),ol(n,e)}});function cl(t,e,n,r,o,a){var i=mn(t,"x","maxPool"),s=i,u=!1;3===i.rank&&(u=!0,s=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),null==r&&(r=[1,1]),C(4===s.rank,(function(){return "Error in maxPool: input must be rank 4 but got rank "+s.rank+"."})),C(Mo(n,r),(function(){return "Error in maxPool: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+r+"'"})),null!=a&&C(A(o),(function(){return "Error in maxPool: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+o+"."}));var c=Io(s.shape,e,n,r,o,a);if(1===c.filterWidth&&1===c.filterHeight&&S(c.inShape,c.outShape))return i.clone();var l=[s],h=Lt.runKernelFunc((function(t,e){var n=t.maxPool(s,c);return e([s,n]),n}),{x:s},(function(t,a){var i=a[0],s=a[1];return {x:function(){return function(t,e,n,r,o,a,i,s){var u=mn(t,"dy","maxPoolBackprop"),c=mn(e,"input","maxPoolBackprop"),l=mn(n,"output","maxPoolBackprop");C(c.rank===u.rank,(function(){return "Rank of input ("+c.rank+") does not match rank of dy ("+u.rank+")"})),null==a&&(a=[1,1]);C(Mo(o,a),(function(){return "Error in maxPoolBackProp: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+a+"'"})),C(4===u.rank,(function(){return "Error in maxPoolBackprop: dy must be rank 4 but got rank "+u.rank+"."})),C(4===c.rank,(function(){return "Error in maxPoolBackprop: input must be rank 4 but got rank "+c.rank+"."})),null!=s&&C(A(i),(function(){return "Error in maxPoolBackprop: pad must be an integer when using, dimRoundingMode "+s+" but got pad "+i+"."}));var h=Io(c.shape,r,o,a,i,s);return Lt.runKernelFunc((function(t){return t.maxPoolBackprop(u,c,l,h)}),{$dy:u,$input:c})}(t,i,s,e,n,r,o)}}}),"MaxPool",c,l);return u?h.as3D(h.shape[1],h.shape[2],h.shape[3]):h}function ll(t,e,n,r,o,a){var i=mn(t,"x","avgPool","float32");null==r&&(r=[1,1]),C(Mo(n,r),(function(){return "Error in avgPool: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+r+"'"}));var s=i,u=!1;3===i.rank&&(u=!0,s=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),C(4===s.rank,(function(){return "Error in avgPool: x must be rank 4 but got rank "+s.rank+"."})),null!=a&&C(A(o),(function(){return "Error in avgPool: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+o+"."}));var c=Io(s.shape,e,n,r,o,a);if(1===c.filterWidth&&1===c.filterHeight&&S(c.inShape,c.outShape))return i.clone();var l=Lt.runKernelFunc((function(t){return t.avgPool(s,c)}),{x:s},(function(t){return {x:function(){return function(t,e,n,r,o,a){var i=mn(t,"dy","avgPoolBackprop"),s=mn(e,"input","avgPoolBackprop");C(s.rank===i.rank,(function(){return "Rank of input ("+s.rank+") does not match rank of dy ("+i.rank+")"})),null==o&&(o=[1,1]);C(Mo(r,o),(function(){return "Error in avgPoolBackprop: Either strides or dilations must be 1. Got strides "+r+" and dilations '"+o+"'"}));var u=s,c=i,l=!1;3===s.rank&&(l=!0,u=s.as4D(1,s.shape[0],s.shape[1],s.shape[2]),c=i.as4D(1,i.shape[0],i.shape[1],i.shape[2]));C(4===c.rank,(function(){return "Error in avgPoolBackprop: dy must be rank 4 but got rank "+c.rank+"."})),C(4===u.rank,(function(){return "Error in avgPoolBackprop: input must be rank 4 but got rank "+u.rank+"."}));var h=Io(u.shape,n,r,o,a),f=Lt.runKernelFunc((function(t){return t.avgPoolBackprop(c,u,h)}),{dy4D:c,input4D:u});if(l)return f.as3D(f.shape[1],f.shape[2],f.shape[3]);return f}(t,s,e,n,r,o)}}}),"AvgPool",c);return l=l.cast(i.dtype),u?l.as3D(l.shape[1],l.shape[2],l.shape[3]):l}var hl=An({maxPool_:function(t,e,n,r,o){return cl(t,e,n,1,r,o)}}),fl=An({avgPool_:function(t,e,n,r,o){return ll(t,e,n,1,r,o)}}),dl=An({pool_:function(t,e,n,r,o,a){null==o&&(o=[1,1]),null==a&&(a=1),0===r&&(r="valid");var i=mn(t,"x","maxPool"),s=i,u=!1;3===i.rank&&(u=!0,s=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),C(Mo(a,o),(function(){return "Error in pool: Either strides or dilations must be 1. Got strides "+a+" and dilations '"+o+"'"}));var c,l=Io(s.shape,e,a,o,r),h=[l.dilationHeight,l.dilationWidth];c="same"===r?function(t,e){var n=t.map((function(t,n){return t+(t-1)*(e[n]-1)})).map((function(t){return t-1})),r=n.map((function(t){return Math.floor(t/2)})),o=n.map((function(t,e){return t-r[e]}));return n.map((function(t,e){return [r[e],o[e]]}))}([l.filterHeight,l.filterWidth],h):[[0,0],[0,0]];var f=1===h[0]&&1===h[1],d=function(t,e,n){var r=n.map((function(t){return t[0]})),o=n.map((function(t){return t[1]})),a=t.concat(r,o),i=e.map((function(t,e){return (t-a[e]%t)%t})),s=o.map((function(t,e){return t+i[e]})),u=e.map((function(t,e){return [r[e],s[e]]})),c=e.map((function(t,e){return [0,i[e]]}));return [u,c]}([l.inHeight,l.inWidth],h,c),p=d[0],v=d[1],m=f?r:"valid",g=f?s:Mr(s,h,p),y=("avg"===n?function(){return ll(g,e,a,1,m)}:function(){return cl(g,e,a,1,m)})(),x=f?y:vr(y,h,v);return u?x.as3D(x.shape[1],x.shape[2],x.shape[3]):x}}),pl=An({maxPool3d_:function(t,e,n,r,o,a,i){void 0===a&&(a="NDHWC");var s=mn(t,"x","maxPool3d"),u=s,c=!1;4===s.rank&&(c=!0,u=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3])),null==i&&(i=[1,1,1]),C(5===u.rank,(function(){return "Error in maxPool3d: x must be rank 5 but got rank "+u.rank+"."})),C("NDHWC"===a,(function(){return "Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of "+a})),C(Mo(n,i),(function(){return "Error in maxPool3d: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+i+"'"})),null!=o&&C(A(r),(function(){return "Error in maxPool3d: pad must be an integer when using, dimRoundingMode "+o+" but got pad "+r+"."}));var l=ko(u.shape,e,n,i,r,o,a),h=Lt.runKernelFunc((function(t,e){var n=t.maxPool3d(u,l);return e([u,n]),n}),{x:u},(function(t,a){var s=a[0],u=a[1];return {x:function(){return function(t,e,n,r,o,a,i,s){var u=mn(t,"dy","maxPool3dBackprop"),c=mn(e,"input","maxPool3dBackprop"),l=mn(n,"output","maxPool3dBackprop"),h=u,f=c,d=l,p=!1;4===c.rank&&(p=!0,h=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]),f=c.as5D(1,c.shape[0],c.shape[1],c.shape[2],c.shape[3]),d=l.as5D(1,l.shape[0],l.shape[1],l.shape[2],l.shape[3]));C(5===h.rank,(function(){return "Error in maxPool3dBackprop: dy must be rank 5 but got rank "+h.rank+"."})),C(5===f.rank,(function(){return "Error in maxPool3dBackprop: input must be rank 5 but got rank "+f.rank+"."})),C(5===d.rank,(function(){return "Error in maxPool3dBackprop: output must be rank 5 but got rank "+d.rank+"."})),null==a&&(a=[1,1,1]);C(Mo(o,a),(function(){return "Error in maxPool3dBackprop: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+a+"'"})),null!=s&&C(A(i),(function(){return "Error in maxPool3dBackprop: pad must be an integer when using, dimRoundingMode "+s+" but got pad "+i+"."}));var v=ko(f.shape,r,o,a,i,s),m=Lt.runKernelFunc((function(t){return t.maxPool3dBackprop(h,f,d,v)}),{dy5D:h,input5D:f});if(p)return m.as4D(m.shape[1],m.shape[2],m.shape[3],m.shape[4]);return m}(t,s,u,e,n,i,r,o)}}}));return c?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}}),vl=An({avgPool3d_:function(t,e,n,r,o,a,i){void 0===a&&(a="NDHWC");var s=mn(t,"x","avgPool3d","float32"),u=s,c=!1;4===s.rank&&(c=!0,u=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3])),null==i&&(i=[1,1,1]),C(5===u.rank,(function(){return "Error in avgPool3d: x must be rank 5 but got rank "+u.rank+"."})),C("NDHWC"===a,(function(){return "Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of "+a})),C(Mo(n,i),(function(){return "Error in avgPool3d: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+i+"'"})),null!=o&&C(A(r),(function(){return "Error in avgPool3d: pad must be an integer when using, dimRoundingMode "+o+" but got pad "+r+"."}));var l=ko(u.shape,e,n,i,r,o,a),h=Lt.runKernelFunc((function(t){return t.avgPool3d(u,l)}),{x:u},(function(t){return {x:function(){return function(t,e,n,r,o,a,i){var s=mn(t,"dy","avgPool3dBackprop"),u=mn(e,"input","avgPool3dBackprop"),c=s,l=u,h=!1;4===u.rank&&(h=!0,c=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3]),l=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]));C(5===c.rank,(function(){return "Error in avgPool3dBackprop: dy must be rank 5 but got rank "+c.rank+"."})),C(5===l.rank,(function(){return "Error in avgPool3dBackprop: input must be rank 5 but got rank "+l.rank+"."})),null==o&&(o=[1,1,1]);C(Mo(r,o),(function(){return "Error in avgPool3dBackprop: Either strides or dilations must be 1. 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Array(a.rank-n.length).fill(-1)):n).map((function(t,e){return t>=0?t:(C(-1===t,(function(){return "Negative size values should be exactly -1 but got "+t+" for the slice() size at index "+e+"."})),a.shape[e]-r[e])})),eo(a,r,o);var i=a.shape,s={begin:r,size:o};return Lt.runKernelFunc((function(t){return t.slice(a,r,o)}),{x:a},(function(t){for(var e=[],n=0;n<t.rank;n++)e.push([r[n],i[n]-r[n]-o[n]]);return {x:function(){return t.pad(e)}}}),"Slice",s)}}),gl=An({slice1d_:function(t,e,n){var r=mn(t,"x","slice1d");return C(1===r.rank,(function(){return "slice1d expects a rank-1 tensor, but got a rank-"+r.rank+" tensor"})),ml(r,[e],[n])}}),yl=An({slice2d_:function(t,e,n){var r=mn(t,"x","slice2d");return C(2===r.rank,(function(){return "slice2d expects a rank-2 tensor, but got a rank-"+r.rank+" tensor"})),ml(r,e,n)}}),xl=An({slice3d_:function(t,e,n){var r=mn(t,"x","slice3d");return C(3===r.rank,(function(){return "slice3d expects a rank-3 tensor, but got a rank-"+r.rank+" 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0===e&&(e=null),void 0===n&&(n=!1);var r=mn(t,"x","max"),o=r,a=O(e,r.shape),i=a,s=En(i,r.rank);null!=s&&(r=r.transpose(s),i=In(i.length,r.rank));var u=[r],c=Lt.runKernelFunc((function(t,e){var n=t.max(r,i);return e([o,n]),n}),{x:r},(function(t,e){return wl(t,e[1],e[0],a,s)}),"Max",{axes:i},u,[!0]);if(n){var l=wn(c.shape,a);c=c.reshape(l);}return c}}),Al=An({mean_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=mn(t,"x","mean"),o=O(e,r.shape),a=k(bn(r.shape,o)[1]);return vo((function(t){var r=On(a);return {value:(r.dtype===t.dtype?t:t.cast(r.dtype)).div(r).sum(e,n),gradFunc:function(e){var n=t.shape.slice();return o.forEach((function(t){n[t]=1;})),e.reshape(n).mul(zn(t.shape,"float32")).div(a)}}}))(r)}}),Dl=An({min_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=mn(t,"x","min"),o=r,a=O(e,r.shape),i=a,s=En(i,r.rank);null!=s&&(r=r.transpose(s),i=In(i.length,r.rank));var u=[r],c=Lt.runKernelFunc((function(t,e){var n=t.min(r,i);return e([o,n]),n}),{x:r},(function(t,e){return wl(t,e[1],e[0],a,s)}),"Min",{axes:i},u,[!0]);if(n){var l=wn(c.shape,a);c=c.reshape(l);}return c}}),Tl=An({moments_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=O(e,(t=mn(t,"x","moments")).shape),o=t.mean(r,n),a=o.shape;n||(a=wn(o.shape,r));var i=t.toFloat().sub(o.reshape(a)).square();return {mean:o,variance:i.mean(r,n)}}}),Nl=An({sum_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=mn(t,"x","sum");"bool"===r.dtype&&(r=r.toInt());var o=O(e,r.shape);return vo((function(t){var e=En(o,t.rank),r=o,a=t;null!=e&&(a=t.transpose(e),r=In(r.length,t.rank));var i=function(e){var n=t.shape.slice();return o.forEach((function(t){n[t]=1;})),e.reshape(n).mul(zn(t.shape,"float32"))},s={axes:r},u=Lt.runKernelFunc((function(t){return t.sum(a,r)}),{x:a},(function(t){return {x:function(){return i(t)}}}),"Sum",s);if(n){var c=wn(u.shape,o);u=u.reshape(c);}return {value:u,gradFunc:i}}))(r)}}),Fl=An({prod_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=mn(t,"x","prod");"bool"===r.dtype&&(r=r.toInt());var o=O(e,r.shape),a=En(o,r.rank),i=o,s=r;null!=a&&(s=r.transpose(a),i=In(i.length,r.rank));var u=Lt.runKernelFunc((function(t){return t.prod(s,i)}),{permutedX:s});if(n){var c=wn(u.shape,o);u=u.reshape(c);}return u}});var _l=An({elu_:function(t){var e=mn(t,"x","elu");return Lt.runKernelFunc((function(t,n){var r=t.elu(e);return n([r]),r}),{$x:e},(function(t,e){var n=e[0];return {$x:function(){return Lt.runKernelFunc((function(e){return e.eluDer(t,n)}),{dy:t,y:n})}}}))}}),Ol=An({leakyRelu_:function(t,e){void 0===e&&(e=.2);var n=mn(t,"x","leakyRelu");return hc(On(e).mul(n),n)}}),Ml=An({prelu_:function(t,e){var n=mn(t,"x","prelu"),r=mn(e,"alpha","prelu");return Lt.runKernelFunc((function(t,e){var o=t.prelu(n,r);return e([n,r]),o}),{x:n,alpha:r},(function(t,e){var n=e[0],r=e[1],o=n.greater(0);return {x:function(){return ec(o,t,t.mul(r))},alpha:function(){var e=ec(o,Xn(t),t.mul(n)),a=Eo(r.shape,t.shape);return a.length>0&&(e=e.sum(a)),e.reshape(r.shape)}}}),"Prelu")}}),Bl=An({relu_:function(t){var e=mn(t,"x","relu");return "bool"===e.dtype?e.toInt():Lt.runKernelFunc((function(t,n){var r=t.relu(e);return n([e]),r}),{x:e},(function(t,e){var n=e[0];return {x:function(){return t.mulStrict(n.step().toFloat())}}}),"Relu")}}),Pl=An({relu6_:function(t){var e=mn(t,"x","relu6");return "bool"===e.dtype?e.toInt():Lt.runKernelFunc((function(t,n){var r=t.relu6(e);return n([e]),r}),{x:e},(function(t,e){var n=e[0],r=n.lessEqual(6).mul(n.step());return {x:function(){return t.mulStrict(r.toFloat())}}}),"Relu6")}}),Ll=An({selu_:function(t){var e=mn(t,"x","selu");return Lt.runKernelFunc((function(t,n){var r=t.selu(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return {$x:function(){var e=n.greater(On(0)),r=On(bs),o=On(ws),a=t.mul(o),i=t.mul(r).mul(n.toFloat().exp());return ec(e,a,i)}}}))}});var Wl=An({transpose_:function(t,e){var n=mn(t,"x","transpose");if(null==e&&(e=n.shape.map((function(t,e){return e})).reverse()),C(n.rank===e.length,(function(){return "Error in transpose: rank of input "+n.rank+" must match length of perm "+e+"."})),e.forEach((function(t){C(t>=0&&t<n.rank,(function(){return "All entries in 'perm' must be between 0 and "+(n.rank-1)+" but got "+e}));})),n.rank<=1)return n.clone();var r={perm:e};return Lt.runKernelFunc((function(t){return t.transpose(n,e)}),{x:n},(function(t){var n=Rn(e);return {x:function(){return t.transpose(n)}}}),"Transpose",r)}});var Ul=An({localResponseNormalization_:function(t,e,n,r,o){void 0===e&&(e=5),void 0===n&&(n=1),void 0===r&&(r=1),void 0===o&&(o=.5);var a=mn(t,"x","localResponseNormalization");C(4===a.rank||3===a.rank,(function(){return "Error in localResponseNormalization: x must be rank 3 or 4 but got\n               rank "+a.rank+"."})),C(A(e),(function(){return "Error in localResponseNormalization: depthRadius must be an integer but got depthRadius "+e+"."}));var i=a,s=!1;3===a.rank&&(s=!0,i=a.as4D(1,a.shape[0],a.shape[1],a.shape[2]));var u=Lt.runKernelFunc((function(t,a){var s=t.localResponseNormalization4D(i,e,n,r,o);return a([i,s]),s}),{x4D:i},(function(t,a){var i=a[0],s=a[1];return {x4D:function(){return Lt.runKernelFunc((function(a){return a.LRNGrad(t,i,s,e,n,r,o)}),{})}}}));return s?u.as3D(u.shape[1],u.shape[2],u.shape[3]):u}});var Vl=An({norm_:function(t,e,n,r){void 0===e&&(e="euclidean"),void 0===n&&(n=null),void 0===r&&(r=!1);var o=function t(e,n,r){void 0===r&&(r=null);if(0===e.rank)return e.abs();if(1!==e.rank&&null===r)return t(e.reshape([-1]),n,r);if(1===e.rank||"number"==typeof r||Array.isArray(r)&&1===r.length){if(1===n)return e.abs().sum(r);if(n===1/0)return e.abs().max(r);if(n===-1/0)return e.abs().min(r);if("euclidean"===n||2===n)return e.abs().pow(On(2,"int32")).sum(r).sqrt();throw new Error("Error in norm: invalid ord value: "+n)}if(Array.isArray(r)&&2===r.length){if(1===n)return 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o=mn(e,"data","multiRNNCell"),a=gn(n,"c","multiRNNCell"),i=gn(r,"h","multiRNNCell"),s=o,u=[],c=0;c<t.length;c++){var l=t[c](s,a[c],i[c]);u.push(l[0]),u.push(l[1]),s=l[1];}var h=[],f=[];for(c=0;c<u.length;c+=2)h.push(u[c]),f.push(u[c+1]);return [h,f]}});var Hl=An({movingAverage_:function(t,e,n,r,o){void 0===o&&(o=!0);var a=mn(t,"v","movingAverage"),i=mn(e,"x","movingAverage"),s=mn(n,"decay","movingAverage");Ft(a,i),C(S(a.shape,i.shape),(function(){return "Shape mismatch in v and x"}));var u=On(1),c=u.sub(s),l=i.sub(a).mul(c);if(o){C(null!=r,(function(){return "When using zeroDebias: true, step is required."}));var h=mn(r,"step","movingAverage");l=l.div(u.sub(xc(s,h)));}return a.add(l)}});var ql=An({stridedSlice_:function(t,e,n,r,o,a,i,s,u){if(void 0===o&&(o=0),void 0===a&&(a=0),void 0===i&&(i=0),void 0===s&&(s=0),void 0===u&&(u=0),null==r&&(r=new Array(e.length)),0!==i)throw new Error("ellipsis mask is not yet supported");var 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Expected "+i+", but was "+e.shape[0]})),C(0<=a&&a<=1,(function(){return "softNmsSigma must be in [0, 1], but was '"+a+"'"})),{maxOutputSize:n,iouThreshold:r,scoreThreshold:o,softNmsSigma:a}}var Sh=An({resizeBilinear_:function(t,e,n){void 0===n&&(n=!1);var r=mn(t,"images","resizeBilinear");C(3===r.rank||4===r.rank,(function(){return "Error in resizeBilinear: x must be rank 3 or 4, but got rank "+r.rank+"."})),C(2===e.length,(function(){return "Error in resizeBilinear: new shape must 2D, but got shape "+e+"."}));var o=r,a=!1;3===r.rank&&(a=!0,o=r.as4D(1,r.shape[0],r.shape[1],r.shape[2]));var i=e[0],s=e[1],u=Lt.runKernelFunc((function(t,e){return e([o]),t.resizeBilinear(o,i,s,n)}),{x:o},(function(t,e){return {x:function(){return Lt.runKernelFunc((function(r){return r.resizeBilinearBackprop(t,e[0],n)}),{})}}}),"ResizeBilinear",{alignCorners:n,newHeight:i,newWidth:s});return a?u.as3D(u.shape[1],u.shape[2],u.shape[3]):u}}),Ah=An({resizeNearestNeighbor_:function(t,e,n){void 0===n&&(n=!1);var r=mn(t,"images","resizeNearestNeighbor");C(3===r.rank||4===r.rank,(function(){return "Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank "+r.rank+"."})),C(2===e.length,(function(){return "Error in resizeNearestNeighbor: new shape must 2D, but got shape "+e+"."})),C("float32"===r.dtype||"int32"===r.dtype,(function(){return "`images` must have `int32` or `float32` as dtype"}));var o=r,a=!1;3===r.rank&&(a=!0,o=r.as4D(1,r.shape[0],r.shape[1],r.shape[2]));var i=e[0],s=e[1],u=Lt.runKernelFunc((function(t,e){return e([o]),t.resizeNearestNeighbor(o,i,s,n)}),{batchImages:o},(function(t,e){return {batchImages:function(){return Lt.runKernelFunc((function(r){return r.resizeNearestNeighborBackprop(t,e[0],n)}),{})}}}));return a?u.as3D(u.shape[1],u.shape[2],u.shape[3]):u}}),Dh=An({nonMaxSuppression_:function(t,e,n,r,o){void 0===r&&(r=.5),void 0===o&&(o=Number.NEGATIVE_INFINITY);var a=mn(t,"boxes","nonMaxSuppression"),i=mn(e,"scores","nonMaxSuppression"),s=kh(a,i,n,r,o);n=s.maxOutputSize,r=s.iouThreshold,o=s.scoreThreshold;var u={maxOutputSize:n,iouThreshold:r,scoreThreshold:o};return Lt.runKernelFunc((function(t){return t.nonMaxSuppression(a,i,n,r,o)}),{boxes:a,scores:i},null,"NonMaxSuppressionV3",u)}}),Th=function(t,e,o,a,i){return void 0===a&&(a=.5),void 0===i&&(i=Number.NEGATIVE_INFINITY),n(this,void 0,void 0,(function(){var n,s,u,c,l,h,f;return r(this,(function(r){switch(r.label){case 0:return n=mn(t,"boxes","nonMaxSuppressionAsync"),s=mn(e,"scores","nonMaxSuppressionAsync"),u=kh(n,s,o,a,i),o=u.maxOutputSize,a=u.iouThreshold,i=u.scoreThreshold,[4,Promise.all([n.data(),s.data()])];case 1:return c=r.sent(),l=c[0],h=c[1],f=jo(l,h,o,a,i),n!==t&&n.dispose(),s!==e&&s.dispose(),[2,f]}}))}))},Nh=An({nonMaxSuppressionWithScore_:function(t,e,n,r,o,a){void 0===r&&(r=.5),void 0===o&&(o=Number.NEGATIVE_INFINITY),void 0===a&&(a=0);var i=mn(t,"boxes","nonMaxSuppression"),s=mn(e,"scores","nonMaxSuppression"),u=kh(i,s,n,r,o,a),c={maxOutputSize:n=u.maxOutputSize,iouThreshold:r=u.iouThreshold,scoreThreshold:o=u.scoreThreshold,softNmsSigma:a=u.softNmsSigma},l=Lt.runKernel("NonMaxSuppressionV5",{boxes:i,scores:s},c);return {selectedIndices:l[0],selectedScores:l[1]}}}),Fh=function(t,e,o,a,i,s){return void 0===a&&(a=.5),void 0===i&&(i=Number.NEGATIVE_INFINITY),void 0===s&&(s=0),n(this,void 0,void 0,(function(){var n,u,c,l,h,f,d;return r(this,(function(r){switch(r.label){case 0:return n=mn(t,"boxes","nonMaxSuppressionAsync"),u=mn(e,"scores","nonMaxSuppressionAsync"),c=kh(n,u,o,a,i,s),o=c.maxOutputSize,a=c.iouThreshold,i=c.scoreThreshold,s=c.softNmsSigma,[4,Promise.all([n.data(),u.data()])];case 1:return l=r.sent(),h=l[0],f=l[1],d=Xo(h,f,o,a,i,s),n!==t&&n.dispose(),u!==e&&u.dispose(),[2,d]}}))}))},_h=An({cropAndResize_:function(t,e,n,r,o,a){var i=mn(t,"image","cropAndResize"),s=mn(e,"boxes","cropAndResize","float32"),u=mn(n,"boxInd","cropAndResize","int32");o=o||"bilinear",a=a||0;var c=s.shape[0];return C(4===i.rank,(function(){return "Error in cropAndResize: image must be rank 4,but got rank "+i.rank+"."})),C(2===s.rank&&4===s.shape[1],(function(){return "Error in cropAndResize: boxes must be have size ["+c+",4] but had shape "+s.shape+"."})),C(1===u.rank&&u.shape[0]===c,(function(){return "Error in cropAndResize: boxInd must be have size ["+c+"] but had shape "+s.shape+"."})),C(2===r.length,(function(){return "Error in cropAndResize: cropSize must be of length 2, but got length "+r.length+"."})),C(r[0]>=1&&r[1]>=1,(function(){return "cropSize must be atleast [1,1], but was "+r})),C("bilinear"===o||"nearest"===o,(function(){return "method must be bilinear or nearest, but was "+o})),Lt.runKernelFunc((function(t,e){return t.cropAndResize(i,s,u,r,o,a)}),{images:i,boxes:s,boxInd:u},null,"CropAndResize",{method:o,extrapolationValue:a,cropSize:r})}}),Oh=Object.freeze({resizeBilinear:Sh,resizeNearestNeighbor:Ah,nonMaxSuppression:Dh,nonMaxSuppressionAsync:Th,nonMaxSuppressionWithScore:Nh,nonMaxSuppressionWithScoreAsync:Fh,cropAndResize:_h}),Mh=function(t,e){return !(t>0)||"linear"===e},Bh=function(t,e,n){if(null==n||"linear"===n)return t;if("relu"===n)return t.mul(e.step());throw new Error("Gradient for activation "+n+" has not been implemented yet.")},Ph=function(t,e){var n=e,r=Eo(t.shape,e.shape);return r.length>0&&(n=n.sum(r)),n.reshape(t.shape)},Lh=function(t,e,n){if("linear"===e)return t;if("relu"===e)return Bl(t);if("elu"===e)return _l(t);if("relu6"===e)return Pl(t);if("prelu"===e)return Ml(t,n);throw new Error("Unknown fused activation "+e+".")};var Wh=An({fusedMatMul_:function(t){var e,n=t.a,r=t.b,o=t.transposeA,a=void 0!==o&&o,i=t.transposeB,s=void 0!==i&&i,u=t.bias,c=t.activation,l=void 0===c?"linear":c,h=t.preluActivationWeights;if(!1===Mh(Lt.state.gradientDepth,l)){var f=el(n,r,a,s);return null!=u&&(f=rc(f,u)),Lh(f,l,h)}var d=mn(n,"a","fused matMul"),p=mn(r,"b","fused matMul");e=Nt(d,p),d=e[0],p=e[1];var v=a?d.shape[d.rank-2]:d.shape[d.rank-1],m=s?p.shape[p.rank-1]:p.shape[p.rank-2],g=a?d.shape[d.rank-1]:d.shape[d.rank-2],y=s?p.shape[p.rank-2]:p.shape[p.rank-1],x=d.shape.slice(0,-2),b=p.shape.slice(0,-2),w=k(x),E=k(b);C(d.rank>=2&&p.rank>=2&&d.rank===p.rank,(function(){return "Error in fused matMul: inputs must have the same rank of at least 2, got ranks "+d.rank+" and "+p.rank+"."})),C(S(x,b),(function(){return "Error in fused matMul: outer dimensions ("+x+") and ("+b+") of Tensors with shapes "+d.shape+" and "+p.shape+" must match."})),C(v===m,(function(){return "Error in fused matMul: inner shapes ("+v+") and ("+m+") of Tensors with shapes "+d.shape+" and "+p.shape+" and transposeA="+a+" and transposeB="+s+" must match."}));var R,I,A=d.shape.slice(0,-2).concat([g,y]),D=a?d.as3D(w,v,g):d.as3D(w,g,v),T=s?p.as3D(E,y,m):p.as3D(E,m,y);null!=u&&Ro(A,(R=Nt(R=mn(u,"bias","fused matMul"),d)[0]).shape),null!=h&&(I=mn(h,"prelu weights","fused matMul"));var N={a:D,b:T};null!=u&&(N.bias=R),null!=h&&(N.preluActivationWeights=I);var F=[D,T];return Lt.runKernelFunc((function(t,e){var n=t.fusedBatchMatMul({a:D,b:T,transposeA:a,transposeB:s,bias:R,activation:l,preluActivationWeights:I});return e([D,T,n]),n}),N,(function(t,e){var n=e[0],r=e[1],o=e[2],i=Bh(t,o,l),c={};return null!=u&&(c={bias:function(){return Ph(R,i)}}),a||s?!a&&s?Object.assign({a:function(){return i.matMul(r,!1,!1)},b:function(){return i.matMul(n,!0,!1)}},c):a&&!s?Object.assign({a:function(){return r.matMul(i,!1,!0)},b:function(){return n.matMul(i,!1,!1)}},c):Object.assign({a:function(){return r.matMul(i,!0,!0)},b:function(){return i.matMul(n,!0,!0)}},c):Object.assign({a:function(){return i.matMul(r,!1,!0)},b:function(){return n.matMul(i,!0,!1)}},c)}),"_FusedMatMul",{transposeA:a,transposeB:s,activation:l},F,[!0]).reshape(A)}}),Uh=An({fusedConv2d_:function(t){var e=t.x,n=t.filter,r=t.strides,o=t.pad,a=t.dataFormat,i=void 0===a?"NHWC":a,s=t.dilations,u=void 0===s?[1,1]:s,c=t.dimRoundingMode,l=t.bias,h=t.activation,f=void 0===h?"linear":h,d=t.preluActivationWeights;if(f=f||"linear",!1===Mh(Lt.state.gradientDepth,f)){var p=qc(e,n,r,o,i,u,c);return null!=l&&(p=rc(p,l)),Lh(p,f,d)}var v=mn(e,"x","conv2d"),m=mn(n,"filter","conv2d"),g=v,y=!1;3===v.rank&&(y=!0,g=v.as4D(1,v.shape[0],v.shape[1],v.shape[2])),C(4===g.rank,(function(){return "Error in fused conv2d: input must be rank 4, but got rank "+g.rank+"."})),C(4===m.rank,(function(){return "Error in fused conv2d: filter must be rank 4, but got rank "+m.rank+"."})),null!=c&&C(A(o),(function(){return "Error in fused conv2d: pad must be an integer when using, dimRoundingMode "+c+" but got pad "+o+"."})),C(g.shape[3]===m.shape[2],(function(){return "Error in conv2d: depth of input ("+g.shape[3]+") must match input depth for filter "+m.shape[2]+"."})),C(Mo(r,u),(function(){return "Error in conv2D: Either strides or dilations must be 1. Got strides "+r+" and dilations '"+u+"'"})),C("NHWC"===i,(function(){return "Error in conv2d: got dataFormat of "+i+" but only NHWC is currently supported."}));var x,b,w=So(g.shape,m.shape,r,u,o,c);null!=l&&(x=Nt(x=mn(l,"bias","fused conv2d"),v)[0],Ro(w.outShape,x.shape)),null!=d&&(b=mn(d,"prelu weights","fused conv2d"));var E={x:g,filter:m};null!=l&&(E.bias=x),null!=d&&(E.preluActivationWeights=b);var R=[m,g],I=Lt.runKernelFunc((function(t,e){var n=t.fusedConv2d({input:g,filter:m,convInfo:w,bias:x,activation:f,preluActivationWeights:b});return e([m,g,n]),n}),E,(function(t,e){var n=e,a=n[0],i=n[1],s=n[2],c=Bh(t,s,f);C(Oo(u),(function(){return "Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '"+u+"'"}));var h={};return null!=l&&(h={bias:function(){return Ph(x,c)}}),Object.assign({x:function(){return Xc(i.shape,c,a,r,o)},filter:function(){return jc(i,c,a.shape,r,o)}},h)}),"FusedConv2D",{convInfo:w,activation:f},R,[!0]);return y?I.as3D(I.shape[1],I.shape[2],I.shape[3]):I}}),Vh=An({fusedDepthwiseConv2d_:function(t){var e=t.x,n=t.filter,r=t.strides,o=t.pad,a=t.dataFormat,i=void 0===a?"NHWC":a,s=t.dilations,u=void 0===s?[1,1]:s,c=t.dimRoundingMode,l=t.bias,h=t.activation,f=void 0===h?"linear":h,d=t.preluActivationWeights;if(!1===Mh(Lt.state.gradientDepth,f)){var p=Yc(e,n,r,o,i,u,c);return null!=l&&(p=rc(p,l)),Lh(p,f,d)}var v=mn(e,"x","depthwiseConv2d"),m=mn(n,"filter","depthwiseConv2d"),g=v,y=!1;3===v.rank&&(y=!0,g=v.as4D(1,v.shape[0],v.shape[1],v.shape[2])),C(4===g.rank,(function(){return "Error in fused depthwiseConv2d: input must be rank 4, but got rank "+g.rank+"."})),C(4===m.rank,(function(){return "Error in fused depthwiseConv2d: filter must be rank 4, but got rank "+m.rank+"."})),C(g.shape[3]===m.shape[2],(function(){return "Error in fused depthwiseConv2d: number of input channels ("+g.shape[3]+") must match the inChannels dimension in filter "+m.shape[2]+"."})),null==u&&(u=[1,1]),C(Mo(r,u),(function(){return "Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides "+r+" and dilations '"+u+"'"})),null!=c&&C(A(o),(function(){return "Error in fused depthwiseConv2d: pad must be an integer when using dimRoundingMode "+c+" but got pad "+o+"."}));var x,b,w=So(g.shape,m.shape,r,u,o,c,!0);null!=l&&(x=Nt(x=mn(l,"bias","fused conv2d"),v)[0],Ro(w.outShape,x.shape)),null!=d&&(b=mn(d,"prelu weights","fused depthwiseConv2d"));var E={x:g,filter:m};null!=l&&(E.bias=x),null!=d&&(E.preluActivationWeights=b);var R=[m,g],I=Lt.runKernelFunc((function(t,e){var n=t.fusedDepthwiseConv2D({input:g,filter:m,convInfo:w,bias:x,activation:f,preluActivationWeights:b});return e([m,g,n]),n}),E,(function(t,e){C(Oo(u),(function(){return "Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. 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Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. 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Nn(t)}));return Dn(this.concat(r,e),this.concat(o,e))}var a=t.map((function(t){var n=k(t.shape.slice(e));return t.as2D(-1,n)})),i=Sn(a.map((function(t){return t.shape})),1),s=dr(i,t[0].dtype).values;if(1===a[0].shape[0]){var u=0;a.forEach((function(t){s.set(n.readSync(t.dataId),u),u+=t.size;}));}else {var c=0;a.forEach((function(t){for(var e=n.readSync(t.dataId),r=0,o=0;o<t.shape[0];++o)for(var a=o*i[1]+c,u=0;u<t.shape[1];++u)s[a+u]=e[r++];c+=t.shape[1];}));}var l=Sn(t.map((function(t){return t.shape})),e);return Fn(s,l,t[0].dtype)},o.prototype.neg=function(t){return Hh(t,"neg"),this.multiply(On(-1),t)},o.prototype.add=function(t,e){return "complex64"===t.dtype||"complex64"===e.dtype?this.broadcastedBinaryComplexOp(t.cast("complex64"),e.cast("complex64"),(function(t,e,n,r){return {real:t+n,imag:e+r}})):this.broadcastedBinaryOp(t,e,Dt(t.dtype,e.dtype),(function(t,e){return t+e}))},o.prototype.addN=function(t){var e=this;Hh(t,"addN");for(var n=t.map((function(t){return e.readSync(t.dataId)})),r=dr(t[0].shape,t[0].dtype),o=r.values,a=0;a<t.length;a++)for(var i=n[a],s=0;s<o.length;s++)o[s]+=i[s];return r.toTensor()},o.prototype.softmax=function(t,e){var n=O([e],t.shape),r=this.max(t,n),o=wn(r.shape,n),a=this.subtract(t,r.reshape(o)),i=this.exp(a),s=this.sum(i,n).reshape(o);return this.realDivide(i,s)},o.prototype.subtract=function(t,e){return "complex64"===t.dtype||"complex64"===e.dtype?this.broadcastedBinaryComplexOp(t.cast("complex64"),e.cast("complex64"),(function(t,e,n,r){return {real:t-n,imag:e-r}})):this.broadcastedBinaryOp(t,e,Dt(t.dtype,e.dtype),(function(t,e){return t-e}))},o.prototype.pow=function(t,e){return Hh([t,e],"pow"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return Math.pow(t,e)}))},o.prototype.batchMatMul=function(t,e,n,r){Hh([t,e],"matMul");for(var o=n?t.shape[1]:t.shape[2],a=n?t.shape[2]:t.shape[1],i=r?e.shape[1]:e.shape[2],s=t.shape[0],u=this.readSync(t.dataId),c=this.readSync(e.dataId),l=n?[t.strides[0],1,t.strides[1]]:[t.strides[0],t.strides[1],1],h=l[0],f=l[1],d=l[2],p=r?[1,e.strides[1],e.strides[0]]:[e.strides[1],1,e.strides[0]],v=p[0],m=p[1],g=p[2],y=a*i,x=dr([s,a,i],t.dtype),b=x.values,w=this.blockSize,C=0;C<s;C++)for(var E=0;E<a;E+=w)for(var R=0;R<i;R+=w)for(var I=0;I<o;I+=w)for(var k=Math.min(E+w,a),S=Math.min(R+w,i),A=Math.min(I+w,o),D=E;D<k;D++)for(var T=R;T<S;T++){for(var N=0,F=I;F<A;F++)N+=u[C*h+D*f+F*d]*c[F*v+T*m+C*g];b[C*y+(D*i+T)]+=N;}return x.toTensor()},o.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,a=t.bias,i=t.activation,s=t.preluActivationWeights,u=this.batchMatMul(e,n,r,o);return a&&(u=this.add(u,a)),i&&(u=qh(this,u,i,s)),u},o.prototype.multiply=function(t,e){return "complex64"===t.dtype||"complex64"===e.dtype?this.broadcastedBinaryComplexOp(t.cast("complex64"),e.cast("complex64"),(function(t,e,n,r){return {real:t*n-e*r,imag:t*r+e*n}})):this.broadcastedBinaryOp(t,e,Dt(t.dtype,e.dtype),(function(t,e){return t*e}))},o.prototype.realDivide=function(t,e){Hh([t,e],"realDivide");return this.broadcastedBinaryOp(t,e,"float32",(function(t,e){return t/e}))},o.prototype.floorDiv=function(t,e){Hh([t,e],"floorDiv");return this.broadcastedBinaryOp(t,e,"int32",(function(t,e){return Math.floor(t/e)}))},o.prototype.sum=function(t,e){Hh(t,"sum"),Cn("sum",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,Dt(t.dtype,"int32")),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=0,f=0;f<i;++f)h+=u[l+f];s[c]=h;}return a},o.prototype.prod=function(t,e){Hh(t,"sum");for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,Dt(t.dtype,"int32")),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=1,f=0;f<i;++f)h*=u[l+f];s[c]=h;}return a},o.prototype.unsortedSegmentSum=function(t,e,n){Hh(t,"unsortedSegmentSum");for(var r=[],o=t.rank-e.rank,a=0;a<o;++a)e=e.expandDims(a+1);for(a=0;a<n;++a){var i=On(a,"int32"),s=Rc(i,e).asType("float32").mul(t).sum(0);r.push(s);}return Pr(r)},o.prototype.argMin=function(t,e){Hh(t,"argMin");var n=[e];Cn("argMin",n,t.rank);for(var r=bn(t.shape,n),o=r[0],a=r[1],i=Gn(o,"int32"),s=k(a),u=this.readSync(i.dataId),c=this.readSync(t.dataId),l=0;l<u.length;++l){for(var h=l*s,f=c[h],d=0,p=0;p<s;++p){var v=c[h+p];v<f&&(f=v,d=p);}u[l]=d;}return i},o.prototype.argMax=function(t,e){Hh(t,"argMax");var n=[e];Cn("argMax",n,t.rank);for(var r=bn(t.shape,n),o=r[0],a=r[1],i=Gn(o,"int32"),s=k(a),u=this.readSync(i.dataId),c=this.readSync(t.dataId),l=0;l<u.length;++l){for(var h=l*s,f=c[h],d=0,p=0;p<s;++p){var v=c[h+p];v>f&&(f=v,d=p);}u[l]=d;}return i},o.prototype.cumsum=function(t,e,n,r){if(Hh(t,"cumsum"),e!==t.rank-1)throw new Error("backend.cumsum in CPU expects an inner-most axis="+(t.rank-1)+" but got axis="+e);for(var o=Dt(t.dtype,"int32"),a=Gn(t.shape,o),i=this.readSync(a.dataId),s=this.readSync(t.dataId),u=t.shape[t.rank-1],c=r?function(t,e){return t+u-e-1}:function(t,e){return t+e},l=0;l<s.length;l+=u)for(var h=0;h<u;h++){var f=c(l,h);if(0===h)i[f]=n?0:s[f];else {var d=c(l,h-1);i[f]=n?s[d]+i[d]:s[f]+i[d];}}return a},o.prototype.equal=function(t,e){return Hh([t,e],"equal"),this.broadcastedBinaryOp(t,e,"bool",(function(t,e){return t===e?1:0}))},o.prototype.notEqual=function(t,e){return Hh([t,e],"notEqual"),this.broadcastedBinaryOp(t,e,"bool",(function(t,e){return t!==e?1:0}))},o.prototype.less=function(t,e){return Hh([t,e],"less"),this.broadcastedBinaryOp(t,e,"bool",(function(t,e){return t<e?1:0}))},o.prototype.lessEqual=function(t,e){return Hh([t,e],"lessEqual"),this.broadcastedBinaryOp(t,e,"bool",(function(t,e){return t<=e?1:0}))},o.prototype.greater=function(t,e){return Hh([t,e],"greater"),this.broadcastedBinaryOp(t,e,"bool",(function(t,e){return t>e?1:0}))},o.prototype.greaterEqual=function(t,e){return Hh([t,e],"greaterEqual"),this.broadcastedBinaryOp(t,e,"bool",(function(t,e){return t>=e?1:0}))},o.prototype.logicalNot=function(t){Hh(t,"logicalNot");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)n[r]=e[r]?0:1;return this.makeOutput(n,t.shape,"bool")},o.prototype.logicalAnd=function(t,e){return Hh([t,e],"logicalAnd"),this.broadcastedBinaryOp(t,e,"bool",(function(t,e){return t&&e}))},o.prototype.logicalOr=function(t,e){return Hh([t,e],"logicalOr"),this.broadcastedBinaryOp(t,e,"bool",(function(t,e){return t||e}))},o.prototype.select=function(t,e,n){Hh([t,e,n],"select");for(var r=this.readSync(t.dataId),o=this.readSync(e.dataId),a=this.readSync(n.dataId),i=Gn(e.shape,Dt(e.dtype,n.dtype)),s=this.readSync(i.dataId),u=0,c=0===t.rank||t.rank>1||1===e.rank?1:k(e.shape.slice(1)),l=0;l<r.length;l++)for(var h=0;h<c;h++)1===r[l]?s[u++]=o[l]:s[u++]=a[l];return i},o.prototype.where=function(t){Hh([t],"where");var e=this.readSync(t.dataId);return na(t.shape,e)},o.prototype.topk=function(t,e,n){return Hh(t,"topk"),ea(this.readSync(t.dataId),t.shape,t.dtype,e)},o.prototype.min=function(t,e){Hh(t,"min"),Cn("min",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,t.dtype),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=u[l],f=0;f<i;++f){var d=u[l+f];d<h&&(h=d);}s[c]=h;}return a},o.prototype.minimum=function(t,e){return Hh([t,e],"minimum"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return Math.min(t,e)}))},o.prototype.mod=function(t,e){return Hh([t,e],"mod"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){var n=t%e;return t<0&&e<0||t>=0&&e>=0?n:(n+e)%e}))},o.prototype.max=function(t,e){Hh(t,"max"),Cn("max",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,t.dtype),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=u[l],f=0;f<i;++f){var d=u[l+f];d>h&&(h=d);}s[c]=h;}return a},o.prototype.maximum=function(t,e){return Hh([t,e],"maximum"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return Math.max(t,e)}))},o.prototype.all=function(t,e){Hh(t,"all"),Cn("all",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,t.dtype),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=u[l],f=0;f<i;++f){var d=u[l+f];h=h&&d;}s[c]=h;}return a},o.prototype.any=function(t,e){Hh(t,"any"),Cn("any",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,t.dtype),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=u[l],f=0;f<i;++f){var d=u[l+f];h=h||d;}s[c]=h;}return a},o.prototype.squaredDifference=function(t,e){return Hh([t,e],"squaredDifference"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){var n=t-e;return n*n}))},o.prototype.ceil=function(t){Hh(t,"ceil");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.ceil(e[r]);return this.makeOutput(n,t.shape,"float32")},o.prototype.floor=function(t){Hh(t,"floor");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.floor(e[r]);return this.makeOutput(n,t.shape,"float32")},o.prototype.sign=function(t){Hh(t,"x");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)e[r]<0?n[r]=-1:e[r]>0?n[r]=1:n[r]=0;return this.makeOutput(n,t.shape,"float32")},o.prototype.isNaN=function(t){Hh(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isNaN(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},o.prototype.isInf=function(t){Hh(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Math.abs(e[r])===1/0&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},o.prototype.isFinite=function(t){Hh(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isFinite(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},o.prototype.round=function(t){Hh(t,"round");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=Math.floor(e[r]);e[r]-o<.5?n[r]=Math.floor(e[r]):e[r]-o>.5?n[r]=Math.ceil(e[r]):n[r]=o%2==0?o:o+1;}return this.makeOutput(n,t.shape,"float32")},o.prototype.exp=function(t){Hh(t,"exp");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.exp(e[r]);return this.makeOutput(n,t.shape,"float32")},o.prototype.expm1=function(t){Hh(t,"expm1");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.expm1(e[r]);return this.makeOutput(n,t.shape,"float32")},o.prototype.log=function(t){Hh(t,"log");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log(o);}return this.makeOutput(n,t.shape,"float32")},o.prototype.log1p=function(t){Hh(t,"log1p");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log1p(o);}return this.makeOutput(n,t.shape,"float32")},o.prototype.sqrt=function(t){Hh(t,"sqrt");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.sqrt(o);}return this.makeOutput(n,t.shape,"float32")},o.prototype.rsqrt=function(t){Hh(t,"rsqrt");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=1/Math.sqrt(o);}return this.makeOutput(n,t.shape,"float32")},o.prototype.reciprocal=function(t){Hh(t,"reciprocal");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=1/e[r];return this.makeOutput(n,t.shape,"float32")},o.prototype.linear=function(t){return t},o.prototype.relu=function(t){Hh(t,"relu");for(var e=Gn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.max(0,r[o]);return e},o.prototype.relu6=function(t){Hh(t,"relu");for(var e=Gn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.min(Math.max(0,r[o]),6);return e},o.prototype.prelu=function(t,e){return Hh([t,e],"prelu"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return t<0?e*t:t}))},o.prototype.elu=function(t){Hh(t,"elu");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=n[r];e[r]=o>=0?o:Math.exp(o)-1;}return this.makeOutput(e,t.shape,"float32")},o.prototype.eluDer=function(t,e){Hh([t,e],"eluDer");for(var n=new Float32Array(e.size),r=this.readSync(e.dataId),o=this.readSync(t.dataId),a=0;a<r.length;++a){var i=r[a];n[a]=i>=1?o[a]:o[a]*(i+1);}return this.makeOutput(n,e.shape,"float32")},o.prototype.selu=function(t){Hh(t,"selu");for(var e=bs,n=ws,r=new Float32Array(t.size),o=this.readSync(t.dataId),a=0;a<o.length;++a){var i=o[a];r[a]=i>=0?n*i:e*(Math.exp(i)-1);}return this.makeOutput(r,t.shape,"float32")},o.prototype.clip=function(t,e,n){Hh(t,"clip");for(var r=new Float32Array(t.size),o=this.readSync(t.dataId),a=0;a<o.length;++a){var i=o[a];r[a]=i>n?n:i<e?e:i;}return this.makeOutput(r,t.shape,"float32")},o.prototype.abs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.abs(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.complexAbs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<t.size;++r){var o=n[2*r],a=n[2*r+1];e[r]=Math.hypot(o,a);}return this.makeOutput(e,t.shape,"float32")},o.prototype.int=function(t){Hh(t,"int");for(var e=new Int32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=n[r];return this.makeOutput(e,t.shape,"int32")},o.prototype.sigmoid=function(t){Hh(t,"sigmoid");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=1/(1+Math.exp(-n[r]));return this.makeOutput(e,t.shape,"float32")},o.prototype.softplus=function(t){Hh(t,"softplus");for(var e=Math.log(1.1920928955078125e-7)+2,n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var a=r[o]>-e,i=r[o]<e,s=Math.exp(r[o]),u=void 0;u=i?s:a?r[o]:Math.log(1+s),n[o]=u;}return this.makeOutput(n,t.shape,"float32")},o.prototype.sin=function(t){Hh(t,"sin");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sin(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.cos=function(t){Hh(t,"cos");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cos(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.tan=function(t){Hh(t,"tan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.tan(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.asin=function(t){Hh(t,"asin");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asin(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.acos=function(t){Hh(t,"acos");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acos(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.atan=function(t){Hh(t,"atan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atan(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.atan2=function(t,e){return Hh([t,e],"atan2"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return Math.atan2(t,e)}))},o.prototype.sinh=function(t){Hh(t,"sinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sinh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.cosh=function(t){Hh(t,"cosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cosh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.tanh=function(t){Hh(t,"tanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=D(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.asinh=function(t){Hh(t,"asinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asinh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.acosh=function(t){Hh(t,"acosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acosh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.atanh=function(t){Hh(t,"atanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atanh(n[r]);return this.makeOutput(e,t.shape,"float32")},o.prototype.erf=function(t){Hh(t,"erf");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=Math.sign(n[r]),a=Math.abs(n[r]),i=1/(1+.3275911*a);e[r]=o*(1-((((1.061405429*i-1.453152027)*i+1.421413741)*i-.284496736)*i+.254829592)*i*Math.exp(-a*a));}return this.makeOutput(e,t.shape,"float32")},o.prototype.step=function(t,e){void 0===e&&(e=0),Hh(t,"step");for(var n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var a=r[o];isNaN(a)?n[o]=NaN:n[o]=a>0?1:e;}return this.makeOutput(n,t.shape,"float32")},o.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,i=t.preluActivationWeights,s=this.conv2d(e,n,r);return o&&(s=this.add(s,o)),a&&(s=qh(this,s,a,i)),s},o.prototype.conv2d=function(t,e,n){Hh([t,e],"conv2d");for(var r=n.filterHeight,o=n.filterWidth,a=n.dilationHeight,i=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,c="channelsLast"===n.dataFormat,l=dr(n.outShape,t.dtype),h=t.strides[0],f=c?t.strides[1]:t.strides[2],d=c?t.strides[2]:1,p=c?1:t.strides[1],v=l.strides[0],m=c?l.strides[1]:l.strides[2],g=c?l.strides[2]:1,y=c?1:l.strides[1],x=this.readSync(t.dataId),b=this.readSync(e.dataId),w=l.values,C=0;C<n.batchSize;++C)for(var E=C*h,R=C*v,I=0;I<n.outHeight;++I)for(var k=R+I*m,S=I*n.strideHeight-u,A=0;A<r;A++){var D=S+A*a;if(!(D<0||D>=n.inHeight))for(var T=A*e.strides[0],N=E+D*f,F=0;F<n.outWidth;++F)for(var _=k+F*g,O=F*n.strideWidth-s,M=0;M<o;M++){var B=O+M*i;if(!(B<0||B>=n.inWidth))for(var P=N+B*d,L=T+M*e.strides[1],W=0;W<n.inChannels;++W){for(var U=x[P+W*p],V=0;V<n.outChannels;++V)w[_+V*y]+=U*b[L+V];L+=n.outChannels;}}}return l.toTensor()},o.prototype.conv3d=function(t,e,n){for(var r=n.filterDepth,o=n.filterHeight,a=n.filterWidth,i=n.dilationDepth,s=n.dilationHeight,u=n.dilationWidth,c=n.padInfo.front,l=n.padInfo.left,h=n.padInfo.top,f=dr(n.outShape,t.dtype),d=this.readSync(t.dataId),p=this.readSync(e.dataId),v=f.values,m=0;m<n.batchSize;++m)for(var g=m*t.strides[0],y=m*f.strides[0],x=0;x<n.outDepth;++x)for(var b=y+x*f.strides[1],w=x*n.strideDepth-c,C=0;C<r;C++){var E=w+C*i;if(!(E<0||E>=n.inDepth))for(var R=C*e.strides[0],I=g+E*t.strides[1],k=0;k<n.outHeight;++k)for(var S=b+k*f.strides[2],A=k*n.strideHeight-h,D=0;D<o;D++){var T=A+D*s;if(!(T<0||T>=n.inHeight))for(var N=R+D*e.strides[1],F=I+T*t.strides[2],_=0;_<n.outWidth;++_)for(var O=S+_*n.outChannels,M=_*n.strideWidth-l,B=0;B<a;B++){var P=M+B*u;if(!(P<0||P>=n.inWidth))for(var L=N+B*e.strides[2],W=F+P*n.inChannels,U=L,V=0;V<n.inChannels;++V){for(var z=d[W+V],G=0;G<n.outChannels;++G)v[O+G]+=z*p[U+G];U+=n.outChannels;}}}}return f.toTensor()},o.prototype.conv2dDerInput=function(t,e,n){Hh([t,e],"conv2dDerInput");for(var r=dr(n.inShape,"float32"),o=r.values,a=this.readSync(t.dataId),i=this.readSync(e.dataId),s=e.strides,u=s[0],c=s[1],l=s[2],h=n.batchSize,f=n.filterHeight,d=n.filterWidth,p=n.inChannels,v=n.inHeight,m=n.inWidth,g=n.outChannels,y=n.outHeight,x=n.outWidth,b=n.strideHeight,w=n.strideWidth,C=n.dataFormat,E=f-1-n.padInfo.top,R=d-1-n.padInfo.left,I="channelsLast"===C,k=r.strides[0],S=I?r.strides[1]:r.strides[2],A=I?r.strides[2]:1,D=I?1:r.strides[1],T=t.strides[0],N=I?t.strides[1]:t.strides[2],F=I?t.strides[2]:1,_=I?1:t.strides[1],O=0;O<h;++O)for(var M=0;M<p;++M)for(var B=0;B<v;++B)for(var P=B-E,L=Math.max(0,Math.ceil(P/b)),W=Math.min(y,(f+P)/b),U=0;U<m;++U){for(var V=U-R,z=Math.max(0,Math.ceil(V/w)),G=Math.min(x,(d+V)/w),H=0,q=L;q<W;++q)for(var K=q*b-P,j=z;j<G;++j)for(var X=T*O+N*q+F*j,Y=u*(f-1-K)+c*(d-1-(j*w-V))+l*M,$=0;$<g;++$){H+=a[X+_*$]*i[Y+$];}o[k*O+S*B+A*U+D*M]=H;}return r.toTensor()},o.prototype.conv3dDerInput=function(t,e,n){for(var r=dr(n.inShape,"float32"),o=r.values,a=r.strides,i=a[0],s=a[1],u=a[2],c=a[3],l=this.readSync(t.dataId),h=t.strides,f=h[0],d=h[1],p=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=n.batchSize,E=n.filterDepth,R=n.filterHeight,I=n.filterWidth,k=n.inChannels,S=n.inDepth,A=n.inHeight,D=n.inWidth,T=n.outChannels,N=n.outDepth,F=n.outHeight,_=n.outWidth,O=n.strideDepth,M=n.strideHeight,B=n.strideWidth,P=E-1-n.padInfo.front,L=R-1-n.padInfo.top,W=I-1-n.padInfo.left,U=0;U<C;++U)for(var V=0;V<k;++V)for(var z=0;z<S;++z)for(var G=z-P,H=Math.max(0,Math.ceil(G/O)),q=Math.min(N,(E+G)/O),K=0;K<A;++K)for(var j=K-L,X=Math.max(0,Math.ceil(j/M)),Y=Math.min(F,(R+j)/M),$=0;$<D;++$){for(var Q=$-W,J=Math.max(0,Math.ceil(Q/B)),Z=Math.min(_,(I+Q)/B),tt=0,et=H;et<q;++et)for(var nt=et*O-G,rt=X;rt<Y;++rt)for(var ot=rt*M-j,at=J;at<Z;++at)for(var it=f*U+d*et+p*rt+v*at,st=y*(E-1-nt)+x*(R-1-ot)+b*(I-1-(at*B-Q))+w*V,ut=0;ut<T;++ut){tt+=l[it+ut]*m[st+ut];}o[i*U+s*z+u*K+c*$+V]=tt;}return r.toTensor()},o.prototype.conv2dDerFilter=function(t,e,n){Hh([t,e],"conv2dDerFilter");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,s="channelsLast"===n.dataFormat,u=dr(n.filterShape,"float32"),c=n.padInfo.left,l=n.padInfo.top,h=this.bufferSync(t),f=this.bufferSync(e),d=0;d<a;++d)for(var p=Math.max(0,Math.ceil((l-d)/r)),v=Math.min(n.outHeight,(n.inHeight+l-d)/r),m=0;m<i;++m)for(var g=Math.max(0,Math.ceil((c-m)/o)),y=Math.min(n.outWidth,(n.inWidth+c-m)/o),x=0;x<n.inChannels;++x)for(var b=0;b<n.outChannels;++b){for(var w=0,C=0;C<n.batchSize;++C)for(var E=p;E<v;++E)for(var R=d+E*r-l,I=g;I<y;++I){var k=m+I*o-c;w+=s?h.get(C,R,k,x)*f.get(C,E,I,b):h.get(C,x,R,k)*f.get(C,b,E,I);}u.set(w,d,m,x,b);}return u.toTensor()},o.prototype.conv3dDerFilter=function(t,e,n){for(var r=n.strideDepth,o=n.strideHeight,a=n.strideWidth,i=n.filterDepth,s=n.filterHeight,u=n.filterWidth,c=dr(n.filterShape,"float32"),l=c.values,h=c.strides,f=h[0],d=h[1],p=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=this.readSync(t.dataId),E=t.strides,R=E[0],I=E[1],k=E[2],S=E[3],A=n.padInfo.front,D=n.padInfo.left,T=n.padInfo.top,N=0;N<i;++N)for(var F=Math.max(0,Math.ceil((A-N)/r)),_=Math.min(n.outDepth,(n.inDepth+A-N)/r),O=N*f,M=0;M<s;++M)for(var B=Math.max(0,Math.ceil((T-M)/o)),P=Math.min(n.outHeight,(n.inHeight+T-M)/o),L=M*d+O,W=0;W<u;++W)for(var U=Math.max(0,Math.ceil((D-W)/a)),V=Math.min(n.outWidth,(n.inWidth+D-W)/a),z=W*p+L,G=0;G<n.inChannels;++G)for(var H=G*v+z,q=0;q<n.outChannels;++q){for(var K=0,j=0;j<n.batchSize;++j)for(var X=j*R,Y=j*y,$=F;$<_;++$)for(var Q=(N+$*r-A)*I+X,J=$*x+Y,Z=B;Z<P;++Z)for(var tt=(M+Z*o-T)*k+Q,et=Z*b+J,nt=U;nt<V;++nt){var rt=nt*w+et;K+=C[(W+nt*a-D)*S+tt+G]*m[rt+q];}l[H+q]=K;}return c.toTensor()},o.prototype.fusedDepthwiseConv2D=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,i=t.preluActivationWeights,s=this.depthwiseConv2D(e,n,r);return o&&(s=this.add(s,o)),a&&(s=qh(this,s,a,i)),s},o.prototype.depthwiseConv2D=function(t,e,n){Hh([t,e],"depthwiseConv2D");for(var r=n.filterHeight,o=n.filterWidth,a=n.dilationHeight,i=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,c=n.outChannels/n.inChannels,l=dr(n.outShape,t.dtype),h=this.readSync(t.dataId),f=this.readSync(e.dataId),d=l.values,p=0;p<n.batchSize;++p)for(var v=p*t.strides[0],m=p*l.strides[0],g=0;g<n.outHeight;++g)for(var y=m+g*l.strides[1],x=g*n.strideHeight-s,b=0;b<r;++b){var w=x+b*a;if(!(w<0||w>=n.inHeight))for(var C=b*e.strides[0],E=v+w*t.strides[1],R=0;R<n.outWidth;++R)for(var I=y+R*l.strides[2],k=R*n.strideWidth-u,S=0;S<o;++S){var A=k+S*i;if(!(A<0||A>=n.inWidth))for(var D=C+S*e.strides[1],T=E+A*n.inChannels,N=I,F=D,_=0;_<n.inChannels;++_){for(var O=h[T+_],M=0;M<c;++M)d[N+M]+=O*f[F+M];N+=c,F+=c;}}}return l.toTensor()},o.prototype.depthwiseConv2DDerInput=function(t,e,n){Hh([t,e],"depthwiseConv2DDerInput");for(var r=dr(n.inShape,"float32"),o=r.values,a=r.strides,i=a[0],s=a[1],u=a[2],c=this.readSync(t.dataId),l=t.strides,h=l[0],f=l[1],d=l[2],p=this.readSync(e.dataId),v=e.strides,m=v[0],g=v[1],y=v[2],x=n.batchSize,b=n.filterHeight,w=n.filterWidth,C=n.inChannels,E=n.inHeight,R=n.inWidth,I=n.outChannels,k=n.outHeight,S=n.outWidth,A=n.strideHeight,D=n.strideWidth,T=b-1-n.padInfo.top,N=w-1-n.padInfo.left,F=I/C,_=0;_<x;++_)for(var O=0;O<C;++O)for(var M=0;M<E;++M)for(var B=M-T,P=Math.max(0,Math.ceil(B/A)),L=Math.min(k,(b+B)/A),W=0;W<R;++W){for(var U=W-N,V=Math.max(0,Math.ceil(U/D)),z=Math.min(S,(w+U)/D),G=0,H=P;H<L;++H)for(var q=H*A-B,K=V;K<z;++K)for(var j=h*_+f*H+d*K,X=m*(b-1-q)+g*(w-1-(K*D-U))+y*O,Y=0;Y<F;++Y){G+=c[j+(O*F+Y)]*p[X+Y];}o[i*_+s*M+u*W+O]=G;}return r.toTensor()},o.prototype.depthwiseConv2DDerFilter=function(t,e,n){Hh([t,e],"depthwiseConv2DDerFilter");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,s=dr(n.filterShape,"float32"),u=n.padInfo.left,c=n.padInfo.top,l=n.outChannels/n.inChannels,h=this.bufferSync(t),f=this.bufferSync(e),d=0;d<a;++d)for(var p=Math.max(0,Math.ceil((c-d)/r)),v=Math.min(n.outHeight,(n.inHeight+c-d)/r),m=0;m<i;++m)for(var g=Math.max(0,Math.ceil((u-m)/o)),y=Math.min(n.outWidth,(n.inWidth+u-m)/o),x=0;x<n.outChannels;++x){for(var b=Math.trunc(x/l),w=x%l,C=0,E=0;E<n.batchSize;++E)for(var R=p;R<v;++R)for(var I=d+R*r-c,k=g;k<y;++k){var S=m+k*o-u;C+=h.get(E,I,S,b)*f.get(E,R,k,x);}s.set(C,d,m,b,w);}return s.toTensor()},o.prototype.tile=function(t,e){return Hh(t,"tile"),ta(this.bufferSync(t),e)},o.prototype.pad=function(t,e,n){Hh(t,"pad");var r=e.map((function(e,n){return e[0]+t.shape[n]+e[1]})),o=e.map((function(t){return t[0]})),a=this.bufferSync(t),i=dr(r,t.dtype);0!==n&&i.values.fill(n);for(var s=0;s<t.size;s++){var u=a.indexToLoc(s),c=u.map((function(t,e){return t+o[e]}));i.set.apply(i,[a.get.apply(a,u)].concat(c));}return i.toTensor()},o.prototype.transpose=function(t,e){Hh(t,"transpose");for(var n=new Array(t.rank),r=0;r<n.length;r++)n[r]=t.shape[e[r]];var o=this.readSync(t.dataId),a=dr(n,t.dtype),i=this.bufferSync(t);for(r=0;r<t.size;++r){for(var s=i.indexToLoc(r),u=new Array(s.length),c=0;c<u.length;c++)u[c]=s[e[c]];var l=a.locToIndex(u);a.values[l]=o[r];}return a.toTensor()},o.prototype.gather=function(t,e,n){Hh([t,e],"gather");var r=t.shape.slice(),o=this.readSync(e.dataId);r[n]=o.length;for(var a=dr(r,t.dtype),i=this.bufferSync(t),s=0;s<a.size;++s){var u=a.indexToLoc(s),c=u.slice();c[n]=o[u[n]];var l=i.locToIndex(c);a.values[s]=i.values[l];}return a.toTensor()},o.prototype.batchToSpaceND=function(t,e,n){Hh([t],"batchToSpaceND");var r=e.reduce((function(t,e){return t*e})),o=zr(t.shape,e,r),a=Gr(o.length,e.length),i=Hr(t.shape,e,r),s=qr(n,e.length),u=Kr(i,n,e.length);return t.reshape(o).transpose(a).reshape(i).slice(s,u)},o.prototype.spaceToBatchND=function(t,e,n){Hh([t],"spaceToBatchND");var r=e.reduce((function(t,e){return t*e})),o=[[0,0]];o.push.apply(o,n);for(var a=1+e.length;a<t.shape.length;++a)o.push([0,0]);var i=t.pad(o),s=zr(i.shape,e,r,!1),u=Gr(s.length,e.length,!1),c=Hr(i.shape,e,r,!1);return i.reshape(s).transpose(u).reshape(c)},o.prototype.pool=function(t,e,n){Hh(t,"pool");for(var r=e.strideHeight,o=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=this.readSync(t.dataId),d=dr(e.outShape,t.dtype),p=d.values,v=e.outShape[1]*e.outShape[2]*e.outShape[3],m=e.outShape[2]*e.outShape[3],g=e.outShape[3],y=0;y<e.batchSize;++y)for(var x=y*v,b=y*t.strides[0],w=0;w<e.inChannels;++w)for(var C=0;C<e.outHeight;++C)for(var E=C*r-c,R=Math.max(0,E),I=Math.min(e.inHeight,s+E),k=x+C*m,S=0;S<e.outWidth;++S){for(var A=S*o-l,D=Math.max(0,A),T=Math.min(e.inWidth,u+A),N=h,F=0,_=0,O=R;O<I;O+=a){for(var M=b+O*t.strides[1],B=D;B<T;B+=i){var P=f[M+B*t.strides[2]+w];"max"===n&&P>N?N=P:"avg"===n&&(F+=P,_++);}if(isNaN(N))break}p[k+S*g+w]="avg"===n?F/_:N;}return d.toTensor()},o.prototype.maxPool=function(t,e){return this.pool(t,e,"max")},o.prototype.maxPoolPositions=function(t,e){for(var n=dr(e.outShape,"int32"),r=e.strideHeight,o=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h=this.bufferSync(t),f=0;f<e.batchSize;++f)for(var d=0;d<e.inChannels;++d)for(var p=0;p<e.outHeight;++p){for(var v=p*r-c,m=v;m<0;)m+=a;for(var g=Math.min(e.inHeight,s+v),y=0;y<e.outWidth;++y){for(var x=y*o-l,b=x;b<0;)b+=i;for(var w=Math.min(e.inWidth,u+x),C=Number.NEGATIVE_INFINITY,E=-1,R=m;R<g;R+=a)for(var I=R-v,k=b;k<w;k+=i){var S=k-x,A=h.get(f,R,k,d);A>C&&(C=A,E=I*u+S);}n.set(E,f,p,y,d);}}return n.toTensor()},o.prototype.maxPoolBackprop=function(t,e,n,r){Hh([e,n],"maxPoolBackprop");for(var o=this.maxPoolPositions(e,r),a=r.strideHeight,i=r.strideWidth,s=r.dilationHeight,u=r.dilationWidth,c=r.effectiveFilterHeight,l=r.effectiveFilterWidth,h=l-1-r.padInfo.left,f=c-1-r.padInfo.top,d=dr(e.shape,"float32"),p=this.bufferSync(o),v=this.bufferSync(t),m=0;m<r.batchSize;++m)for(var g=0;g<r.inChannels;++g)for(var y=0;y<r.inHeight;++y)for(var x=0;x<r.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=s){var R=(b+E)/a;if(!(R<0||R>=r.outHeight||Math.floor(R)!==R))for(var I=0;I<l;I+=u){var k=(w+I)/i;if(!(k<0||k>=r.outWidth||Math.floor(k)!==k)){var S=c*l-1-p.get(m,R,k,g)===E*l+I?1:0;if(0!==S)C+=v.get(m,R,k,g)*S;}}}d.set(C,m,y,x,g);}return d.toTensor()},o.prototype.avgPoolBackprop=function(t,e,n){Hh([t,e],"avgPoolBackprop");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,s=n.dilationHeight,u=n.dilationWidth,c=n.effectiveFilterHeight,l=n.effectiveFilterWidth,h=l-1-n.padInfo.left,f=c-1-n.padInfo.top,d=dr(e.shape,"float32"),p=1/(a*i),v=this.bufferSync(t),m=0;m<n.batchSize;++m)for(var g=0;g<n.inChannels;++g)for(var y=0;y<n.inHeight;++y)for(var x=0;x<n.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=s){var R=(b+E)/r;if(!(R<0||R>=n.outHeight||Math.floor(R)!==R))for(var I=0;I<l;I+=u){var k=(w+I)/o;if(!(k<0||k>=n.outWidth||Math.floor(k)!==k))C+=v.get(m,R,k,g);}}d.set(C*p,m,y,x,g);}return d.toTensor()},o.prototype.pool3d=function(t,e,n){Hh(t,"pool3d");for(var r=e.strideDepth,o=e.strideHeight,a=e.strideWidth,i=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,d=e.padInfo.top,p=e.padInfo.left,v="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=this.readSync(t.dataId),g=dr(e.outShape,t.dtype),y=g.values,x=e.outShape[1]*e.outShape[2]*e.outShape[3]*e.outShape[4],b=e.outShape[2]*e.outShape[3]*e.outShape[4],w=e.outShape[3]*e.outShape[4],C=e.outShape[4],E=0;E<e.batchSize;++E)for(var R=E*x,I=E*t.strides[0],k=0;k<e.inChannels;++k)for(var S=0;S<e.outDepth;++S){for(var A=S*r-f,D=A;D<0;)D+=i;for(var T=Math.min(e.inDepth,c+A),N=R+S*b,F=0;F<e.outHeight;++F){for(var _=F*o-d,O=_;O<0;)O+=s;for(var M=Math.min(e.inHeight,l+_),B=N+F*w,P=0;P<e.outWidth;++P){for(var L=P*a-p,W=L;W<0;)W+=u;for(var U=Math.min(e.inWidth,h+L),V=B+P*C,z=v,G=0,H=0,q=D;q<T;q+=i){for(var K=I+q*t.strides[1],j=O;j<M;j+=s){for(var X=K+j*t.strides[2],Y=W;Y<U;Y+=u){var $=m[X+Y*t.strides[3]+k];if("max"===n&&$>z?z=$:"avg"===n&&(G+=$,H++),isNaN(z))break}if(isNaN(z))break}if(isNaN(z))break}y[V+k]="avg"===n?G/H:z;}}}return g.toTensor()},o.prototype.avgPool3d=function(t,e){return Hh(t,"avgPool3d"),this.pool3d(t,e,"avg").toFloat()},o.prototype.avgPool3dBackprop=function(t,e,n){Hh([t,e],"avgPool3dBackprop");for(var r=n.strideDepth,o=n.strideHeight,a=n.strideWidth,i=n.filterDepth,s=n.filterHeight,u=n.filterWidth,c=n.dilationDepth,l=n.dilationHeight,h=n.dilationWidth,f=n.effectiveFilterDepth,d=n.effectiveFilterHeight,p=n.effectiveFilterWidth,v=f-1-n.padInfo.front,m=p-1-n.padInfo.left,g=d-1-n.padInfo.top,y=dr(e.shape,"float32"),x=1/(i*s*u),b=this.bufferSync(t),w=0;w<n.batchSize;++w)for(var C=0;C<n.inChannels;++C)for(var E=0;E<n.inDepth;++E)for(var R=0;R<n.inHeight;++R)for(var I=0;I<n.inWidth;++I){for(var k=E-v,S=R-g,A=I-m,D=0,T=0;T<f;T+=c){var N=(k+T)/r;if(!(N<0||N>=n.outDepth||Math.floor(N)!==N))for(var F=0;F<d;F+=l){var _=(S+F)/o;if(!(_<0||_>=n.outHeight||Math.floor(_)!==_))for(var O=0;O<p;O+=h){var M=(A+O)/a;if(!(M<0||M>=n.outWidth||Math.floor(M)!==M))D+=b.get(w,N,_,M,C);}}}y.set(D*x,w,E,R,I,C);}return y.toTensor()},o.prototype.maxPool3d=function(t,e){return Hh(t,"maxPool3d"),this.pool3d(t,e,"max").toFloat()},o.prototype.maxPool3dPositions=function(t,e){for(var n=dr(e.outShape,"int32"),r=e.strideDepth,o=e.strideHeight,a=e.strideWidth,i=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,d=e.padInfo.top,p=e.padInfo.left,v=this.bufferSync(t),m=0;m<e.batchSize;++m)for(var g=0;g<e.inChannels;++g)for(var y=0;y<e.outDepth;++y){for(var x=y*r-f,b=x;b<0;)b+=i;for(var w=Math.min(e.inDepth,c+x),C=0;C<e.outHeight;++C){for(var E=C*o-d,R=E;R<0;)R+=s;for(var I=Math.min(e.inHeight,l+E),k=0;k<e.outWidth;++k){for(var S=k*a-p,A=S;A<0;)A+=u;for(var D=Math.min(e.inWidth,h+S),T=Number.NEGATIVE_INFINITY,N=-1,F=b;F<w;F+=i)for(var _=F-x,O=R;O<I;O+=s)for(var M=O-E,B=A;B<D;B+=u){var P=B-S,L=v.get(m,F,O,B,g);L>=T&&(T=L,N=_*l*h+M*l+P);}n.set(N,m,y,C,k,g);}}}return n.toTensor()},o.prototype.maxPool3dBackprop=function(t,e,n,r){Hh([e,n],"maxPool3dBackprop");for(var o=this.maxPool3dPositions(e,r),a=r.strideDepth,i=r.strideHeight,s=r.strideWidth,u=r.dilationDepth,c=r.dilationHeight,l=r.dilationWidth,h=r.effectiveFilterDepth,f=r.effectiveFilterHeight,d=r.effectiveFilterWidth,p=h-1-r.padInfo.front,v=d-1-r.padInfo.left,m=f-1-r.padInfo.top,g=dr(e.shape,"float32"),y=this.bufferSync(o),x=this.bufferSync(t),b=0;b<r.batchSize;++b)for(var w=0;w<r.inChannels;++w)for(var C=0;C<r.inDepth;++C)for(var E=0;E<r.inHeight;++E)for(var R=0;R<r.inWidth;++R){for(var I=C-p,k=E-m,S=R-v,A=0,D=0;D<h;D+=u){var T=(I+D)/a;if(!(T<0||T>=r.outDepth||Math.floor(T)!==T))for(var N=0;N<f;N+=c){var F=(k+N)/i;if(!(F<0||F>=r.outHeight||Math.floor(F)!==F))for(var _=0;_<d;_+=l){var O=(S+_)/s;if(!(O<0||O>=r.outWidth||Math.floor(O)!==O)){var M=h*f*d-1-y.get(b,T,F,O,w)===D*f*d+N*d+_?1:0;if(0!==M)A+=x.get(b,T,F,O,w)*M;}}}}g.set(A,b,C,E,R,w);}return g.toTensor()},o.prototype.cast=function(t,e){return Po(t,e,this)},o.prototype.reshape=function(t,e){return Lo(t,e)},o.prototype.avgPool=function(t,e){return Hh(t,"avgPool"),this.pool(t,e,"avg").toFloat()},o.prototype.resizeBilinear=function(t,e,n,r){Hh(t,"resizeBilinear");for(var o=t.shape,a=o[0],i=o[1],s=o[2],u=o[3],c=this.readSync(t.dataId),l=new Float32Array(k([a,e,n,u])),h=[r&&e>1?i-1:i,r&&n>1?s-1:s],f=[r&&e>1?e-1:e,r&&n>1?n-1:n],d=0,p=h[0]/f[0],v=h[1]/f[1],m=0;m<a;m++)for(var g=0;g<e;g++)for(var y=p*g,x=Math.floor(y),b=y-x,w=Math.min(i-1,Math.ceil(y)),C=m*t.strides[0]+x*t.strides[1],E=m*t.strides[0]+w*t.strides[1],R=0;R<n;R++)for(var I=v*R,S=Math.floor(I),A=I-S,D=Math.min(s-1,Math.ceil(I)),T=C+S*t.strides[2],N=E+S*t.strides[2],F=C+D*t.strides[2],_=E+D*t.strides[2],O=0;O<u;O++){var M=c[T+O],B=c[N+O],P=M+(c[F+O]-M)*A,L=P+(B+(c[_+O]-B)*A-P)*b;l[d++]=L;}return Fn(l,[a,e,n,u])},o.prototype.resizeBilinearBackprop=function(t,e,n){Hh([t,e],"resizeBilinearBackprop");for(var r=e.shape,o=r[0],a=r[1],i=r[2],s=r[3],u=t.shape,c=u[1],l=u[2],h=new Float32Array(o*a*i*s),f=[n&&c>1?a-1:a,n&&l>1?i-1:i],d=[n&&c>1?c-1:c,n&&l>1?l-1:l],p=f[0]/d[0],v=f[1]/d[1],m=this.readSync(t.dataId),g=0,y=0;y<o;y++)for(var x=y*e.strides[0],b=0;b<c;b++)for(var w=b*p,C=Math.floor(w),E=Math.min(Math.ceil(w),a-1),R=x+C*e.strides[1],I=x+E*e.strides[1],k=w-C,S=1-k,A=0;A<l;A++)for(var D=A*v,T=Math.floor(D),N=Math.min(Math.ceil(D),i-1),F=D-T,_=1-F,O=R+T*e.strides[2],M=R+N*e.strides[2],B=I+T*e.strides[2],P=I+N*e.strides[2],L=S*_,W=S*F,U=k*_,V=k*F,z=0;z<s;z++){var G=m[g++];h[O+z]+=G*L,h[M+z]+=G*W,h[B+z]+=G*U,h[P+z]+=G*V;}return Ln(h,[o,i,a,s],e.dtype)},o.prototype.resizeNearestNeighbor=function(t,e,n,r){Hh(t,"resizeNearestNeighbor");for(var o=t.shape,a=o[0],i=o[1],s=o[2],u=o[3],c=this.readSync(t.dataId),l=new Float32Array(a*e*n*u),h=[r&&e>1?i-1:i,r&&n>1?s-1:s],f=[r&&e>1?e-1:e,r&&n>1?n-1:n],d=h[0]/f[0],p=h[1]/f[1],v=0,m=0;m<a;m++)for(var g=m*t.strides[0],y=0;y<e;y++)for(var x=d*y,b=g+Math.min(i-1,r?Math.round(x):Math.floor(x))*t.strides[1],w=0;w<n;w++)for(var C=p*w,E=b+Math.min(s-1,r?Math.round(C):Math.floor(C))*t.strides[2],R=0;R<u;R++){var I=c[E+R];l[v++]=I;}return Fn(l,[a,e,n,u],t.dtype)},o.prototype.resizeNearestNeighborBackprop=function(t,e,n){Hh([t,e],"resizeNearestNeighborBackprop");for(var r=e.shape,o=r[0],a=r[1],i=r[2],s=r[3],u=t.shape,c=u[1],l=u[2],h=new Float32Array(o*a*i*s),f=this.readSync(t.dataId),d=[n&&c>1?a-1:a,n&&l>1?i-1:i],p=[n&&c>1?c-1:c,n&&l>1?l-1:l],v=d[0]/p[0],m=d[1]/p[1],g=1/v,y=1/m,x=2*Math.ceil(g)+2,b=2*Math.ceil(y)+2,w=0;w<o;w++)for(var C=w*e.strides[0],E=0;E<a;E++)for(var R=C+E*e.strides[1],I=Math.floor(E*g),k=Math.floor(I-x/2),S=0;S<i;S++)for(var A=R+S*e.strides[2],D=Math.floor(S*y),T=Math.floor(D-b/2),N=0;N<s;N++){for(var F=0,_=0;_<x;_++){var O=_+k;if(!(O<0||O>=c)){var M=C+O*t.strides[1],B=O*v;if(E===Math.min(a-1,n?Math.round(B):Math.floor(B)))for(var P=0;P<b;P++){var L=P+T;if(!(L<0||L>=l)){var W=M+L*t.strides[2],U=L*m;S===Math.min(i-1,n?Math.round(U):Math.floor(U))&&(F+=f[W+N]);}}}}h[A+N]=F;}return Ln(h,e.shape,e.dtype)},o.prototype.batchNormalization=function(t,e,n,r,o,a){Hh([t,e,n,o,a],"batchNorm");for(var i=this.readSync(t.dataId),s=this.readSync(e.dataId),u=this.readSync(n.dataId),c=o?this.readSync(o.dataId):new Float32Array([1]),l=a?this.readSync(a.dataId):new Float32Array([0]),h=new Float32Array(i.length),f=l.length,d=c.length,p=u.length,v=s.length,m=0,g=0,y=0,x=0,b=0;b<i.length;++b)h[b]=l[m++]+(i[b]-s[g++])*c[y++]/Math.sqrt(u[x++]+r),m>=f&&(m=0),g>=v&&(g=0),y>=d&&(y=0),x>=p&&(x=0);return Ln(h,t.shape)},o.prototype.localResponseNormalization4D=function(t,e,n,r,o){Hh(t,"localResponseNormalization4D");var a=t.shape[3],i=a-1,s=this.readSync(t.dataId),u=t.size,c=new Float32Array(u);function l(t){for(var n=t%a,r=t-n+Math.max(0,n-e),o=t-n+Math.min(n+e,i),u=0;r<=o;r++){var c=s[r];u+=c*c;}return u}for(var h=0;h<u;h++){var f=l(h),d=s[h]*Math.pow(n+r*f,-o);c[h]=d;}return Ln(c,t.shape)},o.prototype.LRNGrad=function(t,e,n,r,o,a,i){Hh(t,"LRNGrad");for(var s=t.shape[3],u=this.readSync(t.dataId),c=this.readSync(e.dataId),l=this.readSync(n.dataId),h=new Float32Array(t.size),f=t.size,d=0;d<f;d++){for(var p=d%s,v=d-p+Math.max(0,p-r),m=d-p+Math.min(s,p+r+1),g=0,y=v;y<m;y++)g+=Math.pow(c[y],2);g=a*g+o;for(y=v;y<m;y++){var x=-2*a*i*c[y]*l[d]/g;d===y&&(x+=Math.pow(g,-i)),x*=u[d],h[y]+=x;}}return Ln(h,t.shape)},o.prototype.multinomial=function(t,e,n,r){Hh(t,"multinomial");for(var o=e?t:go(t),a=o.shape[0],i=o.shape[1],s=Gn([a,n],"int32"),u=this.readSync(s.dataId),c=this.readSync(o.dataId),l=0;l<a;++l){var h=l*i,f=new Float32Array(i-1);f[0]=c[h];for(var d=1;d<f.length;++d)f[d]=f[d-1]+c[h+d];for(var p=cr(r.toString()),v=l*n,m=0;m<n;++m){var g=p();u[v+m]=f.length;for(var y=0;y<f.length;y++)if(g<f[y]){u[v+m]=y;break}}}return s},o.prototype.oneHot=function(t,e,n,r){Hh(t,"oneHot");var o=new Float32Array(t.size*e);o.fill(r);for(var a=this.readSync(t.dataId),i=0;i<t.size;++i)a[i]>=0&&a[i]<e&&(o[i*e+a[i]]=n);return Bn(o,[t.size,e],"int32")},o.prototype.nonMaxSuppression=function(t,e,n,r,o){return Hh(t,"nonMaxSuppression"),jo(this.readSync(t.dataId),this.readSync(e.dataId),n,r,o)},o.prototype.fft=function(t){return this.fftBatch(t,!1)},o.prototype.ifft=function(t){return this.fftBatch(t,!0)},o.prototype.fftBatch=function(t,e){for(var n=t.shape[0],r=t.shape[1],o=dr(t.shape,"float32"),a=dr(t.shape,"float32"),i=Tn(t).as2D(n,r),s=Nn(t).as2D(n,r),u=0;u<n;u++)for(var c=i.slice([u,0],[1,r]),l=s.slice([u,0],[1,r]),h=Dn(c,l),f=this.readSync(this.fftImpl(h,e).dataId),d=0;d<r;d++){var p=zo(f,d);o.values[u*r+d]=p.real,a.values[u*r+d]=p.imag;}return Dn(o.toTensor(),a.toTensor()).as2D(n,r)},o.prototype.fftImpl=function(t,e){var n=t.as1D(),r=n.size;if(this.isExponentOf2(r)){var o=this.fftRadix2(n,r,e).as2D(t.shape[0],t.shape[1]);return e&&(o=Dn(Tn(o).div(On(r)),Nn(o).div(On(r)))),o}var a=this.readSync(t.dataId),i=function(t){for(var e=new Float32Array(t.length/2),n=new Float32Array(t.length/2),r=0;r<t.length;r+=2)e[r/2]=t[r],n[r/2]=t[r+1];return {real:e,imag:n}}(this.fourierTransformByMatmul(a,r,e));return Dn(i.real,i.imag).as2D(t.shape[0],t.shape[1])},o.prototype.isExponentOf2=function(t){return 0==(t&t-1)},o.prototype.fftRadix2=function(t,e,n){if(1===e)return t;var r=this.readSync(t.dataId),o=e/2,a=function(t){for(var e=Math.ceil(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=0;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return {real:n,imag:r}}(r),i=Dn(a.real,a.imag).as1D(),s=function(t){for(var e=Math.floor(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=2;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return {real:n,imag:r}}(r),u=Dn(s.real,s.imag).as1D();i=this.fftRadix2(i,o,n),u=this.fftRadix2(u,o,n);var c=function(t,e){for(var n=new Float32Array(t/2),r=new Float32Array(t/2),o=0;o<Math.ceil(t/2);o++){var a=(e?2:-2)*Math.PI*(o/t);n[o]=Math.cos(a),r[o]=Math.sin(a);}return {real:n,imag:r}}(e,n),l=Dn(c.real,c.imag).mul(u),h=i.add(l),f=i.sub(l),d=Tn(h).concat(Tn(f)),p=Nn(h).concat(Nn(f));return Dn(d,p).as1D()},o.prototype.fourierTransformByMatmul=function(t,e,n){for(var r=new Float32Array(2*e),o=0;o<e;o++){for(var a=0,i=0,s=0;s<e;s++){var u=Ho(o*s,e,n),c=zo(t,s);a+=c.real*u.real-c.imag*u.imag,i+=c.real*u.imag+c.imag*u.real;}n&&(a/=e,i/=e),Go(r,a,i,o);}return r},o.prototype.depthToSpace=function(t,e,n){C("NHWC"===n,(function(){return "Only NHWC dataFormat supported on CPU for depthToSpace. Got "+n})),C(e>1,(function(){return "blockSize should be > 1 for depthToSpace, but was: "+e}));for(var r=t.shape[0],o=t.shape[1],a=t.shape[2],i=t.shape[3],s=o*e,u=a*e,c=i/(e*e),l=this.readSync(t.dataId),h=new Float32Array(r*s*u*c),f=0,d=0;d<r;++d)for(var p=0;p<s;++p)for(var v=Math.floor(p/e),m=p%e,g=0;g<u;++g)for(var y=Math.floor(g/e),x=(m*e+g%e)*c,b=0;b<c;++b){var w=b+x+i*(y+a*(v+o*d));h[f++]=l[w];}return Ln(h,[r,s,u,c])},o.prototype.broadcastedBinaryOp=function(t,e,n,r){var o=Ro(t.shape,e.shape),a=dr(o,n),i=this.readSync(t.dataId),s=this.readSync(e.dataId),u=Co(t.shape,o),c=Co(e.shape,o),l=a.values;if(u.length+c.length===0)for(var h=0;h<l.length;++h)l[h]=r(i[h%i.length],s[h%s.length]);else {var f=this.bufferSync(t),d=this.bufferSync(e),p=function(n){var o=a.indexToLoc(n),h=o.slice(-t.rank);u.forEach((function(t){return h[t]=0}));var p=f.locToIndex(h),v=o.slice(-e.rank);c.forEach((function(t){return v[t]=0}));var m=d.locToIndex(v);l[n]=r(i[p],s[m]);};for(h=0;h<l.length;++h)p(h);}return a.toTensor()},o.prototype.broadcastedBinaryComplexOp=function(t,e,n){var r=Ro(t.shape,e.shape),o=dr(r,"float32"),a=dr(r,"float32"),i=this.readSync(t.dataId),s=this.readSync(e.dataId),u=Co(t.shape,r),c=Co(e.shape,r),l=o.values,h=a.values;if(u.length+c.length===0)for(var f=0;f<l.length;f++){var d=f%i.length,p=f%s.length,v=n(i[2*d],i[2*d+1],s[2*p],s[2*p+1]);l[f]=v.real,h[f]=v.imag;}else {var m=this.bufferSync(this.data.get(t.dataId).complexTensors.real),g=this.bufferSync(this.data.get(e.dataId).complexTensors.real),y=function(r){var a=o.indexToLoc(r),f=a.slice(-t.rank);u.forEach((function(t){return f[t]=0}));var d=m.locToIndex(f),p=a.slice(-e.rank);c.forEach((function(t){return p[t]=0}));var v=g.locToIndex(p),y=n(i[2*d],i[2*d+1],s[2*v],s[2*v+1]);l[r]=y.real,h[r]=y.imag;};for(f=0;f<l.length;f++)y(f);}return this.complex(o.toTensor(),a.toTensor())},o.prototype.split=function(t,e,n){return Zo(t,e,n)},o.prototype.dispose=function(){},o.prototype.floatPrecision=function(){return 32},o.prototype.epsilon=function(){return 1e-7},o.prototype.cropAndResize=function(t,e,n,r,o,a){for(var i=t.shape,s=i[0],u=i[1],c=i[2],l=i[3],h=e.shape[0],f=r[0],d=r[1],p=dr([h,f,d,l],"float32"),v=this.readSync(e.dataId),m=this.readSync(n.dataId),g=this.readSync(t.dataId),y=t.strides,x=p.strides,b=0;b<h;b++){var w=4*b,C=v[w],E=v[w+1],R=v[w+2],I=v[w+3],k=m[b];if(!(k>=s))for(var S=f>1?(R-C)*(u-1)/(f-1):0,A=d>1?(I-E)*(c-1)/(d-1):0,D=0;D<f;D++){var T=f>1?C*(u-1)+D*S:.5*(C+R)*(u-1);if(T<0||T>u-1)for(var N=0;N<d;N++)for(var F=0;F<l;F++){var _=F+N*x[2]+D*x[1]+b*x[0];p.values[_]=a;}else if("bilinear"===o){var O=Math.floor(T),M=Math.ceil(T),B=T-O;for(N=0;N<d;N++){if((q=d>1?E*(c-1)+N*A:.5*(E+I)*(c-1))<0||q>c-1)for(F=0;F<l;F++){_=F+N*x[2]+D*x[1]+b*x[0];p.values[_]=a;}else {var P=Math.floor(q),L=Math.ceil(q),W=q-P;for(F=0;F<l;F++){var U=g[_=F+P*y[2]+O*y[1]+k*y[0]],V=g[_=F+L*y[2]+O*y[1]+k*y[0]],z=g[_=F+P*y[2]+M*y[1]+k*y[0]],G=U+(V-U)*W,H=z+(g[_=F+L*y[2]+M*y[1]+k*y[0]]-z)*W;_=F+N*x[2]+D*x[1]+b*x[0],p.values[_]=G+(H-G)*B;}}}}else for(N=0;N<d;++N){var q;if((q=d>1?E*(c-1)+N*A:.5*(E+I)*(c-1))<0||q>c-1)for(F=0;F<l;F++){_=F+N*x[2]+D*x[1]+b*x[0];p.values[_]=a;}else {var K=Math.round(q),j=Math.round(T);for(F=0;F<l;F++){var X=F+K*y[2]+j*y[1]+k*y[0],Y=F+N*x[2]+D*x[1]+b*x[0];p.values[Y]=g[X];}}}}}return p.toTensor()},o.prototype.sparseToDense=function(t,e,n,r){var o=Zr(0,t,n),a=o.sliceRank,i=o.numUpdates,s=o.sliceSize,u=o.strides,c=o.outputSize;return this.scatter(t,e,n,c,s,i,a,u,r,!1)},o.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=jr(t,e),a=o[0],i=o[1],s=o[2],u=o[3];if(0===i)return Fn([],a,t.dtype);for(var c=new gt([i,s],t.dtype),l=this.readSync(e.dataId),h=this.readSync(t.dataId),f=0;f<i;f++){for(var d=[],p=0,v=0;v<r;v++){var m=l[f*r+v];p+=m*u[v],d.push(m);}if(p<0||p>=t.size/s)throw new Error("Invalid 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y=h[p*i+g];v.push(y),m+=y*s[g];}if(m<0||m>=r/o)throw new Error("Invalid indices: "+v+" does not index into "+n);for(var x=0;x<o;x++)c?d.values[m*o+x]+=f[p*o+x]:d.values[m*o+x]=0===e.rank?f[0]:f[p*o+x];}return d.toTensor().reshape(n)},o}(bo);Lt.registerBackend("cpu",(function(){return new Kh}),1);for(var jh=0,Xh=[{kernelName:"NonMaxSuppressionV5",backendName:"cpu",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=t.attrs,o=e,a=o.boxes,i=o.scores,s=r,u=s.maxOutputSize,c=s.iouThreshold,l=s.scoreThreshold,h=s.softNmsSigma,f=n;Hh(a,"NonMaxSuppressionWithScore");var d=Xo(f.data.get(a.dataId).values,f.data.get(i.dataId).values,u,c,l,h);return [d.selectedIndices,d.selectedScores]}},{kernelName:"Square",backendName:"cpu",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e.x,o=n;Hh(r,"square");for(var a=o.data.get(r.dataId).values,i=new Float32Array(a.length),s=0;s<a.length;++s){var u=a[s];i[s]=u*u;}return {dataId:o.write(i,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},{kernelName:eu,backendName:"cpu",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e,o=r.a,a=r.b,i=n;Hh([o,a],eu);var s=i.data.get(o.dataId).values,u=i.data.get(a.dataId).values,c=function(t,e,n,r,o,a){var i=Ro(t,e),s=i.length,u=$(i),c=B(o,k(i)),l=t.length,h=e.length,f=$(t),d=$(e),p=Co(t,i),v=Co(e,i);if(p.length+v.length===0)for(var m=0;m<c.length;++m)c[m]=a(n[m%n.length],r[m%r.length]);else {var g=function(t){var e=it(t,s,u),o=e.slice(-l);p.forEach((function(t){return o[t]=0}));var i=at(o,l,f),m=e.slice(-h);v.forEach((function(t){return m[t]=0}));var g=at(m,h,d);c[t]=a(n[i],r[g]);};for(m=0;m<c.length;++m)g(m);}return [c,i]}(o.shape,a.shape,s,u,o.dtype,(function(t,e){var n=t-e;return n*n})),l=c[0],h=c[1];return {dataId:i.write(l,h,o.dtype),shape:h,dtype:o.dtype}}}];jh<Xh.length;jh++){d(Xh[jh]);}var Yh,$h=function(t){this.variableNames=["A"];var e=ua(),n=t[0],r=t[1];this.outputShape=t,this.userCode="\n      void main() 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t.prototype.listModels=function(){return n(this,void 0,void 0,(function(){var t=this;return r(this,(function(e){return [2,new Promise((function(e,n){var r=t.indexedDB.open("tensorflowjs",1);r.onupgradeneeded=function(){return Rf(r)},r.onsuccess=function(){var t=r.result,o=t.transaction(Cf,"readonly"),a=o.objectStore(Cf).getAll();a.onsuccess=function(){for(var t={},n=0,r=a.result;n<r.length;n++){var o=r[n];t[o.modelPath]=o.modelArtifactsInfo;}e(t);},a.onerror=function(e){return t.close(),n(a.error)},o.oncomplete=function(){return t.close()};},r.onerror=function(t){return n(r.error)};}))]}))}))},t.prototype.removeModel=function(t){return n(this,void 0,void 0,(function(){var e=this;return r(this,(function(n){var r;return t=(r=t).startsWith(If.URL_SCHEME)?r.slice(If.URL_SCHEME.length):r,[2,new Promise((function(n,r){var o=e.indexedDB.open("tensorflowjs",1);o.onupgradeneeded=function(){return Rf(o)},o.onsuccess=function(){var 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this.LS.setItem(this.keys.info,JSON.stringify(o)),this.LS.setItem(this.keys.topology,e),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,function(t){if(hf)return Buffer.from(t).toString("base64");for(var e=new Uint8Array(t),n="",r=0,o=e.length;r<o;r++)n+=String.fromCharCode(e[r]);return btoa(n)}(t.weightData)),this.LS.setItem(this.keys.modelMetadata,JSON.stringify({format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,userDefinedMetadata:t.userDefinedMetadata})),[2,{modelArtifactsInfo:o}]}catch(t){throw this.LS.removeItem(this.keys.info),this.LS.removeItem(this.keys.topology),this.LS.removeItem(this.keys.weightSpecs),this.LS.removeItem(this.keys.weightData),this.LS.removeItem(this.keys.modelMetadata),new Error("Failed to save model '"+this.modelPath+"' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes="+o.modelTopologyBytes+", weightSpecsBytes="+o.weightSpecsBytes+", weightDataBytes="+o.weightDataBytes+".")}return [2]}))}))},t.prototype.load=function(){return n(this,void 0,void 0,(function(){var t,e,n,o,a,i,s;return r(this,(function(r){if(null==(t=JSON.parse(this.LS.getItem(this.keys.info))))throw new Error("In local storage, there is no model with name '"+this.modelPath+"'");if("JSON"!==t.modelTopologyType)throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");if(e={},null==(n=JSON.parse(this.LS.getItem(this.keys.topology))))throw new Error("In local storage, the topology of model '"+this.modelPath+"' is missing.");if(e.modelTopology=n,null==(o=JSON.parse(this.LS.getItem(this.keys.weightSpecs))))throw new Error("In local storage, the weight specs of model '"+this.modelPath+"' are 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n=JSON.parse(this.LS.getItem(e.info)),this.LS.removeItem(e.info),this.LS.removeItem(e.topology),this.LS.removeItem(e.weightSpecs),this.LS.removeItem(e.weightData),[2,n]}))}))},t}();if(i().getBool("IS_BROWSER"))try{yf.registerManager(Pf.URL_SCHEME,new Wf);}catch(t){}var Uf="model",Vf=".json",zf=".weights.bin";function Gf(t){return new Promise((function(t){return setTimeout(t)})).then(t)}var Hf=function(){function t(e){if(!i().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(t.URL_SCHEME)&&(e=e.slice(t.URL_SCHEME.length)),null!=e&&0!==e.length||(e=Uf),this.modelTopologyFileName=e+Vf,this.weightDataFileName=e+zf;}return t.prototype.save=function(t){return n(this,void 0,void 0,(function(){var e,n,o,a,i,s;return r(this,(function(r){switch(r.label){case 0:if("undefined"==typeof document)throw new Error("Browser downloads are not supported in this environment since `document` is not 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3:r.sent(),r.label=4;case 4:return [2,{modelArtifactsInfo:vf(t)}]}}))}))},t.URL_SCHEME="downloads://",t}(),qf=function(){function t(t){if(null==t||t.length<1)throw new Error("When calling browserFiles, at least 1 file is required, but received "+t);this.files=t;}return t.prototype.load=function(){return n(this,void 0,void 0,(function(){var t,e,n=this;return r(this,(function(r){return t=this.files[0],e=this.files.slice(1),[2,new Promise((function(r,o){var a=new FileReader;a.onload=function(a){var i=JSON.parse(a.target.result),s=i.modelTopology;if(null!=s){0===e.length&&r({modelTopology:s});var u=i.weightsManifest;if(null!=u){var c;try{c=n.checkManifestAndWeightFiles(u,e);}catch(t){return void o(t)}var l=[],h=[],f=[];u.forEach((function(t){t.paths.forEach((function(t){h.push(t),f.push(null);})),l.push.apply(l,t.weights);})),u.forEach((function(t){t.paths.forEach((function(t){var e=new FileReader;e.onload=function(e){var 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Please verify this URL points to the model JSON of the model to load.");r.label=2;case 2:return r.trys.push([2,4,,5]),[4,t.json()];case 3:return e=r.sent(),[3,5];case 4:throw r.sent(),n="Failed to parse model JSON of response from "+this.path+".",this.path.endsWith(".pb")?n+=" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.":n+=" Please make sure the server is serving valid JSON for this request.",new Error(n);case 5:if(o=e.modelTopology,a=e.weightsManifest,i=e.generatedBy,s=e.convertedBy,u=e.format,c=e.userDefinedMetadata,null==o&&null==a)throw new Error("The JSON from HTTP path "+this.path+" contains neither model topology or manifest for weights.");return null==a?[3,7]:[4,this.loadWeights(a)];case 6:f=r.sent(),l=f[0],h=f[1],r.label=7;case 7:return [2,{modelTopology:o,weightSpecs:l,weightData:h,userDefinedMetadata:c,generatedBy:i,convertedBy:s,format:u}]}}))}))},t.prototype.loadWeights=function(t){return n(this,void 0,void 0,(function(){var e,n,o,a,i,s,u,c,l,h,f;return r(this,(function(r){switch(r.label){case 0:for(e=Array.isArray(this.path)?this.path[1]:this.path,n=function(t){var e=t.lastIndexOf("/"),n=t.lastIndexOf("?"),r=t.substring(0,e),o=n>e?t.substring(n):"";return [r+"/",o]}(e),o=n[0],a=n[1],i=this.weightPathPrefix||o,s=[],u=0,c=t;u<c.length;u++)l=c[u],s.push.apply(s,l.weights);return h=[],t.forEach((function(t){t.paths.forEach((function(t){h.push(i+t+a);}));})),[4,jf(h,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress})];case 1:return f=r.sent(),[2,[s,df(f)]]}}))}))},t.URL_SCHEME_REGEX=/^https?:\/\//,t}();function $f(t){return null!=t.match(Yf.URL_SCHEME_REGEX)}var Qf=function(t,e){if("undefined"==typeof fetch)return null;return (Array.isArray(t)?t.every((function(t){return $f(t)})):$f(t))?Jf(t,{onProgress:e}):null};function Jf(t,e){return new Yf(t,e)}mf.registerSaveRouter(Qf),mf.registerLoadRouter(Qf);var Zf=function(){function t(t){this.modelArtifacts=t;}return t.prototype.load=function(){return n(this,void 0,void 0,(function(){return r(this,(function(t){return [2,this.modelArtifacts]}))}))},t}(),td=function(){function t(t){this.saveHandler=t;}return t.prototype.save=function(t){return n(this,void 0,void 0,(function(){return r(this,(function(e){return [2,this.saveHandler(t)]}))}))},t}();var ed=Object.freeze({browserFiles:function(t){return new qf(t)},browserHTTPRequest:function(t,e){return Jf(t,e)},concatenateArrayBuffers:df,decodeWeights:cf,encodeWeights:function(t,e){return n(this,void 0,void 0,(function(){var o,a,i,s,u,c=this;return r(this,(function(l){switch(l.label){case 0:for(o=[],a=[],i=Array.isArray(t)?t.map((function(t){return t.name})):Object.keys(t),s=function(s){var u=i[s],l=Array.isArray(t)?t[s].tensor:t[u];if("float32"!==l.dtype&&"int32"!==l.dtype&&"bool"!==l.dtype&&"string"!==l.dtype)throw new Error("Unsupported dtype in weight '"+u+"': "+l.dtype);var h={name:u,shape:l.shape,dtype:l.dtype};if("string"===l.dtype){var f=new Promise((function(t){return n(c,void 0,void 0,(function(){var e,n,o,a,i,s,u;return r(this,(function(r){switch(r.label){case 0:return [4,l.bytes()];case 1:for(e=r.sent(),n=e.reduce((function(t,e){return t+e.length}),0)+uf*e.length,o=new Uint8Array(n),a=0,i=0;i<e.length;i++)s=e[i],u=new Uint8Array(new Uint32Array([s.length]).buffer),o.set(u,a),a+=uf,o.set(s,a),a+=s.length;return t(o),[2]}}))}))}));a.push(f);}else a.push(l.data());null!=e&&(h.group=e),o.push(h);},u=0;u<i.length;++u)s(u);return [4,Promise.all(a)];case 1:return [2,{data:lf(l.sent()),specs:o}]}}))}))},fromMemory:function(t,e,n,r){return 1===arguments.length?null!=t.modelTopology||null!=t.weightSpecs?new Zf(t):(console.warn("Please call tf.io.fromMemory() with only one argument. 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The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new Zf({modelTopology:t,weightSpecs:e,weightData:n,trainingConfig:r}))},getLoadHandlers:function(t,e){return mf.getLoadHandlers(t,e)},getModelArtifactsInfoForJSON:vf,getSaveHandlers:function(t){return mf.getSaveHandlers(t)},http:Jf,isHTTPScheme:$f,loadWeights:function(t,e,o,a){return void 0===e&&(e=""),n(this,void 0,void 0,(function(){return r(this,(function(n){return [2,Xf((function(t){return jf(t,{requestInit:a})}))(t,e,o)]}))}))},registerLoadRouter:function(t){return mf.registerLoadRouter(t)},registerSaveRouter:function(t){return mf.registerSaveRouter(t)},weightsLoaderFactory:Xf,withSaveHandler:function(t){return new td(t)},copyModel:function(t,e){return n(this,void 0,void 0,(function(){return r(this,(function(n){return [2,bf(t,e,!1)]}))}))},listModels:function(){return n(this,void 0,void 0,(function(){var t,e,n,o,a,i,s;return r(this,(function(r){switch(r.label){case 0:t=yf.getSchemes(),e={},n=0,o=t,r.label=1;case 1:return n<o.length?(a=o[n],[4,yf.getManager(a).listModels()]):[3,4];case 2:for(s in i=r.sent())e[a+gf+s]=i[s];r.label=3;case 3:return n++,[3,1];case 4:return [2,e]}}))}))},moveModel:function(t,e){return n(this,void 0,void 0,(function(){return r(this,(function(n){return [2,bf(t,e,!0)]}))}))},removeModel:function(t){return n(this,void 0,void 0,(function(){var e;return r(this,(function(n){return e=xf(t),[2,yf.getManager(e.scheme).removeModel(e.path)]}))}))}});var nd,rd=An({confusionMatrix_:function(t,e,n){var r=mn(t,"labels","confusionMatrix"),o=mn(e,"predictions","confusionMatrix");C(null==n||n>0&&Number.isInteger(n),(function(){return "If provided, numClasses must be a positive integer, but got "+n})),C(1===r.rank,(function(){return "Expected the rank of labels to be 1, but got "+r.rank})),C(1===o.rank,(function(){return "Expected the rank of predictions to be 1, but got "+o.rank})),C(r.shape[0]===o.shape[0],(function(){return "Mismatch in the number of examples: "+r.shape[0]+" vs. "+o.shape[0]+". Labels and predictions should have the same number of elements."})),C(n>0&&Number.isInteger(n),(function(){return "numClasses is required to be a positive integer, but got "+n}));var a=Rr(r.asType("int32"),n),i=Rr(o.asType("int32"),n);return a.transpose().matMul(i).asType("int32")}}),od=Object.freeze({confusionMatrix:rd});var ad=An({fromPixels_:function(t,e){if(void 0===e&&(e=3),e>4)throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");if(null==t)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");var n=!1,r=!1,o=!1,a=!1,i=!1;if(t.data instanceof Uint8Array)n=!0;else if("undefined"!=typeof ImageData&&t instanceof ImageData)r=!0;else if("undefined"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement)o=!0;else if("undefined"!=typeof HTMLImageElement&&t instanceof HTMLImageElement)a=!0;else {if(null==t.getContext)throw new Error("pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was "+t.constructor.name);i=!0;}if(o){if(o&&t.readyState<2)throw new Error("The video element has not loaded data yet. 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vd(t,e,0)}))},expectNumbersClose:function(t,e,n){if(null==n&&(n=dd()),!vd(t,e,n))throw new Error("Numbers differ: actual === "+t+", expected === "+e)},expectValuesInRange:function(t,e,n){for(var r=0;r<t.length;r++)if(t[r]<e||t[r]>n)throw new Error("Value out of range:"+t[r]+" low: "+e+", high: "+n)},expectArrayBuffersEqual:function(t,e){expect(new Float32Array(t)).toEqual(new Float32Array(e));}}),gd="1.7.0";var yd=Object.freeze({gpgpu_util:Mi,webgl_util:Ge,forceHalfFloat:function(){i().set("WEBGL_FORCE_F16_TEXTURES",!0);},MathBackendWebGL:Zs,setWebGLContext:Kt,GPGPUContext:Bi}),xd=function(t){function o(){return null!==t&&t.apply(this,arguments)||this}return e(o,t),o.prototype.minimize=function(t,e,n){void 0===e&&(e=!1);var r=this.computeGradients(t,n),o=r.value,a=r.grads;if(null!=n){var i=n.map((function(t){return {name:t.name,tensor:a[t.name]}}));this.applyGradients(i);}else this.applyGradients(a);return 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e=this,n=Array.isArray(t)?t.map((function(t){return t.name})):Object.keys(t);Ze((function(){var r=Cc(1,e.accBeta1),o=Cc(1,e.accBeta2);n.forEach((function(n,a){var i=Lt.registeredVariables[n];null==e.accumulatedFirstMoment[a]&&(e.accumulatedFirstMoment[a]={originalName:n+"/m",variable:Ze((function(){return Xn(i).variable(!1)}))}),null==e.accumulatedSecondMoment[a]&&(e.accumulatedSecondMoment[a]={originalName:n+"/v",variable:Ze((function(){return Xn(i).variable(!1)}))});var s=Array.isArray(t)?t[a].tensor:t[n];if(null!=s){var u=e.accumulatedFirstMoment[a].variable,c=e.accumulatedSecondMoment[a].variable,l=u.mul(e.beta1).add(s.mul(1-e.beta1)),h=c.mul(e.beta2).add(s.square().mul(1-e.beta2)),f=l.div(r),d=h.div(o);u.assign(l),c.assign(h);var 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+    floor: gu,
+    floorDiv: lc,
+    frame: ih,
+    fused: zh,
+    gather: Lc,
+    gatherND: th,
+    gather_util: Xr,
+    getBackend: an,
+    getGradient: h,
+    getKernel: l,
+    getKernelsForBackend: f,
+    grad: co,
+    grads: lo,
+    greater: kc,
+    greaterEqual: Sc,
+    greaterEqualStrict: Ac,
+    greaterStrict: Dc,
+    hammingWindow: ah,
+    hannWindow: oh,
+    ifft: Yl,
+    imag: Nn,
+    image: Oh,
+    inTopKAsync: lh,
+    io: ed,
+    irfft: Ql,
+    isFinite: Du,
+    isInf: Au,
+    isNaN: Su,
+    keep: en,
+    leakyRelu: Ol,
+    less: Tc,
+    lessEqual: Nc,
+    lessEqualStrict: Fc,
+    lessStrict: _c,
+    linalg: Ih,
+    linspace: qn,
+    localResponseNormalization: Ul,
+    log: yu,
+    log1p: xu,
+    logSigmoid: bu,
+    logSoftmax: yo,
+    logSumExp: kl,
+    logicalAnd: Qu,
+    logicalNot: Ju,
+    logicalOr: Zu,
+    logicalXor: tc,
+    losses: bh,
+    matMul: el,
+    math: od,
+    max: Sl,
+    maxPool: hl,
+    maxPool3d: pl,
+    maximum: hc,
+    maximumStrict: fc,
+    mean: Al,
+    memory: Qe,
+    min: Dl,
+    minimum: dc,
+    minimumStrict: pc,
+    mod: vc,
+    modStrict: mc,
+    moments: Tl,
+    movingAverage: Hl,
+    mul: gc,
+    mulStrict: yc,
+    multiRNNCell: Gl,
+    multinomial: Er,
+    neg: wu,
+    nextFrame: Td,
+    norm: Vl,
+    notEqual: Oc,
+    notEqualStrict: Mc,
+    oneHot: Rr,
+    ones: zn,
+    onesLike: jn,
+    op: An,
+    outerProduct: rl,
+    pad: Ir,
+    pad1d: kr,
+    pad2d: Sr,
+    pad3d: Ar,
+    pad4d: Dr,
+    pool: dl,
+    pow: xc,
+    powStrict: bc,
+    prelu: Ml,
+    print: pr,
+    prod: Fl,
+    profile: Je,
+    rand: Tr,
+    randomGamma: Fr,
+    randomNormal: Nr,
+    randomUniform: _r,
+    range: Kn,
+    ready: on,
+    real: Tn,
+    reciprocal: Cu,
+    registerBackend: ln,
+    registerGradient: p,
+    registerKernel: d,
+    relu: Bl,
+    relu6: Pl,
+    removeBackend: sn,
+    reshape: Or,
+    reverse: ol,
+    reverse1d: al,
+    reverse2d: il,
+    reverse3d: sl,
+    reverse4d: ul,
+    rfft: $l,
+    round: Eu,
+    rsqrt: Ru,
+    scalar: On,
+    scatterND: jl,
+    scatter_util: to,
+    selu: Ll,
+    separableConv2d: Jc,
+    serialization: ld,
+    setBackend: rn,
+    setPlatform: fn,
+    setdiff1dAsync: Vr,
+    sigmoid: Iu,
+    sign: ku,
+    signal: uh,
+    sin: Tu,
+    sinh: Nu,
+    slice: ml,
+    slice1d: gl,
+    slice2d: yl,
+    slice3d: xl,
+    slice4d: bl,
+    slice_util: uo,
+    softmax: go,
+    softplus: Fu,
+    spaceToBatchND: Mr,
+    sparseToDense: Zl,
+    spectral: Jl,
+    split: tr,
+    sqrt: _u,
+    square: tu,
+    squaredDifference: nu,
+    squaredDifferenceStrict: wc,
+    squeeze: Br,
+    stack: Pr,
+    step: Ou,
+    stft: sh,
+    stridedSlice: ql,
+    sub: Cc,
+    subStrict: Ec,
+    sum: Nl,
+    sumOutType: Tt,
+    tan: Mu,
+    tanh: Bu,
+    tensor: Fn,
+    tensor1d: Mn,
+    tensor2d: Bn,
+    tensor3d: Pn,
+    tensor4d: Ln,
+    tensor5d: Wn,
+    tensor6d: Un,
+    tensor_util: Mt,
+    test_util: md,
+    tidy: Ze,
+    tile: Lr,
+    time: nn,
+    topk: Kl,
+    train: Ad,
+    transpose: Wl,
+    truncatedNormal: Wr,
+    unregisterGradient: m,
+    unregisterKernel: v,
+    unsortedSegmentSum: Wc,
+    unstack: Ur,
+    util: st,
+    valueAndGrad: ho,
+    valueAndGrads: fo,
+    variable: Vn,
+    variableGrads: po,
+    version_core: gd,
+    webgl: yd,
+    where: ec,
+    whereAsync: nc,
+    zeros: Gn,
+    zerosLike: Xn
   });
 
   function drawContour(ctx, points, isClosed) {
@@ -432,7 +438,7 @@
   }());
 
   function isTensor(tensor, dim) {
-      return tensor instanceof dt && tensor.shape.length === dim;
+      return tensor instanceof wt && tensor.shape.length === dim;
   }
   function isTensor1D(tensor) {
       return isTensor(tensor, 1);
@@ -851,13 +857,13 @@
   }
 
   function normalize(x, meanRgb) {
-      return Ke(function () {
+      return Ze(function () {
           var r = meanRgb[0], g = meanRgb[1], b = meanRgb[2];
-          var avg_r = Pn(__spreadArrays(x.shape.slice(0, 3), [1]), r);
-          var avg_g = Pn(__spreadArrays(x.shape.slice(0, 3), [1]), g);
-          var avg_b = Pn(__spreadArrays(x.shape.slice(0, 3), [1]), b);
-          var avg_rgb = zn([avg_r, avg_g, avg_b], 3);
-          return ac(x, avg_rgb);
+          var avg_r = Hn(__spreadArrays(x.shape.slice(0, 3), [1]), r);
+          var avg_g = Hn(__spreadArrays(x.shape.slice(0, 3), [1]), g);
+          var avg_b = Hn(__spreadArrays(x.shape.slice(0, 3), [1]), b);
+          var avg_rgb = Yn([avg_r, avg_g, avg_b], 3);
+          return Cc(x, avg_rgb);
       });
   }
 
@@ -871,7 +877,7 @@
    */
   function padToSquare(imgTensor, isCenterImage) {
       if (isCenterImage === void 0) { isCenterImage = false; }
-      return Ke(function () {
+      return Ze(function () {
           var _a = imgTensor.shape.slice(1), height = _a[0], width = _a[1];
           if (height === width) {
               return imgTensor;
@@ -882,7 +888,7 @@
           var createPaddingTensor = function (paddingAmount) {
               var paddingTensorShape = imgTensor.shape.slice();
               paddingTensorShape[paddingAxis] = paddingAmount;
-              return Pn(paddingTensorShape, 0);
+              return Hn(paddingTensorShape, 0);
           };
           var paddingTensorAppend = createPaddingTensor(paddingAmount);
           var remainingPaddingAmount = dimDiff - paddingTensorAppend.shape[paddingAxis];
@@ -896,7 +902,7 @@
           ]
               .filter(function (t) { return !!t; })
               .map(function (t) { return t.toFloat(); });
-          return zn(tensorsToStack, paddingAxis);
+          return Yn(tensorsToStack, paddingAxis);
       });
   }
 
@@ -1589,8 +1595,8 @@
                   case 0:
                       targetCanvas = canvas || env.getEnv().createCanvasElement();
                       _a = imgTensor.shape.slice(isTensor4D(imgTensor) ? 1 : 0), height = _a[0], width = _a[1], numChannels = _a[2];
-                      imgTensor3D = Ke(function () { return imgTensor.as3D(height, width, numChannels).toInt(); });
-                      return [4 /*yield*/, Mf.toPixels(imgTensor3D, targetCanvas)];
+                      imgTensor3D = Ze(function () { return imgTensor.as3D(height, width, numChannels).toInt(); });
+                      return [4 /*yield*/, id.toPixels(imgTensor3D, targetCanvas)];
                   case 1:
                       _b.sent();
                       imgTensor3D.dispose();
@@ -1742,23 +1748,23 @@
           var _this = this;
           if (isCenterInputs === void 0) { isCenterInputs = true; }
           this._inputSize = inputSize;
-          return Ke(function () {
+          return Ze(function () {
               var inputTensors = range(_this.batchSize, 0, 1).map(function (batchIdx) {
                   var input = _this.getInput(batchIdx);
-                  if (input instanceof dt) {
+                  if (input instanceof wt) {
                       var imgTensor = isTensor4D(input) ? input : input.expandDims();
                       imgTensor = padToSquare(imgTensor, isCenterInputs);
                       if (imgTensor.shape[1] !== inputSize || imgTensor.shape[2] !== inputSize) {
-                          imgTensor = vh.resizeBilinear(imgTensor, [inputSize, inputSize]);
+                          imgTensor = Oh.resizeBilinear(imgTensor, [inputSize, inputSize]);
                       }
                       return imgTensor.as3D(inputSize, inputSize, 3);
                   }
                   if (input instanceof env.getEnv().Canvas) {
-                      return Mf.fromPixels(imageToSquare(input, inputSize, isCenterInputs));
+                      return id.fromPixels(imageToSquare(input, inputSize, isCenterInputs));
                   }
                   throw new Error("toBatchTensor - at batchIdx " + batchIdx + ", expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have " + input);
               });
-              var batchTensor = Tr(inputTensors.map(function (t) { return t.toFloat(); })).as4D(_this.batchSize, inputSize, inputSize, 3);
+              var batchTensor = Pr(inputTensors.map(function (t) { return t.toFloat(); })).as4D(_this.batchSize, inputSize, inputSize, 3);
               return batchTensor;
           });
       };
@@ -1885,7 +1891,7 @@
               if (isTensor4D(imageTensor) && imageTensor.shape[0] > 1) {
                   throw new Error('extractFaceTensors - batchSize > 1 not supported');
               }
-              return [2 /*return*/, Ke(function () {
+              return [2 /*return*/, Ze(function () {
                       var _a = imageTensor.shape.slice(isTensor4D(imageTensor) ? 1 : 0), imgHeight = _a[0], imgWidth = _a[1], numChannels = _a[2];
                       var boxes = detections.map(function (det) { return det instanceof FaceDetection
                           ? det.forSize(imgWidth, imgHeight).box
@@ -1893,7 +1899,7 @@
                           .map(function (box) { return box.clipAtImageBorders(imgWidth, imgHeight); });
                       var faceTensors = boxes.map(function (_a) {
                           var x = _a.x, y = _a.y, width = _a.width, height = _a.height;
-                          return nl(imageTensor.as3D(imgHeight, imgWidth, numChannels), [y, x, 0], [height, width, numChannels]);
+                          return xl(imageTensor.as3D(imgHeight, imgWidth, numChannels), [y, x, 0], [height, width, numChannels]);
                       });
                       return faceTensors;
                   })];
@@ -2004,7 +2010,7 @@
                       return [4 /*yield*/, fetchJson(manifestUri)];
                   case 1:
                       manifest = _b.sent();
-                      return [2 /*return*/, Tf.loadWeights(manifest, modelBaseUri)];
+                      return [2 /*return*/, ed.loadWeights(manifest, modelBaseUri)];
               }
           });
       });
@@ -2061,10 +2067,10 @@
           });
       };
       NeuralNetwork.prototype.getTrainableParams = function () {
-          return this.getParamList().filter(function (param) { return param.tensor instanceof bt; });
+          return this.getParamList().filter(function (param) { return param.tensor instanceof St; });
       };
       NeuralNetwork.prototype.getFrozenParams = function () {
-          return this.getParamList().filter(function (param) { return !(param.tensor instanceof bt); });
+          return this.getParamList().filter(function (param) { return !(param.tensor instanceof St); });
       };
       NeuralNetwork.prototype.variable = function () {
           var _this = this;
@@ -2077,7 +2083,7 @@
           var _this = this;
           this.getTrainableParams().forEach(function (_a) {
               var path = _a.path, variable = _a.tensor;
-              var tensor = In(variable.dataSync());
+              var tensor = Fn(variable.dataSync());
               variable.dispose();
               _this.reassignParamFromPath(path, tensor);
           });
@@ -2147,7 +2153,7 @@
                           readFile = env.getEnv().readFile;
                           _a = getModelUris(filePath, this.getDefaultModelName()), manifestUri = _a.manifestUri, modelBaseUri = _a.modelBaseUri;
                           fetchWeightsFromDisk = function (filePaths) { return Promise.all(filePaths.map(function (filePath) { return readFile(filePath).then(function (buf) { return buf.buffer; }); })); };
-                          loadWeights = Tf.weightsLoaderFactory(fetchWeightsFromDisk);
+                          loadWeights = ed.weightsLoaderFactory(fetchWeightsFromDisk);
                           _c = (_b = JSON).parse;
                           return [4 /*yield*/, readFile(manifestUri)];
                       case 1:
@@ -2182,7 +2188,7 @@
               return { obj: res.nextObj, objProp: objProp, nextObj: res.nextObj[objProp] };
           }, { nextObj: this.params });
           var obj = result.obj, objProp = result.objProp;
-          if (!obj || !objProp || !(obj[objProp] instanceof dt)) {
+          if (!obj || !objProp || !(obj[objProp] instanceof wt)) {
               throw new Error("traversePropertyPath - parameter is not a tensor, for path " + paramPath);
           }
           return { obj: obj, objProp: objProp };
@@ -2191,47 +2197,47 @@
   }());
 
   function depthwiseSeparableConv(x, params, stride) {
-      return Ke(function () {
-          var out = Mc(x, params.depthwise_filter, params.pointwise_filter, stride, 'same');
-          out = Ws(out, params.bias);
+      return Ze(function () {
+          var out = Jc(x, params.depthwise_filter, params.pointwise_filter, stride, 'same');
+          out = rc(out, params.bias);
           return out;
       });
   }
 
   function denseBlock3(x, denseBlockParams, isFirstLayer) {
       if (isFirstLayer === void 0) { isFirstLayer = false; }
-      return Ke(function () {
-          var out1 = xl(isFirstLayer
-              ? Ws(Ac(x, denseBlockParams.conv0.filters, [2, 2], 'same'), denseBlockParams.conv0.bias)
+      return Ze(function () {
+          var out1 = Bl(isFirstLayer
+              ? rc(qc(x, denseBlockParams.conv0.filters, [2, 2], 'same'), denseBlockParams.conv0.bias)
               : depthwiseSeparableConv(x, denseBlockParams.conv0, [2, 2]));
           var out2 = depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1]);
-          var in3 = xl(Ws(out1, out2));
+          var in3 = Bl(rc(out1, out2));
           var out3 = depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1]);
-          return xl(Ws(out1, Ws(out2, out3)));
+          return Bl(rc(out1, rc(out2, out3)));
       });
   }
   function denseBlock4(x, denseBlockParams, isFirstLayer, isScaleDown) {
       if (isFirstLayer === void 0) { isFirstLayer = false; }
       if (isScaleDown === void 0) { isScaleDown = true; }
-      return Ke(function () {
-          var out1 = xl(isFirstLayer
-              ? Ws(Ac(x, denseBlockParams.conv0.filters, isScaleDown ? [2, 2] : [1, 1], 'same'), denseBlockParams.conv0.bias)
+      return Ze(function () {
+          var out1 = Bl(isFirstLayer
+              ? rc(qc(x, denseBlockParams.conv0.filters, isScaleDown ? [2, 2] : [1, 1], 'same'), denseBlockParams.conv0.bias)
               : depthwiseSeparableConv(x, denseBlockParams.conv0, isScaleDown ? [2, 2] : [1, 1]));
           var out2 = depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1]);
-          var in3 = xl(Ws(out1, out2));
+          var in3 = Bl(rc(out1, out2));
           var out3 = depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1]);
-          var in4 = xl(Ws(out1, Ws(out2, out3)));
+          var in4 = Bl(rc(out1, rc(out2, out3)));
           var out4 = depthwiseSeparableConv(in4, denseBlockParams.conv3, [1, 1]);
-          return xl(Ws(out1, Ws(out2, Ws(out3, out4))));
+          return Bl(rc(out1, rc(out2, rc(out3, out4))));
       });
   }
 
   function convLayer(x, params, padding, withRelu) {
       if (padding === void 0) { padding = 'same'; }
       if (withRelu === void 0) { withRelu = false; }
-      return Ke(function () {
-          var out = Ws(Ac(x, params.filters, [1, 1], padding), params.bias);
-          return withRelu ? xl(out) : out;
+      return Ze(function () {
+          var out = rc(qc(x, params.filters, [1, 1], padding), params.bias);
+          return withRelu ? Bl(out) : out;
       });
   }
 
@@ -2245,8 +2251,8 @@
 
   function extractConvParamsFactory(extractWeights, paramMappings) {
       return function (channelsIn, channelsOut, filterSize, mappedPrefix) {
-          var filters = Nn(extractWeights(channelsIn * channelsOut * filterSize * filterSize), [filterSize, filterSize, channelsIn, channelsOut]);
-          var bias = An(extractWeights(channelsOut));
+          var filters = Ln(extractWeights(channelsIn * channelsOut * filterSize * filterSize), [filterSize, filterSize, channelsIn, channelsOut]);
+          var bias = Mn(extractWeights(channelsOut));
           paramMappings.push({ paramPath: mappedPrefix + "/filters" }, { paramPath: mappedPrefix + "/bias" });
           return { filters: filters, bias: bias };
       };
@@ -2254,8 +2260,8 @@
 
   function extractFCParamsFactory(extractWeights, paramMappings) {
       return function (channelsIn, channelsOut, mappedPrefix) {
-          var fc_weights = Dn(extractWeights(channelsIn * channelsOut), [channelsIn, channelsOut]);
-          var fc_bias = An(extractWeights(channelsOut));
+          var fc_weights = Bn(extractWeights(channelsIn * channelsOut), [channelsIn, channelsOut]);
+          var fc_bias = Mn(extractWeights(channelsOut));
           paramMappings.push({ paramPath: mappedPrefix + "/weights" }, { paramPath: mappedPrefix + "/bias" });
           return {
               weights: fc_weights,
@@ -2275,9 +2281,9 @@
 
   function extractSeparableConvParamsFactory(extractWeights, paramMappings) {
       return function (channelsIn, channelsOut, mappedPrefix) {
-          var depthwise_filter = Nn(extractWeights(3 * 3 * channelsIn), [3, 3, channelsIn, 1]);
-          var pointwise_filter = Nn(extractWeights(channelsIn * channelsOut), [1, 1, channelsIn, channelsOut]);
-          var bias = An(extractWeights(channelsOut));
+          var depthwise_filter = Ln(extractWeights(3 * 3 * channelsIn), [3, 3, channelsIn, 1]);
+          var pointwise_filter = Ln(extractWeights(channelsIn * channelsOut), [1, 1, channelsIn, channelsOut]);
+          var bias = Mn(extractWeights(channelsOut));
           paramMappings.push({ paramPath: mappedPrefix + "/depthwise_filter" }, { paramPath: mappedPrefix + "/pointwise_filter" }, { paramPath: mappedPrefix + "/bias" });
           return new SeparableConvParams(depthwise_filter, pointwise_filter, bias);
       };
@@ -2419,15 +2425,15 @@
           if (!params) {
               throw new Error('FaceFeatureExtractor - load model before inference');
           }
-          return Ke(function () {
+          return Ze(function () {
               var batchTensor = input.toBatchTensor(112, true);
               var meanRgb = [122.782, 117.001, 104.298];
-              var normalized = normalize(batchTensor, meanRgb).div(Sn(255));
+              var normalized = normalize(batchTensor, meanRgb).div(On(255));
               var out = denseBlock4(normalized, params.dense0, true);
               out = denseBlock4(out, params.dense1);
               out = denseBlock4(out, params.dense2);
               out = denseBlock4(out, params.dense3);
-              out = $c(out, [7, 7], [2, 2], 'valid');
+              out = fl(out, [7, 7], [2, 2], 'valid');
               return out;
           });
       };
@@ -2457,8 +2463,8 @@
   }(NeuralNetwork));
 
   function fullyConnectedLayer(x, params) {
-      return Ke(function () {
-          return Ws(Lc(x, params.weights), params.bias);
+      return Ze(function () {
+          return rc(el(x, params.weights), params.bias);
       });
   }
 
@@ -2521,7 +2527,7 @@
           if (!params) {
               throw new Error(this._name + " - load model before inference");
           }
-          return Ke(function () {
+          return Ze(function () {
               var bottleneckFeatures = input instanceof NetInput
                   ? _this.faceFeatureExtractor.forwardInput(input)
                   : input;
@@ -2586,7 +2592,7 @@
       }
       FaceExpressionNet.prototype.forwardInput = function (input) {
           var _this = this;
-          return Ke(function () { return io(_this.runNet(input)); });
+          return Ze(function () { return go(_this.runNet(input)); });
       };
       FaceExpressionNet.prototype.forward = function (input) {
           return __awaiter(this, void 0, void 0, function () {
@@ -2613,7 +2619,7 @@
                           return [4 /*yield*/, this.forwardInput(netInput)];
                       case 2:
                           out = _a.sent();
-                          return [4 /*yield*/, Promise.all(_r(out).map(function (t) { return __awaiter(_this, void 0, void 0, function () {
+                          return [4 /*yield*/, Promise.all(Ur(out).map(function (t) { return __awaiter(_this, void 0, void 0, function () {
                                   var data;
                                   return __generator(this, function (_a) {
                                       switch (_a.label) {
@@ -2875,22 +2881,22 @@
   }
 
   function conv(x, params, stride) {
-      return Ws(Ac(x, params.filters, stride, 'same'), params.bias);
+      return rc(qc(x, params.filters, stride, 'same'), params.bias);
   }
   function reductionBlock(x, params, isActivateInput) {
       if (isActivateInput === void 0) { isActivateInput = true; }
-      var out = isActivateInput ? xl(x) : x;
+      var out = isActivateInput ? Bl(x) : x;
       out = depthwiseSeparableConv(out, params.separable_conv0, [1, 1]);
-      out = depthwiseSeparableConv(xl(out), params.separable_conv1, [1, 1]);
-      out = Xc(out, [3, 3], [2, 2], 'same');
-      out = Ws(out, conv(x, params.expansion_conv, [2, 2]));
+      out = depthwiseSeparableConv(Bl(out), params.separable_conv1, [1, 1]);
+      out = hl(out, [3, 3], [2, 2], 'same');
+      out = rc(out, conv(x, params.expansion_conv, [2, 2]));
       return out;
   }
   function mainBlock(x, params) {
-      var out = depthwiseSeparableConv(xl(x), params.separable_conv0, [1, 1]);
-      out = depthwiseSeparableConv(xl(out), params.separable_conv1, [1, 1]);
-      out = depthwiseSeparableConv(xl(out), params.separable_conv2, [1, 1]);
-      out = Ws(out, x);
+      var out = depthwiseSeparableConv(Bl(x), params.separable_conv0, [1, 1]);
+      out = depthwiseSeparableConv(Bl(out), params.separable_conv1, [1, 1]);
+      out = depthwiseSeparableConv(Bl(out), params.separable_conv2, [1, 1]);
+      out = rc(out, x);
       return out;
   }
   var TinyXception = /** @class */ (function (_super) {
@@ -2906,18 +2912,18 @@
           if (!params) {
               throw new Error('TinyXception - load model before inference');
           }
-          return Ke(function () {
+          return Ze(function () {
               var batchTensor = input.toBatchTensor(112, true);
               var meanRgb = [122.782, 117.001, 104.298];
-              var normalized = normalize(batchTensor, meanRgb).div(Sn(256));
-              var out = xl(conv(normalized, params.entry_flow.conv_in, [2, 2]));
+              var normalized = normalize(batchTensor, meanRgb).div(On(256));
+              var out = Bl(conv(normalized, params.entry_flow.conv_in, [2, 2]));
               out = reductionBlock(out, params.entry_flow.reduction_block_0, false);
               out = reductionBlock(out, params.entry_flow.reduction_block_1);
               range(_this._numMainBlocks, 0, 1).forEach(function (idx) {
                   out = mainBlock(out, params.middle_flow["main_block_" + idx]);
               });
               out = reductionBlock(out, params.exit_flow.reduction_block);
-              out = xl(depthwiseSeparableConv(out, params.exit_flow.separable_conv, [1, 1]));
+              out = Bl(depthwiseSeparableConv(out, params.exit_flow.separable_conv, [1, 1]));
               return out;
           });
       };
@@ -3005,11 +3011,11 @@
           if (!params) {
               throw new Error(this._name + " - load model before inference");
           }
-          return Ke(function () {
+          return Ze(function () {
               var bottleneckFeatures = input instanceof NetInput
                   ? _this.faceFeatureExtractor.forwardInput(input)
                   : input;
-              var pooled = $c(bottleneckFeatures, [7, 7], [2, 2], 'valid').as2D(bottleneckFeatures.shape[0], -1);
+              var pooled = fl(bottleneckFeatures, [7, 7], [2, 2], 'valid').as2D(bottleneckFeatures.shape[0], -1);
               var age = fullyConnectedLayer(pooled, params.fc.age).as1D();
               var gender = fullyConnectedLayer(pooled, params.fc.gender);
               return { age: age, gender: gender };
@@ -3017,9 +3023,9 @@
       };
       AgeGenderNet.prototype.forwardInput = function (input) {
           var _this = this;
-          return Ke(function () {
+          return Ze(function () {
               var _a = _this.runNet(input), age = _a.age, gender = _a.gender;
-              return { age: age, gender: io(gender) };
+              return { age: age, gender: go(gender) };
           });
       };
       AgeGenderNet.prototype.forward = function (input) {
@@ -3047,8 +3053,8 @@
                           return [4 /*yield*/, this.forwardInput(netInput)];
                       case 2:
                           out = _a.sent();
-                          ages = _r(out.age);
-                          genders = _r(out.gender);
+                          ages = Ur(out.age);
+                          genders = Ur(out.gender);
                           ageAndGenderTensors = ages.map(function (ageTensor, i) { return ({
                               ageTensor: ageTensor,
                               genderTensor: genders[i]
@@ -3132,11 +3138,11 @@
               };
           });
           var batchSize = inputDimensions.length;
-          return Ke(function () {
+          return Ze(function () {
               var createInterleavedTensor = function (fillX, fillY) {
-                  return Tr([
-                      Pn([68], fillX),
-                      Pn([68], fillY)
+                  return Pr([
+                      Hn([68], fillX),
+                      Hn([68], fillY)
                   ], 1).as2D(1, 136).as1D();
               };
               var getPadding = function (batchIdx, cond) {
@@ -3146,11 +3152,11 @@
               var getPaddingX = function (batchIdx) { return getPadding(batchIdx, function (w, h) { return w < h; }); };
               var getPaddingY = function (batchIdx) { return getPadding(batchIdx, function (w, h) { return h < w; }); };
               var landmarkTensors = output
-                  .mul(Pn([batchSize, 136], inputSize))
-                  .sub(Tr(Array.from(Array(batchSize), function (_, batchIdx) {
+                  .mul(Hn([batchSize, 136], inputSize))
+                  .sub(Pr(Array.from(Array(batchSize), function (_, batchIdx) {
                   return createInterleavedTensor(getPaddingX(batchIdx), getPaddingY(batchIdx));
               })))
-                  .div(Tr(Array.from(Array(batchSize), function (_, batchIdx) {
+                  .div(Pr(Array.from(Array(batchSize), function (_, batchIdx) {
                   return createInterleavedTensor(inputDimensions[batchIdx].width, inputDimensions[batchIdx].height);
               })));
               return landmarkTensors;
@@ -3158,7 +3164,7 @@
       };
       FaceLandmark68NetBase.prototype.forwardInput = function (input) {
           var _this = this;
-          return Ke(function () {
+          return Ze(function () {
               var out = _this.runNet(input);
               return _this.postProcess(out, input.inputSize, input.inputDimensions.map(function (_a) {
                   var height = _a[0], width = _a[1];
@@ -3188,7 +3194,7 @@
                       case 0: return [4 /*yield*/, toNetInput(input)];
                       case 1:
                           netInput = _a.sent();
-                          landmarkTensors = Ke(function () { return _r(_this.forwardInput(netInput)); });
+                          landmarkTensors = Ze(function () { return Ur(_this.forwardInput(netInput)); });
                           return [4 /*yield*/, Promise.all(landmarkTensors.map(function (landmarkTensor, batchIdx) { return __awaiter(_this, void 0, void 0, function () {
                                   var landmarksArray, _a, _b, xCoords, yCoords;
                                   return __generator(this, function (_c) {
@@ -3276,14 +3282,14 @@
           if (!params) {
               throw new Error('TinyFaceFeatureExtractor - load model before inference');
           }
-          return Ke(function () {
+          return Ze(function () {
               var batchTensor = input.toBatchTensor(112, true);
               var meanRgb = [122.782, 117.001, 104.298];
-              var normalized = normalize(batchTensor, meanRgb).div(Sn(255));
+              var normalized = normalize(batchTensor, meanRgb).div(On(255));
               var out = denseBlock3(normalized, params.dense0, true);
               out = denseBlock3(out, params.dense1);
               out = denseBlock3(out, params.dense2);
-              out = $c(out, [14, 14], [2, 2], 'valid');
+              out = fl(out, [14, 14], [2, 2], 'valid');
               return out;
           });
       };
@@ -3336,16 +3342,16 @@
   }(FaceLandmark68Net));
 
   function scale(x, params) {
-      return Ws(Zs(x, params.weights), params.biases);
+      return rc(gc(x, params.weights), params.biases);
   }
 
   function convLayer$1(x, params, strides, withRelu, padding) {
       if (padding === void 0) { padding = 'same'; }
       var _a = params.conv, filters = _a.filters, bias = _a.bias;
-      var out = Ac(x, filters, strides, padding);
-      out = Ws(out, bias);
+      var out = qc(x, filters, strides, padding);
+      out = rc(out, bias);
       out = scale(out, params.scale);
-      return withRelu ? xl(out) : out;
+      return withRelu ? Bl(out) : out;
   }
   function conv$1(x, params) {
       return convLayer$1(x, params, [1, 1], true);
@@ -3364,17 +3370,17 @@
           if (isFloat(depth)) {
               throw new Error("depth has to be an integer: " + depth + ", weights.length: " + weights.length + ", numFilters: " + numFilters + ", filterSize: " + filterSize);
           }
-          return Ke(function () { return Cl(Nn(weights, [numFilters, depth, filterSize, filterSize]), [2, 3, 1, 0]); });
+          return Ze(function () { return Wl(Ln(weights, [numFilters, depth, filterSize, filterSize]), [2, 3, 1, 0]); });
       }
       function extractConvParams(numFilterValues, numFilters, filterSize, mappedPrefix) {
           var filters = extractFilterValues(numFilterValues, numFilters, filterSize);
-          var bias = An(extractWeights(numFilters));
+          var bias = Mn(extractWeights(numFilters));
           paramMappings.push({ paramPath: mappedPrefix + "/filters" }, { paramPath: mappedPrefix + "/bias" });
           return { filters: filters, bias: bias };
       }
       function extractScaleLayerParams(numWeights, mappedPrefix) {
-          var weights = An(extractWeights(numWeights));
-          var biases = An(extractWeights(numWeights));
+          var weights = Mn(extractWeights(numWeights));
+          var biases = Mn(extractWeights(numWeights));
           paramMappings.push({ paramPath: mappedPrefix + "/weights" }, { paramPath: mappedPrefix + "/biases" });
           return {
               weights: weights,
@@ -3416,7 +3422,7 @@
       var conv256_1 = extractResidualLayerParams(589824, 256, 3, 'conv256_1');
       var conv256_2 = extractResidualLayerParams(589824, 256, 3, 'conv256_2');
       var conv256_down_out = extractResidualLayerParams(589824, 256, 3, 'conv256_down_out');
-      var fc = Ke(function () { return Cl(Dn(extractWeights(256 * 128), [128, 256]), [1, 0]); });
+      var fc = Ze(function () { return Wl(Bn(extractWeights(256 * 128), [128, 256]), [1, 0]); });
       paramMappings.push({ paramPath: "fc" });
       if (getRemainingWeights().length !== 0) {
           throw new Error("weights remaing after extract: " + getRemainingWeights().length);
@@ -3514,30 +3520,30 @@
   function residual(x, params) {
       var out = conv$1(x, params.conv1);
       out = convNoRelu(out, params.conv2);
-      out = Ws(out, x);
-      out = xl(out);
+      out = rc(out, x);
+      out = Bl(out);
       return out;
   }
   function residualDown(x, params) {
       var out = convDown(x, params.conv1);
       out = convNoRelu(out, params.conv2);
-      var pooled = $c(x, 2, 2, 'valid');
-      var zeros = Bn(pooled.shape);
+      var pooled = fl(x, 2, 2, 'valid');
+      var zeros = Gn(pooled.shape);
       var isPad = pooled.shape[3] !== out.shape[3];
       var isAdjustShape = pooled.shape[1] !== out.shape[1] || pooled.shape[2] !== out.shape[2];
       if (isAdjustShape) {
           var padShapeX = __spreadArrays(out.shape);
           padShapeX[1] = 1;
-          var zerosW = Bn(padShapeX);
-          out = zn([out, zerosW], 1);
+          var zerosW = Gn(padShapeX);
+          out = Yn([out, zerosW], 1);
           var padShapeY = __spreadArrays(out.shape);
           padShapeY[2] = 1;
-          var zerosH = Bn(padShapeY);
-          out = zn([out, zerosH], 2);
+          var zerosH = Gn(padShapeY);
+          out = Yn([out, zerosH], 2);
       }
-      pooled = isPad ? zn([pooled, zeros], 3) : pooled;
-      out = Ws(pooled, out);
-      out = xl(out);
+      pooled = isPad ? Yn([pooled, zeros], 3) : pooled;
+      out = rc(pooled, out);
+      out = Bl(out);
       return out;
   }
 
@@ -3551,12 +3557,12 @@
           if (!params) {
               throw new Error('FaceRecognitionNet - load model before inference');
           }
-          return Ke(function () {
+          return Ze(function () {
               var batchTensor = input.toBatchTensor(150, true).toFloat();
               var meanRgb = [122.782, 117.001, 104.298];
-              var normalized = normalize(batchTensor, meanRgb).div(Sn(256));
+              var normalized = normalize(batchTensor, meanRgb).div(On(256));
               var out = convDown(normalized, params.conv32_down);
-              out = Xc(out, 3, 2, 'valid');
+              out = hl(out, 3, 2, 'valid');
               out = residual(out, params.conv32_1);
               out = residual(out, params.conv32_2);
               out = residual(out, params.conv32_3);
@@ -3572,7 +3578,7 @@
               out = residual(out, params.conv256_2);
               out = residualDown(out, params.conv256_down_out);
               var globalAvg = out.mean([1, 2]);
-              var fullyConnected = Lc(globalAvg, params.fc);
+              var fullyConnected = el(globalAvg, params.fc);
               return fullyConnected;
           });
       };
@@ -3598,7 +3604,7 @@
                       case 0: return [4 /*yield*/, toNetInput(input)];
                       case 1:
                           netInput = _a.sent();
-                          faceDescriptorTensors = Ke(function () { return _r(_this.forwardInput(netInput)); });
+                          faceDescriptorTensors = Ze(function () { return Ur(_this.forwardInput(netInput)); });
                           return [4 /*yield*/, Promise.all(faceDescriptorTensors.map(function (t) { return t.data(); }))];
                       case 2:
                           faceDescriptorsForBatch = _a.sent();
@@ -3708,11 +3714,11 @@
 
   function extractorsFactory$4(extractWeights, paramMappings) {
       function extractDepthwiseConvParams(numChannels, mappedPrefix) {
-          var filters = Nn(extractWeights(3 * 3 * numChannels), [3, 3, numChannels, 1]);
-          var batch_norm_scale = An(extractWeights(numChannels));
-          var batch_norm_offset = An(extractWeights(numChannels));
-          var batch_norm_mean = An(extractWeights(numChannels));
-          var batch_norm_variance = An(extractWeights(numChannels));
+          var filters = Ln(extractWeights(3 * 3 * numChannels), [3, 3, numChannels, 1]);
+          var batch_norm_scale = Mn(extractWeights(numChannels));
+          var batch_norm_offset = Mn(extractWeights(numChannels));
+          var batch_norm_mean = Mn(extractWeights(numChannels));
+          var batch_norm_variance = Mn(extractWeights(numChannels));
           paramMappings.push({ paramPath: mappedPrefix + "/filters" }, { paramPath: mappedPrefix + "/batch_norm_scale" }, { paramPath: mappedPrefix + "/batch_norm_offset" }, { paramPath: mappedPrefix + "/batch_norm_mean" }, { paramPath: mappedPrefix + "/batch_norm_variance" });
           return {
               filters: filters,
@@ -3723,8 +3729,8 @@
           };
       }
       function extractConvParams(channelsIn, channelsOut, filterSize, mappedPrefix, isPointwiseConv) {
-          var filters = Nn(extractWeights(channelsIn * channelsOut * filterSize * filterSize), [filterSize, filterSize, channelsIn, channelsOut]);
-          var bias = An(extractWeights(channelsOut));
+          var filters = Ln(extractWeights(channelsIn * channelsOut * filterSize * filterSize), [filterSize, filterSize, channelsIn, channelsOut]);
+          var bias = Mn(extractWeights(channelsOut));
           paramMappings.push({ paramPath: mappedPrefix + "/filters" }, { paramPath: mappedPrefix + "/" + (isPointwiseConv ? 'batch_norm_offset' : 'bias') });
           return { filters: filters, bias: bias };
       }
@@ -3845,7 +3851,7 @@
       var _b = extractorsFactory$4(extractWeights, paramMappings), extractMobilenetV1Params = _b.extractMobilenetV1Params, extractPredictionLayerParams = _b.extractPredictionLayerParams;
       var mobilenetv1 = extractMobilenetV1Params();
       var prediction_layer = extractPredictionLayerParams();
-      var extra_dim = Tn(extractWeights(5118 * 4), [1, 5118, 4]);
+      var extra_dim = Pn(extractWeights(5118 * 4), [1, 5118, 4]);
       var output_layer = {
           extra_dim: extra_dim
       };
@@ -3962,26 +3968,26 @@
   }
 
   function pointwiseConvLayer(x, params, strides) {
-      return Ke(function () {
-          var out = Ac(x, params.filters, strides, 'same');
-          out = Ws(out, params.batch_norm_offset);
-          return ju(out, 0, 6);
+      return Ze(function () {
+          var out = qc(x, params.filters, strides, 'same');
+          out = rc(out, params.batch_norm_offset);
+          return hu(out, 0, 6);
       });
   }
 
   var epsilon = 0.0010000000474974513;
   function depthwiseConvLayer(x, params, strides) {
-      return Ke(function () {
-          var out = Fc(x, params.filters, strides, 'same');
-          out = Ds(out, params.batch_norm_mean, params.batch_norm_variance, params.batch_norm_offset, params.batch_norm_scale, epsilon);
-          return ju(out, 0, 6);
+      return Ze(function () {
+          var out = Yc(x, params.filters, strides, 'same');
+          out = ju(out, params.batch_norm_mean, params.batch_norm_variance, params.batch_norm_offset, params.batch_norm_scale, epsilon);
+          return hu(out, 0, 6);
       });
   }
   function getStridesForLayerIdx(layerIdx) {
       return [2, 4, 6, 12].some(function (idx) { return idx === layerIdx; }) ? [2, 2] : [1, 1];
   }
   function mobileNetV1(x, params) {
-      return Ke(function () {
+      return Ze(function () {
           var conv11 = null;
           var out = pointwiseConvLayer(x, params.conv_0, [2, 2]);
           var convPairParams = [
@@ -4073,14 +4079,14 @@
   }
 
   function getCenterCoordinatesAndSizesLayer(x) {
-      var vec = _r(Cl(x, [1, 0]));
+      var vec = Ur(Wl(x, [1, 0]));
       var sizes = [
-          ac(vec[2], vec[0]),
-          ac(vec[3], vec[1])
+          Cc(vec[2], vec[0]),
+          Cc(vec[3], vec[1])
       ];
       var centers = [
-          Ws(vec[0], Gs(sizes[0], Sn(2))),
-          Ws(vec[1], Gs(sizes[1], Sn(2)))
+          rc(vec[0], sc(sizes[0], On(2))),
+          rc(vec[1], sc(sizes[1], On(2)))
       ];
       return {
           sizes: sizes,
@@ -4089,28 +4095,28 @@
   }
   function decodeBoxesLayer(x0, x1) {
       var _a = getCenterCoordinatesAndSizesLayer(x0), sizes = _a.sizes, centers = _a.centers;
-      var vec = _r(Cl(x1, [1, 0]));
-      var div0_out = Gs(Zs(Qu(Gs(vec[2], Sn(5))), sizes[0]), Sn(2));
-      var add0_out = Ws(Zs(Gs(vec[0], Sn(10)), sizes[0]), centers[0]);
-      var div1_out = Gs(Zs(Qu(Gs(vec[3], Sn(5))), sizes[1]), Sn(2));
-      var add1_out = Ws(Zs(Gs(vec[1], Sn(10)), sizes[1]), centers[1]);
-      return Cl(Tr([
-          ac(add0_out, div0_out),
-          ac(add1_out, div1_out),
-          Ws(add0_out, div0_out),
-          Ws(add1_out, div1_out)
+      var vec = Ur(Wl(x1, [1, 0]));
+      var div0_out = sc(gc(vu(sc(vec[2], On(5))), sizes[0]), On(2));
+      var add0_out = rc(gc(sc(vec[0], On(10)), sizes[0]), centers[0]);
+      var div1_out = sc(gc(vu(sc(vec[3], On(5))), sizes[1]), On(2));
+      var add1_out = rc(gc(sc(vec[1], On(10)), sizes[1]), centers[1]);
+      return Wl(Pr([
+          Cc(add0_out, div0_out),
+          Cc(add1_out, div1_out),
+          rc(add0_out, div0_out),
+          rc(add1_out, div1_out)
       ]), [1, 0]);
   }
   function outputLayer(boxPredictions, classPredictions, params) {
-      return Ke(function () {
+      return Ze(function () {
           var batchSize = boxPredictions.shape[0];
-          var boxes = decodeBoxesLayer(Sr(Nr(params.extra_dim, [batchSize, 1, 1]), [-1, 4]), Sr(boxPredictions, [-1, 4]));
-          boxes = Sr(boxes, [batchSize, (boxes.shape[0] / batchSize), 4]);
-          var scoresAndClasses = us(Zc(classPredictions, [0, 0, 1], [-1, -1, -1]));
-          var scores = Zc(scoresAndClasses, [0, 0, 0], [-1, -1, 1]);
-          scores = Sr(scores, [batchSize, scores.shape[1]]);
-          var boxesByBatch = _r(boxes);
-          var scoresByBatch = _r(scores);
+          var boxes = decodeBoxesLayer(Or(Lr(params.extra_dim, [batchSize, 1, 1]), [-1, 4]), Or(boxPredictions, [-1, 4]));
+          boxes = Or(boxes, [batchSize, (boxes.shape[0] / batchSize), 4]);
+          var scoresAndClasses = Iu(ml(classPredictions, [0, 0, 1], [-1, -1, -1]));
+          var scores = ml(scoresAndClasses, [0, 0, 0], [-1, -1, 1]);
+          scores = Or(scores, [batchSize, scores.shape[1]]);
+          var boxesByBatch = Ur(boxes);
+          var scoresByBatch = Ur(scores);
           return {
               boxes: boxesByBatch,
               scores: scoresByBatch
@@ -4119,10 +4125,10 @@
   }
 
   function boxPredictionLayer(x, params) {
-      return Ke(function () {
+      return Ze(function () {
           var batchSize = x.shape[0];
-          var boxPredictionEncoding = Sr(convLayer(x, params.box_encoding_predictor), [batchSize, -1, 1, 4]);
-          var classPrediction = Sr(convLayer(x, params.class_predictor), [batchSize, -1, 3]);
+          var boxPredictionEncoding = Or(convLayer(x, params.box_encoding_predictor), [batchSize, -1, 1, 4]);
+          var classPrediction = Or(convLayer(x, params.class_predictor), [batchSize, -1, 3]);
           return {
               boxPredictionEncoding: boxPredictionEncoding,
               classPrediction: classPrediction
@@ -4131,7 +4137,7 @@
   }
 
   function predictionLayer(x, conv11, params) {
-      return Ke(function () {
+      return Ze(function () {
           var conv0 = pointwiseConvLayer(x, params.conv_0, [1, 1]);
           var conv1 = pointwiseConvLayer(conv0, params.conv_1, [2, 2]);
           var conv2 = pointwiseConvLayer(conv1, params.conv_2, [1, 1]);
@@ -4146,7 +4152,7 @@
           var boxPrediction3 = boxPredictionLayer(conv3, params.box_predictor_3);
           var boxPrediction4 = boxPredictionLayer(conv5, params.box_predictor_4);
           var boxPrediction5 = boxPredictionLayer(conv7, params.box_predictor_5);
-          var boxPredictions = zn([
+          var boxPredictions = Yn([
               boxPrediction0.boxPredictionEncoding,
               boxPrediction1.boxPredictionEncoding,
               boxPrediction2.boxPredictionEncoding,
@@ -4154,7 +4160,7 @@
               boxPrediction4.boxPredictionEncoding,
               boxPrediction5.boxPredictionEncoding
           ], 1);
-          var classPredictions = zn([
+          var classPredictions = Yn([
               boxPrediction0.classPrediction,
               boxPrediction1.classPrediction,
               boxPrediction2.classPrediction,
@@ -4205,9 +4211,9 @@
           if (!params) {
               throw new Error('SsdMobilenetv1 - load model before inference');
           }
-          return Ke(function () {
+          return Ze(function () {
               var batchTensor = input.toBatchTensor(512, false).toFloat();
-              var x = ac(Zs(batchTensor, Sn(0.007843137718737125)), Sn(1));
+              var x = Cc(gc(batchTensor, On(0.007843137718737125)), On(1));
               var features = mobileNetV1(x, params.mobilenetv1);
               var _a = predictionLayer(features.out, features.conv11, params.prediction_layer), boxPredictions = _a.boxPredictions, classPredictions = _a.classPredictions;
               return outputLayer(boxPredictions, classPredictions, params.output_layer);
@@ -4354,29 +4360,29 @@
   }
 
   function leaky(x) {
-      return Ke(function () {
-          var min = Zs(x, Sn(0.10000000149011612));
-          return Ws(xl(ac(x, min)), min);
+      return Ze(function () {
+          var min = gc(x, On(0.10000000149011612));
+          return rc(Bl(Cc(x, min)), min);
           //return tf.maximum(x, min)
       });
   }
 
   function convWithBatchNorm(x, params) {
-      return Ke(function () {
-          var out = yr(x, [[0, 0], [1, 1], [1, 1], [0, 0]]);
-          out = Ac(out, params.conv.filters, [1, 1], 'valid');
-          out = ac(out, params.bn.sub);
-          out = Zs(out, params.bn.truediv);
-          out = Ws(out, params.conv.bias);
+      return Ze(function () {
+          var out = Ir(x, [[0, 0], [1, 1], [1, 1], [0, 0]]);
+          out = qc(out, params.conv.filters, [1, 1], 'valid');
+          out = Cc(out, params.bn.sub);
+          out = gc(out, params.bn.truediv);
+          out = rc(out, params.conv.bias);
           return leaky(out);
       });
   }
 
   function depthwiseSeparableConv$1(x, params) {
-      return Ke(function () {
-          var out = yr(x, [[0, 0], [1, 1], [1, 1], [0, 0]]);
-          out = Mc(out, params.depthwise_filter, params.pointwise_filter, [1, 1], 'valid');
-          out = Ws(out, params.bias);
+      return Ze(function () {
+          var out = Ir(x, [[0, 0], [1, 1], [1, 1], [0, 0]]);
+          out = Jc(out, params.depthwise_filter, params.pointwise_filter, [1, 1], 'valid');
+          out = rc(out, params.bias);
           return leaky(out);
       });
   }
@@ -4384,8 +4390,8 @@
   function extractorsFactory$6(extractWeights, paramMappings) {
       var extractConvParams = extractConvParamsFactory(extractWeights, paramMappings);
       function extractBatchNormParams(size, mappedPrefix) {
-          var sub = An(extractWeights(size));
-          var truediv = An(extractWeights(size));
+          var sub = Mn(extractWeights(size));
+          var truediv = Mn(extractWeights(size));
           paramMappings.push({ paramPath: mappedPrefix + "/sub" }, { paramPath: mappedPrefix + "/truediv" });
           return { sub: sub, truediv: truediv };
       }
@@ -4562,17 +4568,17 @@
       });
       TinyYolov2Base.prototype.runTinyYolov2 = function (x, params) {
           var out = convWithBatchNorm(x, params.conv0);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = convWithBatchNorm(out, params.conv1);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = convWithBatchNorm(out, params.conv2);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = convWithBatchNorm(out, params.conv3);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = convWithBatchNorm(out, params.conv4);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = convWithBatchNorm(out, params.conv5);
-          out = Xc(out, [2, 2], [1, 1], 'same');
+          out = hl(out, [2, 2], [1, 1], 'same');
           out = convWithBatchNorm(out, params.conv6);
           out = convWithBatchNorm(out, params.conv7);
           return convLayer(out, params.conv8, 'valid', false);
@@ -4581,17 +4587,17 @@
           var out = this.config.isFirstLayerConv2d
               ? leaky(convLayer(x, params.conv0, 'valid', false))
               : depthwiseSeparableConv$1(x, params.conv0);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = depthwiseSeparableConv$1(out, params.conv1);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = depthwiseSeparableConv$1(out, params.conv2);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = depthwiseSeparableConv$1(out, params.conv3);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = depthwiseSeparableConv$1(out, params.conv4);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = depthwiseSeparableConv$1(out, params.conv5);
-          out = Xc(out, [2, 2], [1, 1], 'same');
+          out = hl(out, [2, 2], [1, 1], 'same');
           out = params.conv6 ? depthwiseSeparableConv$1(out, params.conv6) : out;
           out = params.conv7 ? depthwiseSeparableConv$1(out, params.conv7) : out;
           return convLayer(out, params.conv8, 'valid', false);
@@ -4602,12 +4608,12 @@
           if (!params) {
               throw new Error('TinyYolov2 - load model before inference');
           }
-          return Ke(function () {
+          return Ze(function () {
               var batchTensor = input.toBatchTensor(inputSize, false).toFloat();
               batchTensor = _this.config.meanRgb
                   ? normalize(batchTensor, _this.config.meanRgb)
                   : batchTensor;
-              batchTensor = batchTensor.div(Sn(256));
+              batchTensor = batchTensor.div(On(256));
               return _this.config.withSeparableConvs
                   ? _this.runMobilenet(batchTensor, params)
                   : _this.runTinyYolov2(batchTensor, params);
@@ -4642,7 +4648,7 @@
                           return [4 /*yield*/, this.forwardInput(netInput, inputSize)];
                       case 2:
                           out = _b.sent();
-                          out0 = Ke(function () { return _r(out)[0].expandDims(); });
+                          out0 = Ze(function () { return Ur(out)[0].expandDims(); });
                           inputDimensions = {
                               width: netInput.getInputWidth(0),
                               height: netInput.getInputHeight(0)
@@ -4692,13 +4698,13 @@
                           correctionFactorY = inputSize / height;
                           numCells = outputTensor.shape[1];
                           numBoxes = this.config.anchors.length;
-                          _a = Ke(function () {
+                          _a = Ze(function () {
                               var reshaped = outputTensor.reshape([numCells, numCells, numBoxes, _this.boxEncodingSize]);
                               var boxes = reshaped.slice([0, 0, 0, 0], [numCells, numCells, numBoxes, 4]);
                               var scores = reshaped.slice([0, 0, 0, 4], [numCells, numCells, numBoxes, 1]);
                               var classScores = _this.withClassScores
-                                  ? io(reshaped.slice([0, 0, 0, 5], [numCells, numCells, numBoxes, _this.config.classes.length]), 3)
-                                  : Sn(0);
+                                  ? go(reshaped.slice([0, 0, 0, 5], [numCells, numCells, numBoxes, _this.config.classes.length]), 3)
+                                  : On(0);
                               return [boxes, scores, classScores];
                           }), boxesTensor = _a[0], scoresTensor = _a[1], classScoresTensor = _a[2];
                           results = [];
@@ -4903,7 +4909,7 @@
                       });
                       _a = extractedFaces;
                       if (_a) return [3 /*break*/, 5];
-                      if (!(input instanceof dt)) return [3 /*break*/, 2];
+                      if (!(input instanceof wt)) return [3 /*break*/, 2];
                       return [4 /*yield*/, extractFaceTensors(input, faceBoxes)];
                   case 1:
                       _b = _c.sent();
@@ -4920,7 +4926,7 @@
                       return [4 /*yield*/, computeResults(faces)];
                   case 6:
                       results = _c.sent();
-                      faces.forEach(function (f) { return f instanceof dt && f.dispose(); });
+                      faces.forEach(function (f) { return f instanceof wt && f.dispose(); });
                       return [2 /*return*/, results];
               }
           });
@@ -4938,7 +4944,7 @@
   }
 
   function bgrToRgbTensor(tensor) {
-      return Ke(function () { return Tr(_r(tensor, 3).reverse(), 3); });
+      return Ze(function () { return Pr(Ur(tensor, 3).reverse(), 3); });
   }
 
   var CELL_STRIDE = 2;
@@ -4948,7 +4954,7 @@
       var extractConvParams = extractConvParamsFactory(extractWeights, paramMappings);
       var extractFCParams = extractFCParamsFactory(extractWeights, paramMappings);
       function extractPReluParams(size, paramPath) {
-          var alpha = An(extractWeights(size));
+          var alpha = Mn(extractWeights(size));
           paramMappings.push({ paramPath: paramPath });
           return alpha;
       }
@@ -5102,24 +5108,24 @@
   }(Box));
 
   function normalize$1(x) {
-      return Ke(function () { return Zs(ac(x, Sn(127.5)), Sn(0.0078125)); });
+      return Ze(function () { return gc(Cc(x, On(127.5)), On(0.0078125)); });
   }
 
   function prelu(x, alpha) {
-      return Ke(function () {
-          return Ws(xl(x), Zs(alpha, rs(xl(rs(x)))));
+      return Ze(function () {
+          return rc(Bl(x), gc(alpha, wu(Bl(wu(x)))));
       });
   }
 
   function sharedLayer(x, params, isPnet) {
       if (isPnet === void 0) { isPnet = false; }
-      return Ke(function () {
+      return Ze(function () {
           var out = convLayer(x, params.conv1, 'valid');
           out = prelu(out, params.prelu1_alpha);
-          out = Xc(out, isPnet ? [2, 2] : [3, 3], [2, 2], 'same');
+          out = hl(out, isPnet ? [2, 2] : [3, 3], [2, 2], 'same');
           out = convLayer(out, params.conv2, 'valid');
           out = prelu(out, params.prelu2_alpha);
-          out = isPnet ? out : Xc(out, [3, 3], [2, 2], 'valid');
+          out = isPnet ? out : hl(out, [3, 3], [2, 2], 'valid');
           out = convLayer(out, params.conv3, 'valid');
           out = prelu(out, params.prelu3_alpha);
           return out;
@@ -5127,22 +5133,22 @@
   }
 
   function PNet(x, params) {
-      return Ke(function () {
+      return Ze(function () {
           var out = sharedLayer(x, params, true);
           var conv = convLayer(out, params.conv4_1, 'valid');
-          var max = dr(ll(conv, 3), 3);
-          var prob = io(ac(conv, max), 3);
+          var max = wr(Sl(conv, 3), 3);
+          var prob = go(Cc(conv, max), 3);
           var regions = convLayer(out, params.conv4_2, 'valid');
           return { prob: prob, regions: regions };
       });
   }
 
   function rescaleAndNormalize(x, scale) {
-      return Ke(function () {
+      return Ze(function () {
           var _a = getSizesForScale(scale, x.shape.slice(1)), height = _a.height, width = _a.width;
-          var resized = vh.resizeBilinear(x, [height, width]);
+          var resized = Oh.resizeBilinear(x, [height, width]);
           var normalized = normalize$1(resized);
-          return Cl(normalized, [0, 2, 1, 3]);
+          return Wl(normalized, [0, 2, 1, 3]);
       });
   }
   function extractBoundingBoxes(scoresTensor, regionsTensor, scale, scoreThreshold) {
@@ -5171,14 +5177,14 @@
   }
   function stage1(imgTensor, scales, scoreThreshold, params, stats) {
       stats.stage1 = [];
-      var pnetOutputs = scales.map(function (scale) { return Ke(function () {
+      var pnetOutputs = scales.map(function (scale) { return Ze(function () {
           var statsForScale = { scale: scale };
           var resized = rescaleAndNormalize(imgTensor, scale);
           var ts = Date.now();
           var _a = PNet(resized, params), prob = _a.prob, regions = _a.regions;
           statsForScale.pnet = Date.now() - ts;
-          var scoresTensor = _r(_r(prob, 3)[1])[0];
-          var regionsTensor = _r(regions)[0];
+          var scoresTensor = Ur(Ur(prob, 3)[1])[0];
+          var regionsTensor = Ur(regions)[0];
           return {
               scoresTensor: scoresTensor,
               regionsTensor: regionsTensor,
@@ -5260,8 +5266,8 @@
                           imagePatchesDatas.push(currData);
                       });
                       return [2 /*return*/, imagePatchesDatas.map(function (data) {
-                              var t = Ke(function () {
-                                  var imagePatchTensor = Cl(Nn(data, [1, width, height, 3]), [0, 2, 1, 3]).toFloat();
+                              var t = Ze(function () {
+                                  var imagePatchTensor = Wl(Ln(data, [1, width, height, 3]), [0, 2, 1, 3]).toFloat();
                                   return normalize$1(imagePatchTensor);
                               });
                               return t;
@@ -5272,16 +5278,16 @@
   }
 
   function RNet(x, params) {
-      return Ke(function () {
+      return Ze(function () {
           var convOut = sharedLayer(x, params);
-          var vectorized = Sr(convOut, [convOut.shape[0], params.fc1.weights.shape[0]]);
+          var vectorized = Or(convOut, [convOut.shape[0], params.fc1.weights.shape[0]]);
           var fc1 = fullyConnectedLayer(vectorized, params.fc1);
           var prelu4 = prelu(fc1, params.prelu4_alpha);
           var fc2_1 = fullyConnectedLayer(prelu4, params.fc2_1);
-          var max = dr(ll(fc2_1, 1), 1);
-          var prob = io(ac(fc2_1, max), 1);
+          var max = wr(Sl(fc2_1, 1), 1);
+          var prob = go(Cc(fc2_1, max), 1);
           var regions = fullyConnectedLayer(prelu4, params.fc2_2);
-          var scores = _r(prob, 1)[1];
+          var scores = Ur(prob, 1)[1];
           return { scores: scores, regions: regions };
       });
   }
@@ -5305,7 +5311,7 @@
                       });
                       stats.stage2_rnet = Date.now() - ts;
                       scoresTensor = rnetOuts.length > 1
-                          ? zn(rnetOuts.map(function (out) { return out.scores; }))
+                          ? Yn(rnetOuts.map(function (out) { return out.scores; }))
                           : rnetOuts[0].scores;
                       _b = (_a = Array).from;
                       return [4 /*yield*/, scoresTensor.data()];
@@ -5348,20 +5354,20 @@
   }
 
   function ONet(x, params) {
-      return Ke(function () {
+      return Ze(function () {
           var out = sharedLayer(x, params);
-          out = Xc(out, [2, 2], [2, 2], 'same');
+          out = hl(out, [2, 2], [2, 2], 'same');
           out = convLayer(out, params.conv4, 'valid');
           out = prelu(out, params.prelu4_alpha);
-          var vectorized = Sr(out, [out.shape[0], params.fc1.weights.shape[0]]);
+          var vectorized = Or(out, [out.shape[0], params.fc1.weights.shape[0]]);
           var fc1 = fullyConnectedLayer(vectorized, params.fc1);
           var prelu5 = prelu(fc1, params.prelu5_alpha);
           var fc2_1 = fullyConnectedLayer(prelu5, params.fc2_1);
-          var max = dr(ll(fc2_1, 1), 1);
-          var prob = io(ac(fc2_1, max), 1);
+          var max = wr(Sl(fc2_1, 1), 1);
+          var prob = go(Cc(fc2_1, max), 1);
           var regions = fullyConnectedLayer(prelu5, params.fc2_2);
           var points = fullyConnectedLayer(prelu5, params.fc2_3);
-          var scores = _r(prob, 1)[1];
+          var scores = Ur(prob, 1)[1];
           return { scores: scores, regions: regions, points: points };
       });
   }
@@ -5385,7 +5391,7 @@
                       });
                       stats.stage3_onet = Date.now() - ts;
                       scoresTensor = onetOuts.length > 1
-                          ? zn(onetOuts.map(function (out) { return out.scores; }))
+                          ? Yn(onetOuts.map(function (out) { return out.scores; }))
                           : onetOuts[0].scores;
                       _b = (_a = Array).from;
                       return [4 /*yield*/, scoresTensor.data()];
@@ -5475,8 +5481,8 @@
                           }
                           stats = {};
                           tsTotal = Date.now();
-                          imgTensor = Ke(function () {
-                              return bgrToRgbTensor(dr(Mf.fromPixels(inputCanvas)).toFloat());
+                          imgTensor = Ze(function () {
+                              return bgrToRgbTensor(wr(id.fromPixels(inputCanvas)).toFloat());
                           });
                           onReturn = function (results) {
                               // dispose tensors on return
@@ -6061,7 +6067,7 @@
                       case 1:
                           parentResults = _b.sent();
                           detections = parentResults.map(function (res) { return res.detection; });
-                          if (!(this.input instanceof dt)) return [3 /*break*/, 3];
+                          if (!(this.input instanceof wt)) return [3 /*break*/, 3];
                           return [4 /*yield*/, extractFaceTensors(this.input, detections)];
                       case 2:
                           _a = _b.sent();
@@ -6075,7 +6081,7 @@
                           return [4 /*yield*/, Promise.all(faces.map(function (face) { return _this.landmarkNet.detectLandmarks(face); }))];
                       case 6:
                           faceLandmarksByFace = _b.sent();
-                          faces.forEach(function (f) { return f instanceof dt && f.dispose(); });
+                          faces.forEach(function (f) { return f instanceof wt && f.dispose(); });
                           return [2 /*return*/, parentResults.map(function (parentResult, i) {
                                   return extendWithFaceLandmarks(parentResult, faceLandmarksByFace[i]);
                               })];
@@ -6111,7 +6117,7 @@
                               return [2 /*return*/];
                           }
                           detection = parentResult.detection;
-                          if (!(this.input instanceof dt)) return [3 /*break*/, 3];
+                          if (!(this.input instanceof wt)) return [3 /*break*/, 3];
                           return [4 /*yield*/, extractFaceTensors(this.input, [detection])];
                       case 2:
                           _a = _b.sent();
@@ -6125,7 +6131,7 @@
                           return [4 /*yield*/, this.landmarkNet.detectLandmarks(faces[0])];
                       case 6:
                           landmarks = _b.sent();
-                          faces.forEach(function (f) { return f instanceof dt && f.dispose(); });
+                          faces.forEach(function (f) { return f instanceof wt && f.dispose(); });
                           return [2 /*return*/, extendWithFaceLandmarks(parentResult, landmarks)];
                   }
               });
diff --git a/dist/face-api.js.map b/dist/face-api.js.map
index a88b87b3..e1dea86e 100644
--- a/dist/face-api.js.map
+++ b/dist/face-api.js.map
@@ -1 +1 @@
-{"version":3,"file":"face-api.js","sources":["../node_modules/@tensorflow/tfjs-core/dist/tf-core.esm.js","../src/draw/drawContour.ts","../src/classes/Dimensions.ts","../src/utils/index.ts","../src/classes/Point.ts","../src/classes/Box.ts","../src/classes/BoundingBox.ts","../src/classes/ObjectDetection.ts","../src/classes/FaceDetection.ts","../src/ops/iou.ts","../src/ops/minBbox.ts","../src/ops/nonMaxSuppression.ts","../src/ops/normalize.ts","../src/ops/padToSquare.ts","../src/ops/shuffleArray.ts","../src/ops/index.ts","../src/classes/Rect.ts","../src/classes/FaceLandmarks.ts","../src/classes/FaceLandmarks5.ts","../src/classes/FaceLandmarks68.ts","../src/classes/FaceMatch.ts","../src/classes/LabeledBox.ts","../src/classes/LabeledFaceDescriptors.ts","../src/classes/PredictedBox.ts","../src/factories/WithFaceDetection.ts","../src/env/createBrowserEnv.ts","../src/env/createFileSystem.ts","../src/env/createNodejsEnv.ts","../src/env/isBrowser.ts","../src/env/isNodejs.ts","../src/env/index.ts","../src/dom/resolveInput.ts","../src/dom/getContext2dOrThrow.ts","../src/draw/DrawTextField.ts","../src/draw/DrawBox.ts","../src/draw/drawDetections.ts","../src/dom/isMediaLoaded.ts","../src/dom/awaitMediaLoaded.ts","../src/dom/bufferToImage.ts","../src/dom/getMediaDimensions.ts","../src/dom/createCanvas.ts","../src/dom/imageTensorToCanvas.ts","../src/dom/isMediaElement.ts","../src/dom/imageToSquare.ts","../src/dom/NetInput.ts","../src/dom/toNetInput.ts","../src/dom/extractFaces.ts","../src/dom/extractFaceTensors.ts","../src/dom/fetchOrThrow.ts","../src/dom/fetchImage.ts","../src/dom/fetchJson.ts","../src/dom/fetchNetWeights.ts","../src/common/getModelUris.ts","../src/dom/loadWeightMap.ts","../src/dom/matchDimensions.ts","../src/NeuralNetwork.ts","../src/common/depthwiseSeparableConv.ts","../src/faceFeatureExtractor/denseBlock.ts","../src/common/convLayer.ts","../src/common/disposeUnusedWeightTensors.ts","../src/common/extractConvParamsFactory.ts","../src/common/extractFCParamsFactory.ts","../src/common/types.ts","../src/common/extractSeparableConvParamsFactory.ts","../src/common/extractWeightEntryFactory.ts","../src/common/extractWeightsFactory.ts","../src/faceFeatureExtractor/extractorsFactory.ts","../src/faceFeatureExtractor/extractParams.ts","../src/common/loadConvParamsFactory.ts","../src/faceFeatureExtractor/loadParamsFactory.ts","../src/faceFeatureExtractor/extractParamsFromWeigthMap.ts","../src/faceFeatureExtractor/FaceFeatureExtractor.ts","../src/common/fullyConnectedLayer.ts","../src/faceProcessor/extractParams.ts","../src/faceProcessor/extractParamsFromWeigthMap.ts","../src/faceProcessor/util.ts","../src/faceProcessor/FaceProcessor.ts","../src/faceExpressionNet/FaceExpressions.ts","../src/faceExpressionNet/FaceExpressionNet.ts","../src/factories/WithFaceExpressions.ts","../src/draw/drawFaceExpressions.ts","../src/factories/WithFaceLandmarks.ts","../src/draw/DrawFaceLandmarks.ts","../src/xception/extractParams.ts","../src/xception/extractParamsFromWeigthMap.ts","../src/xception/TinyXception.ts","../src/ageGenderNet/extractParams.ts","../src/ageGenderNet/extractParamsFromWeigthMap.ts","../src/ageGenderNet/types.ts","../src/ageGenderNet/AgeGenderNet.ts","../src/faceLandmarkNet/FaceLandmark68NetBase.ts","../src/faceLandmarkNet/FaceLandmark68Net.ts","../src/faceFeatureExtractor/extractParamsFromWeigthMapTiny.ts","../src/faceFeatureExtractor/extractParamsTiny.ts","../src/faceFeatureExtractor/TinyFaceFeatureExtractor.ts","../src/faceLandmarkNet/FaceLandmark68TinyNet.ts","../src/faceLandmarkNet/index.ts","../src/faceRecognitionNet/scaleLayer.ts","../src/faceRecognitionNet/convLayer.ts","../src/faceRecognitionNet/extractParams.ts","../src/faceRecognitionNet/extractParamsFromWeigthMap.ts","../src/faceRecognitionNet/residualLayer.ts","../src/faceRecognitionNet/FaceRecognitionNet.ts","../src/faceRecognitionNet/index.ts","../src/factories/WithFaceDescriptor.ts","../src/factories/WithAge.ts","../src/factories/WithGender.ts","../src/mtcnn/MtcnnOptions.ts","../src/ssdMobilenetv1/extractParams.ts","../src/ssdMobilenetv1/extractParamsFromWeigthMap.ts","../src/ssdMobilenetv1/pointwiseConvLayer.ts","../src/ssdMobilenetv1/mobileNetV1.ts","../src/ssdMobilenetv1/nonMaxSuppression.ts","../src/ssdMobilenetv1/outputLayer.ts","../src/ssdMobilenetv1/boxPredictionLayer.ts","../src/ssdMobilenetv1/predictionLayer.ts","../src/ssdMobilenetv1/SsdMobilenetv1Options.ts","../src/ssdMobilenetv1/SsdMobilenetv1.ts","../src/ssdMobilenetv1/index.ts","../src/tinyYolov2/const.ts","../src/tinyYolov2/config.ts","../src/tinyYolov2/leaky.ts","../src/tinyYolov2/convWithBatchNorm.ts","../src/tinyYolov2/depthwiseSeparableConv.ts","../src/tinyYolov2/extractParams.ts","../src/tinyYolov2/extractParamsFromWeigthMap.ts","../src/tinyYolov2/TinyYolov2Options.ts","../src/tinyYolov2/TinyYolov2Base.ts","../src/tinyYolov2/TinyYolov2.ts","../src/tinyYolov2/index.ts","../src/tinyFaceDetector/TinyFaceDetectorOptions.ts","../src/globalApi/ComposableTask.ts","../src/globalApi/extractFacesAndComputeResults.ts","../src/mtcnn/bgrToRgbTensor.ts","../src/mtcnn/config.ts","../src/mtcnn/extractParams.ts","../src/mtcnn/extractParamsFromWeigthMap.ts","../src/mtcnn/getSizesForScale.ts","../src/mtcnn/pyramidDown.ts","../src/mtcnn/MtcnnBox.ts","../src/mtcnn/normalize.ts","../src/mtcnn/prelu.ts","../src/mtcnn/sharedLayers.ts","../src/mtcnn/PNet.ts","../src/mtcnn/stage1.ts","../src/mtcnn/extractImagePatches.ts","../src/mtcnn/RNet.ts","../src/mtcnn/stage2.ts","../src/mtcnn/ONet.ts","../src/mtcnn/stage3.ts","../src/mtcnn/Mtcnn.ts","../src/tinyFaceDetector/const.ts","../src/tinyFaceDetector/TinyFaceDetector.ts","../src/globalApi/nets.ts","../src/globalApi/PredictFaceExpressionsTask.ts","../src/globalApi/PredictAgeAndGenderTask.ts","../src/globalApi/ComputeFaceDescriptorsTasks.ts","../src/globalApi/DetectFaceLandmarksTasks.ts","../src/globalApi/DetectFacesTasks.ts","../src/globalApi/detectFaces.ts","../src/globalApi/allFaces.ts","../src/euclideanDistance.ts","../src/globalApi/FaceMatcher.ts","../src/mtcnn/index.ts","../src/tinyFaceDetector/index.ts","../src/resizeResults.ts"],"sourcesContent":["/**\n * @license\n * Copyright 2019 Google LLC. 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match\");ht().disposeTensor(this),this.dataId=t.dataId,ht().incRef(this,null)},n.prototype.dispose=function(){ht().disposeVariable(this),this.isDisposedInternal=!0},n}(dt);Object.defineProperty(bt,Symbol.hasInstance,{value:function(t){return t instanceof dt&&null!=t.assign&&t.assign instanceof Function}}),function(t){t.R0=\"R0\",t.R1=\"R1\",t.R2=\"R2\",t.R3=\"R3\",t.R4=\"R4\",t.R5=\"R5\",t.R6=\"R6\"}(vt||(vt={})),function(t){t.float32=\"float32\",t.int32=\"int32\",t.bool=\"int32\",t.complex64=\"complex64\"}(mt||(mt={})),function(t){t.float32=\"float32\",t.int32=\"int32\",t.bool=\"bool\",t.complex64=\"complex64\"}(gt||(gt={})),function(t){t.float32=\"float32\",t.int32=\"float32\",t.bool=\"float32\",t.complex64=\"complex64\"}(yt||(yt={})),function(t){t.float32=\"complex64\",t.int32=\"complex64\",t.bool=\"complex64\",t.complex64=\"complex64\"}(xt||(xt={}));var wt={float32:yt,int32:mt,bool:gt,complex64:xt};function Ct(t,e){if(\"string\"===t||\"string\"===e){if(\"string\"===t&&\"string\"===e)return\"string\";throw new Error(\"Can not upcast \"+t+\" with \"+e)}return wt[t][e]}function Et(t){return Ct(t,\"int32\")}function Rt(t,e){if(t.dtype===e.dtype)return[t,e];var n=Ct(t.dtype,e.dtype);return[t.cast(n),e.cast(n)]}function It(t,e){g(t.dtype===e.dtype,function(){return\"The dtypes of the first(\"+t.dtype+\") and second(\"+e.dtype+\") input must match\"})}function kt(t){var e=[];return function t(e,n,r){if(null==e)return;if(e instanceof dt)return void n.push(e);if(o=e,!Array.isArray(o)&&\"object\"!=typeof o)return;var o;var a=e;for(var i in a){var u=a[i];r.has(u)||(r.add(u),t(u,n,r))}}(t,e,new Set),e}var St,At=Object.freeze({makeTypesMatch:Rt,assertTypesMatch:It,isTensorInList:function(t,e){for(var n=0;n<e.length;n++)if(e[n].id===t.id)return!0;return!1},getTensorsInContainer:kt}),Dt=function(){function t(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null}}return t.prototype.dispose=function(){for(var t in this.registeredVariables)this.registeredVariables[t].dispose()},t}(),Tt=function(){function t(t){this.ENV=t,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Dt}return t.prototype.ready=function(){return n(this,void 0,void 0,function(){var t,e,n;return r(this,function(r){switch(r.label){case 0:if(null!=this.pendingBackendInit)return[2,this.pendingBackendInit.then(function(){})];if(null!=this.backendInstance)return[2];t=this.getSortedBackends(),e=0,r.label=1;case 1:return e<t.length?(n=t[e],[4,this.initializeBackend(n).success]):[3,5];case 2:return r.sent()?[4,this.setBackend(n)]:[3,4];case 3:return r.sent(),[2];case 4:return e++,[3,1];case 5:throw new Error(\"Could not initialize any backends, all backend initializations failed.\")}})})},Object.defineProperty(t.prototype,\"backend\",{get:function(){if(null!=this.pendingBackendInit)throw new Error(\"Backend '\"+this.backendName+\"' has not yet been initialized. Make sure to await tf.ready() before calling other methods\");if(null==this.backendInstance){var t=this.initializeBackendsAndReturnBest(),e=t.name;if(t.asyncInit)throw new Error(\"The highest priority backend '\"+e+\"' has not yet been initialized. Make sure to await tf.ready() before calling other methods\");this.setBackend(e)}return this.backendInstance},enumerable:!0,configurable:!0}),t.prototype.backendNames=function(){return Object.keys(this.registryFactory)},t.prototype.findBackend=function(t){if(!(t in this.registry)){if(!(t in this.registryFactory))return null;if(this.initializeBackend(t).asyncInit)return null}return this.registry[t]},t.prototype.findBackendFactory=function(t){return t in this.registryFactory?this.registryFactory[t].factory:null},t.prototype.registerBackend=function(t,e,n){return void 0===n&&(n=1),t in this.registryFactory?(console.warn(t+\" backend was already registered. Reusing existing backend factory.\"),!1):(this.registryFactory[t]={factory:e,priority:n},!0)},t.prototype.setBackend=function(t){return n(this,void 0,void 0,function(){var e,n,o;return r(this,function(r){switch(r.label){case 0:if(null==this.registryFactory[t])throw new Error(\"Backend name '\"+t+\"' not found in registry\");return this.backendName=t,null!=this.registry[t]?[3,4]:(this.backendInstance=null,e=this.initializeBackend(t),n=e.success,e.asyncInit?[4,n]:[3,2]);case 1:return o=r.sent(),[3,3];case 2:o=n,r.label=3;case 3:if(!o)return[2,!1];r.label=4;case 4:return this.backendInstance=this.registry[t],this.setupRegisteredKernels(),this.profiler=new et(this.backendInstance),[2,!0]}})})},t.prototype.setupRegisteredKernels=function(){var t=this;c(this.backendName).forEach(function(e){null!=e.setupFunc&&e.setupFunc(t.backendInstance)})},t.prototype.disposeRegisteredKernels=function(t){var e=this;c(t).forEach(function(n){null!=n.disposeFunc&&n.disposeFunc(e.registry[t])})},t.prototype.initializeBackend=function(t){var e=this,n=this.registryFactory[t];if(null==n)throw new Error(\"Cannot initialize backend \"+t+\", no registration found.\");try{var r=n.factory();if(Promise.resolve(r)===r){var o=++this.pendingBackendInitId,a=r.then(function(n){return!(o<e.pendingBackendInitId)&&(e.registry[t]=n,e.pendingBackendInit=null,!0)}).catch(function(n){return!(o<e.pendingBackendInitId)&&(e.pendingBackendInit=null,console.warn(\"Initialization of backend \"+t+\" failed\"),console.warn(n.stack||n.message),!1)});return this.pendingBackendInit=a,{success:a,asyncInit:!0}}return this.registry[t]=r,{success:!0,asyncInit:!1}}catch(e){return console.warn(\"Initialization of backend \"+t+\" failed\"),console.warn(e.stack||e.message),{success:!1,asyncInit:!1}}},t.prototype.removeBackend=function(t){if(!(t in this.registryFactory))throw new Error(t+\" backend not found in registry\");this.backendName===t&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)},t.prototype.getSortedBackends=function(){var t=this;if(0===Object.keys(this.registryFactory).length)throw new Error(\"No backend found in registry.\");return Object.keys(this.registryFactory).sort(function(e,n){return t.registryFactory[n].priority-t.registryFactory[e].priority})},t.prototype.initializeBackendsAndReturnBest=function(){for(var t=this.getSortedBackends(),e=0;e<t.length;e++){var n=t[e],r=this.initializeBackend(n),o=r.success,a=r.asyncInit;if(a||o)return{name:n,asyncInit:a}}throw new Error(\"Could not initialize any backends, all backend initializations failed.\")},t.prototype.moveData=function(t,e){var n=this.state.tensorInfo.get(e),r=n.backend,o=this.readSync(e);r.disposeData(e),n.backend=t,t.move(e,o,n.shape,n.dtype),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++},t.prototype.tidy=function(t,e){var n,r=this,o=null;if(null==e){if(\"function\"!=typeof t)throw new Error(\"Please provide a function to tidy()\");e=t}else{if(\"string\"!=typeof t&&!(t instanceof String))throw new Error(\"When calling with two arguments, the first argument to tidy() must be a string\");if(\"function\"!=typeof e)throw new Error(\"When calling with two arguments, the 2nd argument to tidy() must be a function\");o=t}return this.scopedRun(function(){return r.startScope(o)},function(){return r.endScope(n)},function(){return(n=e())instanceof Promise&&console.error(\"Cannot return a Promise inside of tidy.\"),n})},t.prototype.scopedRun=function(t,e,n){t();try{var r=n();return e(),r}catch(t){throw e(),t}},t.prototype.nextTensorId=function(){return t.nextTensorId++},t.prototype.nextVariableId=function(){return t.nextVariableId++},t.prototype.clone=function(t){var e=this.makeTensorFromDataId(t.dataId,t.shape,t.dtype),n={x:t};return this.addTapeNode(this.state.activeScope.name,n,[e],function(t){return{x:function(){return t.toFloat()}}},[]),e},t.prototype.runKernel=function(t,e,n,r,o){return this.runKernelFunc(null,e,null,t,n,r,o)},t.prototype.shouldCheckForMemLeaks=function(){return this.ENV.getBool(\"IS_TEST\")},t.prototype.checkKernelForMemLeak=function(t,e,n){var r=this.backend.numDataIds(),o=0;n.forEach(function(t){o+=\"complex64\"===t.dtype?3:1});var a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-e-o-a;if(i>0)throw new Error(\"Backend '\"+this.backendName+\"' has an internal memory leak (\"+i+\" data ids) after running '\"+t+\"'\")},t.prototype.runKernelFunc=function(t,e,n,r,o,a,i){var u,c=this;void 0===a&&(a=[]),void 0===i&&(i=[]);var l,h=[],f=this.isTapeOn(),p=null!=this.state.activeScope?this.state.activeScope.name:\"\",d=function(t){f&&(h=t.map(function(t){return c.keep(c.clone(t))}))},v=this.state.numBytes,m=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);var g,y=s(r,this.backendName);return l=null!=y?function(){var t=c.backend.numDataIds();g=y.kernelFunc({inputs:e,attrs:o,backend:c.backend});var n=Array.isArray(g)?g:[g];c.shouldCheckForMemLeaks()&&c.checkKernelForMemLeak(p,t,n);var r=n.map(function(t){var e=t.dataId,n=t.shape,r=t.dtype;return c.makeTensorFromDataId(e,n,r)}),u=r.filter(function(t,e){return i[e]});return d(a.slice().concat(u)),r}:function(){var e=c.backend.numDataIds();g=c.tidy(function(){return t(c.backend,d)});var n=Array.isArray(g)?g:[g];return c.shouldCheckForMemLeaks()&&c.checkKernelForMemLeak(p,e,n),n},this.scopedRun(function(){return c.state.kernelDepth++},function(){return c.state.kernelDepth--},function(){u=c.ENV.getBool(\"DEBUG\")?c.profiler.profileKernel(p,e,function(){return l()}):l()}),f&&this.addTapeNode(p,e,u,n,h),this.state.profiling&&this.state.activeProfile.kernels.push({name:p,bytesAdded:this.state.numBytes-v,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-m,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(e).map(function(t){return e[t].shape}),outputShapes:u.map(function(t){return t.shape})}),Array.isArray(g)?u:u[0]},t.prototype.makeTensor=function(t,e,n,r){if(null==t)throw new Error(\"Values passed to engine.makeTensor() are null\");n=n||\"float32\",r=r||this.backend;var o=t;\"string\"===n&&W(t[0])&&(o=t.map(function(t){return J(t)}));var a=r.write(o,e,n),i=new dt(e,n,a,this.nextTensorId());if(this.incRef(i,r),\"string\"===n){var u=this.state.tensorInfo.get(a),s=L(o);this.state.numBytes+=s-u.bytes,u.bytes=s}return i},t.prototype.makeTensorFromDataId=function(t,e,n,r){var o=new dt(e,n=n||\"float32\",t,this.nextTensorId());return this.incRef(o,r),o},t.prototype.makeVariable=function(t,e,n,r){void 0===e&&(e=!0),n=n||this.nextVariableId().toString(),null!=r&&r!==t.dtype&&(t=t.asType(r));var o=new bt(t,e,n,this.nextTensorId());if(null!=this.state.registeredVariables[o.name])throw new Error(\"Variable with name \"+o.name+\" was already registered\");return this.state.registeredVariables[o.name]=o,this.incRef(o,this.backend),o},t.prototype.incRef=function(t,e){var n=this.state.tensorInfo.has(t.dataId)?this.state.tensorInfo.get(t.dataId).refCount:0;if(this.state.numTensors++,\"string\"===t.dtype&&this.state.numStringTensors++,0===n){this.state.numDataBuffers++;var r=0;\"complex64\"!==t.dtype&&\"string\"!==t.dtype&&(r=t.size*P(t.dtype)),this.state.tensorInfo.set(t.dataId,{backend:e||this.backend,dtype:t.dtype,shape:t.shape,bytes:r,refCount:0}),this.state.numBytes+=r}this.state.tensorInfo.get(t.dataId).refCount++,t instanceof bt||this.track(t)},t.prototype.disposeTensor=function(t){if(this.state.tensorInfo.has(t.dataId)){this.state.numTensors--,\"string\"===t.dtype&&this.state.numStringTensors--;var e=this.state.tensorInfo.get(t.dataId);e.refCount<=1?(\"complex64\"!==t.dtype&&(this.state.numBytes-=e.bytes),this.state.numDataBuffers--,e.backend.disposeData(t.dataId),this.state.tensorInfo.delete(t.dataId)):this.state.tensorInfo.get(t.dataId).refCount--}},t.prototype.disposeVariables=function(){for(var t in this.state.registeredVariables){var e=this.state.registeredVariables[t];this.disposeVariable(e)}},t.prototype.disposeVariable=function(t){this.disposeTensor(t),null!=this.state.registeredVariables[t.name]&&delete this.state.registeredVariables[t.name]},t.prototype.memory=function(){var t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(t.unreliable=!0,null==t.reasons&&(t.reasons=[]),t.reasons.push(\"Memory usage by string tensors is approximate (2 bytes per character)\")),t},t.prototype.profile=function(t){return n(this,void 0,void 0,function(){var e,n;return r(this,function(r){return this.state.profiling=!0,e=this.state.numBytes,n=this.state.numTensors,this.state.activeProfile.kernels=[],this.state.activeProfile.result=t(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max.apply(Math,this.state.activeProfile.kernels.map(function(t){return t.totalBytesSnapshot})),this.state.activeProfile.newBytes=this.state.numBytes-e,this.state.activeProfile.newTensors=this.state.numTensors-n,[2,this.state.activeProfile]})})},t.prototype.isTapeOn=function(){return this.state.gradientDepth>0&&0===this.state.kernelDepth},t.prototype.addTapeNode=function(t,e,n,r,o){var a=this,i={id:this.state.nextTapeNodeId++,name:t,inputs:e,outputs:n,saved:o};null!=r&&(i.gradient=function(t){return t=t.map(function(t,e){if(null==t){var r=n[e],o=$(r.size,r.dtype);return a.makeTensor(o,r.shape,r.dtype)}return t}),r(t.length>1?t:t[0],o)}),this.state.activeTape.push(i)},t.prototype.keep=function(t){return t.kept=!0,t},t.prototype.startTape=function(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++},t.prototype.endTape=function(){this.state.gradientDepth--},t.prototype.startScope=function(t){var e={track:[],name:\"unnamed scope\",id:this.state.nextScopeId++};t&&(e.name=t),this.state.scopeStack.push(e),this.state.activeScope=e},t.prototype.endScope=function(t){for(var e=this,n=kt(t),r=new Set(n.map(function(t){return t.id})),o=0;o<this.state.activeScope.track.length;o++){var a=this.state.activeScope.track[o];a.kept||r.has(a.id)||a.dispose()}var i=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],n.forEach(function(t){t.kept||t.scopeId!==i.id||e.track(t)})},t.prototype.gradients=function(t,e,n,r){var o=this;if(void 0===r&&(r=!1),g(e.length>0,function(){return\"gradients() received an empty list of xs.\"}),null!=n&&\"float32\"!==n.dtype)throw new Error(\"dy must have 'float32' dtype, but has '\"+n.dtype+\"'\");var a=this.scopedRun(function(){return o.startTape()},function(){return o.endTape()},function(){return o.tidy(\"forward\",t)});g(a instanceof dt,function(){return\"The result y returned by f() must be a tensor.\"});var i=function(t,e,n){for(var r={},o={},a=0;a<e.length;a++)r[e[a].id]=!0;for(a=0;a<t.length;a++){var i=(d=t[a]).inputs;for(var u in i){for(var s=i[u],c=!1,l=0;l<e.length;l++)if(r[s.id]){d.outputs.forEach(function(t){return r[t.id]=!0}),c=!0,o[d.id]=!0;break}if(c)break}}var h={};h[n.id]=!0;var f={};for(a=t.length-1;a>=0;a--)for(i=(d=t[a]).inputs,l=0;l<d.outputs.length;l++)if(h[d.outputs[l].id]){for(var u in i)h[i[u].id]=!0,f[d.id]=!0;break}var p=[];for(a=0;a<t.length;a++){var d;if(o[(d=t[a]).id]&&f[d.id]){var v={};for(var u in d.inputs){var m=d.inputs[u];r[m.id]&&(v[u]=m)}var g=Object.assign({},d);g.inputs=v,g.outputs=d.outputs,p.push(g)}}return p}(this.state.activeTape,e,a);if(!r&&0===i.length&&e.length>0)throw new Error(\"Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.\");return this.tidy(\"backward\",function(){var t,r,u={};u[a.id]=null==n?(t=a.shape,r=X(w(t),\"float32\"),Nt.makeTensor(r,t,\"float32\")):n,function(t,e,n){for(var r=function(r){var o=e[r],a=[];if(o.outputs.forEach(function(e){var n=t[e.id];null!=n?a.push(n):a.push(null)}),null==o.gradient)throw new Error(\"Cannot compute gradient: gradient function not found for \"+o.name+\".\");var i=o.gradient(a),u=function(e){if(!(e in i))throw new Error(\"Cannot backprop through input \"+e+\". Available gradients found: \"+Object.keys(i)+\".\");var r=n(function(){return i[e]()});if(\"float32\"!==r.dtype)throw new Error(\"Error in gradient for op \"+o.name+\". The gradient of input \"+e+\" must have 'float32' dtype, but has '\"+r.dtype+\"'\");var a=o.inputs[e];if(!C(r.shape,a.shape))throw new Error(\"Error in gradient for op \"+o.name+\". The gradient of input '\"+e+\"' has shape '\"+r.shape+\"', which does not match the shape of the input '\"+a.shape+\"'\");if(null==t[a.id])t[a.id]=r;else{var u=t[a.id];t[a.id]=u.add(r),u.dispose()}};for(var s in o.inputs)u(s)},o=e.length-1;o>=0;o--)r(o)}(u,i,function(t){return o.tidy(t)});var s=e.map(function(t){return u[t.id]});return 0===o.state.gradientDepth&&(o.state.activeTape.forEach(function(t){for(var e=0,n=t.saved;e<n.length;e++){n[e].dispose()}}),o.state.activeTape=null),{value:a,grads:s}})},t.prototype.customGrad=function(t){var e=this;return g(G(t),function(){return\"The f passed in customGrad(f) must be a function.\"}),function(){for(var n,r=[],o=0;o<arguments.length;o++)r[o]=arguments[o];g(r.every(function(t){return t instanceof dt}),function(){return\"The args passed in customGrad(f)(x1, x2,...) must all be tensors\"});var a={};return r.forEach(function(t,e){a[e]=t}),e.runKernelFunc(function(e,o){return g((n=t.apply(void 0,r.concat([o]))).value instanceof dt,function(){return\"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor\"}),g(G(n.gradFunc),function(){return\"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function.\"}),n.value},a,function(t,e){var o=n.gradFunc(t,e),a=Array.isArray(o)?o:[o];g(a.length===r.length,function(){return\"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...).\"}),g(a.every(function(t){return t instanceof dt}),function(){return\"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.\"});var i={};return a.forEach(function(t,e){i[e]=function(){return t}}),i})}},t.prototype.readSync=function(t){return this.state.tensorInfo.get(t).backend.readSync(t)},t.prototype.read=function(t){return this.state.tensorInfo.get(t).backend.read(t)},t.prototype.time=function(t){return n(this,void 0,void 0,function(){var e,n;return r(this,function(r){switch(r.label){case 0:return e=Y(),[4,this.backend.time(t)];case 1:return(n=r.sent()).wallMs=Y()-e,[2,n]}})})},t.prototype.track=function(t){return null!=this.state.activeScope&&(t.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(t)),t},Object.defineProperty(t.prototype,\"registeredVariables\",{get:function(){return this.state.registeredVariables},enumerable:!0,configurable:!0}),t.prototype.reset=function(){for(var t in this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new Dt,this.registry)this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null},t.nextTensorId=0,t.nextVariableId=0,t}();var Nt=function(){var t=function(){if(null==St){var t=void 0;if(\"undefined\"!=typeof window)t=window;else if(\"undefined\"!=typeof global)t=global;else if(\"undefined\"!=typeof process)t=process;else{if(\"undefined\"==typeof self)throw new Error(\"Could not find a global object\");t=self}St=t}return St}();if(null==t._tfengine){var e=new o(t);t._tfengine=new Tt(e)}return function(t){i=t}(t._tfengine.ENV),ht=function(){return t._tfengine},t._tfengine}();function Ft(){return\"undefined\"!=typeof window&&null!=window.document||\"undefined\"!=typeof WorkerGlobalScope}var _t=a();_t.registerFlag(\"DEBUG\",function(){return!1},function(t){t&&console.warn(\"Debugging mode is ON. 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    bestValue = candidate;\\n            bestIndex = inIdx;\\n          }\\n        }\\n        setOutput(float(bestIndex));\\n      }\\n    \"}}();function Ho(t,e){return[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"].slice(0,e).map(function(e){return t+\".\"+e})}function qo(t,e){return 1===e?[t]:Ho(t,e)}function Ko(){var t,e,n,r,o,i,u,s,c,l;return 2===a().getNumber(\"WEBGL_VERSION\")?(t=\"#version 300 es\",e=\"in\",n=\"out\",r=\"in\",o=\"texture\",i=\"outputColor\",u=\"out vec4 outputColor;\",s=\"\\n      bool isnan_custom(float val) {\\n        return (val > 0.0 || val < 0.0) ? false : val != 0.0;\\n      }\\n\\n      bvec4 isnan_custom(vec4 val) {\\n        return bvec4(isnan_custom(val.x),\\n          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));\\n      }\\n\\n      #define isnan(value) isnan_custom(value)\\n    \",c=\"\",l=\"\\n      #define round(value) newRound(value)\\n      int newRound(float value) {\\n        return int(floor(value + 0.5));\\n      }\\n\\n      ivec4 newRound(vec4 value) {\\n        return ivec4(floor(value + vec4(0.5)));\\n      }\\n    \"):(t=\"\",e=\"attribute\",n=\"varying\",r=\"varying\",o=\"texture2D\",i=\"gl_FragColor\",u=\"\",s=\"\\n      #define isnan(value) isnan_custom(value)\\n      bool isnan_custom(float val) {\\n        return (val > 0. || val < 1. || val == 0.) ? false : true;\\n      }\\n      bvec4 isnan_custom(vec4 val) {\\n        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));\\n      }\\n    \",c=\"\\n      uniform float INFINITY;\\n\\n      bool isinf(float val) {\\n        return abs(val) == INFINITY;\\n      }\\n      bvec4 isinf(vec4 val) {\\n        return equal(abs(val), vec4(INFINITY));\\n      }\\n    \",l=\"\\n      int round(float value) {\\n        return int(floor(value + 0.5));\\n      }\\n\\n      ivec4 round(vec4 value) {\\n        return ivec4(floor(value + vec4(0.5)));\\n      }\\n    \"),{version:t,attribute:e,varyingVs:n,varyingFs:r,texture2D:o,output:i,defineOutput:u,defineSpecialNaN:s,defineSpecialInf:c,defineRound:l}}function jo(t,e,n){void 0===n&&(n=\"index\");var r=q(e);return r.map(function(e,o){return\"int \"+t[o]+\" = \"+n+\" / \"+e+\"; \"+(o===r.length-1?\"int \"+t[o+1]+\" = \"+n+\" - \"+t[o]+\" * \"+e:\"index -= \"+t[o]+\" * \"+e)+\";\"}).join(\"\")}function Xo(t){var e=q(t).map(function(t){return t.toString()});return\"\\n  int getFlatIndex(ivec3 coords) {\\n    return coords.x * \"+e[0]+\" + coords.y * \"+e[1]+\" + coords.z;\\n  }\\n\"}var $o=\"\\n  const float FLOAT_MAX = 1.70141184e38;\\n  const float FLOAT_MIN = 1.17549435e-38;\\n\\n  lowp vec4 encode_float(highp float v) {\\n    if (isnan(v)) {\\n      return vec4(255, 255, 255, 255);\\n    }\\n\\n    highp float av = abs(v);\\n\\n    if(av < FLOAT_MIN) {\\n      return vec4(0.0, 0.0, 0.0, 0.0);\\n    } else if(v > FLOAT_MAX) {\\n      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;\\n    } else if(v < -FLOAT_MAX) {\\n      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;\\n    }\\n\\n    highp vec4 c = vec4(0,0,0,0);\\n\\n    highp float e = floor(log2(av));\\n    highp float m = exp2(fract(log2(av))) - 1.0;\\n\\n    c[2] = floor(128.0 * m);\\n    m -= c[2] / 128.0;\\n    c[1] = floor(32768.0 * m);\\n    m -= c[1] / 32768.0;\\n    c[0] = floor(8388608.0 * m);\\n\\n    highp float ebias = e + 127.0;\\n    c[3] = floor(ebias / 2.0);\\n    ebias -= c[3] * 2.0;\\n    c[2] += floor(ebias) * 128.0;\\n\\n    c[3] += 128.0 * step(0.0, -v);\\n\\n    return c / 255.0;\\n  }\\n\";function Yo(t,e,n,r){var o=[];t.forEach(function(t){var e=w(t.shapeInfo.logicalShape);t.shapeInfo.isUniform?o.push(\"uniform float \"+t.name+(e>1?\"[\"+e+\"]\":\"\")+\";\"):(o.push(\"uniform sampler2D \"+t.name+\";\"),o.push(\"uniform int offset\"+t.name+\";\"))});var a,i,u=o.join(\"\\n\"),s=t.map(function(t){return function(t,e,n){void 0===n&&(n=!1);var r=\"\";r+=n?Jo(t):Qo(t);var o=t.shapeInfo.logicalShape,a=e.logicalShape;o.length<=a.length&&(r+=n?function(t,e){var n,r=t.name,o=r.charAt(0).toUpperCase()+r.slice(1),a=\"get\"+o+\"AtOutCoords\",i=t.shapeInfo.logicalShape.length,u=e.logicalShape.length,s=ho(t.shapeInfo.logicalShape,e.logicalShape),c=aa(u),l=u-i,h=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"];n=0===i?\"\":u<2&&s.length>=1?\"coords = 0;\":s.map(function(t){return\"coords.\"+h[t+l]+\" = 0;\"}).join(\"\\n\");var f=\"\";f=u<2&&i>0?\"coords\":t.shapeInfo.logicalShape.map(function(t,e){return\"coords.\"+h[e+l]}).join(\", \");var p=\"return outputValue;\",d=1===w(t.shapeInfo.logicalShape),v=1===w(e.logicalShape);if(1!==i||d||v){if(d&&!v)p=1===u?\"\\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\\n      \":\"\\n        return vec4(outputValue.x);\\n      \";else if(s.length){var m=i-2,g=i-1;s.indexOf(m)>-1&&s.indexOf(g)>-1?p=\"return vec4(outputValue.x);\":s.indexOf(m)>-1?p=\"return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);\":s.indexOf(g)>-1&&(p=\"return vec4(outputValue.xx, outputValue.zz);\")}}else p=\"\\n      return vec4(outputValue.xy, outputValue.xy);\\n    \";return\"\\n    vec4 \"+a+\"() {\\n      \"+c+\" coords = getOutputCoords();\\n      \"+n+\"\\n      vec4 outputValue = get\"+o+\"(\"+f+\");\\n      \"+p+\"\\n    }\\n  \"}(t,e):function(t,e){var n=t.name,r=n.charAt(0).toUpperCase()+n.slice(1),o=\"get\"+r+\"AtOutCoords\",a=e.texShape,i=t.shapeInfo.texShape,u=t.shapeInfo.logicalShape.length,s=e.logicalShape.length;if(!t.shapeInfo.isUniform&&u===s&&null==t.shapeInfo.flatOffset&&C(i,a))return\"\\n      float \"+o+\"() {\\n        return sampleTexture(\"+n+\", resultUV);\\n      }\\n    \";var c,l=aa(s),h=ho(t.shapeInfo.logicalShape,e.logicalShape),f=s-u,p=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"];c=0===u?\"\":s<2&&h.length>=1?\"coords = 0;\":h.map(function(t){return\"coords.\"+p[t+f]+\" = 0;\"}).join(\"\\n\");var d=\"\";d=s<2&&u>0?\"coords\":t.shapeInfo.logicalShape.map(function(t,e){return\"coords.\"+p[e+f]}).join(\", \");return\"\\n    float \"+o+\"() {\\n      \"+l+\" coords = getOutputCoords();\\n      \"+c+\"\\n      return get\"+r+\"(\"+d+\");\\n    }\\n  \"}(t,e));return r}(t,e,r)}).join(\"\\n\"),c=e.texShape,l=Ko(),h=function(t){return\"\\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\\n      return \"+t.texture2D+\"(textureSampler, uv).r;\\n    }\\n  \"}(l),f=function(t){return t.version+\"\\n    precision highp float;\\n    precision highp int;\\n    precision highp sampler2D;\\n    \"+t.varyingFs+\" vec2 resultUV;\\n    \"+t.defineOutput+\"\\n    const vec2 halfCR = vec2(0.5, 0.5);\\n\\n    struct ivec5\\n    {\\n      int x;\\n      int y;\\n      int z;\\n      int w;\\n      int u;\\n    };\\n\\n    struct ivec6\\n    {\\n      int x;\\n      int y;\\n      int z;\\n      int w;\\n      int u;\\n      int v;\\n    };\\n\\n    uniform float NAN;\\n    \"+t.defineSpecialNaN+\"\\n    \"+t.defineSpecialInf+\"\\n    \"+t.defineRound+\"\\n\\n    int imod(int x, int y) {\\n      return x - y * (x / y);\\n    }\\n\\n    int idiv(int a, int b, float sign) {\\n      int res = a / b;\\n      int mod = imod(a, b);\\n      if (sign < 0. && mod != 0) {\\n        res -= 1;\\n      }\\n      return res;\\n    }\\n\\n    //Based on the work of Dave Hoskins\\n    //https://www.shadertoy.com/view/4djSRW\\n    #define HASHSCALE1 443.8975\\n    float random(float seed){\\n      vec2 p = resultUV * seed;\\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\\n      p3 += dot(p3, p3.yzx + 19.19);\\n      return fract((p3.x + p3.y) * p3.z);\\n    }\\n\\n    \"+Zo+\"\\n    \"+ta+\"\\n    \"+ea+\"\\n  \"}(l);return e.isPacked?(a=function(t,e){switch(t.length){case 0:return\"\\n    int getOutputCoords() {\\n      return 0;\\n    }\\n  \";case 1:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(1===n[0])return\"\\n      int getOutputCoords() {\\n        return 2 * int(resultUV.x * \"+n[1]+\".0);\\n      }\\n    \";if(1===n[1])return\"\\n      int getOutputCoords() {\\n        return 2 * int(resultUV.y * \"+n[0]+\".0);\\n      }\\n    \";return\"\\n    int getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+n[0]+\", \"+n[1]+\"));\\n      return 2 * (resTexRC.x * \"+n[1]+\" + resTexRC.y);\\n    }\\n  \"}(0,e);case 2:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(C(t,e))return\"\\n      ivec2 getOutputCoords() {\\n        return 2 * ivec2(resultUV.yx * vec2(\"+n[0]+\", \"+n[1]+\"));\\n      }\\n    \";var r=Math.ceil(t[1]/2);return\"\\n    ivec2 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+n[0]+\", \"+n[1]+\"));\\n\\n      int index = resTexRC.x * \"+n[1]+\" + resTexRC.y;\\n      int r = 2 * (index / \"+r+\");\\n      int c = imod(index, \"+r+\") * 2;\\n\\n      return ivec2(r, c);\\n    }\\n  \"}(t,e);case 3:return n=t,r=e,o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=Math.ceil(n[2]/2),i=a*Math.ceil(n[1]/2),\"\\n    ivec3 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+o[0]+\", \"+o[1]+\"));\\n      int index = resTexRC.x * \"+o[1]+\" + resTexRC.y;\\n\\n      int b = index / \"+i+\";\\n      index -= b * \"+i+\";\\n\\n      int r = 2 * (index / \"+a+\");\\n      int c = imod(index, \"+a+\") * 2;\\n\\n      return ivec3(b, r, c);\\n    }\\n  \";default:return function(t,e){for(var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],r=Math.ceil(t[t.length-1]/2),o=r*Math.ceil(t[t.length-2]/2),a=o,i=\"\",u=\"b, r, c\",s=2;s<t.length-1;s++)a*=t[t.length-s-1],i=\"\\n      int b\"+s+\" = index / \"+a+\";\\n      index -= b\"+s+\" * \"+a+\";\\n    \"+i,u=\"b\"+s+\", \"+u;return\"\\n    ivec\"+t.length+\" getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+n[0]+\", \"+n[1]+\"));\\n      int index = resTexRC.x * \"+n[1]+\" + resTexRC.y;\\n\\n      \"+i+\"\\n\\n      int b = index / \"+o+\";\\n      index -= b * \"+o+\";\\n\\n      int r = 2 * (index / \"+r+\");\\n      int c = imod(index, \"+r+\") * 2;\\n\\n      return ivec\"+t.length+\"(\"+u+\");\\n    }\\n  \"}(t,e)}var n,r,o,a,i}(e.logicalShape,c),i=function(t){return\"\\n    void setOutput(vec4 val) {\\n      \"+t.output+\" = val;\\n    }\\n  \"}(l)):(a=function(t,e){switch(t.length){case 0:return\"\\n    int getOutputCoords() {\\n      return 0;\\n    }\\n  \";case 1:return function(t,e){if(1===e[0])return\"\\n      int getOutputCoords() {\\n        return int(resultUV.x * \"+e[1]+\".0);\\n      }\\n    \";if(1===e[1])return\"\\n      int getOutputCoords() {\\n        return int(resultUV.y * \"+e[0]+\".0);\\n      }\\n    \";return\"\\n    int getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+e[0]+\", \"+e[1]+\"));\\n      return resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n    }\\n  \"}(0,e);case 2:return function(t,e){if(C(t,e))return\"\\n      ivec2 getOutputCoords() {\\n        return ivec2(resultUV.yx * vec2(\"+e[0]+\", \"+e[1]+\"));\\n      }\\n    \";if(1===t[1])return\"\\n      ivec2 getOutputCoords() {\\n        ivec2 resTexRC = ivec2(resultUV.yx *\\n                               vec2(\"+e[0]+\", \"+e[1]+\"));\\n        int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n        return ivec2(index, 0);\\n      }\\n    \";if(1===t[0])return\"\\n      ivec2 getOutputCoords() {\\n        ivec2 resTexRC = ivec2(resultUV.yx *\\n                               vec2(\"+e[0]+\", \"+e[1]+\"));\\n        int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n        return ivec2(0, index);\\n      }\\n    \";return\"\\n    ivec2 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+e[0]+\", \"+e[1]+\"));\\n      int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n      int r = index / \"+t[1]+\";\\n      int c = index - r * \"+t[1]+\";\\n      return ivec2(r, c);\\n    }\\n  \"}(t,e);case 3:return n=e,r=jo([\"r\",\"c\",\"d\"],t),\"\\n    ivec3 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+n[0]+\", \"+n[1]+\"));\\n      int index = resTexRC.x * \"+n[1]+\" + resTexRC.y;\\n      \"+r+\"\\n      return ivec3(r, c, d);\\n    }\\n  \";case 4:return function(t,e){var n=jo([\"r\",\"c\",\"d\",\"d2\"],t);return\"\\n    ivec4 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n        vec2(\"+e[0]+\", \"+e[1]+\"));\\n      int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n      \"+n+\"\\n      return ivec4(r, c, d, d2);\\n    }\\n  \"}(t,e);case 5:return function(t,e){var n=jo([\"r\",\"c\",\"d\",\"d2\",\"d3\"],t);return\"\\n    ivec5 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2(\"+e[0]+\",\\n                             \"+e[1]+\"));\\n\\n      int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n\\n      \"+n+\"\\n\\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\\n      return outShape;\\n    }\\n  \"}(t,e);case 6:return function(t,e){var n=jo([\"r\",\"c\",\"d\",\"d2\",\"d3\",\"d4\"],t);return\"\\n    ivec6 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n        vec2(\"+e[0]+\", \"+e[1]+\"));\\n      int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n\\n      \"+n+\"\\n\\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\\n      return result;\\n    }\\n  \"}(t,e);default:throw new Error(t.length+\"-D output sampling is not yet supported\")}var n,r}(e.logicalShape,c),i=function(t){return\"\\n    void setOutput(float val) {\\n      \"+t.output+\" = vec4(val, 0, 0, 0);\\n    }\\n  \"}(l)),r&&(f+=na),[f,h,i,u,a,s,n].join(\"\\n\")}function Qo(t){var e=t.shapeInfo.logicalShape;switch(e.length){case 0:return function(t){var e=t.name,n=\"get\"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return\"float \"+n+\"() {return \"+e+\";}\";var r=t.shapeInfo.texShape,o=r[0],a=r[1];if(1===o&&1===a)return\"\\n      float \"+n+\"() {\\n        return sampleTexture(\"+e+\", halfCR);\\n      }\\n    \";var i=t.shapeInfo.texShape,u=i[0],s=i[1],c=ra(e);return\"\\n    float \"+n+\"() {\\n      vec2 uv = uvFromFlat(\"+u+\", \"+s+\", \"+c+\");\\n      return sampleTexture(\"+e+\", uv);\\n    }\\n  \"}(t);case 1:return function(t){var e=t.name,n=\"get\"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return\"\\n      float \"+n+\"(int index) {\\n        \"+oa(t)+\"\\n      }\\n    \";var r=t.shapeInfo.texShape,o=r[0],a=r[1];if(1===a&&1===o)return\"\\n      float \"+n+\"(int index) {\\n        return sampleTexture(\"+e+\", halfCR);\\n      }\\n    \";var i=ra(e);if(1===a)return\"\\n      float \"+n+\"(int index) {\\n        vec2 uv = vec2(0.5, (float(index + \"+i+\") + 0.5) / \"+o+\".0);\\n        return sampleTexture(\"+e+\", uv);\\n      }\\n    \";if(1===o)return\"\\n      float \"+n+\"(int index) {\\n        vec2 uv = vec2((float(index + \"+i+\") + 0.5) / \"+a+\".0, 0.5);\\n        return sampleTexture(\"+e+\", uv);\\n      }\\n    \";return\"\\n    float \"+n+\"(int index) {\\n      vec2 uv = uvFromFlat(\"+o+\", \"+a+\", index + \"+i+\");\\n      return sampleTexture(\"+e+\", uv);\\n    }\\n  \"}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape;if(null!=o&&C(e,o)){var a=o[0],i=o[1];return\"\\n    float \"+r+\"(int row, int col) {\\n      vec2 uv = (vec2(col, row) + halfCR) / vec2(\"+i+\".0, \"+a+\".0);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \"}var u=T(e),s=u.newShape,c=u.keptDims,l=s;if(l.length<e.length){var h=ia(t,l);return\"\\n      \"+Qo(h)+\"\\n      float \"+r+\"(int row, int col) {\\n        return \"+r+\"(\"+ua([\"row\",\"col\"],c)+\");\\n      }\\n    \"}if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col) {\\n        int index = round(dot(vec2(row, col), vec2(\"+e[1]+\", 1)));\\n        \"+oa(t)+\"\\n      }\\n    \";var f=o[0],p=o[1],d=ra(n);if(1===p)return\"\\n    float \"+r+\"(int row, int col) {\\n      float index = dot(vec3(row, col, \"+d+\"), vec3(\"+e[1]+\", 1, 1));\\n      vec2 uv = vec2(0.5, (index + 0.5) / \"+f+\".0);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \";if(1===f)return\"\\n    float \"+r+\"(int row, int col) {\\n      float index = dot(vec3(row, col, \"+d+\"), vec3(\"+e[1]+\", 1, 1));\\n      vec2 uv = vec2((index + 0.5) / \"+p+\".0, 0.5);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \";return\"\\n  float \"+r+\"(int row, int col) {\\n    // Explicitly use integer operations as dot() only works on floats.\\n    int index = row * \"+e[1]+\" + col + \"+d+\";\\n    vec2 uv = uvFromFlat(\"+f+\", \"+p+\", index);\\n    return sampleTexture(\"+n+\", uv);\\n  }\\n\"}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=e[1]*e[2],a=e[2],i=T(e),u=i.newShape,s=i.keptDims,c=u;if(c.length<e.length){var l=ia(t,c);return\"\\n        \"+Qo(l)+\"\\n        float \"+r+\"(int row, int col, int depth) {\\n          return \"+r+\"(\"+ua([\"row\",\"col\",\"depth\"],s)+\");\\n        }\\n      \"}if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col, int depth) {\\n        int index = round(dot(vec3(row, col, depth),\\n                          vec3(\"+o+\", \"+a+\", 1)));\\n        \"+oa(t)+\"\\n      }\\n    \";var h=t.shapeInfo.texShape,f=h[0],p=h[1],d=t.shapeInfo.flatOffset;if(p===o&&null==d)return\"\\n        float \"+r+\"(int row, int col, int depth) {\\n          float texR = float(row);\\n          float texC = dot(vec2(col, depth), vec2(\"+a+\", 1));\\n          vec2 uv = (vec2(texC, texR) + halfCR) /\\n                     vec2(\"+p+\".0, \"+f+\".0);\\n          return sampleTexture(\"+n+\", uv);\\n        }\\n      \";if(p===a&&null==d)return\"\\n    float \"+r+\"(int row, int col, int depth) {\\n      float texR = dot(vec2(row, col), vec2(\"+e[1]+\", 1));\\n      float texC = float(depth);\\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(\"+p+\".0, \"+f+\".0);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \";var v=ra(n);return\"\\n      float \"+r+\"(int row, int col, int depth) {\\n        // Explicitly use integer operations as dot() only works on floats.\\n        int index = row * \"+o+\" + col * \"+a+\" + depth + \"+v+\";\\n        vec2 uv = uvFromFlat(\"+f+\", \"+p+\", index);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n  \"}(t);case 4:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=e[3],a=e[2]*o,i=e[1]*a,u=T(e),s=u.newShape,c=u.keptDims;if(s.length<e.length){var l=ia(t,s);return\"\\n      \"+Qo(l)+\"\\n      float \"+r+\"(int row, int col, int depth, int depth2) {\\n        return \"+r+\"(\"+ua([\"row\",\"col\",\"depth\",\"depth2\"],c)+\");\\n      }\\n    \"}if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2) {\\n        int index = round(dot(vec4(row, col, depth, depth2),\\n                          vec4(\"+i+\", \"+a+\", \"+o+\", 1)));\\n        \"+oa(t)+\"\\n      }\\n    \";var h=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,p=f[0],d=f[1];if(d===i&&null==h)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2) {\\n        float texR = float(row);\\n        float texC =\\n            dot(vec3(col, depth, depth2),\\n                vec3(\"+a+\", \"+o+\", 1));\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                   vec2(\"+d+\".0, \"+p+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";if(d===o&&null==h)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2) {\\n        float texR = dot(vec3(row, col, depth),\\n                         vec3(\"+e[1]*e[2]+\", \"+e[2]+\", 1));\\n        float texC = float(depth2);\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                  vec2(\"+d+\".0, \"+p+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";var v=ra(n);return\"\\n    float \"+r+\"(int row, int col, int depth, int depth2) {\\n      // Explicitly use integer operations as dot() only works on floats.\\n      int index = row * \"+i+\" + col * \"+a+\" +\\n          depth * \"+o+\" + depth2;\\n      vec2 uv = uvFromFlat(\"+p+\", \"+d+\", index + \"+v+\");\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \"}(t);case 5:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=e[4],a=e[3]*o,i=e[2]*a,u=e[1]*i,s=T(e),c=s.newShape,l=s.keptDims;if(c.length<e.length){var h=ia(t,c);return\"\\n      \"+Qo(h)+\"\\n      float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n        return \"+r+\"(\"+ua([\"row\",\"col\",\"depth\",\"depth2\",\"depth3\"],l)+\");\\n      }\\n    \"}if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n        float index = dot(\\n          vec4(row, col, depth, depth2),\\n          vec4(\"+u+\", \"+i+\", \"+a+\", \"+o+\")) +\\n          depth3;\\n        \"+oa(t)+\"\\n      }\\n    \";var f=t.shapeInfo.flatOffset,p=t.shapeInfo.texShape,d=p[0],v=p[1];if(v===u&&null==f)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n        int texR = row;\\n        float texC = dot(vec4(col, depth, depth2, depth3),\\n                         vec4(\"+i+\", \"+a+\", \"+o+\", 1));\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                   vec2(\"+v+\".0, \"+d+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";if(v===o&&null==f)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n        float texR = dot(\\n          vec4(row, col, depth, depth2),\\n          vec4(\"+e[1]*e[2]*e[3]+\",\\n               \"+e[2]*e[3]+\", \"+e[3]+\", 1));\\n        int texC = depth3;\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                  vec2(\"+v+\".0, \"+d+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";var m=ra(n);return\"\\n    float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n      // Explicitly use integer operations as dot() only works on floats.\\n      int index = row * \"+u+\" + col * \"+i+\" + depth * \"+a+\" +\\n          depth2 * \"+o+\" + depth3 + \"+m+\";\\n      vec2 uv = uvFromFlat(\"+d+\", \"+v+\", index);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \"}(t);case 6:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=T(e),a=o.newShape,i=o.keptDims;if(a.length<e.length){var u=ia(t,a);return\"\\n      \"+Qo(u)+\"\\n      float \"+r+\"(int row, int col, int depth,\\n                    int depth2, int depth3, int depth4) {\\n        return \"+r+\"(\"+ua([\"row\",\"col\",\"depth\",\"depth2\",\"depth3\",\"depth4\"],i)+\");\\n      }\\n    \"}var s=e[5],c=e[4]*s,l=e[3]*c,h=e[2]*l,f=e[1]*h;if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col, int depth,\\n                  int depth2, int depth3, int depth4) {\\n        int index = round(dot(\\n          vec4(row, col, depth, depth2),\\n          vec4(\"+f+\", \"+h+\", \"+l+\", \"+c+\")) +\\n          dot(\\n            vec2(depth3, depth4),\\n            vec2(\"+s+\", 1)));\\n        \"+oa(t)+\"\\n      }\\n    \";var p=t.shapeInfo.flatOffset,d=t.shapeInfo.texShape,v=d[0],m=d[1];if(m===f&&null==p)return\"\\n      float \"+r+\"(int row, int col, int depth,\\n                    int depth2, int depth3, int depth4) {\\n        int texR = row;\\n        float texC = dot(vec4(col, depth, depth2, depth3),\\n          vec4(\"+h+\", \"+l+\", \"+c+\", \"+s+\")) +\\n               float(depth4);\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                   vec2(\"+m+\".0, \"+v+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";if(m===s&&null==p)return\"\\n      float \"+r+\"(int row, int col, int depth,\\n                    int depth2, int depth3, int depth4) {\\n        float texR = dot(vec4(row, col, depth, depth2),\\n          vec4(\"+e[1]*e[2]*e[3]*e[4]+\",\\n               \"+e[2]*e[3]*e[4]+\",\\n               \"+e[3]*e[4]+\",\\n               \"+e[4]+\")) + float(depth3);\\n        int texC = depth4;\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                  vec2(\"+m+\".0, \"+v+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";var g=ra(n);return\"\\n    float \"+r+\"(int row, int col, int depth,\\n                  int depth2, int depth3, int depth4) {\\n      // Explicitly use integer operations as dot() only works on floats.\\n      int index = row * \"+f+\" + col * \"+h+\" + depth * \"+l+\" +\\n          depth2 * \"+c+\" + depth3 * \"+s+\" + depth4 + \"+g+\";\\n      vec2 uv = uvFromFlat(\"+v+\", \"+m+\", index);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \"}(t);default:throw new Error(e.length+\"-D input sampling is not yet supported\")}}function Jo(t){var e,n,r;switch(t.shapeInfo.logicalShape.length){case 0:return e=t.name,n=\"get\"+e.charAt(0).toUpperCase()+e.slice(1),r=Ko(),\"\\n    vec4 \"+n+\"() {\\n      return \"+r.texture2D+\"(\"+e+\", halfCR);\\n    }\\n  \";case 1:return function(t){var e=t.name,n=\"get\"+e.charAt(0).toUpperCase()+e.slice(1),r=t.shapeInfo.texShape,o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=Ko();return\"\\n    vec4 \"+n+\"(int index) {\\n      vec2 uv = packedUVfrom1D(\\n        \"+o[0]+\", \"+o[1]+\", index);\\n      return \"+a.texture2D+\"(\"+e+\", uv);\\n    }\\n  \"}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,a=o[0],i=o[1],u=Ko();if(null!=o&&C(e,o))return\"\\n      vec4 \"+r+\"(int row, int col) {\\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(\"+i+\".0, \"+a+\".0);\\n\\n        return \"+u.texture2D+\"(\"+n+\", uv);\\n      }\\n    \";var s=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],c=Math.ceil(e[1]/2);return\"\\n    vec4 \"+r+\"(int row, int col) {\\n      vec2 uv = packedUVfrom2D(\"+c+\", \"+s[0]+\", \"+s[1]+\", row, col);\\n      return \"+u.texture2D+\"(\"+n+\", uv);\\n    }\\n  \"}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,a=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];if(1===e[0]){var i=e.slice(1),u=ia(t,i);return\"\\n        \"+Jo(u)+\"\\n        vec4 \"+r+\"(int b, int row, int col) {\\n          return \"+r+\"(\"+ua([\"b\",\"row\",\"col\"],[1,2])+\");\\n        }\\n      \"}var s=a[0],c=a[1],l=Math.ceil(e[2]/2),h=l*Math.ceil(e[1]/2),f=Ko();return\"\\n    vec4 \"+r+\"(int b, int row, int col) {\\n      vec2 uv = packedUVfrom3D(\\n        \"+s+\", \"+c+\", \"+h+\", \"+l+\", b, row, col);\\n      return \"+f.texture2D+\"(\"+n+\", uv);\\n    }\\n  \"}(t);default:return function(t){for(var e=t.shapeInfo.logicalShape,n=e.length,r=t.name,o=\"get\"+r.charAt(0).toUpperCase()+r.slice(1),a=t.shapeInfo.texShape,i=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],u=i[0],s=i[1],c=Math.ceil(e[n-1]/2),l=c*Math.ceil(e[n-2]/2),h=\"int b, int row, int col\",f=\"b * \"+l+\" + (row / 2) * \"+c+\" + (col / 2)\",p=2;p<n-1;p++)h=\"int b\"+p+\", \"+h,l*=e[n-p-1],f=\"b\"+p+\" * \"+l+\" + \"+f;var d=Ko();return\"\\n    vec4 \"+o+\"(\"+h+\") {\\n      int index = \"+f+\";\\n      int texR = index / \"+s+\";\\n      int texC = index - texR * \"+s+\";\\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(\"+s+\", \"+u+\");\\n      return \"+d.texture2D+\"(\"+r+\", uv);\\n    }\\n  \"}(t)}}var Zo=\"\\nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\\n  int texR = index / texNumC;\\n  int texC = index - texR * texNumC;\\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\\n}\\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\\n  int texelIndex = index / 2;\\n  int texR = texelIndex / texNumC;\\n  int texC = texelIndex - texR * texNumC;\\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\\n}\\n\",ta=\"\\nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\\n  int texNumC, int row, int col) {\\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\\n  int texR = texelIndex / texNumC;\\n  int texC = texelIndex - texR * texNumC;\\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\\n}\\n\",ea=\"\\nvec2 packedUVfrom3D(int texNumR, int texNumC,\\n    int texelsInBatch, int texelsInLogicalRow, int b,\\n    int row, int col) {\\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\\n  int texR = index / texNumC;\\n  int texC = index - texR * texNumC;\\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\\n}\\n\",na=\"\\n  float getChannel(vec4 frag, vec2 innerDims) {\\n    vec2 modCoord = mod(innerDims, 2.);\\n    return modCoord.x == 0. ?\\n      (modCoord.y == 0. ? frag.r : frag.g) :\\n      (modCoord.y == 0. ? frag.b : frag.a);\\n  }\\n  float getChannel(vec4 frag, int dim) {\\n    float modCoord = mod(float(dim), 2.);\\n    return modCoord == 0. ? frag.r : frag.g;\\n  }\\n\";function ra(t){return\"offset\"+t}function oa(t){var e=t.name,n=w(t.shapeInfo.logicalShape);return n<2?\"return \"+e+\";\":\"\\n    for (int i = 0; i < \"+n+\"; i++) {\\n      if (i == index) {\\n        return \"+e+\"[i];\\n      }\\n    }\\n  \"}function aa(t){if(t<=1)return\"int\";if(2===t)return\"ivec2\";if(3===t)return\"ivec3\";if(4===t)return\"ivec4\";if(5===t)return\"ivec5\";if(6===t)return\"ivec6\";throw Error(\"GPU for rank \"+t+\" is not yet supported\")}function ia(t,e){var n=JSON.parse(JSON.stringify(t));return n.shapeInfo.logicalShape=e,n}function ua(t,e){return e.map(function(e){return t[e]}).join(\", \")}var sa=function(){return function(t,e,n,r){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,g(t.length>2,function(){return\"Packed arg\"+(n.charAt(0).toUpperCase()+n.slice(1))+\" supports only inputs with rank above 2.\"});var o=t[t.length-1],a=Math.ceil(o/e);this.outputShape=t.slice(0,-1),a>1&&this.outputShape.push(a),r||this.variableNames.push(\"bestIndicesA\");var i,u,s=this.outputShape,c=s.length,l=aa(c),h=qo(\"coords\",c);if(1===a){var f=aa(u=c+1);i=\"\\n        \"+f+\" sourceLocR = \"+f+\"(\"+h.join()+\", 0);\\n        ++\"+h[c-1]+\";\\n        \"+f+\" sourceLocG = \"+f+\"(\"+h.join()+\", 0);\\n        ++\"+h[c-2]+\";\\n        \"+f+\" sourceLocA = \"+f+\"(\"+h.join()+\", 0);\\n        --\"+h[c-1]+\";\\n        \"+f+\" sourceLocB = \"+f+\"(\"+h.join()+\", 0);\\n        --\"+h[c-2]+\";\"}else u=c,i=\"\\n        \"+l+\" sourceLocR = coords;\\n        ++\"+h[c-1]+\";\\n        \"+l+\" sourceLocG = coords;\\n        ++\"+h[c-2]+\";\\n        \"+l+\" sourceLocA = coords;\\n        --\"+h[c-1]+\";\\n        \"+l+\" sourceLocB = coords;\\n        --\"+h[c-2]+\";\";var p=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"].slice(0,u),d=\".\"+p[u-1],v=p.map(function(t){return\"int \"+t}),m=qo(\"sourceLocR\",u-1).concat(\"inIdx.r\"),y=qo(\"sourceLocG\",u-1).concat(\"inIdx.g\"),x=qo(\"sourceLocB\",u-1).concat(\"inIdx.b\"),b=qo(\"sourceLocA\",u-1).concat(\"inIdx.a\"),w=\"max\"===n?\"greaterThan\":\"lessThan\",C=r?\"\":\"\\n          inIdx = round(vec4(getBestIndicesAChannel(\"+m.join()+\"),\\n                             getBestIndicesAChannel(\"+y.join()+\"),\\n                             getBestIndicesAChannel(\"+x.join()+\"),\\n                             getBestIndicesAChannel(\"+b.join()+\")));\",E=\"vec4(\\n            getAChannel(\"+m.join()+\"),\\n            hasNextCol ? getAChannel(\"+y.join()+\") : 0.,\\n            hasNextRow ? getAChannel(\"+x.join()+\") : 0.,\\n            hasNextRow && hasNextCol ? getAChannel(\"+b.join()+\") : 0.)\",R=r?\"\":\"\\n      float getBestIndicesAChannel(\"+v.join()+\") {\\n        return getChannel(getBestIndicesA(\"+p.join()+\"),\\n                                          vec2(\"+p.slice(-2).join()+\"));\\n      }\";this.userCode=\"\\n      float getAChannel(\"+v.join()+\") {\\n        return getChannel(getA(\"+p.join()+\"),\\n                               vec2(\"+p.slice(-2).join()+\"));\\n      }\\n      \"+R+\"\\n      void main() {\\n        \"+l+\" coords = getOutputCoords();\\n        bool hasNextCol = \"+h[c-1]+\" < \"+(s[c-1]-1)+\";\\n        bool hasNextRow = \"+h[c-2]+\" < \"+(s[c-2]-1)+\";\\n        \"+i+\"\\n        ivec4 srcIdx = ivec4(sourceLocR\"+d+\", sourceLocG\"+d+\",\\n          sourceLocB\"+d+\", sourceLocA\"+d+\") * \"+e+\";\\n        ivec4 inIdx = srcIdx;\\n        vec4 bestIndex = vec4(inIdx);\\n        vec4 bestValue = \"+E+\";\\n\\n        for (int i = 0; i < \"+e+\"; i++) {\\n          inIdx = srcIdx;\\n          \"+C+\"\\n          vec4 candidate = \"+E+\";\\n          bvec4 nan = isnan(candidate);\\n          bvec4 replace = bvec4(\\n            vec4(\"+w+\"(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\\n\\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\\n                           replace.y  ? candidate.y : bestValue.y,\\n                           replace.z  ? candidate.z : bestValue.z,\\n                           replace.w  ? candidate.w : bestValue.w);\\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\\n          srcIdx++;\\n        }\\n        setOutput(bestIndex);\\n      }\\n    \"}}(),ca=function(){return function(t){this.variableNames=[\"dy\"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=t.dilationHeight,i=t.dilationWidth,u=t.effectiveFilterHeight,s=t.effectiveFilterWidth,c=u-1-t.padInfo.top,l=s-1-t.padInfo.left,h=1/(e*n);this.userCode=\"\\n      const ivec2 pads = ivec2(\"+c+\", \"+l+\");\\n      const float avgMultiplier = float(\"+h+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n\\n        ivec2 dyRCCorner = coords.yz - pads;\\n        int dyRCorner = dyRCCorner.x;\\n        int dyCCorner = dyRCCorner.y;\\n\\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        for (int wR = 0; wR < \"+u+\";\\n            wR += \"+a+\") {\\n          float dyR = float(dyRCorner + wR) / \"+r+\".0;\\n\\n          if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 || fract(dyR) > 0.0) {\\n            continue;\\n          }\\n          int idyR = int(dyR);\\n\\n          for (int wC = 0; wC < \"+s+\";\\n            wC+= \"+i+\") {\\n            float dyC = float(dyCCorner + wC) / \"+o+\".0;\\n\\n            if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                fract(dyC) > 0.0) {\\n              continue;\\n            }\\n            int idyC = int(dyC);\\n\\n            float dyValue = getDy(b, idyR, idyC, d);\\n\\n            dotProd += dyValue * avgMultiplier;\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),la=function(){return function(t){this.variableNames=[\"dy\"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,u=t.dilationDepth,s=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,p=l-1-t.padInfo.front,d=h-1-t.padInfo.top,v=f-1-t.padInfo.left,m=1/(e*n*r);this.userCode=\"\\n      const ivec3 pads = ivec3(\"+p+\", \"+d+\", \"+v+\");\\n      const float avgMultiplier = float(\"+m+\");\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int ch = coords.u;\\n\\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\\n        int dyDCorner = dyCorner.x;\\n        int dyRCorner = dyCorner.y;\\n        int dyCCorner = dyCorner.z;\\n\\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\\n        // dx(xD, xR, xC, ch).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n\\n        for (int wD = 0; wD < \"+l+\";\\n            wD += \"+u+\") {\\n          float dyD = float(dyDCorner + wD) / \"+o+\".0;\\n\\n          if (dyD < 0.0 || dyD >= \"+t.outDepth+\".0 || fract(dyD) > 0.0) {\\n            continue;\\n          }\\n          int idyD = int(dyD);\\n\\n          for (int wR = 0; wR < \"+h+\";\\n              wR += \"+s+\") {\\n            float dyR = float(dyRCorner + wR) / \"+a+\".0;\\n\\n            if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 ||\\n                fract(dyR) > 0.0) {\\n              continue;\\n            }\\n            int idyR = int(dyR);\\n\\n            for (int wC = 0; wC < \"+f+\";\\n                wC += \"+c+\") {\\n              float dyC = float(dyCCorner + wC) / \"+i+\".0;\\n\\n              if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                  fract(dyC) > 0.0) {\\n                continue;\\n              }\\n              int idyC = int(dyC);\\n\\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\\n\\n              dotProd += dyValue * avgMultiplier;\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),ha=function(){return function(t,e,n,r,o,a){this.outputShape=[],this.variableNames=[\"x\",\"mean\",\"variance\"],po(t,e),po(t,n);var i=\"0.0\";null!=r&&(po(t,r),this.variableNames.push(\"offset\"),i=\"getOffsetAtOutCoords()\");var u=\"1.0\";null!=o&&(po(t,o),this.variableNames.push(\"scale\"),u=\"getScaleAtOutCoords()\"),this.outputShape=t,this.userCode=\"\\n      void main() {\\n        float x = getXAtOutCoords();\\n        float mean = getMeanAtOutCoords();\\n        float variance = getVarianceAtOutCoords();\\n        float offset = \"+i+\";\\n        float scale = \"+u+\";\\n        float inv = scale * inversesqrt(variance + float(\"+a+\"));\\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\\n      }\\n    \"}}(),fa=function(){return function(t,e,n,r,o,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=[\"x\",\"mean\",\"variance\"],po(t,e),po(t,n);var i=\"vec4(0.0)\";null!=r&&(po(t,r),this.variableNames.push(\"offset\"),i=\"getOffsetAtOutCoords()\");var u=\"vec4(1.0)\";null!=o&&(po(t,o),this.variableNames.push(\"scale\"),u=\"getScaleAtOutCoords()\"),this.outputShape=t,this.userCode=\"\\n      void main() {\\n        vec4 offset = \"+i+\";\\n        vec4 scale = \"+u+\";\\n\\n        vec4 x = getXAtOutCoords();\\n        vec4 mean = getMeanAtOutCoords();\\n        vec4 variance = getVarianceAtOutCoords();\\n\\n        vec4 inv = scale * inversesqrt(variance + vec4(\"+a+\"));\\n\\n        setOutput((x - mean) * inv + offset);\\n      }\\n    \"}}(),pa=\"return areal * breal - aimag * bimag;\",da=\"return areal * bimag + aimag * breal;\",va=function(){return function(t,e,n){this.variableNames=[\"AReal\",\"AImag\",\"BReal\",\"BImag\"],this.outputShape=po(e,n),this.userCode=\"\\n      float binaryOpComplex(\\n          float areal, float aimag, float breal, float bimag) {\\n        \"+t+\"\\n      }\\n\\n      void main() {\\n        float areal = getARealAtOutCoords();\\n        float aimag = getAImagAtOutCoords();\\n        float breal = getBRealAtOutCoords();\\n        float bimag = getBImagAtOutCoords();\\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\\n      }\\n    \"}}(),ma=\"return a + b;\",ga=\"return a - b;\",ya=\"return a * b;\",xa=\"return (a < 0.) ? b * a : a;\",ba=function(){return function(t,e,n){this.variableNames=[\"A\",\"B\"],this.outputShape=po(e,n),this.userCode=\"\\n      float binaryOperation(float a, float b) {\\n        \"+t+\"\\n      }\\n\\n      void main() {\\n        float a = getAAtOutCoords();\\n        float b = getBAtOutCoords();\\n        setOutput(binaryOperation(a, b));\\n      }\\n    \"}}(),wa=\"\\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\\n\",Ca=function(){return function(t,e,n,r){void 0===r&&(r=!1),this.variableNames=[\"A\",\"B\"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=po(e,n);var o=this.outputShape.length,a=\"\";if(r)if(0===o||1===w(this.outputShape))a=\"\\n          result.y = 0.;\\n          result.z = 0.;\\n          result.w = 0.;\\n        \";else if(a=\"\\n          \"+aa(o)+\" coords = getOutputCoords();\\n        \",1===o)a+=\"\\n            result.y = (coords + 1) >= \"+this.outputShape[0]+\" ? 0. : result.y;\\n            result.z = 0.;\\n            result.w = 0.;\\n          \";else{var i=qo(\"coords\",o);a+=\"\\n            bool nextRowOutOfBounds =\\n              (\"+i[o-2]+\" + 1) >= \"+this.outputShape[o-2]+\";\\n            bool nextColOutOfBounds =\\n              (\"+i[o-1]+\" + 1) >= \"+this.outputShape[o-1]+\";\\n            result.y = nextColOutOfBounds ? 0. : result.y;\\n            result.z = nextRowOutOfBounds ? 0. : result.z;\\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\\n          \"}this.userCode=\"\\n      vec4 binaryOperation(vec4 a, vec4 b) {\\n        \"+t+\"\\n      }\\n\\n      void main() {\\n        vec4 a = getAAtOutCoords();\\n        vec4 b = getBAtOutCoords();\\n\\n        vec4 result = binaryOperation(a, b);\\n        \"+a+\"\\n\\n        setOutput(result);\\n      }\\n    \"}}(),Ea=function(){function t(t){this.variableNames=[\"A\"],this.outputShape=t,this.userCode=\"\\n      uniform float minVal;\\n      uniform float maxVal;\\n\\n      void main() {\\n        float value = getAAtOutCoords();\\n        if (isnan(value)) {\\n          setOutput(value);\\n          return;\\n        }\\n\\n        setOutput(clamp(value, minVal, maxVal));\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,o){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(o,\"minVal\"),n.maxLoc=r.getUniformLocationNoThrow(o,\"maxVal\")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e)}},t}(),Ra=function(){function t(t){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode=\"\\n      uniform float minVal;\\n      uniform float maxVal;\\n\\n      void main() {\\n        vec4 value = getAAtOutCoords();\\n\\n        if (any(isnan(value))) {\\n          setOutput(value);\\n          return;\\n        }\\n\\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,o){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(o,\"minVal\"),n.maxLoc=r.getUniformLocationNoThrow(o,\"maxVal\")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e)}},t}(),Ia=function(){return function(t){this.variableNames=[\"real\",\"imag\"],this.outputShape=t,this.userCode=\"\\n      void main() {\\n        float re = abs(getRealAtOutCoords());\\n        float im = abs(getImagAtOutCoords());\\n        float mx = max(re, im);\\n\\n        // sadly the length function in glsl is not underflow-safe\\n        // (at least not on Intel GPUs). So the safe solution is\\n        // to ensure underflow-safety in all cases.\\n        setOutput(\\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\\n        );\\n      }\\n    \"}}(),ka=function(){return function(t){this.outputShape=[],this.outputShape=bn(t,1),this.variableNames=t.map(function(t,e){return\"T\"+e});var e=new Array(t.length-1);e[0]=t[0][1];for(var n=1;n<e.length;n++)e[n]=e[n-1]+t[n][1];var r=[\"if (yC < \"+e[0]+\") setOutput(getT0(yR, yC));\"];for(n=1;n<e.length;n++){var o=e[n-1];r.push(\"else if (yC < \"+e[n]+\") setOutput(getT\"+n+\"(yR, yC-\"+o+\"));\")}var a=e.length,i=e[e.length-1];r.push(\"else setOutput(getT\"+a+\"(yR, yC-\"+i+\"));\"),this.userCode=\"\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int yR = coords.x;\\n        int yC = coords.y;\\n\\n        \"+r.join(\"\\n        \")+\"\\n      }\\n    \"}}(),Sa=function(){return function(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=bn(t,e);var n=this.outputShape,r=n.length,o=aa(r),a=qo(\"coords\",r),i=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"].slice(0,r);this.variableNames=t.map(function(t,e){return\"T\"+e});var u=new Array(t.length-1);u[0]=t[0][e];for(var s=1;s<u.length;s++)u[s]=u[s-1]+t[s][e];var c=i[e],l=i.slice(-2),h=i.join(),f=\"if (\"+c+\" < \"+u[0]+\") {\\n        return getChannel(\\n            getT0(\"+h+\"), vec2(\"+l.join()+\"));\\n        }\";for(s=1;s<u.length;s++){var p=u[s-1];f+=\"\\n        if (\"+c+\" < \"+u[s]+\"  && \"+c+\" >= \"+u[s-1]+\") {\\n          return getChannel(\\n            getT\"+s+\"(\"+Aa(i,c,p)+\"),\\n            vec2(\"+Aa(l,c,p)+\"));\\n        }\"}var d=u.length,v=u[u.length-1];f+=\"\\n        return getChannel(\\n          getT\"+d+\"(\"+Aa(i,c,v)+\"),\\n          vec2(\"+Aa(l,c,v)+\"));\",this.userCode=\"\\n      float getValue(\"+i.map(function(t){return\"int \"+t})+\") {\\n        \"+f+\"\\n      }\\n\\n      void main() {\\n        \"+o+\" coords = getOutputCoords();\\n        vec4 result = vec4(getValue(\"+a+\"), 0., 0., 0.);\\n\\n        \"+a[r-1]+\" = \"+a[r-1]+\" + 1;\\n        if (\"+a[r-1]+\" < \"+n[r-1]+\") {\\n          result.g = getValue(\"+a+\");\\n        }\\n\\n        \"+a[r-2]+\" = \"+a[r-2]+\" + 1;\\n        if (\"+a[r-2]+\" < \"+n[r-2]+\") {\\n          result.a = getValue(\"+a+\");\\n        }\\n\\n        \"+a[r-1]+\" = \"+a[r-1]+\" - 1;\\n        if (\"+a[r-2]+\" < \"+n[r-2]+\" &&\\n            \"+a[r-1]+\" < \"+n[r-1]+\") {\\n          result.b = getValue(\"+a+\");\\n        }\\n        setOutput(result);\\n      }\\n    \"}}();function Aa(t,e,n){var r=t.indexOf(e);return t.map(function(t,e){return e===r?t+\" - \"+n:t}).join()}var Da=function(){return function(t){this.variableNames=[\"x\",\"dy\"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,a=\"channelsLast\"===t.dataFormat;this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int wR = coords.x;\\n        int wC = coords.y;\\n        int d1 = coords.z;\\n        int d2 = coords.w;\\n\\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n\\n        for (int b = 0; b < \"+t.batchSize+\"; b++) {\\n          for (int yR = 0; yR < \"+t.outHeight+\"; yR++) {\\n            int xR = wR + yR * \"+e+\" - \"+r+\";\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int yC = 0; yC < \"+t.outWidth+\"; yC++) {\\n              int xC = wC + yC * \"+n+\" - \"+o+\";\\n\\n              if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                continue;\\n              }\\n\\n              if (\"+a+\") {\\n                float dyValue = getDy(b, yR, yC, d2);\\n                float xValue = getX(b, xR, xC, d1);\\n                dotProd += (xValue * dyValue);\\n              } else {\\n                float dyValue = getDy(b, d2, yR, yC);\\n                float xValue = getX(b, d1, xR, xC);\\n                dotProd += (xValue * dyValue);\\n              }\\n\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),Ta=function(){return function(t){this.variableNames=[\"dy\",\"W\"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=\"channelsLast\"===t.dataFormat,i=e-1-t.padInfo.top,u=n-1-t.padInfo.left,s=a?1:2,c=a?2:3,l=a?3:1;this.userCode=\"\\n      const ivec2 pads = ivec2(\"+i+\", \"+u+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int d1 = coords[\"+l+\"];\\n\\n        ivec2 dyCorner = ivec2(coords[\"+s+\"], coords[\"+c+\"]) - pads;\\n        int dyRCorner = dyCorner.x;\\n        int dyCCorner = dyCorner.y;\\n\\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        for (int wR = 0; wR < \"+e+\"; wR++) {\\n          float dyR = float(dyRCorner + wR) / \"+r+\".0;\\n\\n          if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 || fract(dyR) > 0.0) {\\n            continue;\\n          }\\n          int idyR = int(dyR);\\n\\n          int wRPerm = \"+e+\" - 1 - wR;\\n\\n          for (int wC = 0; wC < \"+n+\"; wC++) {\\n            float dyC = float(dyCCorner + wC) / \"+o+\".0;\\n\\n            if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                fract(dyC) > 0.0) {\\n              continue;\\n            }\\n            int idyC = int(dyC);\\n\\n            int wCPerm = \"+n+\" - 1 - wC;\\n\\n            for (int d2 = 0; d2 < \"+t.outChannels+\"; d2++) {\\n\\n              if (\"+a+\") {\\n                float xValue = getDy(batch, idyR, idyC, d2);\\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\\n                dotProd += xValue * wValue;\\n              } else {\\n                float xValue = getDy(batch, d2, idyR, idyC);\\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\\n                dotProd += xValue * wValue;\\n              }\\n\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),Na=function(){return function(t){this.variableNames=[\"x\",\"dy\"],this.outputShape=t.filterShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.padInfo.front,a=t.padInfo.top,i=t.padInfo.left;this.userCode=\"\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int wF = coords.x;\\n        int wR = coords.y;\\n        int wC = coords.z;\\n        int d1 = coords.w;\\n        int d2 = coords.u;\\n\\n        float dotProd = 0.0;\\n\\n        for (int b = 0; b < \"+t.batchSize+\"; b++) {\\n          for (int yF = 0; yF < \"+t.outDepth+\"; yF++) {\\n            int xF = wF + yF * \"+e+\" - \"+o+\";\\n\\n            if (xF < 0 || xF >= \"+t.inDepth+\") {\\n              continue;\\n            }\\n\\n            for (int yR = 0; yR < \"+t.outHeight+\"; yR++) {\\n              int xR = wR + yR * \"+n+\" - \"+a+\";\\n\\n              if (xR < 0 || xR >= \"+t.inHeight+\") {\\n                continue;\\n              }\\n\\n              for (int yC = 0; yC < \"+t.outWidth+\"; yC++) {\\n                int xC = wC + yC * \"+r+\" - \"+i+\";\\n\\n                if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                  continue;\\n                }\\n\\n                float dyValue = getDy(b, yF, yR, yC, d2);\\n                float xValue = getX(b, xF, xR, xC, d1);\\n                dotProd += (xValue * dyValue);\\n              }\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),Fa=function(){return function(t){this.variableNames=[\"dy\",\"W\"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,u=e-1-t.padInfo.front,s=n-1-t.padInfo.top,c=r-1-t.padInfo.left;this.userCode=\"\\n      const ivec3 pads = ivec3(\"+u+\", \"+s+\", \"+c+\");\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int d1 = coords.u;\\n\\n\\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\\n        int dyFCorner = dyCorner.x;\\n        int dyRCorner = dyCorner.y;\\n        int dyCCorner = dyCorner.z;\\n\\n        float dotProd = 0.0;\\n        for (int wF = 0; wF < \"+e+\"; wF++) {\\n          float dyF = float(dyFCorner + wF) / \"+o+\".0;\\n\\n          if (dyF < 0.0 || dyF >= \"+t.outDepth+\".0 || fract(dyF) > 0.0) {\\n            continue;\\n          }\\n          int idyF = int(dyF);\\n\\n          int wFPerm = \"+e+\" - 1 - wF;\\n\\n          for (int wR = 0; wR < \"+n+\"; wR++) {\\n            float dyR = float(dyRCorner + wR) / \"+a+\".0;\\n\\n            if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 ||\\n              fract(dyR) > 0.0) {\\n              continue;\\n            }\\n            int idyR = int(dyR);\\n\\n            int wRPerm = \"+n+\" - 1 - wR;\\n\\n            for (int wC = 0; wC < \"+r+\"; wC++) {\\n              float dyC = float(dyCCorner + wC) / \"+i+\".0;\\n\\n              if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                  fract(dyC) > 0.0) {\\n                continue;\\n              }\\n              int idyC = int(dyC);\\n\\n              int wCPerm = \"+r+\" - 1 - wC;\\n\\n              for (int d2 = 0; d2 < \"+t.outChannels+\"; d2++) {\\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\\n                dotProd += xValue * wValue;\\n              }\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),_a=function(){return function(t){this.variableNames=[\"x\",\"dy\"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,a=t.outChannels/t.inChannels;this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int wR = coords.x;\\n        int wC = coords.y;\\n        int d1 = coords.z;\\n        int dm = coords.w;\\n        int d2 = d1 * \"+a+\" + dm;\\n\\n        float dotProd = 0.0;\\n\\n        // TO DO: Vec4 over the batch size\\n        for (int b = 0; b < \"+t.batchSize+\"; b++) {\\n          for (int yR = 0; yR < \"+t.outHeight+\"; yR++) {\\n            int xR = wR + yR * \"+e+\" - \"+r+\";\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int yC = 0; yC < \"+t.outWidth+\"; yC++) {\\n              int xC = wC + yC * \"+n+\" - \"+o+\";\\n\\n              if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                continue;\\n              }\\n\\n              float dyValue = getDy(b, yR, yC, d2);\\n              float xValue = getX(b, xR, xC, d1);\\n              dotProd += (xValue * dyValue);\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),Oa=function(){return function(t){this.variableNames=[\"dy\",\"W\"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=e-1-t.padInfo.top,i=n-1-t.padInfo.left,u=t.outChannels/t.inChannels;this.userCode=\"\\n      const ivec2 pads = ivec2(\"+a+\", \"+i+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int d1 = coords[3];\\n        ivec2 dyCorner = coords.yz - pads;\\n        int dyRCorner = dyCorner.x;\\n        int dyCCorner = dyCorner.y;\\n\\n        float dotProd = 0.0;\\n\\n        for (int wR = 0; wR < \"+e+\"; wR++) {\\n          float dyR = float(dyRCorner + wR) / \"+r+\".0;\\n\\n          if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 || fract(dyR) > 0.0) {\\n            continue;\\n          }\\n          int idyR = int(dyR);\\n\\n          int wRPerm = \"+e+\" - 1 - wR;\\n\\n          for (int wC = 0; wC < \"+n+\"; wC++) {\\n            float dyC = float(dyCCorner + wC) / \"+o+\".0;\\n\\n            if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                fract(dyC) > 0.0) {\\n              continue;\\n            }\\n            int idyC = int(dyC);\\n\\n            int wCPerm = \"+n+\" - 1 - wC;\\n\\n            // TO DO: Vec4 over the channelMul\\n            for (int dm = 0; dm < \"+u+\"; dm++) {\\n              int d2 = d1 * \"+u+\" + dm;\\n              float xValue = getDy(batch, idyR, idyC, d2);\\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\\n              dotProd += xValue * wValue;\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),Ma=function(){return function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=[\"x\",\"W\"],this.outputShape=t.outShape;var o=t.padInfo.top,a=t.padInfo.left,i=t.strideHeight,u=t.strideWidth,s=t.dilationHeight,c=t.dilationWidth,l=t.filterHeight,h=t.filterWidth,f=4*Math.floor(t.inChannels/4),p=t.inChannels%4,d=\"channelsLast\"===t.dataFormat,v=d?1:2,m=d?2:3,g=d?3:1,y=\"\",x=\"\";n&&(y=r?\"float activation(float a) {\\n          float b = getPreluActivationWeightsAtOutCoords();\\n          \"+n+\"\\n        }\":\"\\n          float activation(float x) {\\n            \"+n+\"\\n          }\\n        \",x=\"result = activation(result);\");var b=e?\"result += getBiasAtOutCoords();\":\"\";e&&this.variableNames.push(\"bias\"),r&&this.variableNames.push(\"preluActivationWeights\"),this.userCode=\"\\n      \"+y+\"\\n\\n      const ivec2 strides = ivec2(\"+i+\", \"+u+\");\\n      const ivec2 pads = ivec2(\"+o+\", \"+a+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int d2 = coords[\"+g+\"];\\n\\n        ivec2 xRCCorner =\\n            ivec2(coords[\"+v+\"], coords[\"+m+\"]) * strides - pads;\\n        int xRCorner = xRCCorner.x;\\n        int xCCorner = xRCCorner.y;\\n\\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        for (int wR = 0; wR < \"+l+\"; wR++) {\\n          int xR = xRCorner + wR * \"+s+\";\\n\\n          if (xR < 0 || xR >= \"+t.inHeight+\") {\\n            continue;\\n          }\\n\\n          for (int wC = 0; wC < \"+h+\"; wC++) {\\n            int xC = xCCorner + wC * \"+c+\";\\n\\n            if (xC < 0 || xC >= \"+t.inWidth+\") {\\n              continue;\\n            }\\n\\n            for (int d1 = 0; d1 < \"+f+\"; d1 += 4) {\\n              vec4 wValues = vec4(\\n                getW(wR, wC, d1, d2),\\n                getW(wR, wC, d1 + 1, d2),\\n                getW(wR, wC, d1 + 2, d2),\\n                getW(wR, wC, d1 + 3, d2)\\n              );\\n\\n              if (\"+d+\") {\\n                vec4 xValues = vec4(\\n                  getX(batch, xR, xC, d1),\\n                  getX(batch, xR, xC, d1 + 1),\\n                  getX(batch, xR, xC, d1 + 2),\\n                  getX(batch, xR, xC, d1 + 3)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              } else {\\n                vec4 xValues = vec4(\\n                  getX(batch, d1, xR, xC),\\n                  getX(batch, d1 + 1, xR, xC),\\n                  getX(batch, d1 + 2, xR, xC),\\n                  getX(batch, d1 + 3, xR, xC)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              }\\n            }\\n\\n            if (\"+(1===p)+\") {\\n\\n              if (\"+d+\") {\\n                dotProd +=\\n                    getX(batch, xR, xC, \"+f+\") *\\n                    getW(wR, wC, \"+f+\", d2);\\n              } else {\\n                dotProd +=\\n                    getX(batch, \"+f+\", xR, xC) *\\n                    getW(wR, wC, \"+f+\", d2);\\n              }\\n\\n            } else if (\"+(2===p)+\") {\\n              vec2 wValues = vec2(\\n                getW(wR, wC, \"+f+\", d2),\\n                getW(wR, wC, \"+f+\" + 1, d2)\\n              );\\n\\n              if (\"+d+\") {\\n                vec2 xValues = vec2(\\n                  getX(batch, xR, xC, \"+f+\"),\\n                  getX(batch, xR, xC, \"+f+\" + 1)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              } else {\\n                vec2 xValues = vec2(\\n                  getX(batch, \"+f+\", xR, xC),\\n                  getX(batch, \"+f+\" + 1, xR, xC)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              }\\n\\n            } else if (\"+(3===p)+\") {\\n              vec3 wValues = vec3(\\n                getW(wR, wC, \"+f+\", d2),\\n                getW(wR, wC, \"+f+\" + 1, d2),\\n                getW(wR, wC, \"+f+\" + 2, d2)\\n              );\\n\\n              if (\"+d+\") {\\n                vec3 xValues = vec3(\\n                  getX(batch, xR, xC, \"+f+\"),\\n                  getX(batch, xR, xC, \"+f+\" + 1),\\n                  getX(batch, xR, xC, \"+f+\" + 2)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              } else {\\n                vec3 xValues = vec3(\\n                  getX(batch, \"+f+\", xR, xC),\\n                  getX(batch, \"+f+\" + 1, xR, xC),\\n                  getX(batch, \"+f+\" + 2, xR, xC)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              }\\n\\n            }\\n          }\\n        }\\n\\n        float result = dotProd;\\n        \"+b+\"\\n        \"+x+\"\\n        setOutput(result);\\n      }\\n    \"}}(),Ba=function(){return function(t){this.variableNames=[\"x\",\"W\"],this.outputShape=t.outShape;var e=t.padInfo.front,n=t.padInfo.top,r=t.padInfo.left,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,u=t.dilationDepth,s=t.dilationHeight,c=t.dilationWidth,l=t.filterDepth,h=t.filterHeight,f=t.filterWidth,p=4*Math.floor(t.inChannels/4),d=t.inChannels%4;this.userCode=\"\\n      const ivec3 strides = ivec3(\"+o+\", \"+a+\", \"+i+\");\\n      const ivec3 pads = ivec3(\"+e+\", \"+n+\", \"+r+\");\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int d2 = coords.u;\\n\\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\\n        int xFCorner = xFRCCorner.x;\\n        int xRCorner = xFRCCorner.y;\\n        int xCCorner = xFRCCorner.z;\\n\\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\\n        // values in that axis.\\n        float dotProd = 0.0;\\n        for (int wF = 0; wF < \"+l+\"; wF++) {\\n          int xF = xFCorner + wF * \"+u+\";\\n\\n          if (xF < 0 || xF >= \"+t.inDepth+\") {\\n            continue;\\n          }\\n\\n          for (int wR = 0; wR < \"+h+\"; wR++) {\\n            int xR = xRCorner + wR * \"+s+\";\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int wC = 0; wC < \"+f+\"; wC++) {\\n              int xC = xCCorner + wC * \"+c+\";\\n\\n              if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                continue;\\n              }\\n\\n              for (int d1 = 0; d1 < \"+p+\"; d1 += 4) {\\n                vec4 xValues = vec4(\\n                  getX(batch, xF, xR, xC, d1),\\n                  getX(batch, xF, xR, xC, d1 + 1),\\n                  getX(batch, xF, xR, xC, d1 + 2),\\n                  getX(batch, xF, xR, xC, d1 + 3)\\n                );\\n                vec4 wValues = vec4(\\n                  getW(wF, wR, wC, d1, d2),\\n                  getW(wF, wR, wC, d1 + 1, d2),\\n                  getW(wF, wR, wC, d1 + 2, d2),\\n                  getW(wF, wR, wC, d1 + 3, d2)\\n                );\\n\\n                dotProd += dot(xValues, wValues);\\n              }\\n\\n              if (\"+(1===d)+\") {\\n                dotProd +=\\n                  getX(batch, xF, xR, xC, \"+p+\") *\\n                  getW(wF, wR, wC, \"+p+\", d2);\\n              } else if (\"+(2===d)+\") {\\n                vec2 xValues = vec2(\\n                  getX(batch, xF, xR, xC, \"+p+\"),\\n                  getX(batch, xF, xR, xC, \"+p+\" + 1)\\n                );\\n                vec2 wValues = vec2(\\n                  getW(wF, wR, wC, \"+p+\", d2),\\n                  getW(wF, wR, wC, \"+p+\" + 1, d2)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              } else if (\"+(3===d)+\") {\\n                vec3 xValues = vec3(\\n                  getX(batch, xF, xR, xC, \"+p+\"),\\n                  getX(batch, xF, xR, xC, \"+p+\" + 1),\\n                  getX(batch, xF, xR, xC, \"+p+\" + 2)\\n                );\\n                vec3 wValues = vec3(\\n                  getW(wF, wR, wC, \"+p+\", d2),\\n                  getW(wF, wR, wC, \"+p+\" + 1, d2),\\n                  getW(wF, wR, wC, \"+p+\" + 2, d2)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              }\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),Pa=function(){return function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=[\"x\",\"W\"],this.outputShape=t.outShape;var o=t.inHeight,a=t.inWidth,i=t.padInfo.top,u=t.padInfo.left,s=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,p=t.filterWidth,d=t.outChannels/t.inChannels,v=\"\",m=\"\";n&&(v=r?\"float activation(float a) {\\n          float b = getPreluActivationWeightsAtOutCoords();\\n          \"+n+\"\\n        }\":\"\\n          float activation(float x) {\\n            \"+n+\"\\n          }\\n        \",m=\"result = activation(result);\");var g=e?\"result += getBiasAtOutCoords();\":\"\";e&&this.variableNames.push(\"bias\"),r&&this.variableNames.push(\"preluActivationWeights\"),this.userCode=\"\\n      \"+v+\"\\n\\n      const ivec2 strides = ivec2(\"+s+\", \"+c+\");\\n      const ivec2 pads = ivec2(\"+i+\", \"+u+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords.x;\\n        ivec2 xRCCorner = coords.yz * strides - pads;\\n        int d2 = coords.w;\\n        int d1 = d2 / \"+d+\";\\n        int q = d2 - d1 * \"+d+\";\\n\\n        int xRCorner = xRCCorner.x;\\n        int xCCorner = xRCCorner.y;\\n\\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\\n        for (int wR = 0; wR < \"+f+\"; wR++) {\\n          int xR = xRCorner + wR * \"+l+\";\\n\\n          if (xR < 0 || xR >= \"+o+\") {\\n            continue;\\n          }\\n\\n          for (int wC = 0; wC < \"+p+\"; wC++) {\\n            int xC = xCCorner + wC * \"+h+\";\\n\\n            if (xC < 0 || xC >= \"+a+\") {\\n              continue;\\n            }\\n\\n            float xVal = getX(batch, xR, xC, d1);\\n            float wVal = getW(wR, wC, d1, q);\\n            dotProd += xVal * wVal;\\n          }\\n        }\\n\\n        float result = dotProd;\\n        \"+g+\"\\n        \"+m+\"\\n        setOutput(result);\\n      }\\n    \"}}(),La=function(){return function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=[\"x\",\"W\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.outShape;for(var o=t.inHeight,a=t.inWidth,i=t.padInfo.top,u=t.padInfo.left,s=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,p=t.filterWidth,d=p,m=\"int xR; int xC; int xCOffset;\",g=0;g<f;g++)for(var y=0;y<p;y++)m+=\"\\n          vec4 xTexelR\"+g+\"C\"+2*y+\" = vec4(0.);\\n          vec4 wR\"+g+\"C\"+y+\" = vec4(0.);\\n          vec4 xR\"+g+\"C\"+y+\" = vec4(0.);\";for(g=0;g<f;g++)for(var x=0;x<d;x++){if(m+=\"\\n          xR = xRCorner + \"+g*l+\";\\n          xC = xCCorner + \"+(y=2*x)*h+\";\\n        \",1===c){if(y<p&&(m+=u%2==1?\"\\n                xCOffset = xC + 1;\\n                if(xR >= 0 && xR < \"+o+\" && xCOffset >= 0 && xCOffset < \"+a+\") {\\n                  xTexelR\"+g+\"C\"+y+\" = getX(batch, xR, xCOffset, d1);\\n                } else {\\n                  xTexelR\"+g+\"C\"+y+\" = vec4(0.);\\n                }\\n\\n                xCOffset = xC + 1 - 2;\\n                if(xR >= 0 && xR < \"+o+\" && xCOffset >= 0 && xCOffset < \"+a+\") {\\n                  vec4 previous = getX(batch, xR, xCOffset, d1);\\n                  xR\"+g+\"C\"+y+\" = vec4(previous.zw, xTexelR\"+g+\"C\"+y+\".xy);\\n                } else {\\n                  xR\"+g+\"C\"+y+\" = vec4(0, 0, xTexelR\"+g+\"C\"+y+\".xy);\\n                }\\n              \":\"\\n                if(xR >= 0 && xR < \"+o+\" && xC >= 0 && xC < \"+a+\") {\\n                  xTexelR\"+g+\"C\"+y+\" = getX(batch, xR, xC, d1);\\n                } else {\\n                  xTexelR\"+g+\"C\"+y+\" = vec4(0.);\\n                }\\n\\n                xR\"+g+\"C\"+y+\" = xTexelR\"+g+\"C\"+y+\";\\n              \",y+1<p)){var b=u%2==0?v(h):h;h%2==0&&u%2==1||h%2!=0&&u%2!=1?(m+=\"\\n                  xCOffset = xC + \"+u%2+\" + \"+b+\";\\n\\n                  if(xR >= 0 && xR < \"+o+\" &&\\n                    xCOffset >= 0 && xCOffset < \"+a+\") {\\n                    xTexelR\"+g+\"C\"+(y+2)+\" = getX(batch, xR, xCOffset, d1);\\n                  }\\n                \",h>1&&(m+=\"\\n                    xCOffset -= 2;\\n                    if(xR >= 0 && xR < \"+o+\" &&\\n                      xCOffset >= 0 && xCOffset < \"+a+\") {\\n                      xTexelR\"+g+\"C\"+y+\" = getX(batch, xR, xCOffset, d1);\\n                    } else {\\n                      xTexelR\"+g+\"C\"+y+\" = vec4(0.);\\n                    }\\n                  \"),m+=\"\\n                  xR\"+g+\"C\"+(y+1)+\" = vec4(\\n                    xTexelR\"+g+\"C\"+y+\".zw, xTexelR\"+g+\"C\"+(y+2)+\".xy);\\n                \"):m+=\"\\n                  xCOffset = xC + \"+b+\";\\n\\n                  if(xR >= 0 && xR < \"+o+\" &&\\n                    xCOffset >= 0 && xCOffset < \"+a+\") {\\n                    xTexelR\"+g+\"C\"+(y+2)+\" = getX(batch, xR, xCOffset, d1);\\n                  }\\n\\n                  xR\"+g+\"C\"+(y+1)+\" = xTexelR\"+g+\"C\"+(y+2)+\";\\n                \"}}else y<p&&(m+=\"\\n              if(xR >= 0 && xR < \"+o+\") {\\n            \",u%2==1?(m+=\"\\n                xCOffset = xC + 1 - \"+c+\";\\n                if(xCOffset >= 0 && xCOffset < \"+a+\") {\\n                  xTexelR\"+g+\"C\"+y+\" = getX(batch, xR, xCOffset, d1);\\n                } else {\\n                  xTexelR\"+g+\"C\"+y+\" = vec4(0.);\\n                }\\n\\n                if(xC + 1 >= 0 && xC + 1 < \"+a+\") {\\n                  xTexelR\"+g+\"C\"+(y+2)+\" = getX(batch, xR, xC + 1, d1);\\n                } else {\\n                  xTexelR\"+g+\"C\"+(y+2)+\" = vec4(0.);\\n                }\\n\\n                xR\"+g+\"C\"+y+\" = vec4(\\n                  xTexelR\"+g+\"C\"+y+\".zw, xTexelR\"+g+\"C\"+(y+2)+\".zw);\\n              \",y+1<p&&(m+=\"\\n                  vec4 final = vec4(0.);\\n                  xCOffset = xC + 1 + \"+c+\";\\n                  if(xCOffset >= 0 && xCOffset < \"+a+\") {\\n                    final = getX(batch, xR, xCOffset, d1);\\n                  }\\n                  xR\"+g+\"C\"+(y+1)+\" = vec4(xTexelR\"+g+\"C\"+(y+2)+\".xy, final.xy);\\n                \")):(m+=\"\\n                if(xC >= 0 && xC < \"+a+\") {\\n                  xTexelR\"+g+\"C\"+y+\" = getX(batch, xR, xC, d1);\\n                } else {\\n                  xTexelR\"+g+\"C\"+y+\" = vec4(0.);\\n                }\\n\\n                xCOffset = xC + \"+c+\";\\n                if(xCOffset >= 0 && xCOffset < \"+a+\") {\\n                  xTexelR\"+g+\"C\"+(y+2)+\" = getX(batch, xR, xCOffset, d1);\\n                } else {\\n                  xTexelR\"+g+\"C\"+(y+2)+\" = vec4(0.);\\n                }\\n\\n                xR\"+g+\"C\"+y+\" = vec4(\\n                  xTexelR\"+g+\"C\"+y+\".xy, xTexelR\"+g+\"C\"+(y+2)+\".xy);\\n              \",y+1<p&&(m+=\"\\n                  xR\"+g+\"C\"+(y+1)+\" = vec4(\\n                    xTexelR\"+g+\"C\"+y+\".zw, xTexelR\"+g+\"C\"+(y+2)+\".zw);\\n                \")),m+=\"}\");y<p&&(m+=\"\\n            vec4 wTexelR\"+g+\"C\"+y+\" = getW(\"+g+\", \"+y+\", d1, q);\\n            wR\"+g+\"C\"+y+\" = vec4(wTexelR\"+g+\"C\"+y+\".xz, wTexelR\"+g+\"C\"+y+\".xz);\\n          \",y+1<p&&(m+=\"\\n              vec4 wTexelR\"+g+\"C\"+(y+1)+\" = getW(\"+g+\", \"+(y+1)+\", d1, q);\\n              wR\"+g+\"C\"+(y+1)+\" =\\n                vec4(wTexelR\"+g+\"C\"+(y+1)+\".xz, wTexelR\"+g+\"C\"+(y+1)+\".xz);\"))}for(g=0;g<f;g++)for(y=0;y<p;y++)m+=\"dotProd += xR\"+g+\"C\"+y+\" * wR\"+g+\"C\"+y+\";\";var w=\"\",C=\"\";n&&(w=r?\"vec4 activation(vec4 a) {\\n          vec4 b = getPreluActivationWeightsAtOutCoords();\\n          \"+n+\"\\n        }\":\"vec4 activation(vec4 x) {\\n          \"+n+\"\\n        }\",C=\"result = activation(result);\");var E=e?\"result += getBiasAtOutCoords();\":\"\";e&&this.variableNames.push(\"bias\"),r&&this.variableNames.push(\"preluActivationWeights\"),this.userCode=\"\\n      \"+w+\"\\n\\n      const ivec2 strides = ivec2(\"+s+\", \"+c+\");\\n      const ivec2 pads = ivec2(\"+i+\", \"+u+\");\\n\\n      void main() {\\n\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords.x;\\n        ivec2 xRCCorner = coords.yz * strides - pads;\\n        int d2 = coords.w;\\n        int d1 = d2;\\n        int q = 0;\\n        int xRCorner = xRCCorner.x;\\n        int xCCorner = xRCCorner.y;\\n\\n        vec4 dotProd = vec4(0.);\\n\\n        \"+m+\"\\n\\n        vec4 result = dotProd;\\n        \"+E+\"\\n        \"+C+\"\\n        setOutput(result);\\n      }\\n    \"}}(),Wa=function(){return function(t,e,n,r,o){this.variableNames=[\"Image\",\"Boxes\",\"BoxInd\"],this.outputShape=[];var a=t[0],i=t[1],u=t[2],s=t[3],c=e[0],l=n[0],h=n[1];this.outputShape=[c,l,h,s];var f=\"bilinear\"===r?1:0,p=[i-1+\".0\",u-1+\".0\"],d=p[0],v=p[1],m=l>1?[\"\"+(i-1)/(l-1),\"(y2-y1) * height_ratio\",\"y1*\"+d+\" + float(y)*(height_scale)\"]:[\"0.0\",\"0.0\",\"0.5 * (y1+y2) * \"+d],g=m[0],y=m[1],x=m[2],b=h>1?[\"\"+(u-1)/(h-1),\"(x2-x1) * width_ratio\",\"x1*\"+v+\" + float(x)*(width_scale)\"]:[\"0.0\",\"0.0\",\"0.5 * (x1+x2) * \"+v],w=b[0],C=b[1],E=b[2];this.userCode=\"\\n      const float height_ratio = float(\"+g+\");\\n      const float width_ratio = float(\"+w+\");\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int y = coords[1];\\n        int x = coords[2];\\n        int d = coords[3];\\n\\n        // get box vals\\n        float y1 = getBoxes(b,0);\\n        float x1 = getBoxes(b,1);\\n        float y2 = getBoxes(b,2);\\n        float x2 = getBoxes(b,3);\\n\\n        // get image in batch index\\n        int bInd = round(getBoxInd(b));\\n        if(bInd < 0 || bInd >= \"+a+\") {\\n          return;\\n        }\\n\\n        float height_scale = \"+y+\";\\n        float width_scale = \"+C+\";\\n\\n        float in_y = \"+x+\";\\n        if( in_y < 0.0 || in_y > \"+d+\" ) {\\n          setOutput(float(\"+o+\"));\\n          return;\\n        }\\n        float in_x = \"+E+\";\\n        if( in_x < 0.0 || in_x > \"+v+\" ) {\\n          setOutput(float(\"+o+\"));\\n          return;\\n        }\\n\\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\\n        if(\"+f+\" == 1) {\\n          // Compute the four integer indices.\\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\\n\\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\\n\\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\\n\\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\\n          float newValue = top + (bottom - top) * fracCR.y;\\n          setOutput(newValue);\\n        } else {\\n          // Compute the coordinators of nearest neighbor point.\\n          ivec2 sourceNearestCR = ivec2(floor(\\n            sourceFracIndexCR + vec2(0.5,0.5)));\\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\\n          setOutput(newValue);\\n        }\\n      }\\n    \"}}(),Ua=function(){return function(t,e,n){this.variableNames=[\"x\"],this.outputShape=t;var r=t.length,o=t[t.length-1],a=n?\"<\":\">\";this.userCode=\"\\n      int getIndex(int i) {\\n        \"+(n?\"return \"+o+\" -i - 1;\":\"return i;\")+\"\\n      }\\n\\n      void main() {\\n        \"+aa(r)+\" coords = getOutputCoords();\\n        int end = \"+Va(r,\"coords\")+\";\\n        float val = 0.0;\\n        for (int i = \"+o+\" - 1; i >= 0; i -= 1) {\\n          int idx = getIndex(i);\\n          if (idx \"+a+\" end) {\\n            continue;\\n          }\\n          if (idx == end && \"+e+\") {\\n            continue;\\n          }\\n          \"+Va(r,\"coords\")+\" = idx;\\n          val += getX(\"+function(t,e){if(1===t)return\"\"+e;if(2===t)return e+\".x, \"+e+\".y\";if(3===t)return e+\".x, \"+e+\".y, \"+e+\".z\";if(4===t)return e+\".x, \"+e+\".y, \"+e+\".z, \"+e+\".w\";throw Error(\"Cumulative sum for rank \"+t+\" is not yet supported\")}(r,\"coords\")+\");\\n        }\\n        setOutput(val);\\n      }\\n    \"}}();function Va(t,e){if(1===t)return\"\"+e;if(2===t)return e+\".y\";if(3===t)return e+\".z\";if(4===t)return e+\".w\";throw Error(\"Cumulative sum for rank \"+t+\" is not yet supported\")}var za=function(){return function(t){this.variableNames=[\"A\"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Ot.DENSE;var e=zt(t),n=Ko();this.outputShape=t,this.userCode=\"\\n      ivec3 outCoordsFromFlatIndex(int index) {\\n        \"+jo([\"r\",\"c\",\"d\"],t)+\"\\n        return ivec3(r, c, d);\\n      }\\n\\n      void main() {\\n        ivec2 resTexRC = ivec2(resultUV.yx *\\n          vec2(\"+e[0]+\", \"+e[1]+\"));\\n        int index = 4 * (resTexRC.x * \"+e[1]+\" + resTexRC.y);\\n\\n        vec4 result = vec4(0.);\\n\\n        for (int i=0; i<4; i++) {\\n          int flatIndex = index + i;\\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\\n          result[i] = getA(rc.x, rc.y, rc.z);\\n        }\\n\\n        \"+n.output+\" = result;\\n      }\\n    \"}}(),Ga=function(){return function(t){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Ot.DENSE;var e=zt(t),n=Ko();this.outputShape=t,this.userCode=\"\\n      ivec3 outCoordsFromFlatIndex(int index) {\\n        \"+jo([\"r\",\"c\",\"d\"],t)+\"\\n        return ivec3(r, c, d);\\n      }\\n\\n      void main() {\\n        ivec2 resTexRC = ivec2(resultUV.yx *\\n          vec2(\"+e[0]+\", \"+e[1]+\"));\\n        int index = 4 * (resTexRC.x * \"+e[1]+\" + resTexRC.y);\\n\\n        vec4 result = vec4(0.);\\n\\n        for (int i=0; i<4; i++) {\\n          int flatIndex = index + i;\\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\\n        }\\n\\n        \"+n.output+\" = result;\\n      }\\n    \"}}(),Ha=function(){function t(t,e,n){this.variableNames=[\"x\"],this.outputShape=[],this.outputShape=t,this.blockSize=e,this.dataFormat=n,this.userCode=\"\\n    void main() {\\n      ivec4 coords = getOutputCoords();\\n      int b = coords[0];\\n      int h = \"+this.getHeightCoordString()+\";\\n      int w = \"+this.getWidthCoordString()+\";\\n      int d = \"+this.getDepthCoordString()+\";\\n\\n      int in_h = h / \"+e+\";\\n      int offset_h = imod(h, \"+e+\");\\n      int in_w = w / \"+e+\";\\n      int offset_w = imod(w, \"+e+\");\\n      int offset_d = (offset_h * \"+e+\" + offset_w) *\\n        \"+this.getOutputDepthSize()+\";\\n      int in_d = d + offset_d;\\n\\n      float result = \"+this.getInputSamplingString()+\";\\n      setOutput(result);\\n    }\\n  \"}return t.prototype.getHeightCoordString=function(){return\"NHWC\"===this.dataFormat?\"coords[1]\":\"coords[2]\"},t.prototype.getWidthCoordString=function(){return\"NHWC\"===this.dataFormat?\"coords[2]\":\"coords[3]\"},t.prototype.getDepthCoordString=function(){return\"NHWC\"===this.dataFormat?\"coords[3]\":\"coords[1]\"},t.prototype.getOutputDepthSize=function(){return\"NHWC\"===this.dataFormat?this.outputShape[3]:this.outputShape[1]},t.prototype.getInputSamplingString=function(){return\"NHWC\"===this.dataFormat?\"getX(b, in_h, in_w, in_d)\":\"getX(b, in_d, in_h, in_w)\"},t}(),qa=function(){return function(t){this.variableNames=[\"X\"],this.outputShape=[t,t],this.userCode=\"\\n      void main() {\\n          ivec2 coords = getOutputCoords();\\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\\n          setOutput(val);\\n      }\\n    \"}}(),Ka=function(){return function(t){this.variableNames=[\"A\"],this.outTexUsage=Mt.DOWNLOAD;var e=Ko();this.outputShape=t,this.userCode=\"\\n      \"+$o+\"\\n\\n      void main() {\\n        float x = getAAtOutCoords();\\n        \"+e.output+\" = encode_float(x);\\n      }\\n    \"}}(),ja=function(){return function(t){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Mt.DOWNLOAD;var e=Ko();this.outputShape=t,this.userCode=\"\\n      \"+$o+\"\\n\\n      void main() {\\n        ivec3 coords = getOutputCoords();\\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\\n        \"+e.output+\" = encode_float(x);\\n      }\\n    \"}}(),Xa=function(){return function(t,e,n){void 0===n&&(n=!1),this.variableNames=[\"A\"];var r=Ko(),o=e[0],a=e[1];this.outputShape=t;var i=\"result\";n&&(i=\"floor(result * 255. + 0.5)\"),this.userCode=\"\\n      \"+Xo(t)+\"\\n\\n      void main() {\\n        ivec3 coords = getOutputCoords();\\n\\n        int flatIndex = getFlatIndex(coords);\\n        int offset = imod(flatIndex, 4);\\n\\n        flatIndex = idiv(flatIndex, 4, 1.);\\n        \\n        int r = flatIndex / \"+a+\";\\n        int c = imod(flatIndex, \"+a+\");\\n        vec2 uv = (vec2(c, r) + halfCR) / vec2(\"+a+\".0, \"+o+\".0);\\n        vec4 values = \"+r.texture2D+\"(A, uv);\\n\\n        float result;\\n\\n        if(offset == 0) {\\n          result = values[0];\\n        } else if(offset == 1) {\\n          result = values[1];\\n        } else if(offset == 2) {\\n          result = values[2];\\n        } else {\\n          result = values[3];\\n        }\\n\\n        \"+r.output+\" = vec4(\"+i+\", 0., 0., 0.);\\n      }\\n    \"}}(),$a=function(){return function(t,e,n){void 0===n&&(n=!1),this.variableNames=[\"A\"],this.packedInputs=!1,this.packedOutput=!0;var r=Ko(),o=e[0],a=e[1];this.outputShape=t;var i=\"\",u=\"result\";n&&(u=\"floor(result * 255. + 0.5)\");for(var s=0;s<=1;s++)for(var c=0;c<=1;c++){var l=2*s+c;i+=\"\\n          localCoords = coords;\\n          if(localCoords[2] + \"+c+\" < \"+t[2]+\") {\\n            localCoords[2] += \"+c+\";\\n            if(localCoords[1] + \"+s+\" < \"+t[1]+\") {\\n              localCoords[1] += \"+s+\";\\n\\n              flatIndex = getFlatIndex(localCoords);\\n              offset = imod(flatIndex, 4);\\n\\n              flatIndex = idiv(flatIndex, 4, 1.);\\n\\n              r = flatIndex / \"+a+\";\\n              c = imod(flatIndex, \"+a+\");\\n              uv = (vec2(c, r) + halfCR) / vec2(\"+a+\".0, \"+o+\".0);\\n              values = \"+r.texture2D+\"(A, uv);\\n\\n              if(offset == 0) {\\n                result[\"+l+\"] = values[0];\\n              } else if(offset == 1) {\\n                result[\"+l+\"] = values[1];\\n              } else if(offset == 2) {\\n                result[\"+l+\"] = values[2];\\n              } else {\\n                result[\"+l+\"] = values[3];\\n              }\\n            }\\n          }\\n        \"}this.userCode=\"\\n      \"+Xo(t)+\"\\n\\n      void main() {\\n        ivec3 coords = getOutputCoords();\\n\\n        vec4 result = vec4(0.);\\n        int flatIndex, r, c, offset;\\n        ivec3 localCoords;\\n        vec2 uv;\\n        vec4 values;\\n\\n        \"+i+\"\\n\\n        \"+r.output+\" = \"+u+\";\\n      }\\n    \"}}(),Ya=\"return real * expR - imag * expI;\",Qa=\"return real * expI + imag * expR;\",Ja=function(){return function(t,e,n){this.variableNames=[\"real\",\"imag\"];var r=e[1];this.outputShape=e;var o=n?\"2.0 * \"+Math.PI:\"-2.0 * \"+Math.PI,a=n?r+\".0\":\"1.0\";this.userCode=\"\\n      const float exponentMultiplier = \"+o+\";\\n\\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\\n        \"+t+\"\\n      }\\n\\n      float mulMatDFT(int batch, int index) {\\n        float indexRatio = float(index) / float(\"+r+\");\\n        float exponentMultiplierTimesIndexRatio =\\n            exponentMultiplier * indexRatio;\\n\\n        float result = 0.0;\\n\\n        for (int i = 0; i < \"+r+\"; i++) {\\n          // x = (-2|2 * PI / N) * index * i;\\n          float x = exponentMultiplierTimesIndexRatio * float(i);\\n          float expR = cos(x);\\n          float expI = sin(x);\\n          float real = getReal(batch, i);\\n          float imag = getImag(batch, i);\\n\\n          result +=\\n              unaryOpComplex(real, expR, imag, expI) / \"+a+\";\\n        }\\n\\n        return result;\\n      }\\n\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        setOutput(mulMatDFT(coords[0], coords[1]));\\n      }\\n    \"}}(),Za=function(){function t(t,e){this.outputShape=[],this.variableNames=[\"x\"],this.outputShape=t,this.userCode=\"\\n      uniform float value;\\n      void main() {\\n        // Input can be obtained from uniform value.\\n        setOutput(value);\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.valueLoc&&(e.valueLoc=n.getUniformLocationNoThrow(r,\"value\")),n.gl.uniform1f(e.valueLoc,t)}},t}(),ti=function(){return function(t,e,n){this.variableNames=[\"A\",\"indices\"];var r=t.slice();r[n]=e,this.outputShape=r,this.rank=r.length;var o=aa(this.rank),a=function(t,e){var n=t.length;if(n>4)throw Error(\"Gather for rank \"+n+\" is not yet supported\");if(1===n)return\"int(getIndices(resRC))\";for(var r=[\"resRC.x\",\"resRC.y\",\"resRC.z\",\"resRC.w\"],o=[],a=0;a<t.length;a++)a===e?o.push(\"int(getIndices(\"+r[a]+\"))\"):o.push(\"\"+r[a]);return o.join()}(t,n);this.userCode=\"\\n      void main() {\\n        \"+o+\" resRC = getOutputCoords();\\n        setOutput(getA(\"+a+\"));\\n      }\\n    \"}}();var ei=function(){return function(t,e,n){this.sliceDim=t,this.strides=e,this.variableNames=[\"x\",\"indices\"],this.outputShape=n;var r=aa(e.length),o=aa(n.length),a=this.sliceDim>1?\"strides[j]\":\"strides\";this.userCode=\"\\n        \"+r+\" strides = \"+r+\"(\"+this.strides+\");\\n         void main() {\\n          \"+o+\" coords = getOutputCoords();\\n          int flattenIndex = 0;\\n          for (int j = 0; j < \"+this.sliceDim+\"; j++) {\\n            int index = round(getIndices(coords[0], j));\\n            flattenIndex += index * \"+a+\";\\n          }\\n          setOutput(getX(flattenIndex, coords[1]));\\n        }\\n      \"}}();function ni(t,e){var n=Ko();return Qt(t,e,n.version+\"\\n    precision highp float;\\n    \"+n.attribute+\" vec3 clipSpacePos;\\n    \"+n.attribute+\" vec2 uv;\\n    \"+n.varyingVs+\" vec2 resultUV;\\n\\n    void main() {\\n      gl_Position = vec4(clipSpacePos, 1);\\n      resultUV = uv;\\n    }\")}function ri(t,e){return ae(t,e,new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]))}function oi(t,e){return ie(t,e,new Uint16Array([0,1,2,2,1,3]))}function ai(t,e,n,r,o,a,i){se(n,r);var u=ue(t,e),s=t.TEXTURE_2D;return qt(t,e,function(){return t.bindTexture(s,u)}),qt(t,e,function(){return t.texParameteri(s,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE)}),qt(t,e,function(){return t.texParameteri(s,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE)}),qt(t,e,function(){return t.texParameteri(s,t.TEXTURE_MIN_FILTER,t.NEAREST)}),qt(t,e,function(){return t.texParameteri(s,t.TEXTURE_MAG_FILTER,t.NEAREST)}),qt(t,e,function(){return t.texImage2D(s,0,o,n,r,0,a,i,null)}),qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)}),u}function ii(t,e,n,r,o){var a=Vt(n,r);return ai(t,e,a[0],a[1],o.internalFormatFloat,o.textureFormatFloat,t.FLOAT)}function ui(t,e,n,r,o){var a=Vt(n,r);return ai(t,e,a[0],a[1],o.internalFormatHalfFloat,o.textureFormatFloat,o.textureTypeHalfFloat)}function si(t,e,n,r,o){var a=Vt(n,r);return ai(t,e,a[0],a[1],t.RGBA,t.RGBA,t.UNSIGNED_BYTE)}function ci(t,e,n,r,o){var a=Gt(n,r);return ai(t,e,a[0],a[1],o.internalFormatPackedFloat,t.RGBA,t.FLOAT)}function li(t,e,n,r,o){var a=Gt(n,r);return ai(t,e,a[0],a[1],o.internalFormatPackedHalfFloat,t.RGBA,o.textureTypeHalfFloat)}function hi(t,e,n,r){return qt(t,e,function(){return t.bindBuffer(t.ARRAY_BUFFER,r)}),le(t,e,n,\"clipSpacePos\",r,3,20,0)&&le(t,e,n,\"uv\",r,2,20,12)}function fi(t,e,n,r,o,a,i){var u,s,c;qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),a instanceof Uint8Array?(u=new Uint8Array(r*o*4),s=t.UNSIGNED_BYTE,c=t.RGBA):(u=new Float32Array(r*o*4),s=t.FLOAT,c=i.internalFormatPackedFloat),u.set(a),qt(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,c,r,o,0,t.RGBA,s,u)}),qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)})}function pi(t,e,n,r){qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),r.data instanceof Uint8Array?qt(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,r.width,r.height,0,t.RGBA,t.UNSIGNED_BYTE,r.data)}):qt(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,r)}),qt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)})}function di(t,e,n,r,o){var a=t.createBuffer();qt(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,a)});var i=16*n*r;return qt(t,e,function(){return t.bufferData(t.PIXEL_PACK_BUFFER,i,t.STREAM_READ)}),qt(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,0)}),qt(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,null)}),a}function vi(t,e,n){var r=t,o=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,e),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,o),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),o}function mi(t,e,n,r,o){var a=Vt(n,r),i=a[0],u=a[1],s=new Uint8Array(n*r*4);return qt(t,e,function(){return t.readPixels(0,0,i,u,o.downloadTextureFormat,t.UNSIGNED_BYTE,s)}),new Float32Array(s.buffer)}function gi(t,e,n,r,o,a,i,u){var s=t,c=new Float32Array(function(t,e){var n=Gt(t,e);return n[0]*n[1]*4}(a,i));return s.bindBuffer(s.PIXEL_PACK_BUFFER,e),s.getBufferSubData(s.PIXEL_PACK_BUFFER,0,c),s.bindBuffer(s.PIXEL_PACK_BUFFER,null),c}function yi(t,e,n,r){var o=new Float32Array(n*r*4);return qt(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,o)}),o}var xi=Object.freeze({createVertexShader:ni,createVertexBuffer:ri,createIndexBuffer:oi,createFloat32MatrixTexture:ii,createFloat16MatrixTexture:ui,createUnsignedBytesMatrixTexture:si,createPackedMatrixTexture:ci,createFloat16PackedMatrixTexture:li,bindVertexProgramAttributeStreams:hi,uploadDenseMatrixToTexture:fi,uploadPixelDataToTexture:pi,createBufferFromOutputTexture:di,downloadFloat32MatrixFromBuffer:vi,downloadByteEncodedFloatMatrixFromOutputTexture:mi,downloadPackedMatrixFromBuffer:gi,downloadMatrixFromPackedOutputTexture:yi}),bi=function(){function t(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];var e=a().getNumber(\"WEBGL_VERSION\");null!=t?(this.gl=t,Wt(e,t)):this.gl=Ut(e);var n=\"WEBGL_color_buffer_float\";if(1===a().getNumber(\"WEBGL_VERSION\")){if(this.textureFloatExtension=Yt(this.gl,this.debug,\"OES_texture_float\"),Te(this.gl,\"OES_texture_half_float\"))this.textureHalfFloatExtension=Yt(this.gl,this.debug,\"OES_texture_half_float\");else if(a().get(\"WEBGL_FORCE_F16_TEXTURES\"))throw new Error(\"GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.\");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Te(this.gl,\"EXT_color_buffer_half_float\"))this.colorBufferHalfFloatExtension=Yt(this.gl,this.debug,\"EXT_color_buffer_half_float\");else if(a().get(\"WEBGL_FORCE_F16_TEXTURES\"))throw new Error(\"GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.\")}else if(n=\"EXT_color_buffer_float\",Te(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else{if(!Te(this.gl,\"EXT_color_buffer_half_float\"))throw new Error(\"GL context does not support color renderable floats\");this.colorBufferHalfFloatExtension=this.gl.getExtension(\"EXT_color_buffer_half_float\")}this.vertexBuffer=ri(this.gl,this.debug),this.indexBuffer=oi(this.gl,this.debug),this.framebuffer=ce(this.gl,this.debug),this.textureConfig=Ht(this.gl,this.textureHalfFloatExtension)}return Object.defineProperty(t.prototype,\"debug\",{get:function(){return a().getBool(\"DEBUG\")},enumerable:!0,configurable:!0}),t.prototype.dispose=function(){var t=this;if(!this.disposed){null!=this.program&&console.warn(\"Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing.\"),null!=this.outputTexture&&console.warn(\"Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.\");var e=this.gl;qt(e,this.debug,function(){return e.finish()}),qt(e,this.debug,function(){return e.bindFramebuffer(e.FRAMEBUFFER,null)}),qt(e,this.debug,function(){return e.deleteFramebuffer(t.framebuffer)}),qt(e,this.debug,function(){return e.bindBuffer(e.ARRAY_BUFFER,null)}),qt(e,this.debug,function(){return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)}),qt(e,this.debug,function(){return e.deleteBuffer(t.indexBuffer)}),this.disposed=!0}},t.prototype.createFloat32MatrixTexture=function(t,e){return this.throwIfDisposed(),ii(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createFloat16MatrixTexture=function(t,e){return this.throwIfDisposed(),ui(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createUnsignedBytesMatrixTexture=function(t,e){return this.throwIfDisposed(),si(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.uploadPixelDataToTexture=function(t,e){this.throwIfDisposed(),pi(this.gl,this.debug,t,e)},t.prototype.uploadDenseMatrixToTexture=function(t,e,n,r){this.throwIfDisposed(),fi(this.gl,this.debug,t,e,n,r,this.textureConfig)},t.prototype.createFloat16PackedMatrixTexture=function(t,e){return this.throwIfDisposed(),li(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createPackedMatrixTexture=function(t,e){return this.throwIfDisposed(),ci(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.deleteMatrixTexture=function(t){var e=this;this.throwIfDisposed(),this.outputTexture===t&&(me(this.gl,this.debug,this.framebuffer),this.outputTexture=null),qt(this.gl,this.debug,function(){return e.gl.deleteTexture(t)})},t.prototype.downloadByteEncodedFloatMatrixFromOutputTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return mi(r.gl,r.debug,e,n,r.textureConfig)})},t.prototype.downloadPackedMatrixFromBuffer=function(t,e,n,r,o,a){return gi(this.gl,t,0,0,0,o,a,this.textureConfig)},t.prototype.downloadFloat32MatrixFromBuffer=function(t,e){return vi(this.gl,t,e)},t.prototype.createBufferFromTexture=function(t,e,n){this.bindTextureToFrameBuffer(t);var r=di(this.gl,this.debug,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r},t.prototype.createAndWaitForFence=function(){var t=this.createFence(this.gl);return this.pollFence(t)},t.prototype.createFence=function(t){var e,n,r=this;if(a().getBool(\"WEBGL_FENCE_API_ENABLED\")){var o=t,i=o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE,0);t.flush(),n=function(){var t=o.clientWaitSync(i,0,0);return t===o.ALREADY_SIGNALED||t===o.CONDITION_SATISFIED},e=i}else a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")>0?(e=this.beginQuery(),this.endQuery(),n=function(){return r.isQueryAvailable(e,a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"))}):n=function(){return!0};return{query:e,isFencePassed:n}},t.prototype.downloadMatrixFromPackedTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return yi(r.gl,r.debug,e,n)})},t.prototype.createProgram=function(t){this.throwIfDisposed();var e=this.gl,n=Jt(e,this.debug,t),r=ni(e,this.debug),o=ne(e,this.debug);return qt(e,this.debug,function(){return e.attachShader(o,r)}),qt(e,this.debug,function(){return e.attachShader(o,n)}),re(e,this.debug,o),this.debug&&oe(e,this.debug,o),this.vertexAttrsAreBound||(this.setProgram(o),this.vertexAttrsAreBound=hi(e,this.debug,this.program,this.vertexBuffer)),o},t.prototype.deleteProgram=function(t){var e=this;this.throwIfDisposed(),t===this.program&&(this.program=null),null!=t&&qt(this.gl,this.debug,function(){return e.gl.deleteProgram(t)})},t.prototype.setProgram=function(t){var e=this;this.throwIfDisposed(),this.program=t,null!=this.program&&this.debug&&oe(this.gl,this.debug,this.program),qt(this.gl,this.debug,function(){return e.gl.useProgram(t)})},t.prototype.getUniformLocation=function(t,e,n){return void 0===n&&(n=!0),this.throwIfDisposed(),n?fe(this.gl,this.debug,t,e):pe(this.gl,t,e)},t.prototype.getAttributeLocation=function(t,e){var n=this;return this.throwIfDisposed(),qt(this.gl,this.debug,function(){return n.gl.getAttribLocation(t,e)})},t.prototype.getUniformLocationNoThrow=function(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)},t.prototype.setInputMatrixTexture=function(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),de(this.gl,this.debug,this.program,t,e,n)},t.prototype.setOutputMatrixTexture=function(t,e,n){this.setOutputMatrixTextureDriver(t,n,e)},t.prototype.setOutputPackedMatrixTexture=function(t,e,n){this.throwIfDisposed();var r=Gt(e,n),o=r[0],a=r[1];this.setOutputMatrixTextureDriver(t,o,a)},t.prototype.setOutputMatrixWriteRegion=function(t,e,n,r){this.setOutputMatrixWriteRegionDriver(n,t,r,e)},t.prototype.setOutputPackedMatrixWriteRegion=function(t,e,n,r){throw new Error(\"setOutputPackedMatrixWriteRegion not implemented.\")},t.prototype.debugValidate=function(){null!=this.program&&oe(this.gl,this.debug,this.program),ge(this.gl)},t.prototype.executeProgram=function(){this.throwIfDisposed(),this.throwIfNoProgram();var t=this.gl;this.debug&&this.debugValidate(),qt(t,this.debug,function(){return t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0)})},t.prototype.blockUntilAllProgramsCompleted=function(){var t=this;this.throwIfDisposed(),qt(this.gl,this.debug,function(){return t.gl.finish()})},t.prototype.getQueryTimerExtension=function(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=Yt(this.gl,this.debug,2===a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")?\"EXT_disjoint_timer_query_webgl2\":\"EXT_disjoint_timer_query\")),this.disjointQueryTimerExtension},t.prototype.getQueryTimerExtensionWebGL2=function(){return this.getQueryTimerExtension()},t.prototype.getQueryTimerExtensionWebGL1=function(){return this.getQueryTimerExtension()},t.prototype.beginQuery=function(){if(2===a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")){var t=this.gl,e=this.getQueryTimerExtensionWebGL2(),n=t.createQuery();return t.beginQuery(e.TIME_ELAPSED_EXT,n),n}var r=this.getQueryTimerExtensionWebGL1(),o=r.createQueryEXT();return r.beginQueryEXT(r.TIME_ELAPSED_EXT,o),o},t.prototype.endQuery=function(){if(2!==a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")){var t=this.getQueryTimerExtensionWebGL1();t.endQueryEXT(t.TIME_ELAPSED_EXT)}else{var e=this.gl,n=this.getQueryTimerExtensionWebGL2();e.endQuery(n.TIME_ELAPSED_EXT)}},t.prototype.waitForQueryAndGetTime=function(t){return n(this,void 0,void 0,function(){var e=this;return r(this,function(n){switch(n.label){case 0:return[4,S(function(){return e.disposed||e.isQueryAvailable(t,a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"))})];case 1:return n.sent(),[2,this.getQueryTime(t,a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"))]}})})},t.prototype.getQueryTime=function(t,e){if(0===e)return null;if(2===e){var n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}var r=this.getQueryTimerExtensionWebGL1();return r.getQueryObjectEXT(t,r.QUERY_RESULT_EXT)/1e6},t.prototype.isQueryAvailable=function(t,e){if(0===e)return!0;if(2===e){var n=this.gl,r=this.getQueryTimerExtensionWebGL2(),o=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint}o=(r=this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(t,r.QUERY_RESULT_AVAILABLE_EXT);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint},t.prototype.pollFence=function(t){var e=this;return new Promise(function(n){e.addItemToPoll(function(){return t.isFencePassed()},function(){return n()})})},t.prototype.pollItems=function(){for(var t=function(t){for(var e=0;e<t.length;++e){var n=t[e]();if(!n)break}return e-1}(this.itemsToPoll.map(function(t){return t.isDoneFn})),e=0;e<=t;++e){(0,this.itemsToPoll[e].resolveFn)()}this.itemsToPoll=this.itemsToPoll.slice(t+1)},t.prototype.addItemToPoll=function(t,e){var n=this;this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),this.itemsToPoll.length>1||S(function(){return n.pollItems(),0===n.itemsToPoll.length})},t.prototype.bindTextureToFrameBuffer=function(t){this.throwIfDisposed(),ve(this.gl,this.debug,t,this.framebuffer),this.debug&&ge(this.gl)},t.prototype.unbindTextureToFrameBuffer=function(){null!=this.outputTexture?(ve(this.gl,this.debug,this.outputTexture,this.framebuffer),this.debug&&ge(this.gl)):me(this.gl,this.debug,this.framebuffer)},t.prototype.downloadMatrixDriver=function(t,e){this.bindTextureToFrameBuffer(t);var n=e();return this.unbindTextureToFrameBuffer(),n},t.prototype.setOutputMatrixTextureDriver=function(t,e,n){this.throwIfDisposed();var r=this.gl;ve(r,this.debug,t,this.framebuffer),this.debug&&ge(r),this.outputTexture=t,qt(r,this.debug,function(){return r.viewport(0,0,e,n)}),qt(r,this.debug,function(){return r.scissor(0,0,e,n)})},t.prototype.setOutputMatrixWriteRegionDriver=function(t,e,n,r){var o=this;this.throwIfDisposed(),qt(this.gl,this.debug,function(){return o.gl.scissor(t,e,n,r)})},t.prototype.throwIfDisposed=function(){if(this.disposed)throw new Error(\"Attempted to use disposed GPGPUContext.\")},t.prototype.throwIfNoProgram=function(){if(null==this.program)throw new Error(\"No GPU program is currently set.\")},t}();function wi(t,e){if(t.length!==e.length)throw Error(\"Binary was compiled with \"+t.length+\" inputs, but was executed with \"+e.length+\" inputs\");t.forEach(function(t,n){var r=t.logicalShape,o=e[n],a=o.shape;if(!C(r,a))throw Error(\"Binary was compiled with different shapes than the current args. Shapes \"+r+\" and \"+a+\" must match\");if(!t.isUniform||!o.isUniform){var i=t.texShape,u=o.isUniform?null:o.texData.texShape;if(!C(i,u))throw Error(\"Binary was compiled with different texture shapes than the current args. Shape \"+i+\" and \"+u+\" must match\")}})}var Ci=function(){return function(t,e,n){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var r=n.filterWidth,o=n.inChannels,a=n.strideWidth,i=n.strideHeight,u=n.padInfo,s=n.outWidth,c=n.dilationWidth,l=n.dilationHeight,h=n.dataFormat,f=u.left,p=u.top,d=o*r,v=Ko(),m=\"channelsLast\"===h,g=m?0:1,y=m?1:2,x=\"\",b=0;b<=1;b++)for(var w=0;w<=1;w++)x+=\"\\n          blockIndex = rc.y + \"+w+\";\\n          pos = rc.x + \"+b+\";\\n\\n          if(blockIndex < \"+t[1]+\" && pos < \"+t[0]+\") {\\n            offsetY = int(blockIndex / (\"+s+\")) * \"+i+\" - \"+p+\";\\n            d0 = offsetY + \"+l+\" * (pos / \"+d+\");\\n\\n            if(d0 < \"+e[g]+\" && d0 >= 0) {\\n\\n              offsetX = int(mod(float(blockIndex), \"+s+\".) * \"+a+\". - \"+f+\".);\\n              d1 = offsetX + \"+c+\" * (int(mod(float(pos), \"+d+\".) / \"+o+\".));\\n\\n              if(d1 < \"+e[y]+\" && d1 >= 0) {\\n\\n                ch = int(mod(float(pos), \"+o+\".));\\n\\n                if (\"+m+\") {\\n                  innerDims = vec2(d1, ch);\\n                  result[\"+(2*b+w)+\"] = getChannel(\\n                    getA(d0, int(innerDims.x),\\n                    int(innerDims.y)), innerDims);\\n                } else {\\n                  innerDims = vec2(d0, d1);\\n                  result[\"+(2*b+w)+\"] = getChannel(\\n                    getA(ch, int(innerDims.x),\\n                    int(innerDims.y)), innerDims);\\n                }\\n              }\\n            }\\n          }\\n        \";this.userCode=\"\\n      void main() {\\n        ivec2 rc = getOutputCoords();\\n\\n        vec4 result = vec4(0);\\n\\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\\n        vec2 innerDims;\\n\\n        \"+x+\"\\n\\n        \"+v.output+\" = result;\\n      }\\n    \"}}(),Ei=function(){return function(t,e,n,r,o){this.variableNames=[\"x\"],this.outputShape=[];var a,i=e,u=t[3]-1;this.outputShape=t;var s=\"float(\"+n+\") + float(\"+r+\") * sum\";a=.5===o?\"inversesqrt(\"+s+\")\":1===o?\"1.0/(\"+s+\")\":\"exp(log(\"+s+\") * float(-\"+o+\"));\",this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int r = coords[1];\\n        int c = coords[2];\\n        int d = coords[3];\\n        float x = getX(b, r, c, d);\\n        float sum = 0.0;\\n        for (int j = -\"+i+\"; j <= \"+i+\"; j++) {\\n          int idx = d + j;\\n          if (idx >= 0 && idx <=  \"+u+\") {\\n            float z = getX(b, r, c, idx);\\n            sum += z * z;\\n          }\\n        }\\n        float val = x * \"+a+\";\\n        setOutput(val);\\n      }\\n    \"}}(),Ri=function(){return function(t,e,n,r,o){this.variableNames=[\"inputImage\",\"outputImage\",\"dy\"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=r,this.beta=o,this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int r = coords[1];\\n        int c = coords[2];\\n\\n        float result = 0.0;\\n        for (int d = 0; d < \"+this.depth+\"; ++d) {\\n          int depthBegin = int(max(0.0, float(d - \"+e+\")));\\n          int depthEnd = int(min(float(\"+this.depth+\"),\\n              float(d + \"+e+\" + 1)));\\n\\n          const int MIN_DEPTH_BEGIN = 0;\\n          const int MAX_DEPTH_END = \"+this.depth+\";\\n\\n          float norm = 0.0;\\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\\n            if (k < depthBegin){\\n              continue;\\n            }\\n            else if (k >= depthBegin && k < depthEnd) {\\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\\n            }\\n            else {\\n              break;\\n            }\\n          }\\n\\n          norm = float(\"+r+\") * norm + float(\"+n+\");\\n\\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\\n            if (k < depthBegin){\\n              continue;\\n            }\\n            else if (k >= depthBegin && k < depthEnd){\\n              float dyi = -2.0 * float(\"+r+\")\\n                * float(\"+o+\")\\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\\n                / norm;\\n              if (k == d) {\\n                dyi += pow(norm, -1.0 * \"+o+\");\\n              }\\n              if (k == coords[3]) {\\n                dyi *= getDy(b, r, c, d);\\n                result += dyi;\\n              }\\n            }\\n            else {\\n              break;\\n            }\\n          }\\n      }\\n      setOutput(result);\\n      }\\n    \"}}(),Ii=function(){return function(t,e,n,r,o){this.variableNames=[\"x\"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;var a,i=e,u=t[3]-1;this.outputShape=t;var s=\"float(\"+n+\") + float(\"+r+\") * sum\";a=.5===o?\"inversesqrt(\"+s+\")\":1===o?\"1.0/(\"+s+\")\":\"exp(log(\"+s+\") * float(-\"+o+\"));\",this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords.x;\\n        int r = coords.y;\\n        int c = coords.z;\\n        int d = coords.w;\\n\\n        bool hasNextCol = d < \"+this.outputShape[3]+\";\\n        bool hasNextRow = c < \"+this.outputShape[2]+\";\\n\\n        vec4 sum = vec4(0.);\\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\\n\\n        vec4 xAtOutputCoords = vec4(\\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\\n          hasNextCol ?\\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\\n          hasNextRow ?\\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\\n        );\\n\\n        int firstChannel = d - \"+i+\";\\n        vec2 cache = vec2(0.);\\n        if(firstChannel >= 0){\\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\\n            if(hasNextRow){\\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\\n            }\\n        }\\n\\n        ivec2 depth = ivec2(d, d + 1);\\n        for (int j = - \"+i+\"; j <= \"+i+\"; j++) {\\n          ivec2 idx = depth + j;\\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(\"+u+\"));\\n\\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\\n\\n          if(depthInRange || depthPlusOneInRange){\\n            vec4 z = vec4(0.);\\n            vec4 xFragAtCurrentDepth;\\n            z.xz = cache.xy;\\n            if(depthPlusOneInRange && hasNextCol){\\n              xFragAtCurrentDepth = idx.y != d ?\\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\\n              if(hasNextRow){\\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\\n              }\\n            }\\n            cache.xy = z.yw;\\n            sum += z * z;\\n          }\\n        }\\n        vec4 result = xAtOutputCoords * \"+a+\";\\n        setOutput(result);\\n      }\\n    \"}}(),ki=function(){return function(t){this.variableNames=[\"dy\",\"maxPos\"],this.outputShape=t.inShape;var e=t.strideHeight,n=t.strideWidth,r=t.dilationHeight,o=t.effectiveFilterHeight,a=t.effectiveFilterWidth,i=o-1-t.padInfo.top,u=a-1-t.padInfo.left,s=o*a-1;this.userCode=\"\\n      const ivec2 pads = ivec2(\"+i+\", \"+u+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n\\n        ivec2 dyRCCorner = coords.yz - pads;\\n        int dyRCorner = dyRCCorner.x;\\n        int dyCCorner = dyRCCorner.y;\\n\\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        for (int wR = 0; wR < \"+o+\";\\n          wR += \"+r+\") {\\n          float dyR = float(dyRCorner + wR) / \"+e+\".0;\\n\\n          if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 || fract(dyR) > 0.0) {\\n            continue;\\n          }\\n          int idyR = int(dyR);\\n\\n          for (int wC = 0; wC < \"+a+\"; wC++) {\\n            float dyC = float(dyCCorner + wC) / \"+n+\".0;\\n\\n            if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                fract(dyC) > 0.0) {\\n              continue;\\n            }\\n            int idyC = int(dyC);\\n\\n            float dyValue = getDy(b, idyR, idyC, d);\\n            int maxPosValue = \"+s+\" - int(getMaxPos(b, idyR, idyC, d));\\n\\n            // Get the current value, check it against the value from the\\n            // position matrix.\\n            int curPosValue = wR * \"+a+\" + wC;\\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\\n\\n            dotProd += dyValue * mask;\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),Si=function(){return function(t){this.variableNames=[\"dy\",\"maxPos\"],this.outputShape=t.inShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.dilationDepth,a=t.dilationHeight,i=t.dilationWidth,u=t.effectiveFilterDepth,s=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=u-1-t.padInfo.front,h=s-1-t.padInfo.top,f=c-1-t.padInfo.left,p=u*s*c-1;this.userCode=\"\\n      const ivec3 pads = ivec3(\"+l+\", \"+h+\", \"+f+\");\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int ch = coords.u;\\n\\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\\n        int dyDCorner = dyCorner.x;\\n        int dyRCorner = dyCorner.y;\\n        int dyCCorner = dyCorner.z;\\n\\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\\n        // dx(xD, xR, xC, ch).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n\\n        for (int wD = 0; wD < \"+u+\";\\n           wD += \"+o+\") {\\n          float dyD = float(dyDCorner + wD) / \"+e+\".0;\\n\\n          if (dyD < 0.0 || dyD >= \"+t.outDepth+\".0 || fract(dyD) > 0.0) {\\n            continue;\\n          }\\n          int idyD = int(dyD);\\n\\n          for (int wR = 0; wR < \"+s+\";\\n              wR += \"+a+\") {\\n            float dyR = float(dyRCorner + wR) / \"+n+\".0;\\n\\n            if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 ||\\n                fract(dyR) > 0.0) {\\n              continue;\\n            }\\n            int idyR = int(dyR);\\n\\n            for (int wC = 0; wC < \"+c+\";\\n                wC += \"+i+\") {\\n              float dyC = float(dyCCorner + wC) / \"+r+\".0;\\n\\n              if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                  fract(dyC) > 0.0) {\\n                continue;\\n              }\\n              int idyC = int(dyC);\\n\\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\\n              int maxPosValue = \"+p+\" -\\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\\n\\n              // Get the current value, check it against the value from the\\n              // position matrix.\\n              int curPosValue =\\n                  wD * \"+s+\" * \"+c+\" +\\n                  wR * \"+c+\" + wC;\\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\\n\\n              dotProd += dyValue * mask;\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"}}(),Ai=function(){return function(t,e,n,r,o,a,i){void 0===n&&(n=!1),void 0===r&&(r=!1),void 0===o&&(o=!1),void 0===a&&(a=null),void 0===i&&(i=!1),this.variableNames=[\"matrixA\",\"matrixB\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;var u=n?t[1]:t[2],s=Math.ceil(u/2),c=n?\"i * 2, rc.y\":\"rc.y, i * 2\",l=r?\"rc.z, i * 2\":\"i * 2, rc.z\",h=n?[\"a.xxyy\",\"a.zzww\"]:[\"a.xxzz\",\"a.yyww\"],f=r?[\"b.xzxz\",\"b.ywyw\"]:[\"b.xyxy\",\"b.zwzw\"],p=\"\",d=\"\";a&&(p=i?\"vec4 activation(vec4 a) {\\n          vec4 b = getPreluActivationWeightsAtOutCoords();\\n          \"+a+\"\\n        }\":\"vec4 activation(vec4 x) {\\n          \"+a+\"\\n        }\",d=\"result = activation(result);\");var v=o?\"result += getBiasAtOutCoords();\":\"\";o&&this.variableNames.push(\"bias\"),i&&this.variableNames.push(\"preluActivationWeights\"),this.userCode=\"\\n      \"+p+\"\\n\\n      const float sharedDimension = \"+s+\".0;\\n\\n      vec4 dot2x2ARowBCol(ivec3 rc) {\\n        vec4 result = vec4(0);\\n        for (int i = 0; i < \"+s+\"; i++) {\\n          vec4 a = getMatrixA(rc.x, \"+c+\");\\n          vec4 b = getMatrixB(rc.x, \"+l+\");\\n\\n          // These swizzled products need to be separately added.\\n          // See: https://github.com/tensorflow/tfjs/issues/1735\\n          result += (\"+h[0]+\" * \"+f[0]+\");\\n          result += (\"+h[1]+\" * \"+f[1]+\");\\n        }\\n        return result;\\n      }\\n\\n      void main() {\\n        ivec3 rc = getOutputCoords();\\n        vec4 result = dot2x2ARowBCol(rc);\\n\\n        \"+v+\"\\n\\n        \"+d+\"\\n\\n        setOutput(result);\\n      }\\n    \"}}(),Di=function(){function t(t,e,n){this.variableNames=[\"probs\"],this.outputShape=[t,n],this.userCode=\"\\n      uniform float seed;\\n\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int batch = coords[0];\\n\\n        float r = random(seed);\\n        float cdf = 0.0;\\n\\n        for (int i = 0; i < \"+(e-1)+\"; i++) {\\n          cdf += getProbs(batch, i);\\n\\n          if (r < cdf) {\\n            setOutput(float(i));\\n            return;\\n          }\\n        }\\n\\n        // If no other event happened, last event happened.\\n        setOutput(float(\"+(e-1)+\"));\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.seedLoc&&(e.seedLoc=n.getUniformLocation(r,\"seed\")),n.gl.uniform1f(e.seedLoc,t)}},t}(),Ti=function(){return function(t,e,n,r){this.variableNames=[\"indices\"],this.outputShape=[t,e],this.userCode=\"\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int index = round(getIndices(coords.x));\\n        setOutput(mix(float(\"+r+\"), float(\"+n+\"),\\n                      float(index == coords.y)));\\n      }\\n    \"}}(),Ni=function(){return function(t){this.variableNames=[\"A\"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=t;var e=t.length;if(0===e)this.userCode=\"\\n        void main() {\\n          setOutput(vec4(getA(), 0., 0., 0.));\\n        }\\n      \";else{var n=qo(\"rc\",e),r=aa(e),o=function(t,e,n){if(1===t)return\"rc > \"+e[0];for(var r=\"\",o=t-2;o<t;o++)r+=n[o]+\" >= \"+e[o],o<t-1&&(r+=\"||\");return r}(e,t,n),a=function(t,e,n,r){if(1===t)return\"\";var o=r.slice(-2);return\"\\n    int r = \"+o[0]+\";\\n    int c = \"+o[1]+\";\\n    int rp1 = r + 1;\\n    int cp1 = c + 1;\\n\\n    bool cEdge = cp1 >= \"+e+\";\\n    bool rEdge = rp1 >= \"+n+\";\\n  \"}(e,t[t.length-1],t[t.length-2],n),i=function(t,e){var n=t.length,r=function(t,e){for(var n=[],r=0;r<=1;r++)for(var o=0;o<=1;o++){for(var a=(0===r?\"r\":\"rp1\")+\", \"+(0===o?\"c\":\"cp1\"),i=2;i<t;i++)a=e[e.length-1-i]+\",\"+a;n.push(a)}return n}(n,e);return 1===n?\"getA(rc),\\n            rc + 1 >= \"+t[0]+\" ? 0. : getA(rc + 1),\\n            0, 0\":\"getA(\"+r[0]+\"),\\n          cEdge ? 0. : getA(\"+r[1]+\"),\\n          rEdge ? 0. : getA(\"+r[2]+\"),\\n          rEdge || cEdge ? 0. : getA(\"+r[3]+\")\"}(t,n);this.userCode=\"\\n        void main() {\\n          \"+r+\" rc = getOutputCoords();\\n\\n          if(\"+o+\") {\\n            setOutput(vec4(0));\\n          } else {\\n            \"+a+\"\\n\\n            setOutput(vec4(\"+i+\"));\\n          }\\n        }\\n      \"}}}();var Fi=function(){return function(t,e,n){this.variableNames=[\"x\"],this.outputShape=e.map(function(e,n){return e[0]+t[n]+e[1]});var r=t.length,o=aa(r),a=e.map(function(t){return t[0]}).join(\",\"),i=e.map(function(e,n){return e[0]+t[n]}).join(\",\"),u=[\"coords[0]\",\"coords[1]\",\"coords[2]\",\"coords[3]\"].slice(0,r);this.userCode=1!==r?\"\\n      \"+o+\" start = \"+o+\"(\"+a+\");\\n      \"+o+\" end = \"+o+\"(\"+i+\");\\n\\n      void main() {\\n        \"+o+\" outC = getOutputCoords();\\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\\n          setOutput(float(\"+n+\"));\\n        } else {\\n          \"+o+\" coords = outC - start;\\n          setOutput(getX(\"+u+\"));\\n        }\\n      }\\n    \":\"\\n        int start = \"+a+\";\\n        int end = \"+i+\";\\n\\n        void main() {\\n          int outC = getOutputCoords();\\n          if (outC < start || outC >= end) {\\n            setOutput(float(\"+n+\"));\\n          } else {\\n            setOutput(getX(outC - start));\\n          }\\n        }\\n      \"}}(),_i=function(){return function(t,e,n){this.variableNames=[\"x\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.map(function(e,n){return e[0]+t[n]+e[1]});for(var r=t.length,o=aa(r),a=e.map(function(t){return t[0]}).join(\",\"),i=e.map(function(e,n){return e[0]+t[n]}).join(\",\"),u=qo(\"rc\",r),s=qo(\"source\",r),c=u[r-1]+\" < \"+this.outputShape[r-1],l=1===r?\"source\":\"vec2(\"+s.slice(-2).join()+\")\",h=[o+\" rc = outputLoc;\",u[r-1]+\" += 1;\\n       if(\"+c+\") {\\n      \",1===r?\"\":\"}\\n       rc = outputLoc;\\n       \"+u[r-2]+\" += 1;\\n       if(\"+u[r-2]+\" < \"+this.outputShape[r-2]+\") {\",1===r?\"\":\"  \"+u[r-1]+\" += 1;\\n         if(\"+c+\") {\"],f=1===r?\"rc < start || rc >= end\":\"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))\",p=\"\",d=0,v=1===r?2:4;d<v;d++)p+=\"\\n        \"+h[d]+\"\\n        if (\"+f+\") {\\n          result[\"+d+\"] = float(\"+n+\");\\n        } else {\\n          \"+o+\" source = rc - start;\\n          result[\"+d+\"] = getChannel(getX(\"+s.join()+\"), \"+l+\");\\n        }\\n      \";p+=1===r?\"} \":\"}}\",this.userCode=\"\\n      const \"+o+\" start = \"+o+\"(\"+a+\");\\n      const \"+o+\" end = \"+o+\"(\"+i+\");\\n\\n      void main() {\\n        \"+o+\" outputLoc = getOutputCoords();\\n        vec4 result = vec4(0.);\\n        \"+p+\"\\n        setOutput(result);\\n      }\\n    \"}}(),Oi=function(){return function(t,e,n){if(this.variableNames=[\"x\"],\"avg\"===e&&n)throw new Error(\"Cannot compute positions for average pool.\");var r=t.filterWidth,o=t.strideHeight,a=t.strideWidth,i=t.dilationHeight,u=t.dilationWidth,s=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=t.padInfo.top,h=t.padInfo.left;this.outputShape=t.outShape;var f=\"avg\"===e,p=\"0.0\";if(f||(p=\"-1.0 / 1e-20\"),n)this.userCode=\"\\n        const ivec2 strides = ivec2(\"+o+\", \"+a+\");\\n        const ivec2 pads = ivec2(\"+l+\", \"+h+\");\\n\\n        void main() {\\n          ivec4 coords = getOutputCoords();\\n          int batch = coords[0];\\n          int d = coords[3];\\n\\n          ivec2 xRCCorner = coords.yz * strides - pads;\\n          int xRCorner = xRCCorner.x;\\n          int xCCorner = xRCCorner.y;\\n\\n          // max/min x(?, ?, d) to get y(yR, yC, d).\\n          // ? = to be determined\\n          float minMaxValue = 0.0;\\n          float minMaxValueFound = 0.0;\\n          int minMaxPosition = 0;\\n          float avgValue = 0.0;\\n\\n          for (int wR = 0; wR < \"+s+\";\\n              wR += \"+i+\") {\\n            int xR = xRCorner + wR;\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int wC = 0; wC < \"+c+\";\\n                wC += \"+u+\") {\\n              int xC = xCCorner + wC;\\n\\n              if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                continue;\\n              }\\n\\n              float value = getX(batch, xR, xC, d);\\n\\n              // If a min / max value has already been found, use it. If not,\\n              // use the current value.\\n              float currMinMaxValue = mix(\\n                  value, minMaxValue, minMaxValueFound);\\n              if (value >= currMinMaxValue) {\\n                minMaxValue = value;\\n                minMaxValueFound = 1.0;\\n                minMaxPosition = wR * \"+c+\" + wC;\\n              }\\n            }\\n          }\\n          setOutput(float(minMaxPosition));\\n        }\\n      \";else{var d=e+\"(\"+e+\"(\"+e+\"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])\";\"avg\"===e&&(d=\"avgValue / count\");var v=4*Math.floor(r/4),m=r%4,g=\"\\n      if (\"+f+\") {\\n        avgValue += dot(values, ones);\\n      } else {\\n        minMaxValue = max(values, minMaxValue);\\n      }\\n    \";this.userCode=\"\\n      const ivec2 strides = ivec2(\"+o+\", \"+a+\");\\n      const ivec2 pads = ivec2(\"+l+\", \"+h+\");\\n      const float initializationValue = \"+p+\";\\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\\n\\n      float count = 0.0;\\n\\n      float getValue(int batch, int xR, int xC, int d) {\\n        if (xC < 0 || xC >= \"+t.inWidth+\") {\\n          return initializationValue;\\n        }\\n        count += 1.0;\\n        return getX(batch, xR, xC, d);\\n      }\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int d = coords[3];\\n\\n        ivec2 xRCCorner = coords.yz * strides - pads;\\n        int xRCorner = xRCCorner.x;\\n        int xCCorner = xRCCorner.y;\\n\\n        // max/min x(?, ?, d) to get y(yR, yC, d).\\n        // ? = to be determined\\n        vec4 minMaxValue = vec4(\"+p+\");\\n        float avgValue = 0.0;\\n        count = 0.0;\\n\\n        for (int wR = 0; wR < \"+s+\";\\n            wR += \"+i+\") {\\n          int xR = xRCorner + wR;\\n\\n          if (xR < 0 || xR >= \"+t.inHeight+\") {\\n            continue;\\n          }\\n\\n          for (int wC = 0; wC < \"+v+\"; wC += 4) {\\n            int xC = xCCorner + wC * \"+u+\";\\n\\n            vec4 values = vec4(\\n              getValue(batch, xR, xC, d),\\n              getValue(batch, xR, xC + \"+u+\", d),\\n              getValue(batch, xR, xC + 2 * \"+u+\", d),\\n              getValue(batch, xR, xC + 3 * \"+u+\", d)\\n            );\\n\\n            \"+g+\"\\n          }\\n\\n          int xC = xCCorner + \"+v+\";\\n          if (\"+(1===m)+\") {\\n            vec4 values = vec4(\\n              getValue(batch, xR, xC, d),\\n              initializationValue,\\n              initializationValue,\\n              initializationValue\\n            );\\n\\n            \"+g+\"\\n          } else if (\"+(2===m)+\") {\\n            vec4 values = vec4(\\n              getValue(batch, xR, xC, d),\\n              getValue(batch, xR, xC + \"+u+\", d),\\n              initializationValue,\\n              initializationValue\\n            );\\n\\n            \"+g+\"\\n          } else if (\"+(3===m)+\") {\\n            vec4 values = vec4(\\n              getValue(batch, xR, xC, d),\\n              getValue(batch, xR, xC + \"+u+\", d),\\n              getValue(batch, xR, xC + 2 * \"+u+\", d),\\n              initializationValue\\n            );\\n\\n            \"+g+\"\\n          }\\n        }\\n        setOutput(\"+d+\");\\n      }\\n    \"}}}(),Mi=function(){return function(t,e,n){if(this.variableNames=[\"x\"],\"avg\"===e&&n)throw new Error(\"Cannot compute positions for average pool.\");var r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,u=t.dilationDepth,s=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,p=t.padInfo.front,d=t.padInfo.top,v=t.padInfo.left;this.outputShape=t.outShape;var m=\"avg\"===e,g=\"0.0\";if(m||(g=\"-1.0 / 1e-20\"),n)this.userCode=\"\\n        const ivec3 strides =\\n            ivec3(\"+o+\", \"+a+\", \"+i+\");\\n        const ivec3 pads = ivec3(\"+p+\", \"+d+\", \"+v+\");\\n\\n        void main() {\\n          ivec5 coords = getOutputCoords();\\n          int batch = coords.x;\\n          int ch = coords.u;\\n\\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\\n          int xDCorner = xCorner.x;\\n          int xRCorner = xCorner.y;\\n          int xCCorner = xCorner.z;\\n\\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\\n          // ? = to be determined\\n          float minMaxValue = 0.0;\\n          float minMaxValueFound = 0.0;\\n          int minMaxPosition = 0;\\n\\n          for (int wD = 0; wD < \"+l+\";\\n              wD += \"+u+\") {\\n            int xD = xDCorner + wD;\\n\\n            if (xD < 0 || xD >= \"+t.inDepth+\") {\\n              continue;\\n            }\\n\\n            for (int wR = 0; wR < \"+h+\";\\n                wR += \"+s+\") {\\n              int xR = xRCorner + wR;\\n\\n              if (xR < 0 || xR >= \"+t.inHeight+\") {\\n                continue;\\n              }\\n\\n              for (int wC = 0; wC < \"+f+\";\\n                  wC += \"+c+\") {\\n                int xC = xCCorner + wC;\\n\\n                if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                  continue;\\n                }\\n\\n                float value = getX(batch, xD, xR, xC, ch);\\n\\n                // If a min / max value has already been found, use it. If not,\\n                // use the current value.\\n                float currMinMaxValue = mix(\\n                    value, minMaxValue, minMaxValueFound);\\n                if (value >= currMinMaxValue) {\\n                  minMaxValue = value;\\n                  minMaxValueFound = 1.0;\\n                  minMaxPosition =\\n                      wD * \"+h+\" * \"+f+\" +\\n                      wR * \"+f+\" + wC;;\\n                }\\n              }\\n            }\\n          }\\n          setOutput(float(minMaxPosition));\\n        }\\n      \";else{var y=e+\"(\"+e+\"(\"+e+\"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])\";\"avg\"===e&&(y=\"avgValue / count\");var x=4*Math.floor(r/4),b=r%4,w=\"\\n      if (\"+m+\") {\\n        avgValue += dot(values, ones);\\n      } else {\\n        minMaxValue = max(values, minMaxValue);\\n      }\\n    \";this.userCode=\"\\n      const ivec3 strides =\\n        ivec3(\"+o+\", \"+a+\", \"+i+\");\\n      const ivec3 pads = ivec3(\"+p+\", \"+d+\", \"+v+\");\\n      const float initializationValue = \"+g+\";\\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\\n\\n      float count = 0.0;\\n\\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\\n        if (xC < 0 || xC >= \"+t.inWidth+\") {\\n          return initializationValue;\\n        }\\n        count += 1.0;\\n        return getX(batch, xD, xR, xC, ch);\\n      }\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int ch = coords.u;\\n\\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\\n        int xDCorner = xCorner.x;\\n        int xRCorner = xCorner.y;\\n        int xCCorner = xCorner.z;\\n\\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\\n        // ? = to be determined\\n        vec4 minMaxValue = vec4(\"+g+\");\\n        float avgValue = 0.0;\\n        count = 0.0;\\n\\n        for (int wD = 0; wD < \"+l+\";\\n            wD += \"+u+\") {\\n          int xD = xDCorner + wD;\\n\\n          if (xD < 0 || xD >= \"+t.inDepth+\") {\\n            continue;\\n          }\\n\\n          for (int wR = 0; wR < \"+h+\";\\n            wR += \"+s+\") {\\n            int xR = xRCorner + wR;\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int wC = 0; wC < \"+x+\"; wC += 4) {\\n              int xC = xCCorner + wC * \"+c+\";\\n\\n              vec4 values = vec4(\\n                getValue(batch, xD, xR, xC, ch),\\n                getValue(batch, xD, xR, xC + \"+c+\", ch),\\n                getValue(batch, xD, xR, xC + 2 * \"+c+\", ch),\\n                getValue(batch, xD, xR, xC + 3 * \"+c+\", ch)\\n              );\\n\\n              \"+w+\"\\n            }\\n\\n            int xC = xCCorner + \"+x+\";\\n            if (\"+(1===b)+\") {\\n              vec4 values = vec4(\\n                getValue(batch, xD, xR, xC, ch),\\n                initializationValue,\\n                initializationValue,\\n                initializationValue\\n              );\\n\\n              \"+w+\"\\n            } else if (\"+(2===b)+\") {\\n              vec4 values = vec4(\\n                getValue(batch, xD, xR, xC, ch),\\n                getValue(batch, xD, xR, xC + \"+c+\", ch),\\n                initializationValue,\\n                initializationValue\\n              );\\n\\n              \"+w+\"\\n            } else if (\"+(3===b)+\") {\\n              vec4 values = vec4(\\n                getValue(batch, xD, xR, xC, ch),\\n                getValue(batch, xD, xR, xC + \"+c+\", ch),\\n                getValue(batch, xD, xR, xC + 2 * \"+c+\", ch),\\n                initializationValue\\n              );\\n\\n              \"+w+\"\\n            }\\n          }\\n          setOutput(\"+y+\");\\n        }\\n      }\\n    \"}}}(),Bi=function(){return function(t,e){this.variableNames=[\"x\"];var n=t.windowSize,r=t.batchSize,o=t.inSize,a=Math.ceil(o/n);this.outputShape=[r,a];var i=\"0.0\",u=\"\";\"prod\"===e?i=\"1.0\":\"min\"===e?(i=\"1.0 / 1e-20\",u=\"min\"):\"max\"===e&&(i=\"-1.0 / 1e-20\",u=\"max\");var s=e+\"(\"+e+\"(\"+e+\"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])\";\"sum\"===e?s=\"sumValue\":\"prod\"===e?s=\"prodValue\":\"all\"===e?s=\"allValue\":\"any\"===e&&(s=\"anyValue\");var c=4*Math.floor(n/4),l=n%4,h=\"\\n      if (\"+(\"sum\"===e)+\") {\\n        sumValue += dot(values, ones);\\n      } else if (\"+(\"prod\"===e)+\") {\\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\\n        prodValue *= tmp[0] * tmp[1];\\n      } else {\\n        minMaxValue = \"+u+\"(values, minMaxValue);\\n      }\\n    \",f=\"vec4\";\"all\"===e?(i=\"1.0\",h=\"\\n        bool reducedAllValue = all(values);\\n        float floatedReducedAllValue = float(reducedAllValue);\\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\\n      \",f=\"bvec4\"):\"any\"===e&&(i=\"0.0\",h=\"\\n        bool reducedAnyValue = any(values);\\n        float floatedReducedAnyValue = float(reducedAnyValue);\\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\\n      \",f=\"bvec4\");var p=\"\";o%n>0&&(p=\"\\n        if (inIdx < 0 || inIdx >= \"+o+\") {\\n          return initializationValue;\\n        }\\n      \"),this.userCode=\"\\n      const float initializationValue = \"+i+\";\\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\\n\\n      float getValue(int batch, int inIdx) {\\n        \"+p+\"\\n        return getX(batch, inIdx);\\n      }\\n\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int outIdx = coords[1];\\n        int inOffset = outIdx * \"+n+\";\\n\\n        vec4 minMaxValue = vec4(\"+i+\");\\n        float prodValue = 1.0;\\n        float sumValue = 0.0;\\n        float allValue = 1.0;\\n        float anyValue = 0.0;\\n\\n        for (int i = 0; i < \"+c+\"; i += 4) {\\n          int inIdx = inOffset + i;\\n          \"+f+\" values = \"+f+\"(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            getValue(batch, inIdx + 2),\\n            getValue(batch, inIdx + 3)\\n          );\\n\\n          \"+h+\"\\n        }\\n\\n        int inIdx = inOffset + \"+c+\";\\n        if (\"+(1===l)+\") {\\n          \"+f+\" values = \"+f+\"(\\n            getValue(batch, inIdx),\\n            initializationValue,\\n            initializationValue,\\n            initializationValue\\n          );\\n\\n          \"+h+\"\\n        } else if (\"+(2===l)+\") {\\n          \"+f+\" values = \"+f+\"(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            initializationValue,\\n            initializationValue\\n          );\\n\\n          \"+h+\"\\n        } else if (\"+(3===l)+\") {\\n          \"+f+\" values = \"+f+\"(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            getValue(batch, inIdx + 2),\\n            initializationValue\\n          );\\n\\n          \"+h+\"\\n        }\\n        setOutput(\"+s+\");\\n      }\\n    \"}}(),Pi=function(){return function(t,e){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var n=\"\",r=0;r<4;r++){var o=\"thisRC = rc;\";r%2==1&&(o+=\"thisRC.z += 1;\"),r>1&&(o+=\"thisRC.y += 1;\"),n+=\"\\n        \"+o+\"\\n        \"+(r>0?\"if(thisRC.y < rows && thisRC.z < cols){\":\"\")+\"\\n          int flatIndex = getFlatIndex(thisRC);\\n\\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\\n\\n          result[\"+r+\"] =\\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\\n        \"+(r>0?\"}\":\"\")+\"\\n      \"}this.userCode=\"\\n      \\n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\\n      \"+jo([\"r\",\"c\",\"d\"],e)+\"\\n      return ivec3(r, c, d);\\n    }\\n  \\n      \"+Xo(t)+\"\\n\\n      void main() {\\n        ivec3 rc = getOutputCoords();\\n\\n        vec4 result = vec4(0.);\\n\\n        ivec3 thisRC;\\n        int rows = \"+t[1]+\";\\n        int cols = \"+t[2]+\";\\n\\n        \"+n+\"\\n\\n        setOutput(result);\\n      }\\n    \"}}();var Li=function(){return function(t,e,n){this.variableNames=[\"dy\"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],a=r[2],i=t.shape,u=i[1],s=i[2],c=[n&&u>1?o-1:o,n&&s>1?a-1:a],l=[n&&u>1?u-1:u,n&&s>1?s-1:s],h=c[0]/l[0],f=c[1]/l[1],p=1/h,d=1/f,v=2*Math.ceil(p)+2,m=2*Math.ceil(d)+2;this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        int r = coords[1];\\n        int c = coords[2];\\n\\n        float accumulator = 0.0;\\n\\n        const float heightScale = float(\"+h+\");\\n        const float widthScale = float(\"+f+\");\\n\\n        const float invHeightScale = float(\"+p+\");\\n        const float invWidthScale = float(\"+d+\");\\n\\n        const int winHeight = int(\"+v+\");\\n        const int winWidth = int(\"+m+\");\\n\\n        // Compute bounds for where in dy we will look\\n        float startRLerp = floor(float(r) * invHeightScale);\\n        int startDyR = int(startRLerp - float(winHeight / 2));\\n\\n        float startCLerp = floor(float(c) * invWidthScale);\\n        int startDyC = int(startCLerp - float(winWidth / 2));\\n\\n        // Loop over dy\\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\\n          int dyR = dyROffset + startDyR;\\n\\n          // Guard against the window exceeding the bounds of dy\\n          if (dyR < 0 || dyR >= \"+u+\") {\\n            continue;\\n          }\\n\\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\\n            int dyC = dyCOffset + startDyC;\\n\\n            // Guard against the window exceeding the bounds of dy\\n            if (dyC < 0 || dyC >= \"+s+\") {\\n              continue;\\n            }\\n\\n            float dxR = float(dyR) * heightScale;\\n            int topDxRIndex = int(floor(dxR));\\n            int bottomDxRIndex = int(min(ceil(dxR), \"+(o-1)+\".0));\\n            float dxRLerp = dxR - float(topDxRIndex);\\n            float inverseDxRLerp = 1.0 - dxRLerp;\\n\\n            float dxC = float(dyC) * widthScale;\\n            int leftDxCIndex = int(floor(dxC));\\n            int rightDxCIndex = int(min(ceil(dxC), \"+(a-1)+\".0));\\n            float dxCLerp = dxC - float(leftDxCIndex);\\n            float inverseDxCLerp = 1.0 - dxCLerp;\\n\\n            if (r == topDxRIndex && c == leftDxCIndex) {\\n              // topLeft\\n              accumulator +=\\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\\n            }\\n\\n            if (r == topDxRIndex && c == rightDxCIndex) {\\n              // topRight\\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\\n            }\\n\\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\\n              // bottomLeft\\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\\n            }\\n\\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\\n              // bottomRight\\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\\n            }\\n          }\\n        }\\n        // End loop over dy\\n\\n        setOutput(accumulator);\\n      }\\n    \"}}(),Wi=function(){return function(t,e,n,r){this.variableNames=[\"A\"],this.outputShape=[];var o=t[0],a=t[1],i=t[2],u=t[3];this.outputShape=[o,e,n,u];var s=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode=\"\\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\\n          \"+s[0]/c[0]+\",\\n          \"+s[1]/c[1]+\");\\n      const vec2 inputShapeRC = vec2(\"+a+\".0, \"+i+\".0);\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        ivec2 yRC = coords.yz;\\n\\n        // Fractional source index.\\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\\n\\n        // Compute the four integer indices.\\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\\n        ivec2 sourceCeilRC = ivec2(\\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\\n\\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\\n\\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\\n\\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\\n        float newValue = top + (bottom - top) * fracRC.x;\\n\\n        setOutput(newValue);\\n      }\\n    \"}}(),Ui=function(){return function(t,e,n,r){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var o=t[0],a=t[1],i=t[2],u=t[3];this.outputShape=[o,e,n,u];var s=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode=\"\\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\\n          \"+s[0]/c[0]+\",\\n          \"+s[1]/c[1]+\",\\n          \"+s[1]/c[1]+\");\\n      const vec3 inputShapeRC = vec3(\"+a+\".0, \"+i+\".0,\\n                                     \"+i+\".0);\\n\\n      float getAValue(int b, int r, int c, int d) {\\n        return getChannel(getA(b, r, c, d), vec2(c, d));\\n      }\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        // Calculate values for next column in yRC.z.\\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\\n\\n        // Fractional source index.\\n        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;\\n\\n        // Compute the four integer indices.\\n        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);\\n        ivec3 sourceCeilRC = ivec3(\\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\\n\\n        // Should we calculate next column and row elements in 2x2 packed cell.\\n        bool hasNextCol = d < \"+(u-1)+\";\\n        bool hasNextRow = coords.z < \"+(n-1)+\";\\n\\n        // In parallel, construct four corners for all four components in\\n        // packed 2x2 cell.\\n        vec4 topLeft = vec4(\\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\\n                     : 0.0,\\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\\n                     : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\\n\\n        vec4 bottomLeft = vec4(\\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\\n                     : 0.0,\\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\\n                     : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\\n\\n        vec4 topRight = vec4(\\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\\n                     : 0.0,\\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\\n                     : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\\n\\n        vec4 bottomRight = vec4(\\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\\n                     : 0.0,\\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\\n                     : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\\n\\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\\n\\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\\n        vec4 newValue = mix(top, bottom, fracRC.x);\\n\\n        setOutput(newValue);\\n      }\\n    \"}}(),Vi=function(){return function(t,e,n){this.variableNames=[\"dy\"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],a=r[2],i=t.shape,u=i[1],s=i[2],c=[n&&u>1?o-1:o,n&&s>1?a-1:a],l=[n&&u>1?u-1:u,n&&s>1?s-1:s],h=c[0]/l[0],f=c[1]/l[1],p=1/h,d=1/f,v=2*Math.ceil(p)+2,m=2*Math.ceil(d)+2;this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        int r = coords[1];\\n        int c = coords[2];\\n\\n        float accumulator = 0.0;\\n\\n        const float heightScale = float(\"+h+\");\\n        const float widthScale = float(\"+f+\");\\n\\n        const float invHeightScale = float(\"+p+\");\\n        const float invWidthScale = float(\"+d+\");\\n\\n        const int winHeight = int(\"+v+\");\\n        const int winWidth = int(\"+m+\");\\n\\n        // Compute bounds for where in dy we will look\\n        float startRLerp = floor(float(r) * invHeightScale);\\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\\n\\n        float startCLerp = floor(float(c) * invWidthScale);\\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\\n\\n        // Loop over dy\\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\\n          int dyR = dyROffset + startDyR;\\n\\n          // Guard against the window exceeding the bounds of dy\\n          if (dyR < 0 || dyR >= \"+u+\") {\\n            continue;\\n          }\\n\\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\\n            int dyC = dyCOffset + startDyC;\\n\\n            // Guard against the window exceeding the bounds of dy\\n            if (dyC < 0 || dyC >= \"+s+\") {\\n              continue;\\n            }\\n\\n            float sourceFracRow =\\n              float(\"+c[0]+\") *\\n                (float(dyR) / float(\"+l[0]+\"));\\n\\n            float sourceFracCol =\\n                float(\"+c[1]+\") *\\n                  (float(dyC) / float(\"+l[1]+\"));\\n\\n            int sourceNearestRow = int(min(\\n                float(int(\"+o+\") - 1),\\n                \"+n+\" ? float(round(sourceFracRow)) :\\n                                  float(floor(sourceFracRow))));\\n\\n            int sourceNearestCol = int(min(\\n                float(int(\"+a+\") - 1),\\n                \"+n+\" ? float(round(sourceFracCol)) :\\n                                  float(floor(sourceFracCol))));\\n\\n            if (r == sourceNearestRow && c == sourceNearestCol) {\\n              accumulator += getDy(b, dyR, dyC, d);\\n            }\\n          }\\n        }\\n        // End loop over dy\\n\\n        setOutput(accumulator);\\n      }\\n    \"}}(),zi=function(){return function(t,e,n,r){this.variableNames=[\"A\"],this.outputShape=[];var o=t[0],a=t[1],i=t[2],u=t[3];this.outputShape=[o,e,n,u];var s=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n],l=r?\"0.5\":\"0.0\";this.userCode=\"\\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\\n          \"+s[0]/c[0]+\",\\n          \"+s[1]/c[1]+\");\\n      const vec2 inputShapeRC = vec2(\"+a+\".0, \"+i+\".0);\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        ivec2 yRC = coords.yz;\\n\\n        // Fractional source index.\\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\\n\\n        // Compute the coordinators of nearest neighbor point.\\n        ivec2 sourceNearestRC = ivec2(\\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + \"+l+\")));\\n\\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\\n\\n        setOutput(newValue);\\n      }\\n    \"}}(),Gi=function(){return function(t,e){this.variableNames=[\"x\"];var n=t.length;if(n>4)throw new Error(\"WebGL backend: Reverse of rank-\"+n+\" tensor is not yet supported\");if(this.outputShape=t,1!==n){var r=t.map(function(n,r){return function(n){return-1!==e.indexOf(n)&&1!==t[n]?t[n]+\" - coords[\"+n+\"] - 1\":\"coords[\"+n+\"]\"}(r)}).join(\",\"),o=aa(n);this.userCode=\"\\n      void main() {\\n        \"+o+\" coords = getOutputCoords();\\n        setOutput(getX(\"+r+\"));\\n      }\\n    \"}else this.userCode=\"\\n        void main() {\\n          int coord = getOutputCoords();\\n          setOutput(getX(\"+t[0]+\" - coord - 1));\\n        }\\n      \"}}(),Hi=function(){return function(t,e){this.variableNames=[\"x\"],this.packedInputs=!0,this.packedOutput=!0;var n=t.length;if(n>4)throw new Error(\"WebGL backend: Reverse of rank-\"+n+\" tensor is not yet supported\");this.outputShape=t;var r=qo(\"rc\",n),o=r[n-1]+\" + 1 < \"+this.outputShape[n-1],a=r[n-2]+\" + 1 < \"+this.outputShape[n-2],i=aa(n);function u(n){var r=t.map(function(r,o){return function(n,r){return-1!==e.indexOf(n)&&1!==t[n]?t[n]+\" - \"+r[n]+\" - 1\":\"\"+r[n]}(o,n)});return\"getChannel(getX(\"+r.join(\",\")+\"), vec2(\"+r.slice(-2).join(\",\")+\"))\"}this.userCode=1===n?\"\\n        void main(){\\n          int rc = getOutputCoords();\\n          vec4 result = vec4(0.);\\n          result.r = getChannel(getX(\"+t[0]+\" - rc - 1),\\n            \"+t[0]+\" - rc - 1);\\n          if(\"+o+\"){\\n              result.g = getChannel(getX(\"+t[0]+\" - (rc  + 1) - 1),\\n                \"+t[0]+\" - (rc  + 1) - 1);\\n          }\\n          setOutput(result);\\n        }\\n      \":\"\\n        void main() {\\n          \"+i+\" rc = getOutputCoords();\\n          vec4 result = vec4(0.);\\n          result.r = \"+function(t){return u(t)}(r.slice())+\";\\n          if(\"+o+\"){\\n            result.g = \"+function(t){return t[n-1]=\"(\"+t[n-1]+\" + 1)\",u(t)}(r.slice())+\";\\n          }\\n          if(\"+a+\") {\\n            result.b = \"+function(t){return t[n-2]=\"(\"+t[n-2]+\" + 1)\",u(t)}(r.slice())+\";\\n            if(\"+o+\") {\\n              result.a = \"+function(t){return t[n-1]=\"(\"+t[n-1]+\" + 1)\",t[n-2]=\"(\"+t[n-2]+\" + 1)\",u(t)}(r.slice())+\";\\n            }\\n          }\\n          setOutput(result);\\n        }\\n    \"}}(),qi=function(){return function(t,e,n,r,o,a,i){void 0===i&&(i=!0),this.variableNames=[\"updates\",\"indices\",\"defaultValue\"],this.outputShape=a;var u=aa(o.length),s=aa(a.length),c=\"\";1===n?c=\"i\":2===n&&(c=\"i, j\");var l=\"getIndices(\"+c+\")\",h=\"\";1===r?h=\"i\":2===r&&(h=\"i, coords[1]\");var f=\"getUpdates(\"+h+\")\",p=e>1?\"strides[j]\":\"strides\";this.userCode=\"\\n        \"+u+\" strides = \"+u+\"(\"+o+\");\\n\\n        void main() {\\n          \"+s+\" coords = getOutputCoords();\\n          float sum = 0.0;\\n          bool found = false;\\n          for (int i = 0; i < \"+t+\"; i++) {\\n            int flattenedIndex = 0;\\n            for (int j = 0; j < \"+e+\"; j++) {\\n              int index = round(\"+l+\");\\n              flattenedIndex += index * \"+p+\";\\n            }\\n            if (flattenedIndex == coords[0]) {\\n              sum += \"+f+\";\\n              found = true;\\n            }\\n          }\\n          setOutput(mix(getDefaultValue(), sum, float(found)));\\n        }\\n      \"}}(),Ki=function(){return function(t,e){this.variableNames=[\"x\",\"segmentIds\"];var n=t.windowSize,r=t.batchSize,o=t.inSize,a=t.numSegments,i=a*Math.ceil(o/n);this.outputShape=[r,i];var u=4*Math.floor(n/4),s=n%4,c=\"\\n        sumValue += dot(values, segFilter);\\n    \",l=\"\";o%n>0&&(l=\"\\n        if (inIdx < 0 || inIdx >= \"+o+\") {\\n          return initializationValue;\\n        }\\n      \");var h=\"\";o%n>0&&(h=\"\\n        if (inIdx < 0 || inIdx >= \"+o+\") {\\n          return -1.0;\\n        }\\n      \"),this.userCode=\"\\n      const float initializationValue = 0.0;\\n\\n      float getValue(int batch, int inIdx) {\\n        \"+l+\"\\n        return getX(batch, inIdx);\\n      }\\n\\n      float getSegmentIdAtIndex(int inIdx) {\\n        \"+h+\"\\n        return getSegmentIds(inIdx);\\n      }\\n\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int outIdx = coords[1];\\n        int inOffset = int(floor(float(outIdx) / float(\\n          \"+a+\")) * float(\"+n+\"));\\n        int currentSeg = int(mod(float(outIdx), float(\"+a+\")));\\n\\n        float sumValue = 0.0;\\n\\n        for (int i = 0; i < \"+u+\"; i += 4) {\\n          int inIdx = inOffset + i;\\n          vec4 values = vec4(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            getValue(batch, inIdx + 2),\\n            getValue(batch, inIdx + 3)\\n          );\\n\\n          vec4 segFilter = vec4(\\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\\n          );\\n\\n          \"+c+\"\\n        }\\n\\n        int inIdx = inOffset + \"+u+\";\\n        if (\"+(1===s)+\") {\\n          vec4 values = vec4(\\n            getValue(batch, inIdx),\\n            initializationValue,\\n            initializationValue,\\n            initializationValue\\n          );\\n\\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\\n\\n          vec4 segFilter = vec4(\\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\\n            0,\\n            0,\\n            0\\n          );\\n\\n          \"+c+\"\\n        } else if (\"+(2===s)+\") {\\n          vec4 values = vec4(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            initializationValue,\\n            initializationValue\\n          );\\n\\n          vec4 segFilter = vec4(\\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\\n              0,\\n              0\\n          );\\n\\n          \"+c+\"\\n        } else if (\"+(3===s)+\") {\\n          vec4 values = vec4(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            getValue(batch, inIdx + 2),\\n            initializationValue\\n          );\\n\\n          vec4 segFilter = vec4(\\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\\n            0\\n          );\\n\\n          \"+c+\"\\n        }\\n        setOutput(sumValue);\\n      }\\n    \"}}(),ji=function(){return function(t,e,n){var r,o;if(this.variableNames=[\"c\",\"a\",\"b\"],this.outputShape=e,n>4)throw Error(\"Where for rank \"+n+\" is not yet supported\");if(1===n)o=\"resRC\",r=\"resRC\";else{for(var a=[\"resRC.x\",\"resRC.y\",\"resRC.z\",\"resRC.w\"],i=[],u=[],s=0;s<e.length;s++)u.push(\"\"+a[s]),s<t&&i.push(\"\"+a[s]);r=i.join(),o=u.join()}var c=aa(n);this.userCode=\"\\n      void main() {\\n        \"+c+\" resRC = getOutputCoords();\\n        float cVal = getC(\"+r+\");\\n        if (cVal >= 1.0) {\\n          setOutput(getA(\"+o+\"));\\n        } else {\\n          setOutput(getB(\"+o+\"));\\n        }\\n      }\\n    \"}}(),Xi=function(){function t(t){this.variableNames=[\"source\"],this.outputShape=t,this.rank=t.length;var e,n=aa(this.rank),r=\"uniform int start[\"+this.rank+\"];\",o=function(t){if(1===t)return\"sourceLoc\";if(t<=6)return $i.slice(0,t).map(function(t){return\"sourceLoc.\"+t}).join(\",\");throw Error(\"Slicing for rank \"+t+\" is not yet supported\")}(this.rank);e=\"\\n        \"+n+\" sourceLoc;\\n        \"+n+\" coords = getOutputCoords();\\n        \"+t.map(function(t,e){return\"sourceLoc.\"+$i[e]+\" = start[\"+e+\"] + coords.\"+$i[e]+\";\"}).join(\"\\n\")+\"\\n      \",this.userCode=\"\\n      \"+r+\"\\n      void main() {\\n        \"+e+\"\\n        setOutput(getSource(\"+o+\"));\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error(\"The rank (\"+this.rank+\") of the program must match the length of start (\"+t.length+\")\");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,\"start\"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t)}},t}(),$i=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"];var Yi=function(){function t(t){this.variableNames=[\"source\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length;var e=aa(this.rank),n=qo(\"coords\",this.rank),r=qo(\"sourceLoc\",this.rank),o=1===this.rank?\"sourceLoc\":\"vec2(\"+r.slice(-2).join()+\")\",a=\"getChannel(getSource(\"+r.join()+\"), \"+o+\")\",i=\"\\n      result.x = \"+a+\";\\n      if (++\"+n[this.rank-1]+\" < \"+t[this.rank-1]+\") {\\n        ++\"+r[this.rank-1]+\";\\n        result.y = \"+a+\";\\n        --\"+r[this.rank-1]+\";\\n      }\\n    \",u=1===this.rank?\"\":\"\\n      --\"+n[this.rank-1]+\";\\n      if (++\"+n[this.rank-2]+\" < \"+t[this.rank-2]+\") {\\n        ++\"+r[this.rank-2]+\";\\n        result.z = \"+a+\";\\n        if (++\"+n[this.rank-1]+\" < \"+t[this.rank-1]+\") {\\n          ++\"+r[this.rank-1]+\";\\n          result.w = \"+a+\";\\n        }\\n      }\\n    \",s=this.rank<=4?\"sourceLoc = coords +\\n            \"+e+\"(\"+t.map(function(t,e){return\"start[\"+e+\"]\"}).join()+\");\":t.map(function(t,e){return r[e]+\" = \"+n[e]+\" + start[\"+e+\"];\"}).join(\"\\n\");this.userCode=\"\\n      uniform int start[\"+this.rank+\"];\\n      void main() {\\n        \"+e+\" coords = getOutputCoords();\\n        \"+e+\" sourceLoc;\\n        \"+s+\"\\n        vec4 result = vec4(0.);\\n        \"+i+\"\\n        \"+u+\"\\n        setOutput(result);\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error(\"The rank (\"+this.rank+\") of the program must match the length of start (\"+t.length+\")\");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,\"start\"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t)}},t}(),Qi=function(){return function(t,e,n){this.variableNames=[\"x\"],this.outputShape=n;var r=n.length,o=aa(n.length),a=aa(n.length),i=\"\";if(1===r)i=\"coords * strides + begin\";else{var u=0;i=n.map(function(t,e){return u++,1===n.length?\"coords * strides[\"+e+\"] + begin[\"+e+\"]\":\"coords[\"+(u-1)+\"] * strides[\"+e+\"] + begin[\"+e+\"]\"}).join(\",\")}this.userCode=\"\\n      \"+o+\" begin = \"+o+\"(\"+t+\");\\n      \"+o+\" strides = \"+o+\"(\"+e+\");\\n\\n      void main() {\\n        \"+a+\" coords = getOutputCoords();\\n        setOutput(getX(\"+i+\"));\\n      }\\n    \"}}(),Ji=function(){function t(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}return t.prototype.acquireTexture=function(t,e,n){var r,o=Zi(e,n),a=tu(t,o,n);if(a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]),this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this.log();var i=this.freeTextures[a].shift();return this.usedTextures[a].push(i),i}return this.numUsedTextures++,this.log(),o===Bt.PACKED_2X2_FLOAT32?r=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Bt.PACKED_2X2_FLOAT16?r=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Bt.UNPACKED_FLOAT32?r=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Bt.UNPACKED_FLOAT16?r=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Bt.PACKED_4X1_UNSIGNED_BYTE&&(r=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[a].push(r),r},t.prototype.releaseTexture=function(t,e,n,r){if(null!=this.freeTextures){var o=tu(e,Zi(n,r),r);o in this.freeTextures||(this.freeTextures[o]=[]),this.freeTextures[o].push(t),this.numFreeTextures++,this.numUsedTextures--;var a=this.usedTextures[o],i=a.indexOf(t);if(i<0)throw new Error(\"Cannot release a texture that was never provided by this texture manager\");a.splice(i,1),this.log()}},t.prototype.log=function(){if(this.logEnabled){var t=this.numFreeTextures+this.numUsedTextures;console.log(\"Free/Used\",this.numFreeTextures+\" / \"+this.numUsedTextures,\"(\"+t+\")\")}},t.prototype.getNumUsedTextures=function(){return this.numUsedTextures},t.prototype.getNumFreeTextures=function(){return this.numFreeTextures},t.prototype.dispose=function(){var t=this;if(null!=this.freeTextures){for(var e in this.freeTextures)this.freeTextures[e].forEach(function(e){t.gpgpu.deleteMatrixTexture(e)});for(var e in this.usedTextures)this.usedTextures[e].forEach(function(e){t.gpgpu.deleteMatrixTexture(e)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0}},t}();function Zi(t,e){if(t===Mt.UPLOAD)return Bt.PACKED_2X2_FLOAT32;if(t===Mt.RENDER||null==t)return function(t){return a().getBool(\"WEBGL_RENDER_FLOAT32_ENABLED\")?t?Bt.PACKED_2X2_FLOAT32:Bt.UNPACKED_FLOAT32:t?Bt.PACKED_2X2_FLOAT16:Bt.UNPACKED_FLOAT16}(e);if(t===Mt.DOWNLOAD||t===Mt.PIXELS)return Bt.PACKED_4X1_UNSIGNED_BYTE;throw new Error(\"Unknown logical texture type \"+t)}function tu(t,e,n){return t[0]+\"_\"+t[1]+\"_\"+e+\"_\"+n}var eu=function(){return function(t,e){this.variableNames=[\"A\"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[r]*e[r];this.outputShape=n,this.rank=n.length;var o=aa(this.rank),a=function(t){var e=t.length;if(e>5)throw Error(\"Tile for rank \"+e+\" is not yet supported\");if(1===e)return\"imod(resRC, \"+t[0]+\")\";for(var n=[\"resRC.x\",\"resRC.y\",\"resRC.z\",\"resRC.w\",\"resRC.u\"],r=[],o=0;o<t.length;o++)r.push(\"imod(\"+n[o]+\", \"+t[o]+\")\");return r.join()}(t);this.userCode=\"\\n      void main() {\\n        \"+o+\" resRC = getOutputCoords();\\n        setOutput(getA(\"+a+\"));\\n      }\\n    \"}}();var nu=function(){return function(t,e){this.variableNames=[\"A\"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];this.outputShape=n,this.rank=n.length;var o=aa(this.rank),a=function(t){var e=t.length;if(e>6)throw Error(\"Transpose for rank \"+e+\" is not yet supported\");for(var n=[\"resRC.x\",\"resRC.y\",\"resRC.z\",\"resRC.w\",\"resRC.u\",\"resRC.v\"],r=new Array(e),o=0;o<t.length;o++)r[t[o]]=n[o];return r.join()}(e);this.userCode=\"\\n    void main() {\\n      \"+o+\" resRC = getOutputCoords();\\n      setOutput(getA(\"+a+\"));\\n    }\\n    \"}}();var ru=function(){return function(t,e){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0;for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(\"Packed transpose for rank \"+this.rank+\" is not yet supported.\");var o=aa(this.rank),a=Ho(\"rc\",this.rank),i=new Array(this.rank);for(r=0;r<e.length;r++)i[e[r]]=a[r];var u=\"vec2(\"+i.slice(-2).join()+\")\",s=\"++\"+a[this.rank-1]+\" < \"+n[this.rank-1],c=\"getChannel(getA(\"+i.join()+\"), \"+u+\")\";this.userCode=\"\\n    void main() {\\n      \"+o+\" rc = getOutputCoords();\\n      vec4 result = vec4(0.);\\n      result[0] = \"+c+\";\\n      if(\"+s+\") {\\n        result[1] = \"+c+\";\\n      }\\n      --\"+a[this.rank-1]+\";\\n      if(++\"+a[this.rank-2]+\" < \"+n[this.rank-2]+\") {\\n        result[2] = \"+c+\";\\n        if(\"+s+\") {\\n          result[3] = \"+c+\";\\n        }\\n      }\\n      setOutput(result);\\n    }\\n    \"}}(),ou=1.7580993408473768,au=1.0507009873554805,iu=function(){return function(t,e){this.variableNames=[\"A\"],this.outputShape=t,this.userCode=\"\\n      float unaryOperation(float x) {\\n        \"+e+\"\\n      }\\n\\n      void main() {\\n        float x = getAAtOutCoords();\\n        float y = unaryOperation(x);\\n\\n        setOutput(y);\\n      }\\n    \"}}(),uu=\"if (isnan(x)) return x;\",su=\"return x;\",cu=\"return abs(x);\",lu=uu+\"\\n  return (x < 0.0) ? 0.0 : x;\\n\",hu=uu+\"\\n  return (x < 0.0) ? 0.0 : min(6.0, x);\\n\",fu=\"return (x >= 0.0) ? x : (exp(x) - 1.0);\",pu=\"\\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\\n  // see: https://arxiv.org/abs/1706.02515\\n  float scaleAlpha = \"+ou+\";\\n  float scale = \"+au+\";\\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\\n\";var du=\"return -x;\",vu=\"return ceil(x);\",mu=\"return floor(x);\",gu=\"return exp(x);\",yu=\"return exp(x) - 1.0;\",xu=uu+\"\\n  return sin(x);\\n\",bu=uu+\"\\n  return cos(x);\\n\",wu=uu+\"\\n  if (abs(x) > 1.) {\\n    return NAN;\\n  }\\n  return asin(x);\\n\",Cu=uu+\"\\n  if (abs(x) > 1.) {\\n    return NAN;\\n  }\\n  return acos(x);\\n\",Eu=uu+\"\\n  return atan(x);\\n\",Ru=uu+\"return log(x + sqrt(x * x + 1.0));\",Iu=uu+\"\\n  if (x < 1.0) return NAN;\\n  return log(x + sqrt(x * x - 1.0));\",ku=uu+\"\\n  if ((x < -1.0) || (x > 1.0)) return NAN;\\n  return (log(1.0 + x) - log(1.0 - x)) / 2.0;\",Su=\"return x;\",Au=\"return x;\",Du=\"\\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\\n  bvec4 isNaN = isnan(x);\\n\\n  result.r = isNaN.r ? x.r : result.r;\\n  result.g = isNaN.g ? x.g : result.g;\\n  result.b = isNaN.b ? x.b : result.b;\\n  result.a = isNaN.a ? x.a : result.a;\\n\\n  return result;\\n\",Tu=\"\\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\\n  bvec4 isNaN = isnan(x);\\n\\n  result.r = isNaN.r ? x.r : result.r;\\n  result.g = isNaN.g ? x.g : result.g;\\n  result.b = isNaN.b ? x.b : result.b;\\n  result.a = isNaN.a ? x.a : result.a;\\n\\n  return result;\\n\",Nu=\"\\n  vec4 result;\\n\\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\\n\\n  return result;\\n\",Fu=function(){return function(t,e){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode=\"\\n      vec4 unaryOperation(vec4 x) {\\n        \"+e+\"\\n      }\\n\\n      void main() {\\n        vec4 x = getAAtOutCoords();\\n        vec4 y = unaryOperation(x);\\n\\n        setOutput(y);\\n      }\\n    \"}}(),_u=function(){return function(t){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=t;var e=t.length,n=qo(\"rc\",e),r=aa(e),o=function(t,e){if(1===t)return\"rc\";for(var n=\"\",r=0;r<t;r++)n+=e[r],r<t-1&&(n+=\",\");return n}(e,n),a=n.slice(-2),i=e<=1?\"rc\":\"vec2(\"+a.join(\",\")+\")\";this.userCode=\"\\n      void main() {\\n        \"+r+\" rc = getOutputCoords();\\n        vec4 packedInput = getA(\"+o+\");\\n\\n        setOutput(getChannel(packedInput, \"+i+\"));\\n      }\\n    \"}}(),Ou={};function Mu(t,e){if(void 0===e&&(e=!1),\"linear\"===t)return e?Au:su;if(\"relu\"===t)return e?Du:lu;if(\"elu\"===t)return e?Nu:fu;if(\"relu6\"===t)return e?Tu:hu;if(\"prelu\"===t)return e?wa:xa;throw new Error(\"Activation \"+t+\" has not been implemented for the WebGL backend.\")}var Bu=600;var Pu=function(t){function o(e){var n,r=t.call(this)||this;if(r.pendingRead=new WeakMap,r.pendingDisposal=new WeakSet,r.dataRefCount=new WeakMap,r.numBytesInGPU=0,r.uploadWaitMs=0,r.downloadWaitMs=0,r.warnedAboutMemory=!1,r.pendingDeletes=0,r.disposed=!1,!a().getBool(\"HAS_WEBGL\"))throw new Error(\"WebGL is not supported on this device\");if(null==e){var o=Ut(a().getNumber(\"WEBGL_VERSION\"));r.binaryCache=(n=a().getNumber(\"WEBGL_VERSION\"))in Ou?Ou[n]:(Ou[n]={},Ou[n]),r.gpgpu=new bi(o),r.canvas=o.canvas,r.gpgpuCreatedLocally=!0}else r.gpgpu=e,r.binaryCache={},r.gpgpuCreatedLocally=!1,r.canvas=e.gl.canvas;return r.textureManager=new Ji(r.gpgpu),r.numMBBeforeWarning=null==a().global.screen?1024:a().global.screen.height*a().global.screen.width*window.devicePixelRatio*Bu/1024/1024,r.texData=new so(r,Nt),r}return e(o,t),o.prototype.numDataIds=function(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes},o.prototype.write=function(t,e,n){if(a().getBool(\"DEBUG\")&&this.checkNumericalProblems(t),\"complex64\"===n&&null!=t)throw new Error(\"Cannot write to a complex64 dtype. Please use tf.complex(real, imag).\");var r={};return this.texData.set(r,{shape:e,dtype:n,values:t,usage:Mt.UPLOAD}),r},o.prototype.move=function(t,e,n,r){if(a().getBool(\"DEBUG\")&&this.checkNumericalProblems(e),\"complex64\"===r)throw new Error(\"Cannot write to a complex64 dtype. Please use tf.complex(real, imag).\");this.texData.set(t,{shape:n,dtype:r,values:e,usage:Mt.UPLOAD})},o.prototype.readSync=function(t){var e=this.texData.get(t),n=e.values,r=e.dtype,o=e.complexTensors,a=e.slice,i=e.shape,u=e.isPacked;if(null!=a){var s=void 0;s=u?new Fu(i,Su):new iu(i,Su);var c=this.runWebGLProgram(s,[{dataId:t,shape:i,dtype:r}],r),l=this.readSync(c.dataId);return this.disposeData(c.dataId),l}if(null!=n)return this.convertAndCacheOnCPU(t);if(\"string\"===r)return n;var h,f,p=null!=this.activeTimers;(p&&(h=Y()),\"complex64\"===r)?f=No(o.real.dataSync(),o.imag.dataSync()):f=this.getValuesFromTexture(t);return p&&(this.downloadWaitMs+=Y()-h),this.convertAndCacheOnCPU(t,f)},o.prototype.read=function(t){return n(this,void 0,void 0,function(){var e,n,o,i,u,s,c,l,h,f,p,d,v,m,g,y,x,b,C,E,R,I;return r(this,function(r){switch(r.label){case 0:if(this.pendingRead.has(t))return e=this.pendingRead.get(t),[2,new Promise(function(t){return e.push(t)})];if(n=this.texData.get(t),o=n.values,i=n.shape,u=n.slice,s=n.dtype,c=n.complexTensors,l=n.isPacked,null!=u)return h=void 0,h=l?new Fu(i,Su):new iu(i,Su),f=this.runWebGLProgram(h,[{dataId:t,shape:i,dtype:s}],s),p=this.read(f.dataId),this.disposeData(f.dataId),[2,p];if(null!=o)return[2,this.convertAndCacheOnCPU(t)];if(!a().getBool(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\")&&2===a().getNumber(\"WEBGL_VERSION\"))throw new Error(\"tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.\");return d=null,\"complex64\"!==s&&a().get(\"WEBGL_BUFFER_SUPPORTED\")&&(v=this.decode(t),m=this.texData.get(v.dataId),d=(I=this.gpgpu).createBufferFromTexture.apply(I,[m.texture].concat(zt(i)))),this.pendingRead.set(t,[]),\"complex64\"===s?[3,2]:[4,this.gpgpu.createAndWaitForFence()];case 1:r.sent(),r.label=2;case 2:return\"complex64\"!==s?[3,4]:[4,Promise.all([c.real.data(),c.imag.data()])];case 3:return y=r.sent(),x=y[0],b=y[1],g=No(x,b),[3,5];case 4:null==d?g=this.getValuesFromTexture(t):(C=w(i),g=this.gpgpu.downloadFloat32MatrixFromBuffer(d,C)),r.label=5;case 5:return null!=v&&this.disposeData(v.dataId),E=this.convertAndCacheOnCPU(t,g),R=this.pendingRead.get(t),this.pendingRead.delete(t),R.forEach(function(t){return t(E)}),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t),this.pendingDeletes--),[2,E]}})})},o.prototype.checkNumericalProblems=function(t){if(null!=t)for(var e=0;e<t.length;e++){var n=t[e];if(!Xt(n)){if(a().getBool(\"WEBGL_RENDER_FLOAT32_CAPABLE\"))throw Error(\"The value \"+n+\" cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'\");throw Error(\"The value \"+n+\" cannot be represented on this device.\")}}},o.prototype.getValuesFromTexture=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,i=n.isPacked,u=w(r);if(a().getBool(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\")){var s=this.decode(t),c=this.texData.get(s.dataId),l=(e=this.gpgpu).downloadMatrixFromPackedTexture.apply(e,[c.texture].concat(zt(r))).subarray(0,u);return this.disposeData(s.dataId),l}var h=a().getBool(\"WEBGL_PACK\")&&!0===i,f=h?Ee(r):r,p=h?new ja(f):new Ka(f),d=this.runWebGLProgram(p,[{shape:f,dtype:o,dataId:t}],\"float32\"),v=this.texData.get(d.dataId),m=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(v.texture,v.texShape[0],v.texShape[1]).subarray(0,u);return this.disposeData(d.dataId),m},o.prototype.time=function(t){return n(this,void 0,void 0,function(){var e,n,o,a,i,u,s;return r(this,function(r){switch(r.label){case 0:return e=this.activeTimers,n=[],o=!1,null==this.programTimersStack?(this.programTimersStack=n,o=!0):this.activeTimers.push(n),this.activeTimers=n,t(),a=b(this.activeTimers.map(function(t){return t.query})).filter(function(t){return null!=t}),i=b(this.activeTimers.map(function(t){return t.name})).filter(function(t){return null!=t}),this.activeTimers=e,o&&(this.programTimersStack=null),[4,Promise.all(a)];case 1:return u=r.sent(),s={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:m(u),getExtraProfileInfo:function(){return u.map(function(t,e){return{name:i[e],ms:t}}).map(function(t){return t.name+\": \"+t.ms}).join(\", \")},wallMs:null},this.uploadWaitMs=0,this.downloadWaitMs=0,[2,s]}})})},o.prototype.memory=function(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU}},o.prototype.startTimer=function(){return a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")>0?this.gpgpu.beginQuery():{startMs:Y(),endMs:null}},o.prototype.endTimer=function(t){return a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")>0?(this.gpgpu.endQuery(),t):(t.endMs=Y(),t)},o.prototype.getQueryTime=function(t){return n(this,void 0,void 0,function(){var e;return r(this,function(n){return a().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")>0?[2,this.gpgpu.waitForQueryAndGetTime(t)]:[2,(e=t).endMs-e.startMs]})})},o.prototype.disposeData=function(t){if(!this.pendingDisposal.has(t)){if(this.pendingRead.has(t))return this.pendingDisposal.add(t),void this.pendingDeletes++;if(this.texData.has(t)){this.releaseGPUData(t);var e=this.texData.get(t).complexTensors;null!=e&&(e.real.dispose(),e.imag.dispose()),this.texData.delete(t)}}},o.prototype.releaseGPUData=function(t){var e=this.texData.get(t),n=e.texture,r=e.dtype,o=e.texShape,a=e.usage,i=e.isPacked,u=e.slice,s=u&&u.origDataId||t,c=this.dataRefCount.get(s);c>1?this.dataRefCount.set(s,c-1):(this.dataRefCount.delete(s),null!=n&&(this.numBytesInGPU-=this.computeBytes(o,r),this.textureManager.releaseTexture(n,o,a,i)));var l=this.texData.get(t);l.texture=null,l.texShape=null,l.isPacked=!1,l.slice=null},o.prototype.getTexture=function(t){return this.uploadToGPU(t),this.texData.get(t).texture},o.prototype.getDataInfo=function(t){return this.texData.get(t)},o.prototype.getCPUBackend=function(){return a().getBool(\"WEBGL_CPU_FORWARD\")?(null==this.cpuBackend&&(this.cpuBackend=Nt.findBackend(\"cpu\")),this.cpuBackend):null},o.prototype.shouldExecuteOnCPU=function(t,e){var n=this;return void 0===e&&(e=128),null!=this.getCPUBackend()&&t.every(function(t){return null==n.texData.get(t.dataId).texture&&t.size<e})},o.prototype.getGPGPUContext=function(){return this.gpgpu},o.prototype.complex=function(t,e){var n=this.makeOutput(t.shape,\"complex64\");return this.texData.get(n.dataId).complexTensors={real:Nt.keep(t.clone()),imag:Nt.keep(e.clone())},n},o.prototype.real=function(t){return this.texData.get(t.dataId).complexTensors.real.clone()},o.prototype.imag=function(t){return this.texData.get(t.dataId).complexTensors.imag.clone()},o.prototype.slice=function(t,e,n){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.slice(t,e,n);if(0===w(n))return In([],n,t.dtype);var r=this.texData.get(t.dataId).isPacked,o=Yr(t.shape,e,n);if(r||!o){var i=a().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")?new Yi(n):new Xi(n),u=i.getCustomSetupFunc(e);return this.compileAndRun(i,[t],null,u)}return this.uploadToGPU(t.dataId),this.shallowSlice(t,e,n)},o.prototype.shallowSlice=function(t,e,n){var r=this.texData.get(t.dataId),o=this.makeOutput(n,t.dtype),a=this.texData.get(o.dataId);Object.assign(a,r),a.shape=n,a.dtype=t.dtype;var i=Qr(e,t.strides);r.slice&&(i+=r.slice.flatOffset),a.slice={flatOffset:i,origDataId:r.slice&&r.slice.origDataId||t.dataId};var u=this.dataRefCount.get(a.slice.origDataId)||1;return this.dataRefCount.set(a.slice.origDataId,u+1),o},o.prototype.stridedSlice=function(t,e,n,r){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.stridedSlice(t,e,n,r);var o=jr(e,n,r);if(o.some(function(t){return 0===t}))return In([],o);var a=new Qi(e,r,o);return this.compileAndRun(a,[t])},o.prototype.reverse=function(t,e){var n=a().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")?new Hi(t.shape,e):new Gi(t.shape,e);return this.compileAndRun(n,[t])},o.prototype.concat=function(t,e){if(\"complex64\"===t[0].dtype){var n=t.map(function(t){return En(t)}),r=t.map(function(t){return Rn(t)});return Cn(this.concat(n,e),this.concat(r,e))}if(this.shouldExecuteOnCPU(t))return this.cpuBackend.concat(t,e);if(1===t.length)return t[0];if(t.length>a().getNumber(\"WEBGL_MAX_TEXTURES_IN_SHADER\")){var o=Math.floor(t.length/2),i=this.concat(t.slice(0,o),e),u=this.concat(t.slice(o),e);return this.concat([i,u],e)}if(a().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")&&t[0].rank>1){var s=new Sa(t.map(function(t){return t.shape}),e);return this.compileAndRun(s,t)}var c=bn(t.map(function(t){return t.shape}),e),l=t.map(function(t){return t.as2D(-1,w(t.shape.slice(e)))}),h=new ka(l.map(function(t){return t.shape}));return this.compileAndRun(h,l).reshape(c)},o.prototype.neg=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.neg(t);if(a().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,du,t.dtype);var e=new iu(t.shape,du);return this.compileAndRun(e,[t])},o.prototype.batchMatMul=function(t,e,n,r){var o=n?t.shape[2]:t.shape[1],a=r?e.shape[1]:e.shape[2],i=n?t.shape[1]:t.shape[2],u=t.shape[0];if((1===o||1===a)&&i>1e3){n&&(t=t.transpose([0,2,1])),r&&(e=e.transpose([0,2,1]));var s=1===a?t:t.as3D(u,i,1),c=1===a?2:1,l=1===a?e.as3D(u,1,i):e;return this.multiply(s,l).sum(c,!0)}var h=Ct(t.dtype,e.dtype),f=new Ai(t.shape,[u,o,a],n,r);return this.compileAndRun(f,[t,e],h)},o.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,a=t.bias,i=t.activation,u=t.preluActivationWeights,s=r?e.shape[2]:e.shape[1],c=o?n.shape[1]:n.shape[2],l=e.shape[0],h=Ct(e.dtype,n.dtype),f=null!=a,p=null!=u,d=i?Mu(i,!0):null,v=new Ai(e.shape,[l,s,c],r,o,f,d,p),m=[e,n];return a&&m.push(a),u&&m.push(u),this.compileAndRun(v,m,h)},o.prototype.multiply=function(t,e){if(\"complex64\"===t.dtype){var n=this.texData.get(t.dataId),r=this.texData.get(e.dataId),o=new va(pa,t.shape,e.shape),i=new va(da,t.shape,e.shape),u=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag),this.makeComplexComponentTensorInfo(e,r.complexTensors.real),this.makeComplexComponentTensorInfo(e,r.complexTensors.imag)],s=this.compileAndRun(o,u),c=this.compileAndRun(i,u),l=this.complex(s,c);return s.dispose(),c.dispose(),l}if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.multiply(t,e);if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,ya,t.dtype);var h=new ba(ya,t.shape,e.shape);return this.compileAndRun(h,[t,e],t.dtype)},o.prototype.batchNormalization=function(t,e,n,r,o,i){var u=[t,e,n],s=null;null!=i&&(s=i.shape,u.push(i));var c=null;if(null!=o&&(c=o.shape,u.push(o)),a().getBool(\"WEBGL_PACK_NORMALIZATION\")){var l=new fa(t.shape,e.shape,n.shape,s,c,r);return this.compileAndRun(l,u)}var h=new ha(t.shape,e.shape,n.shape,s,c,r);return this.compileAndRun(h,u)},o.prototype.localResponseNormalization4D=function(t,e,n,r,o){var i=a().getBool(\"WEBGL_PACK_NORMALIZATION\")?new Ii(t.shape,e,n,r,o):new Ei(t.shape,e,n,r,o);return this.compileAndRun(i,[t])},o.prototype.LRNGrad=function(t,e,n,r,o,a,i){var u=new Ri(e.shape,r,o,a,i);return this.compileAndRun(u,[e,n,t])},o.prototype.tile=function(t,e){if(\"string\"===t.dtype){var n=this.readSync(t.dataId).map(function(t){return Z(t)});return Lo(ir(t.shape,t.dtype,n),e)}var r=new eu(t.shape,e);return this.compileAndRun(r,[t])},o.prototype.pad=function(t,e,n){var r=a().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")?new _i(t.shape,e,n):new Fi(t.shape,e,n);return this.compileAndRun(r,[t])},o.prototype.transpose=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.transpose(t,e);var n=a().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")?new ru(t.shape,e):new nu(t.shape,e);return this.compileAndRun(n,[t])},o.prototype.gather=function(t,e,n){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.gather(t,e,n);var r=new ti(t.shape,e.size,n);return this.compileAndRun(r,[t,e])},o.prototype.batchToSpaceND=function(t,e,n){g(t.rank<=4,function(){return\"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet\"});var r=e.reduce(function(t,e){return t*e}),o=Mr(t.shape,e,r),a=Br(o.length,e.length),i=Pr(t.shape,e,r),u=Lr(n,e.length),s=Wr(i,n,e.length);return t.reshape(o).transpose(a).reshape(i).slice(u,s)},o.prototype.spaceToBatchND=function(t,e,n){g(t.rank<=4,function(){return\"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet\"});var r=e.reduce(function(t,e){return t*e}),o=[[0,0]];o.push.apply(o,n);for(var a=1+e.length;a<t.shape.length;++a)o.push([0,0]);var i=t.pad(o),u=Mr(i.shape,e,r,!1),s=Br(u.length,e.length,!1),c=Pr(i.shape,e,r,!1);return i.reshape(u).transpose(s).reshape(c)},o.prototype.reduce=function(t,e,n){var r=t.shape[0],o=t.shape[1],a=zr(o),i=new Bi({windowSize:a,inSize:o,batchSize:r},e),u=this.compileAndRun(i,[t],n);return 1===u.shape[1]?u:this.reduce(u,e,n)},o.prototype.argReduce=function(t,e,n){void 0===n&&(n=null);var r=t.shape[0],o=t.shape[1];null!=n&&(r=n.shape[0],o=n.shape[1]);var a=zr(o),i=new Go({windowSize:a,inSize:o,batchSize:r},e,null==n),u=[t];null!=n&&u.push(n);var s=this.compileAndRun(i,u,\"int32\");return 1===s.shape[1]?s:this.argReduce(t,e,s)},o.prototype.argReducePacked=function(t,e,n){void 0===n&&(n=null);var r=null!=n?n.shape:t.shape,o=zr(r[r.length-1]),a=new sa(r,o,e,null==n),i=null==n?[t]:[t,n],u=this.compileAndRun(a,i,\"int32\");return u.rank===t.rank?this.argReducePacked(t,e,u):u},o.prototype.sum=function(t,e){vn(\"sum\",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o),i=Et(t.dtype);return this.reduce(a,\"sum\",i).reshape(r)},o.prototype.prod=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.prod(t,e);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o),i=Et(t.dtype);return this.reduce(a,\"prod\",i).reshape(r)},o.prototype.unsortedSegmentSum=function(t,e,n){var r=0,o=mn([r],t.rank),a=t;null!=o&&(a=t.transpose(o),r=yn(1,t.rank)[0]);var i=function(t,e,n){for(var r=[],o=t.length,a=0;a<o;a++)a!==e?r.push(t[a]):r.push(n);return r}(a.shape,r,n),u=w([a.shape[r]]),s=a.as2D(-1,u),c=Et(t.dtype),l=this.segOpCompute(s,\"unsortedSegmentSum\",e,c,n).reshape(i);return null!=o&&(l=l.transpose(gn(o))),l},o.prototype.segOpCompute=function(t,e,n,r,o){var a=t.shape[0],i=t.shape[1],u=function(t,e){var n,r=!1;for(t<=Vr?(n=t,r=!0):n=H(t,Math.floor(Math.sqrt(t)));!r;)n>e||n===t?r=!0:n=H(t,n+1);return n}(i,o),s=new Ki({windowSize:u,inSize:i,batchSize:a,numSegments:o},e),c=this.compileAndRun(s,[t,n],r);return c.shape[1]===o?c:(n=Wn(0,o).tile([i/u]),this.segOpCompute(c,e,n,r,o))},o.prototype.argMinMaxReduce=function(t,e,n){var r=[e];if(vn(\"arg\"+n.charAt(0).toUpperCase()+n.slice(1),r,t.rank),!a().getBool(\"WEBGL_PACK_REDUCE\")||t.rank<=2){var o=pn(t.shape,r),i=o[0],u=w(o[1]),s=t.as2D(-1,u);return this.argReduce(s,n).reshape(i)}return this.argReducePacked(t,n)},o.prototype.argMin=function(t,e){return this.argMinMaxReduce(t,e,\"min\")},o.prototype.argMax=function(t,e){return this.argMinMaxReduce(t,e,\"max\")},o.prototype.cumsum=function(t,e,n,r){if(e!==t.rank-1)throw new Error(\"WebGL cumsum shader expects an inner-most axis=\"+(t.rank-1)+\" but got axis=\"+e);var o=new Ua(t.shape,n,r);return this.compileAndRun(o,[t])},o.prototype.equal=function(t,e){if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(equal(a, b));\\n\",\"bool\");var n=new ba(\"return float(a == b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.notEqual=function(t,e){if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(notEqual(a, b));\\n\",\"bool\");var n=new ba(\"return float(a != b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.less=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.less(t,e);if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(lessThan(a, b));\\n\",\"bool\");var n=new ba(\"return float(a < b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.lessEqual=function(t,e){if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(lessThanEqual(a, b));\\n\",\"bool\");var n=new ba(\"return float(a <= b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.greater=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.greater(t,e);if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(greaterThan(a, b));\\n\",\"bool\");var n=new ba(\"return float(a > b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.greaterEqual=function(t,e){if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(greaterThanEqual(a, b));\\n\",\"bool\");var n=new ba(\"return float(a >= b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.logicalNot=function(t){var e=new iu(t.shape,\"return float(!(x >= 1.0));\");return this.compileAndRun(e,[t])},o.prototype.logicalAnd=function(t,e){if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(\\n    vec4(greaterThanEqual(a, vec4(1.0))) *\\n    vec4(greaterThanEqual(b, vec4(1.0))));\\n\",\"bool\");var n=new ba(\"return float(a >= 1.0 && b >= 1.0);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.logicalOr=function(t,e){if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return min(\\n    vec4(greaterThanEqual(a, vec4(1.0))) +\\n    vec4(greaterThanEqual(b, vec4(1.0))),\\n    vec4(1.0));\\n\",\"bool\");var n=new ba(\"return float(a >= 1.0 || b >= 1.0);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.select=function(t,e,n){var r=new ji(t.rank,e.shape,e.rank);return this.compileAndRun(r,[t,e,n],Ct(e.dtype,n.dtype))},o.prototype.where=function(t){an(\"tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead\");var e=t.dataSync();return Uo(t.shape,e)},o.prototype.topk=function(t,e,n){return Wo(t.dataSync(),t.shape,t.dtype,e)},o.prototype.min=function(t,e){vn(\"min\",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o);return this.reduce(a,\"min\",a.dtype).reshape(r)},o.prototype.minimum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.minimum(t,e);var n=a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new Ca(\"\\n  vec4 result = vec4(min(a, b));\\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new ba(\"\\n  if (isnan(a)) return a;\\n  if (isnan(b)) return b;\\n\\n  return min(a, b);\\n\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.mod=function(t,e){var n=a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new Ca(\"\\n  vec4 result = mod(a, b);\\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new ba(\"if (b == 0.0) return NAN;\\n  return mod(a, b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.max=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.max(t,e);vn(\"max\",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o);return this.reduce(a,\"max\",a.dtype).reshape(r)},o.prototype.maximum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.maximum(t,e);var n=a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new Ca(\"\\n  vec4 result = vec4(max(a, b));\\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new ba(\"\\n  if (isnan(a)) return a;\\n  if (isnan(b)) return b;\\n\\n  return max(a, b);\\n\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.all=function(t,e){vn(\"all\",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o);return this.reduce(a,\"all\",a.dtype).reshape(r)},o.prototype.any=function(t,e){vn(\"any\",e,t.rank);var n=pn(t.shape,e),r=n[0],o=w(n[1]),a=t.as2D(-1,o);return this.reduce(a,\"any\",a.dtype).reshape(r)},o.prototype.squaredDifference=function(t,e){var n=a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new Ca(\"return (a - b) * (a - b);\",t.shape,e.shape):new ba(\"return (a - b) * (a - b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.realDivide=function(t,e){if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")){return this.packedBinaryOp(t,e,\"\\n  // vec4 one = vec4(equal(a, b));\\n  // return one + (vec4(1.0) - one) * a / b;\\n  vec4 result = a / b;\\n  if(a.x == b.x) {\\n    result.x = 1.;\\n  }\\n  if(a.y == b.y) {\\n    result.y = 1.;\\n  }\\n  if(a.z == b.z) {\\n    result.z = 1.;\\n  }\\n  if(a.w == b.w) {\\n    result.w = 1.;\\n  }\\n\\n  return result;\\n\",\"float32\",!0)}var n=new ba(\"\\nif (a == b) {\\n  return 1.0;\\n};\\nreturn a / b;\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"float32\")},o.prototype.floorDiv=function(t,e){if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  ivec4 ia = round(a);\\n  ivec4 ib = round(b);\\n  bvec4 cond = notEqual(ib, ivec4(0));\\n  ivec4 result = ivec4(0);\\n  vec4 s = sign(a) * sign(b);\\n\\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\\n  if (cond[0]) {\\n    result[0] = idiv(ia[0], ib[0], s[0]);\\n  }\\n  if (cond[1]) {\\n    result[1] = idiv(ia[1], ib[1], s[1]);\\n  }\\n  if (cond[2]) {\\n    result[2] = idiv(ia[2], ib[2], s[2]);\\n  }\\n  if (cond[3]) {\\n    result[3] = idiv(ia[3], ib[3], s[3]);\\n  }\\n  return vec4(result);\\n\",\"int32\");var n=new ba(\"\\n  float s = sign(a) * sign(b);\\n  int ia = round(a);\\n  int ib = round(b);\\n  if (ib != 0) {\\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\\n    return float(idiv(ia, ib, s));\\n  } else {\\n    return NAN;\\n  }\\n\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"int32\")},o.prototype.add=function(t,e){if(\"complex64\"===t.dtype&&\"complex64\"===e.dtype)return this.complexSeparableBinaryOp(t,e,ma);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.add(t,e);var n=Ct(t.dtype,e.dtype);if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,ma,n);var r=new ba(ma,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},o.prototype.packedUnaryOp=function(t,e,n){var r=new Fu(t.shape,e);return this.compileAndRun(r,[t],n)},o.prototype.packedBinaryOp=function(t,e,n,r,o){void 0===o&&(o=!1);var a=new Ca(n,t.shape,e.shape,o);return this.compileAndRun(a,[t,e],r)},o.prototype.complexSeparableBinaryOp=function(t,e,n){var r=this,o=this.texData.get(t.dataId),a=this.texData.get(e.dataId),i=[[o.complexTensors.real,a.complexTensors.real],[o.complexTensors.imag,a.complexTensors.imag]].map(function(o){var a=o[0],i=o[1],u=r.makeComplexComponentTensorInfo(t,a),s=r.makeComplexComponentTensorInfo(e,i),c=new ba(n,t.shape,e.shape);return r.compileAndRun(c,[u,s],Ct(a.dtype,i.dtype))}),u=i[0],s=i[1],c=this.complex(u,s);return u.dispose(),s.dispose(),c},o.prototype.makeComplexComponentTensorInfo=function(t,e){return{dataId:e.dataId,dtype:e.dtype,shape:t.shape}},o.prototype.addN=function(t){if(1===t.length)return t[0];if(t.length>a().get(\"WEBGL_MAX_TEXTURES_IN_SHADER\")){var e=Math.floor(t.length/2),n=this.addN(t.slice(0,e)),r=this.addN(t.slice(e));return this.addN([n,r])}var o=t.map(function(t){return t.dtype}).reduce(function(t,e){return Ct(t,e)}),i=t.map(function(t){return t.shape}),u=a().getBool(\"WEBGL_PACK\")?new zo(t[0].shape,i):new Vo(t[0].shape,i);return this.compileAndRun(u,t,o)},o.prototype.subtract=function(t,e){if(\"complex64\"===t.dtype&&\"complex64\"===e.dtype)return this.complexSeparableBinaryOp(t,e,ga);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.subtract(t,e);var n=Ct(t.dtype,e.dtype);if(a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,ga,t.dtype);var r=new ba(ga,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},o.prototype.pow=function(t,e){var n=a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new Ca(\"\\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\\n  vec4 result = multiplier * pow(abs(a), b);\\n\\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\\n  bvec4 isExpZero = equal(b, vec4(0.0));\\n  result.r = isExpZero.r ? 1.0 : result.r;\\n  result.g = isExpZero.g ? 1.0 : result.g;\\n  result.b = isExpZero.b ? 1.0 : result.b;\\n  result.a = isExpZero.a ? 1.0 : result.a;\\n\\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new ba(\"\\nif(a < 0.0 && floor(b) < b){\\n  return NAN;\\n}\\nif (b == 0.0) {\\n  return 1.0;\\n}\\nreturn (round(mod(b, 2.0)) != 1) ?\\n    pow(abs(a), b) : sign(a) * pow(abs(a), b);\\n\",t.shape,e.shape),r=Ct(t.dtype,e.dtype);return this.compileAndRun(n,[t,e],r)},o.prototype.ceil=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.ceil(t);if(a().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,vu,t.dtype);var e=new iu(t.shape,vu);return this.compileAndRun(e,[t])},o.prototype.floor=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.floor(t);if(a().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,mu,t.dtype);var e=new iu(t.shape,mu);return this.compileAndRun(e,[t])},o.prototype.sign=function(t){var e=new iu(t.shape,\"\\n  if (isnan(x)) { return 0.0; }\\n  return sign(x);\\n\");return this.compileAndRun(e,[t])},o.prototype.isNaN=function(t){var e=new iu(t.shape,\"return float(isnan(x));\");return this.compileAndRun(e,[t],\"bool\")},o.prototype.isInf=function(t){var e=new iu(t.shape,\"return float(isinf(x));\");return this.compileAndRun(e,[t],\"bool\")},o.prototype.isFinite=function(t){var e=new iu(t.shape,\"return float(!isnan(x) && !isinf(x));\");return this.compileAndRun(e,[t],\"bool\")},o.prototype.round=function(t){var e=new iu(t.shape,\"\\n  // OpenGL ES does not support round function.\\n  // The algorithm is based on banker's rounding.\\n  float base = floor(x);\\n  if ((x - base) < 0.5) {\\n    return floor(x);\\n  } else if ((x - base) > 0.5) {\\n    return ceil(x);\\n  } else {\\n    if (mod(base, 2.0) == 0.0) {\\n      return base;\\n    } else {\\n      return base + 1.0;\\n    }\\n  }\\n\");return this.compileAndRun(e,[t])},o.prototype.exp=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.exp(t);if(a().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,gu,t.dtype);var e=new iu(t.shape,gu);return this.compileAndRun(e,[t])},o.prototype.expm1=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.expm1(t);if(a().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,yu,t.dtype);var e=new iu(t.shape,yu);return this.compileAndRun(e,[t])},o.prototype.log=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.log(t);if(a().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,\"\\n  vec4 result = log(x);\\n  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));\\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\\n\\n  return result;\\n\",t.dtype);var e=new iu(t.shape,\"if (x < 0.0) return NAN;\\n  return log(x);\");return this.compileAndRun(e,[t])},o.prototype.log1p=function(t){var e=new iu(t.shape,\"return log(1.0 + x);\");return this.compileAndRun(e,[t])},o.prototype.sqrt=function(t){var e=new iu(t.shape,\"return sqrt(x);\");return this.compileAndRun(e,[t])},o.prototype.rsqrt=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.rsqrt(t);var e=new iu(t.shape,\"return inversesqrt(x);\");return this.compileAndRun(e,[t])},o.prototype.reciprocal=function(t){var e=new iu(t.shape,\"return 1.0 / x;\");return this.compileAndRun(e,[t])},o.prototype.relu=function(t){var e;return e=a().getBool(\"WEBGL_PACK\")?new Fu(t.shape,Du):new iu(t.shape,lu),this.compileAndRun(e,[t])},o.prototype.relu6=function(t){var e;return e=a().getBool(\"WEBGL_PACK\")?new Fu(t.shape,Tu):new iu(t.shape,hu),this.compileAndRun(e,[t])},o.prototype.prelu=function(t,e){var n=a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new Ca(wa,t.shape,e.shape):new ba(xa,t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.elu=function(t){if(a().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,Nu,t.dtype);var e=new iu(t.shape,fu);return this.compileAndRun(e,[t])},o.prototype.eluDer=function(t,e){var n=a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new Ca(\"\\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\\n\",t.shape,e.shape):new ba(\"return (b >= 1.0) ? a : a * (b + 1.0);\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.selu=function(t){var e=new iu(t.shape,pu);return this.compileAndRun(e,[t])},o.prototype.int=function(t){var e=new iu(t.shape,\"return float(int(x));\");return this.compileAndRun(e,[t],\"int32\")},o.prototype.clip=function(t,e,n){var r,o=(r=a().getBool(\"WEBGL_PACK_CLIP\")?new Ra(t.shape):new Ea(t.shape)).getCustomSetupFunc(e,n);return this.compileAndRun(r,[t],null,o)},o.prototype.abs=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.abs(t);if(a().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,cu,t.dtype);var e=new iu(t.shape,cu);return this.compileAndRun(e,[t])},o.prototype.complexAbs=function(t){var e=this.texData.get(t.dataId),n=new Ia(t.shape),r=[this.makeComplexComponentTensorInfo(t,e.complexTensors.real),this.makeComplexComponentTensorInfo(t,e.complexTensors.imag)];return this.compileAndRun(n,r)},o.prototype.sigmoid=function(t){var e=new iu(t.shape,\"return 1.0 / (1.0 + exp(-1.0 * x));\");return this.compileAndRun(e,[t])},o.prototype.softplus=function(t){var e=new iu(t.shape,\"\\n  float epsilon = 1.1920928955078125e-7;\\n  float threshold = log(epsilon) + 2.0;\\n\\n  bool too_large = x > -threshold;\\n  bool too_small = x < threshold;\\n\\n  float result;\\n  float exp_x = exp(x);\\n\\n  if (too_large){\\n    result = x;\\n  }\\n  else if (too_small){\\n    result = exp_x;\\n  }\\n  else{\\n    result = log(exp_x + 1.0);\\n  }\\n  return result;\\n\");return this.compileAndRun(e,[t])},o.prototype.sin=function(t){var e=new iu(t.shape,xu);return this.compileAndRun(e,[t])},o.prototype.cos=function(t){var e=new iu(t.shape,bu);return this.compileAndRun(e,[t])},o.prototype.tan=function(t){var e=new iu(t.shape,\"return tan(x);\");return this.compileAndRun(e,[t])},o.prototype.asin=function(t){var e=new iu(t.shape,wu);return this.compileAndRun(e,[t])},o.prototype.acos=function(t){var e=new iu(t.shape,Cu);return this.compileAndRun(e,[t])},o.prototype.atan=function(t){var e=new iu(t.shape,Eu);return this.compileAndRun(e,[t])},o.prototype.atan2=function(t,e){var n=a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new Ca(\"\\n  vec4 result = atan(a, b);\\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new ba(\"\\n  if (isnan(a)) return a;\\n  if (isnan(b)) return b;\\n\\n  return atan(a, b);\\n\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.sinh=function(t){var e=new iu(t.shape,\"\\n  float e2x = exp(x);\\n  return (e2x - 1.0 / e2x) / 2.0;\\n\");return this.compileAndRun(e,[t])},o.prototype.cosh=function(t){var e=new iu(t.shape,\"\\n  float e2x = exp(-x);\\n  return (e2x + 1.0 / e2x) / 2.0;\\n\");return this.compileAndRun(e,[t])},o.prototype.tanh=function(t){var e=new iu(t.shape,\"\\n  float e2x = exp(-2.0 * abs(x));\\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\\n\");return this.compileAndRun(e,[t])},o.prototype.asinh=function(t){var e=new iu(t.shape,Ru);return this.compileAndRun(e,[t])},o.prototype.acosh=function(t){var e=new iu(t.shape,Iu);return this.compileAndRun(e,[t])},o.prototype.atanh=function(t){var e=new iu(t.shape,ku);return this.compileAndRun(e,[t])},o.prototype.erf=function(t){var e=new iu(t.shape,'\\n  // Error function is calculated approximately with elementary function.\\n  // See \"Handbook of Mathematical Functions with Formulas,\\n  // Graphs, and Mathematical Tables\", Abramowitz and Stegun.\\n  float p = 0.3275911;\\n  float a1 = 0.254829592;\\n  float a2 = -0.284496736;\\n  float a3 = 1.421413741;\\n  float a4 = -1.453152027;\\n  float a5 = 1.061405429;\\n\\n  float sign = sign(x);\\n  x = abs(x);\\n  float t = 1.0 / (1.0 + p * x);\\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\\n');return this.compileAndRun(e,[t])},o.prototype.step=function(t,e){var n=new iu(t.shape,function(t){return void 0===t&&(t=0),uu+\"\\n    return x > 0.0 ? 1.0 : float(\"+t+\");\\n  \"}(e));return this.compileAndRun(n,[t])},o.prototype.conv2dByMatMul=function(t,e,n,r,o,i){var u=t.shape,s=this.texData.get(t.dataId),c=n.inChannels,l=u[0]*u[1]*u[2],h=n.outChannels,f=\"channelsLast\"===n.dataFormat,p=(1===l||1===h)&&c>1e3,d=u[2]%2!=0&&!!s.isPacked;if(p||!a().getBool(\"WEBGL_LAZILY_UNPACK\")||!a().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")||!d){var v=f?u[0]*u[1]*u[2]:u[0]*u[2]*u[3],m=this.reshape(t,[1,v,n.inChannels]),y=this.reshape(e,[1,n.inChannels,n.outChannels]);return this.reshape(this.fusedBatchMatMul({a:m,b:y,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:i}),n.outShape)}var x=f?u[0]*u[1]*(u[2]+1):u[0]*u[2]*(u[3]+1),b={dataId:t.dataId,shape:[1,x,n.inChannels],dtype:t.dtype},w=s.shape;s.shape=s.shape.slice(),s.shape[s.shape.length-2]++,g(ke(s.shape,b.shape),function(){return\"packed reshape \"+s.shape+\" to \"+b.shape+\" isn't free\"});var C=this.reshape(e,[1,n.inChannels,n.outChannels]),E=this.fusedBatchMatMul({a:b,b:C,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:i}),R=this.texData.get(E.dataId);return g(R.isPacked,function(){return\"batchMatMul result is expected to be packed\"}),s.shape=w,R.shape=n.outShape,Nt.makeTensorFromDataId(E.dataId,n.outShape,E.dtype)},o.prototype.conv2dWithIm2Row=function(t,e,n,r,o,a){var i=n.filterWidth,u=n.filterHeight,s=n.inChannels,c=n.outWidth,l=n.outHeight,h=\"channelsLast\"===n.dataFormat,f=i*u*s,p=l*c,d=[f,p],v=t.squeeze([0]),m=e.reshape([1,f,-1]),g=new Ci(d,v.shape,n),y=this.compileAndRun(g,[v]).reshape([1,d[0],d[1]]),x=null!=r,b=null!=a,w=o?Mu(o,!0):null,C=new Ai(y.shape,[1,p,n.outChannels],!0,!1,x,w,b),E=[y,m];r&&E.push(r),b&&E.push(a);var R=this.compileAndRun(C,E);return h?R.reshape([1,l,c,n.outChannels]):R.reshape([1,n.outChannels,l,c])},o.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,i=t.activation,u=t.preluActivationWeights;if(1===r.filterHeight&&1===r.filterWidth&&1===r.dilationHeight&&1===r.dilationWidth&&1===r.strideHeight&&1===r.strideWidth&&(\"SAME\"===r.padInfo.type||\"VALID\"===r.padInfo.type))return this.conv2dByMatMul(e,n,r,o,i,u);if(a().getBool(\"WEBGL_CONV_IM2COL\")&&1===e.shape[0])return this.conv2dWithIm2Row(e,n,r,o,i,u);var s=null!=o,c=null!=u,l=i?Mu(i,!1):null,h=new Ma(r,s,l,c),f=[e,n];return o&&f.push(o),u&&f.push(u),this.compileAndRun(h,f)},o.prototype.conv2d=function(t,e,n){if(1===n.filterHeight&&1===n.filterWidth&&1===n.dilationHeight&&1===n.dilationWidth&&1===n.strideHeight&&1===n.strideWidth&&(\"SAME\"===n.padInfo.type||\"VALID\"===n.padInfo.type))return this.conv2dByMatMul(t,e,n);if(a().getBool(\"WEBGL_CONV_IM2COL\")&&1===t.shape[0])return this.conv2dWithIm2Row(t,e,n);var r=new Ma(n);return this.compileAndRun(r,[t,e])},o.prototype.conv2dDerInput=function(t,e,n){var r=new Ta(n);return this.compileAndRun(r,[t,e])},o.prototype.conv2dDerFilter=function(t,e,n){var r=new Da(n);return this.compileAndRun(r,[t,e])},o.prototype.fusedDepthwiseConv2D=function(t){var e,n=t.input,r=t.filter,o=t.convInfo,i=t.bias,u=t.activation,s=t.preluActivationWeights,c=a().getBool(\"WEBGL_PACK_DEPTHWISECONV\")&&o.strideWidth<=2&&o.outChannels/o.inChannels==1,l=u?Mu(u,c):null,h=[n,r],f=null!=i,p=null!=s;return f&&h.push(i),p&&h.push(s),c?(e=new La(o,f,l,p),this.compileAndRun(e,h)):(e=new Pa(o,f,l,p),this.compileAndRun(e,h))},o.prototype.depthwiseConv2D=function(t,e,n){var r;return a().getBool(\"WEBGL_PACK_DEPTHWISECONV\")&&n.strideWidth<=2&&n.outChannels/n.inChannels==1?(r=new La(n),this.compileAndRun(r,[t,e])):(r=new Pa(n),this.compileAndRun(r,[t,e]))},o.prototype.depthwiseConv2DDerInput=function(t,e,n){var r=new Oa(n);return this.compileAndRun(r,[t,e])},o.prototype.depthwiseConv2DDerFilter=function(t,e,n){var r=new _a(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3d=function(t,e,n){var r=new Ba(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3dDerInput=function(t,e,n){var r=new Fa(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3dDerFilter=function(t,e,n){var r=new Na(n);return this.compileAndRun(r,[t,e])},o.prototype.maxPool=function(t,e){var n=new Oi(e,\"max\",!1);return this.compileAndRun(n,[t])},o.prototype.avgPool=function(t,e){var n=new Oi(e,\"avg\",!1);return this.compileAndRun(n,[t],\"float32\")},o.prototype.maxPoolBackprop=function(t,e,n,r){var o=new Oi(r,\"max\",!0),a=this.compileAndRun(o,[e]),i=new ki(r),u=this.compileAndRun(i,[t,a],e.dtype);return a.dispose(),u},o.prototype.avgPoolBackprop=function(t,e,n){var r=new ca(n);return this.compileAndRun(r,[t],e.dtype)},o.prototype.cast=function(t,e){return So(t,e,this)},o.prototype.unstack=function(t,e){for(var n=t.shape[e],r=new Array(t.rank-1),o=0,a=0;a<t.rank;a++)a!==e&&(r[o++]=t.shape[a]);var i=new Array(t.rank).fill(0),u=t.shape.slice();u[e]=1;var s=new Array(n);for(a=0;a<s.length;a++)i[e]=a,s[a]=this.slice(t,i,u).reshape(r);return s},o.prototype.avgPool3d=function(t,e){var n=new Mi(e,\"avg\",!1);return this.compileAndRun(n,[t],\"float32\")},o.prototype.avgPool3dBackprop=function(t,e,n){var r=new la(n);return this.compileAndRun(r,[t],e.dtype)},o.prototype.maxPool3d=function(t,e){var n=new Mi(e,\"max\",!1);return this.compileAndRun(n,[t],\"float32\")},o.prototype.maxPool3dBackprop=function(t,e,n,r){var o=new Mi(r,\"max\",!0),a=this.compileAndRun(o,[e]),i=new Si(r),u=this.compileAndRun(i,[t,a],e.dtype);return a.dispose(),u},o.prototype.reshape=function(t,e){var n=this.texData.get(t.dataId);if(n.isPacked&&!ke(t.shape,e)&&(null===n.texture||!ke(n.shape,e))){var r=this.packedReshape(t,e);return Nt.makeTensorFromDataId(r.dataId,r.shape,r.dtype)}return Ao(t,e)},o.prototype.resizeBilinear=function(t,e,n,r){var o=a().getBool(\"WEBGL_PACK_IMAGE_OPERATIONS\")?new Ui(t.shape,e,n,r):new Wi(t.shape,e,n,r);return this.compileAndRun(o,[t],\"float32\")},o.prototype.resizeBilinearBackprop=function(t,e,n){var r=new Li(t,e,n);return this.compileAndRun(r,[t])},o.prototype.resizeNearestNeighbor=function(t,e,n,r){var o=new zi(t.shape,e,n,r);return this.compileAndRun(o,[t])},o.prototype.resizeNearestNeighborBackprop=function(t,e,n){var r=new Vi(t,e,n);return this.compileAndRun(r,[t])},o.prototype.multinomial=function(t,e,n,r){var o=e?t:io(t),a=o.shape[0],i=o.shape[1],u=new Di(a,i,n),s=u.getCustomSetupFunc(r);return this.compileAndRun(u,[o],\"int32\",s)},o.prototype.oneHot=function(t,e,n,r){var o=new Ti(t.size,e,n,r);return this.compileAndRun(o,[t])},o.prototype.diag=function(t){var e=new qa(t.size);return this.compileAndRun(e,[t])},o.prototype.nonMaxSuppression=function(t,e,n,r,o){return an(\"tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\"),Mo(t.dataSync(),e.dataSync(),n,r,o)},o.prototype.cropAndResize=function(t,e,n,r,o,a){var i=new Wa(t.shape,e.shape,r,o,a);return this.compileAndRun(i,[t,e,n],\"float32\")},o.prototype.depthToSpace=function(t,e,n){g(e>1,function(){return\"blockSize should be > 1 for depthToSpace, but was: \"+e});var r=t.shape[0],o=\"NHWC\"===n?t.shape[1]:t.shape[2],a=\"NHWC\"===n?t.shape[2]:t.shape[3],i=\"NHWC\"===n?t.shape[3]:t.shape[1],u=o*e,s=a*e,c=i/(e*e),l=new Ha(\"NHWC\"===n?[r,u,s,c]:[r,c,u,s],e,n);return this.compileAndRun(l,[t])},o.prototype.split=function(t,e,n){return Po(t,e,n)},o.prototype.scatterND=function(t,e,n){var r=Hr(0,t,n),o=r.sliceRank,a=r.numUpdates,i=r.sliceSize,u=r.strides,s=r.outputSize,c=[s/i,i],l=t.reshape([a,o]),h=e.reshape([a,i]);if(0===s)return Ao(In([]),n);var f=Sn(0),p=new qi(a,o,l.rank,h.rank,u,c);return this.compileAndRun(p,[h,l,f]).reshape(n)},o.prototype.sparseToDense=function(t,e,n,r){var o=Hr(0,t,n),a=o.sliceRank,i=o.numUpdates,u=o.strides,s=o.outputSize,c=new qi(i,a,t.rank,e.rank,u,[s,1],!1);return this.compileAndRun(c,[e,t,r]).reshape(n)},o.prototype.fft=function(t){return this.fftImpl(t,!1)},o.prototype.ifft=function(t){return this.fftImpl(t,!0)},o.prototype.fftImpl=function(t,e){var n=this.texData.get(t.dataId),r=new Ja(Ya,t.shape,e),o=new Ja(Qa,t.shape,e),a=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag)],i=this.compileAndRun(r,a),u=this.compileAndRun(o,a),s=this.complex(i,u).as2D(t.shape[0],t.shape[1]);return i.dispose(),u.dispose(),s},o.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=Ur(t,e),a=o[0],i=o[1],u=o[2],s=o[3],c=e.reshape([i,r]),l=t.reshape([t.size/u,u]),h=new ei(r,s,[i,u]);return this.compileAndRun(h,[l,c]).reshape(a)},o.prototype.fill=function(t,e,n){if(\"string\"===(n=n||z(e))){var r=F(n,w(t));return r.fill(e),Nt.makeTensor(r,t,n,this)}var o=new Za(t,e),a=o.getCustomSetupFunc(e);return this.compileAndRun(o,[],n,a)},o.prototype.onesLike=function(t){if(\"string\"===t.dtype)throw new Error(\"onesLike is not supported under string dtype\");return this.fill(t.shape,1,t.dtype)},o.prototype.zerosLike=function(t){return this.fill(t.shape,\"string\"===t.dtype?\"\":0,t.dtype)},o.prototype.linspace=function(t,e,n){return Do(t,e,n)},o.prototype.makeTensorInfo=function(t,e){var n=this.write(null,t,e);return this.texData.get(n).usage=null,{dataId:n,shape:t,dtype:e}},o.prototype.makeOutput=function(t,e){var n=this.makeTensorInfo(t,e).dataId;return Nt.makeTensorFromDataId(n,t,e,this)},o.prototype.unpackTensor=function(t){var e=new _u(t.shape);return this.runWebGLProgram(e,[t],t.dtype)},o.prototype.packTensor=function(t){var e=new Ni(t.shape);return this.runWebGLProgram(e,[t],t.dtype,null,!0)},o.prototype.packedReshape=function(t,e){var n=[we(t.shape)].concat(Ce(t.shape)),r={dtype:t.dtype,shape:n,dataId:t.dataId},o=[we(e)].concat(Ce(e)),a=new Pi(o,n),i=this.runWebGLProgram(a,[r],t.dtype,null,!0);return{dataId:i.dataId,shape:e,dtype:i.dtype}},o.prototype.decode=function(t){var e,n=this.texData.get(t),r=n.isPacked,o=n.shape,a=n.dtype,i=Ee(o);e=r?new Ga(i):new za(i);return{dtype:a,shape:o,dataId:this.runWebGLProgram(e,[{shape:i,dtype:a,dataId:t}],a,null,!0).dataId}},o.prototype.runWebGLProgram=function(t,e,n,r,o){var i=this;void 0===o&&(o=!1);var u=this.makeTensorInfo(t.outputShape,n),s=this.texData.get(u.dataId);if(t.packedOutput&&(s.isPacked=!0),t.outPackingScheme===Ot.DENSE){var c=zt(t.outputShape);s.texShape=c.map(function(t){return 2*t})}if(null!=t.outTexUsage&&(s.usage=t.outTexUsage),0===w(u.shape))return s.values=N(u.dtype,0),u;var l=[],h=e.map(function(e){if(\"complex64\"===e.dtype)throw new Error(\"GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.\");var n=i.texData.get(e.dataId);if(null==n.texture){if(!t.packedInputs&&w(e.shape)<=a().getNumber(\"WEBGL_SIZE_UPLOAD_UNIFORM\"))return{shape:e.shape,texData:null,isUniform:!0,uniformValues:n.values};t.packedInputs&&(n.isPacked=!0,n.shape=e.shape)}else if(!!n.isPacked!=!!t.packedInputs)e=n.isPacked?i.unpackTensor(e):i.packTensor(e),l.push(e),n=i.texData.get(e.dataId);else if(n.isPacked&&!ke(n.shape,e.shape)){var r=e,o=e.shape;e.shape=n.shape,e=i.packedReshape(e,o),l.push(e),n=i.texData.get(e.dataId),r.shape=o}return i.uploadToGPU(e.dataId),{shape:e.shape,texData:n,isUniform:!1}});this.uploadToGPU(u.dataId);var f,p={shape:u.shape,texData:s,isUniform:!1},d=function(t,e,n){var r=\"\";e.concat(n).forEach(function(t){var e=null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0,n=t.isUniform?\"uniform\":t.texData.texShape;r+=t.shape+\"_\"+n+\"_\"+e});var o=t.userCode,a=t.constructor.name;return a+=\"_\"+r+\"_\"+o}(t,h,p),v=this.getAndSaveBinary(d,function(){return function(t,e,n,r){var o=e.userCode,i=n.map(function(t,n){var r={logicalShape:t.shape,texShape:t.isUniform?null:t.texData.texShape,isUniform:t.isUniform,isPacked:!t.isUniform&&t.texData.isPacked,flatOffset:null};return null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0&&(r.flatOffset=t.texData.slice.flatOffset),{name:e.variableNames[n],shapeInfo:r}}),u=i.map(function(t){return t.shapeInfo}),s={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},c=Yo(i,s,o,e.packedInputs),l=t.createProgram(c),h=null,f=t.getUniformLocation(l,\"NAN\",!1);1===a().getNumber(\"WEBGL_VERSION\")&&(h=t.getUniformLocation(l,\"INFINITY\",!1));for(var p={},d=0;d<e.variableNames.length;d++){var v=e.variableNames[d];p[v]=t.getUniformLocation(l,v,!1),p[\"offset\"+v]=t.getUniformLocation(l,\"offset\"+v,!1)}return{program:e,source:c,webGLProgram:l,uniformLocations:p,inShapeInfos:u,outShapeInfo:s,infLoc:h,nanLoc:f}}(i.gpgpu,t,h,p)}),m=null!=this.activeTimers;if(m&&(f=this.startTimer()),function(t,e,n,r,o){wi(e.inShapeInfos,n),wi([e.outShapeInfo],[r]);var i=r.texData.texture,u=r.texData.texShape;r.texData.isPacked?t.setOutputPackedMatrixTexture(i,u[0],u[1]):t.setOutputMatrixTexture(i,u[0],u[1]),t.setProgram(e.webGLProgram),1===a().getNumber(\"WEBGL_VERSION\")&&null!==e.infLoc&&t.gl.uniform1f(e.infLoc,1/0),null!==e.nanLoc&&t.gl.uniform1f(e.nanLoc,NaN),n.forEach(function(n,r){var o=e.program.variableNames[r],a=e.uniformLocations[o],i=e.uniformLocations[\"offset\"+o];if(null!=a)if(n.isUniform)if(w(n.shape)<2)t.gl.uniform1f(a,n.uniformValues[0]);else{var u=n.uniformValues;u instanceof Float32Array||(u=new Float32Array(u)),t.gl.uniform1fv(a,u)}else null!=n.texData.slice&&null!=i&&t.gl.uniform1i(i,n.texData.slice.flatOffset),t.setInputMatrixTexture(n.texData.texture,a,r)}),null!=o&&o(t,e.webGLProgram),t.executeProgram()}(this.gpgpu,v,h,p,r),l.forEach(function(t){return i.disposeData(t.dataId)}),m&&(f=this.endTimer(f),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(f)})),!a().getBool(\"WEBGL_LAZILY_UNPACK\")&&s.isPacked&&!1===o){var g=this.unpackTensor(u);return this.disposeData(u.dataId),g}return u},o.prototype.compileAndRun=function(t,e,n,r,o){void 0===o&&(o=!1),n=n||e[0].dtype;var a=this.runWebGLProgram(t,e,n,r,o);return Nt.makeTensorFromDataId(a.dataId,a.shape,a.dtype)},o.prototype.getAndSaveBinary=function(t,e){return t in this.binaryCache||(this.binaryCache[t]=e()),this.binaryCache[t]},o.prototype.getTextureManager=function(){return this.textureManager},o.prototype.dispose=function(){this.disposed||(this.textureManager.dispose(),null!=this.canvas&&\"undefined\"!=typeof HTMLCanvasElement&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)},o.prototype.floatPrecision=function(){var t=this;return null==this.floatPrecisionValue&&(this.floatPrecisionValue=Ke(function(){if(!a().get(\"WEBGL_RENDER_FLOAT32_ENABLED\")){var e=a().getBool(\"DEBUG\");a().set(\"DEBUG\",!1);var n=t.abs(Sn(1e-8)).dataSync()[0];if(a().set(\"DEBUG\",e),n>0)return 32}return 16})),this.floatPrecisionValue},o.prototype.epsilon=function(){return 32===this.floatPrecision()?1e-7:1e-4},o.prototype.uploadToGPU=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,a=n.values,i=n.texture,u=n.usage,s=n.isPacked;if(null==i){var c,l=null!=this.activeTimers;l&&(c=Y());var h=n.texShape;if(null==h&&(h=Re(r,s),n.texShape=h),null!=a){var f=Ee(r),p=void 0,d=h[1],v=h[0],m=a instanceof Uint8Array;s?(d=(e=Gt(h[0],h[1]))[0],v=e[1],p=new $a(f,[v,d],m)):p=new Xa(f,[v,d],m);var g=this.makeTensorInfo([v,d],o);this.texData.get(g.dataId).usage=m?Mt.PIXELS:Mt.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId),d,v,a);var y=this.runWebGLProgram(p,[g],o,null,!0),x=this.texData.get(y.dataId);n.texture=x.texture,n.texShape=x.texShape,n.isPacked=x.isPacked,n.usage=x.usage,this.disposeData(g.dataId),this.texData.delete(y.dataId),n.values=null,l&&(this.uploadWaitMs+=Y()-c)}else{var b=this.acquireTexture(h,u,o,s);n.texture=b}}},o.prototype.convertAndCacheOnCPU=function(t,e){var n=this.texData.get(t),r=n.dtype;return this.releaseGPUData(t),null!=e&&(n.values=function(t,e){if(\"float32\"===e||\"complex64\"===e)return t;if(\"int32\"===e||\"bool\"===e){for(var n=\"int32\"===e?new Int32Array(t.length):new Uint8Array(t.length),r=0;r<n.length;++r)n[r]=Math.round(t[r]);return n}throw new Error(\"Unknown dtype \"+e)}(e,r)),n.values},o.prototype.acquireTexture=function(t,e,n,r){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>1024*this.numMBBeforeWarning*1024){var o=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(\"High memory usage in GPU: \"+o+\" MB, most likely due to a memory leak\")}return this.textureManager.acquireTexture(t,e,r)},o.prototype.computeBytes=function(t,e){return t[0]*t[1]*P(e)},o}(co);Ft()&&Nt.registerBackend(\"webgl\",function(){return new Pu},2);var Lu=wn({square_:function(t){var e=cn(t,\"x\",\"square\"),n=[e];return Nt.runKernelFunc(function(t,n){return n([e]),t.square(e)},{x:e},function(t,e){var n=e[0];return{x:function(){return t.mul(n.toFloat().mul(2))}}},\"Square\",{},n,[])}});var Wu=wn({abs_:function(t){var e=cn(t,\"x\",\"abs\");return\"complex64\"===e.dtype?Nt.runKernelFunc(function(t){return t.complexAbs(e)},{$x:e}):Nt.runKernelFunc(function(t,n){var r=t.abs(e);return n([e]),r},{x:e},function(t,e){var n=e[0];return{x:function(){return t.mul(n.toFloat().step(-1))}}},\"Abs\")}}),Uu=wn({acos_:function(t){var e=cn(t,\"x\",\"acos\");return Nt.runKernelFunc(function(t,n){var r=t.acos(e);return n([e]),r},{$x:e},function(t,e){var n=e[0];return{$x:function(){return t.divStrict(Sn(1).sub(n.toFloat().square()).sqrt()).neg()}}})}}),Vu=wn({acosh_:function(t){var e=cn(t,\"x\",\"acosh\");return Nt.runKernelFunc(function(t,n){var r=t.acosh(e);return n([e]),r},{$x:e},function(t,e){var n=e[0];return{$x:function(){return t.divStrict(n.toFloat().square().sub(1).sqrt())}}})}}),zu=wn({asin_:function(t){var e=cn(t,\"x\",\"asin\");return Nt.runKernelFunc(function(t,n){var r=t.asin(e);return n([e]),r},{$x:e},function(t,e){var n=e[0];return{$x:function(){return t.divStrict(Sn(1).sub(n.toFloat().square()).sqrt())}}})}}),Gu=wn({asinh_:function(t){var e=cn(t,\"x\",\"asinh\");return Nt.runKernelFunc(function(t,n){var r=t.asinh(e);return n([e]),r},{$x:e},function(t,e){var n=e[0];return{$x:function(){return t.divStrict(Sn(1).add(n.toFloat().square()).sqrt())}}})}}),Hu=wn({atan_:function(t){var e=cn(t,\"x\",\"atan\");return Nt.runKernelFunc(function(t,n){var r=t.atan(e);return n([e]),r},{$x:e},function(t,e){var n=e[0];return{$x:function(){return t.div(n.toFloat().square().add(1))}}})}}),qu=wn({atanh_:function(t){var e=cn(t,\"x\",\"atanh\");return Nt.runKernelFunc(function(t,n){var r=t.atanh(e);return n([e]),r},{$x:e},function(t,e){var n=e[0];return{$x:function(){return t.div(Sn(1).sub(n.toFloat().square()))}}})}}),Ku=wn({ceil_:function(t){var e=cn(t,\"x\",\"ceil\");return Nt.runKernelFunc(function(t){return t.ceil(e)},{$x:e},function(t){return{$x:function(){return Vn(t)}}})}}),ju=wn({clipByValue_:function(t,e,n){var r=cn(t,\"x\",\"clipByValue\");g(e<=n,function(){return\"Error in clip: min (\"+e+\") must be less than or equal to max (\"+n+\").\"});var o=[r],a={min:e,max:n};return Nt.runKernelFunc(function(t,o){var a=t.clip(r,e,n);return o([r]),a},{x:r},function(t,r){var o=r[0];return{x:function(){return t.where(o.greaterEqual(e).logicalAnd(o.lessEqual(n)),Vn(t))}}},\"ClipByValue\",a,o)}}),Xu=wn({cos_:function(t){var e=cn(t,\"x\",\"cos\");return Nt.runKernelFunc(function(t,n){var r=t.cos(e);return n([e]),r},{$x:e},function(t,e){var n=e[0];return{$x:function(){return n.toFloat().sin().neg().mul(t)}}})}}),$u=wn({cosh_:function(t){var e=cn(t,\"x\",\"cosh\");return Nt.runKernelFunc(function(t,n){var r=t.cosh(e);return n([e]),r},{$x:e},function(t,e){var n=e[0];return{$x:function(){return n.toFloat().sinh().mulStrict(t)}}})}}),Yu=wn({erf_:function(t){var e=cn(t,\"x\",\"erf\");return g(\"int32\"===e.dtype||\"float32\"===e.dtype,function(){return\"Input dtype must be `int32` or `float32`.\"}),\"int32\"===e.dtype&&(e=e.toFloat()),Nt.runKernelFunc(function(t,n){var r=t.erf(e);return n([e]),r},{$x:e},function(t,e){var n=e[0];return{$x:function(){return 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Got dilations '\"+a+\"'\"});var n=e[0],r=e[1];return{x:function(){return _c(n.shape,t,r,h)},filter:function(){return Oc(n,t,r.shape,h)}}},\"DepthwiseConv2dNative\",h,f);return l?p.as3D(p.shape[1],p.shape[2],p.shape[3]):p}}),_c=wn({depthwiseConv2dDerInput_:function(t,e,n,r){var o=e,a=!1;3===e.rank&&(a=!0,o=e.as4D(1,e.shape[0],e.shape[1],e.shape[2]));var i=Nt.runKernelFunc(function(t){return t.depthwiseConv2DDerInput(o,n,r)},{dy4D:o});return a?i.as3D(i.shape[1],i.shape[2],i.shape[3]):i}}),Oc=wn({depthwiseConv2dDerFilter_:function(t,e,n,r){var o=t;3===t.rank&&(o=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var a=e;return 3===a.rank&&(a=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),Nt.runKernelFunc(function(t){return t.depthwiseConv2DDerFilter(o,a,r)},{x4D:o,dy4D:a})}}),Mc=wn({separableConv2d_:function(t,e,n,r,o,a,i){void 0===a&&(a=[1,1]),void 0===i&&(i=\"NHWC\");var u=cn(t,\"x\",\"separableConv2d\"),s=cn(e,\"depthwiseFilter\",\"separableConv2d\"),c=cn(n,\"pointwiseFilter\",\"separableConv2d\"),l=u,h=!1;if(3===u.rank&&(h=!0,l=u.as4D(1,u.shape[0],u.shape[1],u.shape[2])),\"NCHW\"===i)throw new Error(\"separableConv2d currently does not support dataFormat NCHW; only NHWC is supported\");g(4===l.rank,function(){return\"Error in separableConv2d: input must be rank 4, but got rank \"+l.rank+\".\"}),g(4===s.rank,function(){return\"Error in separableConv2d: depthwise filter must be rank 4, but got rank \"+s.rank+\".\"}),g(4===c.rank,function(){return\"Error in separableConv2d: pointwise filter must be rank 4, but got rank \"+s.rank+\".\"}),g(1===c.shape[0],function(){return\"Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got \"+c.shape[0]+\".\"}),g(1===c.shape[1],function(){return\"Error in separableConv2d: the second dimension of pointwise filter must be 1, but got \"+c.shape[1]+\".\"});var f=s.shape[2],p=s.shape[3];g(c.shape[2]===f*p,function(){return\"Error in separableConv2d: the third dimension of pointwise filter must be \"+f*p+\", but got \"+c.shape[2]+\".\"});var d=Fc(l,s,r,o,i,a),v=Ac(d,c,1,\"valid\",i);return h?v.as3D(v.shape[1],v.shape[2],v.shape[3]):v}}),Bc=wn({conv2dTranspose_:function(t,e,n,r,o,a){return Rc(n,cn(t,\"x\",\"conv2dTranspose\"),cn(e,\"filter\",\"conv2dTranspose\"),r,o,\"NHWC\",a)}}),Pc=wn({conv3dTranspose_:function(t,e,n,r,o){return kc(n,cn(t,\"x\",\"conv3dTranspose\"),cn(e,\"filter\",\"conv3dTranspose\"),r,o)}});var Lc=wn({matMul_:function(t,e,n,r){var o;void 0===n&&(n=!1),void 0===r&&(r=!1);var a=cn(t,\"a\",\"matMul\"),i=cn(e,\"b\",\"matMul\");o=Rt(a,i),a=o[0],i=o[1];var u=n?a.shape[a.rank-2]:a.shape[a.rank-1],s=r?i.shape[i.rank-1]:i.shape[i.rank-2],c=n?a.shape[a.rank-1]:a.shape[a.rank-2],l=r?i.shape[i.rank-2]:i.shape[i.rank-1],h=a.shape.slice(0,-2),f=i.shape.slice(0,-2),p=w(h),d=w(f);g(a.rank>=2&&i.rank>=2&&a.rank===i.rank,function(){return\"Error in matMul: inputs must have the same rank of at least 2, got ranks \"+a.rank+\" and \"+i.rank+\".\"}),g(C(h,f),function(){return\"Error in matMul: outer dimensions (\"+h+\") and (\"+f+\") of Tensors with shapes \"+a.shape+\" and \"+i.shape+\" must match.\"}),g(u===s,function(){return\"Error in matMul: inner shapes (\"+u+\") and (\"+s+\") of Tensors with shapes \"+a.shape+\" and \"+i.shape+\" and transposeA=\"+n+\" and transposeB=\"+r+\" must match.\"});var v=a.shape.slice(0,-2).concat([c,l]),m=n?a.as3D(p,u,c):a.as3D(p,c,u),y=r?i.as3D(d,l,s):i.as3D(d,s,l),x={transposeA:n,transposeB:r};return Nt.runKernelFunc(function(t,e){var o=t.batchMatMul(m,y,n,r);return e([m,y]),o},{a:m,b:y},function(t,e){var o=e,a=o[0],i=o[1];return n||r?!n&&r?{a:function(){return t.matMul(i,!1,!1)},b:function(){return t.matMul(a,!0,!1)}}:n&&!r?{a:function(){return i.matMul(t,!1,!0)},b:function(){return a.matMul(t,!1,!1)}}:{a:function(){return i.matMul(t,!0,!0)},b:function(){return t.matMul(a,!0,!0)}}:{a:function(){return t.matMul(i,!1,!0)},b:function(){return a.matMul(t,!0,!1)}}},\"BatchMatMul\",x).reshape(v)}}),Wc=wn({dot_:function(t,e){var n=cn(t,\"t1\",\"dot\"),r=cn(e,\"t2\",\"dot\");g(!(1!==n.rank&&2!==n.rank||1!==r.rank&&2!==r.rank),function(){return\"Error in dot: inputs must all be rank 1 or 2, but got ranks \"+n.rank+\" and \"+r.rank+\".\"});var o=1===n.rank?n.size:n.shape[1],a=1===r.rank?r.size:r.shape[0];return g(o===a,function(){return\"Error in dot: inner dimensions of inputs must match, but got \"+o+\" and 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\"+e.rank+\".\"}),Vc(e,0)}}),Gc=wn({reverse2d_:function(t,e){var n=cn(t,\"x\",\"reverse\");return g(2===n.rank,function(){return\"Error in reverse2D: x must be rank 2 but got rank \"+n.rank+\".\"}),Vc(n,e)}}),Hc=wn({reverse3d_:function(t,e){var n=cn(t,\"x\",\"reverse\");return g(3===n.rank,function(){return\"Error in reverse3D: x must be rank 3 but got rank \"+n.rank+\".\"}),Vc(n,e)}}),qc=wn({reverse4d_:function(t,e){var n=cn(t,\"x\",\"reverse\");return g(4===n.rank,function(){return\"Error in reverse4D: x must be rank 4 but got rank \"+n.rank+\".\"}),Vc(n,e)}});function Kc(t,e,n,r,o,a){var i=cn(t,\"x\",\"maxPool\"),u=i,s=!1;3===i.rank&&(s=!0,u=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),null==r&&(r=[1,1]),g(4===u.rank,function(){return\"Error in maxPool: input must be rank 4 but got rank \"+u.rank+\".\"}),g(Io(n,r),function(){return\"Error in maxPool: Either strides or dilations must be 1. Got strides \"+n+\" and dilations '\"+r+\"'\"}),null!=a&&g(E(o),function(){return\"Error in maxPool: pad must be an integer when using, dimRoundingMode \"+a+\" but got pad \"+o+\".\"});var c=vo(u.shape,e,n,r,o,a);if(1===c.filterWidth&&1===c.filterHeight&&C(c.inShape,c.outShape))return i.clone();var l=[u],h=Nt.runKernelFunc(function(t,e){var n=t.maxPool(u,c);return e([u,n]),n},{x:u},function(t,a){var i=a[0],u=a[1];return{x:function(){return function(t,e,n,r,o,a,i,u){var s=cn(t,\"dy\",\"maxPoolBackprop\"),c=cn(e,\"input\",\"maxPoolBackprop\"),l=cn(n,\"output\",\"maxPoolBackprop\");g(c.rank===s.rank,function(){return\"Rank of input (\"+c.rank+\") does not match rank of dy (\"+s.rank+\")\"}),null==a&&(a=[1,1]),g(Io(o,a),function(){return\"Error in maxPoolBackProp: Either strides or dilations must be 1. Got strides \"+o+\" and dilations '\"+a+\"'\"}),g(4===s.rank,function(){return\"Error in maxPoolBackprop: dy must be rank 4 but got rank \"+s.rank+\".\"}),g(4===c.rank,function(){return\"Error in maxPoolBackprop: input must be rank 4 but got rank \"+c.rank+\".\"}),null!=u&&g(E(i),function(){return\"Error in maxPoolBackprop: pad must be an integer when using, dimRoundingMode \"+u+\" but got pad \"+i+\".\"});var h=vo(c.shape,r,o,a,i,u);return Nt.runKernelFunc(function(t){return t.maxPoolBackprop(s,c,l,h)},{$dy:s,$input:c})}(t,i,u,e,n,r,o)}}},\"MaxPool\",c,l);return s?h.as3D(h.shape[1],h.shape[2],h.shape[3]):h}function jc(t,e,n,r,o,a){var i=cn(t,\"x\",\"avgPool\",\"float32\");null==r&&(r=[1,1]),g(Io(n,r),function(){return\"Error in avgPool: Either strides or dilations must be 1. Got strides \"+n+\" and dilations '\"+r+\"'\"});var u=i,s=!1;3===i.rank&&(s=!0,u=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),g(4===u.rank,function(){return\"Error in avgPool: x must be rank 4 but got rank \"+u.rank+\".\"}),null!=a&&g(E(o),function(){return\"Error in avgPool: pad must be an integer when using, dimRoundingMode \"+a+\" but got pad \"+o+\".\"});var c=vo(u.shape,e,n,r,o,a);if(1===c.filterWidth&&1===c.filterHeight&&C(c.inShape,c.outShape))return i.clone();var l=Nt.runKernelFunc(function(t){return t.avgPool(u,c)},{x:u},function(t){return{x:function(){return function(t,e,n,r,o,a){var i=cn(t,\"dy\",\"avgPoolBackprop\"),u=cn(e,\"input\",\"avgPoolBackprop\");g(u.rank===i.rank,function(){return\"Rank of input (\"+u.rank+\") does not match rank of dy (\"+i.rank+\")\"}),null==o&&(o=[1,1]),g(Io(r,o),function(){return\"Error in avgPoolBackprop: Either strides or dilations must be 1. Got strides \"+r+\" and dilations '\"+o+\"'\"});var s=u,c=i,l=!1;3===u.rank&&(l=!0,s=u.as4D(1,u.shape[0],u.shape[1],u.shape[2]),c=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),g(4===c.rank,function(){return\"Error in avgPoolBackprop: dy must be rank 4 but got rank \"+c.rank+\".\"}),g(4===s.rank,function(){return\"Error in avgPoolBackprop: input must be rank 4 but got rank \"+s.rank+\".\"});var h=vo(s.shape,n,r,o,a),f=Nt.runKernelFunc(function(t){return t.avgPoolBackprop(c,s,h)},{dy4D:c,input4D:s});return l?f.as3D(f.shape[1],f.shape[2],f.shape[3]):f}(t,u,e,n,r,o)}}},\"AvgPool\",c);return l=l.cast(i.dtype),s?l.as3D(l.shape[1],l.shape[2],l.shape[3]):l}var Xc=wn({maxPool_:function(t,e,n,r,o){return Kc(t,e,n,1,r,o)}}),$c=wn({avgPool_:function(t,e,n,r,o){return jc(t,e,n,1,r,o)}}),Yc=wn({pool_:function(t,e,n,r,o,a){null==o&&(o=[1,1]),null==a&&(a=1),0===r&&(r=\"valid\");var i=cn(t,\"x\",\"maxPool\"),u=i,s=!1;3===i.rank&&(s=!0,u=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),g(Io(a,o),function(){return\"Error in pool: Either strides or dilations must be 1. Got strides \"+a+\" and dilations '\"+o+\"'\"});var c,l=vo(u.shape,e,a,o,r),h=[l.dilationHeight,l.dilationWidth];c=\"same\"===r?function(t,e){var n=t.map(function(t,n){return t+(t-1)*(e[n]-1)}).map(function(t){return t-1}),r=n.map(function(t){return Math.floor(t/2)}),o=n.map(function(t,e){return t-r[e]});return n.map(function(t,e){return[r[e],o[e]]})}([l.filterHeight,l.filterWidth],h):[[0,0],[0,0]];var f=1===h[0]&&1===h[1],p=function(t,e,n){var r=n.map(function(t){return t[0]}),o=n.map(function(t){return t[1]}),a=t.concat(r,o),i=e.map(function(t,e){return(t-a[e]%t)%t}),u=o.map(function(t,e){return t+i[e]}),s=e.map(function(t,e){return[r[e],u[e]]}),c=e.map(function(t,e){return[0,i[e]]});return[s,c]}([l.inHeight,l.inWidth],h,c),d=p[0],v=p[1],m=f?r:\"valid\",y=f?u:Ar(u,h,d),x=(\"avg\"===n?function(){return jc(y,e,a,1,m)}:function(){return Kc(y,e,a,1,m)})(),b=f?x:sr(x,h,v);return s?b.as3D(b.shape[1],b.shape[2],b.shape[3]):b}}),Qc=wn({maxPool3d_:function(t,e,n,r,o,a,i){void 0===a&&(a=\"NDHWC\");var u=cn(t,\"x\",\"maxPool3d\"),s=u,c=!1;4===u.rank&&(c=!0,s=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3])),null==i&&(i=[1,1,1]),g(5===s.rank,function(){return\"Error in maxPool3d: x must be rank 5 but got rank \"+s.rank+\".\"}),g(\"NDHWC\"===a,function(){return\"Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of \"+a}),g(Io(n,i),function(){return\"Error in maxPool3d: Either strides or dilations must be 1. Got strides \"+n+\" and dilations '\"+i+\"'\"}),null!=o&&g(E(r),function(){return\"Error in maxPool3d: pad must be an integer when using, dimRoundingMode \"+o+\" but got pad \"+r+\".\"});var l=mo(s.shape,e,n,i,r,o,a),h=Nt.runKernelFunc(function(t,e){var n=t.maxPool3d(s,l);return e([s,n]),n},{x:s},function(t,a){var u=a[0],s=a[1];return{x:function(){return function(t,e,n,r,o,a,i,u){var s=cn(t,\"dy\",\"maxPool3dBackprop\"),c=cn(e,\"input\",\"maxPool3dBackprop\"),l=cn(n,\"output\",\"maxPool3dBackprop\"),h=s,f=c,p=l,d=!1;4===c.rank&&(d=!0,h=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3]),f=c.as5D(1,c.shape[0],c.shape[1],c.shape[2],c.shape[3]),p=l.as5D(1,l.shape[0],l.shape[1],l.shape[2],l.shape[3])),g(5===h.rank,function(){return\"Error in maxPool3dBackprop: dy must be rank 5 but got rank \"+h.rank+\".\"}),g(5===f.rank,function(){return\"Error in maxPool3dBackprop: input must be rank 5 but got rank \"+f.rank+\".\"}),g(5===p.rank,function(){return\"Error in maxPool3dBackprop: output must be rank 5 but got rank \"+p.rank+\".\"}),null==a&&(a=[1,1,1]),g(Io(o,a),function(){return\"Error in maxPool3dBackprop: Either strides or dilations must be 1. Got strides \"+o+\" and dilations '\"+a+\"'\"}),null!=u&&g(E(i),function(){return\"Error in maxPool3dBackprop: pad must be an integer when using, dimRoundingMode \"+u+\" but got pad \"+i+\".\"});var v=mo(f.shape,r,o,a,i,u),m=Nt.runKernelFunc(function(t){return t.maxPool3dBackprop(h,f,p,v)},{dy5D:h,input5D:f});return d?m.as4D(m.shape[1],m.shape[2],m.shape[3],m.shape[4]):m}(t,u,s,e,n,i,r,o)}}});return c?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}}),Jc=wn({avgPool3d_:function(t,e,n,r,o,a,i){void 0===a&&(a=\"NDHWC\");var u=cn(t,\"x\",\"avgPool3d\",\"float32\"),s=u,c=!1;4===u.rank&&(c=!0,s=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3])),null==i&&(i=[1,1,1]),g(5===s.rank,function(){return\"Error in avgPool3d: x must be rank 5 but got rank \"+s.rank+\".\"}),g(\"NDHWC\"===a,function(){return\"Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of \"+a}),g(Io(n,i),function(){return\"Error in avgPool3d: Either strides or dilations must be 1. Got strides \"+n+\" and dilations '\"+i+\"'\"}),null!=o&&g(E(r),function(){return\"Error in avgPool3d: pad must be an integer when using, dimRoundingMode \"+o+\" but got pad \"+r+\".\"});var l=mo(s.shape,e,n,i,r,o,a),h=Nt.runKernelFunc(function(t){return t.avgPool3d(s,l)},{x:s},function(t){return{x:function(){return function(t,e,n,r,o,a,i){var u=cn(t,\"dy\",\"avgPool3dBackprop\"),s=cn(e,\"input\",\"avgPool3dBackprop\"),c=u,l=s,h=!1;4===s.rank&&(h=!0,c=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]),l=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3])),g(5===c.rank,function(){return\"Error in avgPool3dBackprop: dy must be rank 5 but got rank \"+c.rank+\".\"}),g(5===l.rank,function(){return\"Error in avgPool3dBackprop: input must be rank 5 but got rank \"+l.rank+\".\"}),null==o&&(o=[1,1,1]),g(Io(r,o),function(){return\"Error in avgPool3dBackprop: Either strides or dilations must be 1. Got strides \"+r+\" and dilations '\"+o+\"'\"}),null!=i&&g(E(a),function(){return\"Error in maxPool3dBackprop: pad must be an integer when using, dimRoundingMode \"+i+\" but got pad \"+a+\".\"});var f=mo(l.shape,n,r,o,a,i),p=Nt.runKernelFunc(function(t){return t.avgPool3dBackprop(c,l,f)},{dy5D:c,input5D:l});return h?p.as4D(p.shape[1],p.shape[2],p.shape[3],p.shape[4]):p}(t,s,e,n,i,r,o)}}});return h=h.cast(s.dtype),c?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}});var Zc=wn({slice_:function(t,e,n){var r,o,a=cn(t,\"x\",\"slice\");if(0===a.rank)throw new Error(\"Slicing scalar is not possible\");(r=\"number\"==typeof e?[e].concat(new Array(a.rank-1).fill(0)):e.length<a.rank?e.concat(new Array(a.rank-e.length).fill(0)):e.slice()).forEach(function(t){g(-1!==t,function(){return\"slice() does not support negative begin indexing.\"})}),o=(o=null==n?new Array(a.rank).fill(-1):\"number\"==typeof n?[n].concat(new Array(a.rank-1).fill(-1)):n.length<a.rank?n.concat(new 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c=cn(t,\"x\",\"stridedSlice\"),l=Kr(u),h=c.shape.slice();l.forEach(function(t){e[t]=0,n[t]=1,h.splice(t,0,1)}),c=c.reshape(h);for(var f=0;f<c.rank;f++)e[f]=Xr(o,e,r,c.shape,f),n[f]=$r(a,n,r,c.shape,f),r[f]=r[f]||1;var p=Kr(s);p.forEach(function(t){n[t]=e[t]+1,r[t]=1});var d=jr(e,n,r),v=d.filter(function(t,e){return-1===p.indexOf(e)});return r.every(function(t){return 1===t})?Zc(c,e,d).reshape(v):Nt.runKernelFunc(function(t){return t.stridedSlice(c,e,n,r)},{$x:c}).reshape(v)}});var Dl=wn({topk_:function(t,e,n){void 0===e&&(e=1),void 0===n&&(n=!0);var r=cn(t,\"x\",\"topk\");if(0===r.rank)throw new Error(\"topk() expects the input to be of rank 1 or higher\");var o=r.shape[r.shape.length-1];if(e>o)throw new Error(\"'k' passed to topk() must be <= the last dimension (\"+o+\") but got \"+e);var a=Nt.runKernelFunc(function(t){return t.topk(r,e,n)},{$x:r});return{values:a[0],indices:a[1]}}});var Tl=wn({scatterND_:function(t,e,n){var 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resizeNearestNeighbor: x must be rank 3 or 4, but got rank \"+r.rank+\".\"}),g(2===e.length,function(){return\"Error in resizeNearestNeighbor: new shape must 2D, but got shape \"+e+\".\"}),g(\"float32\"===r.dtype||\"int32\"===r.dtype,function(){return\"`images` must have `int32` or `float32` as dtype\"});var o=r,a=!1;3===r.rank&&(a=!0,o=r.as4D(1,r.shape[0],r.shape[1],r.shape[2]));var i=e[0],u=e[1],s=Nt.runKernelFunc(function(t,e){return e([o]),t.resizeNearestNeighbor(o,i,u,n)},{batchImages:o},function(t,e){return{batchImages:function(){return Nt.runKernelFunc(function(r){return r.resizeNearestNeighborBackprop(t,e[0],n)},{})}}});return a?s.as3D(s.shape[1],s.shape[2],s.shape[3]):s}}),fh=wn({nonMaxSuppression_:function(t,e,n,r,o){void 0===r&&(r=.5),void 0===o&&(o=Number.NEGATIVE_INFINITY);var a=cn(t,\"boxes\",\"nonMaxSuppression\"),i=cn(e,\"scores\",\"nonMaxSuppression\"),u=ch(a,i,n,r,o);n=u.maxOutputSize,r=u.iouThreshold,o=u.scoreThreshold;var s={maxOutputSize:n,iouThreshold:r,scoreThreshold:o};return Nt.runKernelFunc(function(t){return t.nonMaxSuppression(a,i,n,r,o)},{boxes:a,scores:i},null,\"NonMaxSuppressionV3\",s)}}),ph=function(t,e,o,a,i){return void 0===a&&(a=.5),void 0===i&&(i=Number.NEGATIVE_INFINITY),n(this,void 0,void 0,function(){var n,u,s,c,l,h,f;return r(this,function(r){switch(r.label){case 0:return n=cn(t,\"boxes\",\"nonMaxSuppressionAsync\"),u=cn(e,\"scores\",\"nonMaxSuppressionAsync\"),s=ch(n,u,o,a,i),o=s.maxOutputSize,a=s.iouThreshold,i=s.scoreThreshold,[4,Promise.all([n.data(),u.data()])];case 1:return c=r.sent(),l=c[0],h=c[1],f=Mo(l,h,o,a,i),n!==t&&n.dispose(),u!==e&&u.dispose(),[2,f]}})})},dh=wn({cropAndResize_:function(t,e,n,r,o,a){var i=cn(t,\"image\",\"cropAndResize\"),u=cn(e,\"boxes\",\"cropAndResize\",\"float32\"),s=cn(n,\"boxInd\",\"cropAndResize\",\"int32\");o=o||\"bilinear\",a=a||0;var c=u.shape[0];return g(4===i.rank,function(){return\"Error in cropAndResize: image must be rank 4,but got rank 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t.cropAndResize(i,u,s,r,o,a)},{images:i,boxes:u,boxInd:s},null,\"CropAndResize\",{method:o,extrapolationValue:a,cropSize:r})}}),vh=Object.freeze({resizeBilinear:lh,resizeNearestNeighbor:hh,nonMaxSuppression:fh,nonMaxSuppressionAsync:ph,cropAndResize:dh}),mh=function(t,e){return!(t>0)||\"linear\"===e},gh=function(t,e,n){if(null==n||\"linear\"===n)return t;if(\"relu\"===n)return t.mul(e.step());throw new Error(\"Gradient for activation \"+n+\" has not been implemented yet.\")},yh=function(t,e){var n=e,r=fo(t.shape,e.shape);return r.length>0&&(n=n.sum(r)),n.reshape(t.shape)},xh=function(t,e,n){if(\"linear\"===e)return t;if(\"relu\"===e)return xl(t);if(\"elu\"===e)return ml(t);if(\"relu6\"===e)return bl(t);if(\"prelu\"===e)return yl(t,n);throw new Error(\"Unknown fused activation \"+e+\".\")};var bh=wn({fusedMatMul_:function(t){var e,n=t.a,r=t.b,o=t.transposeA,a=void 0!==o&&o,i=t.transposeB,u=void 0!==i&&i,s=t.bias,c=t.activation,l=void 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Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. 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Rn(t)});return Cn(this.concat(r,e),this.concat(o,e))}var a=t.map(function(t){var n=w(t.shape.slice(e));return t.as2D(-1,n)}),i=bn(a.map(function(t){return t.shape}),1),u=ir(i,t[0].dtype).values;if(1===a[0].shape[0]){var s=0;a.forEach(function(t){u.set(n.readSync(t.dataId),s),s+=t.size})}else{var c=0;a.forEach(function(t){for(var e=n.readSync(t.dataId),r=0,o=0;o<t.shape[0];++o)for(var a=o*i[1]+c,s=0;s<t.shape[1];++s)u[a+s]=e[r++];c+=t.shape[1]})}var l=bn(t.map(function(t){return t.shape}),e);return In(u,l,t[0].dtype)},o.prototype.neg=function(t){return Ih(t,\"neg\"),this.multiply(Sn(-1),t)},o.prototype.add=function(t,e){return\"complex64\"===t.dtype||\"complex64\"===e.dtype?this.broadcastedBinaryComplexOp(t.cast(\"complex64\"),e.cast(\"complex64\"),function(t,e,n,r){return{real:t+n,imag:e+r}}):this.broadcastedBinaryOp(t,e,Ct(t.dtype,e.dtype),function(t,e){return t+e})},o.prototype.addN=function(t){var e=this;Ih(t,\"addN\");for(var n=t.map(function(t){return e.readSync(t.dataId)}),r=ir(t[0].shape,t[0].dtype),o=r.values,a=0;a<t.length;a++)for(var i=n[a],u=0;u<o.length;u++)o[u]+=i[u];return r.toTensor()},o.prototype.subtract=function(t,e){return\"complex64\"===t.dtype||\"complex64\"===e.dtype?this.broadcastedBinaryComplexOp(t.cast(\"complex64\"),e.cast(\"complex64\"),function(t,e,n,r){return{real:t-n,imag:e-r}}):this.broadcastedBinaryOp(t,e,Ct(t.dtype,e.dtype),function(t,e){return t-e})},o.prototype.pow=function(t,e){return Ih([t,e],\"pow\"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.pow(t,e)})},o.prototype.batchMatMul=function(t,e,n,r){Ih([t,e],\"matMul\");for(var o=n?t.shape[1]:t.shape[2],a=n?t.shape[2]:t.shape[1],i=r?e.shape[1]:e.shape[2],u=t.shape[0],s=this.readSync(t.dataId),c=this.readSync(e.dataId),l=n?[t.strides[0],1,t.strides[1]]:[t.strides[0],t.strides[1],1],h=l[0],f=l[1],p=l[2],d=r?[1,e.strides[1],e.strides[0]]:[e.strides[1],1,e.strides[0]],v=d[0],m=d[1],g=d[2],y=a*i,x=ir([u,a,i],t.dtype),b=x.values,w=this.blockSize,C=0;C<u;C++)for(var E=0;E<a;E+=w)for(var R=0;R<i;R+=w)for(var I=0;I<o;I+=w)for(var k=Math.min(E+w,a),S=Math.min(R+w,i),A=Math.min(I+w,o),D=E;D<k;D++)for(var T=R;T<S;T++){for(var N=0,F=I;F<A;F++)N+=s[C*h+D*f+F*p]*c[F*v+T*m+C*g];b[C*y+(D*i+T)]+=N}return x.toTensor()},o.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,a=t.bias,i=t.activation,u=t.preluActivationWeights,s=this.batchMatMul(e,n,r,o);return a&&(s=this.add(s,a)),i&&(s=kh(this,s,i,u)),s},o.prototype.multiply=function(t,e){return\"complex64\"===t.dtype||\"complex64\"===e.dtype?this.broadcastedBinaryComplexOp(t.cast(\"complex64\"),e.cast(\"complex64\"),function(t,e,n,r){return{real:t*n-e*r,imag:t*r+e*n}}):this.broadcastedBinaryOp(t,e,Ct(t.dtype,e.dtype),function(t,e){return t*e})},o.prototype.realDivide=function(t,e){Ih([t,e],\"realDivide\");return this.broadcastedBinaryOp(t,e,\"float32\",function(t,e){return t/e})},o.prototype.floorDiv=function(t,e){Ih([t,e],\"floorDiv\");return this.broadcastedBinaryOp(t,e,\"int32\",function(t,e){return Math.floor(t/e)})},o.prototype.sum=function(t,e){Ih(t,\"sum\"),vn(\"sum\",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,Ct(t.dtype,\"int32\")),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=0,f=0;f<i;++f)h+=s[l+f];u[c]=h}return a},o.prototype.prod=function(t,e){Ih(t,\"sum\");for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,Ct(t.dtype,\"int32\")),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=1,f=0;f<i;++f)h*=s[l+f];u[c]=h}return a},o.prototype.unsortedSegmentSum=function(t,e,n){Ih(t,\"unsortedSegmentSum\");for(var r=[],o=t.rank-e.rank,a=0;a<o;++a)e=e.expandDims(a+1);for(a=0;a<n;++a){var i=Sn(a,\"int32\"),u=uc(i,e).asType(\"float32\").mul(t).sum(0);r.push(u)}return Tr(r)},o.prototype.argMin=function(t,e){Ih(t,\"argMin\");var n=[e];vn(\"argMin\",n,t.rank);for(var r=pn(t.shape,n),o=r[0],a=r[1],i=Bn(o,\"int32\"),u=w(a),s=this.readSync(i.dataId),c=this.readSync(t.dataId),l=0;l<s.length;++l){for(var h=l*u,f=c[h],p=0,d=0;d<u;++d){var v=c[h+d];v<f&&(f=v,p=d)}s[l]=p}return i},o.prototype.argMax=function(t,e){Ih(t,\"argMax\");var n=[e];vn(\"argMax\",n,t.rank);for(var r=pn(t.shape,n),o=r[0],a=r[1],i=Bn(o,\"int32\"),u=w(a),s=this.readSync(i.dataId),c=this.readSync(t.dataId),l=0;l<s.length;++l){for(var h=l*u,f=c[h],p=0,d=0;d<u;++d){var v=c[h+d];v>f&&(f=v,p=d)}s[l]=p}return i},o.prototype.cumsum=function(t,e,n,r){if(Ih(t,\"cumsum\"),e!==t.rank-1)throw new Error(\"backend.cumsum in CPU expects an inner-most axis=\"+(t.rank-1)+\" but got axis=\"+e);for(var o=Ct(t.dtype,\"int32\"),a=Bn(t.shape,o),i=this.readSync(a.dataId),u=this.readSync(t.dataId),s=t.shape[t.rank-1],c=r?function(t,e){return t+s-e-1}:function(t,e){return t+e},l=0;l<u.length;l+=s)for(var h=0;h<s;h++){var f=c(l,h);if(0===h)i[f]=n?0:u[f];else{var p=c(l,h-1);i[f]=n?u[p]+i[p]:u[f]+i[p]}}return a},o.prototype.equal=function(t,e){return Ih([t,e],\"equal\"),this.broadcastedBinaryOp(t,e,\"bool\",function(t,e){return t===e?1:0})},o.prototype.notEqual=function(t,e){return Ih([t,e],\"notEqual\"),this.broadcastedBinaryOp(t,e,\"bool\",function(t,e){return t!==e?1:0})},o.prototype.less=function(t,e){return Ih([t,e],\"less\"),this.broadcastedBinaryOp(t,e,\"bool\",function(t,e){return t<e?1:0})},o.prototype.lessEqual=function(t,e){return Ih([t,e],\"lessEqual\"),this.broadcastedBinaryOp(t,e,\"bool\",function(t,e){return t<=e?1:0})},o.prototype.greater=function(t,e){return Ih([t,e],\"greater\"),this.broadcastedBinaryOp(t,e,\"bool\",function(t,e){return t>e?1:0})},o.prototype.greaterEqual=function(t,e){return Ih([t,e],\"greaterEqual\"),this.broadcastedBinaryOp(t,e,\"bool\",function(t,e){return t>=e?1:0})},o.prototype.logicalNot=function(t){Ih(t,\"logicalNot\");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)n[r]=e[r]?0:1;return this.makeOutput(n,t.shape,\"bool\")},o.prototype.logicalAnd=function(t,e){return Ih([t,e],\"logicalAnd\"),this.broadcastedBinaryOp(t,e,\"bool\",function(t,e){return t&&e})},o.prototype.logicalOr=function(t,e){return Ih([t,e],\"logicalOr\"),this.broadcastedBinaryOp(t,e,\"bool\",function(t,e){return t||e})},o.prototype.select=function(t,e,n){Ih([t,e,n],\"select\");for(var r=this.readSync(t.dataId),o=this.readSync(e.dataId),a=this.readSync(n.dataId),i=Bn(e.shape,Ct(e.dtype,n.dtype)),u=this.readSync(i.dataId),s=0,c=0===t.rank||t.rank>1||1===e.rank?1:w(e.shape.slice(1)),l=0;l<r.length;l++)for(var h=0;h<c;h++)1===r[l]?u[s++]=o[l]:u[s++]=a[l];return i},o.prototype.where=function(t){Ih([t],\"where\");var e=this.readSync(t.dataId);return Uo(t.shape,e)},o.prototype.topk=function(t,e,n){return Ih(t,\"topk\"),Wo(this.readSync(t.dataId),t.shape,t.dtype,e)},o.prototype.min=function(t,e){Ih(t,\"min\"),vn(\"min\",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,t.dtype),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=s[l],f=0;f<i;++f){var p=s[l+f];p<h&&(h=p)}u[c]=h}return a},o.prototype.minimum=function(t,e){return Ih([t,e],\"minimum\"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.min(t,e)})},o.prototype.mod=function(t,e){return Ih([t,e],\"mod\"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var n=t%e;return t<0&&e<0||t>=0&&e>=0?n:(n+e)%e})},o.prototype.max=function(t,e){Ih(t,\"max\"),vn(\"max\",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,t.dtype),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=s[l],f=0;f<i;++f){var p=s[l+f];p>h&&(h=p)}u[c]=h}return a},o.prototype.maximum=function(t,e){return Ih([t,e],\"maximum\"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.max(t,e)})},o.prototype.all=function(t,e){Ih(t,\"all\"),vn(\"all\",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,t.dtype),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=s[l],f=0;f<i;++f){var p=s[l+f];h=h&&p}u[c]=h}return a},o.prototype.any=function(t,e){Ih(t,\"any\"),vn(\"any\",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],a=Bn(r,t.dtype),i=w(o),u=this.readSync(a.dataId),s=this.readSync(t.dataId),c=0;c<u.length;++c){for(var l=c*i,h=s[l],f=0;f<i;++f){var p=s[l+f];h=h||p}u[c]=h}return a},o.prototype.squaredDifference=function(t,e){return Ih([t,e],\"squaredDifference\"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var n=t-e;return n*n})},o.prototype.ceil=function(t){Ih(t,\"ceil\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.ceil(e[r]);return this.makeOutput(n,t.shape,\"float32\")},o.prototype.floor=function(t){Ih(t,\"floor\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.floor(e[r]);return this.makeOutput(n,t.shape,\"float32\")},o.prototype.sign=function(t){Ih(t,\"x\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)e[r]<0?n[r]=-1:e[r]>0?n[r]=1:n[r]=0;return this.makeOutput(n,t.shape,\"float32\")},o.prototype.isNaN=function(t){Ih(t,\"x\");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isNaN(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,\"bool\")},o.prototype.isInf=function(t){Ih(t,\"x\");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Math.abs(e[r])===1/0&&(n[r]=1);return this.makeOutput(n,t.shape,\"bool\")},o.prototype.isFinite=function(t){Ih(t,\"x\");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isFinite(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,\"bool\")},o.prototype.round=function(t){Ih(t,\"round\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=Math.floor(e[r]);e[r]-o<.5?n[r]=Math.floor(e[r]):e[r]-o>.5?n[r]=Math.ceil(e[r]):n[r]=o%2==0?o:o+1}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.exp=function(t){Ih(t,\"exp\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.exp(e[r]);return this.makeOutput(n,t.shape,\"float32\")},o.prototype.expm1=function(t){Ih(t,\"expm1\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.expm1(e[r]);return this.makeOutput(n,t.shape,\"float32\")},o.prototype.log=function(t){Ih(t,\"log\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log(o)}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.log1p=function(t){Ih(t,\"log1p\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log1p(o)}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.sqrt=function(t){Ih(t,\"sqrt\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.sqrt(o)}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.rsqrt=function(t){Ih(t,\"rsqrt\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=1/Math.sqrt(o)}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.reciprocal=function(t){Ih(t,\"reciprocal\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=1/e[r];return this.makeOutput(n,t.shape,\"float32\")},o.prototype.linear=function(t){return t},o.prototype.relu=function(t){Ih(t,\"relu\");for(var e=Bn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.max(0,r[o]);return e},o.prototype.relu6=function(t){Ih(t,\"relu\");for(var e=Bn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.min(Math.max(0,r[o]),6);return e},o.prototype.prelu=function(t,e){return Ih([t,e],\"prelu\"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return t<0?e*t:t})},o.prototype.elu=function(t){Ih(t,\"elu\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=n[r];e[r]=o>=0?o:Math.exp(o)-1}return this.makeOutput(e,t.shape,\"float32\")},o.prototype.eluDer=function(t,e){Ih([t,e],\"eluDer\");for(var n=new Float32Array(e.size),r=this.readSync(e.dataId),o=this.readSync(t.dataId),a=0;a<r.length;++a){var i=r[a];n[a]=i>=1?o[a]:o[a]*(i+1)}return this.makeOutput(n,e.shape,\"float32\")},o.prototype.selu=function(t){Ih(t,\"selu\");for(var e=ou,n=au,r=new Float32Array(t.size),o=this.readSync(t.dataId),a=0;a<o.length;++a){var i=o[a];r[a]=i>=0?n*i:e*(Math.exp(i)-1)}return this.makeOutput(r,t.shape,\"float32\")},o.prototype.clip=function(t,e,n){Ih(t,\"clip\");for(var r=new Float32Array(t.size),o=this.readSync(t.dataId),a=0;a<o.length;++a){var i=o[a];r[a]=i>n?n:i<e?e:i}return this.makeOutput(r,t.shape,\"float32\")},o.prototype.abs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.abs(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.complexAbs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<t.size;++r){var o=n[2*r],a=n[2*r+1];e[r]=Math.hypot(o,a)}return this.makeOutput(e,t.shape,\"float32\")},o.prototype.int=function(t){Ih(t,\"int\");for(var e=new Int32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=n[r];return this.makeOutput(e,t.shape,\"int32\")},o.prototype.sigmoid=function(t){Ih(t,\"sigmoid\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=1/(1+Math.exp(-n[r]));return this.makeOutput(e,t.shape,\"float32\")},o.prototype.softplus=function(t){Ih(t,\"softplus\");for(var e=Math.log(1.1920928955078125e-7)+2,n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var a=r[o]>-e,i=r[o]<e,u=Math.exp(r[o]),s=void 0;s=i?u:a?r[o]:Math.log(1+u),n[o]=s}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.sin=function(t){Ih(t,\"sin\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sin(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.cos=function(t){Ih(t,\"cos\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cos(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.tan=function(t){Ih(t,\"tan\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.tan(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.asin=function(t){Ih(t,\"asin\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asin(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.acos=function(t){Ih(t,\"acos\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acos(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.atan=function(t){Ih(t,\"atan\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atan(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.atan2=function(t,e){return Ih([t,e],\"atan2\"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.atan2(t,e)})},o.prototype.sinh=function(t){Ih(t,\"sinh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sinh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.cosh=function(t){Ih(t,\"cosh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cosh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.tanh=function(t){Ih(t,\"tanh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=R(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.asinh=function(t){Ih(t,\"asinh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asinh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.acosh=function(t){Ih(t,\"acosh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acosh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.atanh=function(t){Ih(t,\"atanh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atanh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.erf=function(t){Ih(t,\"erf\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=Math.sign(n[r]),a=Math.abs(n[r]),i=1/(1+.3275911*a);e[r]=o*(1-((((1.061405429*i-1.453152027)*i+1.421413741)*i-.284496736)*i+.254829592)*i*Math.exp(-a*a))}return this.makeOutput(e,t.shape,\"float32\")},o.prototype.step=function(t,e){void 0===e&&(e=0),Ih(t,\"step\");for(var n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var a=r[o];isNaN(a)?n[o]=NaN:n[o]=a>0?1:e}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,i=t.preluActivationWeights,u=this.conv2d(e,n,r);return o&&(u=this.add(u,o)),a&&(u=kh(this,u,a,i)),u},o.prototype.conv2d=function(t,e,n){Ih([t,e],\"conv2d\");for(var r=n.filterHeight,o=n.filterWidth,a=n.dilationHeight,i=n.dilationWidth,u=n.padInfo.left,s=n.padInfo.top,c=\"channelsLast\"===n.dataFormat,l=ir(n.outShape,t.dtype),h=t.strides[0],f=c?t.strides[1]:t.strides[2],p=c?t.strides[2]:1,d=c?1:t.strides[1],v=l.strides[0],m=c?l.strides[1]:l.strides[2],g=c?l.strides[2]:1,y=c?1:l.strides[1],x=this.readSync(t.dataId),b=this.readSync(e.dataId),w=l.values,C=0;C<n.batchSize;++C)for(var E=C*h,R=C*v,I=0;I<n.outHeight;++I)for(var k=R+I*m,S=I*n.strideHeight-s,A=0;A<r;A++){var D=S+A*a;if(!(D<0||D>=n.inHeight))for(var T=A*e.strides[0],N=E+D*f,F=0;F<n.outWidth;++F)for(var _=k+F*g,O=F*n.strideWidth-u,M=0;M<o;M++){var B=O+M*i;if(!(B<0||B>=n.inWidth))for(var P=N+B*p,L=T+M*e.strides[1],W=0;W<n.inChannels;++W){for(var U=x[P+W*d],V=0;V<n.outChannels;++V)w[_+V*y]+=U*b[L+V];L+=n.outChannels}}}return l.toTensor()},o.prototype.conv3d=function(t,e,n){for(var r=n.filterDepth,o=n.filterHeight,a=n.filterWidth,i=n.dilationDepth,u=n.dilationHeight,s=n.dilationWidth,c=n.padInfo.front,l=n.padInfo.left,h=n.padInfo.top,f=ir(n.outShape,t.dtype),p=this.readSync(t.dataId),d=this.readSync(e.dataId),v=f.values,m=0;m<n.batchSize;++m)for(var g=m*t.strides[0],y=m*f.strides[0],x=0;x<n.outDepth;++x)for(var b=y+x*f.strides[1],w=x*n.strideDepth-c,C=0;C<r;C++){var E=w+C*i;if(!(E<0||E>=n.inDepth))for(var R=C*e.strides[0],I=g+E*t.strides[1],k=0;k<n.outHeight;++k)for(var S=b+k*f.strides[2],A=k*n.strideHeight-h,D=0;D<o;D++){var T=A+D*u;if(!(T<0||T>=n.inHeight))for(var N=R+D*e.strides[1],F=I+T*t.strides[2],_=0;_<n.outWidth;++_)for(var O=S+_*n.outChannels,M=_*n.strideWidth-l,B=0;B<a;B++){var P=M+B*s;if(!(P<0||P>=n.inWidth))for(var L=N+B*e.strides[2],W=F+P*n.inChannels,U=L,V=0;V<n.inChannels;++V){for(var z=p[W+V],G=0;G<n.outChannels;++G)v[O+G]+=z*d[U+G];U+=n.outChannels}}}}return f.toTensor()},o.prototype.conv2dDerInput=function(t,e,n){Ih([t,e],\"conv2dDerInput\");for(var r=ir(n.inShape,\"float32\"),o=r.values,a=this.readSync(t.dataId),i=this.readSync(e.dataId),u=e.strides,s=u[0],c=u[1],l=u[2],h=n.batchSize,f=n.filterHeight,p=n.filterWidth,d=n.inChannels,v=n.inHeight,m=n.inWidth,g=n.outChannels,y=n.outHeight,x=n.outWidth,b=n.strideHeight,w=n.strideWidth,C=n.dataFormat,E=f-1-n.padInfo.top,R=p-1-n.padInfo.left,I=\"channelsLast\"===C,k=r.strides[0],S=I?r.strides[1]:r.strides[2],A=I?r.strides[2]:1,D=I?1:r.strides[1],T=t.strides[0],N=I?t.strides[1]:t.strides[2],F=I?t.strides[2]:1,_=I?1:t.strides[1],O=0;O<h;++O)for(var M=0;M<d;++M)for(var B=0;B<v;++B)for(var P=B-E,L=Math.max(0,Math.ceil(P/b)),W=Math.min(y,(f+P)/b),U=0;U<m;++U){for(var V=U-R,z=Math.max(0,Math.ceil(V/w)),G=Math.min(x,(p+V)/w),H=0,q=L;q<W;++q)for(var K=q*b-P,j=z;j<G;++j)for(var X=T*O+N*q+F*j,$=s*(f-1-K)+c*(p-1-(j*w-V))+l*M,Y=0;Y<g;++Y){H+=a[X+_*Y]*i[$+Y]}o[k*O+S*B+A*U+D*M]=H}return r.toTensor()},o.prototype.conv3dDerInput=function(t,e,n){for(var r=ir(n.inShape,\"float32\"),o=r.values,a=r.strides,i=a[0],u=a[1],s=a[2],c=a[3],l=this.readSync(t.dataId),h=t.strides,f=h[0],p=h[1],d=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=n.batchSize,E=n.filterDepth,R=n.filterHeight,I=n.filterWidth,k=n.inChannels,S=n.inDepth,A=n.inHeight,D=n.inWidth,T=n.outChannels,N=n.outDepth,F=n.outHeight,_=n.outWidth,O=n.strideDepth,M=n.strideHeight,B=n.strideWidth,P=E-1-n.padInfo.front,L=R-1-n.padInfo.top,W=I-1-n.padInfo.left,U=0;U<C;++U)for(var V=0;V<k;++V)for(var z=0;z<S;++z)for(var G=z-P,H=Math.max(0,Math.ceil(G/O)),q=Math.min(N,(E+G)/O),K=0;K<A;++K)for(var j=K-L,X=Math.max(0,Math.ceil(j/M)),$=Math.min(F,(R+j)/M),Y=0;Y<D;++Y){for(var Q=Y-W,J=Math.max(0,Math.ceil(Q/B)),Z=Math.min(_,(I+Q)/B),tt=0,et=H;et<q;++et)for(var nt=et*O-G,rt=X;rt<$;++rt)for(var ot=rt*M-j,at=J;at<Z;++at)for(var it=f*U+p*et+d*rt+v*at,ut=y*(E-1-nt)+x*(R-1-ot)+b*(I-1-(at*B-Q))+w*V,st=0;st<T;++st){tt+=l[it+st]*m[ut+st]}o[i*U+u*z+s*K+c*Y+V]=tt}return r.toTensor()},o.prototype.conv2dDerFilter=function(t,e,n){Ih([t,e],\"conv2dDerFilter\");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,u=\"channelsLast\"===n.dataFormat,s=ir(n.filterShape,\"float32\"),c=n.padInfo.left,l=n.padInfo.top,h=this.bufferSync(t),f=this.bufferSync(e),p=0;p<a;++p)for(var d=Math.max(0,Math.ceil((l-p)/r)),v=Math.min(n.outHeight,(n.inHeight+l-p)/r),m=0;m<i;++m)for(var g=Math.max(0,Math.ceil((c-m)/o)),y=Math.min(n.outWidth,(n.inWidth+c-m)/o),x=0;x<n.inChannels;++x)for(var b=0;b<n.outChannels;++b){for(var w=0,C=0;C<n.batchSize;++C)for(var E=d;E<v;++E)for(var R=p+E*r-l,I=g;I<y;++I){var k=m+I*o-c;w+=u?h.get(C,R,k,x)*f.get(C,E,I,b):h.get(C,x,R,k)*f.get(C,b,E,I)}s.set(w,p,m,x,b)}return s.toTensor()},o.prototype.conv3dDerFilter=function(t,e,n){for(var r=n.strideDepth,o=n.strideHeight,a=n.strideWidth,i=n.filterDepth,u=n.filterHeight,s=n.filterWidth,c=ir(n.filterShape,\"float32\"),l=c.values,h=c.strides,f=h[0],p=h[1],d=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=this.readSync(t.dataId),E=t.strides,R=E[0],I=E[1],k=E[2],S=E[3],A=n.padInfo.front,D=n.padInfo.left,T=n.padInfo.top,N=0;N<i;++N)for(var F=Math.max(0,Math.ceil((A-N)/r)),_=Math.min(n.outDepth,(n.inDepth+A-N)/r),O=N*f,M=0;M<u;++M)for(var B=Math.max(0,Math.ceil((T-M)/o)),P=Math.min(n.outHeight,(n.inHeight+T-M)/o),L=M*p+O,W=0;W<s;++W)for(var U=Math.max(0,Math.ceil((D-W)/a)),V=Math.min(n.outWidth,(n.inWidth+D-W)/a),z=W*d+L,G=0;G<n.inChannels;++G)for(var H=G*v+z,q=0;q<n.outChannels;++q){for(var K=0,j=0;j<n.batchSize;++j)for(var X=j*R,$=j*y,Y=F;Y<_;++Y)for(var Q=(N+Y*r-A)*I+X,J=Y*x+$,Z=B;Z<P;++Z)for(var tt=(M+Z*o-T)*k+Q,et=Z*b+J,nt=U;nt<V;++nt){var rt=nt*w+et;K+=C[(W+nt*a-D)*S+tt+G]*m[rt+q]}l[H+q]=K}return c.toTensor()},o.prototype.fusedDepthwiseConv2D=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,i=t.preluActivationWeights,u=this.depthwiseConv2D(e,n,r);return o&&(u=this.add(u,o)),a&&(u=kh(this,u,a,i)),u},o.prototype.depthwiseConv2D=function(t,e,n){Ih([t,e],\"depthwiseConv2D\");for(var r=n.filterHeight,o=n.filterWidth,a=n.dilationHeight,i=n.dilationWidth,u=n.padInfo.left,s=n.padInfo.top,c=n.outChannels/n.inChannels,l=ir(n.outShape,t.dtype),h=this.readSync(t.dataId),f=this.readSync(e.dataId),p=l.values,d=0;d<n.batchSize;++d)for(var v=d*t.strides[0],m=d*l.strides[0],g=0;g<n.outHeight;++g)for(var y=m+g*l.strides[1],x=g*n.strideHeight-u,b=0;b<r;++b){var w=x+b*a;if(!(w<0||w>=n.inHeight))for(var C=b*e.strides[0],E=v+w*t.strides[1],R=0;R<n.outWidth;++R)for(var I=y+R*l.strides[2],k=R*n.strideWidth-s,S=0;S<o;++S){var A=k+S*i;if(!(A<0||A>=n.inWidth))for(var D=C+S*e.strides[1],T=E+A*n.inChannels,N=I,F=D,_=0;_<n.inChannels;++_){for(var O=h[T+_],M=0;M<c;++M)p[N+M]+=O*f[F+M];N+=c,F+=c}}}return l.toTensor()},o.prototype.depthwiseConv2DDerInput=function(t,e,n){Ih([t,e],\"depthwiseConv2DDerInput\");for(var r=ir(n.inShape,\"float32\"),o=r.values,a=r.strides,i=a[0],u=a[1],s=a[2],c=this.readSync(t.dataId),l=t.strides,h=l[0],f=l[1],p=l[2],d=this.readSync(e.dataId),v=e.strides,m=v[0],g=v[1],y=v[2],x=n.batchSize,b=n.filterHeight,w=n.filterWidth,C=n.inChannels,E=n.inHeight,R=n.inWidth,I=n.outChannels,k=n.outHeight,S=n.outWidth,A=n.strideHeight,D=n.strideWidth,T=b-1-n.padInfo.top,N=w-1-n.padInfo.left,F=I/C,_=0;_<x;++_)for(var O=0;O<C;++O)for(var M=0;M<E;++M)for(var B=M-T,P=Math.max(0,Math.ceil(B/A)),L=Math.min(k,(b+B)/A),W=0;W<R;++W){for(var U=W-N,V=Math.max(0,Math.ceil(U/D)),z=Math.min(S,(w+U)/D),G=0,H=P;H<L;++H)for(var q=H*A-B,K=V;K<z;++K)for(var j=h*_+f*H+p*K,X=m*(b-1-q)+g*(w-1-(K*D-U))+y*O,$=0;$<F;++$){G+=c[j+(O*F+$)]*d[X+$]}o[i*_+u*M+s*W+O]=G}return r.toTensor()},o.prototype.depthwiseConv2DDerFilter=function(t,e,n){Ih([t,e],\"depthwiseConv2DDerFilter\");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,u=ir(n.filterShape,\"float32\"),s=n.padInfo.left,c=n.padInfo.top,l=n.outChannels/n.inChannels,h=this.bufferSync(t),f=this.bufferSync(e),p=0;p<a;++p)for(var d=Math.max(0,Math.ceil((c-p)/r)),v=Math.min(n.outHeight,(n.inHeight+c-p)/r),m=0;m<i;++m)for(var g=Math.max(0,Math.ceil((s-m)/o)),y=Math.min(n.outWidth,(n.inWidth+s-m)/o),x=0;x<n.outChannels;++x){for(var b=Math.trunc(x/l),w=x%l,C=0,E=0;E<n.batchSize;++E)for(var R=d;R<v;++R)for(var I=p+R*r-c,k=g;k<y;++k){var S=m+k*o-s;C+=h.get(E,I,S,b)*f.get(E,R,k,x)}u.set(C,p,m,b,w)}return u.toTensor()},o.prototype.tile=function(t,e){return Ih(t,\"tile\"),Lo(this.bufferSync(t),e)},o.prototype.pad=function(t,e,n){Ih(t,\"pad\");var r=e.map(function(e,n){return e[0]+t.shape[n]+e[1]}),o=e.map(function(t){return t[0]}),a=this.bufferSync(t),i=ir(r,t.dtype);0!==n&&i.values.fill(n);for(var u=0;u<t.size;u++){var s=a.indexToLoc(u),c=s.map(function(t,e){return t+o[e]});i.set.apply(i,[a.get.apply(a,s)].concat(c))}return i.toTensor()},o.prototype.transpose=function(t,e){Ih(t,\"transpose\");for(var n=new Array(t.rank),r=0;r<n.length;r++)n[r]=t.shape[e[r]];var o=this.readSync(t.dataId),a=ir(n,t.dtype),i=this.bufferSync(t);for(r=0;r<t.size;++r){for(var u=i.indexToLoc(r),s=new Array(u.length),c=0;c<s.length;c++)s[c]=u[e[c]];var l=a.locToIndex(s);a.values[l]=o[r]}return a.toTensor()},o.prototype.gather=function(t,e,n){Ih([t,e],\"gather\");var r=t.shape.slice(),o=this.readSync(e.dataId);r[n]=o.length;for(var a=ir(r,t.dtype),i=this.bufferSync(t),u=0;u<a.size;++u){var s=a.indexToLoc(u),c=s.slice();c[n]=o[s[n]];var l=i.locToIndex(c);a.values[u]=i.values[l]}return a.toTensor()},o.prototype.batchToSpaceND=function(t,e,n){Ih([t],\"batchToSpaceND\");var r=e.reduce(function(t,e){return t*e}),o=Mr(t.shape,e,r),a=Br(o.length,e.length),i=Pr(t.shape,e,r),u=Lr(n,e.length),s=Wr(i,n,e.length);return t.reshape(o).transpose(a).reshape(i).slice(u,s)},o.prototype.spaceToBatchND=function(t,e,n){Ih([t],\"spaceToBatchND\");var r=e.reduce(function(t,e){return t*e}),o=[[0,0]];o.push.apply(o,n);for(var a=1+e.length;a<t.shape.length;++a)o.push([0,0]);var i=t.pad(o),u=Mr(i.shape,e,r,!1),s=Br(u.length,e.length,!1),c=Pr(i.shape,e,r,!1);return i.reshape(u).transpose(s).reshape(c)},o.prototype.pool=function(t,e,n){Ih(t,\"pool\");for(var r=e.strideHeight,o=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,u=e.effectiveFilterHeight,s=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h=\"max\"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=this.readSync(t.dataId),p=ir(e.outShape,t.dtype),d=p.values,v=e.outShape[1]*e.outShape[2]*e.outShape[3],m=e.outShape[2]*e.outShape[3],g=e.outShape[3],y=0;y<e.batchSize;++y)for(var x=y*v,b=y*t.strides[0],w=0;w<e.inChannels;++w)for(var C=0;C<e.outHeight;++C)for(var E=C*r-c,R=Math.max(0,E),I=Math.min(e.inHeight,u+E),k=x+C*m,S=0;S<e.outWidth;++S){for(var A=S*o-l,D=Math.max(0,A),T=Math.min(e.inWidth,s+A),N=h,F=0,_=0,O=R;O<I;O+=a){for(var M=b+O*t.strides[1],B=D;B<T;B+=i){var P=f[M+B*t.strides[2]+w];\"max\"===n&&P>N?N=P:\"avg\"===n&&(F+=P,_++)}if(isNaN(N))break}d[k+S*g+w]=\"avg\"===n?F/_:N}return p.toTensor()},o.prototype.maxPool=function(t,e){return this.pool(t,e,\"max\")},o.prototype.maxPoolPositions=function(t,e){for(var n=ir(e.outShape,\"int32\"),r=e.strideHeight,o=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,u=e.effectiveFilterHeight,s=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h=this.bufferSync(t),f=0;f<e.batchSize;++f)for(var p=0;p<e.inChannels;++p)for(var d=0;d<e.outHeight;++d){for(var v=d*r-c,m=v;m<0;)m+=a;for(var g=Math.min(e.inHeight,u+v),y=0;y<e.outWidth;++y){for(var x=y*o-l,b=x;b<0;)b+=i;for(var w=Math.min(e.inWidth,s+x),C=Number.NEGATIVE_INFINITY,E=-1,R=m;R<g;R+=a)for(var I=R-v,k=b;k<w;k+=i){var S=k-x,A=h.get(f,R,k,p);A>C&&(C=A,E=I*s+S)}n.set(E,f,d,y,p)}}return n.toTensor()},o.prototype.maxPoolBackprop=function(t,e,n,r){Ih([e,n],\"maxPoolBackprop\");for(var o=this.maxPoolPositions(e,r),a=r.strideHeight,i=r.strideWidth,u=r.dilationHeight,s=r.dilationWidth,c=r.effectiveFilterHeight,l=r.effectiveFilterWidth,h=l-1-r.padInfo.left,f=c-1-r.padInfo.top,p=ir(e.shape,\"float32\"),d=this.bufferSync(o),v=this.bufferSync(t),m=0;m<r.batchSize;++m)for(var g=0;g<r.inChannels;++g)for(var y=0;y<r.inHeight;++y)for(var x=0;x<r.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=u){var R=(b+E)/a;if(!(R<0||R>=r.outHeight||Math.floor(R)!==R))for(var I=0;I<l;I+=s){var k=(w+I)/i;if(!(k<0||k>=r.outWidth||Math.floor(k)!==k)){var S=c*l-1-d.get(m,R,k,g)===E*l+I?1:0;if(0!==S)C+=v.get(m,R,k,g)*S}}}p.set(C,m,y,x,g)}return p.toTensor()},o.prototype.avgPoolBackprop=function(t,e,n){Ih([t,e],\"avgPoolBackprop\");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,u=n.dilationHeight,s=n.dilationWidth,c=n.effectiveFilterHeight,l=n.effectiveFilterWidth,h=l-1-n.padInfo.left,f=c-1-n.padInfo.top,p=ir(e.shape,\"float32\"),d=1/(a*i),v=this.bufferSync(t),m=0;m<n.batchSize;++m)for(var g=0;g<n.inChannels;++g)for(var y=0;y<n.inHeight;++y)for(var x=0;x<n.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=u){var R=(b+E)/r;if(!(R<0||R>=n.outHeight||Math.floor(R)!==R))for(var I=0;I<l;I+=s){var k=(w+I)/o;if(!(k<0||k>=n.outWidth||Math.floor(k)!==k))C+=v.get(m,R,k,g)}}p.set(C*d,m,y,x,g)}return p.toTensor()},o.prototype.pool3d=function(t,e,n){Ih(t,\"pool3d\");for(var r=e.strideDepth,o=e.strideHeight,a=e.strideWidth,i=e.dilationDepth,u=e.dilationHeight,s=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,p=e.padInfo.top,d=e.padInfo.left,v=\"max\"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=this.readSync(t.dataId),g=ir(e.outShape,t.dtype),y=g.values,x=e.outShape[1]*e.outShape[2]*e.outShape[3]*e.outShape[4],b=e.outShape[2]*e.outShape[3]*e.outShape[4],w=e.outShape[3]*e.outShape[4],C=e.outShape[4],E=0;E<e.batchSize;++E)for(var R=E*x,I=E*t.strides[0],k=0;k<e.inChannels;++k)for(var S=0;S<e.outDepth;++S){for(var A=S*r-f,D=A;D<0;)D+=i;for(var T=Math.min(e.inDepth,c+A),N=R+S*b,F=0;F<e.outHeight;++F){for(var _=F*o-p,O=_;O<0;)O+=u;for(var M=Math.min(e.inHeight,l+_),B=N+F*w,P=0;P<e.outWidth;++P){for(var L=P*a-d,W=L;W<0;)W+=s;for(var U=Math.min(e.inWidth,h+L),V=B+P*C,z=v,G=0,H=0,q=D;q<T;q+=i){for(var K=I+q*t.strides[1],j=O;j<M;j+=u){for(var X=K+j*t.strides[2],$=W;$<U;$+=s){var Y=m[X+$*t.strides[3]+k];if(\"max\"===n&&Y>z?z=Y:\"avg\"===n&&(G+=Y,H++),isNaN(z))break}if(isNaN(z))break}if(isNaN(z))break}y[V+k]=\"avg\"===n?G/H:z}}}return g.toTensor()},o.prototype.avgPool3d=function(t,e){return Ih(t,\"avgPool3d\"),this.pool3d(t,e,\"avg\").toFloat()},o.prototype.avgPool3dBackprop=function(t,e,n){Ih([t,e],\"avgPool3dBackprop\");for(var r=n.strideDepth,o=n.strideHeight,a=n.strideWidth,i=n.filterDepth,u=n.filterHeight,s=n.filterWidth,c=n.dilationDepth,l=n.dilationHeight,h=n.dilationWidth,f=n.effectiveFilterDepth,p=n.effectiveFilterHeight,d=n.effectiveFilterWidth,v=f-1-n.padInfo.front,m=d-1-n.padInfo.left,g=p-1-n.padInfo.top,y=ir(e.shape,\"float32\"),x=1/(i*u*s),b=this.bufferSync(t),w=0;w<n.batchSize;++w)for(var C=0;C<n.inChannels;++C)for(var E=0;E<n.inDepth;++E)for(var R=0;R<n.inHeight;++R)for(var I=0;I<n.inWidth;++I){for(var k=E-v,S=R-g,A=I-m,D=0,T=0;T<f;T+=c){var N=(k+T)/r;if(!(N<0||N>=n.outDepth||Math.floor(N)!==N))for(var F=0;F<p;F+=l){var _=(S+F)/o;if(!(_<0||_>=n.outHeight||Math.floor(_)!==_))for(var O=0;O<d;O+=h){var M=(A+O)/a;if(!(M<0||M>=n.outWidth||Math.floor(M)!==M))D+=b.get(w,N,_,M,C)}}}y.set(D*x,w,E,R,I,C)}return y.toTensor()},o.prototype.maxPool3d=function(t,e){return Ih(t,\"maxPool3d\"),this.pool3d(t,e,\"max\").toFloat()},o.prototype.maxPool3dPositions=function(t,e){for(var n=ir(e.outShape,\"int32\"),r=e.strideDepth,o=e.strideHeight,a=e.strideWidth,i=e.dilationDepth,u=e.dilationHeight,s=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,p=e.padInfo.top,d=e.padInfo.left,v=this.bufferSync(t),m=0;m<e.batchSize;++m)for(var g=0;g<e.inChannels;++g)for(var y=0;y<e.outDepth;++y){for(var x=y*r-f,b=x;b<0;)b+=i;for(var w=Math.min(e.inDepth,c+x),C=0;C<e.outHeight;++C){for(var E=C*o-p,R=E;R<0;)R+=u;for(var I=Math.min(e.inHeight,l+E),k=0;k<e.outWidth;++k){for(var S=k*a-d,A=S;A<0;)A+=s;for(var D=Math.min(e.inWidth,h+S),T=Number.NEGATIVE_INFINITY,N=-1,F=b;F<w;F+=i)for(var _=F-x,O=R;O<I;O+=u)for(var M=O-E,B=A;B<D;B+=s){var P=B-S,L=v.get(m,F,O,B,g);L>=T&&(T=L,N=_*l*h+M*l+P)}n.set(N,m,y,C,k,g)}}}return n.toTensor()},o.prototype.maxPool3dBackprop=function(t,e,n,r){Ih([e,n],\"maxPool3dBackprop\");for(var o=this.maxPool3dPositions(e,r),a=r.strideDepth,i=r.strideHeight,u=r.strideWidth,s=r.dilationDepth,c=r.dilationHeight,l=r.dilationWidth,h=r.effectiveFilterDepth,f=r.effectiveFilterHeight,p=r.effectiveFilterWidth,d=h-1-r.padInfo.front,v=p-1-r.padInfo.left,m=f-1-r.padInfo.top,g=ir(e.shape,\"float32\"),y=this.bufferSync(o),x=this.bufferSync(t),b=0;b<r.batchSize;++b)for(var w=0;w<r.inChannels;++w)for(var C=0;C<r.inDepth;++C)for(var E=0;E<r.inHeight;++E)for(var R=0;R<r.inWidth;++R){for(var I=C-d,k=E-m,S=R-v,A=0,D=0;D<h;D+=s){var T=(I+D)/a;if(!(T<0||T>=r.outDepth||Math.floor(T)!==T))for(var N=0;N<f;N+=c){var F=(k+N)/i;if(!(F<0||F>=r.outHeight||Math.floor(F)!==F))for(var _=0;_<p;_+=l){var O=(S+_)/u;if(!(O<0||O>=r.outWidth||Math.floor(O)!==O)){var M=h*f*p-1-y.get(b,T,F,O,w)===D*f*p+N*p+_?1:0;if(0!==M)A+=x.get(b,T,F,O,w)*M}}}}g.set(A,b,C,E,R,w)}return g.toTensor()},o.prototype.cast=function(t,e){return So(t,e,this)},o.prototype.reshape=function(t,e){return Ao(t,e)},o.prototype.avgPool=function(t,e){return Ih(t,\"avgPool\"),this.pool(t,e,\"avg\").toFloat()},o.prototype.resizeBilinear=function(t,e,n,r){Ih(t,\"resizeBilinear\");for(var o=t.shape,a=o[0],i=o[1],u=o[2],s=o[3],c=this.readSync(t.dataId),l=new Float32Array(w([a,e,n,s])),h=[r&&e>1?i-1:i,r&&n>1?u-1:u],f=[r&&e>1?e-1:e,r&&n>1?n-1:n],p=0,d=h[0]/f[0],v=h[1]/f[1],m=0;m<a;m++)for(var g=0;g<e;g++)for(var y=d*g,x=Math.floor(y),b=y-x,C=Math.min(i-1,Math.ceil(y)),E=m*t.strides[0]+x*t.strides[1],R=m*t.strides[0]+C*t.strides[1],I=0;I<n;I++)for(var k=v*I,S=Math.floor(k),A=k-S,D=Math.min(u-1,Math.ceil(k)),T=E+S*t.strides[2],N=R+S*t.strides[2],F=E+D*t.strides[2],_=R+D*t.strides[2],O=0;O<s;O++){var M=c[T+O],B=c[N+O],P=M+(c[F+O]-M)*A,L=P+(B+(c[_+O]-B)*A-P)*b;l[p++]=L}return In(l,[a,e,n,s])},o.prototype.resizeBilinearBackprop=function(t,e,n){Ih([t,e],\"resizeBilinearBackprop\");for(var r=e.shape,o=r[0],a=r[1],i=r[2],u=r[3],s=t.shape,c=s[1],l=s[2],h=new Float32Array(o*a*i*u),f=[n&&c>1?a-1:a,n&&l>1?i-1:i],p=[n&&c>1?c-1:c,n&&l>1?l-1:l],d=f[0]/p[0],v=f[1]/p[1],m=this.readSync(t.dataId),g=0,y=0;y<o;y++)for(var x=y*e.strides[0],b=0;b<c;b++)for(var w=b*d,C=Math.floor(w),E=Math.min(Math.ceil(w),a-1),R=x+C*e.strides[1],I=x+E*e.strides[1],k=w-C,S=1-k,A=0;A<l;A++)for(var D=A*v,T=Math.floor(D),N=Math.min(Math.ceil(D),i-1),F=D-T,_=1-F,O=R+T*e.strides[2],M=R+N*e.strides[2],B=I+T*e.strides[2],P=I+N*e.strides[2],L=S*_,W=S*F,U=k*_,V=k*F,z=0;z<u;z++){var G=m[g++];h[O+z]+=G*L,h[M+z]+=G*W,h[B+z]+=G*U,h[P+z]+=G*V}return Nn(h,[o,i,a,u],e.dtype)},o.prototype.resizeNearestNeighbor=function(t,e,n,r){Ih(t,\"resizeNearestNeighbor\");for(var o=t.shape,a=o[0],i=o[1],u=o[2],s=o[3],c=this.readSync(t.dataId),l=new Float32Array(a*e*n*s),h=[r&&e>1?i-1:i,r&&n>1?u-1:u],f=[r&&e>1?e-1:e,r&&n>1?n-1:n],p=h[0]/f[0],d=h[1]/f[1],v=0,m=0;m<a;m++)for(var g=m*t.strides[0],y=0;y<e;y++)for(var x=p*y,b=g+Math.min(i-1,r?Math.round(x):Math.floor(x))*t.strides[1],w=0;w<n;w++)for(var C=d*w,E=b+Math.min(u-1,r?Math.round(C):Math.floor(C))*t.strides[2],R=0;R<s;R++){var I=c[E+R];l[v++]=I}return In(l,[a,e,n,s],t.dtype)},o.prototype.resizeNearestNeighborBackprop=function(t,e,n){Ih([t,e],\"resizeNearestNeighborBackprop\");for(var r=e.shape,o=r[0],a=r[1],i=r[2],u=r[3],s=t.shape,c=s[1],l=s[2],h=new Float32Array(o*a*i*u),f=this.readSync(t.dataId),p=[n&&c>1?a-1:a,n&&l>1?i-1:i],d=[n&&c>1?c-1:c,n&&l>1?l-1:l],v=p[0]/d[0],m=p[1]/d[1],g=1/v,y=1/m,x=2*Math.ceil(g)+2,b=2*Math.ceil(y)+2,w=0;w<o;w++)for(var C=w*e.strides[0],E=0;E<a;E++)for(var R=C+E*e.strides[1],I=Math.floor(E*g),k=Math.floor(I-x/2),S=0;S<i;S++)for(var A=R+S*e.strides[2],D=Math.floor(S*y),T=Math.floor(D-b/2),N=0;N<u;N++){for(var F=0,_=0;_<x;_++){var O=_+k;if(!(O<0||O>=c)){var M=C+O*t.strides[1],B=O*v;if(E===Math.min(a-1,n?Math.round(B):Math.floor(B)))for(var P=0;P<b;P++){var L=P+T;if(!(L<0||L>=l)){var W=M+L*t.strides[2],U=L*m;S===Math.min(i-1,n?Math.round(U):Math.floor(U))&&(F+=f[W+N])}}}}h[A+N]=F}return Nn(h,e.shape,e.dtype)},o.prototype.batchNormalization=function(t,e,n,r,o,a){Ih([t,e,n,o,a],\"batchNorm\");for(var i=this.readSync(t.dataId),u=this.readSync(e.dataId),s=this.readSync(n.dataId),c=o?this.readSync(o.dataId):new Float32Array([1]),l=a?this.readSync(a.dataId):new Float32Array([0]),h=new Float32Array(i.length),f=l.length,p=c.length,d=s.length,v=u.length,m=0,g=0,y=0,x=0,b=0;b<i.length;++b)h[b]=l[m++]+(i[b]-u[g++])*c[y++]/Math.sqrt(s[x++]+r),m>=f&&(m=0),g>=v&&(g=0),y>=p&&(y=0),x>=d&&(x=0);return Nn(h,t.shape)},o.prototype.localResponseNormalization4D=function(t,e,n,r,o){Ih(t,\"localResponseNormalization4D\");var a=t.shape[3],i=a-1,u=this.readSync(t.dataId),s=t.size,c=new Float32Array(s);function l(t){for(var n=t%a,r=t-n+Math.max(0,n-e),o=t-n+Math.min(n+e,i),s=0;r<=o;r++){var c=u[r];s+=c*c}return s}for(var h=0;h<s;h++){var f=l(h),p=u[h]*Math.pow(n+r*f,-o);c[h]=p}return Nn(c,t.shape)},o.prototype.LRNGrad=function(t,e,n,r,o,a,i){Ih(t,\"LRNGrad\");for(var u=t.shape[3],s=this.readSync(t.dataId),c=this.readSync(e.dataId),l=this.readSync(n.dataId),h=new Float32Array(t.size),f=t.size,p=0;p<f;p++){for(var d=p%u,v=p-d+Math.max(0,d-r),m=p-d+Math.min(u,d+r+1),g=0,y=v;y<m;y++)g+=Math.pow(c[y],2);g=a*g+o;for(y=v;y<m;y++){var x=-2*a*i*c[y]*l[p]/g;p===y&&(x+=Math.pow(g,-i)),x*=s[p],h[y]+=x}}return Nn(h,t.shape)},o.prototype.multinomial=function(t,e,n,r){Ih(t,\"multinomial\");for(var o=e?t:io(t),a=o.shape[0],i=o.shape[1],u=Bn([a,n],\"int32\"),s=this.readSync(u.dataId),c=this.readSync(o.dataId),l=0;l<a;++l){var h=l*i,f=new Float32Array(i-1);f[0]=c[h];for(var p=1;p<f.length;++p)f[p]=f[p-1]+c[h+p];for(var d=nr(r.toString()),v=l*n,m=0;m<n;++m){var g=d();s[v+m]=f.length;for(var y=0;y<f.length;y++)if(g<f[y]){s[v+m]=y;break}}}return u},o.prototype.oneHot=function(t,e,n,r){Ih(t,\"oneHot\");var o=new Float32Array(t.size*e);o.fill(r);for(var a=this.readSync(t.dataId),i=0;i<t.size;++i)a[i]>=0&&a[i]<e&&(o[i*e+a[i]]=n);return Dn(o,[t.size,e],\"int32\")},o.prototype.nonMaxSuppression=function(t,e,n,r,o){return Ih(t,\"nonMaxSuppression\"),Mo(this.readSync(t.dataId),this.readSync(e.dataId),n,r,o)},o.prototype.fft=function(t){return this.fftBatch(t,!1)},o.prototype.ifft=function(t){return this.fftBatch(t,!0)},o.prototype.fftBatch=function(t,e){for(var n=t.shape[0],r=t.shape[1],o=ir(t.shape,\"float32\"),a=ir(t.shape,\"float32\"),i=En(t).as2D(n,r),u=Rn(t).as2D(n,r),s=0;s<n;s++)for(var c=i.slice([s,0],[1,r]),l=u.slice([s,0],[1,r]),h=Cn(c,l),f=this.readSync(this.fftImpl(h,e).dataId),p=0;p<r;p++){var d=Fo(f,p);o.values[s*r+p]=d.real,a.values[s*r+p]=d.imag}return Cn(o.toTensor(),a.toTensor()).as2D(n,r)},o.prototype.fftImpl=function(t,e){var n=t.as1D(),r=n.size;if(this.isExponentOf2(r)){var o=this.fftRadix2(n,r,e).as2D(t.shape[0],t.shape[1]);return e&&(o=Cn(En(o).div(Sn(r)),Rn(o).div(Sn(r)))),o}var a=this.readSync(t.dataId),i=function(t){for(var e=new Float32Array(t.length/2),n=new Float32Array(t.length/2),r=0;r<t.length;r+=2)e[r/2]=t[r],n[r/2]=t[r+1];return{real:e,imag:n}}(this.fourierTransformByMatmul(a,r,e));return Cn(i.real,i.imag).as2D(t.shape[0],t.shape[1])},o.prototype.isExponentOf2=function(t){return 0==(t&t-1)},o.prototype.fftRadix2=function(t,e,n){if(1===e)return t;var r=this.readSync(t.dataId),o=e/2,a=function(t){for(var e=Math.ceil(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=0;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return{real:n,imag:r}}(r),i=Cn(a.real,a.imag).as1D(),u=function(t){for(var e=Math.floor(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=2;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return{real:n,imag:r}}(r),s=Cn(u.real,u.imag).as1D();i=this.fftRadix2(i,o,n),s=this.fftRadix2(s,o,n);var c=function(t,e){for(var n=new Float32Array(t/2),r=new Float32Array(t/2),o=0;o<Math.ceil(t/2);o++){var a=(e?2:-2)*Math.PI*(o/t);n[o]=Math.cos(a),r[o]=Math.sin(a)}return{real:n,imag:r}}(e,n),l=Cn(c.real,c.imag).mul(s),h=i.add(l),f=i.sub(l),p=En(h).concat(En(f)),d=Rn(h).concat(Rn(f));return Cn(p,d).as1D()},o.prototype.fourierTransformByMatmul=function(t,e,n){for(var r=new Float32Array(2*e),o=0;o<e;o++){for(var a=0,i=0,u=0;u<e;u++){var s=Oo(o*u,e,n),c=Fo(t,u);a+=c.real*s.real-c.imag*s.imag,i+=c.real*s.imag+c.imag*s.real}n&&(a/=e,i/=e),_o(r,a,i,o)}return r},o.prototype.depthToSpace=function(t,e,n){g(\"NHWC\"===n,function(){return\"Only NHWC dataFormat supported on CPU for depthToSpace. Got \"+n}),g(e>1,function(){return\"blockSize should be > 1 for depthToSpace, but was: \"+e});for(var r=t.shape[0],o=t.shape[1],a=t.shape[2],i=t.shape[3],u=o*e,s=a*e,c=i/(e*e),l=this.readSync(t.dataId),h=new Float32Array(r*u*s*c),f=0,p=0;p<r;++p)for(var d=0;d<u;++d)for(var v=Math.floor(d/e),m=d%e,y=0;y<s;++y)for(var x=Math.floor(y/e),b=(m*e+y%e)*c,w=0;w<c;++w){var C=w+b+i*(x+a*(v+o*p));h[f++]=l[C]}return Nn(h,[r,u,s,c])},o.prototype.broadcastedBinaryOp=function(t,e,n,r){var o=po(t.shape,e.shape),a=ir(o,n),i=this.readSync(t.dataId),u=this.readSync(e.dataId),s=ho(t.shape,o),c=ho(e.shape,o),l=a.values;if(s.length+c.length===0)for(var h=0;h<l.length;++h)l[h]=r(i[h%i.length],u[h%u.length]);else{var f=this.bufferSync(t),p=this.bufferSync(e),d=function(n){var o=a.indexToLoc(n),h=o.slice(-t.rank);s.forEach(function(t){return h[t]=0});var d=f.locToIndex(h),v=o.slice(-e.rank);c.forEach(function(t){return v[t]=0});var m=p.locToIndex(v);l[n]=r(i[d],u[m])};for(h=0;h<l.length;++h)d(h)}return a.toTensor()},o.prototype.broadcastedBinaryComplexOp=function(t,e,n){var r=po(t.shape,e.shape),o=ir(r,\"float32\"),a=ir(r,\"float32\"),i=this.readSync(t.dataId),u=this.readSync(e.dataId),s=ho(t.shape,r),c=ho(e.shape,r),l=o.values,h=a.values;if(s.length+c.length===0)for(var f=0;f<l.length;f++){var p=f%i.length,d=f%u.length,v=n(i[2*p],i[2*p+1],u[2*d],u[2*d+1]);l[f]=v.real,h[f]=v.imag}else{var m=this.bufferSync(this.data.get(t.dataId).complexTensors.real),g=this.bufferSync(this.data.get(e.dataId).complexTensors.real),y=function(r){var a=o.indexToLoc(r),f=a.slice(-t.rank);s.forEach(function(t){return f[t]=0});var p=m.locToIndex(f),d=a.slice(-e.rank);c.forEach(function(t){return d[t]=0});var v=g.locToIndex(d),y=n(i[2*p],i[2*p+1],u[2*v],u[2*v+1]);l[r]=y.real,h[r]=y.imag};for(f=0;f<l.length;f++)y(f)}return this.complex(o.toTensor(),a.toTensor())},o.prototype.split=function(t,e,n){return Po(t,e,n)},o.prototype.dispose=function(){},o.prototype.floatPrecision=function(){return 32},o.prototype.epsilon=function(){return 1e-7},o.prototype.cropAndResize=function(t,e,n,r,o,a){for(var i=t.shape,u=i[0],s=i[1],c=i[2],l=i[3],h=e.shape[0],f=r[0],p=r[1],d=ir([h,f,p,l],\"float32\"),v=this.readSync(e.dataId),m=this.readSync(n.dataId),g=this.readSync(t.dataId),y=t.strides,x=d.strides,b=0;b<h;b++){var w=4*b,C=v[w],E=v[w+1],R=v[w+2],I=v[w+3],k=m[b];if(!(k>=u))for(var S=f>1?(R-C)*(s-1)/(f-1):0,A=p>1?(I-E)*(c-1)/(p-1):0,D=0;D<f;D++){var T=f>1?C*(s-1)+D*S:.5*(C+R)*(s-1);if(T<0||T>s-1)for(var N=0;N<p;N++)for(var F=0;F<l;F++){var _=F+N*x[2]+D*x[1]+b*x[0];d.values[_]=a}else if(\"bilinear\"===o){var O=Math.floor(T),M=Math.ceil(T),B=T-O;for(N=0;N<p;N++){if((q=p>1?E*(c-1)+N*A:.5*(E+I)*(c-1))<0||q>c-1)for(F=0;F<l;F++){_=F+N*x[2]+D*x[1]+b*x[0];d.values[_]=a}else{var P=Math.floor(q),L=Math.ceil(q),W=q-P;for(F=0;F<l;F++){var U=g[_=F+P*y[2]+O*y[1]+k*y[0]],V=g[_=F+L*y[2]+O*y[1]+k*y[0]],z=g[_=F+P*y[2]+M*y[1]+k*y[0]],G=U+(V-U)*W,H=z+(g[_=F+L*y[2]+M*y[1]+k*y[0]]-z)*W;_=F+N*x[2]+D*x[1]+b*x[0],d.values[_]=G+(H-G)*B}}}}else for(N=0;N<p;++N){var q;if((q=p>1?E*(c-1)+N*A:.5*(E+I)*(c-1))<0||q>c-1)for(F=0;F<l;F++){_=F+N*x[2]+D*x[1]+b*x[0];d.values[_]=a}else{var K=Math.round(q),j=Math.round(T);for(F=0;F<l;F++){var X=F+K*y[2]+j*y[1]+k*y[0],$=F+N*x[2]+D*x[1]+b*x[0];d.values[$]=g[X]}}}}}return d.toTensor()},o.prototype.sparseToDense=function(t,e,n,r){var o=Hr(0,t,n),a=o.sliceRank,i=o.numUpdates,u=o.sliceSize,s=o.strides,c=o.outputSize;return this.scatter(t,e,n,c,u,i,a,s,r,!1)},o.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=Ur(t,e),a=o[0],i=o[1],u=o[2],s=o[3];if(0===i)return In([],a,t.dtype);for(var c=new lt([i,u],t.dtype),l=this.readSync(e.dataId),h=this.readSync(t.dataId),f=0;f<i;f++){for(var p=[],d=0,v=0;v<r;v++){var m=l[f*r+v];d+=m*s[v],p.push(m)}if(d<0||d>=t.size/u)throw new Error(\"Invalid indices: \"+p+\" does not index into \"+t.shape);for(var g=0;g<u;g++)c.values[f*u+g]=h[d*u+g]}return c.toTensor().reshape(a)},o.prototype.scatterND=function(t,e,n){var r=Hr(0,t,n),o=r.sliceRank,a=r.numUpdates,i=r.sliceSize,u=r.strides,s=r.outputSize,c=Sn(0);return this.scatter(t,e,n,s,i,a,o,u,c,!0)},o.prototype.fill=function(t,e,n){var r=F(n=n||z(e),w(t));return r.fill(e),Nt.makeTensor(r,t,n,this)},o.prototype.onesLike=function(t){if(\"string\"===t.dtype)throw new Error(\"onesLike is not supported for string tensors\");return this.fill(t.shape,1,t.dtype)},o.prototype.zerosLike=function(t){var e=F(t.dtype,w(t.shape));return this.makeOutput(e,t.shape,t.dtype)},o.prototype.linspace=function(t,e,n){return Do(t,e,n)},o.prototype.scatter=function(t,e,n,r,o,a,i,u,s,c){var l=[r/o,o],h=this.readSync(t.dataId),f=this.readSync(e.dataId);if(0===r)return In([],n,e.dtype);var p=new lt(l,e.dtype);p.values.fill(this.readSync(s.dataId)[0]);for(var d=0;d<a;d++){for(var v=[],m=0,g=0;g<i;g++){var y=h[d*i+g];v.push(y),m+=y*u[g]}if(m<0||m>=r/o)throw new Error(\"Invalid indices: \"+v+\" does not index into \"+n);for(var x=0;x<o;x++)c?p.values[m*o+x]+=f[d*o+x]:p.values[m*o+x]=0===e.rank?f[0]:f[d*o+x]}return p.toTensor().reshape(n)},o}(co);Nt.registerBackend(\"cpu\",function(){return new Sh},1),l({kernelName:\"Square\",backendName:\"cpu\",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e.x,o=n;Ih(r,\"square\");for(var a=o.data.get(r.dataId).values,i=new Float32Array(a.length),u=0;u<a.length;++u){var s=a[u];i[u]=s*s}return{dataId:o.write(i,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}}),l({kernelName:\"Square\",backendName:\"webgl\",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e.x,o=n,a=new iu(r.shape,\"return x * x;\");return o.runWebGLProgram(a,[r],r.dtype)}});var Ah,Dh=function(){return function(t){this.variableNames=[\"A\"];var e=Ko(),n=t[0],r=t[1];this.outputShape=t,this.userCode=\"\\n      void main() {\\n        ivec3 coords = getOutputCoords();\\n        int texR 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col=0; col<=1; col++) {\\n            texC = coords[1] + row;\\n            depth = coords[2] + col;\\n\\n            vec2 uv = (vec2(texC, texR) + halfCR) /\\n                       vec2(\"+r+\".0, \"+n+\".0);\\n            vec4 values = \"+e.texture2D+\"(A, uv);\\n            float value;\\n            if (depth == 0) {\\n              value = values.r;\\n            } else if (depth == 1) {\\n              value = values.g;\\n            } else if (depth == 2) {\\n              value = values.b;\\n            } else if (depth == 3) {\\n              value = values.a;\\n            }\\n\\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\\n          }\\n        }\\n\\n        \"+e.output+\" = result;\\n      }\\n    \"}}();l({kernelName:\"FromPixels\",backendName:\"webgl\",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=t.attrs,o=e.pixels,i=r.numChannels,u=\"undefined\"!=typeof HTMLVideoElement&&o instanceof HTMLVideoElement,s=\"undefined\"!=typeof HTMLImageElement&&o instanceof HTMLImageElement,c=u?[o.videoWidth,o.videoHeight]:[o.width,o.height],l=c[0],h=c[1],f=[h,l],p=[h,l,i];(s||u)&&(null==Ah&&(Ah=document.createElement(\"canvas\").getContext(\"2d\")),Ah.canvas.width=l,Ah.canvas.height=h,Ah.drawImage(o,0,0,l,h),o=Ah.canvas);var d=n.makeTensorInfo(f,\"int32\");n.texData.get(d.dataId).usage=Mt.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),o);var v=a().getBool(\"WEBGL_PACK\")?new Th(p):new Dh(p),m=n.runWebGLProgram(v,[d],\"int32\");return n.disposeData(d.dataId),m}});var Nh=function(){function t(){}return t.prototype.fetch=function(t,e){return fetch(t,e)},t.prototype.now=function(){return performance.now()},t.prototype.encode=function(t,e){if(\"utf-8\"!==e&&\"utf8\"!==e)throw new Error(\"Browser's encoder only supports utf-8, but got \"+e);return null==this.textEncoder&&(this.textEncoder=new TextEncoder),this.textEncoder.encode(t)},t.prototype.decode=function(t,e){return new 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h=r.sent(),o&&l?[4,Kh.getManager(s).removeModel(c)]:[3,3];case 2:r.sent(),r.label=3;case 3:return[4,u.save(h)];case 4:return f=r.sent(),!o||l?[3,6]:[4,Kh.getManager(s).removeModel(c)];case 5:r.sent(),r.label=6;case 6:return[2,f.modelArtifactsInfo]}})})}var $h=\"models_store\",Yh=\"model_info_store\";function Qh(){if(!a().getBool(\"IS_BROWSER\"))throw new Error(\"Failed to obtain IndexedDB factory because the current environmentis not a web browser.\");var t=window,e=t.indexedDB||t.mozIndexedDB||t.webkitIndexedDB||t.msIndexedDB||t.shimIndexedDB;if(null==e)throw new Error(\"The current browser does not appear to support IndexedDB.\");return e}function Jh(t){var e=t.result;e.createObjectStore($h,{keyPath:\"modelPath\"}),e.createObjectStore(Yh,{keyPath:\"modelPath\"})}var Zh=function(){function t(t){if(this.indexedDB=Qh(),null==t||!t)throw new Error(\"For IndexedDB, modelPath must not be null, undefined or empty.\");this.modelPath=t}return t.prototype.save=function(t){return n(this,void 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s,c=Gh(e),l=a.transaction(Yh,\"readwrite\"),h=l.objectStore(Yh),f=h.put({modelPath:n.modelPath,modelArtifactsInfo:c});f.onsuccess=function(){var o=(s=a.transaction($h,\"readwrite\")).objectStore($h).put({modelPath:n.modelPath,modelArtifacts:e,modelArtifactsInfo:c});o.onsuccess=function(){return t({modelArtifactsInfo:c})},o.onerror=function(t){var e=(h=l.objectStore(Yh)).delete(n.modelPath);e.onsuccess=function(){return a.close(),r(o.error)},e.onerror=function(t){return a.close(),r(o.error)}}},f.onerror=function(t){return a.close(),r(f.error)},l.oncomplete=function(){null==s?a.close():s.oncomplete=function(){return a.close()}}}},o.onerror=function(t){return r(o.error)}})},t.URL_SCHEME=\"indexeddb://\",t}(),tf=function(t){return a().getBool(\"IS_BROWSER\")&&!Array.isArray(t)&&t.startsWith(Zh.URL_SCHEME)?(e=t.slice(Zh.URL_SCHEME.length),new Zh(e)):null;var e};Hh.registerSaveRouter(tf),Hh.registerLoadRouter(tf);var ef=function(){function t(){this.indexedDB=Qh()}return t.prototype.listModels=function(){return n(this,void 0,void 0,function(){var t=this;return r(this,function(e){return[2,new Promise(function(e,n){var r=t.indexedDB.open(\"tensorflowjs\",1);r.onupgradeneeded=function(){return Jh(r)},r.onsuccess=function(){var t=r.result,o=t.transaction(Yh,\"readonly\"),a=o.objectStore(Yh).getAll();a.onsuccess=function(){for(var t={},n=0,r=a.result;n<r.length;n++){var o=r[n];t[o.modelPath]=o.modelArtifactsInfo}e(t)},a.onerror=function(e){return t.close(),n(a.error)},o.oncomplete=function(){return t.close()}},r.onerror=function(t){return n(r.error)}})]})})},t.prototype.removeModel=function(t){return n(this,void 0,void 0,function(){var e=this;return r(this,function(n){var r;return t=(r=t).startsWith(Zh.URL_SCHEME)?r.slice(Zh.URL_SCHEME.length):r,[2,new Promise(function(n,r){var o=e.indexedDB.open(\"tensorflowjs\",1);o.onupgradeneeded=function(){return Jh(o)},o.onsuccess=function(){var e,a=o.result,i=a.transaction(Yh,\"readwrite\"),u=i.objectStore(Yh),s=u.get(t);s.onsuccess=function(){if(null==s.result)return a.close(),r(new Error(\"Cannot find model with path '\"+t+\"' in IndexedDB.\"));var o=u.delete(t),i=function(){var o=(e=a.transaction($h,\"readwrite\")).objectStore($h).delete(t);o.onsuccess=function(){return n(s.result.modelArtifactsInfo)},o.onerror=function(t){return r(s.error)}};o.onsuccess=i,o.onerror=function(t){return i(),a.close(),r(s.error)}},s.onerror=function(t){return a.close(),r(s.error)},i.oncomplete=function(){null==e?a.close():e.oncomplete=function(){return a.close()}}},o.onerror=function(t){return r(o.error)}})]})})},t}();if(a().getBool(\"IS_BROWSER\"))try{Kh.registerManager(Zh.URL_SCHEME,new ef)}catch(t){}var nf=\"/\",rf=\"tensorflowjs_models\",of=\"info\",af=\"model_topology\",uf=\"weight_specs\",sf=\"weight_data\",cf=\"model_metadata\";function lf(t){return{info:[rf,t,of].join(nf),topology:[rf,t,af].join(nf),weightSpecs:[rf,t,uf].join(nf),weightData:[rf,t,sf].join(nf),modelMetadata:[rf,t,cf].join(nf)}}function hf(t){var e=t.split(nf);if(e.length<3)throw new Error(\"Invalid key format: \"+t);return e.slice(1,e.length-1).join(nf)}var ff=function(){function t(t){if(!a().getBool(\"IS_BROWSER\")||void 0===window.localStorage)throw new Error(\"The current environment does not support local storage.\");if(this.LS=window.localStorage,null==t||!t)throw new Error(\"For local storage, modelPath must not be null, undefined or empty.\");this.modelPath=t,this.keys=lf(this.modelPath)}return t.prototype.save=function(t){return n(this,void 0,void 0,function(){var e,n,o;return r(this,function(r){if(t.modelTopology instanceof ArrayBuffer)throw new Error(\"BrowserLocalStorage.save() does not support saving model topology in binary formats yet.\");e=JSON.stringify(t.modelTopology),n=JSON.stringify(t.weightSpecs),o=Gh(t);try{return this.LS.setItem(this.keys.info,JSON.stringify(o)),this.LS.setItem(this.keys.topology,e),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,(a=t.weightData,Wh?Buffer.from(a).toString(\"base64\"):btoa(String.fromCharCode.apply(null,new Uint8Array(a))))),this.LS.setItem(this.keys.modelMetadata,JSON.stringify({format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,userDefinedMetadata:t.userDefinedMetadata})),[2,{modelArtifactsInfo:o}]}catch(t){throw this.LS.removeItem(this.keys.info),this.LS.removeItem(this.keys.topology),this.LS.removeItem(this.keys.weightSpecs),this.LS.removeItem(this.keys.weightData),this.LS.removeItem(this.keys.modelMetadata),new Error(\"Failed to save model '\"+this.modelPath+\"' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=\"+o.modelTopologyBytes+\", weightSpecsBytes=\"+o.weightSpecsBytes+\", weightDataBytes=\"+o.weightDataBytes+\".\")}var a;return[2]})})},t.prototype.load=function(){return n(this,void 0,void 0,function(){var t,e,n,o,a,i,u;return r(this,function(r){if(null==(t=JSON.parse(this.LS.getItem(this.keys.info))))throw new Error(\"In local storage, there is no model with name '\"+this.modelPath+\"'\");if(\"JSON\"!==t.modelTopologyType)throw new Error(\"BrowserLocalStorage does not support loading non-JSON model topology yet.\");if(e={},null==(n=JSON.parse(this.LS.getItem(this.keys.topology))))throw new Error(\"In local storage, the topology of model '\"+this.modelPath+\"' is missing.\");if(e.modelTopology=n,null==(o=JSON.parse(this.LS.getItem(this.keys.weightSpecs))))throw new Error(\"In local storage, the weight specs of model '\"+this.modelPath+\"' are missing.\");if(e.weightSpecs=o,null!=(a=this.LS.getItem(this.keys.modelMetadata))&&(i=JSON.parse(a),e.format=i.format,e.generatedBy=i.generatedBy,e.convertedBy=i.convertedBy,e.userDefinedMetadata=i.userDefinedMetadata),null==(u=this.LS.getItem(this.keys.weightData)))throw new Error(\"In local storage, the binary weight values of model '\"+this.modelPath+\"' are missing.\");return e.weightData=function(t){if(Wh){var e=Buffer.from(t,\"base64\");return e.buffer.slice(e.byteOffset,e.byteOffset+e.byteLength)}for(var n=atob(t),r=new Uint8Array(n.length),o=0;o<n.length;++o)r.set([n.charCodeAt(o)],o);return r.buffer}(u),[2,e]})})},t.URL_SCHEME=\"localstorage://\",t}(),pf=function(t){return a().getBool(\"IS_BROWSER\")&&!Array.isArray(t)&&t.startsWith(ff.URL_SCHEME)?(e=t.slice(ff.URL_SCHEME.length),new ff(e)):null;var e};Hh.registerSaveRouter(pf),Hh.registerLoadRouter(pf);var df=function(){function t(){g(a().getBool(\"IS_BROWSER\"),function(){return\"Current environment is not a web browser\"}),g(void 0!==window.localStorage,function(){return\"Current browser does not appear to support localStorage\"}),this.LS=window.localStorage}return t.prototype.listModels=function(){return n(this,void 0,void 0,function(){var t,e,n,o,a,i;return r(this,function(r){for(t={},e=rf+nf,n=nf+of,o=0;o<this.LS.length;++o)(a=this.LS.key(o)).startsWith(e)&&a.endsWith(n)&&(i=hf(a),t[i]=JSON.parse(this.LS.getItem(a)));return[2,t]})})},t.prototype.removeModel=function(t){return n(this,void 0,void 0,function(){var e,n;return r(this,function(r){var o;if(t=(o=t).startsWith(ff.URL_SCHEME)?o.slice(ff.URL_SCHEME.length):o,e=lf(t),null==this.LS.getItem(e.info))throw new Error(\"Cannot find model at path '\"+t+\"'\");return n=JSON.parse(this.LS.getItem(e.info)),this.LS.removeItem(e.info),this.LS.removeItem(e.topology),this.LS.removeItem(e.weightSpecs),this.LS.removeItem(e.weightData),[2,n]})})},t}();if(a().getBool(\"IS_BROWSER\"))try{Kh.registerManager(ff.URL_SCHEME,new df)}catch(t){}var vf=\"model\",mf=\".json\",gf=\".weights.bin\";function yf(t){return new Promise(function(t){return setTimeout(t)}).then(t)}var xf=function(){function t(e){if(!a().getBool(\"IS_BROWSER\"))throw new Error(\"browserDownloads() cannot proceed because the current environment is not a browser.\");e.startsWith(t.URL_SCHEME)&&(e=e.slice(t.URL_SCHEME.length)),null!=e&&0!==e.length||(e=vf),this.modelTopologyFileName=e+mf,this.weightDataFileName=e+gf}return t.prototype.save=function(t){return n(this,void 0,void 0,function(){var e,n,o,a,i,u;return r(this,function(r){switch(r.label){case 0:if(\"undefined\"==typeof document)throw new Error(\"Browser downloads are not supported in this environment since `document` is not present\");if(e=window.URL.createObjectURL(new Blob([t.weightData],{type:\"application/octet-stream\"})),!(t.modelTopology instanceof ArrayBuffer))return[3,1];throw new Error(\"BrowserDownloads.save() does not support saving model topology in binary formats yet.\");case 1:return n=[{paths:[\"./\"+this.weightDataFileName],weights:t.weightSpecs}],o={modelTopology:t.modelTopology,format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,weightsManifest:n},a=window.URL.createObjectURL(new Blob([JSON.stringify(o)],{type:\"application/json\"})),(i=null==this.jsonAnchor?document.createElement(\"a\"):this.jsonAnchor).download=this.modelTopologyFileName,i.href=a,[4,yf(function(){return i.dispatchEvent(new MouseEvent(\"click\"))})];case 2:return r.sent(),null==t.weightData?[3,4]:((u=null==this.weightDataAnchor?document.createElement(\"a\"):this.weightDataAnchor).download=this.weightDataFileName,u.href=e,[4,yf(function(){return u.dispatchEvent(new MouseEvent(\"click\"))})]);case 3:r.sent(),r.label=4;case 4:return[2,{modelArtifactsInfo:Gh(t)}]}})})},t.URL_SCHEME=\"downloads://\",t}(),bf=function(){function t(t){if(null==t||t.length<1)throw new Error(\"When calling browserFiles, at least 1 file is required, but received \"+t);this.files=t}return t.prototype.load=function(){return n(this,void 0,void 0,function(){var t,e,n=this;return r(this,function(r){return t=this.files[0],e=this.files.slice(1),[2,new Promise(function(r,o){var a=new FileReader;a.onload=function(a){var i=JSON.parse(a.target.result),u=i.modelTopology;if(null!=u){0===e.length&&r({modelTopology:u});var s=i.weightsManifest;if(null!=s){var c;try{c=n.checkManifestAndWeightFiles(s,e)}catch(t){return void o(t)}var l=[],h=[],f=[];s.forEach(function(t){t.paths.forEach(function(t){h.push(t),f.push(null)}),l.push.apply(l,t.weights)}),s.forEach(function(t){t.paths.forEach(function(t){var e=new FileReader;e.onload=function(e){var n=e.target.result,o=h.indexOf(t);f[o]=n,-1===f.indexOf(null)&&r({modelTopology:u,weightSpecs:l,weightData:Vh(f),format:i.format,generatedBy:i.generatedBy,convertedBy:i.convertedBy,userDefinedMetadata:i.userDefinedMetadata})},e.onerror=function(e){return o(\"Failed to weights data from file of path '\"+t+\"'.\")},e.readAsArrayBuffer(c[t])})})}else o(new Error(\"weightManifest field is missing from file \"+t.name))}else o(new Error(\"modelTopology field is missing from file \"+t.name))},a.onerror=function(e){return o(\"Failed to read model topology and weights manifest JSON from file '\"+t.name+\"'. BrowserFiles supports loading Keras-style tf.Model artifacts only.\")},a.readAsText(t)})]})})},t.prototype.checkManifestAndWeightFiles=function(t,e){for(var n=[],r=e.map(function(t){return zh(t.name)}),o={},a=0,i=t;a<i.length;a++){i[a].paths.forEach(function(t){var a=zh(t);if(-1!==n.indexOf(a))throw new Error(\"Duplicate file basename found in weights manifest: '\"+a+\"'\");if(n.push(a),-1===r.indexOf(a))throw new Error(\"Weight file with basename '\"+a+\"' is not provided.\");o[t]=e[r.indexOf(a)]})}if(n.length!==e.length)throw new Error(\"Mismatch in the number of files in weights manifest (\"+n.length+\") and the number of weight files provided (\"+e.length+\").\");return o},t}();function wf(t,e,n,r){!function(t){g(null!=t&&Array.isArray(t)&&t.length>0,function(){return\"promises must be a none empty array\"})}(t),function(t,e){g(t>=0&&t<=1,function(){return\"Progress fraction must be in range [0, 1], but got startFraction \"+t}),g(e>=0&&e<=1,function(){return\"Progress fraction must be in range [0, 1], but got endFraction \"+e}),g(e>=t,function(){return\"startFraction must be no more than endFraction, but got startFraction \"+t+\" and endFraction \"+e})}(n=null==n?0:n,r=null==r?1:r);var o=0;return Promise.all(t.map(function(a){return a.then(function(a){var i=n+ ++o/t.length*(r-n);return e(i),a}),a}))}function Cf(t,e){return n(this,void 0,void 0,function(){var n,o,i,u,s,c,l,h,f;return r(this,function(r){switch(r.label){case 0:return null==e&&(e={}),n=null==e.fetchFunc?a().platform.fetch:e.fetchFunc,o=t.map(function(t){return n(t,e.requestInit,{isBinary:!0})}),i=0,u=.5,null!=e.onProgress?[3,2]:[4,Promise.all(o)];case 1:return s=r.sent(),[3,4];case 2:return[4,wf(o,e.onProgress,i,u)];case 3:s=r.sent(),r.label=4;case 4:return c=s.map(function(t){return t.arrayBuffer()}),l=.5,h=1,null!=e.onProgress?[3,6]:[4,Promise.all(c)];case 5:return f=r.sent(),[3,8];case 6:return[4,wf(c,e.onProgress,l,h)];case 7:f=r.sent(),r.label=8;case 8:return[2,f]}})})}function Ef(t){var e=this;return function(o,a,i){return void 0===a&&(a=\"\"),n(e,void 0,void 0,function(){var e,n,u,s,c,l,h,f,p,d;return r(this,function(r){switch(r.label){case 0:if(e=o.map(function(){return!1}),n={},u=null!=i?i.map(function(){return!1}):[],s=[],o.forEach(function(t,r){var o=0;t.weights.forEach(function(t){var a=\"quantization\"in t?t.quantization.dtype:t.dtype,c=Mh[a]*w(t.shape),l=function(){e[r]=!0,null==n[r]&&(n[r]=[]),n[r].push({manifestEntry:t,groupOffset:o,sizeBytes:c})};null!=i?i.forEach(function(e,n){e===t.name&&(l(),u[n]=!0)}):l(),s.push(t.name),o+=c})}),!u.every(function(t){return t}))throw c=i.filter(function(t,e){return!u[e]}),new Error(\"Could not find weights in manifest with names: \"+c.join(\", \")+\". \\nManifest JSON has weights with names: \"+s.join(\", \")+\".\");return l=e.reduce(function(t,e,n){return e&&t.push(n),t},[]),h=[],l.forEach(function(t){o[t].paths.forEach(function(t){var e=a+(a.endsWith(\"/\")?\"\":\"/\")+t;h.push(e)})}),[4,t(h)];case 1:return f=r.sent(),p={},d=0,l.forEach(function(t){for(var e=o[t].paths.length,r=0,a=0;a<e;a++)r+=f[d+a].byteLength;for(var i=new ArrayBuffer(r),u=new Uint8Array(i),s=0,c=0;c<e;c++){var l=new Uint8Array(f[d+c]);u.set(l,s),s+=l.byteLength}n[t].forEach(function(t){var e=Ph(i.slice(t.groupOffset,t.groupOffset+t.sizeBytes),[t.manifestEntry]);for(var n in e)p[n]=e[n]}),d+=e}),[2,p]}})})}}Hh.registerSaveRouter(function(t){return a().getBool(\"IS_BROWSER\")&&!Array.isArray(t)&&t.startsWith(xf.URL_SCHEME)?(e=t.slice(xf.URL_SCHEME.length),void 0===e&&(e=\"model\"),new xf(e)):null;var e});var Rf=function(){function t(t,e){if(this.DEFAULT_METHOD=\"POST\",null==e&&(e={}),this.weightPathPrefix=e.weightPathPrefix,this.onProgress=e.onProgress,null!=e.fetchFunc?(g(\"function\"==typeof e.fetchFunc,function(){return\"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)\"}),this.fetch=e.fetchFunc):this.fetch=a().platform.fetch,g(null!=t&&t.length>0,function(){return\"URL path for http must not be null, undefined or empty.\"}),Array.isArray(t)&&g(2===t.length,function(){return\"URL paths for http must have a length of 2, (actual length is \"+t.length+\").\"}),this.path=t,null!=e.requestInit&&null!=e.requestInit.body)throw new Error(\"requestInit is expected to have no pre-existing body, but has one.\");this.requestInit=e.requestInit||{}}return t.prototype.save=function(t){return n(this,void 0,void 0,function(){var e,n,o,a;return r(this,function(r){switch(r.label){case 0:if(t.modelTopology instanceof ArrayBuffer)throw new Error(\"BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.\");return(e=Object.assign({method:this.DEFAULT_METHOD},this.requestInit)).body=new FormData,n=[{paths:[\"./model.weights.bin\"],weights:t.weightSpecs}],o={modelTopology:t.modelTopology,format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,userDefinedMetadata:t.userDefinedMetadata,weightsManifest:n},e.body.append(\"model.json\",new Blob([JSON.stringify(o)],{type:\"application/json\"}),\"model.json\"),null!=t.weightData&&e.body.append(\"model.weights.bin\",new Blob([t.weightData],{type:\"application/octet-stream\"}),\"model.weights.bin\"),[4,this.fetch(this.path,e)];case 1:if((a=r.sent()).ok)return[2,{modelArtifactsInfo:Gh(t),responses:[a]}];throw new Error(\"BrowserHTTPRequest.save() failed due to HTTP response status \"+a.status+\".\")}})})},t.prototype.load=function(){return n(this,void 0,void 0,function(){var t,e,n,o,a,i,u,s,c,l,h,f;return r(this,function(r){switch(r.label){case 0:return[4,this.fetch(this.path,this.requestInit)];case 1:if(!(t=r.sent()).ok)throw new Error(\"Request to \"+this.path+\" failed with status code \"+t.status+\". Please verify this URL points to the model JSON of the model to load.\");r.label=2;case 2:return r.trys.push([2,4,,5]),[4,t.json()];case 3:return e=r.sent(),[3,5];case 4:throw r.sent(),n=\"Failed to parse model JSON of response from \"+this.path+\".\",this.path.endsWith(\".pb\")?n+=\" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. 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Please wait for `loadeddata` event on the <video> element.\");if(null!=s(\"FromPixels\",Nt.backendName))return Nt.runKernel(\"FromPixels\",{pixels:t},{numChannels:e});var u,c,l=o?[t.videoWidth,t.videoHeight]:[t.width,t.height],h=l[0],f=l[1];if(i?u=t.getContext(\"2d\").getImageData(0,0,h,f).data:r||n?u=t.data:(a||o)&&(null==Nf&&(Nf=document.createElement(\"canvas\").getContext(\"2d\")),Nf.canvas.width=h,Nf.canvas.height=f,Nf.drawImage(t,0,0,h,f),u=Nf.getImageData(0,0,h,f).data),4===e)c=new Int32Array(u);else{var p=h*f;c=new Int32Array(p*e);for(var d=0;d<p;d++)for(var v=0;v<e;++v)c[d*e+v]=u[4*d+v]}return Tn(c,[f,h,e],\"int32\")}}),Mf=Object.freeze({toPixels:function(t,e){return n(this,void 0,void 0,function(){var n,o,a,i,u,s,c,l,h,f,p,d,v,m,g,y,x,b,w,C,E,R,I;return r(this,function(r){switch(r.label){case 0:if(n=cn(t,\"img\",\"toPixels\"),t instanceof dt||(n=n.toInt()),2!==n.rank&&3!==n.rank)throw new Error(\"toPixels only supports rank 2 or 3 tensors, got rank \"+n.rank+\".\");if(o=n.shape.slice(0,2),a=o[0],i=o[1],(u=2===n.rank?1:n.shape[2])>4||2===u)throw new Error(\"toPixels only supports depth of size 1, 3 or 4 but got \"+u);return[4,n.data()];case 1:return s=r.sent(),c=n.min(),l=n.max(),[4,Promise.all([c.data(),l.data()])];case 2:if(h=r.sent(),f=h[0],p=h[1],d=f[0],v=p[0],c.dispose(),l.dispose(),\"float32\"===n.dtype){if(d<0||v>1)throw new Error(\"Tensor values for a float32 Tensor must be in the range [0 - 1] but got range [\"+d+\" - \"+v+\"].\")}else{if(\"int32\"!==n.dtype)throw new Error(\"Unsupported type for toPixels: \"+n.dtype+\". Please use float32 or int32 tensors.\");if(d<0||v>255)throw new Error(\"Tensor values for a int32 Tensor must be in the range [0 - 255] but got range [\"+d+\" - \"+v+\"].\")}for(m=\"float32\"===n.dtype?255:1,g=new Uint8ClampedArray(i*a*4),y=0;y<a*i;++y)x=void 0,b=void 0,w=void 0,C=void 0,1===u?(x=s[y]*m,b=s[y]*m,w=s[y]*m,C=255):3===u?(x=s[3*y]*m,b=s[3*y+1]*m,w=s[3*y+2]*m,C=255):4===u&&(x=s[4*y]*m,b=s[4*y+1]*m,w=s[4*y+2]*m,C=s[4*y+3]*m),g[0+(E=4*y)]=Math.round(x),g[E+1]=Math.round(b),g[E+2]=Math.round(w),g[E+3]=Math.round(C);return null!=e&&(e.width=i,e.height=a,R=e.getContext(\"2d\"),I=new ImageData(g,i,a),R.putImageData(I,0,0)),n!==t&&n.dispose(),[2,g]}})})},fromPixels:Of}),Bf=function(){function t(){}return t.prototype.getClassName=function(){return this.constructor.className},t.fromConfig=function(t,e){return new t(e)},t}(),Pf=function(){function t(){this.classNameMap={}}return t.getMap=function(){return null==t.instance&&(t.instance=new t),t.instance},t.register=function(e){t.getMap().classNameMap[e.className]=[e,e.fromConfig]},t}();function Lf(t){g(null!=t.className,function(){return\"Class being registered does not have the static className property defined.\"}),g(\"string\"==typeof t.className,function(){return\"className is required to be a string, but got type \"+typeof t.className}),g(t.className.length>0,function(){return\"Class being registered has an empty-string as its className, which is disallowed.\"}),Pf.register(t)}var Wf=Object.freeze({Serializable:Bf,SerializationMap:Pf,registerClass:Lf}),Uf=.001,Vf=.1;function zf(){return 32===Nt.backend.floatPrecision()?Uf:Vf}function Gf(t,e,n){var r=!0;if((B(t)||B(e))&&(r=!1),B(t)&&B(e)&&(r=!0),r){var o=t.constructor.name,a=e.constructor.name;if(o!==a)throw new Error(\"Arrays are of different type. Actual: \"+o+\". Expected: \"+a)}if(Array.isArray(t)&&Array.isArray(e)){var i=un(t),u=un(e);if(!C(i,u))throw new Error(\"Arrays have different shapes. Actual: [\"+i+\"]. Expected: [\"+u+\"]\")}var s=B(t)?t:b(t),c=B(e)?e:b(e);if(s.length!==c.length)throw new Error(\"Arrays have different lengths actual: \"+s.length+\" vs expected: \"+c.length+\".\\nActual:   \"+s+\".\\nExpected: \"+c+\".\");for(var l=0;l<c.length;++l){var h=s[l],f=c[l];if(!n(h,f))throw new Error(\"Arrays differ: actual[\"+l+\"] = \"+h+\", expected[\"+l+\"] = \"+f+\".\\nActual:   \"+s+\".\\nExpected: \"+c+\".\")}}function Hf(t,e,n){return!isFinite(t)&&!isFinite(e)||!(isNaN(t)||isNaN(e)||Math.abs(t-e)>n)}var qf=Object.freeze({TEST_EPSILON_FLOAT16:Vf,expectArraysClose:function(t,e,n){return null==n&&(n=zf()),Gf(t,e,function(t,e){return Hf(t,e,n)})},testEpsilon:zf,expectPromiseToFail:function(t,e){t().then(function(){return e.fail()},function(){return e()})},expectArraysEqual:function(t,e){var n=\"string\"==typeof e||\"number\"==typeof e||\"boolean\"==typeof e?[e]:e;return W(t)||W(t[0])||W(e)||W(e[0])?Gf(t,n,function(t,e){return t==e}):Gf(t,e,function(t,e){return Hf(t,e,0)})},expectNumbersClose:function(t,e,n){if(null==n&&(n=zf()),!Hf(t,e,n))throw new Error(\"Numbers differ: actual === \"+t+\", expected === \"+e)},expectValuesInRange:function(t,e,n){for(var r=0;r<t.length;r++)if(t[r]<e||t[r]>n)throw new Error(\"Value out of range:\"+t[r]+\" low: \"+e+\", high: \"+n)},expectArrayBuffersEqual:function(t,e){expect(new Float32Array(t)).toEqual(new Float32Array(e))}}),Kf=\"1.4.0\";var jf=Object.freeze({gpgpu_util:xi,webgl_util:Be,forceHalfFloat:function(){a().set(\"WEBGL_FORCE_F16_TEXTURES\",!0)},MathBackendWebGL:Pu,setWebGLContext:Wt,GPGPUContext:bi}),Xf=function(t){function o(){return null!==t&&t.apply(this,arguments)||this}return e(o,t),o.prototype.minimize=function(t,e,n){void 0===e&&(e=!1);var r=this.computeGradients(t,n),o=r.value,a=r.grads;if(null!=n){var i=n.map(function(t){return{name:t.name,tensor:a[t.name]}});this.applyGradients(i)}else this.applyGradients(a);return je(a),e?o:(o.dispose(),null)},Object.defineProperty(o.prototype,\"iterations\",{get:function(){return null==this.iterations_&&(this.iterations_=0),this.iterations_},enumerable:!0,configurable:!0}),o.prototype.incrementIterations=function(){this.iterations_=this.iterations+1},o.prototype.computeGradients=function(t,e){return ro(t,e)},o.prototype.dispose=function(){null!=this.iterations_&&je(this.iterations_)},o.prototype.saveIterations=function(){return n(this,void 0,void 0,function(){return r(this,function(t){return null==this.iterations_&&(this.iterations_=0),[2,{name:\"iter\",tensor:Sn(this.iterations_,\"int32\")}]})})},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){return r(this,function(t){throw new Error(\"getWeights() is not implemented for this optimizer yet.\")})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){return r(this,function(t){throw new Error(\"setWeights() is not implemented for this optimizer class 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Vn(o).variable(!1)})}),null==e.accumulatedUpdates[r]&&(e.accumulatedUpdates[r]={originalName:n+\"/accum_var\",variable:Ke(function(){return Vn(o).variable(!1)})});var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var i=e.accumulatedGrads[r].variable,u=e.accumulatedUpdates[r].variable;Ke(function(){var t=i.mul(e.rho).add(a.square().mul(1-e.rho)),n=u.add(e.epsilon).sqrt().div(i.add(e.epsilon).sqrt()).mul(a),r=u.mul(e.rho).add(n.square().mul(1-e.rho));i.assign(t),u.assign(r);var s=n.mul(-e.learningRate).add(o);o.assign(s)})}}),this.incrementIterations()},o.prototype.dispose=function(){null!=this.accumulatedUpdates&&(je(this.accumulatedGrads.map(function(t){return t.variable})),je(this.accumulatedUpdates.map(function(t){return t.variable})))},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){var t;return r(this,function(e){switch(e.label){case 0:return t=this.accumulatedGrads.concat(this.accumulatedUpdates),[4,this.saveIterations()];case 1:return[2,[e.sent()].concat(t.map(function(t){return{name:t.originalName,tensor:t.variable}}))]}})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){var e;return r(this,function(n){switch(n.label){case 0:return[4,this.extractIterations(t)];case 1:return t=n.sent(),e=t.length/2,!1,this.accumulatedGrads=t.slice(0,e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),this.accumulatedUpdates=t.slice(e,2*e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),[2]}})})},o.prototype.getConfig=function(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}},o.fromConfig=function(t,e){return new t(e.learningRate,e.rho,e.epsilon)},o.className=\"Adadelta\",o}(Xf);Lf($f);var Yf=function(t){function o(e,n){void 0===n&&(n=.1);var r=t.call(this)||this;return r.learningRate=e,r.initialAccumulatorValue=n,r.accumulatedGrads=[],r}return e(o,t),o.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var o=Nt.registeredVariables[n];if(null==e.accumulatedGrads[r]){e.accumulatedGrads[r]={originalName:n+\"/accumulator\",variable:Ke(function(){return Pn(o.shape,e.initialAccumulatorValue).variable(!1)})}}var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var i=e.accumulatedGrads[r].variable;Ke(function(){var t=i.add(a.square());i.assign(t);var n=a.div(t.add(Nt.backend.epsilon()).sqrt()).mul(-e.learningRate).add(o);o.assign(n)})}}),this.incrementIterations()},o.prototype.dispose=function(){null!=this.accumulatedGrads&&je(this.accumulatedGrads.map(function(t){return t.variable}))},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){return r(this,function(t){switch(t.label){case 0:return[4,this.saveIterations()];case 1:return[2,[t.sent()].concat(this.accumulatedGrads.map(function(t){return{name:t.originalName,tensor:t.variable}}))]}})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){return r(this,function(e){switch(e.label){case 0:return[4,this.extractIterations(t)];case 1:return t=e.sent(),!1,this.accumulatedGrads=t.map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),[2]}})})},o.prototype.getConfig=function(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}},o.fromConfig=function(t,e){return new t(e.learningRate,e.initialAccumulatorValue)},o.className=\"Adagrad\",o}(Xf);Lf(Yf);var Qf=function(t){function o(e,n,r,o){void 0===o&&(o=null);var a=t.call(this)||this;return a.learningRate=e,a.beta1=n,a.beta2=r,a.epsilon=o,a.accumulatedFirstMoment=[],a.accumulatedSecondMoment=[],Ke(function(){a.accBeta1=Sn(n).variable(),a.accBeta2=Sn(r).variable()}),null==o&&(a.epsilon=Nt.backend.epsilon()),a}return e(o,t),o.prototype.applyGradients=function(t){var e=this,n=Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t);Ke(function(){var r=ac(1,e.accBeta1),o=ac(1,e.accBeta2);n.forEach(function(n,a){var i=Nt.registeredVariables[n];null==e.accumulatedFirstMoment[a]&&(e.accumulatedFirstMoment[a]={originalName:n+\"/m\",variable:Ke(function(){return Vn(i).variable(!1)})}),null==e.accumulatedSecondMoment[a]&&(e.accumulatedSecondMoment[a]={originalName:n+\"/v\",variable:Ke(function(){return Vn(i).variable(!1)})});var u=Array.isArray(t)?t[a].tensor:t[n];if(null!=u){var s=e.accumulatedFirstMoment[a].variable,c=e.accumulatedSecondMoment[a].variable,l=s.mul(e.beta1).add(u.mul(1-e.beta1)),h=c.mul(e.beta2).add(u.square().mul(1-e.beta2)),f=l.div(r),p=h.div(o);s.assign(l),c.assign(h);var d=f.div(p.sqrt().add(e.epsilon)).mul(-e.learningRate).add(i);i.assign(d)}}),e.accBeta1.assign(e.accBeta1.mul(e.beta1)),e.accBeta2.assign(e.accBeta2.mul(e.beta2))}),this.incrementIterations()},o.prototype.dispose=function(){this.accBeta1.dispose(),this.accBeta2.dispose(),null!=this.accumulatedFirstMoment&&je(this.accumulatedFirstMoment.map(function(t){return t.variable})),null!=this.accumulatedSecondMoment&&je(this.accumulatedSecondMoment.map(function(t){return t.variable}))},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){var t;return r(this,function(e){switch(e.label){case 0:return t=this.accumulatedFirstMoment.concat(this.accumulatedSecondMoment),[4,this.saveIterations()];case 1:return[2,[e.sent()].concat(t.map(function(t){return{name:t.originalName,tensor:t.variable}}))]}})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){var e,n=this;return r(this,function(r){switch(r.label){case 0:return[4,this.extractIterations(t)];case 1:return t=r.sent(),Ke(function(){n.accBeta1.assign(ec(n.beta1,n.iterations_+1)),n.accBeta2.assign(ec(n.beta2,n.iterations_+1))}),e=t.length/2,!1,this.accumulatedFirstMoment=t.slice(0,e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),this.accumulatedSecondMoment=t.slice(e,2*e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),[2]}})})},o.prototype.getConfig=function(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}},o.fromConfig=function(t,e){return new t(e.learningRate,e.beta1,e.beta2,e.epsilon)},o.className=\"Adam\",o}(Xf);Lf(Qf);var Jf=function(t){function o(e,n,r,o,a){void 0===o&&(o=null),void 0===a&&(a=0);var i=t.call(this)||this;return i.learningRate=e,i.beta1=n,i.beta2=r,i.epsilon=o,i.decay=a,i.accumulatedFirstMoment=[],i.accumulatedWeightedInfNorm=[],Ke(function(){i.iteration=Sn(0).variable(),i.accBeta1=Sn(n).variable()}),null==o&&(i.epsilon=Nt.backend.epsilon()),i}return e(o,t),o.prototype.applyGradients=function(t){var e=this,n=Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t);Ke(function(){var r=ac(1,e.accBeta1),o=Gs(-e.learningRate,e.iteration.mul(e.decay).add(1));n.forEach(function(n,a){var i=Nt.registeredVariables[n];null==e.accumulatedFirstMoment[a]&&(e.accumulatedFirstMoment[a]={originalName:n+\"/m\",variable:Vn(i).variable(!1)}),null==e.accumulatedWeightedInfNorm[a]&&(e.accumulatedWeightedInfNorm[a]={originalName:n+\"/v\",variable:Vn(i).variable(!1)});var u=Array.isArray(t)?t[a].tensor:t[n];if(null!=u){var s=e.accumulatedFirstMoment[a].variable,c=e.accumulatedWeightedInfNorm[a].variable,l=s.mul(e.beta1).add(u.mul(1-e.beta1)),h=c.mul(e.beta2),f=u.abs(),p=h.maximum(f);s.assign(l),c.assign(p);var d=o.div(r).mul(l.div(p.add(e.epsilon))).add(i);i.assign(d)}}),e.iteration.assign(e.iteration.add(1)),e.accBeta1.assign(e.accBeta1.mul(e.beta1))}),this.incrementIterations()},o.prototype.dispose=function(){this.accBeta1.dispose(),this.iteration.dispose(),null!=this.accumulatedFirstMoment&&je(this.accumulatedFirstMoment.map(function(t){return t.variable})),null!=this.accumulatedWeightedInfNorm&&je(this.accumulatedWeightedInfNorm.map(function(t){return t.variable}))},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){return r(this,function(t){throw new Error(\"getWeights() is not implemented for Adamax yet.\")})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){return r(this,function(t){throw new Error(\"setWeights() is not implemented for Adamax yet.\")})})},o.prototype.getConfig=function(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}},o.fromConfig=function(t,e){return new t(e.learningRate,e.beta1,e.beta2,e.epsilon,e.decay)},o.className=\"Adamax\",o}(Xf);Lf(Jf);var Zf=function(t){function o(e){var n=t.call(this)||this;return n.learningRate=e,n.setLearningRate(e),n}return e(o,t),o.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var o=Array.isArray(t)?t[r].tensor:t[n];if(null!=o){var a=Nt.registeredVariables[n];Ke(function(){var t=e.c.mul(o).add(a);a.assign(t)})}}),this.incrementIterations()},o.prototype.setLearningRate=function(t){this.learningRate=t,null!=this.c&&this.c.dispose(),this.c=Xe(Sn(-t))},o.prototype.dispose=function(){this.c.dispose()},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){return r(this,function(t){switch(t.label){case 0:return[4,this.saveIterations()];case 1:return[2,[t.sent()]]}})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){return r(this,function(e){switch(e.label){case 0:return[4,this.extractIterations(t)];case 1:if(0!==(t=e.sent()).length)throw new Error(\"SGD optimizer does not have settable weights.\");return[2]}})})},o.prototype.getConfig=function(){return{learningRate:this.learningRate}},o.fromConfig=function(t,e){return new t(e.learningRate)},o.className=\"SGD\",o}(Xf);Lf(Zf);var tp=function(t){function o(e,n,r){void 0===r&&(r=!1);var o=t.call(this,e)||this;return o.learningRate=e,o.momentum=n,o.useNesterov=r,o.accumulations=[],o.m=Sn(o.momentum),o}return e(o,t),o.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var o=Nt.registeredVariables[n];if(null==e.accumulations[r]){e.accumulations[r]={originalName:n+\"/momentum\",variable:Ke(function(){return Vn(o).variable(!1)})}}var a=e.accumulations[r].variable,i=Array.isArray(t)?t[r].tensor:t[n];null!=i&&Ke(function(){var t,n=e.m.mul(a).add(i);t=e.useNesterov?e.c.mul(i.add(n.mul(e.m))).add(o):e.c.mul(n).add(o),a.assign(n),o.assign(t)})}),this.incrementIterations()},o.prototype.dispose=function(){this.m.dispose(),null!=this.accumulations&&je(this.accumulations.map(function(t){return t.variable}))},o.prototype.setMomentum=function(t){this.momentum=t},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){return r(this,function(t){switch(t.label){case 0:return[4,this.saveIterations()];case 1:return[2,[t.sent()].concat(this.accumulations.map(function(t){return{name:t.originalName,tensor:t.variable}}))]}})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){return r(this,function(e){switch(e.label){case 0:return[4,this.extractIterations(t)];case 1:return t=e.sent(),!1,this.accumulations=t.map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),[2]}})})},o.prototype.getConfig=function(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}},o.fromConfig=function(t,e){return new t(e.learningRate,e.momentum,e.useNesterov)},o.className=\"Momentum\",o}(Zf);Lf(tp);var ep=function(t){function o(e,n,r,o,a){void 0===n&&(n=.9),void 0===r&&(r=0),void 0===o&&(o=null),void 0===a&&(a=!1);var i=t.call(this)||this;return i.learningRate=e,i.decay=n,i.momentum=r,i.epsilon=o,i.accumulatedMeanSquares=[],i.accumulatedMoments=[],i.accumulatedMeanGrads=[],i.centered=a,null==o&&(i.epsilon=Nt.backend.epsilon()),i}return e(o,t),o.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var o=Nt.registeredVariables[n];null==e.accumulatedMeanSquares[r]&&(e.accumulatedMeanSquares[r]={originalName:n+\"/rms\",variable:Ke(function(){return Vn(o).variable(!1)})}),null==e.accumulatedMoments[r]&&(e.accumulatedMoments[r]={originalName:n+\"/momentum\",variable:Ke(function(){return Vn(o).variable(!1)})}),null==e.accumulatedMeanGrads[r]&&e.centered&&(e.accumulatedMeanGrads[r]={originalName:n+\"/mg\",variable:Ke(function(){return Vn(o).variable(!1)})});var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var i=e.accumulatedMeanSquares[r].variable,u=e.accumulatedMoments[r].variable;Ke(function(){var t=i.mul(e.decay).add(a.square().mul(1-e.decay));if(e.centered){var n=e.accumulatedMeanGrads[r].variable,s=n.mul(e.decay).add(a.mul(1-e.decay)),c=u.mul(e.momentum).add(a.mul(e.learningRate).div(t.sub(s.square().add(e.epsilon)).sqrt()));i.assign(t),n.assign(s),u.assign(c);var l=o.sub(c);o.assign(l)}else{var h=i.mul(e.decay).add(a.square().mul(1-e.decay));c=u.mul(e.momentum).add(a.mul(e.learningRate).div(h.add(e.epsilon).sqrt()));i.assign(h),u.assign(c);l=o.sub(c);o.assign(l)}})}}),this.incrementIterations()},o.prototype.dispose=function(){null!=this.accumulatedMeanSquares&&je(this.accumulatedMeanSquares.map(function(t){return t.variable})),null!=this.accumulatedMeanGrads&&this.centered&&je(this.accumulatedMeanGrads.map(function(t){return t.variable})),null!=this.accumulatedMoments&&je(this.accumulatedMoments.map(function(t){return t.variable}))},o.prototype.getWeights=function(){return n(this,void 0,void 0,function(){var t;return r(this,function(e){switch(e.label){case 0:return t=this.accumulatedMeanSquares.concat(this.accumulatedMoments),this.centered&&t.push.apply(t,this.accumulatedMeanGrads),[4,this.saveIterations()];case 1:return[2,[e.sent()].concat(t.map(function(t){return{name:t.originalName,tensor:t.variable}}))]}})})},o.prototype.setWeights=function(t){return n(this,void 0,void 0,function(){var e;return r(this,function(n){switch(n.label){case 0:return[4,this.extractIterations(t)];case 1:return t=n.sent(),e=this.centered?t.length/3:t.length/2,!1,this.accumulatedMeanSquares=t.slice(0,e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),this.accumulatedMoments=t.slice(e,2*e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),this.centered&&(this.accumulatedMeanGrads=t.slice(2*e,3*e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}})),[2]}})})},o.prototype.getConfig=function(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}},o.fromConfig=function(t,e){return new t(e.learningRate,e.decay,e.momentum,e.epsilon,e.centered)},o.className=\"RMSProp\",o}(Xf);Lf(ep);var np=function(){function t(){}return t.sgd=function(t){return new Zf(t)},t.momentum=function(t,e,n){return void 0===n&&(n=!1),new tp(t,e,n)},t.rmsprop=function(t,e,n,r,o){return void 0===e&&(e=.9),void 0===n&&(n=0),void 0===r&&(r=null),void 0===o&&(o=!1),new ep(t,e,n,r,o)},t.adam=function(t,e,n,r){return void 0===t&&(t=.001),void 0===e&&(e=.9),void 0===n&&(n=.999),void 0===r&&(r=null),new Qf(t,e,n,r)},t.adadelta=function(t,e,n){return void 0===t&&(t=.001),void 0===e&&(e=.95),void 0===n&&(n=null),new $f(t,e,n)},t.adamax=function(t,e,n,r,o){return void 0===t&&(t=.002),void 0===e&&(e=.9),void 0===n&&(n=.999),void 0===r&&(r=null),void 0===o&&(o=0),new Jf(t,e,n,r,o)},t.adagrad=function(t,e){return void 0===e&&(e=.1),new Yf(t,e)},t}(),rp={sgd:np.sgd,momentum:np.momentum,adadelta:np.adadelta,adagrad:np.adagrad,rmsprop:np.rmsprop,adamax:np.adamax,adam:np.adam},op=\"undefined\"!=typeof requestAnimationFrame?requestAnimationFrame:\"undefined\"!=typeof setImmediate?setImmediate:function(t){return t()};function ap(){return new Promise(function(t){return op(function(){return t()})})}ft=Rh;export{$f as AdadeltaOptimizer,Yf as AdagradOptimizer,Qf as AdamOptimizer,Jf as AdamaxOptimizer,so as DataStorage,i as ENV,o as Environment,co as KernelBackend,tp as MomentumOptimizer,Xf as Optimizer,ep as RMSPropOptimizer,vt as Rank,Kl as Reduction,Zf as SGDOptimizer,dt as Tensor,lt as TensorBuffer,bt as Variable,Wu as abs,Uu as acos,Vu as acosh,Ws as add,Us as addN,Vs as addStrict,al as all,il as any,ul as argMax,sl as argMin,zu as asin,Gu as asinh,Hu as atan,zs as atan2,qu as atanh,$c as avgPool,Jc as avgPool3d,rn as backend,To as backend_util,Il as basicLSTMCell,Ds as batchNorm,Ts as batchNorm2d,Ns as batchNorm3d,Fs as batchNorm4d,As as batchNormalization,Is as batchNormalization2d,ks as batchNormalization3d,Ss as batchNormalization4d,sr as batchToSpaceND,Ec as booleanMaskAsync,cr as broadcastTo,Mf as browser,ir as buffer,lr as cast,Ku as ceil,ju as clipByValue,hr as clone,Cn as complex,zn as concat,Gn as concat1d,Hn as concat2d,qn as concat3d,Kn as concat4d,Sc as conv1d,Ac as conv2d,Bc as conv2dTranspose,Dc as conv3d,Pc as conv3dTranspose,Xu as cos,$u as cosh,fr as cumsum,oo as customGrad,Ve as deprecationWarn,pr as depthToSpace,Fc as depthwiseConv2d,Ll as diag,Ue as disableDeprecationWarnings,je as dispose,ze as disposeVariables,Gs as div,Hs as divNoNan,qs as divStrict,Wc as dot,Wl as dropout,ml as elu,We as enableDebugMode,Le as enableProdMode,Ge as engine,a as env,uc as equal,sc as equalStrict,Yu as erf,Qu as exp,dr as expandDims,Ju as expm1,vr as eye,Nl as fft,Pn as fill,tn as findBackend,en as findBackendFactory,Zu as floor,Ks as floorDiv,Gl as frame,Eh as fused,wc as gather,Pl as gatherND,Je as getBackend,s as getKernel,c as getKernelsForBackend,Zr as grad,to as grads,cc as greater,lc as greaterEqual,hc as greaterEqualStrict,fc as greaterStrict,zl as hammingWindow,Vl as hannWindow,Fl as ifft,Rn as imag,vh as image,jl as inTopKAsync,Tf as io,Ol as irfft,hs as isFinite,ls as isInf,cs as isNaN,Xe as keep,gl as leakyRelu,pc as less,dc as lessEqual,vc as lessEqualStrict,mc as lessStrict,sh as linalg,Ln as linspace,El as localResponseNormalization,ts as log,es as log1p,ns as logSigmoid,uo as logSoftmax,cl as logSumExp,_s as logicalAnd,Os as logicalNot,Ms as logicalOr,Bs as logicalXor,rh as losses,Lc as matMul,_f as math,ll as max,Xc as maxPool,Qc as maxPool3d,js as maximum,Xs as maximumStrict,hl as mean,He as memory,fl as min,$s as minimum,Ys as minimumStrict,Qs as mod,Js as modStrict,pl as moments,Sl as movingAverage,Zs as mul,tc as mulStrict,kl as multiRNNCell,mr as multinomial,rs as neg,ap as nextFrame,Rl as norm,gc as notEqual,yc as notEqualStrict,gr as oneHot,Mn as ones,Un as onesLike,wn as op,Uc as outerProduct,yr as pad,xr as pad1d,br as pad2d,wr as pad3d,Cr as pad4d,Yc as pool,ec as pow,nc as powStrict,yl as prelu,ur as print,vl as prod,qe as profile,Er as rand,Ir as randomGamma,Rr as randomNormal,kr as randomUniform,Wn as range,Qe as ready,En as real,os as reciprocal,nn as registerBackend,l as registerKernel,xl as relu,bl as relu6,Ze as removeBackend,Sr as reshape,Vc as reverse,zc as reverse1d,Gc as reverse2d,Hc as reverse3d,qc as reverse4d,_l as rfft,as as round,is as rsqrt,Sn as scalar,Tl as scatterND,wl as selu,Mc as separableConv2d,Wf as serialization,Ye as setBackend,on as setPlatform,Or as setdiff1dAsync,us as sigmoid,ss as sign,ql as signal,fs as sin,ps as sinh,Zc as slice,tl as slice1d,el as slice2d,nl as slice3d,rl as slice4d,Jr as slice_util,io as softmax,ds as softplus,Ar as spaceToBatchND,Bl as sparseToDense,Ml as spectral,jn as split,vs as sqrt,Lu as square,rc as squaredDifference,oc as squaredDifferenceStrict,Dr as squeeze,Tr as stack,ms as step,Hl as stft,Al as stridedSlice,ac as sub,ic as subStrict,dl as sum,gs as tan,ys as tanh,In as tensor,An as tensor1d,Dn as tensor2d,Tn as tensor3d,Nn as tensor4d,Fn as tensor5d,_n as tensor6d,At as tensor_util,qf as test_util,Ke as tidy,Nr as tile,$e as time,Dl as topk,rp as train,Cl as transpose,Fr as truncatedNormal,h as unregisterKernel,Cc as unsortedSegmentSum,_r as unstack,tt as util,eo as valueAndGrad,no as valueAndGrads,On as variable,ro as variableGrads,Kf as version_core,jf as webgl,Ps as where,Ls as whereAsync,Bn as zeros,Vn as zerosLike};\n//# sourceMappingURL=tf-core.esm.js.map\n","import { Point } from '../classes';\r\n\r\nexport function drawContour(\r\n  ctx: CanvasRenderingContext2D,\r\n  points: Point[],\r\n  isClosed: boolean = false\r\n) {\r\n  ctx.beginPath()\r\n\r\n  points.slice(1).forEach(({ x, y }, prevIdx) => {\r\n    const from = points[prevIdx]\r\n    ctx.moveTo(from.x, from.y)\r\n    ctx.lineTo(x, y)\r\n  })\r\n\r\n  if (isClosed) {\r\n    const from = points[points.length - 1]\r\n    const to = points[0]\r\n    if (!from || !to) {\r\n      return\r\n    }\r\n\r\n    ctx.moveTo(from.x, from.y)\r\n    ctx.lineTo(to.x, to.y)\r\n  }\r\n\r\n  ctx.stroke()\r\n}","import { isValidNumber } from '../utils';\r\n\r\nexport interface IDimensions {\r\n  width: number\r\n  height: number\r\n}\r\n\r\nexport class Dimensions implements IDimensions {\r\n\r\n  private _width: number\r\n  private _height: number\r\n\r\n  constructor(width: number, height: number) {\r\n    if (!isValidNumber(width) || !isValidNumber(height)) {\r\n      throw new Error(`Dimensions.constructor - expected width and height to be valid numbers, instead have ${JSON.stringify({ width, height })}`)\r\n    }\r\n\r\n    this._width = width\r\n    this._height = height\r\n  }\r\n\r\n  public get width(): number { return this._width }\r\n  public get height(): number { return this._height }\r\n\r\n  public reverse(): Dimensions {\r\n    return new Dimensions(1 / this.width, 1 / this.height)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Point } from '../classes';\r\nimport { Dimensions, IDimensions } from '../classes/Dimensions';\r\n\r\nexport function isTensor(tensor: any, dim: number) {\r\n  return tensor instanceof tf.Tensor && tensor.shape.length === dim\r\n}\r\n\r\nexport function isTensor1D(tensor: any): tensor is tf.Tensor1D {\r\n  return isTensor(tensor, 1)\r\n}\r\n\r\nexport function isTensor2D(tensor: any): tensor is tf.Tensor2D {\r\n  return isTensor(tensor, 2)\r\n}\r\n\r\nexport function isTensor3D(tensor: any): tensor is tf.Tensor3D {\r\n  return isTensor(tensor, 3)\r\n}\r\n\r\nexport function isTensor4D(tensor: any): tensor is tf.Tensor4D {\r\n  return isTensor(tensor, 4)\r\n}\r\n\r\nexport function isFloat(num: number) {\r\n  return num % 1 !== 0\r\n}\r\n\r\nexport function isEven(num: number) {\r\n  return num % 2 === 0\r\n}\r\n\r\nexport function round(num: number, prec: number = 2) {\r\n  const f = Math.pow(10, prec)\r\n  return Math.floor(num * f) / f\r\n}\r\n\r\nexport function isDimensions(obj: any): boolean {\r\n  return obj && obj.width && obj.height\r\n}\r\n\r\nexport function computeReshapedDimensions({ width, height }: IDimensions, inputSize: number) {\r\n  const scale = inputSize / Math.max(height, width)\r\n  return new Dimensions(Math.round(width * scale), Math.round(height * scale))\r\n}\r\n\r\nexport function getCenterPoint(pts: Point[]): Point {\r\n  return pts.reduce((sum, pt) => sum.add(pt), new Point(0, 0))\r\n    .div(new Point(pts.length, pts.length))\r\n}\r\n\r\nexport function range(num: number, start: number, step: number): number[] {\r\n  return Array(num).fill(0).map((_, i) => start + (i * step))\r\n}\r\n\r\nexport function isValidNumber(num: any) {\r\n  return !!num && num !== Infinity && num !== -Infinity && !isNaN(num) || num === 0\r\n}\r\n\r\nexport function isValidProbablitiy(num: any) {\r\n  return isValidNumber(num) && 0 <= num && num <= 1.0\r\n}","export interface IPoint {\r\n  x: number\r\n  y: number\r\n}\r\n\r\nexport class Point implements IPoint {\r\n  private _x: number\r\n  private _y: number\r\n\r\n  constructor(x: number, y: number) {\r\n    this._x = x\r\n    this._y = y\r\n  }\r\n\r\n  get x(): number { return this._x }\r\n  get y(): number { return this._y }\r\n\r\n  public add(pt: IPoint): Point {\r\n    return new Point(this.x + pt.x, this.y + pt.y)\r\n  }\r\n\r\n  public sub(pt: IPoint): Point {\r\n    return new Point(this.x - pt.x, this.y - pt.y)\r\n  }\r\n\r\n  public mul(pt: IPoint): Point {\r\n    return new Point(this.x * pt.x, this.y * pt.y)\r\n  }\r\n\r\n  public div(pt: IPoint): Point {\r\n    return new Point(this.x / pt.x, this.y / pt.y)\r\n  }\r\n\r\n  public abs(): Point {\r\n    return new Point(Math.abs(this.x), Math.abs(this.y))\r\n  }\r\n\r\n  public magnitude(): number {\r\n    return Math.sqrt(Math.pow(this.x, 2) + Math.pow(this.y, 2))\r\n  }\r\n\r\n  public floor(): Point {\r\n    return new Point(Math.floor(this.x), Math.floor(this.y))\r\n  }\r\n}","import { isDimensions, isValidNumber } from '../utils';\r\nimport { IBoundingBox } from './BoundingBox';\r\nimport { IDimensions } from './Dimensions';\r\nimport { Point } from './Point';\r\nimport { IRect } from './Rect';\r\n\r\nexport class Box<BoxType = any> implements IBoundingBox, IRect {\r\n\r\n  public static isRect(rect: any): boolean {\r\n    return !!rect && [rect.x, rect.y, rect.width, rect.height].every(isValidNumber)\r\n  }\r\n\r\n  public static assertIsValidBox(box: any, callee: string, allowNegativeDimensions: boolean = false) {\r\n    if (!Box.isRect(box)) {\r\n      throw new Error(`${callee} - invalid box: ${JSON.stringify(box)}, expected object with properties x, y, width, height`)\r\n    }\r\n\r\n    if (!allowNegativeDimensions && (box.width < 0 || box.height < 0)) {\r\n      throw new Error(`${callee} - width (${box.width}) and height (${box.height}) must be positive numbers`)\r\n    }\r\n  }\r\n\r\n  private _x: number\r\n  private _y: number\r\n  private _width: number\r\n  private _height: number\r\n\r\n  constructor(_box: IBoundingBox | IRect, allowNegativeDimensions: boolean = true) {\r\n    const box = (_box || {}) as any\r\n\r\n    const isBbox = [box.left, box.top, box.right, box.bottom].every(isValidNumber)\r\n    const isRect = [box.x, box.y, box.width, box.height].every(isValidNumber)\r\n\r\n    if (!isRect && !isBbox) {\r\n      throw new Error(`Box.constructor - expected box to be IBoundingBox | IRect, instead have ${JSON.stringify(box)}`)\r\n    }\r\n\r\n    const [x, y, width, height] = isRect\r\n      ? [box.x, box.y, box.width, box.height]\r\n      : [box.left, box.top, box.right - box.left, box.bottom - box.top]\r\n\r\n    Box.assertIsValidBox({ x, y, width, height }, 'Box.constructor', allowNegativeDimensions)\r\n\r\n    this._x = x\r\n    this._y = y\r\n    this._width = width\r\n    this._height = height\r\n  }\r\n\r\n  public get x(): number { return this._x }\r\n  public get y(): number { return this._y }\r\n  public get width(): number { return this._width }\r\n  public get height(): number { return this._height }\r\n  public get left(): number { return this.x }\r\n  public get top(): number { return this.y }\r\n  public get right(): number { return this.x + this.width }\r\n  public get bottom(): number { return this.y + this.height }\r\n  public get area(): number { return this.width * this.height }\r\n  public get topLeft(): Point { return new Point(this.left, this.top) }\r\n  public get topRight(): Point { return new Point(this.right, this.top) }\r\n  public get bottomLeft(): Point { return new Point(this.left, this.bottom) }\r\n  public get bottomRight(): Point { return new Point(this.right, this.bottom) }\r\n\r\n  public round(): Box<BoxType> {\r\n    const [x, y, width, height] = [this.x, this.y, this.width, this.height]\r\n      .map(val => Math.round(val))\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public floor(): Box<BoxType> {\r\n    const [x, y, width, height] = [this.x, this.y, this.width, this.height]\r\n      .map(val => Math.floor(val))\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public toSquare(): Box<BoxType> {\r\n    let { x, y, width, height } = this\r\n    const diff = Math.abs(width - height)\r\n    if (width < height) {\r\n      x -= (diff / 2)\r\n      width += diff\r\n    }\r\n    if (height < width) {\r\n      y -= (diff / 2)\r\n      height += diff\r\n    }\r\n\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public rescale(s: IDimensions | number): Box<BoxType> {\r\n    const scaleX = isDimensions(s) ? (s as IDimensions).width : s as number\r\n    const scaleY = isDimensions(s) ? (s as IDimensions).height : s as number\r\n    return new Box({\r\n      x: this.x * scaleX,\r\n      y: this.y * scaleY,\r\n      width: this.width * scaleX,\r\n      height: this.height * scaleY\r\n    })\r\n  }\r\n\r\n  public pad(padX: number, padY: number): Box<BoxType> {\r\n    let [x, y, width, height] = [\r\n      this.x - (padX / 2),\r\n      this.y - (padY / 2),\r\n      this.width + padX,\r\n      this.height + padY\r\n    ]\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public clipAtImageBorders(imgWidth: number, imgHeight: number): Box<BoxType> {\r\n    const { x, y, right, bottom } = this\r\n    const clippedX = Math.max(x, 0)\r\n    const clippedY = Math.max(y, 0)\r\n\r\n    const newWidth = right - clippedX\r\n    const newHeight = bottom - clippedY\r\n    const clippedWidth = Math.min(newWidth, imgWidth - clippedX)\r\n    const clippedHeight = Math.min(newHeight, imgHeight - clippedY)\r\n\r\n    return (new Box({ x: clippedX, y: clippedY, width: clippedWidth, height: clippedHeight})).floor()\r\n  }\r\n\r\n  public shift(sx: number, sy: number): Box<BoxType> {\r\n    const { width, height } = this\r\n    const x = this.x + sx\r\n    const y = this.y + sy\r\n\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public padAtBorders(imageHeight: number, imageWidth: number) {\r\n    const w = this.width + 1\r\n    const h = this.height + 1\r\n\r\n    let dx = 1\r\n    let dy = 1\r\n    let edx = w\r\n    let edy = h\r\n\r\n    let x = this.left\r\n    let y = this.top\r\n    let ex = this.right\r\n    let ey = this.bottom\r\n\r\n    if (ex > imageWidth) {\r\n      edx = -ex + imageWidth + w\r\n      ex = imageWidth\r\n    }\r\n    if (ey > imageHeight) {\r\n      edy = -ey + imageHeight + h\r\n      ey = imageHeight\r\n    }\r\n    if (x < 1) {\r\n      edy = 2 - x\r\n      x = 1\r\n    }\r\n    if (y < 1) {\r\n      edy = 2 - y\r\n      y = 1\r\n    }\r\n\r\n    return { dy, edy, dx, edx, y, ey, x, ex, w, h }\r\n  }\r\n\r\n  public calibrate(region: Box) {\r\n    return new Box({\r\n      left: this.left + (region.left * this.width),\r\n      top: this.top + (region.top * this.height),\r\n      right: this.right + (region.right * this.width),\r\n      bottom: this.bottom + (region.bottom * this.height)\r\n    }).toSquare().round()\r\n  }\r\n}","import { Box } from './Box';\r\n\r\nexport interface IBoundingBox {\r\n  left: number\r\n  top: number\r\n  right: number\r\n  bottom: number\r\n}\r\n\r\nexport class BoundingBox extends Box<BoundingBox> implements IBoundingBox {\r\n  constructor(left: number, top: number, right: number, bottom: number, allowNegativeDimensions: boolean = false) {\r\n    super({ left, top, right, bottom }, allowNegativeDimensions)\r\n  }\r\n}","import { Box } from './Box';\r\nimport { Dimensions, IDimensions } from './Dimensions';\r\nimport { IRect, Rect } from './Rect';\r\n\r\nexport class ObjectDetection {\r\n  private _score: number\r\n  private _classScore: number\r\n  private _className: string\r\n  private _box: Rect\r\n  private _imageDims: Dimensions\r\n\r\n  constructor(\r\n    score: number,\r\n    classScore: number,\r\n    className: string,\r\n    relativeBox: IRect,\r\n    imageDims: IDimensions\r\n  ) {\r\n    this._imageDims = new Dimensions(imageDims.width, imageDims.height)\r\n    this._score = score\r\n    this._classScore = classScore\r\n    this._className = className\r\n    this._box = new Box(relativeBox).rescale(this._imageDims)\r\n  }\r\n\r\n  public get score(): number { return this._score }\r\n  public get classScore(): number { return this._classScore }\r\n  public get className(): string { return this._className }\r\n  public get box(): Box { return this._box }\r\n  public get imageDims(): Dimensions { return this._imageDims }\r\n  public get imageWidth(): number { return this.imageDims.width }\r\n  public get imageHeight(): number { return this.imageDims.height }\r\n  public get relativeBox(): Box { return new Box(this._box).rescale(this.imageDims.reverse()) }\r\n\r\n  public forSize(width: number, height: number): ObjectDetection {\r\n    return new ObjectDetection(\r\n      this.score,\r\n      this.classScore,\r\n      this.className,\r\n      this.relativeBox,\r\n      { width, height}\r\n    )\r\n  }\r\n}","import { Box } from './Box';\r\nimport { IDimensions } from './Dimensions';\r\nimport { ObjectDetection } from './ObjectDetection';\r\nimport { Rect } from './Rect';\r\n\r\nexport interface IFaceDetecion {\r\n  score: number\r\n  box: Box\r\n}\r\n\r\nexport class FaceDetection extends ObjectDetection implements IFaceDetecion {\r\n  constructor(\r\n    score: number,\r\n    relativeBox: Rect,\r\n    imageDims: IDimensions\r\n  ) {\r\n    super(score, score, '', relativeBox, imageDims)\r\n  }\r\n\r\n  public forSize(width: number, height: number): FaceDetection {\r\n    const { score, relativeBox, imageDims } = super.forSize(width, height)\r\n    return new FaceDetection(score, relativeBox, imageDims)\r\n  }\r\n}","import { Box } from '../classes/Box';\r\n\r\nexport function iou(box1: Box, box2: Box, isIOU: boolean = true) {\r\n  const width = Math.max(0.0, Math.min(box1.right, box2.right) - Math.max(box1.left, box2.left))\r\n  const height = Math.max(0.0, Math.min(box1.bottom, box2.bottom) - Math.max(box1.top, box2.top))\r\n  const interSection = width * height\r\n\r\n  return isIOU\r\n    ? interSection / (box1.area + box2.area - interSection)\r\n    : interSection / Math.min(box1.area, box2.area)\r\n}","import { BoundingBox, IPoint } from '../classes';\r\n\r\nexport function minBbox(pts: IPoint[]): BoundingBox {\r\n  const xs = pts.map(pt => pt.x)\r\n  const ys = pts.map(pt => pt.y)\r\n  const minX = xs.reduce((min, x) => x < min ? x : min, Infinity)\r\n  const minY = ys.reduce((min, y) => y < min ? y : min, Infinity)\r\n  const maxX = xs.reduce((max, x) => max < x ? x : max, 0)\r\n  const maxY = ys.reduce((max, y) => max < y ? y : max, 0)\r\n\r\n  return new BoundingBox(minX, minY, maxX, maxY)\r\n}\r\n","import { Box } from '../classes/Box';\r\nimport { iou } from './iou';\r\n\r\nexport function nonMaxSuppression(\r\n  boxes: Box[],\r\n  scores: number[],\r\n  iouThreshold: number,\r\n  isIOU: boolean = true\r\n): number[] {\r\n\r\n  let indicesSortedByScore = scores\r\n    .map((score, boxIndex) => ({ score, boxIndex }))\r\n    .sort((c1, c2) => c1.score - c2.score)\r\n    .map(c => c.boxIndex)\r\n\r\n  const pick: number[] = []\r\n\r\n  while(indicesSortedByScore.length > 0) {\r\n    const curr = indicesSortedByScore.pop() as number\r\n    pick.push(curr)\r\n\r\n    const indices = indicesSortedByScore\r\n\r\n    const outputs: number[] = []\r\n    for (let i = 0; i < indices.length; i++) {\r\n      const idx = indices[i]\r\n\r\n      const currBox = boxes[curr]\r\n      const idxBox = boxes[idx]\r\n\r\n      outputs.push(iou(currBox, idxBox, isIOU))\r\n    }\r\n\r\n    indicesSortedByScore = indicesSortedByScore.filter(\r\n      (_, j) => outputs[j] <= iouThreshold\r\n    )\r\n  }\r\n\r\n  return pick\r\n\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function normalize(x: tf.Tensor4D, meanRgb: number[]): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const [r, g, b] = meanRgb\r\n    const avg_r = tf.fill([...x.shape.slice(0, 3), 1], r)\r\n    const avg_g = tf.fill([...x.shape.slice(0, 3), 1], g)\r\n    const avg_b = tf.fill([...x.shape.slice(0, 3), 1], b)\r\n    const avg_rgb = tf.concat([avg_r, avg_g, avg_b], 3)\r\n\r\n    return tf.sub(x, avg_rgb)\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\n/**\r\n * Pads the smaller dimension of an image tensor with zeros, such that width === height.\r\n *\r\n * @param imgTensor The image tensor.\r\n * @param isCenterImage (optional, default: false) If true, add an equal amount of padding on\r\n * both sides of the minor dimension oof the image.\r\n * @returns The padded tensor with width === height.\r\n */\r\nexport function padToSquare(\r\n  imgTensor: tf.Tensor4D,\r\n  isCenterImage: boolean = false\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n\r\n    const [height, width] = imgTensor.shape.slice(1)\r\n    if (height === width) {\r\n      return imgTensor\r\n    }\r\n\r\n    const dimDiff = Math.abs(height - width)\r\n    const paddingAmount = Math.round(dimDiff * (isCenterImage ? 0.5 : 1))\r\n    const paddingAxis = height > width ? 2 : 1\r\n\r\n    const createPaddingTensor = (paddingAmount: number): tf.Tensor => {\r\n      const paddingTensorShape = imgTensor.shape.slice()\r\n      paddingTensorShape[paddingAxis] = paddingAmount\r\n      return tf.fill(paddingTensorShape, 0)\r\n    }\r\n\r\n    const paddingTensorAppend = createPaddingTensor(paddingAmount)\r\n    const remainingPaddingAmount = dimDiff - (paddingTensorAppend.shape[paddingAxis] as number)\r\n\r\n    const paddingTensorPrepend = isCenterImage && remainingPaddingAmount\r\n      ? createPaddingTensor(remainingPaddingAmount)\r\n      : null\r\n\r\n    const tensorsToStack = [\r\n      paddingTensorPrepend,\r\n      imgTensor,\r\n      paddingTensorAppend\r\n    ]\r\n      .filter(t => !!t)\r\n      .map((t: tf.Tensor) => t.toFloat()) as tf.Tensor4D[]\r\n    return tf.concat(tensorsToStack, paddingAxis)\r\n  })\r\n}","export function shuffleArray(inputArray: any[]) {\r\n  const array = inputArray.slice()\r\n  for (let i = array.length - 1; i > 0; i--) {\r\n      const j = Math.floor(Math.random() * (i + 1))\r\n      const x = array[i]\r\n      array[i] = array[j]\r\n      array[j] = x\r\n  }\r\n  return array\r\n}","export * from './iou'\r\nexport * from './minBbox'\r\nexport * from './nonMaxSuppression'\r\nexport * from './normalize'\r\nexport * from './padToSquare'\r\nexport * from './shuffleArray'\r\n\r\nexport function sigmoid(x: number) {\r\n  return 1 / (1 + Math.exp(-x))\r\n}\r\n\r\nexport function inverseSigmoid(x: number) {\r\n  return Math.log(x / (1 - x))\r\n}","import { Box } from './Box';\r\n\r\nexport interface IRect {\r\n  x: number\r\n  y: number\r\n  width: number\r\n  height: number\r\n}\r\n\r\nexport class Rect extends Box<Rect> implements IRect {\r\n  constructor(x: number, y: number, width: number, height: number, allowNegativeDimensions: boolean = false) {\r\n    super({ x, y, width, height }, allowNegativeDimensions)\r\n  }\r\n}","import { minBbox } from '../ops';\r\nimport { getCenterPoint } from '../utils';\r\nimport { IBoundingBox } from './BoundingBox';\r\nimport { Box } from './Box';\r\nimport { Dimensions, IDimensions } from './Dimensions';\r\nimport { FaceDetection } from './FaceDetection';\r\nimport { Point } from './Point';\r\nimport { IRect, Rect } from './Rect';\r\n\r\n// face alignment constants\r\nconst relX = 0.5\r\nconst relY = 0.43\r\nconst relScale = 0.45\r\n\r\nexport interface IFaceLandmarks {\r\n  positions: Point[]\r\n  shift: Point\r\n}\r\n\r\nexport class FaceLandmarks implements IFaceLandmarks {\r\n  protected _shift: Point\r\n  protected _positions: Point[]\r\n  protected _imgDims: Dimensions\r\n\r\n  constructor(\r\n    relativeFaceLandmarkPositions: Point[],\r\n    imgDims: IDimensions,\r\n    shift: Point = new Point(0, 0)\r\n  ) {\r\n    const { width, height } = imgDims\r\n    this._imgDims = new Dimensions(width, height)\r\n    this._shift = shift\r\n    this._positions = relativeFaceLandmarkPositions.map(\r\n      pt => pt.mul(new Point(width, height)).add(shift)\r\n    )\r\n  }\r\n\r\n  public get shift(): Point { return new Point(this._shift.x, this._shift.y) }\r\n  public get imageWidth(): number { return this._imgDims.width }\r\n  public get imageHeight(): number { return this._imgDims.height }\r\n  public get positions(): Point[] { return this._positions }\r\n  public get relativePositions(): Point[] {\r\n    return this._positions.map(\r\n      pt => pt.sub(this._shift).div(new Point(this.imageWidth, this.imageHeight))\r\n    )\r\n  }\r\n\r\n  public forSize<T extends FaceLandmarks>(width: number, height: number): T {\r\n    return new (this.constructor as any)(\r\n      this.relativePositions,\r\n      { width, height }\r\n    )\r\n  }\r\n\r\n  public shiftBy<T extends FaceLandmarks>(x: number, y: number): T {\r\n    return new (this.constructor as any)(\r\n      this.relativePositions,\r\n      this._imgDims,\r\n      new Point(x, y)\r\n    )\r\n  }\r\n\r\n  public shiftByPoint<T extends FaceLandmarks>(pt: Point): T {\r\n    return this.shiftBy(pt.x, pt.y)\r\n  }\r\n\r\n  /**\r\n   * Aligns the face landmarks after face detection from the relative positions of the faces\r\n   * bounding box, or it's current shift. This function should be used to align the face images\r\n   * after face detection has been performed, before they are passed to the face recognition net.\r\n   * This will make the computed face descriptor more accurate.\r\n   *\r\n   * @param detection (optional) The bounding box of the face or the face detection result. If\r\n   * no argument was passed the position of the face landmarks are assumed to be relative to\r\n   * it's current shift.\r\n   * @returns The bounding box of the aligned face.\r\n   */\r\n  public align(\r\n    detection?: FaceDetection | IRect | IBoundingBox | null,\r\n    options: { useDlibAlignment?: boolean, minBoxPadding?: number } = { }\r\n  ): Box {\r\n    if (detection) {\r\n      const box = detection instanceof FaceDetection\r\n        ? detection.box.floor()\r\n        : new Box(detection)\r\n\r\n      return this.shiftBy(box.x, box.y).align(null, options)\r\n    }\r\n\r\n    const { useDlibAlignment, minBoxPadding } = Object.assign({}, { useDlibAlignment: false, minBoxPadding: 0.2 }, options)\r\n\r\n    if (useDlibAlignment) {\r\n      return this.alignDlib()\r\n    }\r\n\r\n    return this.alignMinBbox(minBoxPadding)\r\n  }\r\n\r\n  private alignDlib(): Box {\r\n\r\n    const centers = this.getRefPointsForAlignment()\r\n\r\n    const [leftEyeCenter, rightEyeCenter, mouthCenter] = centers\r\n    const distToMouth = (pt: Point) => mouthCenter.sub(pt).magnitude()\r\n    const eyeToMouthDist = (distToMouth(leftEyeCenter) + distToMouth(rightEyeCenter)) / 2\r\n\r\n    const size = Math.floor(eyeToMouthDist / relScale)\r\n\r\n    const refPoint = getCenterPoint(centers)\r\n    // TODO: pad in case rectangle is out of image bounds\r\n    const x = Math.floor(Math.max(0, refPoint.x - (relX * size)))\r\n    const y = Math.floor(Math.max(0, refPoint.y - (relY * size)))\r\n\r\n    return new Rect(x, y, Math.min(size, this.imageWidth + x), Math.min(size, this.imageHeight + y))\r\n  }\r\n\r\n  private alignMinBbox(padding: number): Box {\r\n    const box = minBbox(this.positions)\r\n    return box.pad(box.width * padding, box.height * padding)\r\n  }\r\n\r\n  protected getRefPointsForAlignment(): Point[] {\r\n    throw new Error('getRefPointsForAlignment not implemented by base class')\r\n  }\r\n}","import { getCenterPoint } from '../utils';\r\nimport { FaceLandmarks } from './FaceLandmarks';\r\nimport { Point } from './Point';\r\n\r\n\r\nexport class FaceLandmarks5 extends FaceLandmarks {\r\n\r\n  protected getRefPointsForAlignment(): Point[] {\r\n    const pts = this.positions\r\n    return [\r\n      pts[0],\r\n      pts[1],\r\n      getCenterPoint([pts[3], pts[4]])\r\n    ]\r\n  }\r\n}","import { getCenterPoint } from '../utils';\r\nimport { FaceLandmarks } from './FaceLandmarks';\r\nimport { Point } from './Point';\r\n\r\nexport class FaceLandmarks68 extends FaceLandmarks {\r\n  public getJawOutline(): Point[] {\r\n    return this.positions.slice(0, 17)\r\n  }\r\n\r\n  public getLeftEyeBrow(): Point[] {\r\n    return this.positions.slice(17, 22)\r\n  }\r\n\r\n  public getRightEyeBrow(): Point[] {\r\n    return this.positions.slice(22, 27)\r\n  }\r\n\r\n  public getNose(): Point[] {\r\n    return this.positions.slice(27, 36)\r\n  }\r\n\r\n  public getLeftEye(): Point[] {\r\n    return this.positions.slice(36, 42)\r\n  }\r\n\r\n  public getRightEye(): Point[] {\r\n    return this.positions.slice(42, 48)\r\n  }\r\n\r\n  public getMouth(): Point[] {\r\n    return this.positions.slice(48, 68)\r\n  }\r\n\r\n  protected getRefPointsForAlignment(): Point[] {\r\n    return [\r\n      this.getLeftEye(),\r\n      this.getRightEye(),\r\n      this.getMouth()\r\n    ].map(getCenterPoint)\r\n  }\r\n}","import { round } from '../utils';\r\n\r\nexport interface IFaceMatch {\r\n  label: string\r\n  distance: number\r\n}\r\n\r\nexport class FaceMatch implements IFaceMatch {\r\n  private _label: string\r\n  private _distance: number\r\n\r\n  constructor(label: string, distance: number) {\r\n    this._label = label\r\n    this._distance = distance\r\n  }\r\n\r\n  public get label(): string { return this._label }\r\n  public get distance(): number { return this._distance }\r\n\r\n  public toString(withDistance: boolean = true): string {\r\n    return `${this.label}${withDistance ? ` (${round(this.distance)})` : ''}`\r\n  }\r\n}","import { isValidNumber } from '../utils';\r\nimport { IBoundingBox } from './BoundingBox';\r\nimport { Box } from './Box';\r\nimport { IRect } from './Rect';\r\n\r\nexport class LabeledBox extends Box<LabeledBox> {\r\n\r\n  public static assertIsValidLabeledBox(box: any, callee: string) {\r\n    Box.assertIsValidBox(box, callee)\r\n\r\n    if (!isValidNumber(box.label)) {\r\n      throw new Error(`${callee} - expected property label (${box.label}) to be a number`)\r\n    }\r\n  }\r\n\r\n  private _label: number\r\n\r\n  constructor(box: IBoundingBox | IRect | any, label: number) {\r\n    super(box)\r\n    this._label = label\r\n  }\r\n\r\n  public get label(): number { return this._label }\r\n\r\n}","export class LabeledFaceDescriptors {\r\n  private _label: string\r\n  private _descriptors: Float32Array[]\r\n\r\n  constructor(label: string, descriptors: Float32Array[]) {\r\n    if (!(typeof label === 'string')) {\r\n      throw new Error('LabeledFaceDescriptors - constructor expected label to be a string')\r\n    }\r\n\r\n    if (!Array.isArray(descriptors) || descriptors.some(desc => !(desc instanceof Float32Array))) {\r\n      throw new Error('LabeledFaceDescriptors - constructor expected descriptors to be an array of Float32Array')\r\n    }\r\n\r\n    this._label = label\r\n    this._descriptors = descriptors\r\n  }\r\n\r\n  public get label(): string { return this._label }\r\n  public get descriptors(): Float32Array[] { return this._descriptors }\r\n\r\n  public toJSON(): any {\r\n    return {\r\n      label: this.label,\r\n      descriptors: this.descriptors.map((d) => Array.from(d))\r\n    };\r\n  }\r\n\r\n  public static fromJSON(json: any): LabeledFaceDescriptors {\r\n    const descriptors = json.descriptors.map((d: any) => {\r\n      return new Float32Array(d);\r\n    });\r\n    return new LabeledFaceDescriptors(json.label, descriptors);\r\n  }\r\n\r\n}","import { isValidProbablitiy } from '../utils';\r\nimport { IBoundingBox } from './BoundingBox';\r\nimport { LabeledBox } from './LabeledBox';\r\nimport { IRect } from './Rect';\r\n\r\nexport class PredictedBox extends LabeledBox {\r\n\r\n  public static assertIsValidPredictedBox(box: any, callee: string) {\r\n    LabeledBox.assertIsValidLabeledBox(box, callee)\r\n\r\n    if (\r\n      !isValidProbablitiy(box.score)\r\n      || !isValidProbablitiy(box.classScore)\r\n    ) {\r\n      throw new Error(`${callee} - expected properties score (${box.score}) and (${box.classScore}) to be a number between [0, 1]`)\r\n    }\r\n  }\r\n\r\n  private _score: number\r\n  private _classScore: number\r\n\r\n  constructor(box: IBoundingBox | IRect | any, label: number, score: number, classScore: number) {\r\n    super(box, label)\r\n    this._score = score\r\n    this._classScore = classScore\r\n  }\r\n\r\n  public get score(): number { return this._score }\r\n  public get classScore(): number { return this._classScore }\r\n\r\n}","import { FaceDetection } from '../classes/FaceDetection';\r\n\r\nexport type WithFaceDetection<TSource> = TSource & {\r\n  detection: FaceDetection\r\n}\r\n\r\nexport function isWithFaceDetection(obj: any): obj is WithFaceDetection<{}> {\r\n  return obj['detection'] instanceof FaceDetection\r\n}\r\n\r\nexport function extendWithFaceDetection<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  detection: FaceDetection\r\n): WithFaceDetection<TSource> {\r\n\r\n  const extension = { detection }\r\n  return Object.assign({}, sourceObj, extension)\r\n}\r\n","import { Environment } from './types';\r\n\r\nexport function createBrowserEnv(): Environment {\r\n\r\n  const fetch = window['fetch'] || function() {\r\n    throw new Error('fetch - missing fetch implementation for browser environment')\r\n  }\r\n\r\n  const readFile = function() {\r\n    throw new Error('readFile - filesystem not available for browser environment')\r\n  }\r\n\r\n  return {\r\n    Canvas: HTMLCanvasElement,\r\n    CanvasRenderingContext2D: CanvasRenderingContext2D,\r\n    Image: HTMLImageElement,\r\n    ImageData: ImageData,\r\n    Video: HTMLVideoElement,\r\n    createCanvasElement: () => document.createElement('canvas'),\r\n    createImageElement: () => document.createElement('img'),\r\n    fetch,\r\n    readFile\r\n  }\r\n}","import { FileSystem } from './types';\r\n\r\nexport function createFileSystem(fs?: any): FileSystem {\r\n\r\n  let requireFsError = ''\r\n\r\n  if (!fs) {\r\n    try {\r\n      fs = require('fs')\r\n    } catch (err) {\r\n      requireFsError = err.toString()\r\n    }\r\n  }\r\n\r\n  const readFile = fs\r\n    ? function(filePath: string) {\r\n      return new Promise<Buffer>((res, rej) => {\r\n        fs.readFile(filePath, function(err: any, buffer: Buffer) {\r\n          return err ? rej(err) : res(buffer)\r\n        })\r\n      })\r\n    }\r\n    : function() {\r\n      throw new Error(`readFile - failed to require fs in nodejs environment with error: ${requireFsError}`)\r\n    }\r\n\r\n  return {\r\n    readFile\r\n  }\r\n}","import { createFileSystem } from './createFileSystem';\r\nimport { Environment } from './types';\r\n\r\nexport function createNodejsEnv(): Environment {\r\n\r\n  const Canvas = global['Canvas'] || global['HTMLCanvasElement']\r\n  const Image = global['Image'] || global['HTMLImageElement']\r\n\r\n  const createCanvasElement = function() {\r\n    if (Canvas) {\r\n      return new Canvas()\r\n    }\r\n    throw new Error('createCanvasElement - missing Canvas implementation for nodejs environment')\r\n  }\r\n\r\n  const createImageElement = function() {\r\n    if (Image) {\r\n      return new Image()\r\n    }\r\n    throw new Error('createImageElement - missing Image implementation for nodejs environment')\r\n  }\r\n\r\n  const fetch = global['fetch'] || function() {\r\n    throw new Error('fetch - missing fetch implementation for nodejs environment')\r\n  }\r\n\r\n  const fileSystem = createFileSystem()\r\n\r\n  return {\r\n    Canvas: Canvas || class {},\r\n    CanvasRenderingContext2D: global['CanvasRenderingContext2D'] || class {},\r\n    Image: Image || class {},\r\n    ImageData: global['ImageData'] || class {},\r\n    Video: global['HTMLVideoElement'] || class {},\r\n    createCanvasElement,\r\n    createImageElement,\r\n    fetch,\r\n    ...fileSystem\r\n  }\r\n}","export function isBrowser(): boolean {\r\n  return typeof window === 'object'\r\n    && typeof document !== 'undefined'\r\n    && typeof HTMLImageElement !== 'undefined'\r\n    && typeof HTMLCanvasElement !== 'undefined'\r\n    && typeof HTMLVideoElement !== 'undefined'\r\n    && typeof ImageData !== 'undefined'\r\n    && typeof CanvasRenderingContext2D !== 'undefined'\r\n}","export function isNodejs(): boolean {\r\n  return typeof global === 'object'\r\n    && typeof require === 'function'\r\n    && typeof module !== 'undefined'\r\n    // issues with gatsby.js: module.exports is undefined\r\n    // && !!module.exports\r\n    && typeof process !== 'undefined' && !!process.version\r\n}","import { createBrowserEnv } from './createBrowserEnv';\r\nimport { createFileSystem } from './createFileSystem';\r\nimport { createNodejsEnv } from './createNodejsEnv';\r\nimport { isBrowser } from './isBrowser';\r\nimport { isNodejs } from './isNodejs';\r\nimport { Environment } from './types';\r\n\r\nlet environment: Environment | null\r\n\r\nfunction getEnv(): Environment {\r\n  if (!environment) {\r\n    throw new Error('getEnv - environment is not defined, check isNodejs() and isBrowser()')\r\n  }\r\n  return environment\r\n}\r\n\r\nfunction setEnv(env: Environment) {\r\n  environment = env\r\n}\r\n\r\nfunction initialize() {\r\n  // check for isBrowser() first to prevent electron renderer process\r\n  // to be initialized with wrong environment due to isNodejs() returning true\r\n  if (isBrowser()) {\r\n    setEnv(createBrowserEnv())\r\n  }\r\n  if (isNodejs()) {\r\n    setEnv(createNodejsEnv())\r\n  }\r\n}\r\n\r\nfunction monkeyPatch(env: Partial<Environment>) {\r\n  if (!environment) {\r\n    initialize()\r\n  }\r\n\r\n  if (!environment) {\r\n    throw new Error('monkeyPatch - environment is not defined, check isNodejs() and isBrowser()')\r\n  }\r\n\r\n  const { Canvas = environment.Canvas, Image = environment.Image } = env\r\n  environment.Canvas = Canvas\r\n  environment.Image = Image\r\n  environment.createCanvasElement = env.createCanvasElement || (() => new Canvas())\r\n  environment.createImageElement = env.createImageElement || (() => new Image())\r\n\r\n  environment.ImageData = env.ImageData || environment.ImageData\r\n  environment.Video = env.Video || environment.Video\r\n  environment.fetch = env.fetch || environment.fetch\r\n  environment.readFile = env.readFile || environment.readFile\r\n}\r\n\r\nexport const env = {\r\n  getEnv,\r\n  setEnv,\r\n  initialize,\r\n  createBrowserEnv,\r\n  createFileSystem,\r\n  createNodejsEnv,\r\n  monkeyPatch,\r\n  isBrowser,\r\n  isNodejs\r\n}\r\n\r\ninitialize()\r\n\r\nexport * from './types'\r\n","import { env } from '../env';\r\n\r\nexport function resolveInput(arg: string | any) {\r\n  if (!env.isNodejs() && typeof arg === 'string') {\r\n    return document.getElementById(arg)\r\n  }\r\n  return arg\r\n}","import { env } from '../env';\r\nimport { resolveInput } from './resolveInput';\r\n\r\nexport function getContext2dOrThrow(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D): CanvasRenderingContext2D {\r\n\r\n  const { Canvas, CanvasRenderingContext2D } = env.getEnv()\r\n\r\n  if (canvasArg instanceof CanvasRenderingContext2D) {\r\n    return canvasArg\r\n  }\r\n\r\n  const canvas = resolveInput(canvasArg)\r\n\r\n  if (!(canvas instanceof Canvas)) {\r\n    throw new Error('resolveContext2d - expected canvas to be of instance of Canvas')\r\n  }\r\n\r\n  const ctx = canvas.getContext('2d')\r\n  if (!ctx) {\r\n    throw new Error('resolveContext2d - canvas 2d context is null')\r\n  }\r\n\r\n  return ctx\r\n}","import { IDimensions, IPoint } from '../classes';\r\nimport { getContext2dOrThrow } from '../dom/getContext2dOrThrow';\r\nimport { resolveInput } from '../dom/resolveInput';\r\n\r\nexport enum AnchorPosition {\r\n  TOP_LEFT = 'TOP_LEFT',\r\n  TOP_RIGHT = 'TOP_RIGHT',\r\n  BOTTOM_LEFT = 'BOTTOM_LEFT',\r\n  BOTTOM_RIGHT = 'BOTTOM_RIGHT'\r\n}\r\n\r\nexport interface IDrawTextFieldOptions {\r\n  anchorPosition?: AnchorPosition\r\n  backgroundColor?: string\r\n  fontColor?: string\r\n  fontSize?: number\r\n  fontStyle?: string\r\n  padding?: number\r\n}\r\n\r\nexport class DrawTextFieldOptions implements IDrawTextFieldOptions {\r\n  public anchorPosition: AnchorPosition\r\n  public backgroundColor: string\r\n  public fontColor: string\r\n  public fontSize: number\r\n  public fontStyle: string\r\n  public padding: number\r\n\r\n  constructor(options: IDrawTextFieldOptions = {}) {\r\n    const { anchorPosition, backgroundColor, fontColor, fontSize, fontStyle, padding } = options\r\n    this.anchorPosition = anchorPosition || AnchorPosition.TOP_LEFT\r\n    this.backgroundColor = backgroundColor || 'rgba(0, 0, 0, 0.5)'\r\n    this.fontColor = fontColor || 'rgba(255, 255, 255, 1)'\r\n    this.fontSize = fontSize || 14\r\n    this.fontStyle = fontStyle || 'Georgia'\r\n    this.padding = padding || 4\r\n  }\r\n}\r\n\r\nexport class DrawTextField {\r\n  public text: string[]\r\n  public anchor : IPoint\r\n  public options: DrawTextFieldOptions\r\n\r\n  constructor(\r\n    text: string | string[] | DrawTextField,\r\n    anchor: IPoint,\r\n    options: IDrawTextFieldOptions = {}\r\n  ) {\r\n    this.text = typeof text === 'string'\r\n      ? [text]\r\n      : (text instanceof DrawTextField ? text.text : text)\r\n    this.anchor = anchor\r\n    this.options = new DrawTextFieldOptions(options)\r\n  }\r\n\r\n  measureWidth(ctx: CanvasRenderingContext2D): number {\r\n    const { padding } = this.options\r\n    return this.text.map(l => ctx.measureText(l).width).reduce((w0, w1) => w0 < w1 ? w1 : w0, 0) + (2 * padding)\r\n  }\r\n\r\n  measureHeight(): number {\r\n    const { fontSize, padding } = this.options\r\n    return this.text.length * fontSize + (2 * padding)\r\n  }\r\n\r\n  getUpperLeft(ctx: CanvasRenderingContext2D, canvasDims?: IDimensions): IPoint {\r\n    const { anchorPosition } = this.options\r\n    const isShiftLeft = anchorPosition === AnchorPosition.BOTTOM_RIGHT || anchorPosition === AnchorPosition.TOP_RIGHT\r\n    const isShiftTop = anchorPosition === AnchorPosition.BOTTOM_LEFT || anchorPosition === AnchorPosition.BOTTOM_RIGHT\r\n\r\n    const textFieldWidth = this.measureWidth(ctx)\r\n    const textFieldHeight = this.measureHeight()\r\n    const x = (isShiftLeft ? this.anchor.x - textFieldWidth : this.anchor.x)\r\n    const y = isShiftTop ? this.anchor.y - textFieldHeight : this.anchor.y\r\n\r\n    // adjust anchor if text box exceeds canvas borders\r\n    if (canvasDims) {\r\n      const { width, height } = canvasDims\r\n      const newX = Math.max(Math.min(x, width - textFieldWidth), 0)\r\n      const newY = Math.max(Math.min(y, height - textFieldHeight), 0)\r\n      return { x: newX, y: newY }\r\n    }\r\n    return { x, y }\r\n  }\r\n\r\n  draw(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D) {\r\n    const canvas = resolveInput(canvasArg)\r\n    const ctx = getContext2dOrThrow(canvas)\r\n\r\n    const { backgroundColor, fontColor, fontSize, fontStyle, padding } = this.options\r\n\r\n    ctx.font = `${fontSize}px ${fontStyle}`\r\n    const maxTextWidth = this.measureWidth(ctx)\r\n    const textHeight = this.measureHeight()\r\n\r\n    ctx.fillStyle = backgroundColor\r\n    const upperLeft = this.getUpperLeft(ctx, canvas)\r\n    ctx.fillRect(upperLeft.x, upperLeft.y, maxTextWidth, textHeight)\r\n\r\n    ctx.fillStyle = fontColor;\r\n    this.text.forEach((textLine, i) => {\r\n      const x = padding + upperLeft.x\r\n      const y = padding + upperLeft.y + ((i + 1) * fontSize)\r\n      ctx.fillText(textLine, x, y)\r\n    })\r\n  }\r\n}","import { Box, IBoundingBox, IRect } from '../classes';\r\nimport { getContext2dOrThrow } from '../dom/getContext2dOrThrow';\r\nimport { AnchorPosition, DrawTextField, DrawTextFieldOptions, IDrawTextFieldOptions } from './DrawTextField';\r\n\r\nexport interface IDrawBoxOptions {\r\n  boxColor?: string\r\n  lineWidth?: number\r\n  drawLabelOptions?: IDrawTextFieldOptions\r\n  label?: string\r\n}\r\n\r\nexport class DrawBoxOptions {\r\n  public boxColor: string\r\n  public lineWidth: number\r\n  public drawLabelOptions: DrawTextFieldOptions\r\n  public label?: string\r\n\r\n  constructor(options: IDrawBoxOptions = {}) {\r\n    const { boxColor, lineWidth, label, drawLabelOptions } = options\r\n    this.boxColor = boxColor || 'rgba(0, 0, 255, 1)'\r\n    this.lineWidth = lineWidth || 2\r\n    this.label = label\r\n\r\n    const defaultDrawLabelOptions = {\r\n      anchorPosition: AnchorPosition.BOTTOM_LEFT,\r\n      backgroundColor: this.boxColor\r\n    }\r\n    this.drawLabelOptions = new DrawTextFieldOptions(Object.assign({}, defaultDrawLabelOptions, drawLabelOptions))\r\n  }\r\n}\r\n\r\nexport class DrawBox {\r\n  public box: Box\r\n  public options: DrawBoxOptions\r\n\r\n  constructor(\r\n    box: IBoundingBox | IRect,\r\n    options: IDrawBoxOptions = {}\r\n  ) {\r\n    this.box = new Box(box)\r\n    this.options = new DrawBoxOptions(options)\r\n  }\r\n\r\n  draw(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D) {\r\n    const ctx = getContext2dOrThrow(canvasArg)\r\n\r\n    const { boxColor, lineWidth } = this.options\r\n\r\n    const { x, y, width, height } = this.box\r\n    ctx.strokeStyle = boxColor\r\n    ctx.lineWidth = lineWidth\r\n    ctx.strokeRect(x, y, width, height)\r\n\r\n    const { label } = this.options\r\n    if (label) {\r\n      new DrawTextField([label], { x: x - (lineWidth / 2), y }, this.options.drawLabelOptions).draw(canvasArg)\r\n    }\r\n  }\r\n}","import { Box, IBoundingBox, IRect } from '../classes';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { isWithFaceDetection, WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { round } from '../utils';\r\nimport { DrawBox } from './DrawBox';\r\n\r\nexport type TDrawDetectionsInput = IRect | IBoundingBox | FaceDetection | WithFaceDetection<{}>\r\n\r\nexport function drawDetections(\r\n  canvasArg: string | HTMLCanvasElement,\r\n  detections: TDrawDetectionsInput | Array<TDrawDetectionsInput>\r\n) {\r\n  const detectionsArray = Array.isArray(detections) ? detections : [detections]\r\n\r\n  detectionsArray.forEach(det => {\r\n    const score = det instanceof FaceDetection\r\n      ? det.score\r\n      : (isWithFaceDetection(det) ? det.detection.score : undefined)\r\n\r\n    const box = det instanceof FaceDetection\r\n      ? det.box\r\n      : (isWithFaceDetection(det) ? det.detection.box : new Box(det))\r\n\r\n    const label = score ? `${round(score)}` : undefined\r\n    new DrawBox(box, { label }).draw(canvasArg)\r\n  })\r\n}","import { env } from '../env';\r\n\r\nexport function isMediaLoaded(media: HTMLImageElement | HTMLVideoElement) : boolean {\r\n\r\n  const { Image, Video } = env.getEnv()\r\n\r\n  return (media instanceof Image && media.complete)\r\n    || (media instanceof Video && media.readyState >= 3)\r\n}\r\n","import { env } from '../env';\r\nimport { isMediaLoaded } from './isMediaLoaded';\r\n\r\nexport function awaitMediaLoaded(media: HTMLImageElement | HTMLVideoElement | HTMLCanvasElement) {\r\n\r\n  return new Promise((resolve, reject) => {\r\n    if (media instanceof env.getEnv().Canvas || isMediaLoaded(media)) {\r\n      return resolve()\r\n    }\r\n\r\n    function onLoad(e: Event) {\r\n      if (!e.currentTarget) return\r\n      e.currentTarget.removeEventListener('load', onLoad)\r\n      e.currentTarget.removeEventListener('error', onError)\r\n      resolve(e)\r\n    }\r\n\r\n    function onError(e: Event) {\r\n      if (!e.currentTarget) return\r\n      e.currentTarget.removeEventListener('load', onLoad)\r\n      e.currentTarget.removeEventListener('error', onError)\r\n      reject(e)\r\n    }\r\n\r\n    media.addEventListener('load', onLoad)\r\n    media.addEventListener('error', onError)\r\n  })\r\n}","import { env } from '../env';\r\n\r\nexport function bufferToImage(buf: Blob): Promise<HTMLImageElement> {\r\n  return new Promise((resolve, reject) => {\r\n    if (!(buf instanceof Blob)) {\r\n      return reject('bufferToImage - expected buf to be of type: Blob')\r\n    }\r\n\r\n    const reader = new FileReader()\r\n    reader.onload = () => {\r\n      if (typeof reader.result !== 'string') {\r\n        return reject('bufferToImage - expected reader.result to be a string, in onload')\r\n      }\r\n\r\n      const img = env.getEnv().createImageElement()\r\n      img.onload = () => resolve(img)\r\n      img.onerror = reject\r\n      img.src = reader.result\r\n    }\r\n    reader.onerror = reject\r\n    reader.readAsDataURL(buf)\r\n  })\r\n}","import { Dimensions, IDimensions } from '../classes/Dimensions';\r\nimport { env } from '../env';\r\n\r\nexport function getMediaDimensions(input: HTMLImageElement | HTMLCanvasElement | HTMLVideoElement | IDimensions): Dimensions {\r\n\r\n  const { Image, Video } = env.getEnv()\r\n\r\n  if (input instanceof Image) {\r\n    return new Dimensions(input.naturalWidth, input.naturalHeight)\r\n  }\r\n  if (input instanceof Video) {\r\n    return new Dimensions(input.videoWidth, input.videoHeight)\r\n  }\r\n  return new Dimensions(input.width, input.height)\r\n}\r\n","import { IDimensions } from '../classes/Dimensions';\r\nimport { env } from '../env';\r\nimport { getContext2dOrThrow } from './getContext2dOrThrow';\r\nimport { getMediaDimensions } from './getMediaDimensions';\r\nimport { isMediaLoaded } from './isMediaLoaded';\r\n\r\nexport function createCanvas({ width, height }: IDimensions): HTMLCanvasElement {\r\n\r\n  const { createCanvasElement } = env.getEnv()\r\n  const canvas = createCanvasElement()\r\n  canvas.width = width\r\n  canvas.height = height\r\n  return canvas\r\n}\r\n\r\nexport function createCanvasFromMedia(media: HTMLImageElement | HTMLVideoElement | ImageData, dims?: IDimensions): HTMLCanvasElement {\r\n\r\n  const { ImageData } = env.getEnv()\r\n\r\n  if (!(media instanceof ImageData) && !isMediaLoaded(media)) {\r\n    throw new Error('createCanvasFromMedia - media has not finished loading yet')\r\n  }\r\n\r\n  const { width, height } = dims || getMediaDimensions(media)\r\n  const canvas = createCanvas({ width, height })\r\n\r\n  if (media instanceof ImageData) {\r\n    getContext2dOrThrow(canvas).putImageData(media, 0, 0)\r\n  } else {\r\n    getContext2dOrThrow(canvas).drawImage(media, 0, 0, width, height)\r\n  }\r\n  return canvas\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { env } from '../env';\r\nimport { isTensor4D } from '../utils';\r\n\r\nexport async function imageTensorToCanvas(\r\n  imgTensor: tf.Tensor,\r\n  canvas?: HTMLCanvasElement\r\n): Promise<HTMLCanvasElement> {\r\n\r\n  const targetCanvas = canvas || env.getEnv().createCanvasElement()\r\n\r\n  const [height, width, numChannels] = imgTensor.shape.slice(isTensor4D(imgTensor) ? 1 : 0)\r\n  const imgTensor3D = tf.tidy(() => imgTensor.as3D(height, width, numChannels).toInt())\r\n  await tf.browser.toPixels(imgTensor3D, targetCanvas)\r\n\r\n  imgTensor3D.dispose()\r\n\r\n  return targetCanvas\r\n}","import { env } from '../env';\r\n\r\nexport function isMediaElement(input: any) {\r\n\r\n  const { Image, Canvas, Video } = env.getEnv()\r\n\r\n  return input instanceof Image\r\n    || input instanceof Canvas\r\n    || input instanceof Video\r\n}","import { env } from '../env';\r\nimport { createCanvas, createCanvasFromMedia } from './createCanvas';\r\nimport { getContext2dOrThrow } from './getContext2dOrThrow';\r\nimport { getMediaDimensions } from './getMediaDimensions';\r\n\r\nexport function imageToSquare(input: HTMLImageElement | HTMLCanvasElement, inputSize: number, centerImage: boolean = false) {\r\n\r\n  const { Image, Canvas } = env.getEnv()\r\n\r\n  if (!(input instanceof Image || input instanceof Canvas)) {\r\n    throw new Error('imageToSquare - expected arg0 to be HTMLImageElement | HTMLCanvasElement')\r\n  }\r\n\r\n  const dims = getMediaDimensions(input)\r\n  const scale = inputSize / Math.max(dims.height, dims.width)\r\n  const width = scale * dims.width\r\n  const height = scale * dims.height\r\n\r\n  const targetCanvas = createCanvas({ width: inputSize, height: inputSize })\r\n  const inputCanvas = input instanceof Canvas ? input : createCanvasFromMedia(input)\r\n\r\n  const offset = Math.abs(width - height) / 2\r\n  const dx = centerImage && width < height ? offset : 0\r\n  const dy = centerImage && height < width ? offset : 0\r\n  getContext2dOrThrow(targetCanvas).drawImage(inputCanvas, dx, dy, width, height)\r\n\r\n  return targetCanvas\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Dimensions } from '../classes/Dimensions';\r\nimport { env } from '../env';\r\nimport { padToSquare } from '../ops/padToSquare';\r\nimport { computeReshapedDimensions, isTensor3D, isTensor4D, range } from '../utils';\r\nimport { createCanvasFromMedia } from './createCanvas';\r\nimport { imageToSquare } from './imageToSquare';\r\nimport { TResolvedNetInput } from './types';\r\n\r\nexport class NetInput {\r\n  private _imageTensors: Array<tf.Tensor3D | tf.Tensor4D> = []\r\n  private _canvases: HTMLCanvasElement[] = []\r\n  private _batchSize: number\r\n  private _treatAsBatchInput: boolean = false\r\n\r\n  private _inputDimensions: number[][] = []\r\n  private _inputSize: number\r\n\r\n  constructor(\r\n    inputs: Array<TResolvedNetInput>,\r\n    treatAsBatchInput: boolean = false\r\n  ) {\r\n    if (!Array.isArray(inputs)) {\r\n      throw new Error(`NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have ${inputs}`)\r\n    }\r\n\r\n    this._treatAsBatchInput = treatAsBatchInput\r\n    this._batchSize = inputs.length\r\n\r\n    inputs.forEach((input, idx) => {\r\n\r\n      if (isTensor3D(input)) {\r\n        this._imageTensors[idx] = input\r\n        this._inputDimensions[idx] = input.shape\r\n        return\r\n      }\r\n\r\n      if (isTensor4D(input)) {\r\n        const batchSize = input.shape[0]\r\n        if (batchSize !== 1) {\r\n          throw new Error(`NetInput - tf.Tensor4D with batchSize ${batchSize} passed, but not supported in input array`)\r\n        }\r\n\r\n        this._imageTensors[idx] = input\r\n        this._inputDimensions[idx] = input.shape.slice(1)\r\n        return\r\n      }\r\n\r\n      const canvas = input instanceof env.getEnv().Canvas ? input : createCanvasFromMedia(input)\r\n      this._canvases[idx] = canvas\r\n      this._inputDimensions[idx] = [canvas.height, canvas.width, 3]\r\n    })\r\n  }\r\n\r\n  public get imageTensors(): Array<tf.Tensor3D | tf.Tensor4D> {\r\n    return this._imageTensors\r\n  }\r\n\r\n  public get canvases(): HTMLCanvasElement[] {\r\n    return this._canvases\r\n  }\r\n\r\n  public get isBatchInput(): boolean {\r\n    return this.batchSize > 1 || this._treatAsBatchInput\r\n  }\r\n\r\n  public get batchSize(): number {\r\n    return this._batchSize\r\n  }\r\n\r\n  public get inputDimensions(): number[][] {\r\n    return this._inputDimensions\r\n  }\r\n\r\n  public get inputSize(): number | undefined {\r\n    return this._inputSize\r\n  }\r\n\r\n  public get reshapedInputDimensions(): Dimensions[] {\r\n    return range(this.batchSize, 0, 1).map(\r\n      (_, batchIdx) => this.getReshapedInputDimensions(batchIdx)\r\n    )\r\n  }\r\n\r\n  public getInput(batchIdx: number): tf.Tensor3D  | tf.Tensor4D | HTMLCanvasElement {\r\n    return this.canvases[batchIdx] || this.imageTensors[batchIdx]\r\n  }\r\n\r\n  public getInputDimensions(batchIdx: number): number[] {\r\n    return this._inputDimensions[batchIdx]\r\n  }\r\n\r\n  public getInputHeight(batchIdx: number): number {\r\n    return this._inputDimensions[batchIdx][0]\r\n  }\r\n\r\n  public getInputWidth(batchIdx: number): number {\r\n    return this._inputDimensions[batchIdx][1]\r\n  }\r\n\r\n  public getReshapedInputDimensions(batchIdx: number): Dimensions {\r\n    if (typeof this.inputSize !== 'number') {\r\n      throw new Error('getReshapedInputDimensions - inputSize not set, toBatchTensor has not been called yet')\r\n    }\r\n\r\n    const width = this.getInputWidth(batchIdx)\r\n    const height = this.getInputHeight(batchIdx)\r\n    return computeReshapedDimensions({ width, height }, this.inputSize)\r\n  }\r\n\r\n  /**\r\n   * Create a batch tensor from all input canvases and tensors\r\n   * with size [batchSize, inputSize, inputSize, 3].\r\n   *\r\n   * @param inputSize Height and width of the tensor.\r\n   * @param isCenterImage (optional, default: false) If true, add an equal amount of padding on\r\n   * both sides of the minor dimension oof the image.\r\n   * @returns The batch tensor.\r\n   */\r\n  public toBatchTensor(inputSize: number, isCenterInputs: boolean = true): tf.Tensor4D {\r\n\r\n    this._inputSize = inputSize\r\n\r\n    return tf.tidy(() => {\r\n\r\n      const inputTensors = range(this.batchSize, 0, 1).map(batchIdx => {\r\n        const input = this.getInput(batchIdx)\r\n\r\n        if (input instanceof tf.Tensor) {\r\n          let imgTensor = isTensor4D(input) ? input : input.expandDims<tf.Rank.R4>()\r\n          imgTensor = padToSquare(imgTensor, isCenterInputs)\r\n\r\n          if (imgTensor.shape[1] !== inputSize || imgTensor.shape[2] !== inputSize) {\r\n            imgTensor = tf.image.resizeBilinear(imgTensor, [inputSize, inputSize])\r\n          }\r\n\r\n          return imgTensor.as3D(inputSize, inputSize, 3)\r\n        }\r\n\r\n        if (input instanceof env.getEnv().Canvas) {\r\n          return tf.browser.fromPixels(imageToSquare(input, inputSize, isCenterInputs))\r\n        }\r\n\r\n        throw new Error(`toBatchTensor - at batchIdx ${batchIdx}, expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have ${input}`)\r\n      })\r\n\r\n      const batchTensor = tf.stack(inputTensors.map(t => t.toFloat())).as4D(this.batchSize, inputSize, inputSize, 3)\r\n\r\n      return batchTensor\r\n    })\r\n  }\r\n}","import { isTensor3D, isTensor4D } from '../utils';\r\nimport { awaitMediaLoaded } from './awaitMediaLoaded';\r\nimport { isMediaElement } from './isMediaElement';\r\nimport { NetInput } from './NetInput';\r\nimport { resolveInput } from './resolveInput';\r\nimport { TNetInput } from './types';\r\n\r\n/**\r\n * Validates the input to make sure, they are valid net inputs and awaits all media elements\r\n * to be finished loading.\r\n *\r\n * @param input The input, which can be a media element or an array of different media elements.\r\n * @returns A NetInput instance, which can be passed into one of the neural networks.\r\n */\r\nexport async function toNetInput(inputs: TNetInput): Promise<NetInput> {\r\n  if (inputs instanceof NetInput) {\r\n    return inputs\r\n  }\r\n\r\n  let inputArgArray = Array.isArray(inputs)\r\n      ? inputs\r\n      : [inputs]\r\n\r\n  if (!inputArgArray.length) {\r\n    throw new Error('toNetInput - empty array passed as input')\r\n  }\r\n\r\n  const getIdxHint = (idx: number) => Array.isArray(inputs) ? ` at input index ${idx}:` : ''\r\n\r\n  const inputArray = inputArgArray.map(resolveInput)\r\n\r\n  inputArray.forEach((input, i) => {\r\n    if (!isMediaElement(input) && !isTensor3D(input) && !isTensor4D(input)) {\r\n\r\n      if (typeof inputArgArray[i] === 'string') {\r\n        throw new Error(`toNetInput -${getIdxHint(i)} string passed, but could not resolve HTMLElement for element id ${inputArgArray[i]}`)\r\n      }\r\n\r\n      throw new Error(`toNetInput -${getIdxHint(i)} expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id`)\r\n    }\r\n\r\n    if (isTensor4D(input)) {\r\n      // if tf.Tensor4D is passed in the input array, the batch size has to be 1\r\n      const batchSize = input.shape[0]\r\n      if (batchSize !== 1) {\r\n        throw new Error(`toNetInput -${getIdxHint(i)} tf.Tensor4D with batchSize ${batchSize} passed, but not supported in input array`)\r\n      }\r\n    }\r\n  })\r\n\r\n  // wait for all media elements being loaded\r\n  await Promise.all(\r\n    inputArray.map(input => isMediaElement(input) && awaitMediaLoaded(input))\r\n  )\r\n\r\n  return new NetInput(inputArray, Array.isArray(inputs))\r\n}","import { FaceDetection } from '../classes/FaceDetection';\r\nimport { Rect } from '../classes/Rect';\r\nimport { env } from '../env';\r\nimport { createCanvas } from './createCanvas';\r\nimport { getContext2dOrThrow } from './getContext2dOrThrow';\r\nimport { imageTensorToCanvas } from './imageTensorToCanvas';\r\nimport { toNetInput } from './toNetInput';\r\nimport { TNetInput } from './types';\r\n\r\n/**\r\n * Extracts the image regions containing the detected faces.\r\n *\r\n * @param input The image that face detection has been performed on.\r\n * @param detections The face detection results or face bounding boxes for that image.\r\n * @returns The Canvases of the corresponding image region for each detected face.\r\n */\r\nexport async function extractFaces(\r\n  input: TNetInput,\r\n  detections: Array<FaceDetection | Rect>\r\n): Promise<HTMLCanvasElement[]> {\r\n\r\n  const { Canvas } = env.getEnv()\r\n\r\n  let canvas = input as HTMLCanvasElement\r\n\r\n  if (!(input instanceof Canvas)) {\r\n    const netInput = await toNetInput(input)\r\n\r\n    if (netInput.batchSize > 1) {\r\n      throw new Error('extractFaces - batchSize > 1 not supported')\r\n    }\r\n\r\n    const tensorOrCanvas = netInput.getInput(0)\r\n    canvas = tensorOrCanvas instanceof Canvas\r\n      ? tensorOrCanvas\r\n      : await imageTensorToCanvas(tensorOrCanvas)\r\n  }\r\n\r\n  const ctx = getContext2dOrThrow(canvas)\r\n  const boxes = detections.map(\r\n    det => det instanceof FaceDetection\r\n      ? det.forSize(canvas.width, canvas.height).box.floor()\r\n      : det\r\n  )\r\n    .map(box => box.clipAtImageBorders(canvas.width, canvas.height))\r\n\r\n  return boxes.map(({ x, y, width, height }) => {\r\n    const faceImg = createCanvas({ width, height })\r\n    getContext2dOrThrow(faceImg)\r\n      .putImageData(ctx.getImageData(x, y, width, height), 0, 0)\r\n    return faceImg\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Rect } from '../classes';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { isTensor3D, isTensor4D } from '../utils';\r\n\r\n/**\r\n * Extracts the tensors of the image regions containing the detected faces.\r\n * Useful if you want to compute the face descriptors for the face images.\r\n * Using this method is faster then extracting a canvas for each face and\r\n * converting them to tensors individually.\r\n *\r\n * @param imageTensor The image tensor that face detection has been performed on.\r\n * @param detections The face detection results or face bounding boxes for that image.\r\n * @returns Tensors of the corresponding image region for each detected face.\r\n */\r\nexport async function extractFaceTensors(\r\n  imageTensor: tf.Tensor3D | tf.Tensor4D,\r\n  detections: Array<FaceDetection | Rect>\r\n): Promise<tf.Tensor3D[]> {\r\n\r\n  if (!isTensor3D(imageTensor) && !isTensor4D(imageTensor)) {\r\n    throw new Error('extractFaceTensors - expected image tensor to be 3D or 4D')\r\n  }\r\n\r\n  if (isTensor4D(imageTensor) && imageTensor.shape[0] > 1) {\r\n    throw new Error('extractFaceTensors - batchSize > 1 not supported')\r\n  }\r\n\r\n  return tf.tidy(() => {\r\n    const [imgHeight, imgWidth, numChannels] = imageTensor.shape.slice(isTensor4D(imageTensor) ? 1 : 0)\r\n\r\n    const boxes = detections.map(\r\n      det => det instanceof FaceDetection\r\n        ? det.forSize(imgWidth, imgHeight).box\r\n        : det\r\n    )\r\n      .map(box => box.clipAtImageBorders(imgWidth, imgHeight))\r\n\r\n    const faceTensors = boxes.map(({ x, y, width, height }) =>\r\n      tf.slice3d(imageTensor.as3D(imgHeight, imgWidth, numChannels), [y, x, 0], [height, width, numChannels])\r\n    )\r\n\r\n    return faceTensors\r\n  })\r\n}","import { env } from '../env';\r\n\r\nexport async function fetchOrThrow(\r\n  url: string,\r\n  init?: RequestInit\r\n): Promise<Response> {\r\n\r\n  const fetch = env.getEnv().fetch\r\n  const res = await fetch(url, init)\r\n  if (!(res.status < 400)) {\r\n    throw new Error(`failed to fetch: (${res.status}) ${res.statusText}, from url: ${res.url}`)\r\n  }\r\n  return res\r\n}","import { bufferToImage } from './bufferToImage';\r\nimport { fetchOrThrow } from './fetchOrThrow';\r\n\r\nexport async function fetchImage(uri: string): Promise<HTMLImageElement> {\r\n  const res = await fetchOrThrow(uri)\r\n  const blob = await (res).blob()\r\n\r\n  if (!blob.type.startsWith('image/')) {\r\n    throw new Error(`fetchImage - expected blob type to be of type image/*, instead have: ${blob.type}, for url: ${res.url}`)\r\n  }\r\n  return bufferToImage(blob)\r\n}\r\n","import { fetchOrThrow } from './fetchOrThrow';\r\n\r\nexport async function fetchJson<T>(uri: string): Promise<T> {\r\n  return (await fetchOrThrow(uri)).json()\r\n}\r\n","import { fetchOrThrow } from './fetchOrThrow';\r\n\r\nexport async function fetchNetWeights(uri: string): Promise<Float32Array> {\r\n  return new Float32Array(await (await fetchOrThrow(uri)).arrayBuffer())\r\n}\r\n","export function getModelUris(uri: string | undefined, defaultModelName: string) {\r\n  const defaultManifestFilename = `${defaultModelName}-weights_manifest.json`\r\n\r\n  if (!uri) {\r\n    return {\r\n      modelBaseUri: '',\r\n      manifestUri: defaultManifestFilename\r\n    }\r\n  }\r\n\r\n  if (uri === '/') {\r\n    return {\r\n      modelBaseUri: '/',\r\n      manifestUri: `/${defaultManifestFilename}`\r\n    }\r\n  }\r\n  const protocol = uri.startsWith('http://') ? 'http://' : uri.startsWith('https://') ? 'https://' : '';\r\n  uri = uri.replace(protocol, '');\r\n\r\n  const parts = uri.split('/').filter(s => s)\r\n\r\n  const manifestFile = uri.endsWith('.json')\r\n    ? parts[parts.length - 1]\r\n    : defaultManifestFilename\r\n\r\n  let modelBaseUri = protocol + (uri.endsWith('.json') ? parts.slice(0, parts.length - 1) : parts).join('/')\r\n  modelBaseUri = uri.startsWith('/') ? `/${modelBaseUri}` : modelBaseUri\r\n\r\n  return {\r\n    modelBaseUri,\r\n    manifestUri: modelBaseUri === '/' ? `/${manifestFile}` : `${modelBaseUri}/${manifestFile}`\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { getModelUris } from '../common/getModelUris';\r\nimport { fetchJson } from './fetchJson';\r\n\r\nexport async function loadWeightMap(\r\n  uri: string | undefined,\r\n  defaultModelName: string,\r\n): Promise<tf.NamedTensorMap> {\r\n  const { manifestUri, modelBaseUri } = getModelUris(uri, defaultModelName)\r\n\r\n  const manifest = await fetchJson<tf.io.WeightsManifestConfig>(manifestUri)\r\n\r\n  return tf.io.loadWeights(manifest, modelBaseUri)\r\n}","import { IDimensions } from '../classes';\r\nimport { getMediaDimensions } from './getMediaDimensions';\r\n\r\nexport function matchDimensions(input: IDimensions, reference: IDimensions, useMediaDimensions: boolean = false) {\r\n  const { width, height } = useMediaDimensions\r\n    ? getMediaDimensions(reference)\r\n    : reference\r\n  input.width = width\r\n  input.height = height\r\n  return { width, height }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ParamMapping } from './common';\r\nimport { getModelUris } from './common/getModelUris';\r\nimport { loadWeightMap } from './dom';\r\nimport { env } from './env';\r\n\r\nexport abstract class NeuralNetwork<TNetParams> {\r\n\r\n  protected _params: TNetParams | undefined = undefined\r\n  protected _paramMappings: ParamMapping[] = []\r\n\r\n  constructor(protected _name: string) {}\r\n\r\n  public get params(): TNetParams | undefined { return this._params }\r\n  public get paramMappings(): ParamMapping[] { return this._paramMappings }\r\n  public get isLoaded(): boolean { return !!this.params }\r\n\r\n  public getParamFromPath(paramPath: string): tf.Tensor {\r\n    const { obj, objProp } = this.traversePropertyPath(paramPath)\r\n    return obj[objProp]\r\n  }\r\n\r\n  public reassignParamFromPath(paramPath: string, tensor: tf.Tensor) {\r\n    const { obj, objProp } = this.traversePropertyPath(paramPath)\r\n    obj[objProp].dispose()\r\n    obj[objProp] = tensor\r\n  }\r\n\r\n  public getParamList() {\r\n    return this._paramMappings.map(({ paramPath }) => ({\r\n      path: paramPath,\r\n      tensor: this.getParamFromPath(paramPath)\r\n    }))\r\n  }\r\n\r\n  public getTrainableParams() {\r\n    return this.getParamList().filter(param => param.tensor instanceof tf.Variable)\r\n  }\r\n\r\n  public getFrozenParams() {\r\n    return this.getParamList().filter(param => !(param.tensor instanceof tf.Variable))\r\n  }\r\n\r\n  public variable() {\r\n    this.getFrozenParams().forEach(({ path, tensor }) => {\r\n      this.reassignParamFromPath(path, tensor.variable())\r\n    })\r\n  }\r\n\r\n  public freeze() {\r\n    this.getTrainableParams().forEach(({ path, tensor: variable }) => {\r\n      const tensor = tf.tensor(variable.dataSync())\r\n      variable.dispose()\r\n      this.reassignParamFromPath(path, tensor)\r\n    })\r\n  }\r\n\r\n  public dispose(throwOnRedispose: boolean = true) {\r\n    this.getParamList().forEach(param => {\r\n      if (throwOnRedispose && param.tensor.isDisposed) {\r\n        throw new Error(`param tensor has already been disposed for path ${param.path}`)\r\n      }\r\n      param.tensor.dispose()\r\n    })\r\n    this._params = undefined\r\n  }\r\n\r\n  public serializeParams(): Float32Array {\r\n    return new Float32Array(\r\n      this.getParamList()\r\n        .map(({ tensor }) => Array.from(tensor.dataSync()) as number[])\r\n        .reduce((flat, arr) => flat.concat(arr))\r\n    )\r\n  }\r\n\r\n  public async load(weightsOrUrl: Float32Array | string | undefined): Promise<void> {\r\n    if (weightsOrUrl instanceof Float32Array) {\r\n      this.extractWeights(weightsOrUrl)\r\n      return\r\n    }\r\n\r\n    await this.loadFromUri(weightsOrUrl)\r\n  }\r\n\r\n  public async loadFromUri(uri: string | undefined) {\r\n    if (uri && typeof uri !== 'string') {\r\n      throw new Error(`${this._name}.loadFromUri - expected model uri`)\r\n    }\r\n\r\n    const weightMap = await loadWeightMap(uri, this.getDefaultModelName())\r\n    this.loadFromWeightMap(weightMap)\r\n  }\r\n\r\n  public async loadFromDisk(filePath: string | undefined) {\r\n    if (filePath && typeof filePath !== 'string') {\r\n      throw new Error(`${this._name}.loadFromDisk - expected model file path`)\r\n    }\r\n\r\n    const { readFile } = env.getEnv()\r\n\r\n    const { manifestUri, modelBaseUri } = getModelUris(filePath, this.getDefaultModelName())\r\n\r\n    const fetchWeightsFromDisk = (filePaths: string[]) => Promise.all(\r\n      filePaths.map(filePath => readFile(filePath).then(buf => buf.buffer))\r\n    )\r\n    const loadWeights = tf.io.weightsLoaderFactory(fetchWeightsFromDisk)\r\n\r\n    const manifest = JSON.parse((await readFile(manifestUri)).toString())\r\n    const weightMap = await loadWeights(manifest, modelBaseUri)\r\n\r\n    this.loadFromWeightMap(weightMap)\r\n  }\r\n\r\n  public loadFromWeightMap(weightMap: tf.NamedTensorMap) {\r\n    const {\r\n      paramMappings,\r\n      params\r\n    } = this.extractParamsFromWeigthMap(weightMap)\r\n\r\n    this._paramMappings = paramMappings\r\n    this._params = params\r\n  }\r\n\r\n  public extractWeights(weights: Float32Array) {\r\n    const {\r\n      paramMappings,\r\n      params\r\n    } = this.extractParams(weights)\r\n\r\n    this._paramMappings = paramMappings\r\n    this._params = params\r\n  }\r\n\r\n  private traversePropertyPath(paramPath: string) {\r\n    if (!this.params) {\r\n      throw new Error(`traversePropertyPath - model has no loaded params`)\r\n    }\r\n\r\n    const result = paramPath.split('/').reduce((res: { nextObj: any, obj?: any, objProp?: string }, objProp) => {\r\n      if (!res.nextObj.hasOwnProperty(objProp)) {\r\n        throw new Error(`traversePropertyPath - object does not have property ${objProp}, for path ${paramPath}`)\r\n      }\r\n\r\n      return { obj: res.nextObj, objProp, nextObj: res.nextObj[objProp] }\r\n    }, { nextObj: this.params })\r\n\r\n    const { obj, objProp } = result\r\n    if (!obj || !objProp || !(obj[objProp] instanceof tf.Tensor)) {\r\n      throw new Error(`traversePropertyPath - parameter is not a tensor, for path ${paramPath}`)\r\n    }\r\n\r\n    return { obj, objProp }\r\n  }\r\n\r\n  protected abstract getDefaultModelName(): string\r\n  protected abstract extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): { params: TNetParams, paramMappings: ParamMapping[] }\r\n  protected abstract extractParams(weights: Float32Array): { params: TNetParams, paramMappings: ParamMapping[] }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { SeparableConvParams } from './types';\r\n\r\nexport function depthwiseSeparableConv(\r\n  x: tf.Tensor4D,\r\n  params: SeparableConvParams,\r\n  stride: [number, number]\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    let out = tf.separableConv2d(x, params.depthwise_filter, params.pointwise_filter, stride, 'same')\r\n    out = tf.add(out, params.bias)\r\n    return out\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, SeparableConvParams } from '../common';\r\nimport { depthwiseSeparableConv } from '../common/depthwiseSeparableConv';\r\nimport { DenseBlock3Params, DenseBlock4Params } from './types';\r\n\r\nexport function denseBlock3(\r\n  x: tf.Tensor4D,\r\n  denseBlockParams: DenseBlock3Params,\r\n  isFirstLayer: boolean = false\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const out1 = tf.relu(\r\n      isFirstLayer\r\n        ? tf.add(\r\n          tf.conv2d(x, (denseBlockParams.conv0 as ConvParams).filters, [2, 2], 'same'),\r\n          denseBlockParams.conv0.bias\r\n        )\r\n        : depthwiseSeparableConv(x, denseBlockParams.conv0 as SeparableConvParams, [2, 2])\r\n    ) as tf.Tensor4D\r\n    const out2 = depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1])\r\n\r\n    const in3 = tf.relu(tf.add(out1, out2)) as tf.Tensor4D\r\n    const out3 = depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1])\r\n\r\n    return tf.relu(tf.add(out1, tf.add(out2, out3))) as tf.Tensor4D\r\n  })\r\n}\r\n\r\nexport function denseBlock4(\r\n  x: tf.Tensor4D,\r\n  denseBlockParams: DenseBlock4Params,\r\n  isFirstLayer: boolean = false,\r\n  isScaleDown: boolean = true\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const out1 = tf.relu(\r\n      isFirstLayer\r\n        ? tf.add(\r\n          tf.conv2d(x, (denseBlockParams.conv0 as ConvParams).filters, isScaleDown ? [2, 2] : [1, 1], 'same'),\r\n          denseBlockParams.conv0.bias\r\n        )\r\n        : depthwiseSeparableConv(x, denseBlockParams.conv0 as SeparableConvParams, isScaleDown ? [2, 2] : [1, 1])\r\n    ) as tf.Tensor4D\r\n    const out2 = depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1])\r\n\r\n    const in3 = tf.relu(tf.add(out1, out2)) as tf.Tensor4D\r\n    const out3 = depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1])\r\n\r\n    const in4 = tf.relu(tf.add(out1, tf.add(out2, out3))) as tf.Tensor4D\r\n    const out4 = depthwiseSeparableConv(in4, denseBlockParams.conv3, [1, 1])\r\n\r\n    return tf.relu(tf.add(out1, tf.add(out2, tf.add(out3, out4)))) as tf.Tensor4D\r\n  })\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams } from './types';\r\n\r\nexport function convLayer(\r\n  x: tf.Tensor4D,\r\n  params: ConvParams,\r\n  padding: 'valid' | 'same' = 'same',\r\n  withRelu: boolean = false\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const out = tf.add(\r\n      tf.conv2d(x, params.filters, [1, 1], padding),\r\n      params.bias\r\n    ) as tf.Tensor4D\r\n\r\n    return withRelu ? tf.relu(out) : out\r\n  })\r\n}","import { ParamMapping } from './types';\r\n\r\nexport function disposeUnusedWeightTensors(weightMap: any, paramMappings: ParamMapping[]) {\r\n  Object.keys(weightMap).forEach(path => {\r\n    if (!paramMappings.some(pm => pm.originalPath === path)) {\r\n      weightMap[path].dispose()\r\n    }\r\n  })\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, ExtractWeightsFunction, ParamMapping } from './types';\r\n\r\nexport function extractConvParamsFactory(\r\n  extractWeights: ExtractWeightsFunction,\r\n  paramMappings: ParamMapping[]\r\n) {\r\n\r\n  return function(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    filterSize: number,\r\n    mappedPrefix: string\r\n  ): ConvParams {\r\n\r\n    const filters = tf.tensor4d(\r\n      extractWeights(channelsIn * channelsOut * filterSize * filterSize),\r\n      [filterSize, filterSize, channelsIn, channelsOut]\r\n    )\r\n    const bias = tf.tensor1d(extractWeights(channelsOut))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/filters` },\r\n      { paramPath: `${mappedPrefix}/bias` }\r\n    )\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ExtractWeightsFunction, FCParams, ParamMapping } from './types';\r\n\r\n\r\nexport function extractFCParamsFactory(\r\n  extractWeights: ExtractWeightsFunction,\r\n  paramMappings: ParamMapping[]\r\n) {\r\n\r\n  return function(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    mappedPrefix: string\r\n  ): FCParams {\r\n\r\n    const fc_weights = tf.tensor2d(extractWeights(channelsIn * channelsOut), [channelsIn, channelsOut])\r\n    const fc_bias = tf.tensor1d(extractWeights(channelsOut))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/weights` },\r\n      { paramPath: `${mappedPrefix}/bias` }\r\n    )\r\n\r\n    return {\r\n      weights: fc_weights,\r\n      bias: fc_bias\r\n    }\r\n  }\r\n\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport type ExtractWeightsFunction = (numWeights: number) => Float32Array\r\n\r\nexport type ParamMapping = {\r\n  originalPath?: string\r\n  paramPath: string\r\n}\r\n\r\nexport type ConvParams = {\r\n  filters: tf.Tensor4D\r\n  bias: tf.Tensor1D\r\n}\r\n\r\nexport type FCParams = {\r\n  weights: tf.Tensor2D\r\n  bias: tf.Tensor1D\r\n}\r\n\r\nexport class SeparableConvParams {\r\n  constructor(\r\n    public depthwise_filter: tf.Tensor4D,\r\n    public pointwise_filter: tf.Tensor4D,\r\n    public bias: tf.Tensor1D\r\n  ) {}\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ExtractWeightsFunction, ParamMapping, SeparableConvParams } from './types';\r\n\r\nexport function extractSeparableConvParamsFactory(\r\n  extractWeights: ExtractWeightsFunction,\r\n  paramMappings: ParamMapping[]\r\n) {\r\n\r\n  return function(channelsIn: number, channelsOut: number, mappedPrefix: string): SeparableConvParams {\r\n    const depthwise_filter = tf.tensor4d(extractWeights(3 * 3 * channelsIn), [3, 3, channelsIn, 1])\r\n    const pointwise_filter = tf.tensor4d(extractWeights(channelsIn * channelsOut), [1, 1, channelsIn, channelsOut])\r\n    const bias = tf.tensor1d(extractWeights(channelsOut))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/depthwise_filter` },\r\n      { paramPath: `${mappedPrefix}/pointwise_filter` },\r\n      { paramPath: `${mappedPrefix}/bias` }\r\n    )\r\n\r\n    return new SeparableConvParams(\r\n      depthwise_filter,\r\n      pointwise_filter,\r\n      bias\r\n    )\r\n  }\r\n\r\n}\r\n\r\nexport function loadSeparableConvParamsFactory(\r\n  extractWeightEntry: <T>(originalPath: string, paramRank: number) => T\r\n) {\r\n\r\n  return function (prefix: string): SeparableConvParams {\r\n    const depthwise_filter = extractWeightEntry<tf.Tensor4D>(`${prefix}/depthwise_filter`, 4)\r\n    const pointwise_filter = extractWeightEntry<tf.Tensor4D>(`${prefix}/pointwise_filter`, 4)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n\r\n    return new SeparableConvParams(\r\n      depthwise_filter,\r\n      pointwise_filter,\r\n      bias\r\n    )\r\n  }\r\n\r\n}\r\n","import { isTensor } from '../utils';\r\nimport { ParamMapping } from './types';\r\n\r\nexport function extractWeightEntryFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  return function<T> (originalPath: string, paramRank: number, mappedPath?: string): T {\r\n    const tensor = weightMap[originalPath]\r\n\r\n    if (!isTensor(tensor, paramRank)) {\r\n      throw new Error(`expected weightMap[${originalPath}] to be a Tensor${paramRank}D, instead have ${tensor}`)\r\n    }\r\n\r\n    paramMappings.push(\r\n      { originalPath, paramPath: mappedPath || originalPath }\r\n    )\r\n\r\n    return tensor\r\n  }\r\n\r\n}\r\n","export function extractWeightsFactory(weights: Float32Array) {\r\n  let remainingWeights = weights\r\n\r\n  function extractWeights(numWeights: number): Float32Array {\r\n    const ret = remainingWeights.slice(0, numWeights)\r\n    remainingWeights = remainingWeights.slice(numWeights)\r\n    return ret\r\n  }\r\n\r\n  function getRemainingWeights(): Float32Array {\r\n    return remainingWeights\r\n  }\r\n\r\n  return {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  }\r\n}","import {\r\n  extractConvParamsFactory,\r\n  extractSeparableConvParamsFactory,\r\n  ExtractWeightsFunction,\r\n  ParamMapping,\r\n} from '../common';\r\nimport { DenseBlock3Params, DenseBlock4Params } from './types';\r\n\r\nexport function extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  const extractConvParams = extractConvParamsFactory(extractWeights, paramMappings)\r\n  const extractSeparableConvParams = extractSeparableConvParamsFactory(extractWeights, paramMappings)\r\n\r\n  function extractDenseBlock3Params(channelsIn: number, channelsOut: number, mappedPrefix: string, isFirstLayer: boolean = false): DenseBlock3Params {\r\n\r\n    const conv0 = isFirstLayer\r\n      ? extractConvParams(channelsIn, channelsOut, 3, `${mappedPrefix}/conv0`)\r\n      : extractSeparableConvParams(channelsIn, channelsOut, `${mappedPrefix}/conv0`)\r\n    const conv1 = extractSeparableConvParams(channelsOut, channelsOut, `${mappedPrefix}/conv1`)\r\n    const conv2 = extractSeparableConvParams(channelsOut, channelsOut, `${mappedPrefix}/conv2`)\r\n\r\n    return { conv0, conv1, conv2 }\r\n  }\r\n\r\n  function extractDenseBlock4Params(channelsIn: number, channelsOut: number, mappedPrefix: string, isFirstLayer: boolean = false): DenseBlock4Params {\r\n\r\n    const { conv0, conv1, conv2 } = extractDenseBlock3Params(channelsIn, channelsOut, mappedPrefix, isFirstLayer)\r\n    const conv3 = extractSeparableConvParams(channelsOut, channelsOut, `${mappedPrefix}/conv3`)\r\n\r\n    return { conv0, conv1, conv2, conv3 }\r\n  }\r\n\r\n  return {\r\n    extractDenseBlock3Params,\r\n    extractDenseBlock4Params\r\n  }\r\n\r\n}","import { extractWeightsFactory, ParamMapping } from '../common';\r\nimport { extractorsFactory } from './extractorsFactory';\r\nimport { FaceFeatureExtractorParams } from './types';\r\n\r\n\r\nexport function extractParams(weights: Float32Array): { params: FaceFeatureExtractorParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const {\r\n    extractDenseBlock4Params\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const dense0 = extractDenseBlock4Params(3, 32, 'dense0', true)\r\n  const dense1 = extractDenseBlock4Params(32, 64, 'dense1')\r\n  const dense2 = extractDenseBlock4Params(64, 128, 'dense2')\r\n  const dense3 = extractDenseBlock4Params(128, 256, 'dense3')\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { dense0, dense1, dense2, dense3 }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams } from './types';\r\n\r\nexport function loadConvParamsFactory(extractWeightEntry: <T>(originalPath: string, paramRank: number) => T) {\r\n  return function(prefix: string): ConvParams {\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/filters`, 4)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n\r\n    return { filters, bias }\r\n  }\r\n}","import { extractWeightEntryFactory, loadSeparableConvParamsFactory, ParamMapping } from '../common';\r\nimport { loadConvParamsFactory } from '../common/loadConvParamsFactory';\r\nimport { DenseBlock3Params, DenseBlock4Params } from './types';\r\n\r\nexport function loadParamsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  const extractConvParams = loadConvParamsFactory(extractWeightEntry)\r\n  const extractSeparableConvParams = loadSeparableConvParamsFactory(extractWeightEntry)\r\n\r\n  function extractDenseBlock3Params(prefix: string, isFirstLayer: boolean = false): DenseBlock3Params {\r\n    const conv0 = isFirstLayer\r\n      ? extractConvParams(`${prefix}/conv0`)\r\n      : extractSeparableConvParams(`${prefix}/conv0`)\r\n    const conv1 = extractSeparableConvParams(`${prefix}/conv1`)\r\n    const conv2 = extractSeparableConvParams(`${prefix}/conv2`)\r\n\r\n    return { conv0, conv1, conv2 }\r\n  }\r\n\r\n  function extractDenseBlock4Params(prefix: string, isFirstLayer: boolean = false): DenseBlock4Params {\r\n    const conv0 = isFirstLayer\r\n      ? extractConvParams(`${prefix}/conv0`)\r\n      : extractSeparableConvParams(`${prefix}/conv0`)\r\n    const conv1 = extractSeparableConvParams(`${prefix}/conv1`)\r\n    const conv2 = extractSeparableConvParams(`${prefix}/conv2`)\r\n    const conv3 = extractSeparableConvParams(`${prefix}/conv3`)\r\n\r\n    return { conv0, conv1, conv2, conv3 }\r\n  }\r\n\r\n  return {\r\n    extractDenseBlock3Params,\r\n    extractDenseBlock4Params\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, ParamMapping } from '../common';\r\nimport { loadParamsFactory } from './loadParamsFactory';\r\nimport { FaceFeatureExtractorParams } from './types';\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: FaceFeatureExtractorParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractDenseBlock4Params\r\n  } = loadParamsFactory(weightMap, paramMappings)\r\n\r\n  const params = {\r\n    dense0: extractDenseBlock4Params('dense0', true),\r\n    dense1: extractDenseBlock4Params('dense1'),\r\n    dense2: extractDenseBlock4Params('dense2'),\r\n    dense3: extractDenseBlock4Params('dense3')\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { normalize } from '../ops';\r\nimport { denseBlock4 } from './denseBlock';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { FaceFeatureExtractorParams, IFaceFeatureExtractor } from './types';\r\n\r\nexport class FaceFeatureExtractor extends NeuralNetwork<FaceFeatureExtractorParams> implements IFaceFeatureExtractor<FaceFeatureExtractorParams> {\r\n\r\n  constructor() {\r\n    super('FaceFeatureExtractor')\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor4D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('FaceFeatureExtractor - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(112, true)\r\n      const meanRgb = [122.782, 117.001, 104.298]\r\n      const normalized = normalize(batchTensor, meanRgb).div(tf.scalar(255)) as tf.Tensor4D\r\n\r\n      let out = denseBlock4(normalized, params.dense0, true)\r\n      out = denseBlock4(out, params.dense1)\r\n      out = denseBlock4(out, params.dense2)\r\n      out = denseBlock4(out, params.dense3)\r\n      out = tf.avgPool(out, [7, 7], [2, 2], 'valid')\r\n\r\n      return out\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor4D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_feature_extractor_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FCParams } from './types';\r\n\r\nexport function fullyConnectedLayer(\r\n  x: tf.Tensor2D,\r\n  params: FCParams\r\n): tf.Tensor2D {\r\n  return tf.tidy(() =>\r\n    tf.add(\r\n      tf.matMul(x, params.weights),\r\n      params.bias\r\n    )\r\n  )\r\n}","import { extractFCParamsFactory, extractWeightsFactory, ParamMapping } from '../common';\r\nimport { NetParams } from './types';\r\n\r\nexport function extractParams(weights: Float32Array, channelsIn: number, channelsOut: number): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const extractFCParams = extractFCParamsFactory(extractWeights, paramMappings)\r\n\r\n  const fc = extractFCParams(channelsIn, channelsOut, 'fc')\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { fc }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, extractWeightEntryFactory, FCParams, ParamMapping } from '../common';\r\nimport { NetParams } from './types';\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractFcParams(prefix: string): FCParams {\r\n    const weights = extractWeightEntry<tf.Tensor2D>(`${prefix}/weights`, 2)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n    return { weights, bias }\r\n  }\r\n\r\n  const params = {\r\n    fc: extractFcParams('fc')\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function seperateWeightMaps(weightMap: tf.NamedTensorMap) {\r\n\r\n  const featureExtractorMap: tf.NamedTensorMap = {}\r\n  const classifierMap: tf.NamedTensorMap = {}\r\n\r\n  Object.keys(weightMap).forEach(key => {\r\n    const map = key.startsWith('fc') ? classifierMap : featureExtractorMap\r\n    map[key] = weightMap[key]\r\n  })\r\n\r\n  return { featureExtractorMap, classifierMap }\r\n\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { fullyConnectedLayer } from '../common/fullyConnectedLayer';\r\nimport { NetInput } from '../dom';\r\nimport {\r\n  FaceFeatureExtractorParams,\r\n  IFaceFeatureExtractor,\r\n  TinyFaceFeatureExtractorParams,\r\n} from '../faceFeatureExtractor/types';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { NetParams } from './types';\r\nimport { seperateWeightMaps } from './util';\r\n\r\nexport abstract class FaceProcessor<\r\n  TExtractorParams extends FaceFeatureExtractorParams | TinyFaceFeatureExtractorParams\r\n>\r\n  extends NeuralNetwork<NetParams> {\r\n\r\n  protected _faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>\r\n\r\n  constructor(_name: string, faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>) {\r\n    super(_name)\r\n    this._faceFeatureExtractor = faceFeatureExtractor\r\n  }\r\n\r\n  public get faceFeatureExtractor(): IFaceFeatureExtractor<TExtractorParams> {\r\n    return this._faceFeatureExtractor\r\n  }\r\n\r\n  protected abstract getDefaultModelName(): string\r\n  protected abstract getClassifierChannelsIn(): number\r\n  protected abstract getClassifierChannelsOut(): number\r\n\r\n  public runNet(input: NetInput | tf.Tensor4D): tf.Tensor2D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error(`${this._name} - load model before inference`)\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const bottleneckFeatures = input instanceof NetInput\r\n        ? this.faceFeatureExtractor.forwardInput(input)\r\n        : input\r\n      return fullyConnectedLayer(bottleneckFeatures.as2D(bottleneckFeatures.shape[0], -1), params.fc)\r\n    })\r\n  }\r\n\r\n  public dispose(throwOnRedispose: boolean = true) {\r\n    this.faceFeatureExtractor.dispose(throwOnRedispose)\r\n    super.dispose(throwOnRedispose)\r\n  }\r\n\r\n  public loadClassifierParams(weights: Float32Array) {\r\n    const { params, paramMappings } = this.extractClassifierParams(weights)\r\n    this._params = params\r\n    this._paramMappings = paramMappings\r\n  }\r\n\r\n  public extractClassifierParams(weights: Float32Array) {\r\n    return extractParams(weights, this.getClassifierChannelsIn(), this.getClassifierChannelsOut())\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n\r\n    const { featureExtractorMap, classifierMap } = seperateWeightMaps(weightMap)\r\n\r\n    this.faceFeatureExtractor.loadFromWeightMap(featureExtractorMap)\r\n\r\n    return extractParamsFromWeigthMap(classifierMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n\r\n    const cIn = this.getClassifierChannelsIn()\r\n    const cOut = this.getClassifierChannelsOut()\r\n    const classifierWeightSize = (cOut * cIn ) + cOut\r\n\r\n    const featureExtractorWeights = weights.slice(0, weights.length - classifierWeightSize)\r\n    const classifierWeights = weights.slice(weights.length - classifierWeightSize)\r\n\r\n    this.faceFeatureExtractor.extractWeights(featureExtractorWeights)\r\n    return this.extractClassifierParams(classifierWeights)\r\n  }\r\n}","export const FACE_EXPRESSION_LABELS = ['neutral', 'happy', 'sad', 'angry', 'fearful', 'disgusted', 'surprised']\r\n\r\nexport class FaceExpressions {\r\n  public neutral: number\r\n  public happy: number\r\n  public sad: number\r\n  public angry: number\r\n  public fearful: number\r\n  public disgusted: number\r\n  public surprised: number\r\n\r\n  constructor(probabilities: number[] | Float32Array) {\r\n    if (probabilities.length !== 7) {\r\n      throw new Error(`FaceExpressions.constructor - expected probabilities.length to be 7, have: ${probabilities.length}`)\r\n    }\r\n\r\n    FACE_EXPRESSION_LABELS.forEach((expression, idx) => {\r\n      this[expression] = probabilities[idx]\r\n    })\r\n  }\r\n\r\n  asSortedArray() {\r\n    return FACE_EXPRESSION_LABELS\r\n      .map(expression => ({ expression, probability: this[expression] as number }))\r\n      .sort((e0, e1) => e1.probability - e0.probability)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { FaceFeatureExtractor } from '../faceFeatureExtractor/FaceFeatureExtractor';\r\nimport { FaceFeatureExtractorParams } from '../faceFeatureExtractor/types';\r\nimport { FaceProcessor } from '../faceProcessor/FaceProcessor';\r\nimport { FaceExpressions } from './FaceExpressions';\r\n\r\nexport class FaceExpressionNet extends FaceProcessor<FaceFeatureExtractorParams> {\r\n\r\n  constructor(faceFeatureExtractor: FaceFeatureExtractor = new FaceFeatureExtractor()) {\r\n    super('FaceExpressionNet', faceFeatureExtractor)\r\n  }\r\n\r\n  public forwardInput(input: NetInput | tf.Tensor4D): tf.Tensor2D {\r\n    return tf.tidy(() => tf.softmax(this.runNet(input)))\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor2D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async predictExpressions(input: TNetInput) {\r\n    const netInput = await toNetInput(input)\r\n    const out = await this.forwardInput(netInput)\r\n    const probabilitesByBatch = await Promise.all(tf.unstack(out).map(async t => {\r\n      const data = await t.data()\r\n      t.dispose()\r\n      return data\r\n    }))\r\n    out.dispose()\r\n\r\n    const predictionsByBatch = probabilitesByBatch\r\n      .map(probabilites => new FaceExpressions(probabilites as Float32Array))\r\n\r\n    return netInput.isBatchInput\r\n      ? predictionsByBatch\r\n      : predictionsByBatch[0]\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_expression_model'\r\n  }\r\n\r\n  protected getClassifierChannelsIn(): number {\r\n    return 256\r\n  }\r\n\r\n  protected getClassifierChannelsOut(): number {\r\n    return 7\r\n  }\r\n}","import { FaceExpressions } from '../faceExpressionNet/FaceExpressions';\r\n\r\nexport type WithFaceExpressions<TSource> = TSource & {\r\n  expressions: FaceExpressions\r\n}\r\n\r\nexport function isWithFaceExpressions(obj: any): obj is WithFaceExpressions<{}> {\r\n  return obj['expressions'] instanceof FaceExpressions\r\n}\r\n\r\nexport function extendWithFaceExpressions<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  expressions: FaceExpressions\r\n): WithFaceExpressions<TSource> {\r\n\r\n  const extension = { expressions }\r\n  return Object.assign({}, sourceObj, extension)\r\n}","import { IPoint, Point } from '../classes';\r\nimport { FaceExpressions } from '../faceExpressionNet';\r\nimport { isWithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { isWithFaceExpressions, WithFaceExpressions } from '../factories/WithFaceExpressions';\r\nimport { round } from '../utils';\r\nimport { DrawTextField } from './DrawTextField';\r\n\r\nexport type DrawFaceExpressionsInput = FaceExpressions | WithFaceExpressions<{}>\r\n\r\nexport function drawFaceExpressions(\r\n  canvasArg: string | HTMLCanvasElement,\r\n  faceExpressions: DrawFaceExpressionsInput | Array<DrawFaceExpressionsInput>,\r\n  minConfidence = 0.1,\r\n  textFieldAnchor?: IPoint\r\n) {\r\n  const faceExpressionsArray = Array.isArray(faceExpressions) ? faceExpressions : [faceExpressions]\r\n\r\n  faceExpressionsArray.forEach(e => {\r\n    const expr = e instanceof FaceExpressions\r\n      ? e\r\n      : (isWithFaceExpressions(e) ? e.expressions : undefined)\r\n    if (!expr) {\r\n      throw new Error('drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof')\r\n    }\r\n\r\n    const sorted = expr.asSortedArray()\r\n    const resultsToDisplay = sorted.filter(expr => expr.probability > minConfidence)\r\n\r\n    const anchor = isWithFaceDetection(e)\r\n      ? e.detection.box.bottomLeft\r\n      : (textFieldAnchor || new Point(0, 0))\r\n\r\n    const drawTextField = new DrawTextField(\r\n      resultsToDisplay.map(expr => `${expr.expression} (${round(expr.probability)})`),\r\n      anchor\r\n    )\r\n    drawTextField.draw(canvasArg)\r\n  })\r\n}","import { FaceDetection } from '../classes/FaceDetection';\r\nimport { FaceLandmarks } from '../classes/FaceLandmarks';\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { isWithFaceDetection, WithFaceDetection } from './WithFaceDetection';\r\n\r\nexport type WithFaceLandmarks<\r\n  TSource extends WithFaceDetection<{}>,\r\n  TFaceLandmarks extends FaceLandmarks = FaceLandmarks68\r\n> = TSource & {\r\n  landmarks: TFaceLandmarks\r\n  unshiftedLandmarks: TFaceLandmarks\r\n  alignedRect: FaceDetection\r\n}\r\n\r\nexport function isWithFaceLandmarks(obj: any): obj is WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks> {\r\n  return isWithFaceDetection(obj)\r\n    && obj['landmarks'] instanceof FaceLandmarks\r\n    && obj['unshiftedLandmarks'] instanceof FaceLandmarks\r\n    && obj['alignedRect'] instanceof FaceDetection\r\n}\r\n\r\nexport function extendWithFaceLandmarks<\r\n  TSource extends WithFaceDetection<{}>,\r\n  TFaceLandmarks extends FaceLandmarks = FaceLandmarks68\r\n> (\r\n  sourceObj: TSource,\r\n  unshiftedLandmarks: TFaceLandmarks\r\n): WithFaceLandmarks<TSource, TFaceLandmarks> {\r\n\r\n  const { box: shift } = sourceObj.detection\r\n  const landmarks = unshiftedLandmarks.shiftBy<TFaceLandmarks>(shift.x, shift.y)\r\n\r\n  const rect = landmarks.align()\r\n  const { imageDims } = sourceObj.detection\r\n  const alignedRect = new FaceDetection(sourceObj.detection.score, rect.rescale(imageDims.reverse()), imageDims)\r\n\r\n  const extension = {\r\n    landmarks,\r\n    unshiftedLandmarks,\r\n    alignedRect\r\n  }\r\n\r\n  return Object.assign({}, sourceObj, extension)\r\n}","import { IPoint } from '../classes';\r\nimport { FaceLandmarks } from '../classes/FaceLandmarks';\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { getContext2dOrThrow } from '../dom/getContext2dOrThrow';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { isWithFaceLandmarks, WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { drawContour } from './drawContour';\r\n\r\nexport interface IDrawFaceLandmarksOptions {\r\n  drawLines?: boolean\r\n  drawPoints?: boolean\r\n  lineWidth?: number\r\n  pointSize?: number\r\n  lineColor?: string\r\n  pointColor?: string\r\n}\r\n\r\nexport class DrawFaceLandmarksOptions {\r\n  public drawLines: boolean\r\n  public drawPoints: boolean\r\n  public lineWidth: number\r\n  public pointSize: number\r\n  public lineColor: string\r\n  public pointColor: string\r\n\r\n  constructor(options: IDrawFaceLandmarksOptions = {}) {\r\n    const { drawLines = true, drawPoints = true, lineWidth, lineColor, pointSize, pointColor } = options\r\n    this.drawLines = drawLines\r\n    this.drawPoints = drawPoints\r\n    this.lineWidth = lineWidth || 1\r\n    this.pointSize = pointSize || 2\r\n    this.lineColor = lineColor || 'rgba(0, 255, 255, 1)'\r\n    this.pointColor = pointColor || 'rgba(255, 0, 255, 1)'\r\n  }\r\n}\r\n\r\nexport class DrawFaceLandmarks {\r\n  public faceLandmarks: FaceLandmarks\r\n  public options: DrawFaceLandmarksOptions\r\n\r\n  constructor(\r\n    faceLandmarks: FaceLandmarks,\r\n    options: IDrawFaceLandmarksOptions = {}\r\n  ) {\r\n    this.faceLandmarks = faceLandmarks\r\n    this.options = new DrawFaceLandmarksOptions(options)\r\n  }\r\n\r\n  draw(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D) {\r\n    const ctx = getContext2dOrThrow(canvasArg)\r\n\r\n    const { drawLines, drawPoints, lineWidth, lineColor, pointSize, pointColor } = this.options\r\n\r\n    if (drawLines && this.faceLandmarks instanceof FaceLandmarks68) {\r\n      ctx.strokeStyle = lineColor\r\n      ctx.lineWidth = lineWidth\r\n      drawContour(ctx, this.faceLandmarks.getJawOutline())\r\n      drawContour(ctx, this.faceLandmarks.getLeftEyeBrow())\r\n      drawContour(ctx, this.faceLandmarks.getRightEyeBrow())\r\n      drawContour(ctx, this.faceLandmarks.getNose())\r\n      drawContour(ctx, this.faceLandmarks.getLeftEye(), true)\r\n      drawContour(ctx, this.faceLandmarks.getRightEye(), true)\r\n      drawContour(ctx, this.faceLandmarks.getMouth(), true)\r\n    }\r\n\r\n    if (drawPoints) {\r\n      ctx.strokeStyle = pointColor\r\n      ctx.fillStyle = pointColor\r\n\r\n      const drawPoint = (pt: IPoint) => {\r\n        ctx.beginPath()\r\n        ctx.arc(pt.x, pt.y, pointSize, 0, 2 * Math.PI)\r\n        ctx.fill()\r\n      }\r\n      this.faceLandmarks.positions.forEach(drawPoint)\r\n    }\r\n  }\r\n}\r\n\r\nexport type DrawFaceLandmarksInput = FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>>\r\n\r\nexport function drawFaceLandmarks(\r\n  canvasArg: string | HTMLCanvasElement,\r\n  faceLandmarks: DrawFaceLandmarksInput | Array<DrawFaceLandmarksInput>\r\n) {\r\n  const faceLandmarksArray = Array.isArray(faceLandmarks) ? faceLandmarks : [faceLandmarks]\r\n  faceLandmarksArray.forEach(f => {\r\n    const landmarks = f instanceof FaceLandmarks\r\n      ? f\r\n      : (isWithFaceLandmarks(f) ? f.landmarks : undefined)\r\n    if (!landmarks) {\r\n      throw new Error('drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof')\r\n    }\r\n\r\n    new DrawFaceLandmarks(landmarks).draw(canvasArg)\r\n  })\r\n}","import { extractConvParamsFactory, extractSeparableConvParamsFactory, extractWeightsFactory } from '../common';\r\nimport { ExtractWeightsFunction, ParamMapping } from '../common/types';\r\nimport { range } from '../utils';\r\nimport { MainBlockParams, ReductionBlockParams, TinyXceptionParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  const extractConvParams = extractConvParamsFactory(extractWeights, paramMappings)\r\n  const extractSeparableConvParams = extractSeparableConvParamsFactory(extractWeights, paramMappings)\r\n\r\n  function extractReductionBlockParams(channelsIn: number, channelsOut: number, mappedPrefix: string): ReductionBlockParams {\r\n\r\n    const separable_conv0 = extractSeparableConvParams(channelsIn, channelsOut, `${mappedPrefix}/separable_conv0`)\r\n    const separable_conv1 = extractSeparableConvParams(channelsOut, channelsOut, `${mappedPrefix}/separable_conv1`)\r\n    const expansion_conv = extractConvParams(channelsIn, channelsOut, 1, `${mappedPrefix}/expansion_conv`)\r\n\r\n    return { separable_conv0, separable_conv1, expansion_conv }\r\n  }\r\n\r\n  function extractMainBlockParams(channels: number, mappedPrefix: string): MainBlockParams {\r\n\r\n    const separable_conv0 = extractSeparableConvParams(channels, channels, `${mappedPrefix}/separable_conv0`)\r\n    const separable_conv1 = extractSeparableConvParams(channels, channels, `${mappedPrefix}/separable_conv1`)\r\n    const separable_conv2 = extractSeparableConvParams(channels, channels, `${mappedPrefix}/separable_conv2`)\r\n\r\n    return { separable_conv0, separable_conv1, separable_conv2 }\r\n  }\r\n\r\n  return {\r\n    extractConvParams,\r\n    extractSeparableConvParams,\r\n    extractReductionBlockParams,\r\n    extractMainBlockParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(weights: Float32Array, numMainBlocks: number): { params: TinyXceptionParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const {\r\n    extractConvParams,\r\n    extractSeparableConvParams,\r\n    extractReductionBlockParams,\r\n    extractMainBlockParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const entry_flow_conv_in = extractConvParams(3, 32, 3, 'entry_flow/conv_in')\r\n  const entry_flow_reduction_block_0 = extractReductionBlockParams(32, 64, 'entry_flow/reduction_block_0')\r\n  const entry_flow_reduction_block_1 = extractReductionBlockParams(64, 128, 'entry_flow/reduction_block_1')\r\n\r\n  const entry_flow = {\r\n    conv_in: entry_flow_conv_in,\r\n    reduction_block_0: entry_flow_reduction_block_0,\r\n    reduction_block_1: entry_flow_reduction_block_1\r\n  }\r\n\r\n  const middle_flow = {}\r\n  range(numMainBlocks, 0, 1).forEach((idx) => {\r\n    middle_flow[`main_block_${idx}`] = extractMainBlockParams(128, `middle_flow/main_block_${idx}`)\r\n  })\r\n\r\n  const exit_flow_reduction_block = extractReductionBlockParams(128, 256, 'exit_flow/reduction_block')\r\n  const exit_flow_separable_conv = extractSeparableConvParams(256, 512, 'exit_flow/separable_conv')\r\n\r\n  const exit_flow = {\r\n    reduction_block: exit_flow_reduction_block,\r\n    separable_conv: exit_flow_separable_conv\r\n  }\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { entry_flow, middle_flow, exit_flow }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport {\r\n  disposeUnusedWeightTensors,\r\n  extractWeightEntryFactory,\r\n  loadSeparableConvParamsFactory,\r\n  ParamMapping,\r\n} from '../common';\r\nimport { loadConvParamsFactory } from '../common/loadConvParamsFactory';\r\nimport { range } from '../utils';\r\nimport { MainBlockParams, ReductionBlockParams, TinyXceptionParams } from './types';\r\n\r\nfunction loadParamsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  const extractConvParams = loadConvParamsFactory(extractWeightEntry)\r\n  const extractSeparableConvParams = loadSeparableConvParamsFactory(extractWeightEntry)\r\n\r\n  function extractReductionBlockParams(mappedPrefix: string): ReductionBlockParams {\r\n\r\n    const separable_conv0 = extractSeparableConvParams(`${mappedPrefix}/separable_conv0`)\r\n    const separable_conv1 = extractSeparableConvParams(`${mappedPrefix}/separable_conv1`)\r\n    const expansion_conv = extractConvParams(`${mappedPrefix}/expansion_conv`)\r\n\r\n    return { separable_conv0, separable_conv1, expansion_conv }\r\n  }\r\n\r\n  function extractMainBlockParams(mappedPrefix: string): MainBlockParams {\r\n\r\n    const separable_conv0 = extractSeparableConvParams(`${mappedPrefix}/separable_conv0`)\r\n    const separable_conv1 = extractSeparableConvParams(`${mappedPrefix}/separable_conv1`)\r\n    const separable_conv2 = extractSeparableConvParams(`${mappedPrefix}/separable_conv2`)\r\n\r\n    return { separable_conv0, separable_conv1, separable_conv2 }\r\n  }\r\n\r\n  return {\r\n    extractConvParams,\r\n    extractSeparableConvParams,\r\n    extractReductionBlockParams,\r\n    extractMainBlockParams\r\n  }\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap,\r\n  numMainBlocks: number\r\n): { params: TinyXceptionParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvParams,\r\n    extractSeparableConvParams,\r\n    extractReductionBlockParams,\r\n    extractMainBlockParams\r\n  } = loadParamsFactory(weightMap, paramMappings)\r\n\r\n  const entry_flow_conv_in = extractConvParams('entry_flow/conv_in')\r\n  const entry_flow_reduction_block_0 = extractReductionBlockParams('entry_flow/reduction_block_0')\r\n  const entry_flow_reduction_block_1 = extractReductionBlockParams('entry_flow/reduction_block_1')\r\n\r\n  const entry_flow = {\r\n    conv_in: entry_flow_conv_in,\r\n    reduction_block_0: entry_flow_reduction_block_0,\r\n    reduction_block_1: entry_flow_reduction_block_1\r\n  }\r\n\r\n  const middle_flow = {}\r\n  range(numMainBlocks, 0, 1).forEach((idx) => {\r\n    middle_flow[`main_block_${idx}`] = extractMainBlockParams(`middle_flow/main_block_${idx}`)\r\n  })\r\n\r\n  const exit_flow_reduction_block = extractReductionBlockParams('exit_flow/reduction_block')\r\n  const exit_flow_separable_conv = extractSeparableConvParams('exit_flow/separable_conv')\r\n\r\n  const exit_flow = {\r\n    reduction_block: exit_flow_reduction_block,\r\n    separable_conv: exit_flow_separable_conv\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params: { entry_flow, middle_flow, exit_flow }, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, depthwiseSeparableConv } from '../common';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { normalize } from '../ops';\r\nimport { range } from '../utils';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { MainBlockParams, ReductionBlockParams, TinyXceptionParams } from './types';\r\n\r\nfunction conv(x: tf.Tensor4D, params: ConvParams, stride: [number, number]): tf.Tensor4D {\r\n  return tf.add(tf.conv2d(x, params.filters, stride, 'same'), params.bias)\r\n}\r\n\r\nfunction reductionBlock(x: tf.Tensor4D, params: ReductionBlockParams, isActivateInput: boolean = true): tf.Tensor4D {\r\n  let out = isActivateInput ? tf.relu(x) : x\r\n  out = depthwiseSeparableConv(out, params.separable_conv0, [1, 1])\r\n  out = depthwiseSeparableConv(tf.relu(out),  params.separable_conv1, [1, 1])\r\n  out = tf.maxPool(out, [3, 3], [2, 2], 'same')\r\n  out = tf.add(out, conv(x,  params.expansion_conv, [2, 2]))\r\n  return out\r\n}\r\n\r\nfunction mainBlock(x: tf.Tensor4D, params: MainBlockParams): tf.Tensor4D {\r\n  let out = depthwiseSeparableConv(tf.relu(x), params.separable_conv0, [1, 1])\r\n  out = depthwiseSeparableConv(tf.relu(out), params.separable_conv1, [1, 1])\r\n  out = depthwiseSeparableConv(tf.relu(out), params.separable_conv2, [1, 1])\r\n  out = tf.add(out, x)\r\n  return out\r\n}\r\n\r\nexport class TinyXception extends NeuralNetwork<TinyXceptionParams> {\r\n\r\n  private _numMainBlocks: number\r\n\r\n  constructor(numMainBlocks: number) {\r\n    super('TinyXception')\r\n    this._numMainBlocks = numMainBlocks\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor4D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('TinyXception - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(112, true)\r\n      const meanRgb = [122.782, 117.001, 104.298]\r\n      const normalized = normalize(batchTensor, meanRgb).div(tf.scalar(256)) as tf.Tensor4D\r\n\r\n      let out = tf.relu(conv(normalized, params.entry_flow.conv_in, [2, 2]))\r\n      out = reductionBlock(out, params.entry_flow.reduction_block_0, false)\r\n      out = reductionBlock(out, params.entry_flow.reduction_block_1)\r\n\r\n      range(this._numMainBlocks, 0, 1).forEach((idx) => {\r\n        out = mainBlock(out, params.middle_flow[`main_block_${idx}`])\r\n      })\r\n\r\n      out = reductionBlock(out, params.exit_flow.reduction_block)\r\n      out = tf.relu(depthwiseSeparableConv(out, params.exit_flow.separable_conv, [1, 1]))\r\n      return out\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor4D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'tiny_xception_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap, this._numMainBlocks)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights, this._numMainBlocks)\r\n  }\r\n}","import { extractFCParamsFactory, extractWeightsFactory, ParamMapping } from '../common';\r\nimport { NetParams } from './types';\r\n\r\nexport function extractParams(weights: Float32Array): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const extractFCParams = extractFCParamsFactory(extractWeights, paramMappings)\r\n\r\n  const age = extractFCParams(512, 1, 'fc/age')\r\n  const gender = extractFCParams(512, 2, 'fc/gender')\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { fc: { age, gender } }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, extractWeightEntryFactory, FCParams, ParamMapping } from '../common';\r\nimport { NetParams } from './types';\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractFcParams(prefix: string): FCParams {\r\n    const weights = extractWeightEntry<tf.Tensor2D>(`${prefix}/weights`, 2)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n    return { weights, bias }\r\n  }\r\n\r\n  const params = {\r\n    fc: {\r\n      age: extractFcParams('fc/age'),\r\n      gender: extractFcParams('fc/gender')\r\n    }\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FCParams } from '../common';\r\n\r\nexport type AgeAndGenderPrediction = {\r\n  age: number\r\n  gender: Gender\r\n  genderProbability: number\r\n}\r\n\r\nexport enum Gender {\r\n  FEMALE = 'female',\r\n  MALE = 'male'\r\n}\r\n\r\nexport type NetOutput = { age: tf.Tensor1D, gender: tf.Tensor2D }\r\n\r\nexport type NetParams = {\r\n  fc: {\r\n    age: FCParams\r\n    gender: FCParams\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { fullyConnectedLayer } from '../common/fullyConnectedLayer';\r\nimport { seperateWeightMaps } from '../faceProcessor/util';\r\nimport { TinyXception } from '../xception/TinyXception';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { AgeAndGenderPrediction, Gender, NetOutput, NetParams } from './types';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\n\r\nexport class AgeGenderNet extends NeuralNetwork<NetParams> {\r\n\r\n  private _faceFeatureExtractor: TinyXception\r\n\r\n  constructor(faceFeatureExtractor: TinyXception = new TinyXception(2)) {\r\n    super('AgeGenderNet')\r\n    this._faceFeatureExtractor = faceFeatureExtractor\r\n  }\r\n\r\n  public get faceFeatureExtractor(): TinyXception {\r\n    return this._faceFeatureExtractor\r\n  }\r\n\r\n  public runNet(input: NetInput | tf.Tensor4D): NetOutput {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error(`${this._name} - load model before inference`)\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const bottleneckFeatures = input instanceof NetInput\r\n        ? this.faceFeatureExtractor.forwardInput(input)\r\n        : input\r\n\r\n      const pooled = tf.avgPool(bottleneckFeatures, [7, 7], [2, 2], 'valid').as2D(bottleneckFeatures.shape[0], -1)\r\n      const age = fullyConnectedLayer(pooled, params.fc.age).as1D()\r\n      const gender = fullyConnectedLayer(pooled, params.fc.gender)\r\n      return { age, gender }\r\n    })\r\n  }\r\n\r\n  public forwardInput(input: NetInput | tf.Tensor4D): NetOutput {\r\n    return tf.tidy(() => {\r\n      const { age, gender } = this.runNet(input)\r\n      return { age, gender: tf.softmax(gender) }\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<NetOutput> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async predictAgeAndGender(input: TNetInput): Promise<AgeAndGenderPrediction | AgeAndGenderPrediction[]> {\r\n    const netInput = await toNetInput(input)\r\n    const out = await this.forwardInput(netInput)\r\n\r\n    const ages = tf.unstack(out.age)\r\n    const genders = tf.unstack(out.gender)\r\n    const ageAndGenderTensors = ages.map((ageTensor, i) => ({\r\n      ageTensor,\r\n      genderTensor: genders[i]\r\n    }))\r\n\r\n    const predictionsByBatch = await Promise.all(\r\n      ageAndGenderTensors.map(async ({ ageTensor, genderTensor }) => {\r\n        const age = (await ageTensor.data())[0]\r\n        const probMale = (await genderTensor.data())[0]\r\n        const isMale = probMale > 0.5\r\n        const gender = isMale ? Gender.MALE : Gender.FEMALE\r\n        const genderProbability = isMale ? probMale : (1 - probMale)\r\n\r\n        ageTensor.dispose()\r\n        genderTensor.dispose()\r\n        return { age, gender, genderProbability }\r\n      })\r\n    )\r\n    out.age.dispose()\r\n    out.gender.dispose()\r\n\r\n    return netInput.isBatchInput\r\n      ? predictionsByBatch\r\n      : predictionsByBatch[0]\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'age_gender_model'\r\n  }\r\n\r\n  public dispose(throwOnRedispose: boolean = true) {\r\n    this.faceFeatureExtractor.dispose(throwOnRedispose)\r\n    super.dispose(throwOnRedispose)\r\n  }\r\n\r\n  public loadClassifierParams(weights: Float32Array) {\r\n    const { params, paramMappings } = this.extractClassifierParams(weights)\r\n    this._params = params\r\n    this._paramMappings = paramMappings\r\n  }\r\n\r\n  public extractClassifierParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n\r\n    const { featureExtractorMap, classifierMap } = seperateWeightMaps(weightMap)\r\n\r\n    this.faceFeatureExtractor.loadFromWeightMap(featureExtractorMap)\r\n\r\n    return extractParamsFromWeigthMap(classifierMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n\r\n    const classifierWeightSize = (512 * 1 + 1) + (512 * 2 + 2)\r\n\r\n    const featureExtractorWeights = weights.slice(0, weights.length - classifierWeightSize)\r\n    const classifierWeights = weights.slice(weights.length - classifierWeightSize)\r\n\r\n    this.faceFeatureExtractor.extractWeights(featureExtractorWeights)\r\n    return this.extractClassifierParams(classifierWeights)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { IDimensions, Point } from '../classes';\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { FaceFeatureExtractorParams, TinyFaceFeatureExtractorParams } from '../faceFeatureExtractor/types';\r\nimport { FaceProcessor } from '../faceProcessor/FaceProcessor';\r\nimport { isEven } from '../utils';\r\n\r\nexport abstract class FaceLandmark68NetBase<\r\n  TExtractorParams extends FaceFeatureExtractorParams | TinyFaceFeatureExtractorParams\r\n>\r\n  extends FaceProcessor<TExtractorParams> {\r\n\r\n  public postProcess(output: tf.Tensor2D, inputSize: number, originalDimensions: IDimensions[]): tf.Tensor2D {\r\n\r\n    const inputDimensions = originalDimensions.map(({ width, height }) => {\r\n      const scale = inputSize / Math.max(height, width)\r\n      return {\r\n        width: width * scale,\r\n        height: height * scale\r\n      }\r\n    })\r\n\r\n    const batchSize = inputDimensions.length\r\n\r\n    return tf.tidy(() => {\r\n      const createInterleavedTensor = (fillX: number, fillY: number) =>\r\n        tf.stack([\r\n          tf.fill([68], fillX),\r\n          tf.fill([68], fillY)\r\n        ], 1).as2D(1, 136).as1D()\r\n\r\n      const getPadding = (batchIdx: number, cond: (w: number, h: number) => boolean): number => {\r\n        const { width, height } = inputDimensions[batchIdx]\r\n        return cond(width, height) ? Math.abs(width - height) / 2 : 0\r\n      }\r\n      const getPaddingX = (batchIdx: number) => getPadding(batchIdx, (w, h) => w < h)\r\n      const getPaddingY = (batchIdx: number) => getPadding(batchIdx, (w, h) => h < w)\r\n\r\n      const landmarkTensors = output\r\n        .mul(tf.fill([batchSize, 136], inputSize))\r\n        .sub(tf.stack(Array.from(Array(batchSize), (_, batchIdx) =>\r\n          createInterleavedTensor(\r\n            getPaddingX(batchIdx),\r\n            getPaddingY(batchIdx)\r\n          )\r\n        )))\r\n        .div(tf.stack(Array.from(Array(batchSize), (_, batchIdx) =>\r\n          createInterleavedTensor(\r\n            inputDimensions[batchIdx].width,\r\n            inputDimensions[batchIdx].height\r\n          )\r\n        )))\r\n\r\n      return landmarkTensors as tf.Tensor2D\r\n    })\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor2D {\r\n    return tf.tidy(() => {\r\n      const out = this.runNet(input)\r\n      return this.postProcess(\r\n        out,\r\n        input.inputSize as number,\r\n        input.inputDimensions.map(([height, width]) => ({ height, width }))\r\n      )\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor2D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async detectLandmarks(input: TNetInput): Promise<FaceLandmarks68 | FaceLandmarks68[]> {\r\n    const netInput = await toNetInput(input)\r\n    const landmarkTensors = tf.tidy(\r\n      () => tf.unstack(this.forwardInput(netInput))\r\n    )\r\n\r\n    const landmarksForBatch = await Promise.all(landmarkTensors.map(\r\n      async (landmarkTensor, batchIdx) => {\r\n        const landmarksArray = Array.from(await landmarkTensor.data())\r\n        const xCoords = landmarksArray.filter((_, i) => isEven(i))\r\n        const yCoords = landmarksArray.filter((_, i) => !isEven(i))\r\n\r\n        return new FaceLandmarks68(\r\n          Array(68).fill(0).map((_, i) => new Point(xCoords[i], yCoords[i])),\r\n          {\r\n            height: netInput.getInputHeight(batchIdx),\r\n            width : netInput.getInputWidth(batchIdx),\r\n          }\r\n        )\r\n      }\r\n    ))\r\n\r\n    landmarkTensors.forEach(t => t.dispose())\r\n\r\n    return netInput.isBatchInput\r\n      ? landmarksForBatch\r\n      : landmarksForBatch[0]\r\n  }\r\n\r\n  protected getClassifierChannelsOut(): number {\r\n    return 136\r\n  }\r\n}","import { FaceFeatureExtractor } from '../faceFeatureExtractor/FaceFeatureExtractor';\r\nimport { FaceFeatureExtractorParams } from '../faceFeatureExtractor/types';\r\nimport { FaceLandmark68NetBase } from './FaceLandmark68NetBase';\r\n\r\nexport class FaceLandmark68Net extends FaceLandmark68NetBase<FaceFeatureExtractorParams> {\r\n\r\n  constructor(faceFeatureExtractor: FaceFeatureExtractor = new FaceFeatureExtractor()) {\r\n    super('FaceLandmark68Net', faceFeatureExtractor)\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_landmark_68_model'\r\n  }\r\n\r\n  protected getClassifierChannelsIn(): number {\r\n    return 256\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, ParamMapping } from '../common';\r\nimport { loadParamsFactory } from './loadParamsFactory';\r\nimport { TinyFaceFeatureExtractorParams } from './types';\r\n\r\nexport function extractParamsFromWeigthMapTiny(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: TinyFaceFeatureExtractorParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractDenseBlock3Params\r\n  } = loadParamsFactory(weightMap, paramMappings)\r\n\r\n  const params = {\r\n    dense0: extractDenseBlock3Params('dense0', true),\r\n    dense1: extractDenseBlock3Params('dense1'),\r\n    dense2: extractDenseBlock3Params('dense2')\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import { extractWeightsFactory, ParamMapping } from '../common';\r\nimport { extractorsFactory } from './extractorsFactory';\r\nimport { TinyFaceFeatureExtractorParams } from './types';\r\n\r\n\r\n\r\nexport function extractParamsTiny(weights: Float32Array): { params: TinyFaceFeatureExtractorParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const {\r\n    extractDenseBlock3Params\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const dense0 = extractDenseBlock3Params(3, 32, 'dense0', true)\r\n  const dense1 = extractDenseBlock3Params(32, 64, 'dense1')\r\n  const dense2 = extractDenseBlock3Params(64, 128, 'dense2')\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { dense0, dense1, dense2 }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { normalize } from '../ops';\r\nimport { denseBlock3 } from './denseBlock';\r\nimport { extractParamsFromWeigthMapTiny } from './extractParamsFromWeigthMapTiny';\r\nimport { extractParamsTiny } from './extractParamsTiny';\r\nimport { IFaceFeatureExtractor, TinyFaceFeatureExtractorParams } from './types';\r\n\r\nexport class TinyFaceFeatureExtractor extends NeuralNetwork<TinyFaceFeatureExtractorParams> implements IFaceFeatureExtractor<TinyFaceFeatureExtractorParams> {\r\n\r\n  constructor() {\r\n    super('TinyFaceFeatureExtractor')\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor4D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('TinyFaceFeatureExtractor - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(112, true)\r\n      const meanRgb = [122.782, 117.001, 104.298]\r\n      const normalized = normalize(batchTensor, meanRgb).div(tf.scalar(255)) as tf.Tensor4D\r\n\r\n      let out = denseBlock3(normalized, params.dense0, true)\r\n      out = denseBlock3(out, params.dense1)\r\n      out = denseBlock3(out, params.dense2)\r\n      out = tf.avgPool(out, [14, 14], [2, 2], 'valid')\r\n\r\n      return out\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor4D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_feature_extractor_tiny_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMapTiny(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParamsTiny(weights)\r\n  }\r\n}","import { TinyFaceFeatureExtractor } from '../faceFeatureExtractor/TinyFaceFeatureExtractor';\r\nimport { TinyFaceFeatureExtractorParams } from '../faceFeatureExtractor/types';\r\nimport { FaceLandmark68NetBase } from './FaceLandmark68NetBase';\r\n\r\nexport class FaceLandmark68TinyNet extends FaceLandmark68NetBase<TinyFaceFeatureExtractorParams> {\r\n\r\n  constructor(faceFeatureExtractor: TinyFaceFeatureExtractor = new TinyFaceFeatureExtractor()) {\r\n    super('FaceLandmark68TinyNet', faceFeatureExtractor)\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_landmark_68_tiny_model'\r\n  }\r\n\r\n  protected getClassifierChannelsIn(): number {\r\n    return 128\r\n  }\r\n}","import { FaceLandmark68Net } from './FaceLandmark68Net';\r\n\r\nexport * from './FaceLandmark68Net';\r\nexport * from './FaceLandmark68TinyNet';\r\n\r\nexport class FaceLandmarkNet extends FaceLandmark68Net {}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ScaleLayerParams } from './types';\r\n\r\nexport function scale(x: tf.Tensor4D, params: ScaleLayerParams): tf.Tensor4D {\r\n  return tf.add(tf.mul(x, params.weights), params.biases)\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { scale } from './scaleLayer';\r\nimport { ConvLayerParams } from './types';\r\n\r\n\r\nfunction convLayer(\r\n  x: tf.Tensor4D,\r\n  params: ConvLayerParams,\r\n  strides: [number, number],\r\n  withRelu: boolean,\r\n  padding: 'valid' | 'same' = 'same'\r\n): tf.Tensor4D {\r\n  const { filters, bias } = params.conv\r\n\r\n  let out = tf.conv2d(x, filters, strides, padding)\r\n  out = tf.add(out, bias)\r\n  out = scale(out, params.scale)\r\n  return withRelu ? tf.relu(out) : out\r\n}\r\n\r\nexport function conv(x: tf.Tensor4D, params: ConvLayerParams) {\r\n  return convLayer(x, params, [1, 1], true)\r\n}\r\n\r\nexport function convNoRelu(x: tf.Tensor4D, params: ConvLayerParams) {\r\n  return convLayer(x, params, [1, 1], false)\r\n}\r\n\r\nexport function convDown(x: tf.Tensor4D, params: ConvLayerParams) {\r\n  return convLayer(x, params, [2, 2], true, 'valid')\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, extractWeightsFactory, ExtractWeightsFunction, ParamMapping } from '../common';\r\nimport { isFloat } from '../utils';\r\nimport { ConvLayerParams, NetParams, ResidualLayerParams, ScaleLayerParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  function extractFilterValues(numFilterValues: number, numFilters: number, filterSize: number): tf.Tensor4D {\r\n    const weights = extractWeights(numFilterValues)\r\n    const depth = weights.length / (numFilters * filterSize * filterSize)\r\n\r\n    if (isFloat(depth)) {\r\n      throw new Error(`depth has to be an integer: ${depth}, weights.length: ${weights.length}, numFilters: ${numFilters}, filterSize: ${filterSize}`)\r\n    }\r\n\r\n    return tf.tidy(\r\n      () => tf.transpose(\r\n        tf.tensor4d(weights, [numFilters, depth, filterSize, filterSize]),\r\n        [2, 3, 1, 0]\r\n      )\r\n    )\r\n  }\r\n\r\n  function extractConvParams(\r\n    numFilterValues: number,\r\n    numFilters: number,\r\n    filterSize: number,\r\n    mappedPrefix: string\r\n  ): ConvParams {\r\n\r\n    const filters = extractFilterValues(numFilterValues, numFilters, filterSize)\r\n    const bias = tf.tensor1d(extractWeights(numFilters))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/filters` },\r\n      { paramPath: `${mappedPrefix}/bias` }\r\n    )\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractScaleLayerParams(numWeights: number, mappedPrefix: string): ScaleLayerParams {\r\n\r\n    const weights = tf.tensor1d(extractWeights(numWeights))\r\n    const biases = tf.tensor1d(extractWeights(numWeights))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/weights` },\r\n      { paramPath: `${mappedPrefix}/biases` }\r\n    )\r\n\r\n    return {\r\n      weights,\r\n      biases\r\n    }\r\n  }\r\n\r\n  function extractConvLayerParams(\r\n    numFilterValues: number,\r\n    numFilters: number,\r\n    filterSize: number,\r\n    mappedPrefix: string\r\n  ): ConvLayerParams {\r\n\r\n    const conv = extractConvParams(numFilterValues, numFilters, filterSize, `${mappedPrefix}/conv`)\r\n    const scale = extractScaleLayerParams(numFilters, `${mappedPrefix}/scale`)\r\n\r\n    return { conv, scale }\r\n  }\r\n\r\n  function extractResidualLayerParams(\r\n    numFilterValues: number,\r\n    numFilters: number,\r\n    filterSize: number,\r\n    mappedPrefix: string,\r\n    isDown: boolean = false\r\n  ): ResidualLayerParams {\r\n\r\n    const conv1 = extractConvLayerParams((isDown ? 0.5 : 1) * numFilterValues, numFilters, filterSize, `${mappedPrefix}/conv1`)\r\n    const conv2 = extractConvLayerParams(numFilterValues, numFilters, filterSize, `${mappedPrefix}/conv2`)\r\n\r\n    return { conv1, conv2 }\r\n  }\r\n\r\n  return {\r\n    extractConvLayerParams,\r\n    extractResidualLayerParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(weights: Float32Array): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvLayerParams,\r\n    extractResidualLayerParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const conv32_down = extractConvLayerParams(4704, 32, 7, 'conv32_down')\r\n  const conv32_1 = extractResidualLayerParams(9216, 32, 3, 'conv32_1')\r\n  const conv32_2 = extractResidualLayerParams(9216, 32, 3, 'conv32_2')\r\n  const conv32_3 = extractResidualLayerParams(9216, 32, 3, 'conv32_3')\r\n\r\n  const conv64_down = extractResidualLayerParams(36864, 64, 3, 'conv64_down', true)\r\n  const conv64_1 = extractResidualLayerParams(36864, 64, 3, 'conv64_1')\r\n  const conv64_2 = extractResidualLayerParams(36864, 64, 3, 'conv64_2')\r\n  const conv64_3 = extractResidualLayerParams(36864, 64, 3, 'conv64_3')\r\n\r\n  const conv128_down = extractResidualLayerParams(147456, 128, 3, 'conv128_down', true)\r\n  const conv128_1 = extractResidualLayerParams(147456, 128, 3, 'conv128_1')\r\n  const conv128_2 = extractResidualLayerParams(147456, 128, 3, 'conv128_2')\r\n\r\n  const conv256_down = extractResidualLayerParams(589824, 256, 3, 'conv256_down', true)\r\n  const conv256_1 = extractResidualLayerParams(589824, 256, 3, 'conv256_1')\r\n  const conv256_2 = extractResidualLayerParams(589824, 256, 3, 'conv256_2')\r\n  const conv256_down_out = extractResidualLayerParams(589824, 256, 3, 'conv256_down_out')\r\n\r\n  const fc = tf.tidy(\r\n    () => tf.transpose(tf.tensor2d(extractWeights(256 * 128), [128, 256]), [1, 0])\r\n  )\r\n  paramMappings.push({ paramPath: `fc` })\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  const params = {\r\n    conv32_down,\r\n    conv32_1,\r\n    conv32_2,\r\n    conv32_3,\r\n    conv64_down,\r\n    conv64_1,\r\n    conv64_2,\r\n    conv64_3,\r\n    conv128_down,\r\n    conv128_1,\r\n    conv128_2,\r\n    conv256_down,\r\n    conv256_1,\r\n    conv256_2,\r\n    conv256_down_out,\r\n    fc\r\n  }\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, extractWeightEntryFactory, ParamMapping } from '../common';\r\nimport { isTensor2D } from '../utils';\r\nimport { ConvLayerParams, NetParams, ResidualLayerParams, ScaleLayerParams } from './types';\r\n\r\nfunction extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractScaleLayerParams(prefix: string): ScaleLayerParams {\r\n\r\n    const weights = extractWeightEntry<tf.Tensor1D>(`${prefix}/scale/weights`, 1)\r\n    const biases = extractWeightEntry<tf.Tensor1D>(`${prefix}/scale/biases`, 1)\r\n\r\n    return { weights, biases }\r\n  }\r\n\r\n  function extractConvLayerParams(prefix: string): ConvLayerParams {\r\n\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/conv/filters`, 4)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/conv/bias`, 1)\r\n    const scale = extractScaleLayerParams(prefix)\r\n\r\n    return { conv: { filters, bias }, scale }\r\n  }\r\n\r\n  function extractResidualLayerParams(prefix: string): ResidualLayerParams {\r\n    return {\r\n      conv1: extractConvLayerParams(`${prefix}/conv1`),\r\n      conv2: extractConvLayerParams(`${prefix}/conv2`)\r\n    }\r\n  }\r\n\r\n  return {\r\n    extractConvLayerParams,\r\n    extractResidualLayerParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvLayerParams,\r\n    extractResidualLayerParams\r\n  } = extractorsFactory(weightMap, paramMappings)\r\n\r\n  const conv32_down = extractConvLayerParams('conv32_down')\r\n  const conv32_1 = extractResidualLayerParams('conv32_1')\r\n  const conv32_2 = extractResidualLayerParams('conv32_2')\r\n  const conv32_3 = extractResidualLayerParams('conv32_3')\r\n\r\n  const conv64_down = extractResidualLayerParams('conv64_down')\r\n  const conv64_1 = extractResidualLayerParams('conv64_1')\r\n  const conv64_2 = extractResidualLayerParams('conv64_2')\r\n  const conv64_3 = extractResidualLayerParams('conv64_3')\r\n\r\n  const conv128_down = extractResidualLayerParams('conv128_down')\r\n  const conv128_1 = extractResidualLayerParams('conv128_1')\r\n  const conv128_2 = extractResidualLayerParams('conv128_2')\r\n\r\n  const conv256_down = extractResidualLayerParams('conv256_down')\r\n  const conv256_1 = extractResidualLayerParams('conv256_1')\r\n  const conv256_2 = extractResidualLayerParams('conv256_2')\r\n  const conv256_down_out = extractResidualLayerParams('conv256_down_out')\r\n\r\n  const fc = weightMap['fc']\r\n  paramMappings.push({ originalPath: 'fc', paramPath: 'fc' })\r\n\r\n  if (!isTensor2D(fc)) {\r\n    throw new Error(`expected weightMap[fc] to be a Tensor2D, instead have ${fc}`)\r\n  }\r\n\r\n  const params = {\r\n    conv32_down,\r\n    conv32_1,\r\n    conv32_2,\r\n    conv32_3,\r\n    conv64_down,\r\n    conv64_1,\r\n    conv64_2,\r\n    conv64_3,\r\n    conv128_down,\r\n    conv128_1,\r\n    conv128_2,\r\n    conv256_down,\r\n    conv256_1,\r\n    conv256_2,\r\n    conv256_down_out,\r\n    fc\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { conv, convDown, convNoRelu } from './convLayer';\r\nimport { ResidualLayerParams } from './types';\r\n\r\nexport function residual(x: tf.Tensor4D, params: ResidualLayerParams): tf.Tensor4D {\r\n  let out = conv(x, params.conv1)\r\n  out = convNoRelu(out, params.conv2)\r\n  out = tf.add(out, x)\r\n  out = tf.relu(out)\r\n  return out\r\n}\r\n\r\nexport function residualDown(x: tf.Tensor4D, params: ResidualLayerParams): tf.Tensor4D {\r\n  let out = convDown(x, params.conv1)\r\n  out = convNoRelu(out, params.conv2)\r\n\r\n  let pooled = tf.avgPool(x, 2, 2, 'valid') as tf.Tensor4D\r\n  const zeros = tf.zeros<tf.Rank.R4>(pooled.shape)\r\n  const isPad = pooled.shape[3] !== out.shape[3]\r\n  const isAdjustShape = pooled.shape[1] !== out.shape[1] || pooled.shape[2] !== out.shape[2]\r\n\r\n  if (isAdjustShape) {\r\n    const padShapeX = [...out.shape] as [number, number, number, number]\r\n    padShapeX[1] = 1\r\n    const zerosW = tf.zeros<tf.Rank.R4>(padShapeX)\r\n    out = tf.concat([out, zerosW], 1)\r\n\r\n    const padShapeY = [...out.shape] as [number, number, number, number]\r\n    padShapeY[2] = 1\r\n    const zerosH = tf.zeros<tf.Rank.R4>(padShapeY)\r\n    out = tf.concat([out, zerosH], 2)\r\n  }\r\n\r\n  pooled = isPad ? tf.concat([pooled, zeros], 3) : pooled\r\n  out = tf.add(pooled, out) as tf.Tensor4D\r\n\r\n  out = tf.relu(out)\r\n  return out\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { normalize } from '../ops';\r\nimport { convDown } from './convLayer';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { residual, residualDown } from './residualLayer';\r\nimport { NetParams } from './types';\r\n\r\n\r\nexport class FaceRecognitionNet extends NeuralNetwork<NetParams> {\r\n\r\n  constructor() {\r\n    super('FaceRecognitionNet')\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor2D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('FaceRecognitionNet - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(150, true).toFloat()\r\n\r\n      const meanRgb = [122.782, 117.001, 104.298]\r\n      const normalized = normalize(batchTensor, meanRgb).div(tf.scalar(256)) as tf.Tensor4D\r\n\r\n      let out = convDown(normalized, params.conv32_down)\r\n      out = tf.maxPool(out, 3, 2, 'valid')\r\n\r\n      out = residual(out, params.conv32_1)\r\n      out = residual(out, params.conv32_2)\r\n      out = residual(out, params.conv32_3)\r\n\r\n      out = residualDown(out, params.conv64_down)\r\n      out = residual(out, params.conv64_1)\r\n      out = residual(out, params.conv64_2)\r\n      out = residual(out, params.conv64_3)\r\n\r\n      out = residualDown(out, params.conv128_down)\r\n      out = residual(out, params.conv128_1)\r\n      out = residual(out, params.conv128_2)\r\n\r\n      out = residualDown(out, params.conv256_down)\r\n      out = residual(out, params.conv256_1)\r\n      out = residual(out, params.conv256_2)\r\n      out = residualDown(out, params.conv256_down_out)\r\n\r\n      const globalAvg = out.mean([1, 2]) as tf.Tensor2D\r\n      const fullyConnected = tf.matMul(globalAvg, params.fc)\r\n\r\n      return fullyConnected\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor2D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async computeFaceDescriptor(input: TNetInput): Promise<Float32Array|Float32Array[]> {\r\n    const netInput = await toNetInput(input)\r\n\r\n    const faceDescriptorTensors = tf.tidy(\r\n      () => tf.unstack(this.forwardInput(netInput))\r\n    )\r\n\r\n    const faceDescriptorsForBatch = await Promise.all(faceDescriptorTensors.map(\r\n      t => t.data()\r\n    )) as Float32Array[]\r\n\r\n    faceDescriptorTensors.forEach(t => t.dispose())\r\n\r\n    return netInput.isBatchInput\r\n      ? faceDescriptorsForBatch\r\n      : faceDescriptorsForBatch[0]\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_recognition_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n}","import { FaceRecognitionNet } from './FaceRecognitionNet';\r\n\r\nexport * from './FaceRecognitionNet';\r\n\r\nexport function createFaceRecognitionNet(weights: Float32Array) {\r\n  const net = new FaceRecognitionNet()\r\n  net.extractWeights(weights)\r\n  return net\r\n}","export type WithFaceDescriptor<TSource> = TSource & {\r\n  descriptor: Float32Array\r\n}\r\n\r\nexport function extendWithFaceDescriptor<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  descriptor: Float32Array\r\n): WithFaceDescriptor<TSource> {\r\n\r\n  const extension = { descriptor }\r\n  return Object.assign({}, sourceObj, extension)\r\n}\r\n\r\n","export type WithAge<TSource> = TSource & {\r\n  age: number\r\n}\r\n\r\nexport function isWithAge(obj: any): obj is WithAge<{}> {\r\n  return typeof obj['age'] === 'number'\r\n}\r\n\r\nexport function extendWithAge<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  age: number\r\n): WithAge<TSource> {\r\n\r\n  const extension = { age }\r\n  return Object.assign({}, sourceObj, extension)\r\n}","import { Gender } from '../ageGenderNet/types';\r\nimport { isValidProbablitiy } from '../utils';\r\n\r\nexport type WithGender<TSource> = TSource & {\r\n  gender: Gender\r\n  genderProbability: number\r\n}\r\n\r\nexport function isWithGender(obj: any): obj is WithGender<{}> {\r\n  return (obj['gender'] === Gender.MALE || obj['gender'] === Gender.FEMALE)\r\n    && isValidProbablitiy(obj['genderProbability'])\r\n}\r\n\r\nexport function extendWithGender<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  gender: Gender,\r\n  genderProbability: number\r\n): WithGender<TSource> {\r\n\r\n  const extension = { gender, genderProbability }\r\n  return Object.assign({}, sourceObj, extension)\r\n}","export interface IMtcnnOptions {\r\n  minFaceSize?: number\r\n  scaleFactor?: number\r\n  maxNumScales?: number\r\n  scoreThresholds?: number[]\r\n  scaleSteps?: number[]\r\n}\r\n\r\nexport class MtcnnOptions {\r\n  protected _name: string = 'MtcnnOptions'\r\n\r\n  private _minFaceSize: number\r\n  private _scaleFactor: number\r\n  private _maxNumScales: number\r\n  private _scoreThresholds: number[]\r\n  private _scaleSteps: number[] | undefined\r\n\r\n  constructor({ minFaceSize, scaleFactor, maxNumScales, scoreThresholds, scaleSteps }: IMtcnnOptions = {}) {\r\n    this._minFaceSize = minFaceSize || 20\r\n    this._scaleFactor = scaleFactor || 0.709\r\n    this._maxNumScales = maxNumScales || 10\r\n    this._scoreThresholds = scoreThresholds || [0.6, 0.7, 0.7]\r\n    this._scaleSteps = scaleSteps\r\n\r\n    if (typeof this._minFaceSize !== 'number' || this._minFaceSize < 0) {\r\n      throw new Error(`${this._name} - expected minFaceSize to be a number > 0`)\r\n    }\r\n\r\n    if (typeof this._scaleFactor !== 'number' || this._scaleFactor <= 0 || this._scaleFactor >= 1) {\r\n      throw new Error(`${this._name} - expected scaleFactor to be a number between 0 and 1`)\r\n    }\r\n\r\n    if (typeof this._maxNumScales !== 'number' || this._maxNumScales < 0) {\r\n      throw new Error(`${this._name} - expected maxNumScales to be a number > 0`)\r\n    }\r\n\r\n    if (\r\n      !Array.isArray(this._scoreThresholds)\r\n        || this._scoreThresholds.length !== 3\r\n        || this._scoreThresholds.some(th => typeof th !== 'number')\r\n    ) {\r\n      throw new Error(`${this._name} - expected scoreThresholds to be an array of numbers of length 3`)\r\n    }\r\n\r\n    if (\r\n      this._scaleSteps\r\n        && (!Array.isArray(this._scaleSteps) || this._scaleSteps.some(th => typeof th !== 'number'))\r\n    ) {\r\n      throw new Error(`${this._name} - expected scaleSteps to be an array of numbers`)\r\n    }\r\n  }\r\n\r\n  get minFaceSize(): number { return this._minFaceSize }\r\n  get scaleFactor(): number { return this._scaleFactor }\r\n  get maxNumScales(): number { return this._maxNumScales }\r\n  get scoreThresholds(): number[] { return this._scoreThresholds }\r\n  get scaleSteps(): number[] | undefined { return this._scaleSteps }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ExtractWeightsFunction, ParamMapping, ConvParams, extractWeightsFactory } from '../common';\r\nimport { MobileNetV1, NetParams, PointwiseConvParams, PredictionLayerParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  function extractDepthwiseConvParams(numChannels: number, mappedPrefix: string): MobileNetV1.DepthwiseConvParams {\r\n\r\n    const filters = tf.tensor4d(extractWeights(3 * 3 * numChannels), [3, 3, numChannels, 1])\r\n    const batch_norm_scale = tf.tensor1d(extractWeights(numChannels))\r\n    const batch_norm_offset = tf.tensor1d(extractWeights(numChannels))\r\n    const batch_norm_mean = tf.tensor1d(extractWeights(numChannels))\r\n    const batch_norm_variance = tf.tensor1d(extractWeights(numChannels))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/filters` },\r\n      { paramPath: `${mappedPrefix}/batch_norm_scale` },\r\n      { paramPath: `${mappedPrefix}/batch_norm_offset` },\r\n      { paramPath: `${mappedPrefix}/batch_norm_mean` },\r\n      { paramPath: `${mappedPrefix}/batch_norm_variance` }\r\n    )\r\n\r\n    return {\r\n      filters,\r\n      batch_norm_scale,\r\n      batch_norm_offset,\r\n      batch_norm_mean,\r\n      batch_norm_variance\r\n    }\r\n  }\r\n\r\n  function extractConvParams(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    filterSize: number,\r\n    mappedPrefix: string,\r\n    isPointwiseConv?: boolean\r\n  ): ConvParams {\r\n\r\n    const filters = tf.tensor4d(\r\n      extractWeights(channelsIn * channelsOut * filterSize * filterSize),\r\n      [filterSize, filterSize, channelsIn, channelsOut]\r\n    )\r\n    const bias = tf.tensor1d(extractWeights(channelsOut))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/filters` },\r\n      { paramPath: `${mappedPrefix}/${isPointwiseConv ? 'batch_norm_offset' : 'bias'}` }\r\n    )\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractPointwiseConvParams(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    filterSize: number,\r\n    mappedPrefix: string\r\n  ): PointwiseConvParams {\r\n\r\n    const {\r\n      filters,\r\n      bias\r\n    } = extractConvParams(channelsIn, channelsOut, filterSize, mappedPrefix, true)\r\n\r\n    return {\r\n      filters,\r\n      batch_norm_offset: bias\r\n    }\r\n  }\r\n\r\n  function extractConvPairParams(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    mappedPrefix: string\r\n  ): MobileNetV1.ConvPairParams {\r\n\r\n    const depthwise_conv = extractDepthwiseConvParams(channelsIn, `${mappedPrefix}/depthwise_conv`)\r\n    const pointwise_conv = extractPointwiseConvParams(channelsIn, channelsOut, 1, `${mappedPrefix}/pointwise_conv`)\r\n\r\n    return { depthwise_conv, pointwise_conv }\r\n  }\r\n\r\n  function extractMobilenetV1Params(): MobileNetV1.Params {\r\n\r\n    const conv_0 = extractPointwiseConvParams(3, 32, 3, 'mobilenetv1/conv_0')\r\n\r\n    const conv_1 = extractConvPairParams(32, 64, 'mobilenetv1/conv_1')\r\n    const conv_2 = extractConvPairParams(64, 128, 'mobilenetv1/conv_2')\r\n    const conv_3 = extractConvPairParams(128, 128, 'mobilenetv1/conv_3')\r\n    const conv_4 = extractConvPairParams(128, 256, 'mobilenetv1/conv_4')\r\n    const conv_5 = extractConvPairParams(256, 256, 'mobilenetv1/conv_5')\r\n    const conv_6 = extractConvPairParams(256, 512, 'mobilenetv1/conv_6')\r\n    const conv_7 = extractConvPairParams(512, 512, 'mobilenetv1/conv_7')\r\n    const conv_8 = extractConvPairParams(512, 512, 'mobilenetv1/conv_8')\r\n    const conv_9 = extractConvPairParams(512, 512, 'mobilenetv1/conv_9')\r\n    const conv_10 = extractConvPairParams(512, 512, 'mobilenetv1/conv_10')\r\n    const conv_11 = extractConvPairParams(512, 512, 'mobilenetv1/conv_11')\r\n    const conv_12 = extractConvPairParams(512, 1024, 'mobilenetv1/conv_12')\r\n    const conv_13 = extractConvPairParams(1024, 1024, 'mobilenetv1/conv_13')\r\n\r\n    return {\r\n      conv_0,\r\n      conv_1,\r\n      conv_2,\r\n      conv_3,\r\n      conv_4,\r\n      conv_5,\r\n      conv_6,\r\n      conv_7,\r\n      conv_8,\r\n      conv_9,\r\n      conv_10,\r\n      conv_11,\r\n      conv_12,\r\n      conv_13\r\n    }\r\n  }\r\n\r\n  function extractPredictionLayerParams(): PredictionLayerParams {\r\n    const conv_0 = extractPointwiseConvParams(1024, 256, 1, 'prediction_layer/conv_0')\r\n    const conv_1 = extractPointwiseConvParams(256, 512, 3, 'prediction_layer/conv_1')\r\n    const conv_2 = extractPointwiseConvParams(512, 128, 1, 'prediction_layer/conv_2')\r\n    const conv_3 = extractPointwiseConvParams(128, 256, 3, 'prediction_layer/conv_3')\r\n    const conv_4 = extractPointwiseConvParams(256, 128, 1, 'prediction_layer/conv_4')\r\n    const conv_5 = extractPointwiseConvParams(128, 256, 3, 'prediction_layer/conv_5')\r\n    const conv_6 = extractPointwiseConvParams(256, 64, 1, 'prediction_layer/conv_6')\r\n    const conv_7 = extractPointwiseConvParams(64, 128, 3, 'prediction_layer/conv_7')\r\n\r\n    const box_encoding_0_predictor = extractConvParams(512, 12, 1, 'prediction_layer/box_predictor_0/box_encoding_predictor')\r\n    const class_predictor_0 = extractConvParams(512, 9, 1, 'prediction_layer/box_predictor_0/class_predictor')\r\n    const box_encoding_1_predictor = extractConvParams(1024, 24, 1, 'prediction_layer/box_predictor_1/box_encoding_predictor')\r\n    const class_predictor_1 = extractConvParams(1024, 18, 1, 'prediction_layer/box_predictor_1/class_predictor')\r\n    const box_encoding_2_predictor = extractConvParams(512, 24, 1, 'prediction_layer/box_predictor_2/box_encoding_predictor')\r\n    const class_predictor_2 = extractConvParams(512, 18, 1, 'prediction_layer/box_predictor_2/class_predictor')\r\n    const box_encoding_3_predictor = extractConvParams(256, 24, 1, 'prediction_layer/box_predictor_3/box_encoding_predictor')\r\n    const class_predictor_3 = extractConvParams(256, 18, 1, 'prediction_layer/box_predictor_3/class_predictor')\r\n    const box_encoding_4_predictor = extractConvParams(256, 24, 1, 'prediction_layer/box_predictor_4/box_encoding_predictor')\r\n    const class_predictor_4 = extractConvParams(256, 18, 1, 'prediction_layer/box_predictor_4/class_predictor')\r\n    const box_encoding_5_predictor = extractConvParams(128, 24, 1, 'prediction_layer/box_predictor_5/box_encoding_predictor')\r\n    const class_predictor_5 = extractConvParams(128, 18, 1, 'prediction_layer/box_predictor_5/class_predictor')\r\n\r\n    const box_predictor_0 = {\r\n      box_encoding_predictor: box_encoding_0_predictor,\r\n      class_predictor: class_predictor_0\r\n    }\r\n    const box_predictor_1 = {\r\n      box_encoding_predictor: box_encoding_1_predictor,\r\n      class_predictor: class_predictor_1\r\n    }\r\n    const box_predictor_2 = {\r\n      box_encoding_predictor: box_encoding_2_predictor,\r\n      class_predictor: class_predictor_2\r\n    }\r\n    const box_predictor_3 = {\r\n      box_encoding_predictor: box_encoding_3_predictor,\r\n      class_predictor: class_predictor_3\r\n    }\r\n    const box_predictor_4 = {\r\n      box_encoding_predictor: box_encoding_4_predictor,\r\n      class_predictor: class_predictor_4\r\n    }\r\n    const box_predictor_5 = {\r\n      box_encoding_predictor: box_encoding_5_predictor,\r\n      class_predictor: class_predictor_5\r\n    }\r\n\r\n    return {\r\n      conv_0,\r\n      conv_1,\r\n      conv_2,\r\n      conv_3,\r\n      conv_4,\r\n      conv_5,\r\n      conv_6,\r\n      conv_7,\r\n      box_predictor_0,\r\n      box_predictor_1,\r\n      box_predictor_2,\r\n      box_predictor_3,\r\n      box_predictor_4,\r\n      box_predictor_5\r\n    }\r\n  }\r\n\r\n  return {\r\n    extractMobilenetV1Params,\r\n    extractPredictionLayerParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(weights: Float32Array): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const {\r\n    extractMobilenetV1Params,\r\n    extractPredictionLayerParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const mobilenetv1 = extractMobilenetV1Params()\r\n  const prediction_layer = extractPredictionLayerParams()\r\n  const extra_dim = tf.tensor3d(\r\n    extractWeights(5118 * 4),\r\n    [1, 5118, 4]\r\n  )\r\n  const output_layer = {\r\n    extra_dim\r\n  }\r\n\r\n  paramMappings.push({ paramPath: 'output_layer/extra_dim' })\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    params: {\r\n      mobilenetv1,\r\n      prediction_layer,\r\n      output_layer\r\n    },\r\n    paramMappings\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, disposeUnusedWeightTensors, extractWeightEntryFactory, ParamMapping } from '../common';\r\nimport { isTensor3D } from '../utils';\r\nimport { BoxPredictionParams, MobileNetV1, NetParams, PointwiseConvParams, PredictionLayerParams } from './types';\r\n\r\nfunction extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractPointwiseConvParams(prefix: string, idx: number, mappedPrefix: string): PointwiseConvParams {\r\n\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/Conv2d_${idx}_pointwise/weights`, 4, `${mappedPrefix}/filters`)\r\n    const batch_norm_offset = extractWeightEntry<tf.Tensor1D>(`${prefix}/Conv2d_${idx}_pointwise/convolution_bn_offset`, 1, `${mappedPrefix}/batch_norm_offset`)\r\n\r\n    return { filters, batch_norm_offset }\r\n  }\r\n\r\n  function extractConvPairParams(idx: number): MobileNetV1.ConvPairParams {\r\n\r\n    const mappedPrefix = `mobilenetv1/conv_${idx}`\r\n    const prefixDepthwiseConv = `MobilenetV1/Conv2d_${idx}_depthwise`\r\n    const mappedPrefixDepthwiseConv = `${mappedPrefix}/depthwise_conv`\r\n    const mappedPrefixPointwiseConv = `${mappedPrefix}/pointwise_conv`\r\n\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefixDepthwiseConv}/depthwise_weights`, 4, `${mappedPrefixDepthwiseConv}/filters`)\r\n    const batch_norm_scale = extractWeightEntry<tf.Tensor1D>(`${prefixDepthwiseConv}/BatchNorm/gamma`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_scale`)\r\n    const batch_norm_offset = extractWeightEntry<tf.Tensor1D>(`${prefixDepthwiseConv}/BatchNorm/beta`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_offset`)\r\n    const batch_norm_mean = extractWeightEntry<tf.Tensor1D>(`${prefixDepthwiseConv}/BatchNorm/moving_mean`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_mean`)\r\n    const batch_norm_variance = extractWeightEntry<tf.Tensor1D>(`${prefixDepthwiseConv}/BatchNorm/moving_variance`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_variance`)\r\n\r\n    return {\r\n      depthwise_conv: {\r\n        filters,\r\n        batch_norm_scale,\r\n        batch_norm_offset,\r\n        batch_norm_mean,\r\n        batch_norm_variance\r\n      },\r\n      pointwise_conv: extractPointwiseConvParams('MobilenetV1', idx, mappedPrefixPointwiseConv)\r\n    }\r\n  }\r\n\r\n  function extractMobilenetV1Params(): MobileNetV1.Params {\r\n    return {\r\n      conv_0: extractPointwiseConvParams('MobilenetV1', 0, 'mobilenetv1/conv_0'),\r\n      conv_1: extractConvPairParams(1),\r\n      conv_2: extractConvPairParams(2),\r\n      conv_3: extractConvPairParams(3),\r\n      conv_4: extractConvPairParams(4),\r\n      conv_5: extractConvPairParams(5),\r\n      conv_6: extractConvPairParams(6),\r\n      conv_7: extractConvPairParams(7),\r\n      conv_8: extractConvPairParams(8),\r\n      conv_9: extractConvPairParams(9),\r\n      conv_10: extractConvPairParams(10),\r\n      conv_11: extractConvPairParams(11),\r\n      conv_12: extractConvPairParams(12),\r\n      conv_13: extractConvPairParams(13)\r\n    }\r\n  }\r\n\r\n  function extractConvParams(prefix: string, mappedPrefix: string): ConvParams {\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/weights`, 4, `${mappedPrefix}/filters`)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/biases`, 1, `${mappedPrefix}/bias`)\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractBoxPredictorParams(idx: number): BoxPredictionParams {\r\n\r\n    const box_encoding_predictor = extractConvParams(\r\n      `Prediction/BoxPredictor_${idx}/BoxEncodingPredictor`,\r\n      `prediction_layer/box_predictor_${idx}/box_encoding_predictor`\r\n    )\r\n    const class_predictor = extractConvParams(\r\n      `Prediction/BoxPredictor_${idx}/ClassPredictor`,\r\n      `prediction_layer/box_predictor_${idx}/class_predictor`\r\n    )\r\n\r\n    return { box_encoding_predictor, class_predictor }\r\n  }\r\n\r\n  function extractPredictionLayerParams(): PredictionLayerParams {\r\n    return {\r\n      conv_0: extractPointwiseConvParams('Prediction', 0, 'prediction_layer/conv_0'),\r\n      conv_1: extractPointwiseConvParams('Prediction', 1, 'prediction_layer/conv_1'),\r\n      conv_2: extractPointwiseConvParams('Prediction', 2, 'prediction_layer/conv_2'),\r\n      conv_3: extractPointwiseConvParams('Prediction', 3, 'prediction_layer/conv_3'),\r\n      conv_4: extractPointwiseConvParams('Prediction', 4, 'prediction_layer/conv_4'),\r\n      conv_5: extractPointwiseConvParams('Prediction', 5, 'prediction_layer/conv_5'),\r\n      conv_6: extractPointwiseConvParams('Prediction', 6, 'prediction_layer/conv_6'),\r\n      conv_7: extractPointwiseConvParams('Prediction', 7, 'prediction_layer/conv_7'),\r\n      box_predictor_0: extractBoxPredictorParams(0),\r\n      box_predictor_1: extractBoxPredictorParams(1),\r\n      box_predictor_2: extractBoxPredictorParams(2),\r\n      box_predictor_3: extractBoxPredictorParams(3),\r\n      box_predictor_4: extractBoxPredictorParams(4),\r\n      box_predictor_5: extractBoxPredictorParams(5)\r\n    }\r\n  }\r\n\r\n  return {\r\n    extractMobilenetV1Params,\r\n    extractPredictionLayerParams\r\n  }\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractMobilenetV1Params,\r\n    extractPredictionLayerParams\r\n  } = extractorsFactory(weightMap, paramMappings)\r\n\r\n  const extra_dim = weightMap['Output/extra_dim']\r\n  paramMappings.push({ originalPath: 'Output/extra_dim', paramPath: 'output_layer/extra_dim' })\r\n\r\n  if (!isTensor3D(extra_dim)) {\r\n    throw new Error(`expected weightMap['Output/extra_dim'] to be a Tensor3D, instead have ${extra_dim}`)\r\n  }\r\n\r\n  const params = {\r\n    mobilenetv1: extractMobilenetV1Params(),\r\n    prediction_layer: extractPredictionLayerParams(),\r\n    output_layer: {\r\n      extra_dim\r\n    }\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { PointwiseConvParams } from './types';\r\n\r\nexport function pointwiseConvLayer(\r\n  x: tf.Tensor4D,\r\n  params: PointwiseConvParams,\r\n  strides: [number, number]\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    let out = tf.conv2d(x, params.filters, strides, 'same')\r\n    out = tf.add(out, params.batch_norm_offset)\r\n    return tf.clipByValue(out, 0, 6)\r\n\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { pointwiseConvLayer } from './pointwiseConvLayer';\r\nimport { MobileNetV1 } from './types';\r\n\r\nconst epsilon = 0.0010000000474974513\r\n\r\nfunction depthwiseConvLayer(\r\n  x: tf.Tensor4D,\r\n  params: MobileNetV1.DepthwiseConvParams,\r\n  strides: [number, number]\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    let out = tf.depthwiseConv2d(x, params.filters, strides, 'same')\r\n    out = tf.batchNorm<tf.Rank.R4>(\r\n      out,\r\n      params.batch_norm_mean,\r\n      params.batch_norm_variance,\r\n      params.batch_norm_offset,\r\n      params.batch_norm_scale,\r\n      epsilon\r\n    )\r\n    return tf.clipByValue(out, 0, 6)\r\n\r\n  })\r\n}\r\n\r\nfunction getStridesForLayerIdx(layerIdx: number): [number, number] {\r\n  return [2, 4, 6, 12].some(idx => idx === layerIdx) ? [2, 2] : [1, 1]\r\n}\r\n\r\nexport function mobileNetV1(x: tf.Tensor4D, params: MobileNetV1.Params) {\r\n  return tf.tidy(() => {\r\n\r\n    let conv11 = null\r\n    let out = pointwiseConvLayer(x, params.conv_0, [2, 2])\r\n\r\n    const convPairParams = [\r\n      params.conv_1,\r\n      params.conv_2,\r\n      params.conv_3,\r\n      params.conv_4,\r\n      params.conv_5,\r\n      params.conv_6,\r\n      params.conv_7,\r\n      params.conv_8,\r\n      params.conv_9,\r\n      params.conv_10,\r\n      params.conv_11,\r\n      params.conv_12,\r\n      params.conv_13\r\n    ]\r\n\r\n    convPairParams.forEach((param, i) => {\r\n      const layerIdx = i + 1\r\n      const depthwiseConvStrides = getStridesForLayerIdx(layerIdx)\r\n      out = depthwiseConvLayer(out, param.depthwise_conv, depthwiseConvStrides)\r\n      out = pointwiseConvLayer(out, param.pointwise_conv, [1, 1])\r\n      if (layerIdx === 11) {\r\n        conv11 = out\r\n      }\r\n    })\r\n\r\n    if (conv11 === null) {\r\n      throw new Error('mobileNetV1 - output of conv layer 11 is null')\r\n    }\r\n\r\n    return {\r\n      out,\r\n      conv11: conv11 as any\r\n    }\r\n\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core'\r\n\r\nexport function nonMaxSuppression(\r\n  boxes: tf.Tensor2D,\r\n  scores: number[],\r\n  maxOutputSize: number,\r\n  iouThreshold: number,\r\n  scoreThreshold: number\r\n): number[] {\r\n\r\n  const numBoxes = boxes.shape[0]\r\n  const outputSize = Math.min(\r\n    maxOutputSize,\r\n    numBoxes\r\n  )\r\n\r\n  const candidates = scores\r\n    .map((score, boxIndex) => ({ score, boxIndex }))\r\n    .filter(c => c.score > scoreThreshold)\r\n    .sort((c1, c2) => c2.score - c1.score)\r\n\r\n  const suppressFunc = (x: number) => x <= iouThreshold ? 1 : 0\r\n\r\n  const selected: number[] = []\r\n\r\n  candidates.forEach(c => {\r\n    if (selected.length >= outputSize) {\r\n      return\r\n    }\r\n    const originalScore = c.score\r\n\r\n    for (let j = selected.length - 1; j >= 0; --j) {\r\n      const iou = IOU(boxes, c.boxIndex, selected[j])\r\n      if (iou === 0.0) {\r\n        continue\r\n      }\r\n      c.score *= suppressFunc(iou)\r\n      if (c.score <= scoreThreshold) {\r\n        break\r\n      }\r\n    }\r\n\r\n    if (originalScore === c.score) {\r\n      selected.push(c.boxIndex)\r\n    }\r\n  })\r\n\r\n  return selected\r\n}\r\n\r\nfunction IOU(boxes: tf.Tensor2D, i: number, j: number) {\r\n  const boxesData = boxes.arraySync()\r\n  const yminI = Math.min(boxesData[i][0], boxesData[i][2])\r\n  const xminI = Math.min(boxesData[i][1], boxesData[i][3])\r\n  const ymaxI = Math.max(boxesData[i][0], boxesData[i][2])\r\n  const xmaxI = Math.max(boxesData[i][1], boxesData[i][3])\r\n  const yminJ = Math.min(boxesData[j][0], boxesData[j][2])\r\n  const xminJ = Math.min(boxesData[j][1], boxesData[j][3])\r\n  const ymaxJ = Math.max(boxesData[j][0], boxesData[j][2])\r\n  const xmaxJ = Math.max(boxesData[j][1], boxesData[j][3])\r\n  const areaI = (ymaxI - yminI) * (xmaxI - xminI)\r\n  const areaJ = (ymaxJ - yminJ) * (xmaxJ - xminJ)\r\n  if (areaI <= 0 || areaJ <= 0) {\r\n    return 0.0\r\n  }\r\n  const intersectionYmin = Math.max(yminI, yminJ)\r\n  const intersectionXmin = Math.max(xminI, xminJ)\r\n  const intersectionYmax = Math.min(ymaxI, ymaxJ)\r\n  const intersectionXmax = Math.min(xmaxI, xmaxJ)\r\n  const intersectionArea =\r\n      Math.max(intersectionYmax - intersectionYmin, 0.0) *\r\n      Math.max(intersectionXmax - intersectionXmin, 0.0)\r\n  return intersectionArea / (areaI + areaJ - intersectionArea)\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { OutputLayerParams } from './types';\r\n\r\n\r\nfunction getCenterCoordinatesAndSizesLayer(x: tf.Tensor2D) {\r\n  const vec = tf.unstack(tf.transpose(x, [1, 0]))\r\n\r\n  const sizes = [\r\n    tf.sub(vec[2], vec[0]),\r\n    tf.sub(vec[3], vec[1])\r\n  ]\r\n\r\n  const centers = [\r\n    tf.add(vec[0], tf.div(sizes[0], tf.scalar(2))),\r\n    tf.add(vec[1], tf.div(sizes[1], tf.scalar(2)))\r\n  ]\r\n\r\n  return {\r\n    sizes,\r\n    centers\r\n  }\r\n}\r\n\r\nfunction decodeBoxesLayer(x0: tf.Tensor2D, x1: tf.Tensor2D) {\r\n  const {\r\n    sizes,\r\n    centers\r\n  } = getCenterCoordinatesAndSizesLayer(x0)\r\n\r\n  const vec = tf.unstack(tf.transpose(x1, [1, 0]))\r\n\r\n  const div0_out = tf.div(tf.mul(tf.exp(tf.div(vec[2], tf.scalar(5))), sizes[0]), tf.scalar(2))\r\n  const add0_out = tf.add(tf.mul(tf.div(vec[0], tf.scalar(10)), sizes[0]), centers[0])\r\n\r\n  const div1_out = tf.div(tf.mul(tf.exp(tf.div(vec[3], tf.scalar(5))), sizes[1]), tf.scalar(2))\r\n  const add1_out = tf.add(tf.mul(tf.div(vec[1], tf.scalar(10)), sizes[1]), centers[1])\r\n\r\n  return tf.transpose(\r\n    tf.stack([\r\n      tf.sub(add0_out, div0_out),\r\n      tf.sub(add1_out, div1_out),\r\n      tf.add(add0_out, div0_out),\r\n      tf.add(add1_out, div1_out)\r\n    ]),\r\n    [1, 0]\r\n  )\r\n}\r\n\r\nexport function outputLayer(\r\n  boxPredictions: tf.Tensor4D,\r\n  classPredictions: tf.Tensor4D,\r\n  params: OutputLayerParams\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    const batchSize = boxPredictions.shape[0]\r\n\r\n    let boxes = decodeBoxesLayer(\r\n      tf.reshape(tf.tile(params.extra_dim, [batchSize, 1, 1]), [-1, 4]) as tf.Tensor2D,\r\n      tf.reshape(boxPredictions, [-1, 4]) as tf.Tensor2D\r\n    )\r\n    boxes = tf.reshape(\r\n      boxes,\r\n      [batchSize, (boxes.shape[0] / batchSize), 4]\r\n    )\r\n\r\n    const scoresAndClasses = tf.sigmoid(tf.slice(classPredictions, [0, 0, 1], [-1, -1, -1]))\r\n    let scores = tf.slice(scoresAndClasses, [0, 0, 0], [-1, -1, 1]) as tf.Tensor\r\n\r\n    scores = tf.reshape(\r\n      scores,\r\n      [batchSize, scores.shape[1] as number]\r\n    )\r\n\r\n    const boxesByBatch = tf.unstack(boxes) as tf.Tensor2D[]\r\n    const scoresByBatch = tf.unstack(scores) as tf.Tensor1D[]\r\n\r\n    return {\r\n      boxes: boxesByBatch,\r\n      scores: scoresByBatch\r\n    }\r\n\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { convLayer } from '../common';\r\nimport { BoxPredictionParams } from './types';\r\n\r\n\r\nexport function boxPredictionLayer(\r\n  x: tf.Tensor4D,\r\n  params: BoxPredictionParams\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    const batchSize = x.shape[0]\r\n\r\n    const boxPredictionEncoding = tf.reshape(\r\n      convLayer(x, params.box_encoding_predictor),\r\n      [batchSize, -1, 1, 4]\r\n    )\r\n    const classPrediction = tf.reshape(\r\n      convLayer(x, params.class_predictor),\r\n      [batchSize, -1, 3]\r\n    )\r\n\r\n    return {\r\n      boxPredictionEncoding,\r\n      classPrediction\r\n    }\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { boxPredictionLayer } from './boxPredictionLayer';\r\nimport { pointwiseConvLayer } from './pointwiseConvLayer';\r\nimport { PredictionLayerParams } from './types';\r\n\r\nexport function predictionLayer(\r\n  x: tf.Tensor4D,\r\n  conv11: tf.Tensor4D,\r\n  params: PredictionLayerParams\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    const conv0 = pointwiseConvLayer(x, params.conv_0, [1, 1])\r\n    const conv1 = pointwiseConvLayer(conv0, params.conv_1, [2, 2])\r\n    const conv2 = pointwiseConvLayer(conv1, params.conv_2, [1, 1])\r\n    const conv3 = pointwiseConvLayer(conv2, params.conv_3, [2, 2])\r\n    const conv4 = pointwiseConvLayer(conv3, params.conv_4, [1, 1])\r\n    const conv5 = pointwiseConvLayer(conv4, params.conv_5, [2, 2])\r\n    const conv6 = pointwiseConvLayer(conv5, params.conv_6, [1, 1])\r\n    const conv7 = pointwiseConvLayer(conv6, params.conv_7, [2, 2])\r\n\r\n    const boxPrediction0 = boxPredictionLayer(conv11, params.box_predictor_0)\r\n    const boxPrediction1 = boxPredictionLayer(x, params.box_predictor_1)\r\n    const boxPrediction2 = boxPredictionLayer(conv1, params.box_predictor_2)\r\n    const boxPrediction3 = boxPredictionLayer(conv3, params.box_predictor_3)\r\n    const boxPrediction4 = boxPredictionLayer(conv5, params.box_predictor_4)\r\n    const boxPrediction5 = boxPredictionLayer(conv7, params.box_predictor_5)\r\n\r\n    const boxPredictions = tf.concat([\r\n      boxPrediction0.boxPredictionEncoding,\r\n      boxPrediction1.boxPredictionEncoding,\r\n      boxPrediction2.boxPredictionEncoding,\r\n      boxPrediction3.boxPredictionEncoding,\r\n      boxPrediction4.boxPredictionEncoding,\r\n      boxPrediction5.boxPredictionEncoding\r\n    ], 1) as tf.Tensor4D\r\n\r\n    const classPredictions = tf.concat([\r\n      boxPrediction0.classPrediction,\r\n      boxPrediction1.classPrediction,\r\n      boxPrediction2.classPrediction,\r\n      boxPrediction3.classPrediction,\r\n      boxPrediction4.classPrediction,\r\n      boxPrediction5.classPrediction\r\n    ], 1) as tf.Tensor4D\r\n\r\n    return {\r\n      boxPredictions,\r\n      classPredictions\r\n    }\r\n  })\r\n}","export interface ISsdMobilenetv1Options {\r\n  minConfidence?: number\r\n  maxResults?: number\r\n}\r\n\r\nexport class SsdMobilenetv1Options {\r\n  protected _name: string = 'SsdMobilenetv1Options'\r\n\r\n  private _minConfidence: number\r\n  private _maxResults: number\r\n\r\n  constructor({ minConfidence, maxResults }: ISsdMobilenetv1Options = {}) {\r\n    this._minConfidence = minConfidence || 0.5\r\n    this._maxResults = maxResults || 100\r\n\r\n    if (typeof this._minConfidence !== 'number' || this._minConfidence <= 0 || this._minConfidence >= 1) {\r\n      throw new Error(`${this._name} - expected minConfidence to be a number between 0 and 1`)\r\n    }\r\n\r\n    if (typeof this._maxResults !== 'number') {\r\n      throw new Error(`${this._name} - expected maxResults to be a number`)\r\n    }\r\n  }\r\n\r\n  get minConfidence(): number { return this._minConfidence }\r\n  get maxResults(): number { return this._maxResults }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Rect } from '../classes';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { mobileNetV1 } from './mobileNetV1';\r\nimport { nonMaxSuppression } from './nonMaxSuppression';\r\nimport { outputLayer } from './outputLayer';\r\nimport { predictionLayer } from './predictionLayer';\r\nimport { ISsdMobilenetv1Options, SsdMobilenetv1Options } from './SsdMobilenetv1Options';\r\nimport { NetParams } from './types';\r\n\r\n\r\nexport class SsdMobilenetv1 extends NeuralNetwork<NetParams> {\r\n\r\n  constructor() {\r\n    super('SsdMobilenetv1')\r\n  }\r\n\r\n  public forwardInput(input: NetInput) {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('SsdMobilenetv1 - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(512, false).toFloat()\r\n\r\n      const x = tf.sub(tf.mul(batchTensor, tf.scalar(0.007843137718737125)), tf.scalar(1)) as tf.Tensor4D\r\n      const features = mobileNetV1(x, params.mobilenetv1)\r\n\r\n      const {\r\n        boxPredictions,\r\n        classPredictions\r\n      } = predictionLayer(features.out, features.conv11, params.prediction_layer)\r\n\r\n      return outputLayer(boxPredictions, classPredictions, params.output_layer)\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput) {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async locateFaces(\r\n    input: TNetInput,\r\n    options: ISsdMobilenetv1Options = {}\r\n  ): Promise<FaceDetection[]> {\r\n\r\n    const { maxResults, minConfidence } = new SsdMobilenetv1Options(options)\r\n\r\n    const netInput = await toNetInput(input)\r\n\r\n    const {\r\n      boxes: _boxes,\r\n      scores: _scores\r\n    } = this.forwardInput(netInput)\r\n\r\n\r\n    // TODO batches\r\n    const boxes = _boxes[0]\r\n    const scores = _scores[0]\r\n    for (let i = 1; i < _boxes.length; i++) {\r\n      _boxes[i].dispose()\r\n      _scores[i].dispose()\r\n    }\r\n\r\n    // TODO find a better way to filter by minConfidence\r\n    const scoresData = Array.from(await scores.data())\r\n\r\n    const iouThreshold = 0.5\r\n    const indices = nonMaxSuppression(\r\n      boxes,\r\n      scoresData,\r\n      maxResults,\r\n      iouThreshold,\r\n      minConfidence\r\n    )\r\n\r\n    const reshapedDims = netInput.getReshapedInputDimensions(0)\r\n    const inputSize = netInput.inputSize as number\r\n    const padX = inputSize / reshapedDims.width\r\n    const padY = inputSize / reshapedDims.height\r\n\r\n    const boxesData = boxes.arraySync()\r\n    const results = indices\r\n      .map(idx => {\r\n        const [top, bottom] = [\r\n          Math.max(0, boxesData[idx][0]),\r\n          Math.min(1.0, boxesData[idx][2])\r\n        ].map(val => val * padY)\r\n        const [left, right] = [\r\n          Math.max(0, boxesData[idx][1]),\r\n          Math.min(1.0, boxesData[idx][3])\r\n        ].map(val => val * padX)\r\n        return new FaceDetection(\r\n          scoresData[idx],\r\n          new Rect(\r\n            left,\r\n            top,\r\n            right - left,\r\n            bottom - top\r\n          ),\r\n          {\r\n            height: netInput.getInputHeight(0),\r\n            width: netInput.getInputWidth(0)\r\n          }\r\n        )\r\n      })\r\n\r\n    boxes.dispose()\r\n    scores.dispose()\r\n\r\n    return results\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'ssd_mobilenetv1_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n}","import { SsdMobilenetv1 } from './SsdMobilenetv1';\r\n\r\nexport * from './SsdMobilenetv1';\r\nexport * from './SsdMobilenetv1Options';\r\n\r\nexport function createSsdMobilenetv1(weights: Float32Array) {\r\n  const net = new SsdMobilenetv1()\r\n  net.extractWeights(weights)\r\n  return net\r\n}\r\n\r\nexport function createFaceDetectionNet(weights: Float32Array) {\r\n  return createSsdMobilenetv1(weights)\r\n}\r\n\r\n// alias for backward compatibily\r\nexport class FaceDetectionNet extends SsdMobilenetv1 {}","import { Point } from '../classes';\r\n\r\nexport const IOU_THRESHOLD = 0.4\r\n\r\nexport const BOX_ANCHORS = [\r\n  new Point(0.738768, 0.874946),\r\n  new Point(2.42204, 2.65704),\r\n  new Point(4.30971, 7.04493),\r\n  new Point(10.246, 4.59428),\r\n  new Point(12.6868, 11.8741)\r\n]\r\n\r\nexport const BOX_ANCHORS_SEPARABLE = [\r\n  new Point(1.603231, 2.094468),\r\n  new Point(6.041143, 7.080126),\r\n  new Point(2.882459, 3.518061),\r\n  new Point(4.266906, 5.178857),\r\n  new Point(9.041765, 10.66308)\r\n]\r\n\r\nexport const MEAN_RGB_SEPARABLE: [number, number, number] = [117.001, 114.697, 97.404]\r\n\r\nexport const DEFAULT_MODEL_NAME = 'tiny_yolov2_model'\r\nexport const DEFAULT_MODEL_NAME_SEPARABLE_CONV = 'tiny_yolov2_separable_conv_model'","import { Point } from '../classes/Point';\r\n\r\nexport type TinyYolov2Config = {\r\n  withSeparableConvs: boolean\r\n  iouThreshold: number\r\n  anchors: Point[]\r\n  classes: string[]\r\n  meanRgb?: [number, number, number]\r\n  withClassScores?: boolean,\r\n  filterSizes?: number[]\r\n  isFirstLayerConv2d?: boolean\r\n}\r\n\r\nconst isNumber = (arg: any) => typeof arg === 'number'\r\n\r\nexport function validateConfig(config: any) {\r\n  if (!config) {\r\n    throw new Error(`invalid config: ${config}`)\r\n  }\r\n\r\n  if (typeof config.withSeparableConvs !== 'boolean') {\r\n    throw new Error(`config.withSeparableConvs has to be a boolean, have: ${config.withSeparableConvs}`)\r\n  }\r\n\r\n  if (!isNumber(config.iouThreshold) || config.iouThreshold < 0 || config.iouThreshold > 1.0) {\r\n    throw new Error(`config.iouThreshold has to be a number between [0, 1], have: ${config.iouThreshold}`)\r\n  }\r\n\r\n  if (\r\n    !Array.isArray(config.classes)\r\n    || !config.classes.length\r\n    || !config.classes.every((c: any) => typeof c === 'string')\r\n  ) {\r\n\r\n    throw new Error(`config.classes has to be an array class names: string[], have: ${JSON.stringify(config.classes)}`)\r\n  }\r\n\r\n  if (\r\n    !Array.isArray(config.anchors)\r\n    || !config.anchors.length\r\n    || !config.anchors.map((a: any) => a || {}).every((a: any) => isNumber(a.x) && isNumber(a.y))\r\n  ) {\r\n\r\n    throw new Error(`config.anchors has to be an array of { x: number, y: number }, have: ${JSON.stringify(config.anchors)}`)\r\n  }\r\n\r\n  if (config.meanRgb && (\r\n    !Array.isArray(config.meanRgb)\r\n    || config.meanRgb.length !== 3\r\n    || !config.meanRgb.every(isNumber)\r\n  )) {\r\n\r\n    throw new Error(`config.meanRgb has to be an array of shape [number, number, number], have: ${JSON.stringify(config.meanRgb)}`)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function leaky(x: tf.Tensor4D): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const min = tf.mul(x, tf.scalar(0.10000000149011612))\r\n    return tf.add(tf.relu(tf.sub(x, min)), min)\r\n    //return tf.maximum(x, min)\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { leaky } from './leaky';\r\nimport { ConvWithBatchNorm } from './types';\r\n\r\nexport function convWithBatchNorm(x: tf.Tensor4D, params: ConvWithBatchNorm): tf.Tensor4D  {\r\n  return tf.tidy(() => {\r\n    let out = tf.pad(x, [[0, 0], [1, 1], [1, 1], [0, 0]]) as tf.Tensor4D\r\n\r\n    out = tf.conv2d(out, params.conv.filters, [1, 1], 'valid')\r\n    out = tf.sub(out, params.bn.sub)\r\n    out = tf.mul(out, params.bn.truediv)\r\n    out = tf.add(out, params.conv.bias)\r\n\r\n    return leaky(out)\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { SeparableConvParams } from '../common/types';\r\nimport { leaky } from './leaky';\r\n\r\nexport function depthwiseSeparableConv(x: tf.Tensor4D, params: SeparableConvParams): tf.Tensor4D  {\r\n  return tf.tidy(() => {\r\n    let out = tf.pad(x, [[0, 0], [1, 1], [1, 1], [0, 0]]) as tf.Tensor4D\r\n\r\n    out = tf.separableConv2d(out, params.depthwise_filter, params.pointwise_filter, [1, 1], 'valid')\r\n    out = tf.add(out, params.bias)\r\n\r\n    return leaky(out)\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { extractConvParamsFactory } from '../common';\r\nimport { extractSeparableConvParamsFactory } from '../common/extractSeparableConvParamsFactory';\r\nimport { extractWeightsFactory } from '../common/extractWeightsFactory';\r\nimport { ExtractWeightsFunction, ParamMapping } from '../common/types';\r\nimport { TinyYolov2Config } from './config';\r\nimport { BatchNorm, ConvWithBatchNorm, TinyYolov2NetParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  const extractConvParams = extractConvParamsFactory(extractWeights, paramMappings)\r\n\r\n  function extractBatchNormParams(size: number, mappedPrefix: string): BatchNorm {\r\n\r\n    const sub = tf.tensor1d(extractWeights(size))\r\n    const truediv = tf.tensor1d(extractWeights(size))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/sub` },\r\n      { paramPath: `${mappedPrefix}/truediv` }\r\n    )\r\n\r\n    return { sub, truediv }\r\n  }\r\n\r\n  function extractConvWithBatchNormParams(channelsIn: number, channelsOut: number, mappedPrefix: string): ConvWithBatchNorm {\r\n\r\n    const conv = extractConvParams(channelsIn, channelsOut, 3, `${mappedPrefix}/conv`)\r\n    const bn = extractBatchNormParams(channelsOut, `${mappedPrefix}/bn`)\r\n\r\n    return { conv, bn }\r\n  }\r\n  const extractSeparableConvParams = extractSeparableConvParamsFactory(extractWeights, paramMappings)\r\n\r\n  return {\r\n    extractConvParams,\r\n    extractConvWithBatchNormParams,\r\n    extractSeparableConvParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(\r\n  weights: Float32Array,\r\n  config: TinyYolov2Config,\r\n  boxEncodingSize: number,\r\n  filterSizes: number[]\r\n): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvParams,\r\n    extractConvWithBatchNormParams,\r\n    extractSeparableConvParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  let params: TinyYolov2NetParams\r\n\r\n  if (config.withSeparableConvs) {\r\n    const [s0, s1, s2, s3, s4, s5, s6, s7, s8] = filterSizes\r\n\r\n    const conv0 = config.isFirstLayerConv2d\r\n      ? extractConvParams(s0, s1, 3, 'conv0')\r\n      : extractSeparableConvParams(s0, s1, 'conv0')\r\n    const conv1 = extractSeparableConvParams(s1, s2, 'conv1')\r\n    const conv2 = extractSeparableConvParams(s2, s3, 'conv2')\r\n    const conv3 = extractSeparableConvParams(s3, s4, 'conv3')\r\n    const conv4 = extractSeparableConvParams(s4, s5, 'conv4')\r\n    const conv5 = extractSeparableConvParams(s5, s6, 'conv5')\r\n    const conv6 = s7 ? extractSeparableConvParams(s6, s7, 'conv6') : undefined\r\n    const conv7 = s8 ? extractSeparableConvParams(s7, s8, 'conv7') : undefined\r\n    const conv8 = extractConvParams(s8 || s7 || s6, 5 * boxEncodingSize, 1, 'conv8')\r\n    params = { conv0, conv1, conv2, conv3, conv4, conv5, conv6, conv7, conv8 }\r\n  } else {\r\n    const [s0, s1, s2, s3, s4, s5, s6, s7, s8] = filterSizes\r\n    const conv0 = extractConvWithBatchNormParams(s0, s1, 'conv0',)\r\n    const conv1 = extractConvWithBatchNormParams(s1, s2, 'conv1')\r\n    const conv2 = extractConvWithBatchNormParams(s2, s3, 'conv2')\r\n    const conv3 = extractConvWithBatchNormParams(s3, s4, 'conv3')\r\n    const conv4 = extractConvWithBatchNormParams(s4, s5, 'conv4')\r\n    const conv5 = extractConvWithBatchNormParams(s5, s6, 'conv5')\r\n    const conv6 = extractConvWithBatchNormParams(s6, s7, 'conv6')\r\n    const conv7 = extractConvWithBatchNormParams(s7, s8, 'conv7')\r\n    const conv8 = extractConvParams(s8, 5 * boxEncodingSize, 1, 'conv8')\r\n    params = { conv0, conv1, conv2, conv3, conv4, conv5, conv6, conv7, conv8 }\r\n  }\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams } from '../common';\r\nimport { disposeUnusedWeightTensors } from '../common/disposeUnusedWeightTensors';\r\nimport { loadSeparableConvParamsFactory } from '../common/extractSeparableConvParamsFactory';\r\nimport { extractWeightEntryFactory } from '../common/extractWeightEntryFactory';\r\nimport { ParamMapping } from '../common/types';\r\nimport { TinyYolov2Config } from './config';\r\nimport { BatchNorm, ConvWithBatchNorm, TinyYolov2NetParams } from './types';\r\n\r\nfunction extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractBatchNormParams(prefix: string): BatchNorm {\r\n    const sub = extractWeightEntry<tf.Tensor1D>(`${prefix}/sub`, 1)\r\n    const truediv = extractWeightEntry<tf.Tensor1D>(`${prefix}/truediv`, 1)\r\n    return { sub, truediv }\r\n  }\r\n\r\n  function extractConvParams(prefix: string): ConvParams {\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/filters`, 4)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractConvWithBatchNormParams(prefix: string): ConvWithBatchNorm {\r\n    const conv = extractConvParams(`${prefix}/conv`)\r\n    const bn = extractBatchNormParams(`${prefix}/bn`)\r\n    return { conv, bn }\r\n  }\r\n\r\n  const extractSeparableConvParams = loadSeparableConvParamsFactory(extractWeightEntry)\r\n\r\n  return {\r\n    extractConvParams,\r\n    extractConvWithBatchNormParams,\r\n    extractSeparableConvParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap,\r\n  config: TinyYolov2Config\r\n): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvParams,\r\n    extractConvWithBatchNormParams,\r\n    extractSeparableConvParams\r\n  } = extractorsFactory(weightMap, paramMappings)\r\n\r\n  let params: TinyYolov2NetParams\r\n\r\n  if (config.withSeparableConvs) {\r\n    const numFilters = (config.filterSizes && config.filterSizes.length || 9)\r\n    params = {\r\n      conv0: config.isFirstLayerConv2d ? extractConvParams('conv0') : extractSeparableConvParams('conv0'),\r\n      conv1: extractSeparableConvParams('conv1'),\r\n      conv2: extractSeparableConvParams('conv2'),\r\n      conv3: extractSeparableConvParams('conv3'),\r\n      conv4: extractSeparableConvParams('conv4'),\r\n      conv5: extractSeparableConvParams('conv5'),\r\n      conv6: numFilters > 7 ? extractSeparableConvParams('conv6') : undefined,\r\n      conv7: numFilters > 8 ? extractSeparableConvParams('conv7') : undefined,\r\n      conv8: extractConvParams('conv8')\r\n    }\r\n  } else {\r\n    params = {\r\n      conv0: extractConvWithBatchNormParams('conv0'),\r\n      conv1: extractConvWithBatchNormParams('conv1'),\r\n      conv2: extractConvWithBatchNormParams('conv2'),\r\n      conv3: extractConvWithBatchNormParams('conv3'),\r\n      conv4: extractConvWithBatchNormParams('conv4'),\r\n      conv5: extractConvWithBatchNormParams('conv5'),\r\n      conv6: extractConvWithBatchNormParams('conv6'),\r\n      conv7: extractConvWithBatchNormParams('conv7'),\r\n      conv8: extractConvParams('conv8')\r\n    }\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","export enum TinyYolov2SizeType {\r\n  XS = 224,\r\n  SM = 320,\r\n  MD = 416,\r\n  LG = 608\r\n}\r\n\r\nexport interface ITinyYolov2Options {\r\n  inputSize?: number\r\n  scoreThreshold?: number\r\n}\r\n\r\nexport class TinyYolov2Options {\r\n  protected _name: string = 'TinyYolov2Options'\r\n\r\n  private _inputSize: number\r\n  private _scoreThreshold: number\r\n\r\n  constructor({ inputSize, scoreThreshold }: ITinyYolov2Options = {}) {\r\n    this._inputSize = inputSize || 416\r\n    this._scoreThreshold = scoreThreshold || 0.5\r\n\r\n    if (typeof this._inputSize !== 'number' || this._inputSize % 32 !== 0) {\r\n      throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`)\r\n    }\r\n\r\n    if (typeof this._scoreThreshold !== 'number' || this._scoreThreshold <= 0 || this._scoreThreshold >= 1) {\r\n      throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)\r\n    }\r\n  }\r\n\r\n  get inputSize(): number { return this._inputSize }\r\n  get scoreThreshold(): number { return this._scoreThreshold }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { BoundingBox } from '../classes/BoundingBox';\r\nimport { Dimensions } from '../classes/Dimensions';\r\nimport { ObjectDetection } from '../classes/ObjectDetection';\r\nimport { convLayer } from '../common';\r\nimport { ConvParams, SeparableConvParams } from '../common/types';\r\nimport { toNetInput } from '../dom';\r\nimport { NetInput } from '../dom/NetInput';\r\nimport { TNetInput } from '../dom/types';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { sigmoid } from '../ops';\r\nimport { nonMaxSuppression } from '../ops/nonMaxSuppression';\r\nimport { normalize } from '../ops/normalize';\r\nimport { TinyYolov2Config, validateConfig } from './config';\r\nimport { convWithBatchNorm } from './convWithBatchNorm';\r\nimport { depthwiseSeparableConv } from './depthwiseSeparableConv';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { leaky } from './leaky';\r\nimport { ITinyYolov2Options, TinyYolov2Options } from './TinyYolov2Options';\r\nimport { DefaultTinyYolov2NetParams, MobilenetParams, TinyYolov2NetParams } from './types';\r\n\r\nexport class TinyYolov2Base extends NeuralNetwork<TinyYolov2NetParams> {\r\n\r\n  public static DEFAULT_FILTER_SIZES = [\r\n    3, 16, 32, 64, 128, 256, 512, 1024, 1024\r\n  ]\r\n\r\n  private _config: TinyYolov2Config\r\n\r\n  constructor(config: TinyYolov2Config) {\r\n    super('TinyYolov2')\r\n    validateConfig(config)\r\n    this._config = config\r\n  }\r\n\r\n  public get config(): TinyYolov2Config {\r\n    return this._config\r\n  }\r\n\r\n  public get withClassScores(): boolean {\r\n    return this.config.withClassScores || this.config.classes.length > 1\r\n  }\r\n\r\n  public get boxEncodingSize(): number {\r\n    return 5 + (this.withClassScores ? this.config.classes.length : 0)\r\n  }\r\n\r\n  public runTinyYolov2(x: tf.Tensor4D, params: DefaultTinyYolov2NetParams): tf.Tensor4D {\r\n\r\n    let out = convWithBatchNorm(x, params.conv0)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv1)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv2)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv3)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv4)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv5)\r\n    out = tf.maxPool(out, [2, 2], [1, 1], 'same')\r\n    out = convWithBatchNorm(out, params.conv6)\r\n    out = convWithBatchNorm(out, params.conv7)\r\n\r\n    return convLayer(out, params.conv8, 'valid', false)\r\n  }\r\n\r\n  public runMobilenet(x: tf.Tensor4D, params: MobilenetParams): tf.Tensor4D {\r\n\r\n    let out = this.config.isFirstLayerConv2d\r\n      ? leaky(convLayer(x, params.conv0 as ConvParams, 'valid', false))\r\n      : depthwiseSeparableConv(x, params.conv0 as SeparableConvParams)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv1)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv2)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv3)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv4)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv5)\r\n    out = tf.maxPool(out, [2, 2], [1, 1], 'same')\r\n    out = params.conv6 ? depthwiseSeparableConv(out, params.conv6) : out\r\n    out = params.conv7 ? depthwiseSeparableConv(out, params.conv7) : out\r\n\r\n    return convLayer(out, params.conv8, 'valid', false)\r\n  }\r\n\r\n  public forwardInput(input: NetInput, inputSize: number): tf.Tensor4D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('TinyYolov2 - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n\r\n      let batchTensor = input.toBatchTensor(inputSize, false).toFloat()\r\n      batchTensor = this.config.meanRgb\r\n        ? normalize(batchTensor, this.config.meanRgb)\r\n        : batchTensor\r\n      batchTensor = batchTensor.div(tf.scalar(256)) as tf.Tensor4D\r\n\r\n      return this.config.withSeparableConvs\r\n        ? this.runMobilenet(batchTensor, params as MobilenetParams)\r\n        : this.runTinyYolov2(batchTensor, params as DefaultTinyYolov2NetParams)\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput, inputSize: number): Promise<tf.Tensor4D> {\r\n    return await this.forwardInput(await toNetInput(input), inputSize)\r\n  }\r\n\r\n  public async detect(input: TNetInput, forwardParams: ITinyYolov2Options = {}): Promise<ObjectDetection[]> {\r\n\r\n    const { inputSize, scoreThreshold } = new TinyYolov2Options(forwardParams)\r\n\r\n    const netInput = await toNetInput(input)\r\n    const out = await this.forwardInput(netInput, inputSize)\r\n    const out0 = tf.tidy(() => tf.unstack(out)[0].expandDims()) as tf.Tensor4D\r\n\r\n    const inputDimensions = {\r\n      width: netInput.getInputWidth(0),\r\n      height: netInput.getInputHeight(0)\r\n    }\r\n\r\n    const results = await this.extractBoxes(out0, netInput.getReshapedInputDimensions(0), scoreThreshold)\r\n    out.dispose()\r\n    out0.dispose()\r\n\r\n    const boxes = results.map(res => res.box)\r\n    const scores = results.map(res => res.score)\r\n    const classScores = results.map(res => res.classScore)\r\n    const classNames = results.map(res => this.config.classes[res.label])\r\n\r\n    const indices = nonMaxSuppression(\r\n      boxes.map(box => box.rescale(inputSize)),\r\n      scores,\r\n      this.config.iouThreshold,\r\n      true\r\n    )\r\n\r\n    const detections = indices.map(idx =>\r\n      new ObjectDetection(\r\n        scores[idx],\r\n        classScores[idx],\r\n        classNames[idx],\r\n        boxes[idx],\r\n        inputDimensions\r\n      )\r\n    )\r\n\r\n    return detections\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return ''\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap, this.config)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    const filterSizes = this.config.filterSizes || TinyYolov2Base.DEFAULT_FILTER_SIZES\r\n\r\n    const numFilters = filterSizes ? filterSizes.length : undefined\r\n    if (numFilters !== 7 && numFilters !== 8 && numFilters !== 9) {\r\n      throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${numFilters} filterSizes in config`)\r\n    }\r\n    return extractParams(weights, this.config, this.boxEncodingSize, filterSizes)\r\n  }\r\n\r\n  protected async extractBoxes(\r\n    outputTensor: tf.Tensor4D,\r\n    inputBlobDimensions: Dimensions,\r\n    scoreThreshold?: number\r\n  ) {\r\n\r\n    const { width, height } = inputBlobDimensions\r\n    const inputSize = Math.max(width, height)\r\n    const correctionFactorX = inputSize / width\r\n    const correctionFactorY = inputSize / height\r\n\r\n    const numCells = outputTensor.shape[1]\r\n    const numBoxes = this.config.anchors.length\r\n\r\n    const [boxesTensor, scoresTensor, classScoresTensor] = tf.tidy(() => {\r\n      const reshaped = outputTensor.reshape([numCells, numCells, numBoxes, this.boxEncodingSize])\r\n\r\n      const boxes = reshaped.slice([0, 0, 0, 0], [numCells, numCells, numBoxes, 4])\r\n      const scores = reshaped.slice([0, 0, 0, 4], [numCells, numCells, numBoxes, 1])\r\n      const classScores = this.withClassScores\r\n        ? tf.softmax(reshaped.slice([0, 0, 0, 5], [numCells, numCells, numBoxes, this.config.classes.length]), 3)\r\n        : tf.scalar(0)\r\n      return [boxes, scores, classScores]\r\n    })\r\n\r\n    const results = []\r\n\r\n    const scoresData = await scoresTensor.array()\r\n    const boxesData = await boxesTensor.array()\r\n    for (let row = 0; row < numCells; row ++) {\r\n      for (let col = 0; col < numCells; col ++) {\r\n        for (let anchor = 0; anchor < numBoxes; anchor ++) {\r\n\r\n          const score = sigmoid(scoresData[row][col][anchor][0]);\r\n          if (!scoreThreshold || score > scoreThreshold) {\r\n            const ctX = ((col + sigmoid(boxesData[row][col][anchor][0])) / numCells) * correctionFactorX\r\n            const ctY = ((row + sigmoid(boxesData[row][col][anchor][1])) / numCells) * correctionFactorY\r\n            const width = ((Math.exp(boxesData[row][col][anchor][2]) * this.config.anchors[anchor].x) / numCells) * correctionFactorX\r\n            const height = ((Math.exp(boxesData[row][col][anchor][3]) * this.config.anchors[anchor].y) / numCells) * correctionFactorY\r\n\r\n            const x = (ctX - (width / 2))\r\n            const y = (ctY - (height / 2))\r\n\r\n            const pos = { row, col, anchor }\r\n            const { classScore, label } = this.withClassScores\r\n              ? await this.extractPredictedClass(classScoresTensor as tf.Tensor4D, pos)\r\n              : { classScore: 1, label: 0 }\r\n\r\n            results.push({\r\n              box: new BoundingBox(x, y, x + width, y + height),\r\n              score: score,\r\n              classScore: score * classScore,\r\n              label,\r\n              ...pos\r\n            })\r\n          }\r\n        }\r\n      }\r\n    }\r\n\r\n    boxesTensor.dispose()\r\n    scoresTensor.dispose()\r\n    classScoresTensor.dispose()\r\n\r\n    return results\r\n  }\r\n\r\n  private async extractPredictedClass(classesTensor: tf.Tensor4D, pos: { row: number, col: number, anchor: number },) {\r\n    const { row, col, anchor } = pos\r\n    const classesData = await classesTensor.array()\r\n    return Array(this.config.classes.length).fill(0)\r\n      .map((_, i) => classesData[row][col][anchor][i])\r\n      .map((classScore, label) => ({\r\n        classScore,\r\n        label\r\n      }))\r\n      .reduce((max, curr) => max.classScore > curr.classScore ? max : curr)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FaceDetection, Point } from '../classes';\r\nimport { ParamMapping } from '../common/types';\r\nimport { TNetInput } from '../dom/types';\r\nimport {\r\n  BOX_ANCHORS,\r\n  BOX_ANCHORS_SEPARABLE,\r\n  DEFAULT_MODEL_NAME,\r\n  DEFAULT_MODEL_NAME_SEPARABLE_CONV,\r\n  IOU_THRESHOLD,\r\n  MEAN_RGB_SEPARABLE,\r\n} from './const';\r\nimport { TinyYolov2Base } from './TinyYolov2Base';\r\nimport { ITinyYolov2Options } from './TinyYolov2Options';\r\nimport { TinyYolov2NetParams } from './types';\r\n\r\nexport class TinyYolov2 extends TinyYolov2Base {\r\n\r\n  constructor(withSeparableConvs: boolean = true) {\r\n    const config = Object.assign({}, {\r\n      withSeparableConvs,\r\n      iouThreshold: IOU_THRESHOLD,\r\n      classes: ['face']\r\n    },\r\n    withSeparableConvs\r\n      ? {\r\n        anchors: BOX_ANCHORS_SEPARABLE,\r\n        meanRgb: MEAN_RGB_SEPARABLE\r\n      }\r\n      : {\r\n        anchors: BOX_ANCHORS,\r\n        withClassScores: true\r\n      }\r\n    )\r\n\r\n    super(config)\r\n  }\r\n\r\n  public get withSeparableConvs(): boolean {\r\n    return this.config.withSeparableConvs\r\n  }\r\n\r\n  public get anchors(): Point[] {\r\n    return this.config.anchors\r\n  }\r\n\r\n  public async locateFaces(input: TNetInput, forwardParams: ITinyYolov2Options): Promise<FaceDetection[]> {\r\n    const objectDetections = await this.detect(input, forwardParams)\r\n    return objectDetections.map(det => new FaceDetection(det.score, det.relativeBox, { width: det.imageWidth, height: det.imageHeight }))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return this.withSeparableConvs ? DEFAULT_MODEL_NAME_SEPARABLE_CONV : DEFAULT_MODEL_NAME\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {\r\n    return super.extractParamsFromWeigthMap(weightMap)\r\n  }\r\n}","import { TinyYolov2 } from './TinyYolov2';\r\n\r\nexport * from './TinyYolov2Options';\r\n\r\nexport * from './config'\r\nexport * from './types'\r\n\r\nexport { TinyYolov2 }\r\n\r\nexport function createTinyYolov2(weights: Float32Array, withSeparableConvs: boolean = true) {\r\n  const net = new TinyYolov2(withSeparableConvs)\r\n  net.extractWeights(weights)\r\n  return net\r\n}","import { ITinyYolov2Options, TinyYolov2Options } from '../tinyYolov2';\r\n\r\nexport interface ITinyFaceDetectorOptions extends ITinyYolov2Options {}\r\n\r\nexport class TinyFaceDetectorOptions extends TinyYolov2Options {\r\n  protected _name: string = 'TinyFaceDetectorOptions'\r\n}","export class ComposableTask<T> {\r\n\r\n  public async then(\r\n    onfulfilled: (value: T) => T | PromiseLike<T>\r\n  ): Promise<T> {\r\n    return onfulfilled(await this.run())\r\n  }\r\n\r\n  public async run(): Promise<T> {\r\n    throw new Error('ComposableTask - run is not implemented')\r\n  }\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { extractFaces, extractFaceTensors, TNetInput } from '../dom';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { isWithFaceLandmarks, WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\n\r\nexport async function extractAllFacesAndComputeResults<TSource extends WithFaceDetection<{}>, TResult>(\r\n  parentResults: TSource[],\r\n  input: TNetInput,\r\n  computeResults: (faces: Array<HTMLCanvasElement | tf.Tensor3D>) => Promise<TResult>,\r\n  extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null,\r\n  getRectForAlignment: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection = ({ alignedRect }) => alignedRect\r\n) {\r\n  const faceBoxes = parentResults.map(parentResult =>\r\n    isWithFaceLandmarks(parentResult)\r\n      ? getRectForAlignment(parentResult)\r\n      : parentResult.detection\r\n  )\r\n  const faces: Array<HTMLCanvasElement | tf.Tensor3D> = extractedFaces || (\r\n    input instanceof tf.Tensor\r\n      ? await extractFaceTensors(input, faceBoxes)\r\n      : await extractFaces(input, faceBoxes)\r\n  )\r\n\r\n  const results = await computeResults(faces)\r\n\r\n  faces.forEach(f => f instanceof tf.Tensor && f.dispose())\r\n\r\n  return results\r\n}\r\n\r\nexport async function extractSingleFaceAndComputeResult<TSource extends WithFaceDetection<{}>, TResult>(\r\n  parentResult: TSource,\r\n  input: TNetInput,\r\n  computeResult: (face: HTMLCanvasElement | tf.Tensor3D) => Promise<TResult>,\r\n  extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null,\r\n  getRectForAlignment?: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection\r\n) {\r\n  return extractAllFacesAndComputeResults<TSource, TResult>(\r\n    [parentResult],\r\n    input,\r\n    async faces => computeResult(faces[0]),\r\n    extractedFaces,\r\n    getRectForAlignment\r\n  )\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function bgrToRgbTensor(tensor: tf.Tensor4D): tf.Tensor4D {\r\n  return tf.tidy(\r\n    () => tf.stack(tf.unstack(tensor, 3).reverse(), 3)\r\n  ) as tf.Tensor4D\r\n}","export const CELL_STRIDE = 2\r\nexport const CELL_SIZE = 12","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport {\r\n  extractConvParamsFactory,\r\n  extractFCParamsFactory,\r\n  extractWeightsFactory,\r\n  ExtractWeightsFunction,\r\n  ParamMapping,\r\n} from '../common';\r\nimport { NetParams, ONetParams, PNetParams, RNetParams, SharedParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  const extractConvParams = extractConvParamsFactory(extractWeights, paramMappings)\r\n  const extractFCParams = extractFCParamsFactory(extractWeights, paramMappings)\r\n\r\n  function extractPReluParams(size: number, paramPath: string): tf.Tensor1D {\r\n    const alpha = tf.tensor1d(extractWeights(size))\r\n    paramMappings.push({ paramPath })\r\n    return alpha\r\n  }\r\n\r\n  function extractSharedParams(numFilters: number[], mappedPrefix: string, isRnet: boolean = false): SharedParams {\r\n\r\n    const conv1 = extractConvParams(numFilters[0], numFilters[1], 3, `${mappedPrefix}/conv1`)\r\n    const prelu1_alpha = extractPReluParams(numFilters[1], `${mappedPrefix}/prelu1_alpha`)\r\n    const conv2 = extractConvParams(numFilters[1], numFilters[2], 3, `${mappedPrefix}/conv2`)\r\n    const prelu2_alpha = extractPReluParams(numFilters[2], `${mappedPrefix}/prelu2_alpha`)\r\n    const conv3 = extractConvParams(numFilters[2], numFilters[3], isRnet ? 2 : 3, `${mappedPrefix}/conv3`)\r\n    const prelu3_alpha = extractPReluParams(numFilters[3], `${mappedPrefix}/prelu3_alpha`)\r\n\r\n    return { conv1, prelu1_alpha, conv2, prelu2_alpha, conv3, prelu3_alpha }\r\n  }\r\n\r\n  function extractPNetParams(): PNetParams {\r\n\r\n    const sharedParams = extractSharedParams([3, 10, 16, 32], 'pnet')\r\n    const conv4_1 = extractConvParams(32, 2, 1, 'pnet/conv4_1')\r\n    const conv4_2 = extractConvParams(32, 4, 1, 'pnet/conv4_2')\r\n\r\n    return { ...sharedParams, conv4_1, conv4_2 }\r\n  }\r\n\r\n  function extractRNetParams(): RNetParams {\r\n\r\n    const sharedParams = extractSharedParams([3, 28, 48, 64], 'rnet', true)\r\n    const fc1 = extractFCParams(576, 128, 'rnet/fc1')\r\n    const prelu4_alpha = extractPReluParams(128, 'rnet/prelu4_alpha')\r\n    const fc2_1 = extractFCParams(128, 2, 'rnet/fc2_1')\r\n    const fc2_2 = extractFCParams(128, 4, 'rnet/fc2_2')\r\n\r\n    return { ...sharedParams, fc1, prelu4_alpha, fc2_1, fc2_2 }\r\n  }\r\n\r\n  function extractONetParams(): ONetParams {\r\n\r\n    const sharedParams = extractSharedParams([3, 32, 64, 64], 'onet')\r\n    const conv4 = extractConvParams(64, 128, 2, 'onet/conv4')\r\n    const prelu4_alpha = extractPReluParams(128, 'onet/prelu4_alpha')\r\n    const fc1 = extractFCParams(1152, 256, 'onet/fc1')\r\n    const prelu5_alpha = extractPReluParams(256, 'onet/prelu5_alpha')\r\n    const fc2_1 = extractFCParams(256, 2, 'onet/fc2_1')\r\n    const fc2_2 = extractFCParams(256, 4, 'onet/fc2_2')\r\n    const fc2_3 = extractFCParams(256, 10, 'onet/fc2_3')\r\n\r\n    return { ...sharedParams, conv4, prelu4_alpha, fc1, prelu5_alpha, fc2_1, fc2_2, fc2_3 }\r\n  }\r\n\r\n  return {\r\n    extractPNetParams,\r\n    extractRNetParams,\r\n    extractONetParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(weights: Float32Array): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractPNetParams,\r\n    extractRNetParams,\r\n    extractONetParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const pnet = extractPNetParams()\r\n  const rnet = extractRNetParams()\r\n  const onet = extractONetParams()\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return { params: { pnet, rnet, onet }, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, disposeUnusedWeightTensors, extractWeightEntryFactory, FCParams, ParamMapping } from '../common';\r\nimport { NetParams, ONetParams, PNetParams, RNetParams, SharedParams } from './types';\r\n\r\nfunction extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractConvParams(prefix: string): ConvParams {\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/weights`, 4, `${prefix}/filters`)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractFCParams(prefix: string): FCParams {\r\n    const weights = extractWeightEntry<tf.Tensor2D>(`${prefix}/weights`, 2)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n\r\n    return { weights, bias }\r\n  }\r\n\r\n  function extractPReluParams(paramPath: string): tf.Tensor1D {\r\n    return extractWeightEntry<tf.Tensor1D>(paramPath, 1)\r\n  }\r\n\r\n  function extractSharedParams(prefix: string): SharedParams {\r\n\r\n    const conv1 = extractConvParams(`${prefix}/conv1`)\r\n    const prelu1_alpha = extractPReluParams(`${prefix}/prelu1_alpha`)\r\n    const conv2 = extractConvParams(`${prefix}/conv2`)\r\n    const prelu2_alpha = extractPReluParams(`${prefix}/prelu2_alpha`)\r\n    const conv3 = extractConvParams(`${prefix}/conv3`)\r\n    const prelu3_alpha = extractPReluParams(`${prefix}/prelu3_alpha`)\r\n\r\n    return { conv1, prelu1_alpha, conv2, prelu2_alpha, conv3, prelu3_alpha }\r\n  }\r\n\r\n  function extractPNetParams(): PNetParams {\r\n\r\n    const sharedParams = extractSharedParams('pnet')\r\n    const conv4_1 = extractConvParams('pnet/conv4_1')\r\n    const conv4_2 = extractConvParams('pnet/conv4_2')\r\n\r\n    return { ...sharedParams, conv4_1, conv4_2 }\r\n  }\r\n\r\n  function extractRNetParams(): RNetParams {\r\n\r\n    const sharedParams = extractSharedParams('rnet')\r\n    const fc1 = extractFCParams('rnet/fc1')\r\n    const prelu4_alpha = extractPReluParams('rnet/prelu4_alpha')\r\n    const fc2_1 = extractFCParams('rnet/fc2_1')\r\n    const fc2_2 = extractFCParams('rnet/fc2_2')\r\n\r\n    return { ...sharedParams, fc1, prelu4_alpha, fc2_1, fc2_2 }\r\n  }\r\n\r\n  function extractONetParams(): ONetParams {\r\n\r\n    const sharedParams = extractSharedParams('onet')\r\n    const conv4 = extractConvParams('onet/conv4')\r\n    const prelu4_alpha = extractPReluParams('onet/prelu4_alpha')\r\n    const fc1 = extractFCParams('onet/fc1')\r\n    const prelu5_alpha = extractPReluParams('onet/prelu5_alpha')\r\n    const fc2_1 = extractFCParams('onet/fc2_1')\r\n    const fc2_2 = extractFCParams('onet/fc2_2')\r\n    const fc2_3 = extractFCParams('onet/fc2_3')\r\n\r\n    return { ...sharedParams, conv4, prelu4_alpha, fc1, prelu5_alpha, fc2_1, fc2_2, fc2_3 }\r\n  }\r\n\r\n  return {\r\n    extractPNetParams,\r\n    extractRNetParams,\r\n    extractONetParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractPNetParams,\r\n    extractRNetParams,\r\n    extractONetParams\r\n  } = extractorsFactory(weightMap, paramMappings)\r\n\r\n  const pnet = extractPNetParams()\r\n  const rnet = extractRNetParams()\r\n  const onet = extractONetParams()\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params: { pnet, rnet, onet }, paramMappings }\r\n}","export function getSizesForScale(scale: number, [height, width]: number[]) {\r\n  return {\r\n    height: Math.floor(height * scale),\r\n    width: Math.floor(width * scale)\r\n  }\r\n}","import { CELL_SIZE } from './config'\r\n\r\nexport function pyramidDown(minFaceSize: number, scaleFactor: number, dims: number[]): number[] {\r\n\r\n  const [height, width] = dims\r\n  const m = CELL_SIZE / minFaceSize\r\n\r\n  const scales = []\r\n\r\n  let minLayer = Math.min(height, width) * m\r\n  let exp = 0\r\n  while (minLayer >= 12) {\r\n    scales.push(m * Math.pow(scaleFactor, exp))\r\n    minLayer = minLayer * scaleFactor\r\n    exp += 1\r\n  }\r\n\r\n  return scales\r\n}","import { Box } from '../classes';\r\n\r\nexport class MtcnnBox extends Box<MtcnnBox> {\r\n  constructor(left: number, top: number, right: number, bottom: number) {\r\n    super({ left, top, right, bottom }, true)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function normalize(x: tf.Tensor4D): tf.Tensor4D {\r\n  return tf.tidy(\r\n    () => tf.mul(tf.sub(x, tf.scalar(127.5)), tf.scalar(0.0078125))\r\n  )\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function prelu<T extends tf.Tensor>(x: T, alpha: tf.Tensor1D): T {\r\n  return tf.tidy(() =>\r\n    tf.add(\r\n      tf.relu(x),\r\n      tf.mul(alpha, tf.neg(tf.relu(tf.neg(x))))\r\n    )\r\n  )\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { convLayer } from '../common';\r\nimport { prelu } from './prelu';\r\nimport { SharedParams } from './types';\r\n\r\nexport function sharedLayer(x: tf.Tensor4D, params: SharedParams, isPnet: boolean = false) {\r\n  return tf.tidy(() => {\r\n\r\n    let out = convLayer(x, params.conv1, 'valid')\r\n    out = prelu<tf.Tensor4D>(out, params.prelu1_alpha)\r\n    out = tf.maxPool(out, isPnet ? [2, 2]: [3, 3], [2, 2], 'same')\r\n    out = convLayer(out, params.conv2, 'valid')\r\n    out = prelu<tf.Tensor4D>(out, params.prelu2_alpha)\r\n    out = isPnet ? out : tf.maxPool(out, [3, 3], [2, 2], 'valid')\r\n    out = convLayer(out, params.conv3, 'valid')\r\n    out = prelu<tf.Tensor4D>(out, params.prelu3_alpha)\r\n\r\n    return out\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { convLayer } from '../common';\r\nimport { sharedLayer } from './sharedLayers';\r\nimport { PNetParams } from './types';\r\n\r\nexport function PNet(x: tf.Tensor4D, params: PNetParams): { prob: tf.Tensor4D, regions: tf.Tensor4D } {\r\n  return tf.tidy(() => {\r\n\r\n    let out = sharedLayer(x, params, true)\r\n    const conv = convLayer(out, params.conv4_1, 'valid')\r\n    const max = tf.expandDims(tf.max(conv, 3), 3)\r\n    const prob = tf.softmax(tf.sub(conv, max), 3) as tf.Tensor4D\r\n    const regions = convLayer(out, params.conv4_2, 'valid')\r\n\r\n    return { prob, regions }\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { BoundingBox, Point } from '../classes';\r\nimport { nonMaxSuppression } from '../ops';\r\nimport { CELL_SIZE, CELL_STRIDE } from './config';\r\nimport { getSizesForScale } from './getSizesForScale';\r\nimport { MtcnnBox } from './MtcnnBox';\r\nimport { normalize } from './normalize';\r\nimport { PNet } from './PNet';\r\nimport { PNetParams } from './types';\r\n\r\nfunction rescaleAndNormalize(x: tf.Tensor4D, scale: number): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n\r\n    const { height, width } = getSizesForScale(scale, x.shape.slice(1))\r\n    const resized = tf.image.resizeBilinear(x, [height, width])\r\n    const normalized = normalize(resized)\r\n\r\n    return (tf.transpose(normalized, [0, 2, 1, 3]) as tf.Tensor4D)\r\n  })\r\n}\r\n\r\nfunction extractBoundingBoxes(\r\n  scoresTensor: tf.Tensor2D,\r\n  regionsTensor: tf.Tensor3D,\r\n  scale: number,\r\n  scoreThreshold: number\r\n) {\r\n\r\n  // TODO: fix this!, maybe better to use tf.gather here\r\n  const indices: Point[] = []\r\n  const scoresData = scoresTensor.arraySync();\r\n  for (let y = 0; y < scoresTensor.shape[0]; y++) {\r\n    for (let x = 0; x < scoresTensor.shape[1]; x++) {\r\n      if (scoresData[y][x] >= scoreThreshold) {\r\n        indices.push(new Point(x, y))\r\n      }\r\n    }\r\n  }\r\n\r\n  const boundingBoxes = indices.map(idx => {\r\n    const cell = new BoundingBox(\r\n      Math.round((idx.y * CELL_STRIDE + 1) / scale),\r\n      Math.round((idx.x * CELL_STRIDE + 1) / scale),\r\n      Math.round((idx.y * CELL_STRIDE + CELL_SIZE) / scale),\r\n      Math.round((idx.x * CELL_STRIDE + CELL_SIZE) / scale)\r\n    )\r\n\r\n    const score = scoresData[idx.y][idx.x]\r\n\r\n    const regionsData = regionsTensor.arraySync()\r\n    const region = new MtcnnBox(\r\n      regionsData[idx.y][idx.x][0],\r\n      regionsData[idx.y][idx.x][1],\r\n      regionsData[idx.y][idx.x][2],\r\n      regionsData[idx.y][idx.x][3]\r\n    )\r\n\r\n    return {\r\n      cell,\r\n      score,\r\n      region\r\n    }\r\n  })\r\n\r\n  return boundingBoxes\r\n}\r\n\r\nexport function stage1(\r\n  imgTensor: tf.Tensor4D,\r\n  scales: number[],\r\n  scoreThreshold: number,\r\n  params: PNetParams,\r\n  stats: any\r\n) {\r\n  stats.stage1 = []\r\n\r\n  const pnetOutputs = scales.map((scale) => tf.tidy(() => {\r\n    const statsForScale: any = { scale }\r\n    const resized = rescaleAndNormalize(imgTensor, scale)\r\n\r\n    let ts = Date.now()\r\n    const { prob, regions } = PNet(resized, params)\r\n    statsForScale.pnet = Date.now() - ts\r\n\r\n    const scoresTensor = tf.unstack(tf.unstack(prob, 3)[1])[0] as tf.Tensor2D\r\n    const regionsTensor = tf.unstack(regions)[0] as tf.Tensor3D\r\n\r\n    return {\r\n      scoresTensor,\r\n      regionsTensor,\r\n      scale,\r\n      statsForScale\r\n    }\r\n  }))\r\n\r\n  const boxesForScale = pnetOutputs.map(({ scoresTensor, regionsTensor, scale, statsForScale }) => {\r\n    const boundingBoxes = extractBoundingBoxes(\r\n      scoresTensor,\r\n      regionsTensor,\r\n      scale,\r\n      scoreThreshold\r\n    )\r\n\r\n    scoresTensor.dispose()\r\n    regionsTensor.dispose()\r\n\r\n    if (!boundingBoxes.length) {\r\n      stats.stage1.push(statsForScale)\r\n      return []\r\n    }\r\n\r\n    let ts = Date.now()\r\n    const indices = nonMaxSuppression(\r\n      boundingBoxes.map(bbox => bbox.cell),\r\n      boundingBoxes.map(bbox => bbox.score),\r\n      0.5\r\n    )\r\n    statsForScale.nms = Date.now() - ts\r\n    statsForScale.numBoxes = indices.length\r\n\r\n    stats.stage1.push(statsForScale)\r\n    return indices.map(boxIdx => boundingBoxes[boxIdx])\r\n  })\r\n\r\n  const allBoxes = boxesForScale.reduce(\r\n    (all, boxes) => all.concat(boxes), []\r\n  )\r\n\r\n  let finalBoxes: BoundingBox[] = []\r\n  let finalScores: number[] = []\r\n\r\n  if (allBoxes.length > 0) {\r\n    let ts = Date.now()\r\n    const indices = nonMaxSuppression(\r\n      allBoxes.map(bbox => bbox.cell),\r\n      allBoxes.map(bbox => bbox.score),\r\n      0.7\r\n    )\r\n    stats.stage1_nms = Date.now() - ts\r\n\r\n    finalScores = indices.map(idx => allBoxes[idx].score)\r\n    finalBoxes = indices\r\n      .map(idx => allBoxes[idx])\r\n      .map(({ cell, region }) =>\r\n        new BoundingBox(\r\n          cell.left + (region.left * cell.width),\r\n          cell.top + (region.top * cell.height),\r\n          cell.right + (region.right * cell.width),\r\n          cell.bottom + (region.bottom * cell.height)\r\n        ).toSquare().round()\r\n      )\r\n\r\n  }\r\n\r\n  return {\r\n    boxes: finalBoxes,\r\n    scores: finalScores\r\n  }\r\n\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Box, IDimensions } from '../classes';\r\nimport { createCanvas, createCanvasFromMedia, getContext2dOrThrow } from '../dom';\r\nimport { env } from '../env';\r\nimport { normalize } from './normalize';\r\n\r\nexport async function extractImagePatches(\r\n  img: HTMLCanvasElement,\r\n  boxes: Box[],\r\n  { width, height }: IDimensions\r\n): Promise<tf.Tensor4D[]> {\r\n\r\n\r\n  const imgCtx = getContext2dOrThrow(img)\r\n\r\n  const bitmaps = await Promise.all(boxes.map(async box => {\r\n    // TODO: correct padding\r\n    const { y, ey, x, ex } = box.padAtBorders(img.height, img.width)\r\n\r\n    const fromX = x - 1\r\n    const fromY = y - 1\r\n    const imgData = imgCtx.getImageData(fromX, fromY, (ex - fromX), (ey - fromY))\r\n\r\n    return env.isNodejs() ? createCanvasFromMedia(imgData) : createImageBitmap(imgData)\r\n  }))\r\n\r\n  const imagePatchesDatas: number[][] = []\r\n\r\n  bitmaps.forEach(bmp => {\r\n    const patch = createCanvas({ width, height })\r\n    const patchCtx = getContext2dOrThrow(patch)\r\n    patchCtx.drawImage(bmp, 0, 0, width, height)\r\n    const { data } = patchCtx.getImageData(0, 0, width, height)\r\n\r\n    const currData = []\r\n    // RGBA -> BGR\r\n    for(let i = 0; i < data.length; i+=4) {\r\n      currData.push(data[i + 2])\r\n      currData.push(data[i + 1])\r\n      currData.push(data[i])\r\n    }\r\n    imagePatchesDatas.push(currData)\r\n  })\r\n\r\n\r\n  return imagePatchesDatas.map(data => {\r\n    const t = tf.tidy(() => {\r\n      const imagePatchTensor = tf.transpose(\r\n        tf.tensor4d(data, [1, width, height, 3]),\r\n        [0, 2, 1, 3]\r\n      ).toFloat() as tf.Tensor4D\r\n\r\n      return normalize(imagePatchTensor)\r\n    })\r\n    return t\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { fullyConnectedLayer } from '../common/fullyConnectedLayer';\r\nimport { prelu } from './prelu';\r\nimport { sharedLayer } from './sharedLayers';\r\nimport { RNetParams } from './types';\r\n\r\nexport function RNet(x: tf.Tensor4D, params: RNetParams): { scores: tf.Tensor1D, regions: tf.Tensor2D } {\r\n  return tf.tidy(() => {\r\n\r\n    const convOut = sharedLayer(x, params)\r\n    const vectorized = tf.reshape(convOut, [convOut.shape[0], params.fc1.weights.shape[0]]) as tf.Tensor2D\r\n    const fc1 = fullyConnectedLayer(vectorized, params.fc1)\r\n    const prelu4 = prelu<tf.Tensor2D>(fc1, params.prelu4_alpha)\r\n    const fc2_1 = fullyConnectedLayer(prelu4, params.fc2_1)\r\n    const max = tf.expandDims(tf.max(fc2_1, 1), 1)\r\n    const prob = tf.softmax(tf.sub(fc2_1, max), 1) as tf.Tensor2D\r\n    const regions = fullyConnectedLayer(prelu4, params.fc2_2)\r\n\r\n    const scores = tf.unstack(prob, 1)[1] as tf.Tensor1D\r\n    return { scores, regions }\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Box } from '../classes';\r\nimport { nonMaxSuppression } from '../ops';\r\nimport { extractImagePatches } from './extractImagePatches';\r\nimport { MtcnnBox } from './MtcnnBox';\r\nimport { RNet } from './RNet';\r\nimport { RNetParams } from './types';\r\n\r\nexport async function stage2(\r\n  img: HTMLCanvasElement,\r\n  inputBoxes: Box[],\r\n  scoreThreshold: number,\r\n  params: RNetParams,\r\n  stats: any\r\n) {\r\n\r\n  let ts = Date.now()\r\n  const rnetInputs = await extractImagePatches(img, inputBoxes, { width: 24, height: 24 })\r\n  stats.stage2_extractImagePatches = Date.now() - ts\r\n\r\n  ts = Date.now()\r\n  const rnetOuts = rnetInputs.map(\r\n    rnetInput => {\r\n      const out = RNet(rnetInput, params)\r\n      rnetInput.dispose()\r\n      return out\r\n    }\r\n  )\r\n  stats.stage2_rnet = Date.now() - ts\r\n\r\n  const scoresTensor = rnetOuts.length > 1\r\n    ? tf.concat(rnetOuts.map(out => out.scores))\r\n    : rnetOuts[0].scores\r\n  const scores = Array.from(await scoresTensor.data())\r\n  scoresTensor.dispose()\r\n\r\n  const indices = scores\r\n    .map((score, idx) => ({ score, idx }))\r\n    .filter(c => c.score > scoreThreshold)\r\n    .map(({ idx }) => idx)\r\n\r\n  const filteredBoxes = indices.map(idx => inputBoxes[idx])\r\n  const filteredScores = indices.map(idx => scores[idx])\r\n\r\n  let finalBoxes: Box[] = []\r\n  let finalScores: number[] = []\r\n\r\n  if (filteredBoxes.length > 0) {\r\n    ts = Date.now()\r\n    const indicesNms = nonMaxSuppression(\r\n      filteredBoxes,\r\n      filteredScores,\r\n      0.7\r\n    )\r\n    stats.stage2_nms = Date.now() - ts\r\n\r\n    const regions = indicesNms.map(idx =>{\r\n        const regionsData = rnetOuts[indices[idx]].regions.arraySync()\r\n        return new MtcnnBox(\r\n          regionsData[0][0],\r\n          regionsData[0][1],\r\n          regionsData[0][2],\r\n          regionsData[0][3]\r\n        )\r\n      }\r\n    )\r\n\r\n    finalScores = indicesNms.map(idx => filteredScores[idx])\r\n    finalBoxes = indicesNms.map((idx, i) => filteredBoxes[idx].calibrate(regions[i]))\r\n  }\r\n\r\n  rnetOuts.forEach(t => {\r\n    t.regions.dispose()\r\n    t.scores.dispose()\r\n  })\r\n\r\n  return {\r\n    boxes: finalBoxes,\r\n    scores: finalScores\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { convLayer } from '../common';\r\nimport { fullyConnectedLayer } from '../common/fullyConnectedLayer';\r\nimport { prelu } from './prelu';\r\nimport { sharedLayer } from './sharedLayers';\r\nimport { ONetParams } from './types';\r\n\r\nexport function ONet(x: tf.Tensor4D, params: ONetParams): { scores: tf.Tensor1D, regions: tf.Tensor2D, points: tf.Tensor2D } {\r\n  return tf.tidy(() => {\r\n\r\n    let out = sharedLayer(x, params)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convLayer(out, params.conv4, 'valid')\r\n    out = prelu<tf.Tensor4D>(out, params.prelu4_alpha)\r\n\r\n    const vectorized = tf.reshape(out, [out.shape[0], params.fc1.weights.shape[0]]) as tf.Tensor2D\r\n    const fc1 = fullyConnectedLayer(vectorized, params.fc1)\r\n    const prelu5 = prelu<tf.Tensor2D>(fc1, params.prelu5_alpha)\r\n    const fc2_1 = fullyConnectedLayer(prelu5, params.fc2_1)\r\n    const max = tf.expandDims(tf.max(fc2_1, 1), 1)\r\n\r\n    const prob = tf.softmax(tf.sub(fc2_1, max), 1) as tf.Tensor2D\r\n    const regions = fullyConnectedLayer(prelu5, params.fc2_2)\r\n    const points = fullyConnectedLayer(prelu5, params.fc2_3)\r\n\r\n    const scores = tf.unstack(prob, 1)[1] as tf.Tensor1D\r\n    return { scores, regions, points }\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { BoundingBox, Box, Point } from '../classes';\r\nimport { nonMaxSuppression } from '../ops';\r\nimport { extractImagePatches } from './extractImagePatches';\r\nimport { MtcnnBox } from './MtcnnBox';\r\nimport { ONet } from './ONet';\r\nimport { ONetParams } from './types';\r\n\r\nexport async function stage3(\r\n  img: HTMLCanvasElement,\r\n  inputBoxes: BoundingBox[],\r\n  scoreThreshold: number,\r\n  params: ONetParams,\r\n  stats: any\r\n) {\r\n\r\n  let ts = Date.now()\r\n  const onetInputs = await extractImagePatches(img, inputBoxes, { width: 48, height: 48 })\r\n  stats.stage3_extractImagePatches = Date.now() - ts\r\n\r\n  ts = Date.now()\r\n  const onetOuts = onetInputs.map(\r\n    onetInput => {\r\n      const out = ONet(onetInput, params)\r\n      onetInput.dispose()\r\n      return out\r\n    }\r\n  )\r\n  stats.stage3_onet = Date.now() - ts\r\n\r\n  const scoresTensor = onetOuts.length > 1\r\n    ? tf.concat(onetOuts.map(out => out.scores))\r\n    : onetOuts[0].scores\r\n  const scores = Array.from(await scoresTensor.data())\r\n  scoresTensor.dispose()\r\n\r\n  const indices = scores\r\n    .map((score, idx) => ({ score, idx }))\r\n    .filter(c => c.score > scoreThreshold)\r\n    .map(({ idx }) => idx)\r\n\r\n  const filteredRegions = indices.map(idx => {\r\n    const regionsData = onetOuts[idx].regions.arraySync();\r\n    return new MtcnnBox(\r\n      regionsData[0][0],\r\n      regionsData[0][1],\r\n      regionsData[0][2],\r\n      regionsData[0][3]\r\n  )})\r\n  const filteredBoxes = indices\r\n    .map((idx, i) => inputBoxes[idx].calibrate(filteredRegions[i]))\r\n  const filteredScores = indices.map(idx => scores[idx])\r\n\r\n  let finalBoxes: Box[] = []\r\n  let finalScores: number[] = []\r\n  let points: Point[][] = []\r\n\r\n  if (filteredBoxes.length > 0) {\r\n\r\n    ts = Date.now()\r\n    const indicesNms = nonMaxSuppression(\r\n      filteredBoxes,\r\n      filteredScores,\r\n      0.7,\r\n      false\r\n    )\r\n    stats.stage3_nms = Date.now() - ts\r\n\r\n    finalBoxes = indicesNms.map(idx => filteredBoxes[idx])\r\n    finalScores = indicesNms.map(idx => filteredScores[idx])\r\n    points = indicesNms.map((idx, i) =>\r\n      Array(5).fill(0).map((_, ptIdx) =>{\r\n          const pointsData = onetOuts[idx].points.arraySync()\r\n          return new Point(\r\n            ((pointsData[0][ptIdx] * (finalBoxes[i].width + 1)) + finalBoxes[i].left) ,\r\n            ((pointsData[0][ptIdx+5] * (finalBoxes[i].height + 1)) + finalBoxes[i].top)\r\n          )\r\n        }\r\n      )\r\n    )\r\n  }\r\n\r\n  onetOuts.forEach(t => {\r\n    t.regions.dispose()\r\n    t.scores.dispose()\r\n    t.points.dispose()\r\n  })\r\n\r\n  return {\r\n    boxes: finalBoxes,\r\n    scores: finalScores,\r\n    points\r\n  }\r\n\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Point, Rect } from '../classes';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { FaceLandmarks5 } from '../classes/FaceLandmarks5';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { extendWithFaceDetection, extendWithFaceLandmarks } from '../factories';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { bgrToRgbTensor } from './bgrToRgbTensor';\r\nimport { CELL_SIZE } from './config';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { getSizesForScale } from './getSizesForScale';\r\nimport { IMtcnnOptions, MtcnnOptions } from './MtcnnOptions';\r\nimport { pyramidDown } from './pyramidDown';\r\nimport { stage1 } from './stage1';\r\nimport { stage2 } from './stage2';\r\nimport { stage3 } from './stage3';\r\nimport { MtcnnResult, NetParams } from './types';\r\n\r\nexport class Mtcnn extends NeuralNetwork<NetParams> {\r\n\r\n  constructor() {\r\n    super('Mtcnn')\r\n  }\r\n\r\n  public async load(weightsOrUrl: Float32Array | string | undefined): Promise<void> {\r\n    console.warn('mtcnn is deprecated and will be removed soon')\r\n    return super.load(weightsOrUrl)\r\n  }\r\n\r\n  public async loadFromDisk(filePath: string | undefined) {\r\n    console.warn('mtcnn is deprecated and will be removed soon')\r\n    return super.loadFromDisk(filePath)\r\n  }\r\n\r\n  public async forwardInput(\r\n    input: NetInput,\r\n    forwardParams: IMtcnnOptions = {}\r\n  ): Promise<{ results: MtcnnResult[], stats: any }> {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('Mtcnn - load model before inference')\r\n    }\r\n\r\n    const inputCanvas = input.canvases[0]\r\n\r\n    if (!inputCanvas) {\r\n      throw new Error('Mtcnn - inputCanvas is not defined, note that passing tensors into Mtcnn.forwardInput is not supported yet.')\r\n    }\r\n\r\n    const stats: any = {}\r\n\r\n    const tsTotal = Date.now()\r\n\r\n    const imgTensor = tf.tidy(() =>\r\n      bgrToRgbTensor(\r\n        tf.expandDims(tf.browser.fromPixels(inputCanvas)).toFloat() as tf.Tensor4D\r\n      )\r\n    )\r\n\r\n    const onReturn = (results: any) => {\r\n      // dispose tensors on return\r\n      imgTensor.dispose()\r\n      stats.total = Date.now() - tsTotal\r\n      return results\r\n    }\r\n\r\n    const [height, width] = imgTensor.shape.slice(1)\r\n\r\n    const {\r\n      minFaceSize,\r\n      scaleFactor,\r\n      maxNumScales,\r\n      scoreThresholds,\r\n      scaleSteps\r\n    } = new MtcnnOptions(forwardParams)\r\n\r\n    const scales = (scaleSteps || pyramidDown(minFaceSize, scaleFactor, [height, width]))\r\n      .filter(scale => {\r\n        const sizes = getSizesForScale(scale, [height, width])\r\n        return Math.min(sizes.width, sizes.height) > CELL_SIZE\r\n      })\r\n      .slice(0, maxNumScales)\r\n\r\n    stats.scales = scales\r\n    stats.pyramid = scales.map(scale => getSizesForScale(scale, [height, width]))\r\n\r\n    let ts = Date.now()\r\n    const out1 = await stage1(imgTensor, scales, scoreThresholds[0], params.pnet, stats)\r\n    stats.total_stage1 = Date.now() - ts\r\n\r\n    if (!out1.boxes.length) {\r\n      return onReturn({ results: [], stats })\r\n    }\r\n\r\n    stats.stage2_numInputBoxes = out1.boxes.length\r\n    // using the inputCanvas to extract and resize the image patches, since it is faster\r\n    // than doing this on the gpu\r\n    ts = Date.now()\r\n    const out2 = await stage2(inputCanvas, out1.boxes, scoreThresholds[1], params.rnet, stats)\r\n    stats.total_stage2 = Date.now() - ts\r\n\r\n    if (!out2.boxes.length) {\r\n      return onReturn({ results: [], stats })\r\n    }\r\n\r\n    stats.stage3_numInputBoxes = out2.boxes.length\r\n\r\n    ts = Date.now()\r\n    const out3 = await stage3(inputCanvas, out2.boxes, scoreThresholds[2], params.onet, stats)\r\n    stats.total_stage3 = Date.now() - ts\r\n\r\n    const results = out3.boxes.map((box, idx) => extendWithFaceLandmarks(\r\n      extendWithFaceDetection<{}>(\r\n        {},\r\n        new FaceDetection(\r\n          out3.scores[idx],\r\n          new Rect(\r\n            box.left / width,\r\n            box.top / height,\r\n            box.width / width,\r\n            box.height / height\r\n          ),\r\n          {\r\n            height,\r\n            width\r\n          }\r\n        )\r\n      ),\r\n      new FaceLandmarks5(\r\n        out3.points[idx].map(pt => pt.sub(new Point(box.left, box.top)).div(new Point(box.width, box.height))),\r\n        { width: box.width, height: box.height }\r\n      )\r\n    ))\r\n\r\n    return onReturn({ results, stats })\r\n  }\r\n\r\n  public async forward(\r\n    input: TNetInput,\r\n    forwardParams: IMtcnnOptions = {}\r\n  ): Promise<MtcnnResult[]> {\r\n    return (\r\n      await this.forwardInput(\r\n        await toNetInput(input),\r\n        forwardParams\r\n      )\r\n    ).results\r\n  }\r\n\r\n  public async forwardWithStats(\r\n    input: TNetInput,\r\n    forwardParams: IMtcnnOptions = {}\r\n  ): Promise<{ results: MtcnnResult[], stats: any }> {\r\n    return this.forwardInput(\r\n      await toNetInput(input),\r\n      forwardParams\r\n    )\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'mtcnn_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n}","import { Point } from '../classes'\r\n\r\nexport const IOU_THRESHOLD = 0.4\r\n\r\nexport const BOX_ANCHORS = [\r\n  new Point(1.603231, 2.094468),\r\n  new Point(6.041143, 7.080126),\r\n  new Point(2.882459, 3.518061),\r\n  new Point(4.266906, 5.178857),\r\n  new Point(9.041765, 10.66308)\r\n]\r\n\r\nexport const MEAN_RGB: [number, number, number] = [117.001, 114.697, 97.404]","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FaceDetection, Point } from '../classes';\r\nimport { ParamMapping } from '../common';\r\nimport { TNetInput } from '../dom';\r\nimport { ITinyYolov2Options } from '../tinyYolov2';\r\nimport { TinyYolov2Base } from '../tinyYolov2/TinyYolov2Base';\r\nimport { TinyYolov2NetParams } from '../tinyYolov2/types';\r\nimport { BOX_ANCHORS, IOU_THRESHOLD, MEAN_RGB } from './const';\r\n\r\nexport class TinyFaceDetector extends TinyYolov2Base {\r\n\r\n  constructor() {\r\n    const config = {\r\n      withSeparableConvs: true,\r\n      iouThreshold: IOU_THRESHOLD,\r\n      classes: ['face'],\r\n      anchors: BOX_ANCHORS,\r\n      meanRgb: MEAN_RGB,\r\n      isFirstLayerConv2d: true,\r\n      filterSizes: [3, 16, 32, 64, 128, 256, 512]\r\n    }\r\n\r\n    super(config)\r\n  }\r\n\r\n  public get anchors(): Point[] {\r\n    return this.config.anchors\r\n  }\r\n\r\n  public async locateFaces(input: TNetInput, forwardParams: ITinyYolov2Options): Promise<FaceDetection[]> {\r\n    const objectDetections = await this.detect(input, forwardParams)\r\n    return objectDetections.map(det => new FaceDetection(det.score, det.relativeBox, { width: det.imageWidth, height: det.imageHeight }))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'tiny_face_detector_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {\r\n    return super.extractParamsFromWeigthMap(weightMap)\r\n  }\r\n}","import { AgeGenderNet } from '../ageGenderNet/AgeGenderNet';\r\nimport { AgeAndGenderPrediction } from '../ageGenderNet/types';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { FaceLandmarks5 } from '../classes/FaceLandmarks5';\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { TNetInput } from '../dom';\r\nimport { FaceExpressionNet } from '../faceExpressionNet/FaceExpressionNet';\r\nimport { FaceExpressions } from '../faceExpressionNet/FaceExpressions';\r\nimport { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';\r\nimport { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';\r\nimport { FaceRecognitionNet } from '../faceRecognitionNet/FaceRecognitionNet';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { Mtcnn } from '../mtcnn/Mtcnn';\r\nimport { MtcnnOptions } from '../mtcnn/MtcnnOptions';\r\nimport { SsdMobilenetv1 } from '../ssdMobilenetv1/SsdMobilenetv1';\r\nimport { SsdMobilenetv1Options } from '../ssdMobilenetv1/SsdMobilenetv1Options';\r\nimport { TinyFaceDetector } from '../tinyFaceDetector/TinyFaceDetector';\r\nimport { TinyFaceDetectorOptions } from '../tinyFaceDetector/TinyFaceDetectorOptions';\r\nimport { ITinyYolov2Options, TinyYolov2 } from '../tinyYolov2';\r\n\r\nexport const nets = {\r\n  ssdMobilenetv1: new SsdMobilenetv1(),\r\n  tinyFaceDetector: new TinyFaceDetector(),\r\n  tinyYolov2: new TinyYolov2(),\r\n  mtcnn: new Mtcnn(),\r\n  faceLandmark68Net: new FaceLandmark68Net(),\r\n  faceLandmark68TinyNet: new FaceLandmark68TinyNet(),\r\n  faceRecognitionNet: new FaceRecognitionNet(),\r\n  faceExpressionNet: new FaceExpressionNet(),\r\n  ageGenderNet: new AgeGenderNet()\r\n}\r\n\r\n/**\r\n * Attempts to detect all faces in an image using SSD Mobilenetv1 Network.\r\n *\r\n * @param input The input image.\r\n * @param options (optional, default: see SsdMobilenetv1Options constructor for default parameters).\r\n * @returns Bounding box of each face with score.\r\n */\r\nexport const ssdMobilenetv1 = (input: TNetInput, options: SsdMobilenetv1Options): Promise<FaceDetection[]> =>\r\n  nets.ssdMobilenetv1.locateFaces(input, options)\r\n\r\n/**\r\n * Attempts to detect all faces in an image using the Tiny Face Detector.\r\n *\r\n * @param input The input image.\r\n * @param options (optional, default: see TinyFaceDetectorOptions constructor for default parameters).\r\n * @returns Bounding box of each face with score.\r\n */\r\nexport const tinyFaceDetector = (input: TNetInput, options: TinyFaceDetectorOptions): Promise<FaceDetection[]> =>\r\n  nets.tinyFaceDetector.locateFaces(input, options)\r\n\r\n/**\r\n * Attempts to detect all faces in an image using the Tiny Yolov2 Network.\r\n *\r\n * @param input The input image.\r\n * @param options (optional, default: see TinyYolov2Options constructor for default parameters).\r\n * @returns Bounding box of each face with score.\r\n */\r\nexport const tinyYolov2 = (input: TNetInput, options: ITinyYolov2Options): Promise<FaceDetection[]> =>\r\n  nets.tinyYolov2.locateFaces(input, options)\r\n\r\n/**\r\n * Attempts to detect all faces in an image and the 5 point face landmarks\r\n * of each detected face using the MTCNN Network.\r\n *\r\n * @param input The input image.\r\n * @param options (optional, default: see MtcnnOptions constructor for default parameters).\r\n * @returns Bounding box of each face with score and 5 point face landmarks.\r\n */\r\nexport const mtcnn = (input: TNetInput, options: MtcnnOptions): Promise<WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks5>[]> =>\r\n  nets.mtcnn.forward(input, options)\r\n\r\n/**\r\n * Detects the 68 point face landmark positions of the face shown in an image.\r\n *\r\n * @param inputs The face image extracted from the bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns 68 point face landmarks or array thereof in case of batch input.\r\n */\r\nexport const detectFaceLandmarks = (input: TNetInput): Promise<FaceLandmarks68 | FaceLandmarks68[]> =>\r\n  nets.faceLandmark68Net.detectLandmarks(input)\r\n\r\n/**\r\n * Detects the 68 point face landmark positions of the face shown in an image\r\n * using a tinier version of the 68 point face landmark model, which is slightly\r\n * faster at inference, but also slightly less accurate.\r\n *\r\n * @param inputs The face image extracted from the bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns 68 point face landmarks or array thereof in case of batch input.\r\n */\r\nexport const detectFaceLandmarksTiny = (input: TNetInput): Promise<FaceLandmarks68 | FaceLandmarks68[]>  =>\r\n  nets.faceLandmark68TinyNet.detectLandmarks(input)\r\n\r\n/**\r\n * Computes a 128 entry vector (face descriptor / face embeddings) from the face shown in an image,\r\n * which uniquely represents the features of that persons face. The computed face descriptor can\r\n * be used to measure the similarity between faces, by computing the euclidean distance of two\r\n * face descriptors.\r\n *\r\n * @param inputs The face image extracted from the aligned bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns Face descriptor with 128 entries or array thereof in case of batch input.\r\n */\r\nexport const computeFaceDescriptor = (input: TNetInput): Promise<Float32Array | Float32Array[]>  =>\r\n  nets.faceRecognitionNet.computeFaceDescriptor(input)\r\n\r\n\r\n/**\r\n * Recognizes the facial expressions from a face image.\r\n *\r\n * @param inputs The face image extracted from the bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns Facial expressions with corresponding probabilities or array thereof in case of batch input.\r\n */\r\nexport const recognizeFaceExpressions = (input: TNetInput): Promise<FaceExpressions | FaceExpressions[]> =>\r\n  nets.faceExpressionNet.predictExpressions(input)\r\n\r\n/**\r\n * Predicts age and gender from a face image.\r\n *\r\n * @param inputs The face image extracted from the bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns Predictions with age, gender and gender probability or array thereof in case of batch input.\r\n */\r\nexport const predictAgeAndGender = (input: TNetInput): Promise<AgeAndGenderPrediction | AgeAndGenderPrediction[]> =>\r\n  nets.ageGenderNet.predictAgeAndGender(input)\r\n\r\nexport const loadSsdMobilenetv1Model = (url: string) => nets.ssdMobilenetv1.load(url)\r\nexport const loadTinyFaceDetectorModel = (url: string) => nets.tinyFaceDetector.load(url)\r\nexport const loadMtcnnModel = (url: string) => nets.mtcnn.load(url)\r\nexport const loadTinyYolov2Model = (url: string) => nets.tinyYolov2.load(url)\r\nexport const loadFaceLandmarkModel = (url: string) => nets.faceLandmark68Net.load(url)\r\nexport const loadFaceLandmarkTinyModel = (url: string) => nets.faceLandmark68TinyNet.load(url)\r\nexport const loadFaceRecognitionModel = (url: string) => nets.faceRecognitionNet.load(url)\r\nexport const loadFaceExpressionModel = (url: string) => nets.faceExpressionNet.load(url)\r\nexport const loadAgeGenderModel = (url: string) => nets.ageGenderNet.load(url)\r\n\r\n// backward compatibility\r\nexport const loadFaceDetectionModel = loadSsdMobilenetv1Model\r\nexport const locateFaces = ssdMobilenetv1\r\nexport const detectLandmarks = detectFaceLandmarks","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { TNetInput } from '../dom';\r\nimport { FaceExpressions } from '../faceExpressionNet/FaceExpressions';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { extendWithFaceExpressions, WithFaceExpressions } from '../factories/WithFaceExpressions';\r\nimport { WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';\r\nimport { extractAllFacesAndComputeResults, extractSingleFaceAndComputeResult } from './extractFacesAndComputeResults';\r\nimport { nets } from './nets';\r\nimport {\r\n  PredictAllAgeAndGenderTask,\r\n  PredictAllAgeAndGenderWithFaceAlignmentTask,\r\n  PredictSingleAgeAndGenderTask,\r\n  PredictSingleAgeAndGenderWithFaceAlignmentTask,\r\n} from './PredictAgeAndGenderTask';\r\n\r\nexport class PredictFaceExpressionsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>,\r\n    protected input: TNetInput,\r\n    protected extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D>\r\n  ) {\r\n    super()\r\n  }\r\n}\r\n\r\nexport class PredictAllFaceExpressionsTask<\r\n  TSource extends WithFaceDetection<{}>\r\n> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource>[], TSource[]> {\r\n\r\n  public async run(): Promise<WithFaceExpressions<TSource>[]> {\r\n\r\n    const parentResults = await this.parentTask\r\n\r\n    const faceExpressionsByFace = await extractAllFacesAndComputeResults<TSource, FaceExpressions[]>(\r\n      parentResults,\r\n      this.input,\r\n      async faces => await Promise.all(faces.map(\r\n        face => nets.faceExpressionNet.predictExpressions(face) as Promise<FaceExpressions>\r\n      )),\r\n      this.extractedFaces\r\n    )\r\n\r\n    return parentResults.map(\r\n      (parentResult, i) => extendWithFaceExpressions<TSource>(parentResult, faceExpressionsByFace[i])\r\n    )\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictSingleFaceExpressionsTask<\r\n  TSource extends WithFaceDetection<{}>\r\n>  extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource> | undefined, TSource | undefined> {\r\n\r\n  public async run(): Promise<WithFaceExpressions<TSource> | undefined> {\r\n\r\n    const parentResult = await this.parentTask\r\n    if (!parentResult) {\r\n      return\r\n    }\r\n\r\n    const faceExpressions = await extractSingleFaceAndComputeResult<TSource, FaceExpressions>(\r\n      parentResult,\r\n      this.input,\r\n      face => nets.faceExpressionNet.predictExpressions(face) as Promise<FaceExpressions>,\r\n      this.extractedFaces\r\n    )\r\n\r\n    return extendWithFaceExpressions(parentResult, faceExpressions)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictAllFaceExpressionsWithFaceAlignmentTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends PredictAllFaceExpressionsTask<TSource> {\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptors() {\r\n    return new ComputeAllFaceDescriptorsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictSingleFaceExpressionsWithFaceAlignmentTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends PredictSingleFaceExpressionsTask<TSource> {\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptor() {\r\n    return new ComputeSingleFaceDescriptorTask(this, this.input)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { AgeAndGenderPrediction } from '../ageGenderNet/types';\r\nimport { TNetInput } from '../dom';\r\nimport { extendWithAge, WithAge } from '../factories/WithAge';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { extendWithGender, WithGender } from '../factories/WithGender';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';\r\nimport { extractAllFacesAndComputeResults, extractSingleFaceAndComputeResult } from './extractFacesAndComputeResults';\r\nimport { nets } from './nets';\r\nimport {\r\n  PredictAllFaceExpressionsTask,\r\n  PredictAllFaceExpressionsWithFaceAlignmentTask,\r\n  PredictSingleFaceExpressionsTask,\r\n  PredictSingleFaceExpressionsWithFaceAlignmentTask,\r\n} from './PredictFaceExpressionsTask';\r\n\r\nexport class PredictAgeAndGenderTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>,\r\n    protected input: TNetInput,\r\n    protected extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D>\r\n  ) {\r\n    super()\r\n  }\r\n}\r\n\r\nexport class PredictAllAgeAndGenderTask<\r\n  TSource extends WithFaceDetection<{}>\r\n> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>>[], TSource[]> {\r\n\r\n  public async run(): Promise<WithAge<WithGender<TSource>>[]> {\r\n\r\n    const parentResults = await this.parentTask\r\n\r\n    const ageAndGenderByFace = await extractAllFacesAndComputeResults<TSource, AgeAndGenderPrediction[]>(\r\n      parentResults,\r\n      this.input,\r\n      async faces => await Promise.all(faces.map(\r\n        face => nets.ageGenderNet.predictAgeAndGender(face) as Promise<AgeAndGenderPrediction>\r\n      )),\r\n      this.extractedFaces\r\n    )\r\n\r\n    return parentResults.map((parentResult, i) => {\r\n      const { age, gender, genderProbability } = ageAndGenderByFace[i]\r\n      return extendWithAge(extendWithGender(parentResult, gender, genderProbability), age)\r\n    })\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictSingleAgeAndGenderTask<\r\n  TSource extends WithFaceDetection<{}>\r\n>  extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>> | undefined, TSource | undefined> {\r\n\r\n  public async run(): Promise<WithAge<WithGender<TSource>> | undefined> {\r\n\r\n    const parentResult = await this.parentTask\r\n    if (!parentResult) {\r\n      return\r\n    }\r\n\r\n    const { age, gender, genderProbability } = await extractSingleFaceAndComputeResult<TSource, AgeAndGenderPrediction>(\r\n      parentResult,\r\n      this.input,\r\n      face => nets.ageGenderNet.predictAgeAndGender(face) as Promise<AgeAndGenderPrediction>,\r\n      this.extractedFaces\r\n    )\r\n\r\n    return extendWithAge(extendWithGender(parentResult, gender, genderProbability), age)\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictAllAgeAndGenderWithFaceAlignmentTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends PredictAllAgeAndGenderTask<TSource> {\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptors() {\r\n    return new ComputeAllFaceDescriptorsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictSingleAgeAndGenderWithFaceAlignmentTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends PredictSingleAgeAndGenderTask<TSource> {\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptor() {\r\n    return new ComputeSingleFaceDescriptorTask(this, this.input)\r\n  }\r\n}","import { TNetInput } from '../dom';\r\nimport { extendWithFaceDescriptor, WithFaceDescriptor } from '../factories/WithFaceDescriptor';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { extractAllFacesAndComputeResults, extractSingleFaceAndComputeResult } from './extractFacesAndComputeResults';\r\nimport { nets } from './nets';\r\nimport {\r\n  PredictAllAgeAndGenderWithFaceAlignmentTask,\r\n  PredictSingleAgeAndGenderWithFaceAlignmentTask,\r\n} from './PredictAgeAndGenderTask';\r\nimport {\r\n  PredictAllFaceExpressionsWithFaceAlignmentTask,\r\n  PredictSingleFaceExpressionsWithFaceAlignmentTask,\r\n} from './PredictFaceExpressionsTask';\r\n\r\nexport class ComputeFaceDescriptorsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>,\r\n    protected input: TNetInput\r\n  ) {\r\n    super()\r\n  }\r\n}\r\n\r\nexport class ComputeAllFaceDescriptorsTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource>[], TSource[]> {\r\n\r\n  public async run(): Promise<WithFaceDescriptor<TSource>[]> {\r\n\r\n    const parentResults = await this.parentTask\r\n\r\n    const descriptors = await extractAllFacesAndComputeResults<TSource, Float32Array[]>(\r\n      parentResults,\r\n      this.input,\r\n      faces => Promise.all(faces.map(face =>\r\n        nets.faceRecognitionNet.computeFaceDescriptor(face) as Promise<Float32Array>\r\n      )),\r\n      null,\r\n      parentResult => parentResult.landmarks.align(null, { useDlibAlignment: true })\r\n    )\r\n\r\n    return descriptors.map((descriptor, i) => extendWithFaceDescriptor<TSource>(parentResults[i], descriptor))\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class ComputeSingleFaceDescriptorTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource> | undefined, TSource | undefined> {\r\n\r\n  public async run(): Promise<WithFaceDescriptor<TSource> | undefined> {\r\n\r\n    const parentResult = await this.parentTask\r\n    if (!parentResult) {\r\n      return\r\n    }\r\n    const descriptor = await extractSingleFaceAndComputeResult<TSource, Float32Array>(\r\n      parentResult,\r\n      this.input,\r\n      face => nets.faceRecognitionNet.computeFaceDescriptor(face) as Promise<Float32Array>,\r\n      null,\r\n      parentResult => parentResult.landmarks.align(null, { useDlibAlignment: true })\r\n    )\r\n\r\n    return extendWithFaceDescriptor(parentResult, descriptor)\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { extractFaces, extractFaceTensors, TNetInput } from '../dom';\r\nimport { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';\r\nimport { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { extendWithFaceLandmarks, WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';\r\nimport { nets } from './nets';\r\nimport {\r\n  PredictAllAgeAndGenderWithFaceAlignmentTask,\r\n  PredictSingleAgeAndGenderWithFaceAlignmentTask,\r\n} from './PredictAgeAndGenderTask';\r\nimport {\r\n  PredictAllFaceExpressionsWithFaceAlignmentTask,\r\n  PredictSingleFaceExpressionsWithFaceAlignmentTask,\r\n} from './PredictFaceExpressionsTask';\r\n\r\nexport class DetectFaceLandmarksTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>,\r\n    protected input: TNetInput,\r\n    protected useTinyLandmarkNet: boolean\r\n  ) {\r\n    super()\r\n  }\r\n\r\n  protected get landmarkNet(): FaceLandmark68Net | FaceLandmark68TinyNet {\r\n    return this.useTinyLandmarkNet\r\n      ? nets.faceLandmark68TinyNet\r\n      : nets.faceLandmark68Net\r\n  }\r\n}\r\n\r\nexport class DetectAllFaceLandmarksTask<\r\n  TSource extends WithFaceDetection<{}>\r\n> extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource>[], TSource[]> {\r\n\r\n  public async run(): Promise<WithFaceLandmarks<TSource>[]> {\r\n\r\n    const parentResults = await this.parentTask\r\n    const detections = parentResults.map(res => res.detection)\r\n\r\n    const faces: Array<HTMLCanvasElement | tf.Tensor3D> = this.input instanceof tf.Tensor\r\n      ? await extractFaceTensors(this.input, detections)\r\n      : await extractFaces(this.input, detections)\r\n\r\n    const faceLandmarksByFace = await Promise.all(faces.map(\r\n      face => this.landmarkNet.detectLandmarks(face)\r\n    )) as FaceLandmarks68[]\r\n\r\n    faces.forEach(f => f instanceof tf.Tensor && f.dispose())\r\n\r\n    return parentResults.map((parentResult, i) =>\r\n      extendWithFaceLandmarks<TSource>(parentResult, faceLandmarksByFace[i])\r\n    )\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptors() {\r\n    return new ComputeAllFaceDescriptorsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class DetectSingleFaceLandmarksTask<\r\n  TSource extends WithFaceDetection<{}>\r\n>  extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource> | undefined, TSource | undefined> {\r\n\r\n  public async run(): Promise<WithFaceLandmarks<TSource> | undefined> {\r\n\r\n    const parentResult = await this.parentTask\r\n    if (!parentResult) {\r\n      return\r\n    }\r\n\r\n    const { detection } = parentResult\r\n    const faces: Array<HTMLCanvasElement | tf.Tensor3D> = this.input instanceof tf.Tensor\r\n      ? await extractFaceTensors(this.input, [detection])\r\n      : await extractFaces(this.input, [detection])\r\n\r\n    const landmarks = await this.landmarkNet.detectLandmarks(faces[0]) as FaceLandmarks68\r\n\r\n    faces.forEach(f => f instanceof tf.Tensor && f.dispose())\r\n\r\n    return extendWithFaceLandmarks<TSource>(parentResult, landmarks)\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptor() {\r\n    return new ComputeSingleFaceDescriptorTask(this, this.input)\r\n  }\r\n}","import { FaceDetection } from '../classes/FaceDetection';\r\nimport { TNetInput } from '../dom';\r\nimport { extendWithFaceDetection, WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { MtcnnOptions } from '../mtcnn/MtcnnOptions';\r\nimport { SsdMobilenetv1Options } from '../ssdMobilenetv1/SsdMobilenetv1Options';\r\nimport { TinyFaceDetectorOptions } from '../tinyFaceDetector/TinyFaceDetectorOptions';\r\nimport { TinyYolov2Options } from '../tinyYolov2';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { DetectAllFaceLandmarksTask, DetectSingleFaceLandmarksTask } from './DetectFaceLandmarksTasks';\r\nimport { nets } from './nets';\r\nimport { PredictAllAgeAndGenderTask, PredictSingleAgeAndGenderTask } from './PredictAgeAndGenderTask';\r\nimport { PredictAllFaceExpressionsTask, PredictSingleFaceExpressionsTask } from './PredictFaceExpressionsTask';\r\nimport { FaceDetectionOptions } from './types';\r\n\r\nexport class DetectFacesTaskBase<TReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected input: TNetInput,\r\n    protected options: FaceDetectionOptions = new SsdMobilenetv1Options()\r\n  ) {\r\n    super()\r\n  }\r\n}\r\n\r\nexport class DetectAllFacesTask extends DetectFacesTaskBase<FaceDetection[]> {\r\n\r\n  public async run(): Promise<FaceDetection[]> {\r\n\r\n    const { input, options } = this\r\n\r\n    if (options instanceof MtcnnOptions) {\r\n      return (await nets.mtcnn.forward(input, options))\r\n        .map(result => result.detection)\r\n    }\r\n\r\n    const faceDetectionFunction = options instanceof TinyFaceDetectorOptions\r\n      ? (input: TNetInput) => nets.tinyFaceDetector.locateFaces(input, options)\r\n      : (\r\n        options instanceof SsdMobilenetv1Options\r\n          ? (input: TNetInput) => nets.ssdMobilenetv1.locateFaces(input, options)\r\n          : (\r\n            options instanceof TinyYolov2Options\r\n              ? (input: TNetInput) => nets.tinyYolov2.locateFaces(input, options)\r\n              : null\r\n          )\r\n      )\r\n\r\n    if (!faceDetectionFunction) {\r\n      throw new Error('detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | MtcnnOptions | TinyYolov2Options')\r\n    }\r\n\r\n    return faceDetectionFunction(input)\r\n  }\r\n\r\n  private runAndExtendWithFaceDetections(): Promise<WithFaceDetection<{}>[]> {\r\n    return new Promise<WithFaceDetection<{}>[]>(async res => {\r\n      const detections = await this.run()\r\n      return res(detections.map(detection => extendWithFaceDetection({}, detection)))\r\n    })\r\n  }\r\n\r\n  withFaceLandmarks(useTinyLandmarkNet: boolean = false) {\r\n    return new DetectAllFaceLandmarksTask(\r\n      this.runAndExtendWithFaceDetections(),\r\n      this.input,\r\n      useTinyLandmarkNet\r\n    )\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsTask (\r\n      this.runAndExtendWithFaceDetections(),\r\n      this.input\r\n    )\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderTask(\r\n      this.runAndExtendWithFaceDetections(),\r\n      this.input\r\n    )\r\n  }\r\n}\r\n\r\nexport class DetectSingleFaceTask extends DetectFacesTaskBase<FaceDetection | undefined> {\r\n\r\n  public async run(): Promise<FaceDetection | undefined> {\r\n    const faceDetections = await new DetectAllFacesTask(this.input, this.options);\r\n    let faceDetectionWithHighestScore = faceDetections[0];\r\n    faceDetections.forEach(faceDetection => {\r\n      if (faceDetection.score > faceDetectionWithHighestScore.score) {\r\n        faceDetectionWithHighestScore = faceDetection;\r\n      }\r\n    });\r\n    return faceDetectionWithHighestScore;\r\n  }\r\n\r\n  private runAndExtendWithFaceDetection(): Promise<WithFaceDetection<{}>> {\r\n    return new Promise<WithFaceDetection<{}>>(async res => {\r\n      const detection = await this.run()\r\n      return res(detection ? extendWithFaceDetection<{}>({}, detection) : undefined)\r\n    })\r\n  }\r\n\r\n  withFaceLandmarks(useTinyLandmarkNet: boolean = false) {\r\n    return new DetectSingleFaceLandmarksTask(\r\n      this.runAndExtendWithFaceDetection(),\r\n      this.input,\r\n      useTinyLandmarkNet\r\n    )\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsTask(\r\n      this.runAndExtendWithFaceDetection(),\r\n      this.input\r\n    )\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderTask(\r\n      this.runAndExtendWithFaceDetection(),\r\n      this.input\r\n    )\r\n  }\r\n}","import { TNetInput } from '../dom';\r\nimport { SsdMobilenetv1Options } from '../ssdMobilenetv1/SsdMobilenetv1Options';\r\nimport { DetectAllFacesTask, DetectSingleFaceTask } from './DetectFacesTasks';\r\nimport { FaceDetectionOptions } from './types';\r\n\r\nexport function detectSingleFace(\r\n  input: TNetInput,\r\n  options: FaceDetectionOptions = new SsdMobilenetv1Options()\r\n): DetectSingleFaceTask {\r\n  return new DetectSingleFaceTask(input, options)\r\n}\r\n\r\nexport function detectAllFaces(\r\n  input: TNetInput,\r\n  options: FaceDetectionOptions = new SsdMobilenetv1Options()\r\n): DetectAllFacesTask {\r\n  return new DetectAllFacesTask(input, options)\r\n}","import { TNetInput } from '../dom';\r\nimport { WithFaceDescriptor, WithFaceDetection, WithFaceLandmarks } from '../factories';\r\nimport { IMtcnnOptions, MtcnnOptions } from '../mtcnn/MtcnnOptions';\r\nimport { SsdMobilenetv1Options } from '../ssdMobilenetv1';\r\nimport { ITinyYolov2Options, TinyYolov2Options } from '../tinyYolov2';\r\nimport { detectAllFaces } from './detectFaces';\r\n\r\n// export allFaces API for backward compatibility\r\n\r\nexport async function allFacesSsdMobilenetv1(\r\n  input: TNetInput,\r\n  minConfidence?: number\r\n): Promise<WithFaceDescriptor<WithFaceLandmarks<WithFaceDetection<{}>>>[]> {\r\n  console.warn('allFacesSsdMobilenetv1 is deprecated and will be removed soon, use the high level api instead')\r\n  return await detectAllFaces(input, new SsdMobilenetv1Options(minConfidence ? { minConfidence } : {}))\r\n    .withFaceLandmarks()\r\n    .withFaceDescriptors()\r\n}\r\n\r\nexport async function allFacesTinyYolov2(\r\n  input: TNetInput,\r\n  forwardParams: ITinyYolov2Options = {}\r\n): Promise<WithFaceDescriptor<WithFaceLandmarks<WithFaceDetection<{}>>>[]> {\r\n  console.warn('allFacesTinyYolov2 is deprecated and will be removed soon, use the high level api instead')\r\n  return await detectAllFaces(input, new TinyYolov2Options(forwardParams))\r\n    .withFaceLandmarks()\r\n    .withFaceDescriptors()\r\n}\r\n\r\nexport async function allFacesMtcnn(\r\n  input: TNetInput,\r\n  forwardParams: IMtcnnOptions = {}\r\n): Promise<WithFaceDescriptor<WithFaceLandmarks<WithFaceDetection<{}>>>[]> {\r\n  console.warn('allFacesMtcnn is deprecated and will be removed soon, use the high level api instead')\r\n  return await detectAllFaces(input, new MtcnnOptions(forwardParams))\r\n    .withFaceLandmarks()\r\n    .withFaceDescriptors()\r\n}\r\n\r\nexport const allFaces = allFacesSsdMobilenetv1\r\n","export function euclideanDistance(arr1: number[] | Float32Array, arr2: number[] | Float32Array) {\r\n  if (arr1.length !== arr2.length)\r\n    throw new Error('euclideanDistance: arr1.length !== arr2.length')\r\n\r\n  const desc1 = Array.from(arr1)\r\n  const desc2 = Array.from(arr2)\r\n\r\n  return Math.sqrt(\r\n    desc1\r\n      .map((val, i) => val - desc2[i])\r\n      .reduce((res, diff) => res + Math.pow(diff, 2), 0)\r\n  )\r\n}","import { FaceMatch } from '../classes/FaceMatch';\r\nimport { LabeledFaceDescriptors } from '../classes/LabeledFaceDescriptors';\r\nimport { euclideanDistance } from '../euclideanDistance';\r\nimport { WithFaceDescriptor } from '../factories';\r\n\r\nexport class FaceMatcher {\r\n\r\n  private _labeledDescriptors: LabeledFaceDescriptors[]\r\n  private _distanceThreshold: number\r\n\r\n  constructor(\r\n    inputs: LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>,\r\n    distanceThreshold: number = 0.6\r\n  ) {\r\n\r\n    this._distanceThreshold = distanceThreshold\r\n\r\n    const inputArray = Array.isArray(inputs) ? inputs : [inputs]\r\n\r\n    if (!inputArray.length) {\r\n      throw new Error(`FaceRecognizer.constructor - expected atleast one input`)\r\n    }\r\n\r\n    let count = 1\r\n    const createUniqueLabel = () => `person ${count++}`\r\n\r\n    this._labeledDescriptors = inputArray.map((desc) => {\r\n      if (desc instanceof LabeledFaceDescriptors) {\r\n        return desc\r\n      }\r\n\r\n      if (desc instanceof Float32Array) {\r\n        return new LabeledFaceDescriptors(createUniqueLabel(), [desc])\r\n      }\r\n\r\n      if (desc.descriptor && desc.descriptor instanceof Float32Array) {\r\n        return new LabeledFaceDescriptors(createUniqueLabel(), [desc.descriptor])\r\n      }\r\n\r\n      throw new Error(`FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>`)\r\n    })\r\n  }\r\n\r\n  public get labeledDescriptors(): LabeledFaceDescriptors[] { return this._labeledDescriptors }\r\n  public get distanceThreshold(): number { return this._distanceThreshold }\r\n\r\n  public computeMeanDistance(queryDescriptor: Float32Array, descriptors: Float32Array[]): number {\r\n    return descriptors\r\n      .map(d => euclideanDistance(d, queryDescriptor))\r\n      .reduce((d1, d2) => d1 + d2, 0)\r\n        / (descriptors.length || 1)\r\n  }\r\n\r\n  public matchDescriptor(queryDescriptor: Float32Array): FaceMatch {\r\n    return this.labeledDescriptors\r\n      .map(({ descriptors, label }) => new FaceMatch(\r\n          label,\r\n          this.computeMeanDistance(queryDescriptor, descriptors)\r\n      ))\r\n      .reduce((best, curr) => best.distance < curr.distance ? best : curr)\r\n  }\r\n\r\n  public findBestMatch(queryDescriptor: Float32Array): FaceMatch {\r\n    const bestMatch = this.matchDescriptor(queryDescriptor)\r\n    return bestMatch.distance < this.distanceThreshold\r\n      ? bestMatch\r\n      : new FaceMatch('unknown', bestMatch.distance)\r\n  }\r\n\r\n  public toJSON(): any {\r\n    return {\r\n      distanceThreshold: this.distanceThreshold,\r\n      labeledDescriptors: this.labeledDescriptors.map((ld) => ld.toJSON())\r\n    };\r\n  }\r\n\r\n  public static fromJSON(json: any): FaceMatcher {\r\n    const labeledDescriptors = json.labeledDescriptors\r\n      .map((ld: any) => LabeledFaceDescriptors.fromJSON(ld));\r\n    return new FaceMatcher(labeledDescriptors, json.distanceThreshold);\r\n  }\r\n\r\n}","import { Mtcnn } from './Mtcnn';\r\n\r\nexport * from './Mtcnn';\r\nexport * from './MtcnnOptions';\r\n\r\nexport function createMtcnn(weights: Float32Array) {\r\n  const net = new Mtcnn()\r\n  net.extractWeights(weights)\r\n  return net\r\n}","import { TinyFaceDetector } from './TinyFaceDetector';\r\n\r\nexport * from './TinyFaceDetector';\r\nexport * from './TinyFaceDetectorOptions';\r\n\r\nexport function createTinyFaceDetector(weights: Float32Array) {\r\n  const net = new TinyFaceDetector()\r\n  net.extractWeights(weights)\r\n  return net\r\n}","import { Dimensions, IDimensions } from './classes';\r\nimport { FaceDetection } from './classes/FaceDetection';\r\nimport { FaceLandmarks } from './classes/FaceLandmarks';\r\nimport { extendWithFaceDetection, isWithFaceDetection } from './factories/WithFaceDetection';\r\nimport { extendWithFaceLandmarks, isWithFaceLandmarks } from './factories/WithFaceLandmarks';\r\n\r\nexport function resizeResults<T>(results: T, dimensions: IDimensions): T {\r\n\r\n  const { width, height } = new Dimensions(dimensions.width, dimensions.height)\r\n\r\n  if (width <= 0 || height <= 0) {\r\n    throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({ width, height })}`)\r\n  }\r\n\r\n  if (Array.isArray(results)) {\r\n    return results.map(obj => resizeResults(obj, { width, height })) as any as T\r\n  }\r\n\r\n  if (isWithFaceLandmarks(results)) {\r\n    const resizedDetection = results.detection.forSize(width, height)\r\n    const resizedLandmarks = results.unshiftedLandmarks.forSize(resizedDetection.box.width, resizedDetection.box.height)\r\n\r\n    return extendWithFaceLandmarks(extendWithFaceDetection(results, resizedDetection), resizedLandmarks)\r\n  }\r\n\r\n  if (isWithFaceDetection(results)) {\r\n    return extendWithFaceDetection(results, results.detection.forSize(width, height))\r\n  }\r\n\r\n  if (results instanceof FaceLandmarks || results instanceof FaceDetection) {\r\n    return (results as any).forSize(width, height)\r\n  }\r\n\r\n  return 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this.throwIfDisposed(),xt.softplus(this)},t.prototype.zerosLike=function(){return this.throwIfDisposed(),xt.zerosLike(this)},t.prototype.onesLike=function(){return this.throwIfDisposed(),xt.onesLike(this)},t.prototype.sin=function(){return this.throwIfDisposed(),xt.sin(this)},t.prototype.cos=function(){return this.throwIfDisposed(),xt.cos(this)},t.prototype.tan=function(){return this.throwIfDisposed(),xt.tan(this)},t.prototype.asin=function(){return this.throwIfDisposed(),xt.asin(this)},t.prototype.acos=function(){return this.throwIfDisposed(),xt.acos(this)},t.prototype.atan=function(){return this.throwIfDisposed(),xt.atan(this)},t.prototype.sinh=function(){return this.throwIfDisposed(),xt.sinh(this)},t.prototype.cosh=function(){return this.throwIfDisposed(),xt.cosh(this)},t.prototype.tanh=function(){return this.throwIfDisposed(),xt.tanh(this)},t.prototype.asinh=function(){return this.throwIfDisposed(),xt.asinh(this)},t.prototype.acosh=function(){return this.throwIfDisposed(),xt.acosh(this)},t.prototype.atanh=function(){return this.throwIfDisposed(),xt.atanh(this)},t.prototype.erf=function(){return this.throwIfDisposed(),xt.erf(this)},t.prototype.round=function(){return this.throwIfDisposed(),xt.round(this)},t.prototype.step=function(t){return void 0===t&&(t=0),this.throwIfDisposed(),xt.step(this,t)},t.prototype.softmax=function(t){return void 0===t&&(t=-1),this.throwIfDisposed(),xt.softmax(this,t)},t.prototype.logSoftmax=function(t){return void 0===t&&(t=-1),this.throwIfDisposed(),xt.logSoftmax(this,t)},t.prototype.resizeBilinear=function(t,e){return void 0===e&&(e=!1),this.throwIfDisposed(),xt.image.resizeBilinear(this,t,e)},t.prototype.resizeNearestNeighbor=function(t,e){return void 0===e&&(e=!1),this.throwIfDisposed(),xt.image.resizeNearestNeighbor(this,t,e)},t.prototype.conv1d=function(t,e,n,r,o,a){return void 0===r&&(r=\"NWC\"),void 0===o&&(o=1),this.throwIfDisposed(),xt.conv1d(this,t,e,n,r,o,a)},t.prototype.conv2d=function(t,e,n,r,o,a){return void 0===r&&(r=\"NHWC\"),void 0===o&&(o=[1,1]),this.throwIfDisposed(),xt.conv2d(this,t,e,n,r,o,a)},t.prototype.conv2dTranspose=function(t,e,n,r,o){return this.throwIfDisposed(),xt.conv2dTranspose(this,t,e,n,r,o)},t.prototype.depthwiseConv2D=function(t,e,n,r,o,a){return void 0===r&&(r=\"NHWC\"),void 0===o&&(o=[1,1]),this.throwIfDisposed(),xt.depthwiseConv2d(this,t,e,n,r,o,a)},t.prototype.separableConv2d=function(t,e,n,r,o,a){return void 0===o&&(o=[1,1]),void 0===a&&(a=\"NHWC\"),this.throwIfDisposed(),xt.separableConv2d(this,t,e,n,r,o,a)},t.prototype.avgPool=function(t,e,n,r){return this.throwIfDisposed(),xt.avgPool(this,t,e,n,r)},t.prototype.maxPool=function(t,e,n,r){return this.throwIfDisposed(),xt.maxPool(this,t,e,n,r)},t.prototype.localResponseNormalization=function(t,e,n,r){return void 0===t&&(t=5),void 0===e&&(e=1),void 0===n&&(n=1),void 0===r&&(r=.5),xt.localResponseNormalization(this,t,e,n,r)},t.prototype.pool=function(t,e,n,r,o){return this.throwIfDisposed(),xt.pool(this,t,e,n,r,o)},t.prototype.variable=function(t,e,n){return void 0===t&&(t=!0),this.throwIfDisposed(),yt().makeVariable(this,t,e,n)},t.prototype.unsortedSegmentSum=function(t,e){return this.throwIfDisposed(),xt.unsortedSegmentSum(this,t,e)},t.prototype.batchToSpaceND=function(t,e){return this.throwIfDisposed(),xt.batchToSpaceND(this,t,e)},t.prototype.spaceToBatchND=function(t,e){return this.throwIfDisposed(),xt.spaceToBatchND(this,t,e)},t.prototype.topk=function(t,e){return void 0===t&&(t=1),void 0===e&&(e=!0),this.throwIfDisposed(),xt.topk(this,t,e)},t.prototype.stridedSlice=function(t,e,n,r,o,a,i,s){return void 0===r&&(r=0),void 0===o&&(o=0),void 0===a&&(a=0),void 0===i&&(i=0),void 0===s&&(s=0),this.throwIfDisposed(),xt.stridedSlice(this,t,e,n,r,o,a,i,s)},t.prototype.depthToSpace=function(t,e){return this.throwIfDisposed(),xt.depthToSpace(this,t,e)},t.prototype.fft=function(){return this.throwIfDisposed(),xt.spectral.fft(this)},t.prototype.ifft=function(){return this.throwIfDisposed(),xt.spectral.ifft(this)},t.prototype.rfft=function(){return this.throwIfDisposed(),xt.spectral.rfft(this)},t.prototype.irfft=function(){return this.throwIfDisposed(),xt.spectral.irfft(this)},t}();Object.defineProperty(wt,Symbol.hasInstance,{value:function(t){return!!t&&null!=t.dataId&&null!=t.shape&&null!=t.dtype}});var Ct,Et,Rt,It,kt,St=function(t){function n(e,n,r,o){var a=t.call(this,e.shape,e.dtype,e.dataId,o)||this;return a.trainable=n,a.name=r,a}return e(n,t),n.prototype.assign=function(t){if(t.dtype!==this.dtype)throw new Error(\"dtype of the new value (\"+t.dtype+\") and previous value (\"+this.dtype+\") must match\");if(!S(t.shape,this.shape))throw new Error(\"shape of the new value (\"+t.shape+\") and previous value (\"+this.shape+\") must match\");yt().disposeTensor(this),this.dataId=t.dataId,yt().incRef(this,null)},n.prototype.dispose=function(){yt().disposeVariable(this),this.isDisposedInternal=!0},n}(wt);Object.defineProperty(St,Symbol.hasInstance,{value:function(t){return t instanceof wt&&null!=t.assign&&t.assign instanceof Function}}),function(t){t.R0=\"R0\",t.R1=\"R1\",t.R2=\"R2\",t.R3=\"R3\",t.R4=\"R4\",t.R5=\"R5\",t.R6=\"R6\"}(Ct||(Ct={})),function(t){t.float32=\"float32\",t.int32=\"int32\",t.bool=\"int32\",t.complex64=\"complex64\"}(Et||(Et={})),function(t){t.float32=\"float32\",t.int32=\"int32\",t.bool=\"bool\",t.complex64=\"complex64\"}(Rt||(Rt={})),function(t){t.float32=\"float32\",t.int32=\"float32\",t.bool=\"float32\",t.complex64=\"complex64\"}(It||(It={})),function(t){t.float32=\"complex64\",t.int32=\"complex64\",t.bool=\"complex64\",t.complex64=\"complex64\"}(kt||(kt={}));var At={float32:It,int32:Et,bool:Rt,complex64:kt};function Dt(t,e){if(\"string\"===t||\"string\"===e){if(\"string\"===t&&\"string\"===e)return\"string\";throw new Error(\"Can not upcast \"+t+\" with \"+e)}return At[t][e]}function Tt(t){return Dt(t,\"int32\")}function Nt(t,e){if(t.dtype===e.dtype)return[t,e];var n=Dt(t.dtype,e.dtype);return[t.cast(n),e.cast(n)]}function Ft(t,e){C(t.dtype===e.dtype,(function(){return\"The dtypes of the first(\"+t.dtype+\") and second(\"+e.dtype+\") input must match\"}))}function _t(t){var e=[];return function t(e,n,r){if(null==e)return;if(e instanceof wt)return void n.push(e);if(o=e,!Array.isArray(o)&&\"object\"!=typeof o)return;var o;var a=e;for(var i in a){var s=a[i];r.has(s)||(r.add(s),t(s,n,r))}}(t,e,new Set),e}var Ot,Mt=Object.freeze({makeTypesMatch:Nt,assertTypesMatch:Ft,isTensorInList:function(t,e){return e.some((function(e){return e.id===t.id}))},getTensorsInContainer:_t}),Bt=function(){function t(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null}}return t.prototype.dispose=function(){for(var t in this.registeredVariables)this.registeredVariables[t].dispose()},t}(),Pt=function(){function t(t){this.ENV=t,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Bt}return t.prototype.ready=function(){return n(this,void 0,void 0,(function(){var t,e,n;return r(this,(function(r){switch(r.label){case 0:if(null!=this.pendingBackendInit)return[2,this.pendingBackendInit.then((function(){}))];if(null!=this.backendInstance)return[2];t=this.getSortedBackends(),e=0,r.label=1;case 1:return e<t.length?(n=t[e],[4,this.initializeBackend(n).success]):[3,5];case 2:return r.sent()?[4,this.setBackend(n)]:[3,4];case 3:return r.sent(),[2];case 4:return e++,[3,1];case 5:throw new Error(\"Could not initialize any backends, all backend initializations failed.\")}}))}))},Object.defineProperty(t.prototype,\"backend\",{get:function(){if(null!=this.pendingBackendInit)throw new Error(\"Backend '\"+this.backendName+\"' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods\");if(null==this.backendInstance){var t=this.initializeBackendsAndReturnBest(),e=t.name;if(t.asyncInit)throw new Error(\"The highest priority backend '\"+e+\"' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods\");this.setBackend(e)}return this.backendInstance},enumerable:!0,configurable:!0}),t.prototype.backendNames=function(){return Object.keys(this.registryFactory)},t.prototype.findBackend=function(t){if(!(t in this.registry)){if(!(t in this.registryFactory))return null;if(this.initializeBackend(t).asyncInit)return null}return this.registry[t]},t.prototype.findBackendFactory=function(t){return t in this.registryFactory?this.registryFactory[t].factory:null},t.prototype.registerBackend=function(t,e,n){return void 0===n&&(n=1),t in this.registryFactory?(console.warn(t+\" backend was already registered. Reusing existing backend factory.\"),!1):(this.registryFactory[t]={factory:e,priority:n},!0)},t.prototype.setBackend=function(t){return n(this,void 0,void 0,(function(){var e,n,o;return r(this,(function(r){switch(r.label){case 0:if(null==this.registryFactory[t])throw new Error(\"Backend name '\"+t+\"' not found in registry\");return this.backendName=t,null!=this.registry[t]?[3,4]:(this.backendInstance=null,e=this.initializeBackend(t),n=e.success,e.asyncInit?[4,n]:[3,2]);case 1:return o=r.sent(),[3,3];case 2:o=n,r.label=3;case 3:if(!o)return[2,!1];r.label=4;case 4:return this.backendInstance=this.registry[t],this.setupRegisteredKernels(),this.profiler=new ut(this.backendInstance),[2,!0]}}))}))},t.prototype.setupRegisteredKernels=function(){var t=this;f(this.backendName).forEach((function(e){null!=e.setupFunc&&e.setupFunc(t.backendInstance)}))},t.prototype.disposeRegisteredKernels=function(t){var e=this;f(t).forEach((function(n){null!=n.disposeFunc&&n.disposeFunc(e.registry[t])}))},t.prototype.initializeBackend=function(t){var e=this,n=this.registryFactory[t];if(null==n)throw new Error(\"Cannot initialize backend \"+t+\", no registration found.\");try{var r=n.factory();if(Promise.resolve(r)===r){var o=++this.pendingBackendInitId,a=r.then((function(n){return!(o<e.pendingBackendInitId)&&(e.registry[t]=n,e.pendingBackendInit=null,!0)})).catch((function(n){return!(o<e.pendingBackendInitId)&&(e.pendingBackendInit=null,console.warn(\"Initialization of backend \"+t+\" failed\"),console.warn(n.stack||n.message),!1)}));return this.pendingBackendInit=a,{success:a,asyncInit:!0}}return this.registry[t]=r,{success:!0,asyncInit:!1}}catch(e){return console.warn(\"Initialization of backend \"+t+\" failed\"),console.warn(e.stack||e.message),{success:!1,asyncInit:!1}}},t.prototype.removeBackend=function(t){if(!(t in this.registryFactory))throw new Error(t+\" backend not found in registry\");this.backendName===t&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)},t.prototype.getSortedBackends=function(){var t=this;if(0===Object.keys(this.registryFactory).length)throw new Error(\"No backend found in registry.\");return Object.keys(this.registryFactory).sort((function(e,n){return t.registryFactory[n].priority-t.registryFactory[e].priority}))},t.prototype.initializeBackendsAndReturnBest=function(){for(var t=this.getSortedBackends(),e=0;e<t.length;e++){var n=t[e],r=this.initializeBackend(n),o=r.success,a=r.asyncInit;if(a||o)return{name:n,asyncInit:a}}throw new Error(\"Could not initialize any backends, all backend initializations failed.\")},t.prototype.moveData=function(t,e){var n=this.state.tensorInfo.get(e),r=n.backend,o=this.readSync(e);r.disposeData(e),n.backend=t,t.move(e,o,n.shape,n.dtype),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++},t.prototype.tidy=function(t,e){var n,r=this,o=null;if(null==e){if(\"function\"!=typeof t)throw new Error(\"Please provide a function to tidy()\");e=t}else{if(\"string\"!=typeof t&&!(t instanceof String))throw new Error(\"When calling with two arguments, the first argument to tidy() must be a string\");if(\"function\"!=typeof e)throw new Error(\"When calling with two arguments, the 2nd argument to tidy() must be a function\");o=t}return this.scopedRun((function(){return r.startScope(o)}),(function(){return r.endScope(n)}),(function(){return(n=e())instanceof Promise&&console.error(\"Cannot return a Promise inside of tidy.\"),n}))},t.prototype.scopedRun=function(t,e,n){t();try{var r=n();return e(),r}catch(t){throw e(),t}},t.prototype.nextTensorId=function(){return t.nextTensorId++},t.prototype.nextVariableId=function(){return t.nextVariableId++},t.prototype.clone=function(t){var e=this.makeTensorFromDataId(t.dataId,t.shape,t.dtype),n={x:t};return this.addTapeNode(this.state.activeScope.name,n,[e],(function(t){return{x:function(){return t.toFloat()}}}),[]),e},t.prototype.runKernel=function(t,e,n,r,o){return this.runKernelFunc(null,e,null,t,n,r,o)},t.prototype.shouldCheckForMemLeaks=function(){return this.ENV.getBool(\"IS_TEST\")},t.prototype.checkKernelForMemLeak=function(t,e,n){var r=this.backend.numDataIds(),o=0;n.forEach((function(t){o+=\"complex64\"===t.dtype?3:1}));var a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-e-o-a;if(i>0)throw new Error(\"Backend '\"+this.backendName+\"' has an internal memory leak (\"+i+\" data ids) after running '\"+t+\"'\")},t.prototype.runKernelFunc=function(t,e,n,r,o,a,i){var s,u=this;void 0===a&&(a=[]),void 0===i&&(i=[]);var c=[],h=this.isTapeOn();null==r&&(r=null!=this.state.activeScope?this.state.activeScope.name:\"\");var f,d=function(t){h&&(c=t.map((function(t){return u.keep(u.clone(t))})))},p=this.state.numBytes,v=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);var m,g=l(r,this.backendName);return f=null!=g?function(){var t=u.backend.numDataIds();m=g.kernelFunc({inputs:e,attrs:o,backend:u.backend});var n=Array.isArray(m)?m:[m];u.shouldCheckForMemLeaks()&&u.checkKernelForMemLeak(r,t,n);var s=n.map((function(t){var e=t.dataId,n=t.shape,r=t.dtype;return u.makeTensorFromDataId(e,n,r)})),c=s.filter((function(t,e){return i[e]}));return d((a||[]).slice().concat(c)),s}:function(){var e=u.backend.numDataIds();m=u.tidy((function(){return t(u.backend,d)}));var n=Array.isArray(m)?m:[m];return u.shouldCheckForMemLeaks()&&u.checkKernelForMemLeak(r,e,n),n},this.scopedRun((function(){return u.state.kernelDepth++}),(function(){return u.state.kernelDepth--}),(function(){s=u.ENV.getBool(\"DEBUG\")?u.profiler.profileKernel(r,e,(function(){return f()})):f()})),h&&this.addTapeNode(r,e,s,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:r,bytesAdded:this.state.numBytes-p,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-v,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(e).map((function(t){return e[t].shape})),outputShapes:s.map((function(t){return t.shape}))}),Array.isArray(m)?s:s[0]},t.prototype.makeTensor=function(t,e,n,r){if(null==t)throw new Error(\"Values passed to engine.makeTensor() are null\");n=n||\"float32\",r=r||this.backend;var o=t;\"string\"===n&&H(t[0])&&(o=t.map((function(t){return rt(t)})));var a=r.write(o,e,n),i=new wt(e,n,a,this.nextTensorId());if(this.incRef(i,r),\"string\"===n){var s=this.state.tensorInfo.get(a),u=G(o);this.state.numBytes+=u-s.bytes,s.bytes=u}return i},t.prototype.makeTensorFromDataId=function(t,e,n,r){var o=new wt(e,n=n||\"float32\",t,this.nextTensorId());return this.incRef(o,r),o},t.prototype.makeVariable=function(t,e,n,r){void 0===e&&(e=!0),n=n||this.nextVariableId().toString(),null!=r&&r!==t.dtype&&(t=t.asType(r));var o=new St(t,e,n,this.nextTensorId());if(null!=this.state.registeredVariables[o.name])throw new Error(\"Variable with name \"+o.name+\" was already registered\");return this.state.registeredVariables[o.name]=o,this.incRef(o,this.backend),o},t.prototype.incRef=function(t,e){var n=this.state.tensorInfo.has(t.dataId)?this.state.tensorInfo.get(t.dataId).refCount:0;if(this.state.numTensors++,\"string\"===t.dtype&&this.state.numStringTensors++,0===n){this.state.numDataBuffers++;var r=0;\"complex64\"!==t.dtype&&\"string\"!==t.dtype&&(r=t.size*z(t.dtype)),this.state.tensorInfo.set(t.dataId,{backend:e||this.backend,dtype:t.dtype,shape:t.shape,bytes:r,refCount:0}),this.state.numBytes+=r}this.state.tensorInfo.get(t.dataId).refCount++,t instanceof St||this.track(t)},t.prototype.disposeTensor=function(t){if(this.state.tensorInfo.has(t.dataId)){this.state.numTensors--,\"string\"===t.dtype&&this.state.numStringTensors--;var e=this.state.tensorInfo.get(t.dataId);e.refCount<=1?(\"complex64\"!==t.dtype&&(this.state.numBytes-=e.bytes),this.state.numDataBuffers--,e.backend.disposeData(t.dataId),this.state.tensorInfo.delete(t.dataId)):this.state.tensorInfo.get(t.dataId).refCount--}},t.prototype.disposeVariables=function(){for(var t in this.state.registeredVariables){var e=this.state.registeredVariables[t];this.disposeVariable(e)}},t.prototype.disposeVariable=function(t){this.disposeTensor(t),null!=this.state.registeredVariables[t.name]&&delete this.state.registeredVariables[t.name]},t.prototype.memory=function(){var t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(t.unreliable=!0,null==t.reasons&&(t.reasons=[]),t.reasons.push(\"Memory usage by string tensors is approximate (2 bytes per character)\")),t},t.prototype.profile=function(t){return n(this,void 0,void 0,(function(){var e,n;return r(this,(function(r){return this.state.profiling=!0,e=this.state.numBytes,n=this.state.numTensors,this.state.activeProfile.kernels=[],this.state.activeProfile.result=t(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max.apply(Math,this.state.activeProfile.kernels.map((function(t){return t.totalBytesSnapshot}))),this.state.activeProfile.newBytes=this.state.numBytes-e,this.state.activeProfile.newTensors=this.state.numTensors-n,[2,this.state.activeProfile]}))}))},t.prototype.isTapeOn=function(){return this.state.gradientDepth>0&&0===this.state.kernelDepth},t.prototype.addTapeNode=function(t,e,n,r,o){var a=this,i={id:this.state.nextTapeNodeId++,kernelName:t,inputs:e,outputs:n,saved:o},s=h(t);null!=s&&(r=s.gradFunc),null!=r&&(i.gradient=function(t){return t=t.map((function(t,e){if(null==t){var r=n[e],o=tt(r.size,r.dtype);return a.makeTensor(o,r.shape,r.dtype)}return t})),r(t.length>1?t:t[0],o)}),this.state.activeTape.push(i)},t.prototype.keep=function(t){return t.kept=!0,t},t.prototype.startTape=function(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++},t.prototype.endTape=function(){this.state.gradientDepth--},t.prototype.startScope=function(t){var e={track:[],name:\"unnamed scope\",id:this.state.nextScopeId++};t&&(e.name=t),this.state.scopeStack.push(e),this.state.activeScope=e},t.prototype.endScope=function(t){for(var e=this,n=_t(t),r=new Set(n.map((function(t){return t.id}))),o=0;o<this.state.activeScope.track.length;o++){var a=this.state.activeScope.track[o];a.kept||r.has(a.id)||a.dispose()}var i=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],n.forEach((function(t){t.kept||t.scopeId!==i.id||e.track(t)}))},t.prototype.gradients=function(t,e,n,r){var o=this;if(void 0===r&&(r=!1),C(e.length>0,(function(){return\"gradients() received an empty list of xs.\"})),null!=n&&\"float32\"!==n.dtype)throw new Error(\"dy must have 'float32' dtype, but has '\"+n.dtype+\"'\");var a=this.scopedRun((function(){return o.startTape()}),(function(){return o.endTape()}),(function(){return o.tidy(\"forward\",t)}));C(a instanceof wt,(function(){return\"The result y returned by f() must be a tensor.\"}));var i=function(t,e,n){for(var r={},o={},a=0;a<e.length;a++)r[e[a].id]=!0;for(a=0;a<t.length;a++){var i=(p=t[a]).inputs;for(var s in i){for(var u=i[s],c=!1,l=0;l<e.length;l++)if(r[u.id]){p.outputs.forEach((function(t){return r[t.id]=!0})),c=!0,o[p.id]=!0;break}if(c)break}}var h={};h[n.id]=!0;var f={};for(a=t.length-1;a>=0;a--)for(i=(p=t[a]).inputs,l=0;l<p.outputs.length;l++)if(h[p.outputs[l].id]){for(var s in i)h[i[s].id]=!0,f[p.id]=!0;break}var d=[];for(a=0;a<t.length;a++){var p;if(o[(p=t[a]).id]&&f[p.id]){var v={};for(var s in p.inputs){var m=p.inputs[s];r[m.id]&&(v[s]=m)}var g=Object.assign({},p);g.inputs=v,g.outputs=p.outputs,d.push(g)}}return d}(this.state.activeTape,e,a);if(!r&&0===i.length&&e.length>0)throw new Error(\"Cannot compute gradient of y=f(x) with respect to x. 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Float32Array(2*t.length),r=0;r<n.length;r+=2)n[r]=t[r/2],n[r+1]=e[r/2];return n}function zo(t,e){return{real:t[2*e],imag:t[2*e+1]}}function Go(t,e,n,r){t[2*r]=e,t[2*r+1]=n}function Ho(t,e,n){var r=(n?2:-2)*Math.PI*(t/e);return{real:Math.cos(r),imag:Math.sin(r)}}function qo(t,e,n){var r=function(t,e,n){return function(t,e,n){var r=0,o=t.length,a=0,i=!1;for(;r<o;){var s=n(e,t[a=r+(o-r>>>1)]);s>0?r=a+1:(o=a,i=!s)}return i?r:-r-1}(t,e,n||Ko)}(t,e,n),o=r<0?-(r+1):r;t.splice(o,0,e)}function Ko(t,e){return t>e?1:t<e?-1:0}function jo(t,e,n,r,o){return Yo(t,e,n,r,o,0).selectedIndices}function Xo(t,e,n,r,o,a){var i=Yo(t,e,n,r,o,a,!0);return i.numValidOutputs.dispose(),{selectedIndices:i.selectedIndices,selectedScores:i.selectedScores}}function Yo(t,e,n,r,o,a,i,s){void 0===i&&(i=!1),void 0===s&&(s=!1);for(var u=Array.from(e).map((function(t,e){return{score:t,boxIndex:e,suppressBeginIndex:0}})).filter((function(t){return t.score>o})).sort(Jo),c=a>0?-.5/a:0,l=[],h=[];l.length<n&&u.length>0;){var f=u.pop(),d=f.score,p=f.boxIndex,v=f.suppressBeginIndex;if(d<o)break;for(var m=!1,g=l.length-1;g>=v;--g){var y=$o(t,p,l[g]);if(y>=r){m=!0;break}if(f.score=f.score*Qo(r,c,y),f.score<=o)break}f.suppressBeginIndex=l.length,m||(f.score===d?(l.push(p),h.push(f.score)):f.score>o&&qo(u,f,Jo))}var x=l.length;return s&&(l.fill(0,x),h.fill(0,x)),{selectedIndices:Mn(l,\"int32\"),selectedScores:Mn(h,\"float32\"),numValidOutputs:On(x,\"int32\")}}function $o(t,e,n){var r=t.subarray(4*e,4*e+4),o=t.subarray(4*n,4*n+4),a=Math.min(r[0],r[2]),i=Math.min(r[1],r[3]),s=Math.max(r[0],r[2]),u=Math.max(r[1],r[3]),c=Math.min(o[0],o[2]),l=Math.min(o[1],o[3]),h=Math.max(o[0],o[2]),f=Math.max(o[1],o[3]),d=(s-a)*(u-i),p=(h-c)*(f-l);if(d<=0||p<=0)return 0;var v=Math.max(a,c),m=Math.max(i,l),g=Math.min(s,h),y=Math.min(u,f),x=Math.max(g-v,0)*Math.max(y-m,0);return x/(d+p-x)}function Qo(t,e,n){var r=Math.exp(e*n*n);return n<=t?r:0}function Jo(t,e){return t.score-e.score||t.score===e.score&&e.boxIndex-t.boxIndex}function Zo(t,e,n){var r=new Array(t.rank).fill(0),o=t.shape.slice();return e.map((function(e){o[n]=e;var a=t.slice(r,o);return r[n]+=e,a}))}function ta(t,e){for(var n=new Array(t.rank),r=0;r<n.length;r++)n[r]=t.shape[r]*e[r];var o=dr(n,t.dtype);for(r=0;r<o.values.length;++r){for(var a=o.indexToLoc(r),i=new Array(t.rank),s=0;s<i.length;s++)i[s]=a[s]%t.shape[s];var u=t.locToIndex(i);o.values[r]=t.values[u]}return o.toTensor()}function ea(t,e,n,r,o){for(var a=e[e.length-1],i=[t.length/a,a],s=i[0],u=i[1],c=B(n,s*r),l=B(\"int32\",s*r),h=0;h<s;h++){for(var f=h*u,d=t.subarray(f,f+u),p=[],v=0;v<d.length;v++)p.push({value:d[v],index:v});p.sort((function(t,e){return e.value-t.value}));var m=h*r,g=c.subarray(m,m+r),y=l.subarray(m,m+r);for(v=0;v<r;v++)g[v]=p[v].value,y[v]=p[v].index}var x=e.slice();return x[x.length-1]=r,[Fn(c,x,n),Fn(l,x,\"int32\")]}function na(t,e){for(var n=[],r=0;r<e.length;r++)e[r]&&n.push(r);var o=dr(t,\"int32\"),a=dr([n.length,t.length],\"int32\");for(r=0;r<n.length;r++){var i=o.indexToLoc(n[r]),s=r*t.length;a.values.set(i,s)}return a.toTensor()}var ra=function(t,e){this.outputShape=[],this.outputShape=t,this.variableNames=e.map((function(t,e){return\"T\"+e}));var n=[];this.variableNames.forEach((function(t){n.push(\"float v\"+t+\" = get\"+t+\"AtOutCoords();\")}));var r=this.variableNames.map((function(t){return\"v\"+t})).join(\" + \");this.userCode=\"\\n      void main() {\\n        \"+n.join(\"\\n        \")+\"\\n\\n        float result = \"+r+\";\\n        setOutput(result);\\n      }\\n    \"},oa=function(t,e){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.variableNames=e.map((function(t,e){return\"T\"+e}));var n=[];this.variableNames.forEach((function(t){n.push(\"vec4 v\"+t+\" = get\"+t+\"AtOutCoords();\")}));var r=this.variableNames.map((function(t){return\"v\"+t})).join(\" + \");this.userCode=\"\\n      void main() {\\n        \"+n.join(\"\\n        \")+\"\\n\\n        vec4 result = \"+r+\";\\n        setOutput(result);\\n      }\\n    \"},aa=function(t,e,n){this.variableNames=[\"A\"];var r=t.windowSize,o=t.batchSize,a=t.inSize,i=Math.ceil(a/r);n||this.variableNames.push(\"bestIndicesA\"),this.outputShape=[o,i];var s=\"max\"===e?\">\":\"<\",u=n?\"inOffset + i;\":\"round(getBestIndicesA(batch, inOffset + i));\";this.userCode=\"\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int outIdx = coords[1];\\n        int inOffset = outIdx * \"+r+\";\\n\\n        int bestIndex = inOffset;\\n        float bestValue = getA(batch, bestIndex);\\n\\n        for (int i = 0; i < \"+r+\"; i++) {\\n          int inIdx = \"+u+\";\\n          float candidate = getA(batch, inIdx);\\n          if (candidate \"+s+\" bestValue) {\\n            bestValue = candidate;\\n            bestIndex = inIdx;\\n          }\\n        }\\n        setOutput(float(bestIndex));\\n      }\\n    \"};function ia(t,e){return[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"].slice(0,e).map((function(e){return t+\".\"+e}))}function sa(t,e){return 1===e?[t]:ia(t,e)}function ua(){var t,e,n,r,o,a,s,u,c,l;return 2===i().getNumber(\"WEBGL_VERSION\")?(t=\"#version 300 es\",e=\"in\",n=\"out\",r=\"in\",o=\"texture\",a=\"outputColor\",s=\"out vec4 outputColor;\",u=\"\\n      bool isnan_custom(float val) {\\n        return (val > 0.0 || val < 0.0) ? false : val != 0.0;\\n      }\\n\\n      bvec4 isnan_custom(vec4 val) {\\n        return bvec4(isnan_custom(val.x),\\n          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));\\n      }\\n\\n      #define isnan(value) isnan_custom(value)\\n    \",c=\"\",l=\"\\n      #define round(value) newRound(value)\\n      int newRound(float value) {\\n        return int(floor(value + 0.5));\\n      }\\n\\n      ivec4 newRound(vec4 value) {\\n        return ivec4(floor(value + vec4(0.5)));\\n      }\\n    \"):(t=\"\",e=\"attribute\",n=\"varying\",r=\"varying\",o=\"texture2D\",a=\"gl_FragColor\",s=\"\",u=\"\\n      #define isnan(value) isnan_custom(value)\\n      bool isnan_custom(float val) {\\n        return (val > 0. || val < 1. || val == 0.) ? false : true;\\n      }\\n      bvec4 isnan_custom(vec4 val) {\\n        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));\\n      }\\n    \",c=\"\\n      uniform float INFINITY;\\n\\n      bool isinf(float val) {\\n        return abs(val) == INFINITY;\\n      }\\n      bvec4 isinf(vec4 val) {\\n        return equal(abs(val), vec4(INFINITY));\\n      }\\n    \",l=\"\\n      int round(float value) {\\n        return int(floor(value + 0.5));\\n      }\\n\\n      ivec4 round(vec4 value) {\\n        return ivec4(floor(value + vec4(0.5)));\\n      }\\n    \"),{version:t,attribute:e,varyingVs:n,varyingFs:r,texture2D:o,output:a,defineOutput:s,defineSpecialNaN:u,defineSpecialInf:c,defineRound:l}}function ca(t,e,n){void 0===n&&(n=\"index\");var r=$(e);return r.map((function(e,o){return\"int \"+t[o]+\" = \"+n+\" / \"+e+\"; \"+(o===r.length-1?\"int \"+t[o+1]+\" = \"+n+\" - \"+t[o]+\" * \"+e:\"index -= \"+t[o]+\" * \"+e)+\";\"})).join(\"\")}function la(t){var e=$(t).map((function(t){return t.toString()}));return\"\\n  int getFlatIndex(ivec3 coords) {\\n    return coords.x * \"+e[0]+\" + coords.y * \"+e[1]+\" + coords.z;\\n  }\\n\"}var ha=\"\\n  const float FLOAT_MAX = 1.70141184e38;\\n  const float FLOAT_MIN = 1.17549435e-38;\\n\\n  lowp vec4 encode_float(highp float v) {\\n    if (isnan(v)) {\\n      return vec4(255, 255, 255, 255);\\n    }\\n\\n    highp float av = abs(v);\\n\\n    if(av < FLOAT_MIN) {\\n      return vec4(0.0, 0.0, 0.0, 0.0);\\n    } else if(v > FLOAT_MAX) {\\n      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;\\n    } else if(v < -FLOAT_MAX) {\\n      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;\\n    }\\n\\n    highp vec4 c = vec4(0,0,0,0);\\n\\n    highp float e = floor(log2(av));\\n    highp float m = exp2(fract(log2(av))) - 1.0;\\n\\n    c[2] = floor(128.0 * m);\\n    m -= c[2] / 128.0;\\n    c[1] = floor(32768.0 * m);\\n    m -= c[1] / 32768.0;\\n    c[0] = floor(8388608.0 * m);\\n\\n    highp float ebias = e + 127.0;\\n    c[3] = floor(ebias / 2.0);\\n    ebias -= c[3] * 2.0;\\n    c[2] += floor(ebias) * 128.0;\\n\\n    c[3] += 128.0 * step(0.0, -v);\\n\\n    return c / 255.0;\\n  }\\n\";function fa(t,e,n,r){var o=[];t.forEach((function(t){var e=k(t.shapeInfo.logicalShape);t.shapeInfo.isUniform?o.push(\"uniform float \"+t.name+(e>1?\"[\"+e+\"]\":\"\")+\";\"):(o.push(\"uniform sampler2D \"+t.name+\";\"),o.push(\"uniform int offset\"+t.name+\";\"))}));var a,i,s=o.join(\"\\n\"),u=t.map((function(t){return function(t,e,n){void 0===n&&(n=!1);var r=\"\";r+=n?pa(t):da(t);var o=t.shapeInfo.logicalShape,a=e.logicalShape;o.length<=a.length&&(r+=n?function(t,e){var n,r=t.name,o=r.charAt(0).toUpperCase()+r.slice(1),a=\"get\"+o+\"AtOutCoords\",i=t.shapeInfo.logicalShape.length,s=e.logicalShape.length,u=Co(t.shapeInfo.logicalShape,e.logicalShape),c=wa(s),l=s-i,h=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"];n=0===i?\"\":s<2&&u.length>=1?\"coords = 0;\":u.map((function(t){return\"coords.\"+h[t+l]+\" = 0;\"})).join(\"\\n\");var f=\"\";f=s<2&&i>0?\"coords\":t.shapeInfo.logicalShape.map((function(t,e){return\"coords.\"+h[e+l]})).join(\", \");var d=\"return outputValue;\",p=1===k(t.shapeInfo.logicalShape),v=1===k(e.logicalShape);if(1!==i||p||v){if(p&&!v)d=1===s?\"\\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\\n      \":\"\\n        return vec4(outputValue.x);\\n      \";else if(u.length){var m=i-2,g=i-1;u.indexOf(m)>-1&&u.indexOf(g)>-1?d=\"return vec4(outputValue.x);\":u.indexOf(m)>-1?d=\"return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);\":u.indexOf(g)>-1&&(d=\"return vec4(outputValue.xx, outputValue.zz);\")}}else d=\"\\n      return vec4(outputValue.xy, outputValue.xy);\\n    \";return\"\\n    vec4 \"+a+\"() {\\n      \"+c+\" coords = getOutputCoords();\\n      \"+n+\"\\n      vec4 outputValue = get\"+o+\"(\"+f+\");\\n      \"+d+\"\\n    }\\n  \"}(t,e):function(t,e){var n=t.name,r=n.charAt(0).toUpperCase()+n.slice(1),o=\"get\"+r+\"AtOutCoords\",a=e.texShape,i=t.shapeInfo.texShape,s=t.shapeInfo.logicalShape.length,u=e.logicalShape.length;if(!t.shapeInfo.isUniform&&s===u&&null==t.shapeInfo.flatOffset&&S(i,a))return\"\\n      float \"+o+\"() {\\n        return sampleTexture(\"+n+\", resultUV);\\n      }\\n    \";var c,l=wa(u),h=Co(t.shapeInfo.logicalShape,e.logicalShape),f=u-s,d=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"];c=0===s?\"\":u<2&&h.length>=1?\"coords = 0;\":h.map((function(t){return\"coords.\"+d[t+f]+\" = 0;\"})).join(\"\\n\");var p=\"\";p=u<2&&s>0?\"coords\":t.shapeInfo.logicalShape.map((function(t,e){return\"coords.\"+d[e+f]})).join(\", \");return\"\\n    float \"+o+\"() {\\n      \"+l+\" coords = getOutputCoords();\\n      \"+c+\"\\n      return get\"+r+\"(\"+p+\");\\n    }\\n  \"}(t,e));return r}(t,e,r)})).join(\"\\n\"),c=e.texShape,l=ua(),h=function(t){return\"\\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\\n      return \"+t.texture2D+\"(textureSampler, uv).r;\\n    }\\n  \"}(l),f=function(t){return t.version+\"\\n    precision highp float;\\n    precision highp int;\\n    precision highp sampler2D;\\n    \"+t.varyingFs+\" vec2 resultUV;\\n    \"+t.defineOutput+\"\\n    const vec2 halfCR = vec2(0.5, 0.5);\\n\\n    struct ivec5\\n    {\\n      int x;\\n      int y;\\n      int z;\\n      int w;\\n      int u;\\n    };\\n\\n    struct ivec6\\n    {\\n      int x;\\n      int y;\\n      int z;\\n      int w;\\n      int u;\\n      int v;\\n    };\\n\\n    uniform float NAN;\\n    \"+t.defineSpecialNaN+\"\\n    \"+t.defineSpecialInf+\"\\n    \"+t.defineRound+\"\\n\\n    int imod(int x, int y) {\\n      return x - y * (x / y);\\n    }\\n\\n    int idiv(int a, int b, float sign) {\\n      int res = a / b;\\n      int mod = imod(a, b);\\n      if (sign < 0. && mod != 0) {\\n        res -= 1;\\n      }\\n      return res;\\n    }\\n\\n    //Based on the work of Dave Hoskins\\n    //https://www.shadertoy.com/view/4djSRW\\n    #define HASHSCALE1 443.8975\\n    float random(float seed){\\n      vec2 p = resultUV * seed;\\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\\n      p3 += dot(p3, p3.yzx + 19.19);\\n      return fract((p3.x + p3.y) * p3.z);\\n    }\\n\\n    \"+va+\"\\n    \"+ma+\"\\n    \"+ga+\"\\n  \"}(l);return e.isPacked?(a=function(t,e){switch(t.length){case 0:return\"\\n    int getOutputCoords() {\\n      return 0;\\n    }\\n  \";case 1:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(1===n[0])return\"\\n      int getOutputCoords() {\\n        return 2 * int(resultUV.x * \"+n[1]+\".0);\\n      }\\n    \";if(1===n[1])return\"\\n      int getOutputCoords() {\\n        return 2 * int(resultUV.y * \"+n[0]+\".0);\\n      }\\n    \";return\"\\n    int getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+n[0]+\", \"+n[1]+\"));\\n      return 2 * (resTexRC.x * \"+n[1]+\" + resTexRC.y);\\n    }\\n  \"}(0,e);case 2:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(S(t,e))return\"\\n      ivec2 getOutputCoords() {\\n        return 2 * ivec2(resultUV.yx * vec2(\"+n[0]+\", \"+n[1]+\"));\\n      }\\n    \";var r=Math.ceil(t[1]/2);return\"\\n    ivec2 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+n[0]+\", \"+n[1]+\"));\\n\\n      int index = resTexRC.x * \"+n[1]+\" + resTexRC.y;\\n      int r = 2 * (index / \"+r+\");\\n      int c = imod(index, \"+r+\") * 2;\\n\\n      return ivec2(r, c);\\n    }\\n  \"}(t,e);case 3:return n=t,r=e,o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=Math.ceil(n[2]/2),i=a*Math.ceil(n[1]/2),\"\\n    ivec3 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+o[0]+\", \"+o[1]+\"));\\n      int index = resTexRC.x * \"+o[1]+\" + resTexRC.y;\\n\\n      int b = index / \"+i+\";\\n      index -= b * \"+i+\";\\n\\n      int r = 2 * (index / \"+a+\");\\n      int c = imod(index, \"+a+\") * 2;\\n\\n      return ivec3(b, r, c);\\n    }\\n  \";default:return function(t,e){for(var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],r=Math.ceil(t[t.length-1]/2),o=r*Math.ceil(t[t.length-2]/2),a=o,i=\"\",s=\"b, r, c\",u=2;u<t.length-1;u++)a*=t[t.length-u-1],i=\"\\n      int b\"+u+\" = index / \"+a+\";\\n      index -= b\"+u+\" * \"+a+\";\\n    \"+i,s=\"b\"+u+\", \"+s;return\"\\n    ivec\"+t.length+\" getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+n[0]+\", \"+n[1]+\"));\\n      int index = resTexRC.x * \"+n[1]+\" + resTexRC.y;\\n\\n      \"+i+\"\\n\\n      int b = index / \"+o+\";\\n      index -= b * \"+o+\";\\n\\n      int r = 2 * (index / \"+r+\");\\n      int c = imod(index, \"+r+\") * 2;\\n\\n      return ivec\"+t.length+\"(\"+s+\");\\n    }\\n  \"}(t,e)}var n,r,o,a,i}(e.logicalShape,c),i=function(t){return\"\\n    void setOutput(vec4 val) {\\n      \"+t.output+\" = val;\\n    }\\n  \"}(l)):(a=function(t,e){switch(t.length){case 0:return\"\\n    int getOutputCoords() {\\n      return 0;\\n    }\\n  \";case 1:return function(t,e){if(1===e[0])return\"\\n      int getOutputCoords() {\\n        return int(resultUV.x * \"+e[1]+\".0);\\n      }\\n    \";if(1===e[1])return\"\\n      int getOutputCoords() {\\n        return int(resultUV.y * \"+e[0]+\".0);\\n      }\\n    \";return\"\\n    int getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+e[0]+\", \"+e[1]+\"));\\n      return resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n    }\\n  \"}(0,e);case 2:return function(t,e){if(S(t,e))return\"\\n      ivec2 getOutputCoords() {\\n        return ivec2(resultUV.yx * vec2(\"+e[0]+\", \"+e[1]+\"));\\n      }\\n    \";if(1===t[1])return\"\\n      ivec2 getOutputCoords() {\\n        ivec2 resTexRC = ivec2(resultUV.yx *\\n                               vec2(\"+e[0]+\", \"+e[1]+\"));\\n        int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n        return ivec2(index, 0);\\n      }\\n    \";if(1===t[0])return\"\\n      ivec2 getOutputCoords() {\\n        ivec2 resTexRC = ivec2(resultUV.yx *\\n                               vec2(\"+e[0]+\", \"+e[1]+\"));\\n        int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n        return ivec2(0, index);\\n      }\\n    \";return\"\\n    ivec2 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+e[0]+\", \"+e[1]+\"));\\n      int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n      int r = index / \"+t[1]+\";\\n      int c = index - r * \"+t[1]+\";\\n      return ivec2(r, c);\\n    }\\n  \"}(t,e);case 3:return n=e,r=ca([\"r\",\"c\",\"d\"],t),\"\\n    ivec3 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n                             vec2(\"+n[0]+\", \"+n[1]+\"));\\n      int index = resTexRC.x * \"+n[1]+\" + resTexRC.y;\\n      \"+r+\"\\n      return ivec3(r, c, d);\\n    }\\n  \";case 4:return function(t,e){var n=ca([\"r\",\"c\",\"d\",\"d2\"],t);return\"\\n    ivec4 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n        vec2(\"+e[0]+\", \"+e[1]+\"));\\n      int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n      \"+n+\"\\n      return ivec4(r, c, d, d2);\\n    }\\n  \"}(t,e);case 5:return function(t,e){var n=ca([\"r\",\"c\",\"d\",\"d2\",\"d3\"],t);return\"\\n    ivec5 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2(\"+e[0]+\",\\n                             \"+e[1]+\"));\\n\\n      int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n\\n      \"+n+\"\\n\\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\\n      return outShape;\\n    }\\n  \"}(t,e);case 6:return function(t,e){var n=ca([\"r\",\"c\",\"d\",\"d2\",\"d3\",\"d4\"],t);return\"\\n    ivec6 getOutputCoords() {\\n      ivec2 resTexRC = ivec2(resultUV.yx *\\n        vec2(\"+e[0]+\", \"+e[1]+\"));\\n      int index = resTexRC.x * \"+e[1]+\" + resTexRC.y;\\n\\n      \"+n+\"\\n\\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\\n      return result;\\n    }\\n  \"}(t,e);default:throw new Error(t.length+\"-D output sampling is not yet supported\")}var n,r}(e.logicalShape,c),i=function(t){return\"\\n    void setOutput(float val) {\\n      \"+t.output+\" = vec4(val, 0, 0, 0);\\n    }\\n  \"}(l)),r&&(f+=ya),[f,h,i,s,a,u,n].join(\"\\n\")}function da(t){var e=t.shapeInfo.logicalShape;switch(e.length){case 0:return function(t){var e=t.name,n=\"get\"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return\"float \"+n+\"() {return \"+e+\";}\";var r=t.shapeInfo.texShape,o=r[0],a=r[1];if(1===o&&1===a)return\"\\n      float \"+n+\"() {\\n        return sampleTexture(\"+e+\", halfCR);\\n      }\\n    \";var i=t.shapeInfo.texShape,s=i[0],u=i[1],c=xa(e);return\"\\n    float \"+n+\"() {\\n      vec2 uv = uvFromFlat(\"+s+\", \"+u+\", \"+c+\");\\n      return sampleTexture(\"+e+\", uv);\\n    }\\n  \"}(t);case 1:return function(t){var e=t.name,n=\"get\"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return\"\\n      float \"+n+\"(int index) {\\n        \"+ba(t)+\"\\n      }\\n    \";var r=t.shapeInfo.texShape,o=r[0],a=r[1];if(1===a&&1===o)return\"\\n      float \"+n+\"(int index) {\\n        return sampleTexture(\"+e+\", halfCR);\\n      }\\n    \";var i=xa(e);if(1===a)return\"\\n      float \"+n+\"(int index) {\\n        vec2 uv = vec2(0.5, (float(index + \"+i+\") + 0.5) / \"+o+\".0);\\n        return sampleTexture(\"+e+\", uv);\\n      }\\n    \";if(1===o)return\"\\n      float \"+n+\"(int index) {\\n        vec2 uv = vec2((float(index + \"+i+\") + 0.5) / \"+a+\".0, 0.5);\\n        return sampleTexture(\"+e+\", uv);\\n      }\\n    \";return\"\\n    float \"+n+\"(int index) {\\n      vec2 uv = uvFromFlat(\"+o+\", \"+a+\", index + \"+i+\");\\n      return sampleTexture(\"+e+\", uv);\\n    }\\n  \"}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape;if(null!=o&&S(e,o)){var a=o[0],i=o[1];return\"\\n    float \"+r+\"(int row, int col) {\\n      vec2 uv = (vec2(col, row) + halfCR) / vec2(\"+i+\".0, \"+a+\".0);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \"}var s=M(e),u=s.newShape,c=s.keptDims,l=u;if(l.length<e.length){var h=Ca(t,l);return\"\\n      \"+da(h)+\"\\n      float \"+r+\"(int row, int col) {\\n        return \"+r+\"(\"+Ea([\"row\",\"col\"],c)+\");\\n      }\\n    \"}if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col) {\\n        int index = round(dot(vec2(row, col), vec2(\"+e[1]+\", 1)));\\n        \"+ba(t)+\"\\n      }\\n    \";var f=o[0],d=o[1],p=xa(n);if(1===d)return\"\\n    float \"+r+\"(int row, int col) {\\n      float index = dot(vec3(row, col, \"+p+\"), vec3(\"+e[1]+\", 1, 1));\\n      vec2 uv = vec2(0.5, (index + 0.5) / \"+f+\".0);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \";if(1===f)return\"\\n    float \"+r+\"(int row, int col) {\\n      float index = dot(vec3(row, col, \"+p+\"), vec3(\"+e[1]+\", 1, 1));\\n      vec2 uv = vec2((index + 0.5) / \"+d+\".0, 0.5);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \";return\"\\n  float \"+r+\"(int row, int col) {\\n    // Explicitly use integer operations as dot() only works on floats.\\n    int index = row * \"+e[1]+\" + col + \"+p+\";\\n    vec2 uv = uvFromFlat(\"+f+\", \"+d+\", index);\\n    return sampleTexture(\"+n+\", uv);\\n  }\\n\"}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=e[1]*e[2],a=e[2],i=M(e),s=i.newShape,u=i.keptDims,c=s;if(c.length<e.length){var l=Ca(t,c);return\"\\n        \"+da(l)+\"\\n        float \"+r+\"(int row, int col, int depth) {\\n          return \"+r+\"(\"+Ea([\"row\",\"col\",\"depth\"],u)+\");\\n        }\\n      \"}if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col, int depth) {\\n        int index = round(dot(vec3(row, col, depth),\\n                          vec3(\"+o+\", \"+a+\", 1)));\\n        \"+ba(t)+\"\\n      }\\n    \";var h=t.shapeInfo.texShape,f=h[0],d=h[1],p=t.shapeInfo.flatOffset;if(d===o&&null==p)return\"\\n        float \"+r+\"(int row, int col, int depth) {\\n          float texR = float(row);\\n          float texC = dot(vec2(col, depth), vec2(\"+a+\", 1));\\n          vec2 uv = (vec2(texC, texR) + halfCR) /\\n                     vec2(\"+d+\".0, \"+f+\".0);\\n          return sampleTexture(\"+n+\", uv);\\n        }\\n      \";if(d===a&&null==p)return\"\\n    float \"+r+\"(int row, int col, int depth) {\\n      float texR = dot(vec2(row, col), vec2(\"+e[1]+\", 1));\\n      float texC = float(depth);\\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(\"+d+\".0, \"+f+\".0);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \";var v=xa(n);return\"\\n      float \"+r+\"(int row, int col, int depth) {\\n        // Explicitly use integer operations as dot() only works on floats.\\n        int index = row * \"+o+\" + col * \"+a+\" + depth + \"+v+\";\\n        vec2 uv = uvFromFlat(\"+f+\", \"+d+\", index);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n  \"}(t);case 4:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=e[3],a=e[2]*o,i=e[1]*a,s=M(e),u=s.newShape,c=s.keptDims;if(u.length<e.length){var l=Ca(t,u);return\"\\n      \"+da(l)+\"\\n      float \"+r+\"(int row, int col, int depth, int depth2) {\\n        return \"+r+\"(\"+Ea([\"row\",\"col\",\"depth\",\"depth2\"],c)+\");\\n      }\\n    \"}if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2) {\\n        int index = round(dot(vec4(row, col, depth, depth2),\\n                          vec4(\"+i+\", \"+a+\", \"+o+\", 1)));\\n        \"+ba(t)+\"\\n      }\\n    \";var h=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,d=f[0],p=f[1];if(p===i&&null==h)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2) {\\n        float texR = float(row);\\n        float texC =\\n            dot(vec3(col, depth, depth2),\\n                vec3(\"+a+\", \"+o+\", 1));\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                   vec2(\"+p+\".0, \"+d+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";if(p===o&&null==h)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2) {\\n        float texR = dot(vec3(row, col, depth),\\n                         vec3(\"+e[1]*e[2]+\", \"+e[2]+\", 1));\\n        float texC = float(depth2);\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                  vec2(\"+p+\".0, \"+d+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";var v=xa(n);return\"\\n    float \"+r+\"(int row, int col, int depth, int depth2) {\\n      // Explicitly use integer operations as dot() only works on floats.\\n      int index = row * \"+i+\" + col * \"+a+\" +\\n          depth * \"+o+\" + depth2;\\n      vec2 uv = uvFromFlat(\"+d+\", \"+p+\", index + \"+v+\");\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \"}(t);case 5:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=e[4],a=e[3]*o,i=e[2]*a,s=e[1]*i,u=M(e),c=u.newShape,l=u.keptDims;if(c.length<e.length){var h=Ca(t,c);return\"\\n      \"+da(h)+\"\\n      float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n        return \"+r+\"(\"+Ea([\"row\",\"col\",\"depth\",\"depth2\",\"depth3\"],l)+\");\\n      }\\n    \"}if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n        float index = dot(\\n          vec4(row, col, depth, depth2),\\n          vec4(\"+s+\", \"+i+\", \"+a+\", \"+o+\")) +\\n          depth3;\\n        \"+ba(t)+\"\\n      }\\n    \";var f=t.shapeInfo.flatOffset,d=t.shapeInfo.texShape,p=d[0],v=d[1];if(v===s&&null==f)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n        int texR = row;\\n        float texC = dot(vec4(col, depth, depth2, depth3),\\n                         vec4(\"+i+\", \"+a+\", \"+o+\", 1));\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                   vec2(\"+v+\".0, \"+p+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";if(v===o&&null==f)return\"\\n      float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n        float texR = dot(\\n          vec4(row, col, depth, depth2),\\n          vec4(\"+e[1]*e[2]*e[3]+\",\\n               \"+e[2]*e[3]+\", \"+e[3]+\", 1));\\n        int texC = depth3;\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                  vec2(\"+v+\".0, \"+p+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";var m=xa(n);return\"\\n    float \"+r+\"(int row, int col, int depth, int depth2, int depth3) {\\n      // Explicitly use integer operations as dot() only works on floats.\\n      int index = row * \"+s+\" + col * \"+i+\" + depth * \"+a+\" +\\n          depth2 * \"+o+\" + depth3 + \"+m+\";\\n      vec2 uv = uvFromFlat(\"+p+\", \"+v+\", index);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \"}(t);case 6:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=M(e),a=o.newShape,i=o.keptDims;if(a.length<e.length){var s=Ca(t,a);return\"\\n      \"+da(s)+\"\\n      float \"+r+\"(int row, int col, int depth,\\n                    int depth2, int depth3, int depth4) {\\n        return \"+r+\"(\"+Ea([\"row\",\"col\",\"depth\",\"depth2\",\"depth3\",\"depth4\"],i)+\");\\n      }\\n    \"}var u=e[5],c=e[4]*u,l=e[3]*c,h=e[2]*l,f=e[1]*h;if(t.shapeInfo.isUniform)return\"\\n      float \"+r+\"(int row, int col, int depth,\\n                  int depth2, int depth3, int depth4) {\\n        int index = round(dot(\\n          vec4(row, col, depth, depth2),\\n          vec4(\"+f+\", \"+h+\", \"+l+\", \"+c+\")) +\\n          dot(\\n            vec2(depth3, depth4),\\n            vec2(\"+u+\", 1)));\\n        \"+ba(t)+\"\\n      }\\n    \";var d=t.shapeInfo.flatOffset,p=t.shapeInfo.texShape,v=p[0],m=p[1];if(m===f&&null==d)return\"\\n      float \"+r+\"(int row, int col, int depth,\\n                    int depth2, int depth3, int depth4) {\\n        int texR = row;\\n        float texC = dot(vec4(col, depth, depth2, depth3),\\n          vec4(\"+h+\", \"+l+\", \"+c+\", \"+u+\")) +\\n               float(depth4);\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                   vec2(\"+m+\".0, \"+v+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";if(m===u&&null==d)return\"\\n      float \"+r+\"(int row, int col, int depth,\\n                    int depth2, int depth3, int depth4) {\\n        float texR = dot(vec4(row, col, depth, depth2),\\n          vec4(\"+e[1]*e[2]*e[3]*e[4]+\",\\n               \"+e[2]*e[3]*e[4]+\",\\n               \"+e[3]*e[4]+\",\\n               \"+e[4]+\")) + float(depth3);\\n        int texC = depth4;\\n        vec2 uv = (vec2(texC, texR) + halfCR) /\\n                  vec2(\"+m+\".0, \"+v+\".0);\\n        return sampleTexture(\"+n+\", uv);\\n      }\\n    \";var g=xa(n);return\"\\n    float \"+r+\"(int row, int col, int depth,\\n                  int depth2, int depth3, int depth4) {\\n      // Explicitly use integer operations as dot() only works on floats.\\n      int index = row * \"+f+\" + col * \"+h+\" + depth * \"+l+\" +\\n          depth2 * \"+c+\" + depth3 * \"+u+\" + depth4 + \"+g+\";\\n      vec2 uv = uvFromFlat(\"+v+\", \"+m+\", index);\\n      return sampleTexture(\"+n+\", uv);\\n    }\\n  \"}(t);default:throw new Error(e.length+\"-D input sampling is not yet supported\")}}function pa(t){var e,n,r;switch(t.shapeInfo.logicalShape.length){case 0:return e=t.name,n=\"get\"+e.charAt(0).toUpperCase()+e.slice(1),r=ua(),\"\\n    vec4 \"+n+\"() {\\n      return \"+r.texture2D+\"(\"+e+\", halfCR);\\n    }\\n  \";case 1:return function(t){var e=t.name,n=\"get\"+e.charAt(0).toUpperCase()+e.slice(1),r=t.shapeInfo.texShape,o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=ua();return\"\\n    vec4 \"+n+\"(int index) {\\n      vec2 uv = packedUVfrom1D(\\n        \"+o[0]+\", \"+o[1]+\", index);\\n      return \"+a.texture2D+\"(\"+e+\", uv);\\n    }\\n  \"}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,a=o[0],i=o[1],s=ua();if(null!=o&&S(e,o))return\"\\n      vec4 \"+r+\"(int row, int col) {\\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(\"+i+\".0, \"+a+\".0);\\n\\n        return \"+s.texture2D+\"(\"+n+\", uv);\\n      }\\n    \";var u=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],c=Math.ceil(e[1]/2);return\"\\n    vec4 \"+r+\"(int row, int col) {\\n      vec2 uv = packedUVfrom2D(\"+c+\", \"+u[0]+\", \"+u[1]+\", row, col);\\n      return \"+s.texture2D+\"(\"+n+\", uv);\\n    }\\n  \"}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r=\"get\"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,a=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];if(1===e[0]){var i=e.slice(1),s=Ca(t,i);return\"\\n        \"+pa(s)+\"\\n        vec4 \"+r+\"(int b, int row, int col) {\\n          return \"+r+\"(\"+Ea([\"b\",\"row\",\"col\"],[1,2])+\");\\n        }\\n      \"}var u=a[0],c=a[1],l=Math.ceil(e[2]/2),h=l*Math.ceil(e[1]/2),f=ua();return\"\\n    vec4 \"+r+\"(int b, int row, int col) {\\n      vec2 uv = packedUVfrom3D(\\n        \"+u+\", \"+c+\", \"+h+\", \"+l+\", b, row, col);\\n      return \"+f.texture2D+\"(\"+n+\", uv);\\n    }\\n  \"}(t);default:return function(t){for(var e=t.shapeInfo.logicalShape,n=e.length,r=t.name,o=\"get\"+r.charAt(0).toUpperCase()+r.slice(1),a=t.shapeInfo.texShape,i=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],s=i[0],u=i[1],c=Math.ceil(e[n-1]/2),l=c*Math.ceil(e[n-2]/2),h=\"int b, int row, int col\",f=\"b * \"+l+\" + (row / 2) * \"+c+\" + (col / 2)\",d=2;d<n-1;d++)h=\"int b\"+d+\", \"+h,l*=e[n-d-1],f=\"b\"+d+\" * \"+l+\" + \"+f;var p=ua();return\"\\n    vec4 \"+o+\"(\"+h+\") {\\n      int index = \"+f+\";\\n      int texR = index / \"+u+\";\\n      int texC = index - texR * \"+u+\";\\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(\"+u+\", \"+s+\");\\n      return \"+p.texture2D+\"(\"+r+\", uv);\\n    }\\n  \"}(t)}}var va=\"\\nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\\n  int texR = index / texNumC;\\n  int texC = index - texR * texNumC;\\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\\n}\\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\\n  int texelIndex = index / 2;\\n  int texR = texelIndex / texNumC;\\n  int texC = texelIndex - texR * texNumC;\\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\\n}\\n\",ma=\"\\nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\\n  int texNumC, int row, int col) {\\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\\n  int texR = texelIndex / texNumC;\\n  int texC = texelIndex - texR * texNumC;\\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\\n}\\n\",ga=\"\\nvec2 packedUVfrom3D(int texNumR, int texNumC,\\n    int texelsInBatch, int texelsInLogicalRow, int b,\\n    int row, int col) {\\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\\n  int texR = index / texNumC;\\n  int texC = index - texR * texNumC;\\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\\n}\\n\",ya=\"\\n  float getChannel(vec4 frag, vec2 innerDims) {\\n    vec2 modCoord = mod(innerDims, 2.);\\n    return modCoord.x == 0. ?\\n      (modCoord.y == 0. ? frag.r : frag.g) :\\n      (modCoord.y == 0. ? frag.b : frag.a);\\n  }\\n  float getChannel(vec4 frag, int dim) {\\n    float modCoord = mod(float(dim), 2.);\\n    return modCoord == 0. ? frag.r : frag.g;\\n  }\\n\";function xa(t){return\"offset\"+t}function ba(t){var e=t.name,n=k(t.shapeInfo.logicalShape);return n<2?\"return \"+e+\";\":\"\\n    for (int i = 0; i < \"+n+\"; i++) {\\n      if (i == index) {\\n        return \"+e+\"[i];\\n      }\\n    }\\n  \"}function wa(t){if(t<=1)return\"int\";if(2===t)return\"ivec2\";if(3===t)return\"ivec3\";if(4===t)return\"ivec4\";if(5===t)return\"ivec5\";if(6===t)return\"ivec6\";throw Error(\"GPU for rank \"+t+\" is not yet supported\")}function Ca(t,e){var n=JSON.parse(JSON.stringify(t));return n.shapeInfo.logicalShape=e,n}function Ea(t,e){return e.map((function(e){return t[e]})).join(\", \")}var Ra=function(t,e,n,r){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,C(t.length>2,(function(){return\"Packed arg\"+(n.charAt(0).toUpperCase()+n.slice(1))+\" supports only inputs with rank above 2.\"}));var o=t[t.length-1],a=Math.ceil(o/e);this.outputShape=t.slice(0,-1),a>1&&this.outputShape.push(a),r||this.variableNames.push(\"bestIndicesA\");var i,s,u=this.outputShape,c=u.length,l=wa(c),h=sa(\"coords\",c);if(1===a){var f=wa(s=c+1);i=\"\\n        \"+f+\" sourceLocR = \"+f+\"(\"+h.join()+\", 0);\\n        ++\"+h[c-1]+\";\\n        \"+f+\" sourceLocG = \"+f+\"(\"+h.join()+\", 0);\\n        ++\"+h[c-2]+\";\\n        \"+f+\" sourceLocA = \"+f+\"(\"+h.join()+\", 0);\\n        --\"+h[c-1]+\";\\n        \"+f+\" sourceLocB = \"+f+\"(\"+h.join()+\", 0);\\n        --\"+h[c-2]+\";\"}else s=c,i=\"\\n        \"+l+\" sourceLocR = coords;\\n        ++\"+h[c-1]+\";\\n        \"+l+\" sourceLocG = coords;\\n        ++\"+h[c-2]+\";\\n        \"+l+\" sourceLocA = coords;\\n        --\"+h[c-1]+\";\\n        \"+l+\" sourceLocB = coords;\\n        --\"+h[c-2]+\";\";var d=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"].slice(0,s),p=\".\"+d[s-1],v=d.map((function(t){return\"int \"+t})),m=sa(\"sourceLocR\",s-1).concat(\"inIdx.r\"),g=sa(\"sourceLocG\",s-1).concat(\"inIdx.g\"),y=sa(\"sourceLocB\",s-1).concat(\"inIdx.b\"),x=sa(\"sourceLocA\",s-1).concat(\"inIdx.a\"),b=\"max\"===n?\"greaterThan\":\"lessThan\",w=r?\"\":\"\\n          inIdx = round(vec4(getBestIndicesAChannel(\"+m.join()+\"),\\n                             getBestIndicesAChannel(\"+g.join()+\"),\\n                             getBestIndicesAChannel(\"+y.join()+\"),\\n                             getBestIndicesAChannel(\"+x.join()+\")));\",E=\"vec4(\\n            getAChannel(\"+m.join()+\"),\\n            hasNextCol ? getAChannel(\"+g.join()+\") : 0.,\\n            hasNextRow ? getAChannel(\"+y.join()+\") : 0.,\\n            hasNextRow && hasNextCol ? getAChannel(\"+x.join()+\") : 0.)\",R=r?\"\":\"\\n      float getBestIndicesAChannel(\"+v.join()+\") {\\n        return getChannel(getBestIndicesA(\"+d.join()+\"),\\n                                          vec2(\"+d.slice(-2).join()+\"));\\n      }\";this.userCode=\"\\n      float getAChannel(\"+v.join()+\") {\\n        return getChannel(getA(\"+d.join()+\"),\\n                               vec2(\"+d.slice(-2).join()+\"));\\n      }\\n      \"+R+\"\\n      void main() {\\n        \"+l+\" coords = getOutputCoords();\\n        bool hasNextCol = \"+h[c-1]+\" < \"+(u[c-1]-1)+\";\\n        bool hasNextRow = \"+h[c-2]+\" < \"+(u[c-2]-1)+\";\\n        \"+i+\"\\n        ivec4 srcIdx = ivec4(sourceLocR\"+p+\", sourceLocG\"+p+\",\\n          sourceLocB\"+p+\", sourceLocA\"+p+\") * \"+e+\";\\n        ivec4 inIdx = srcIdx;\\n        vec4 bestIndex = vec4(inIdx);\\n        vec4 bestValue = \"+E+\";\\n\\n        for (int i = 0; i < \"+e+\"; i++) {\\n          inIdx = srcIdx;\\n          \"+w+\"\\n          vec4 candidate = \"+E+\";\\n          bvec4 nan = isnan(candidate);\\n          bvec4 replace = bvec4(\\n            vec4(\"+b+\"(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\\n\\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\\n                           replace.y  ? candidate.y : bestValue.y,\\n                           replace.z  ? candidate.z : bestValue.z,\\n                           replace.w  ? candidate.w : bestValue.w);\\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\\n          srcIdx++;\\n        }\\n        setOutput(bestIndex);\\n      }\\n    \"},Ia=function(t){this.variableNames=[\"dy\"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=t.dilationHeight,i=t.dilationWidth,s=t.effectiveFilterHeight,u=t.effectiveFilterWidth,c=s-1-t.padInfo.top,l=u-1-t.padInfo.left,h=1/(e*n);this.userCode=\"\\n      const ivec2 pads = ivec2(\"+c+\", \"+l+\");\\n      const float avgMultiplier = float(\"+h+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n\\n        ivec2 dyRCCorner = coords.yz - pads;\\n        int dyRCorner = dyRCCorner.x;\\n        int dyCCorner = dyRCCorner.y;\\n\\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        for (int wR = 0; wR < \"+s+\";\\n            wR += \"+a+\") {\\n          float dyR = float(dyRCorner + wR) / \"+r+\".0;\\n\\n          if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 || fract(dyR) > 0.0) {\\n            continue;\\n          }\\n          int idyR = int(dyR);\\n\\n          for (int wC = 0; wC < \"+u+\";\\n            wC+= \"+i+\") {\\n            float dyC = float(dyCCorner + wC) / \"+o+\".0;\\n\\n            if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                fract(dyC) > 0.0) {\\n              continue;\\n            }\\n            int idyC = int(dyC);\\n\\n            float dyValue = getDy(b, idyR, idyC, d);\\n\\n            dotProd += dyValue * avgMultiplier;\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},ka=function(t){this.variableNames=[\"dy\"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,d=l-1-t.padInfo.front,p=h-1-t.padInfo.top,v=f-1-t.padInfo.left,m=1/(e*n*r);this.userCode=\"\\n      const ivec3 pads = ivec3(\"+d+\", \"+p+\", \"+v+\");\\n      const float avgMultiplier = float(\"+m+\");\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int ch = coords.u;\\n\\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\\n        int dyDCorner = dyCorner.x;\\n        int dyRCorner = dyCorner.y;\\n        int dyCCorner = dyCorner.z;\\n\\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\\n        // dx(xD, xR, xC, ch).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n\\n        for (int wD = 0; wD < \"+l+\";\\n            wD += \"+s+\") {\\n          float dyD = float(dyDCorner + wD) / \"+o+\".0;\\n\\n          if (dyD < 0.0 || dyD >= \"+t.outDepth+\".0 || fract(dyD) > 0.0) {\\n            continue;\\n          }\\n          int idyD = int(dyD);\\n\\n          for (int wR = 0; wR < \"+h+\";\\n              wR += \"+u+\") {\\n            float dyR = float(dyRCorner + wR) / \"+a+\".0;\\n\\n            if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 ||\\n                fract(dyR) > 0.0) {\\n              continue;\\n            }\\n            int idyR = int(dyR);\\n\\n            for (int wC = 0; wC < \"+f+\";\\n                wC += \"+c+\") {\\n              float dyC = float(dyCCorner + wC) / \"+i+\".0;\\n\\n              if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                  fract(dyC) > 0.0) {\\n                continue;\\n              }\\n              int idyC = int(dyC);\\n\\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\\n\\n              dotProd += dyValue * avgMultiplier;\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},Sa=function(t,e,n,r,o,a){this.outputShape=[],this.variableNames=[\"x\",\"mean\",\"variance\"],Ro(t,e),Ro(t,n);var i=\"0.0\";null!=r&&(Ro(t,r),this.variableNames.push(\"offset\"),i=\"getOffsetAtOutCoords()\");var s=\"1.0\";null!=o&&(Ro(t,o),this.variableNames.push(\"scale\"),s=\"getScaleAtOutCoords()\"),this.outputShape=t,this.userCode=\"\\n      void main() {\\n        float x = getXAtOutCoords();\\n        float mean = getMeanAtOutCoords();\\n        float variance = getVarianceAtOutCoords();\\n        float offset = \"+i+\";\\n        float scale = \"+s+\";\\n        float inv = scale * inversesqrt(variance + float(\"+a+\"));\\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\\n      }\\n    \"},Aa=function(t,e,n,r,o,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=[\"x\",\"mean\",\"variance\"],Ro(t,e),Ro(t,n);var i=\"vec4(0.0)\";null!=r&&(Ro(t,r),this.variableNames.push(\"offset\"),i=\"getOffsetAtOutCoords()\");var s=\"vec4(1.0)\";null!=o&&(Ro(t,o),this.variableNames.push(\"scale\"),s=\"getScaleAtOutCoords()\"),this.outputShape=t,this.userCode=\"\\n      void main() {\\n        vec4 offset = \"+i+\";\\n        vec4 scale = \"+s+\";\\n\\n        vec4 x = getXAtOutCoords();\\n        vec4 mean = getMeanAtOutCoords();\\n        vec4 variance = getVarianceAtOutCoords();\\n\\n        vec4 inv = scale * inversesqrt(variance + vec4(\"+a+\"));\\n\\n        setOutput((x - mean) * inv + offset);\\n      }\\n    \"},Da=\"return areal * breal - aimag * bimag;\",Ta=\"return areal * bimag + aimag * breal;\",Na=function(t,e,n){this.variableNames=[\"AReal\",\"AImag\",\"BReal\",\"BImag\"],this.outputShape=Ro(e,n),this.userCode=\"\\n      float binaryOpComplex(\\n          float areal, float aimag, float breal, float bimag) {\\n        \"+t+\"\\n      }\\n\\n      void main() {\\n        float areal = getARealAtOutCoords();\\n        float aimag = getAImagAtOutCoords();\\n        float breal = getBRealAtOutCoords();\\n        float bimag = getBImagAtOutCoords();\\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\\n      }\\n    \"},Fa=\"return a + b;\",_a=\"return a - b;\",Oa=\"return a * b;\",Ma=\"return (a < 0.) ? b * a : a;\",Ba=function(t,e,n){this.variableNames=[\"A\",\"B\"],this.outputShape=Ro(e,n),this.userCode=\"\\n      float binaryOperation(float a, float b) {\\n        \"+t+\"\\n      }\\n\\n      void main() {\\n        float a = getAAtOutCoords();\\n        float b = getBAtOutCoords();\\n        setOutput(binaryOperation(a, b));\\n      }\\n    \"},Pa=\"\\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\\n\",La=function(t,e,n,r){void 0===r&&(r=!1),this.variableNames=[\"A\",\"B\"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=Ro(e,n);var o=this.outputShape.length,a=\"\";if(r)if(0===o||1===k(this.outputShape))a=\"\\n          result.y = 0.;\\n          result.z = 0.;\\n          result.w = 0.;\\n        \";else if(a=\"\\n          \"+wa(o)+\" coords = getOutputCoords();\\n        \",1===o)a+=\"\\n            result.y = (coords + 1) >= \"+this.outputShape[0]+\" ? 0. : result.y;\\n            result.z = 0.;\\n            result.w = 0.;\\n          \";else{var i=sa(\"coords\",o);a+=\"\\n            bool nextRowOutOfBounds =\\n              (\"+i[o-2]+\" + 1) >= \"+this.outputShape[o-2]+\";\\n            bool nextColOutOfBounds =\\n              (\"+i[o-1]+\" + 1) >= \"+this.outputShape[o-1]+\";\\n            result.y = nextColOutOfBounds ? 0. : result.y;\\n            result.z = nextRowOutOfBounds ? 0. : result.z;\\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\\n          \"}this.userCode=\"\\n      vec4 binaryOperation(vec4 a, vec4 b) {\\n        \"+t+\"\\n      }\\n\\n      void main() {\\n        vec4 a = getAAtOutCoords();\\n        vec4 b = getBAtOutCoords();\\n\\n        vec4 result = binaryOperation(a, b);\\n        \"+a+\"\\n\\n        setOutput(result);\\n      }\\n    \"},Wa=function(){function t(t){this.variableNames=[\"A\"],this.outputShape=t,this.userCode=\"\\n      uniform float minVal;\\n      uniform float maxVal;\\n\\n      void main() {\\n        float value = getAAtOutCoords();\\n        if (isnan(value)) {\\n          setOutput(value);\\n          return;\\n        }\\n\\n        setOutput(clamp(value, minVal, maxVal));\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,o){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(o,\"minVal\"),n.maxLoc=r.getUniformLocationNoThrow(o,\"maxVal\")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e)}},t}(),Ua=function(){function t(t){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode=\"\\n      uniform float minVal;\\n      uniform float maxVal;\\n\\n      void main() {\\n        vec4 value = getAAtOutCoords();\\n\\n        if (any(isnan(value))) {\\n          setOutput(value);\\n          return;\\n        }\\n\\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,o){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(o,\"minVal\"),n.maxLoc=r.getUniformLocationNoThrow(o,\"maxVal\")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e)}},t}(),Va=function(t){this.variableNames=[\"real\",\"imag\"],this.outputShape=t,this.userCode=\"\\n      void main() {\\n        float re = abs(getRealAtOutCoords());\\n        float im = abs(getImagAtOutCoords());\\n        float mx = max(re, im);\\n\\n        // sadly the length function in glsl is not underflow-safe\\n        // (at least not on Intel GPUs). So the safe solution is\\n        // to ensure underflow-safety in all cases.\\n        setOutput(\\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\\n        );\\n      }\\n    \"},za=function(t){this.outputShape=[],this.outputShape=Sn(t,1),this.variableNames=t.map((function(t,e){return\"T\"+e}));var e=new Array(t.length-1);e[0]=t[0][1];for(var n=1;n<e.length;n++)e[n]=e[n-1]+t[n][1];var r=[\"if (yC < \"+e[0]+\") setOutput(getT0(yR, yC));\"];for(n=1;n<e.length;n++){var o=e[n-1];r.push(\"else if (yC < \"+e[n]+\") setOutput(getT\"+n+\"(yR, yC-\"+o+\"));\")}var a=e.length,i=e[e.length-1];r.push(\"else setOutput(getT\"+a+\"(yR, yC-\"+i+\"));\"),this.userCode=\"\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int yR = coords.x;\\n        int yC = coords.y;\\n\\n        \"+r.join(\"\\n        \")+\"\\n      }\\n    \"},Ga=function(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=Sn(t,e);var n=this.outputShape,r=n.length,o=wa(r),a=sa(\"coords\",r),i=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"].slice(0,r);this.variableNames=t.map((function(t,e){return\"T\"+e}));var s=new Array(t.length-1);s[0]=t[0][e];for(var u=1;u<s.length;u++)s[u]=s[u-1]+t[u][e];var c=i[e],l=i.slice(-2),h=i.join(),f=\"if (\"+c+\" < \"+s[0]+\") {\\n        return getChannel(\\n            getT0(\"+h+\"), vec2(\"+l.join()+\"));\\n        }\";for(u=1;u<s.length;u++){var d=s[u-1];f+=\"\\n        if (\"+c+\" < \"+s[u]+\"  && \"+c+\" >= \"+s[u-1]+\") {\\n          return getChannel(\\n            getT\"+u+\"(\"+Ha(i,c,d)+\"),\\n            vec2(\"+Ha(l,c,d)+\"));\\n        }\"}var p=s.length,v=s[s.length-1];f+=\"\\n        return getChannel(\\n          getT\"+p+\"(\"+Ha(i,c,v)+\"),\\n          vec2(\"+Ha(l,c,v)+\"));\",this.userCode=\"\\n      float getValue(\"+i.map((function(t){return\"int \"+t}))+\") {\\n        \"+f+\"\\n      }\\n\\n      void main() {\\n        \"+o+\" coords = getOutputCoords();\\n        vec4 result = vec4(getValue(\"+a+\"), 0., 0., 0.);\\n\\n        \"+a[r-1]+\" = \"+a[r-1]+\" + 1;\\n        if (\"+a[r-1]+\" < \"+n[r-1]+\") {\\n          result.g = getValue(\"+a+\");\\n        }\\n\\n        \"+a[r-2]+\" = \"+a[r-2]+\" + 1;\\n        if (\"+a[r-2]+\" < \"+n[r-2]+\") {\\n          result.a = getValue(\"+a+\");\\n        }\\n\\n        \"+a[r-1]+\" = \"+a[r-1]+\" - 1;\\n        if (\"+a[r-2]+\" < \"+n[r-2]+\" &&\\n            \"+a[r-1]+\" < \"+n[r-1]+\") {\\n          result.b = getValue(\"+a+\");\\n        }\\n        setOutput(result);\\n      }\\n    \"};function Ha(t,e,n){var r=t.indexOf(e);return t.map((function(t,e){return e===r?t+\" - \"+n:t})).join()}var qa=function(t){this.variableNames=[\"x\",\"dy\"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,a=\"channelsLast\"===t.dataFormat;this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int wR = coords.x;\\n        int wC = coords.y;\\n        int d1 = coords.z;\\n        int d2 = coords.w;\\n\\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n\\n        for (int b = 0; b < \"+t.batchSize+\"; b++) {\\n          for (int yR = 0; yR < \"+t.outHeight+\"; yR++) {\\n            int xR = wR + yR * \"+e+\" - \"+r+\";\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int yC = 0; yC < \"+t.outWidth+\"; yC++) {\\n              int xC = wC + yC * \"+n+\" - \"+o+\";\\n\\n              if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                continue;\\n              }\\n\\n              if (\"+a+\") {\\n                float dyValue = getDy(b, yR, yC, d2);\\n                float xValue = getX(b, xR, xC, d1);\\n                dotProd += (xValue * dyValue);\\n              } else {\\n                float dyValue = getDy(b, d2, yR, yC);\\n                float xValue = getX(b, d1, xR, xC);\\n                dotProd += (xValue * dyValue);\\n              }\\n\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},Ka=function(t){this.variableNames=[\"dy\",\"W\"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=\"channelsLast\"===t.dataFormat,i=e-1-t.padInfo.top,s=n-1-t.padInfo.left,u=a?1:2,c=a?2:3,l=a?3:1;this.userCode=\"\\n      const ivec2 pads = ivec2(\"+i+\", \"+s+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int d1 = coords[\"+l+\"];\\n\\n        ivec2 dyCorner = ivec2(coords[\"+u+\"], coords[\"+c+\"]) - pads;\\n        int dyRCorner = dyCorner.x;\\n        int dyCCorner = dyCorner.y;\\n\\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        for (int wR = 0; wR < \"+e+\"; wR++) {\\n          float dyR = float(dyRCorner + wR) / \"+r+\".0;\\n\\n          if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 || fract(dyR) > 0.0) {\\n            continue;\\n          }\\n          int idyR = int(dyR);\\n\\n          int wRPerm = \"+e+\" - 1 - wR;\\n\\n          for (int wC = 0; wC < \"+n+\"; wC++) {\\n            float dyC = float(dyCCorner + wC) / \"+o+\".0;\\n\\n            if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                fract(dyC) > 0.0) {\\n              continue;\\n            }\\n            int idyC = int(dyC);\\n\\n            int wCPerm = \"+n+\" - 1 - wC;\\n\\n            for (int d2 = 0; d2 < \"+t.outChannels+\"; d2++) {\\n\\n              if (\"+a+\") {\\n                float xValue = getDy(batch, idyR, idyC, d2);\\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\\n                dotProd += xValue * wValue;\\n              } else {\\n                float xValue = getDy(batch, d2, idyR, idyC);\\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\\n                dotProd += xValue * wValue;\\n              }\\n\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},ja=function(t){this.variableNames=[\"x\",\"dy\"],this.outputShape=t.filterShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.padInfo.front,a=t.padInfo.top,i=t.padInfo.left;this.userCode=\"\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int wF = coords.x;\\n        int wR = coords.y;\\n        int wC = coords.z;\\n        int d1 = coords.w;\\n        int d2 = coords.u;\\n\\n        float dotProd = 0.0;\\n\\n        for (int b = 0; b < \"+t.batchSize+\"; b++) {\\n          for (int yF = 0; yF < \"+t.outDepth+\"; yF++) {\\n            int xF = wF + yF * \"+e+\" - \"+o+\";\\n\\n            if (xF < 0 || xF >= \"+t.inDepth+\") {\\n              continue;\\n            }\\n\\n            for (int yR = 0; yR < \"+t.outHeight+\"; yR++) {\\n              int xR = wR + yR * \"+n+\" - \"+a+\";\\n\\n              if (xR < 0 || xR >= \"+t.inHeight+\") {\\n                continue;\\n              }\\n\\n              for (int yC = 0; yC < \"+t.outWidth+\"; yC++) {\\n                int xC = wC + yC * \"+r+\" - \"+i+\";\\n\\n                if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                  continue;\\n                }\\n\\n                float dyValue = getDy(b, yF, yR, yC, d2);\\n                float xValue = getX(b, xF, xR, xC, d1);\\n                dotProd += (xValue * dyValue);\\n              }\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},Xa=function(t){this.variableNames=[\"dy\",\"W\"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,s=e-1-t.padInfo.front,u=n-1-t.padInfo.top,c=r-1-t.padInfo.left;this.userCode=\"\\n      const ivec3 pads = ivec3(\"+s+\", \"+u+\", \"+c+\");\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int d1 = coords.u;\\n\\n\\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\\n        int dyFCorner = dyCorner.x;\\n        int dyRCorner = dyCorner.y;\\n        int dyCCorner = dyCorner.z;\\n\\n        float dotProd = 0.0;\\n        for (int wF = 0; wF < \"+e+\"; wF++) {\\n          float dyF = float(dyFCorner + wF) / \"+o+\".0;\\n\\n          if (dyF < 0.0 || dyF >= \"+t.outDepth+\".0 || fract(dyF) > 0.0) {\\n            continue;\\n          }\\n          int idyF = int(dyF);\\n\\n          int wFPerm = \"+e+\" - 1 - wF;\\n\\n          for (int wR = 0; wR < \"+n+\"; wR++) {\\n            float dyR = float(dyRCorner + wR) / \"+a+\".0;\\n\\n            if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 ||\\n              fract(dyR) > 0.0) {\\n              continue;\\n            }\\n            int idyR = int(dyR);\\n\\n            int wRPerm = \"+n+\" - 1 - wR;\\n\\n            for (int wC = 0; wC < \"+r+\"; wC++) {\\n              float dyC = float(dyCCorner + wC) / \"+i+\".0;\\n\\n              if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                  fract(dyC) > 0.0) {\\n                continue;\\n              }\\n              int idyC = int(dyC);\\n\\n              int wCPerm = \"+r+\" - 1 - wC;\\n\\n              for (int d2 = 0; d2 < \"+t.outChannels+\"; d2++) {\\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\\n                dotProd += xValue * wValue;\\n              }\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},Ya=function(t){this.variableNames=[\"x\",\"dy\"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,a=t.outChannels/t.inChannels;this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int wR = coords.x;\\n        int wC = coords.y;\\n        int d1 = coords.z;\\n        int dm = coords.w;\\n        int d2 = d1 * \"+a+\" + dm;\\n\\n        float dotProd = 0.0;\\n\\n        // TO DO: Vec4 over the batch size\\n        for (int b = 0; b < \"+t.batchSize+\"; b++) {\\n          for (int yR = 0; yR < \"+t.outHeight+\"; yR++) {\\n            int xR = wR + yR * \"+e+\" - \"+r+\";\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int yC = 0; yC < \"+t.outWidth+\"; yC++) {\\n              int xC = wC + yC * \"+n+\" - \"+o+\";\\n\\n              if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                continue;\\n              }\\n\\n              float dyValue = getDy(b, yR, yC, d2);\\n              float xValue = getX(b, xR, xC, d1);\\n              dotProd += (xValue * dyValue);\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},$a=function(t){this.variableNames=[\"dy\",\"W\"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,a=e-1-t.padInfo.top,i=n-1-t.padInfo.left,s=t.outChannels/t.inChannels;this.userCode=\"\\n      const ivec2 pads = ivec2(\"+a+\", \"+i+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int d1 = coords[3];\\n        ivec2 dyCorner = coords.yz - pads;\\n        int dyRCorner = dyCorner.x;\\n        int dyCCorner = dyCorner.y;\\n\\n        float dotProd = 0.0;\\n\\n        for (int wR = 0; wR < \"+e+\"; wR++) {\\n          float dyR = float(dyRCorner + wR) / \"+r+\".0;\\n\\n          if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 || fract(dyR) > 0.0) {\\n            continue;\\n          }\\n          int idyR = int(dyR);\\n\\n          int wRPerm = \"+e+\" - 1 - wR;\\n\\n          for (int wC = 0; wC < \"+n+\"; wC++) {\\n            float dyC = float(dyCCorner + wC) / \"+o+\".0;\\n\\n            if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                fract(dyC) > 0.0) {\\n              continue;\\n            }\\n            int idyC = int(dyC);\\n\\n            int wCPerm = \"+n+\" - 1 - wC;\\n\\n            // TO DO: Vec4 over the channelMul\\n            for (int dm = 0; dm < \"+s+\"; dm++) {\\n              int d2 = d1 * \"+s+\" + dm;\\n              float xValue = getDy(batch, idyR, idyC, d2);\\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\\n              dotProd += xValue * wValue;\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},Qa=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=[\"x\",\"W\"],this.outputShape=t.outShape;var o=t.padInfo.top,a=t.padInfo.left,i=t.strideHeight,s=t.strideWidth,u=t.dilationHeight,c=t.dilationWidth,l=t.filterHeight,h=t.filterWidth,f=4*Math.floor(t.inChannels/4),d=t.inChannels%4,p=\"channelsLast\"===t.dataFormat,v=p?1:2,m=p?2:3,g=p?3:1,y=\"\",x=\"\";n&&(y=r?\"float activation(float a) {\\n          float b = getPreluActivationWeightsAtOutCoords();\\n          \"+n+\"\\n        }\":\"\\n          float activation(float x) {\\n            \"+n+\"\\n          }\\n        \",x=\"result = activation(result);\");var b=e?\"result += getBiasAtOutCoords();\":\"\";e&&this.variableNames.push(\"bias\"),r&&this.variableNames.push(\"preluActivationWeights\"),this.userCode=\"\\n      \"+y+\"\\n\\n      const ivec2 strides = ivec2(\"+i+\", \"+s+\");\\n      const ivec2 pads = ivec2(\"+o+\", \"+a+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int d2 = coords[\"+g+\"];\\n\\n        ivec2 xRCCorner =\\n            ivec2(coords[\"+v+\"], coords[\"+m+\"]) * strides - pads;\\n        int xRCorner = xRCCorner.x;\\n        int xCCorner = xRCCorner.y;\\n\\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        for (int wR = 0; wR < \"+l+\"; wR++) {\\n          int xR = xRCorner + wR * \"+u+\";\\n\\n          if (xR < 0 || xR >= \"+t.inHeight+\") {\\n            continue;\\n          }\\n\\n          for (int wC = 0; wC < \"+h+\"; wC++) {\\n            int xC = xCCorner + wC * \"+c+\";\\n\\n            if (xC < 0 || xC >= \"+t.inWidth+\") {\\n              continue;\\n            }\\n\\n            for (int d1 = 0; d1 < \"+f+\"; d1 += 4) {\\n              vec4 wValues = vec4(\\n                getW(wR, wC, d1, d2),\\n                getW(wR, wC, d1 + 1, d2),\\n                getW(wR, wC, d1 + 2, d2),\\n                getW(wR, wC, d1 + 3, d2)\\n              );\\n\\n              if (\"+p+\") {\\n                vec4 xValues = vec4(\\n                  getX(batch, xR, xC, d1),\\n                  getX(batch, xR, xC, d1 + 1),\\n                  getX(batch, xR, xC, d1 + 2),\\n                  getX(batch, xR, xC, d1 + 3)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              } else {\\n                vec4 xValues = vec4(\\n                  getX(batch, d1, xR, xC),\\n                  getX(batch, d1 + 1, xR, xC),\\n                  getX(batch, d1 + 2, xR, xC),\\n                  getX(batch, d1 + 3, xR, xC)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              }\\n            }\\n\\n            if (\"+(1===d)+\") {\\n\\n              if (\"+p+\") {\\n                dotProd +=\\n                    getX(batch, xR, xC, \"+f+\") *\\n                    getW(wR, wC, \"+f+\", d2);\\n              } else {\\n                dotProd +=\\n                    getX(batch, \"+f+\", xR, xC) *\\n                    getW(wR, wC, \"+f+\", d2);\\n              }\\n\\n            } else if (\"+(2===d)+\") {\\n              vec2 wValues = vec2(\\n                getW(wR, wC, \"+f+\", d2),\\n                getW(wR, wC, \"+f+\" + 1, d2)\\n              );\\n\\n              if (\"+p+\") {\\n                vec2 xValues = vec2(\\n                  getX(batch, xR, xC, \"+f+\"),\\n                  getX(batch, xR, xC, \"+f+\" + 1)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              } else {\\n                vec2 xValues = vec2(\\n                  getX(batch, \"+f+\", xR, xC),\\n                  getX(batch, \"+f+\" + 1, xR, xC)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              }\\n\\n            } else if (\"+(3===d)+\") {\\n              vec3 wValues = vec3(\\n                getW(wR, wC, \"+f+\", d2),\\n                getW(wR, wC, \"+f+\" + 1, d2),\\n                getW(wR, wC, \"+f+\" + 2, d2)\\n              );\\n\\n              if (\"+p+\") {\\n                vec3 xValues = vec3(\\n                  getX(batch, xR, xC, \"+f+\"),\\n                  getX(batch, xR, xC, \"+f+\" + 1),\\n                  getX(batch, xR, xC, \"+f+\" + 2)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              } else {\\n                vec3 xValues = vec3(\\n                  getX(batch, \"+f+\", xR, xC),\\n                  getX(batch, \"+f+\" + 1, xR, xC),\\n                  getX(batch, \"+f+\" + 2, xR, xC)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              }\\n\\n            }\\n          }\\n        }\\n\\n        float result = dotProd;\\n        \"+b+\"\\n        \"+x+\"\\n        setOutput(result);\\n      }\\n    \"},Ja=function(t){this.variableNames=[\"x\",\"W\"],this.outputShape=t.outShape;var e=t.padInfo.front,n=t.padInfo.top,r=t.padInfo.left,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.filterDepth,h=t.filterHeight,f=t.filterWidth,d=4*Math.floor(t.inChannels/4),p=t.inChannels%4;this.userCode=\"\\n      const ivec3 strides = ivec3(\"+o+\", \"+a+\", \"+i+\");\\n      const ivec3 pads = ivec3(\"+e+\", \"+n+\", \"+r+\");\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int d2 = coords.u;\\n\\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\\n        int xFCorner = xFRCCorner.x;\\n        int xRCorner = xFRCCorner.y;\\n        int xCCorner = xFRCCorner.z;\\n\\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\\n        // values in that axis.\\n        float dotProd = 0.0;\\n        for (int wF = 0; wF < \"+l+\"; wF++) {\\n          int xF = xFCorner + wF * \"+s+\";\\n\\n          if (xF < 0 || xF >= \"+t.inDepth+\") {\\n            continue;\\n          }\\n\\n          for (int wR = 0; wR < \"+h+\"; wR++) {\\n            int xR = xRCorner + wR * \"+u+\";\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int wC = 0; wC < \"+f+\"; wC++) {\\n              int xC = xCCorner + wC * \"+c+\";\\n\\n              if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                continue;\\n              }\\n\\n              for (int d1 = 0; d1 < \"+d+\"; d1 += 4) {\\n                vec4 xValues = vec4(\\n                  getX(batch, xF, xR, xC, d1),\\n                  getX(batch, xF, xR, xC, d1 + 1),\\n                  getX(batch, xF, xR, xC, d1 + 2),\\n                  getX(batch, xF, xR, xC, d1 + 3)\\n                );\\n                vec4 wValues = vec4(\\n                  getW(wF, wR, wC, d1, d2),\\n                  getW(wF, wR, wC, d1 + 1, d2),\\n                  getW(wF, wR, wC, d1 + 2, d2),\\n                  getW(wF, wR, wC, d1 + 3, d2)\\n                );\\n\\n                dotProd += dot(xValues, wValues);\\n              }\\n\\n              if (\"+(1===p)+\") {\\n                dotProd +=\\n                  getX(batch, xF, xR, xC, \"+d+\") *\\n                  getW(wF, wR, wC, \"+d+\", d2);\\n              } else if (\"+(2===p)+\") {\\n                vec2 xValues = vec2(\\n                  getX(batch, xF, xR, xC, \"+d+\"),\\n                  getX(batch, xF, xR, xC, \"+d+\" + 1)\\n                );\\n                vec2 wValues = vec2(\\n                  getW(wF, wR, wC, \"+d+\", d2),\\n                  getW(wF, wR, wC, \"+d+\" + 1, d2)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              } else if (\"+(3===p)+\") {\\n                vec3 xValues = vec3(\\n                  getX(batch, xF, xR, xC, \"+d+\"),\\n                  getX(batch, xF, xR, xC, \"+d+\" + 1),\\n                  getX(batch, xF, xR, xC, \"+d+\" + 2)\\n                );\\n                vec3 wValues = vec3(\\n                  getW(wF, wR, wC, \"+d+\", d2),\\n                  getW(wF, wR, wC, \"+d+\" + 1, d2),\\n                  getW(wF, wR, wC, \"+d+\" + 2, d2)\\n                );\\n                dotProd += dot(xValues, wValues);\\n              }\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},Za=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=[\"x\",\"W\"],this.outputShape=t.outShape;var o=t.inHeight,a=t.inWidth,i=t.padInfo.top,s=t.padInfo.left,u=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,d=t.filterWidth,p=t.outChannels/t.inChannels,v=\"\",m=\"\";n&&(v=r?\"float activation(float a) {\\n          float b = getPreluActivationWeightsAtOutCoords();\\n          \"+n+\"\\n        }\":\"\\n          float activation(float x) {\\n            \"+n+\"\\n          }\\n        \",m=\"result = activation(result);\");var g=e?\"result += getBiasAtOutCoords();\":\"\";e&&this.variableNames.push(\"bias\"),r&&this.variableNames.push(\"preluActivationWeights\"),this.userCode=\"\\n      \"+v+\"\\n\\n      const ivec2 strides = ivec2(\"+u+\", \"+c+\");\\n      const ivec2 pads = ivec2(\"+i+\", \"+s+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords.x;\\n        ivec2 xRCCorner = coords.yz * strides - pads;\\n        int d2 = coords.w;\\n        int d1 = d2 / \"+p+\";\\n        int q = d2 - d1 * \"+p+\";\\n\\n        int xRCorner = xRCCorner.x;\\n        int xCCorner = xRCCorner.y;\\n\\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\\n        for (int wR = 0; wR < \"+f+\"; wR++) {\\n          int xR = xRCorner + wR * \"+l+\";\\n\\n          if (xR < 0 || xR >= \"+o+\") {\\n            continue;\\n          }\\n\\n          for (int wC = 0; wC < \"+d+\"; wC++) {\\n            int xC = xCCorner + wC * \"+h+\";\\n\\n            if (xC < 0 || xC >= \"+a+\") {\\n              continue;\\n            }\\n\\n            float xVal = getX(batch, xR, xC, d1);\\n            float wVal = getW(wR, wC, d1, q);\\n            dotProd += xVal * wVal;\\n          }\\n        }\\n\\n        float result = dotProd;\\n        \"+g+\"\\n        \"+m+\"\\n        setOutput(result);\\n      }\\n    \"},ti=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=[\"x\",\"W\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.outShape;for(var o=t.inHeight,a=t.inWidth,i=t.padInfo.top,s=t.padInfo.left,u=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,d=t.filterWidth,p=d,v=\"int xR; int xC; int xCOffset;\",m=0;m<f;m++)for(var g=0;g<d;g++)v+=\"\\n          vec4 xTexelR\"+m+\"C\"+2*g+\" = vec4(0.);\\n          vec4 wR\"+m+\"C\"+g+\" = vec4(0.);\\n          vec4 xR\"+m+\"C\"+g+\" = vec4(0.);\";for(m=0;m<f;m++)for(var y=0;y<p;y++){if(v+=\"\\n          xR = xRCorner + \"+m*l+\";\\n          xC = xCCorner + \"+(g=2*y)*h+\";\\n        \",1===c){if(g<d&&(v+=s%2==1?\"\\n                xCOffset = xC + 1;\\n                if(xR >= 0 && xR < \"+o+\" && xCOffset >= 0 && xCOffset < \"+a+\") {\\n                  xTexelR\"+m+\"C\"+g+\" = getX(batch, xR, xCOffset, d1);\\n\\n                  // Need to manually clear unused channels in case\\n                  // we're reading from recycled texture.\\n                  if(xCOffset + 1 >= \"+a+\") {\\n                    xTexelR\"+m+\"C\"+g+\".zw = vec2(0.);\\n                  }\\n                } else {\\n                  xTexelR\"+m+\"C\"+g+\" = vec4(0.);\\n                }\\n\\n                xCOffset = xC + 1 - 2;\\n                if(xR >= 0 && xR < \"+o+\" && xCOffset >= 0 && xCOffset < \"+a+\") {\\n                  vec4 previous = getX(batch, xR, xCOffset, d1);\\n\\n                  // Need to manually clear unused channels in case\\n                  // we're reading from recycled texture.\\n                  if(xCOffset + 1 >= \"+a+\") {\\n                    previous.zw = vec2(0.);\\n                  }\\n\\n                  xR\"+m+\"C\"+g+\" = vec4(previous.zw, xTexelR\"+m+\"C\"+g+\".xy);\\n                } else {\\n                  xR\"+m+\"C\"+g+\" = vec4(0, 0, xTexelR\"+m+\"C\"+g+\".xy);\\n                }\\n              \":\"\\n                if(xR >= 0 && xR < \"+o+\" && xC >= 0 && xC < \"+a+\") {\\n                  xTexelR\"+m+\"C\"+g+\" = getX(batch, xR, xC, d1);\\n                } else {\\n                  xTexelR\"+m+\"C\"+g+\" = vec4(0.);\\n                }\\n\\n                xR\"+m+\"C\"+g+\" = xTexelR\"+m+\"C\"+g+\";\\n              \",g+1<d)){var x=s%2==0?b(h):h;h%2==0&&s%2==1||h%2!=0&&s%2!=1?(v+=\"\\n                  xCOffset = xC + \"+s%2+\" + \"+x+\";\\n\\n                  if(xR >= 0 && xR < \"+o+\" &&\\n                    xCOffset >= 0 && xCOffset < \"+a+\") {\\n                    xTexelR\"+m+\"C\"+(g+2)+\" = getX(batch, xR, xCOffset, d1);\\n                  }\\n                \",h>1&&(v+=\"\\n                    xCOffset -= 2;\\n                    if(xR >= 0 && xR < \"+o+\" &&\\n                      xCOffset >= 0 && xCOffset < \"+a+\") {\\n                      xTexelR\"+m+\"C\"+g+\" = getX(batch, xR, xCOffset, d1);\\n                    } else {\\n                      xTexelR\"+m+\"C\"+g+\" = vec4(0.);\\n                    }\\n                  \"),v+=\"\\n                  xR\"+m+\"C\"+(g+1)+\" = vec4(\\n                    xTexelR\"+m+\"C\"+g+\".zw, xTexelR\"+m+\"C\"+(g+2)+\".xy);\\n                \"):v+=\"\\n                  xCOffset = xC + \"+x+\";\\n\\n                  if(xR >= 0 && xR < \"+o+\" &&\\n                    xCOffset >= 0 && xCOffset < \"+a+\") {\\n                    xTexelR\"+m+\"C\"+(g+2)+\" = getX(batch, xR, xCOffset, d1);\\n                  }\\n\\n                  xR\"+m+\"C\"+(g+1)+\" = xTexelR\"+m+\"C\"+(g+2)+\";\\n                \"}}else g<d&&(v+=\"\\n              if(xR >= 0 && xR < \"+o+\") {\\n            \",s%2==1?(v+=\"\\n                xCOffset = xC + 1 - \"+c+\";\\n                if(xCOffset >= 0 && xCOffset < \"+a+\") {\\n                  xTexelR\"+m+\"C\"+g+\" = getX(batch, xR, xCOffset, d1);\\n                } else {\\n                  xTexelR\"+m+\"C\"+g+\" = vec4(0.);\\n                }\\n\\n                if(xC + 1 >= 0 && xC + 1 < \"+a+\") {\\n                  xTexelR\"+m+\"C\"+(g+2)+\" = getX(batch, xR, xC + 1, d1);\\n                } else {\\n                  xTexelR\"+m+\"C\"+(g+2)+\" = vec4(0.);\\n                }\\n\\n                xR\"+m+\"C\"+g+\" = vec4(\\n                  xTexelR\"+m+\"C\"+g+\".zw, xTexelR\"+m+\"C\"+(g+2)+\".zw);\\n              \",g+1<d&&(v+=\"\\n                  vec4 final = vec4(0.);\\n                  xCOffset = xC + 1 + \"+c+\";\\n                  if(xCOffset >= 0 && xCOffset < \"+a+\") {\\n                    final = getX(batch, xR, xCOffset, d1);\\n                  }\\n                  xR\"+m+\"C\"+(g+1)+\" = vec4(xTexelR\"+m+\"C\"+(g+2)+\".xy, final.xy);\\n                \")):(v+=\"\\n                if(xC >= 0 && xC < \"+a+\") {\\n                  xTexelR\"+m+\"C\"+g+\" = getX(batch, xR, xC, d1);\\n                } else {\\n                  xTexelR\"+m+\"C\"+g+\" = vec4(0.);\\n                }\\n\\n                xCOffset = xC + \"+c+\";\\n                if(xCOffset >= 0 && xCOffset < \"+a+\") {\\n                  xTexelR\"+m+\"C\"+(g+2)+\" = getX(batch, xR, xCOffset, d1);\\n                } else {\\n                  xTexelR\"+m+\"C\"+(g+2)+\" = vec4(0.);\\n                }\\n\\n                xR\"+m+\"C\"+g+\" = vec4(\\n                  xTexelR\"+m+\"C\"+g+\".xy, xTexelR\"+m+\"C\"+(g+2)+\".xy);\\n              \",g+1<d&&(v+=\"\\n                  xR\"+m+\"C\"+(g+1)+\" = vec4(\\n                    xTexelR\"+m+\"C\"+g+\".zw, xTexelR\"+m+\"C\"+(g+2)+\".zw);\\n                \")),v+=\"}\");g<d&&(v+=\"\\n            vec4 wTexelR\"+m+\"C\"+g+\" = getW(\"+m+\", \"+g+\", d1, q);\\n            wR\"+m+\"C\"+g+\" = vec4(wTexelR\"+m+\"C\"+g+\".xz, wTexelR\"+m+\"C\"+g+\".xz);\\n          \",g+1<d&&(v+=\"\\n              vec4 wTexelR\"+m+\"C\"+(g+1)+\" = getW(\"+m+\", \"+(g+1)+\", d1, q);\\n              wR\"+m+\"C\"+(g+1)+\" =\\n                vec4(wTexelR\"+m+\"C\"+(g+1)+\".xz, wTexelR\"+m+\"C\"+(g+1)+\".xz);\"))}for(m=0;m<f;m++)for(g=0;g<d;g++)v+=\"dotProd += xR\"+m+\"C\"+g+\" * wR\"+m+\"C\"+g+\";\";var w=\"\",C=\"\";n&&(w=r?\"vec4 activation(vec4 a) {\\n          vec4 b = getPreluActivationWeightsAtOutCoords();\\n          \"+n+\"\\n        }\":\"vec4 activation(vec4 x) {\\n          \"+n+\"\\n        }\",C=\"result = activation(result);\");var E=e?\"result += getBiasAtOutCoords();\":\"\";e&&this.variableNames.push(\"bias\"),r&&this.variableNames.push(\"preluActivationWeights\"),this.userCode=\"\\n      \"+w+\"\\n\\n      const ivec2 strides = ivec2(\"+u+\", \"+c+\");\\n      const ivec2 pads = ivec2(\"+i+\", \"+s+\");\\n\\n      void main() {\\n\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords.x;\\n        ivec2 xRCCorner = coords.yz * strides - pads;\\n        int d2 = coords.w;\\n        int d1 = d2;\\n        int q = 0;\\n        int xRCorner = xRCCorner.x;\\n        int xCCorner = xRCCorner.y;\\n\\n        vec4 dotProd = vec4(0.);\\n\\n        \"+v+\"\\n\\n        vec4 result = dotProd;\\n        \"+E+\"\\n        \"+C+\"\\n        setOutput(result);\\n      }\\n    \"},ei=function(t,e,n,r,o){this.variableNames=[\"Image\",\"Boxes\",\"BoxInd\"],this.outputShape=[];var a=t[0],i=t[1],s=t[2],u=t[3],c=e[0],l=n[0],h=n[1];this.outputShape=[c,l,h,u];var f=\"bilinear\"===r?1:0,d=[i-1+\".0\",s-1+\".0\"],p=d[0],v=d[1],m=l>1?[\"\"+(i-1)/(l-1),\"(y2-y1) * height_ratio\",\"y1*\"+p+\" + float(y)*(height_scale)\"]:[\"0.0\",\"0.0\",\"0.5 * (y1+y2) * \"+p],g=m[0],y=m[1],x=m[2],b=h>1?[\"\"+(s-1)/(h-1),\"(x2-x1) * width_ratio\",\"x1*\"+v+\" + float(x)*(width_scale)\"]:[\"0.0\",\"0.0\",\"0.5 * (x1+x2) * \"+v],w=b[0],C=b[1],E=b[2];this.userCode=\"\\n      const float height_ratio = float(\"+g+\");\\n      const float width_ratio = float(\"+w+\");\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int y = coords[1];\\n        int x = coords[2];\\n        int d = coords[3];\\n\\n        // get box vals\\n        float y1 = getBoxes(b,0);\\n        float x1 = getBoxes(b,1);\\n        float y2 = getBoxes(b,2);\\n        float x2 = getBoxes(b,3);\\n\\n        // get image in batch index\\n        int bInd = round(getBoxInd(b));\\n        if(bInd < 0 || bInd >= \"+a+\") {\\n          return;\\n        }\\n\\n        float height_scale = \"+y+\";\\n        float width_scale = \"+C+\";\\n\\n        float in_y = \"+x+\";\\n        if( in_y < 0.0 || in_y > \"+p+\" ) {\\n          setOutput(float(\"+o+\"));\\n          return;\\n        }\\n        float in_x = \"+E+\";\\n        if( in_x < 0.0 || in_x > \"+v+\" ) {\\n          setOutput(float(\"+o+\"));\\n          return;\\n        }\\n\\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\\n        if(\"+f+\" == 1) {\\n          // Compute the four integer indices.\\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\\n\\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\\n\\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\\n\\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\\n          float newValue = top + (bottom - top) * fracCR.y;\\n          setOutput(newValue);\\n        } else {\\n          // Compute the coordinators of nearest neighbor point.\\n          ivec2 sourceNearestCR = ivec2(floor(\\n            sourceFracIndexCR + vec2(0.5,0.5)));\\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\\n          setOutput(newValue);\\n        }\\n      }\\n    \"},ni=function(t,e,n){this.variableNames=[\"x\"],this.outputShape=t;var r=t.length,o=t[t.length-1],a=n?\"<\":\">\";this.userCode=\"\\n      int getIndex(int i) {\\n        \"+(n?\"return \"+o+\" -i - 1;\":\"return i;\")+\"\\n      }\\n\\n      void main() {\\n        \"+wa(r)+\" coords = getOutputCoords();\\n        int end = \"+ri(r,\"coords\")+\";\\n        float val = 0.0;\\n        for (int i = \"+o+\" - 1; i >= 0; i -= 1) {\\n          int idx = getIndex(i);\\n          if (idx \"+a+\" end) {\\n            continue;\\n          }\\n          if (idx == end && \"+e+\") {\\n            continue;\\n          }\\n          \"+ri(r,\"coords\")+\" = idx;\\n          val += getX(\"+function(t,e){if(1===t)return\"\"+e;if(2===t)return e+\".x, \"+e+\".y\";if(3===t)return e+\".x, \"+e+\".y, \"+e+\".z\";if(4===t)return e+\".x, \"+e+\".y, \"+e+\".z, \"+e+\".w\";throw Error(\"Cumulative sum for rank \"+t+\" is not yet supported\")}(r,\"coords\")+\");\\n        }\\n        setOutput(val);\\n      }\\n    \"};function ri(t,e){if(1===t)return\"\"+e;if(2===t)return e+\".y\";if(3===t)return e+\".z\";if(4===t)return e+\".w\";throw Error(\"Cumulative sum for rank \"+t+\" is not yet supported\")}var oi=function(t){this.variableNames=[\"A\"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Vt.DENSE;var e=Yt(t),n=ua();this.outputShape=t,this.userCode=\"\\n      ivec3 outCoordsFromFlatIndex(int index) {\\n        \"+ca([\"r\",\"c\",\"d\"],t)+\"\\n        return ivec3(r, c, d);\\n      }\\n\\n      void main() {\\n        ivec2 resTexRC = ivec2(resultUV.yx *\\n          vec2(\"+e[0]+\", \"+e[1]+\"));\\n        int index = 4 * (resTexRC.x * \"+e[1]+\" + resTexRC.y);\\n\\n        vec4 result = vec4(0.);\\n\\n        for (int i=0; i<4; i++) {\\n          int flatIndex = index + i;\\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\\n          result[i] = getA(rc.x, rc.y, rc.z);\\n        }\\n\\n        \"+n.output+\" = result;\\n      }\\n    \"},ai=function(t){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Vt.DENSE;var e=Yt(t),n=ua();this.outputShape=t,this.userCode=\"\\n      ivec3 outCoordsFromFlatIndex(int index) {\\n        \"+ca([\"r\",\"c\",\"d\"],t)+\"\\n        return ivec3(r, c, d);\\n      }\\n\\n      void main() {\\n        ivec2 resTexRC = ivec2(resultUV.yx *\\n          vec2(\"+e[0]+\", \"+e[1]+\"));\\n        int index = 4 * (resTexRC.x * \"+e[1]+\" + resTexRC.y);\\n\\n        vec4 result = vec4(0.);\\n\\n        for (int i=0; i<4; i++) {\\n          int flatIndex = index + i;\\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\\n        }\\n\\n        \"+n.output+\" = result;\\n      }\\n    \"},ii=function(){function t(t,e,n){this.variableNames=[\"x\"],this.outputShape=[],this.outputShape=t,this.blockSize=e,this.dataFormat=n,this.userCode=\"\\n    void main() {\\n      ivec4 coords = getOutputCoords();\\n      int b = coords[0];\\n      int h = \"+this.getHeightCoordString()+\";\\n      int w = \"+this.getWidthCoordString()+\";\\n      int d = \"+this.getDepthCoordString()+\";\\n\\n      int in_h = h / \"+e+\";\\n      int offset_h = imod(h, \"+e+\");\\n      int in_w = w / \"+e+\";\\n      int offset_w = imod(w, \"+e+\");\\n      int offset_d = (offset_h * \"+e+\" + offset_w) *\\n        \"+this.getOutputDepthSize()+\";\\n      int in_d = d + offset_d;\\n\\n      float result = \"+this.getInputSamplingString()+\";\\n      setOutput(result);\\n    }\\n  \"}return t.prototype.getHeightCoordString=function(){return\"NHWC\"===this.dataFormat?\"coords[1]\":\"coords[2]\"},t.prototype.getWidthCoordString=function(){return\"NHWC\"===this.dataFormat?\"coords[2]\":\"coords[3]\"},t.prototype.getDepthCoordString=function(){return\"NHWC\"===this.dataFormat?\"coords[3]\":\"coords[1]\"},t.prototype.getOutputDepthSize=function(){return\"NHWC\"===this.dataFormat?this.outputShape[3]:this.outputShape[1]},t.prototype.getInputSamplingString=function(){return\"NHWC\"===this.dataFormat?\"getX(b, in_h, in_w, in_d)\":\"getX(b, in_d, in_h, in_w)\"},t}(),si=function(t){this.variableNames=[\"X\"],this.outputShape=[t,t],this.userCode=\"\\n      void main() {\\n          ivec2 coords = getOutputCoords();\\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\\n          setOutput(val);\\n      }\\n    \"},ui=function(t){this.variableNames=[\"A\"],this.outTexUsage=zt.DOWNLOAD;var e=ua();this.outputShape=t,this.userCode=\"\\n      \"+ha+\"\\n\\n      void main() {\\n        float x = getAAtOutCoords();\\n        \"+e.output+\" = encode_float(x);\\n      }\\n    \"},ci=function(t){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=zt.DOWNLOAD;var e=ua();this.outputShape=t,this.userCode=\"\\n      \"+ha+\"\\n\\n      void main() {\\n        ivec3 coords = getOutputCoords();\\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\\n        \"+e.output+\" = encode_float(x);\\n      }\\n    \"},li=function(t,e,n){void 0===n&&(n=!1),this.variableNames=[\"A\"];var r=ua(),o=e[0],a=e[1];this.outputShape=t;var i=\"result\";n&&(i=\"floor(result * 255. + 0.5)\"),this.userCode=\"\\n      \"+la(t)+\"\\n\\n      void main() {\\n        ivec3 coords = getOutputCoords();\\n\\n        int flatIndex = getFlatIndex(coords);\\n        int offset = imod(flatIndex, 4);\\n\\n        flatIndex = idiv(flatIndex, 4, 1.);\\n        \\n        int r = flatIndex / \"+a+\";\\n        int c = imod(flatIndex, \"+a+\");\\n        vec2 uv = (vec2(c, r) + halfCR) / vec2(\"+a+\".0, \"+o+\".0);\\n        vec4 values = \"+r.texture2D+\"(A, uv);\\n\\n        float result;\\n\\n        if(offset == 0) {\\n          result = values[0];\\n        } else if(offset == 1) {\\n          result = values[1];\\n        } else if(offset == 2) {\\n          result = values[2];\\n        } else {\\n          result = values[3];\\n        }\\n\\n        \"+r.output+\" = vec4(\"+i+\", 0., 0., 0.);\\n      }\\n    \"},hi=function(t,e,n){void 0===n&&(n=!1),this.variableNames=[\"A\"],this.packedInputs=!1,this.packedOutput=!0;var r=ua(),o=e[0],a=e[1];this.outputShape=t;var i=\"\",s=\"result\";n&&(s=\"floor(result * 255. + 0.5)\");for(var u=0;u<=1;u++)for(var c=0;c<=1;c++){var l=2*u+c;i+=\"\\n          localCoords = coords;\\n          if(localCoords[2] + \"+c+\" < \"+t[2]+\") {\\n            localCoords[2] += \"+c+\";\\n            if(localCoords[1] + \"+u+\" < \"+t[1]+\") {\\n              localCoords[1] += \"+u+\";\\n\\n              flatIndex = getFlatIndex(localCoords);\\n              offset = imod(flatIndex, 4);\\n\\n              flatIndex = idiv(flatIndex, 4, 1.);\\n\\n              r = flatIndex / \"+a+\";\\n              c = imod(flatIndex, \"+a+\");\\n              uv = (vec2(c, r) + halfCR) / vec2(\"+a+\".0, \"+o+\".0);\\n              values = \"+r.texture2D+\"(A, uv);\\n\\n              if(offset == 0) {\\n                result[\"+l+\"] = values[0];\\n              } else if(offset == 1) {\\n                result[\"+l+\"] = values[1];\\n              } else if(offset == 2) {\\n                result[\"+l+\"] = values[2];\\n              } else {\\n                result[\"+l+\"] = values[3];\\n              }\\n            }\\n          }\\n        \"}this.userCode=\"\\n      \"+la(t)+\"\\n\\n      void main() {\\n        ivec3 coords = getOutputCoords();\\n\\n        vec4 result = vec4(0.);\\n        int flatIndex, r, c, offset;\\n        ivec3 localCoords;\\n        vec2 uv;\\n        vec4 values;\\n\\n        \"+i+\"\\n\\n        \"+r.output+\" = \"+s+\";\\n      }\\n    \"},fi=\"return real * expR - imag * expI;\",di=\"return real * expI + imag * expR;\",pi=function(t,e,n){this.variableNames=[\"real\",\"imag\"];var r=e[1];this.outputShape=e;var o=n?\"2.0 * \"+Math.PI:\"-2.0 * \"+Math.PI,a=n?r+\".0\":\"1.0\";this.userCode=\"\\n      const float exponentMultiplier = \"+o+\";\\n\\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\\n        \"+t+\"\\n      }\\n\\n      float mulMatDFT(int batch, int index) {\\n        float indexRatio = float(index) / float(\"+r+\");\\n        float exponentMultiplierTimesIndexRatio =\\n            exponentMultiplier * indexRatio;\\n\\n        float result = 0.0;\\n\\n        for (int i = 0; i < \"+r+\"; i++) {\\n          // x = (-2|2 * PI / N) * index * i;\\n          float x = exponentMultiplierTimesIndexRatio * float(i);\\n          float expR = cos(x);\\n          float expI = sin(x);\\n          float real = getReal(batch, i);\\n          float imag = getImag(batch, i);\\n\\n          result +=\\n              unaryOpComplex(real, expR, imag, expI) / \"+a+\";\\n        }\\n\\n        return result;\\n      }\\n\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        setOutput(mulMatDFT(coords[0], coords[1]));\\n      }\\n    \"},vi=function(){function t(t,e){this.outputShape=[],this.variableNames=[\"x\"],this.outputShape=t,this.userCode=\"\\n      uniform float value;\\n      void main() {\\n        // Input can be obtained from uniform value.\\n        setOutput(value);\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.valueLoc&&(e.valueLoc=n.getUniformLocationNoThrow(r,\"value\")),n.gl.uniform1f(e.valueLoc,t)}},t}(),mi=function(t,e,n){this.variableNames=[\"A\",\"indices\"];var r=t.slice();r[n]=e,this.outputShape=r,this.rank=r.length;var o=wa(this.rank),a=function(t,e){var n=t.length;if(n>4)throw Error(\"Gather for rank \"+n+\" is not yet supported\");if(1===n)return\"int(getIndices(resRC))\";for(var r=[\"resRC.x\",\"resRC.y\",\"resRC.z\",\"resRC.w\"],o=[],a=0;a<t.length;a++)a===e?o.push(\"int(getIndices(\"+r[a]+\"))\"):o.push(\"\"+r[a]);return o.join()}(t,n);this.userCode=\"\\n      void main() {\\n        \"+o+\" resRC = getOutputCoords();\\n        setOutput(getA(\"+a+\"));\\n      }\\n    \"};var gi=function(t,e,n){this.sliceDim=t,this.strides=e,this.variableNames=[\"x\",\"indices\"],this.outputShape=n;var r=wa(e.length),o=wa(n.length),a=this.sliceDim>1?\"strides[j]\":\"strides\";this.userCode=\"\\n        \"+r+\" strides = \"+r+\"(\"+this.strides+\");\\n         void main() {\\n          \"+o+\" coords = getOutputCoords();\\n          int flattenIndex = 0;\\n          for (int j = 0; j < \"+this.sliceDim+\"; j++) {\\n            int index = round(getIndices(coords[0], j));\\n            flattenIndex += index * \"+a+\";\\n          }\\n          setOutput(getX(flattenIndex, coords[1]));\\n        }\\n      \"};function yi(t,e){var n=ua();return oe(t,e,n.version+\"\\n    precision highp float;\\n    \"+n.attribute+\" vec3 clipSpacePos;\\n    \"+n.attribute+\" vec2 uv;\\n    \"+n.varyingVs+\" vec2 resultUV;\\n\\n    void main() {\\n      gl_Position = vec4(clipSpacePos, 1);\\n      resultUV = uv;\\n    }\")}function xi(t,e){return fe(t,e,new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]))}function bi(t,e){return de(t,e,new Uint16Array([0,1,2,2,1,3]))}function wi(t,e,n,r,o,a,i){ve(n,r);var s=pe(t,e),u=t.TEXTURE_2D;return Jt(t,e,(function(){return t.bindTexture(u,s)})),Jt(t,e,(function(){return t.texParameteri(u,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE)})),Jt(t,e,(function(){return t.texParameteri(u,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE)})),Jt(t,e,(function(){return t.texParameteri(u,t.TEXTURE_MIN_FILTER,t.NEAREST)})),Jt(t,e,(function(){return t.texParameteri(u,t.TEXTURE_MAG_FILTER,t.NEAREST)})),Jt(t,e,(function(){return t.texImage2D(u,0,o,n,r,0,a,i,null)})),Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,null)})),s}function Ci(t,e,n,r,o){var a=Xt(n,r);return wi(t,e,a[0],a[1],o.internalFormatFloat,o.textureFormatFloat,t.FLOAT)}function Ei(t,e,n,r,o){var a=Xt(n,r);return wi(t,e,a[0],a[1],o.internalFormatHalfFloat,o.textureFormatFloat,o.textureTypeHalfFloat)}function Ri(t,e,n,r,o){var a=Xt(n,r);return wi(t,e,a[0],a[1],t.RGBA,t.RGBA,t.UNSIGNED_BYTE)}function Ii(t,e,n,r,o){var a=$t(n,r);return wi(t,e,a[0],a[1],o.internalFormatPackedFloat,t.RGBA,t.FLOAT)}function ki(t,e,n,r,o){var a=$t(n,r);return wi(t,e,a[0],a[1],o.internalFormatPackedHalfFloat,t.RGBA,o.textureTypeHalfFloat)}function Si(t,e,n,r){return Jt(t,e,(function(){return t.bindBuffer(t.ARRAY_BUFFER,r)})),ge(t,e,n,\"clipSpacePos\",r,3,20,0)&&ge(t,e,n,\"uv\",r,2,20,12)}function Ai(t,e,n,r,o,a,i){var s,u,c;Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,n)})),a instanceof Uint8Array?(s=new Uint8Array(r*o*4),u=t.UNSIGNED_BYTE,c=t.RGBA):(s=new Float32Array(r*o*4),u=t.FLOAT,c=i.internalFormatPackedFloat),s.set(a),Jt(t,e,(function(){return t.texImage2D(t.TEXTURE_2D,0,c,r,o,0,t.RGBA,u,s)})),Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,null)}))}function Di(t,e,n,r){Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,n)})),r.data instanceof Uint8Array?Jt(t,e,(function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,r.width,r.height,0,t.RGBA,t.UNSIGNED_BYTE,r.data)})):Jt(t,e,(function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,r)})),Jt(t,e,(function(){return t.bindTexture(t.TEXTURE_2D,null)}))}function Ti(t,e,n,r,o){var a=t.createBuffer();Jt(t,e,(function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,a)}));var i=16*n*r;return Jt(t,e,(function(){return t.bufferData(t.PIXEL_PACK_BUFFER,i,t.STREAM_READ)})),Jt(t,e,(function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,0)})),Jt(t,e,(function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,null)})),a}function Ni(t,e,n){var r=t,o=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,e),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,o),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),o}function Fi(t,e,n,r,o){var a=Xt(n,r),i=a[0],s=a[1],u=new Uint8Array(n*r*4);return Jt(t,e,(function(){return t.readPixels(0,0,i,s,o.downloadTextureFormat,t.UNSIGNED_BYTE,u)})),new Float32Array(u.buffer)}function _i(t,e,n,r,o,a,i,s){var u=t,c=new Float32Array(function(t,e){var n=$t(t,e);return n[0]*n[1]*4}(a,i));return u.bindBuffer(u.PIXEL_PACK_BUFFER,e),u.getBufferSubData(u.PIXEL_PACK_BUFFER,0,c),u.bindBuffer(u.PIXEL_PACK_BUFFER,null),c}function Oi(t,e,n,r){var o=new Float32Array(n*r*4);return Jt(t,e,(function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,o)})),o}var Mi=Object.freeze({createVertexShader:yi,createVertexBuffer:xi,createIndexBuffer:bi,createFloat32MatrixTexture:Ci,createFloat16MatrixTexture:Ei,createUnsignedBytesMatrixTexture:Ri,createPackedMatrixTexture:Ii,createFloat16PackedMatrixTexture:ki,bindVertexProgramAttributeStreams:Si,uploadDenseMatrixToTexture:Ai,uploadPixelDataToTexture:Di,createBufferFromOutputTexture:Ti,downloadFloat32MatrixFromBuffer:Ni,downloadByteEncodedFloatMatrixFromOutputTexture:Fi,downloadPackedMatrixFromBuffer:_i,downloadMatrixFromPackedOutputTexture:Oi}),Bi=function(){function t(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];var e=i().getNumber(\"WEBGL_VERSION\");null!=t?(this.gl=t,Kt(e,t)):this.gl=jt(e);var n=\"WEBGL_color_buffer_float\";if(1===i().getNumber(\"WEBGL_VERSION\")){if(this.textureFloatExtension=re(this.gl,this.debug,\"OES_texture_float\"),Pe(this.gl,\"OES_texture_half_float\"))this.textureHalfFloatExtension=re(this.gl,this.debug,\"OES_texture_half_float\");else if(i().get(\"WEBGL_FORCE_F16_TEXTURES\"))throw new Error(\"GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.\");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Pe(this.gl,\"EXT_color_buffer_half_float\"))this.colorBufferHalfFloatExtension=re(this.gl,this.debug,\"EXT_color_buffer_half_float\");else if(i().get(\"WEBGL_FORCE_F16_TEXTURES\"))throw new Error(\"GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.\")}else if(n=\"EXT_color_buffer_float\",Pe(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else{if(!Pe(this.gl,\"EXT_color_buffer_half_float\"))throw new Error(\"GL context does not support color renderable floats\");this.colorBufferHalfFloatExtension=this.gl.getExtension(\"EXT_color_buffer_half_float\")}this.vertexBuffer=xi(this.gl,this.debug),this.indexBuffer=bi(this.gl,this.debug),this.framebuffer=me(this.gl,this.debug),this.textureConfig=Qt(this.gl,this.textureHalfFloatExtension)}return Object.defineProperty(t.prototype,\"debug\",{get:function(){return i().getBool(\"DEBUG\")},enumerable:!0,configurable:!0}),t.prototype.dispose=function(){var t=this;if(!this.disposed){null!=this.program&&console.warn(\"Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing.\"),null!=this.outputTexture&&console.warn(\"Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.\");var e=this.gl;Jt(e,this.debug,(function(){return e.finish()})),Jt(e,this.debug,(function(){return e.bindFramebuffer(e.FRAMEBUFFER,null)})),Jt(e,this.debug,(function(){return e.deleteFramebuffer(t.framebuffer)})),Jt(e,this.debug,(function(){return e.bindBuffer(e.ARRAY_BUFFER,null)})),Jt(e,this.debug,(function(){return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)})),Jt(e,this.debug,(function(){return e.deleteBuffer(t.indexBuffer)})),this.disposed=!0}},t.prototype.createFloat32MatrixTexture=function(t,e){return this.throwIfDisposed(),Ci(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createFloat16MatrixTexture=function(t,e){return this.throwIfDisposed(),Ei(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createUnsignedBytesMatrixTexture=function(t,e){return this.throwIfDisposed(),Ri(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.uploadPixelDataToTexture=function(t,e){this.throwIfDisposed(),Di(this.gl,this.debug,t,e)},t.prototype.uploadDenseMatrixToTexture=function(t,e,n,r){this.throwIfDisposed(),Ai(this.gl,this.debug,t,e,n,r,this.textureConfig)},t.prototype.createFloat16PackedMatrixTexture=function(t,e){return this.throwIfDisposed(),ki(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.createPackedMatrixTexture=function(t,e){return this.throwIfDisposed(),Ii(this.gl,this.debug,t,e,this.textureConfig)},t.prototype.deleteMatrixTexture=function(t){var e=this;this.throwIfDisposed(),this.outputTexture===t&&(Ee(this.gl,this.debug,this.framebuffer),this.outputTexture=null),Jt(this.gl,this.debug,(function(){return e.gl.deleteTexture(t)}))},t.prototype.downloadByteEncodedFloatMatrixFromOutputTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,(function(){return Fi(r.gl,r.debug,e,n,r.textureConfig)}))},t.prototype.downloadPackedMatrixFromBuffer=function(t,e,n,r,o,a){return _i(this.gl,t,0,0,0,o,a,this.textureConfig)},t.prototype.downloadFloat32MatrixFromBuffer=function(t,e){return Ni(this.gl,t,e)},t.prototype.createBufferFromTexture=function(t,e,n){this.bindTextureToFrameBuffer(t);var r=Ti(this.gl,this.debug,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r},t.prototype.createAndWaitForFence=function(){var t=this.createFence(this.gl);return this.pollFence(t)},t.prototype.createFence=function(t){var e,n,r=this;if(i().getBool(\"WEBGL_FENCE_API_ENABLED\")){var o=t,a=o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE,0);t.flush(),n=function(){var t=o.clientWaitSync(a,0,0);return t===o.ALREADY_SIGNALED||t===o.CONDITION_SATISFIED},e=a}else i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")>0?(e=this.beginQuery(),this.endQuery(),n=function(){return r.isQueryAvailable(e,i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"))}):n=function(){return!0};return{query:e,isFencePassed:n}},t.prototype.downloadMatrixFromPackedTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,(function(){return Oi(r.gl,r.debug,e,n)}))},t.prototype.createProgram=function(t){this.throwIfDisposed();var e=this.gl,n=ae(e,this.debug,t),r=yi(e,this.debug),o=ce(e,this.debug);return Jt(e,this.debug,(function(){return e.attachShader(o,r)})),Jt(e,this.debug,(function(){return e.attachShader(o,n)})),le(e,this.debug,o),this.debug&&he(e,this.debug,o),this.vertexAttrsAreBound||(this.setProgram(o),this.vertexAttrsAreBound=Si(e,this.debug,this.program,this.vertexBuffer)),o},t.prototype.deleteProgram=function(t){var e=this;this.throwIfDisposed(),t===this.program&&(this.program=null),null!=t&&Jt(this.gl,this.debug,(function(){return e.gl.deleteProgram(t)}))},t.prototype.setProgram=function(t){var e=this;this.throwIfDisposed(),this.program=t,null!=this.program&&this.debug&&he(this.gl,this.debug,this.program),Jt(this.gl,this.debug,(function(){return e.gl.useProgram(t)}))},t.prototype.getUniformLocation=function(t,e,n){return void 0===n&&(n=!0),this.throwIfDisposed(),n?xe(this.gl,this.debug,t,e):be(this.gl,t,e)},t.prototype.getAttributeLocation=function(t,e){var n=this;return this.throwIfDisposed(),Jt(this.gl,this.debug,(function(){return n.gl.getAttribLocation(t,e)}))},t.prototype.getUniformLocationNoThrow=function(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)},t.prototype.setInputMatrixTexture=function(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),we(this.gl,this.debug,this.program,t,e,n)},t.prototype.setOutputMatrixTexture=function(t,e,n){this.setOutputMatrixTextureDriver(t,n,e)},t.prototype.setOutputPackedMatrixTexture=function(t,e,n){this.throwIfDisposed();var r=$t(e,n),o=r[0],a=r[1];this.setOutputMatrixTextureDriver(t,o,a)},t.prototype.setOutputMatrixWriteRegion=function(t,e,n,r){this.setOutputMatrixWriteRegionDriver(n,t,r,e)},t.prototype.setOutputPackedMatrixWriteRegion=function(t,e,n,r){throw new Error(\"setOutputPackedMatrixWriteRegion not implemented.\")},t.prototype.debugValidate=function(){null!=this.program&&he(this.gl,this.debug,this.program),Re(this.gl)},t.prototype.executeProgram=function(){this.throwIfDisposed(),this.throwIfNoProgram();var t=this.gl;this.debug&&this.debugValidate(),Jt(t,this.debug,(function(){return t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0)}))},t.prototype.blockUntilAllProgramsCompleted=function(){var t=this;this.throwIfDisposed(),Jt(this.gl,this.debug,(function(){return t.gl.finish()}))},t.prototype.getQueryTimerExtension=function(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=re(this.gl,this.debug,2===i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")?\"EXT_disjoint_timer_query_webgl2\":\"EXT_disjoint_timer_query\")),this.disjointQueryTimerExtension},t.prototype.getQueryTimerExtensionWebGL2=function(){return this.getQueryTimerExtension()},t.prototype.getQueryTimerExtensionWebGL1=function(){return this.getQueryTimerExtension()},t.prototype.beginQuery=function(){if(2===i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")){var t=this.gl,e=this.getQueryTimerExtensionWebGL2(),n=t.createQuery();return t.beginQuery(e.TIME_ELAPSED_EXT,n),n}var r=this.getQueryTimerExtensionWebGL1(),o=r.createQueryEXT();return r.beginQueryEXT(r.TIME_ELAPSED_EXT,o),o},t.prototype.endQuery=function(){if(2!==i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")){var t=this.getQueryTimerExtensionWebGL1();t.endQueryEXT(t.TIME_ELAPSED_EXT)}else{var e=this.gl,n=this.getQueryTimerExtensionWebGL2();e.endQuery(n.TIME_ELAPSED_EXT)}},t.prototype.waitForQueryAndGetTime=function(t){return n(this,void 0,void 0,(function(){var e=this;return r(this,(function(n){switch(n.label){case 0:return[4,F((function(){return e.disposed||e.isQueryAvailable(t,i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"))}))];case 1:return n.sent(),[2,this.getQueryTime(t,i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"))]}}))}))},t.prototype.getQueryTime=function(t,e){if(0===e)return null;if(2===e){var n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}var r=this.getQueryTimerExtensionWebGL1();return r.getQueryObjectEXT(t,r.QUERY_RESULT_EXT)/1e6},t.prototype.isQueryAvailable=function(t,e){if(0===e)return!0;if(2===e){var n=this.gl,r=this.getQueryTimerExtensionWebGL2(),o=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint}o=(r=this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(t,r.QUERY_RESULT_AVAILABLE_EXT);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint},t.prototype.pollFence=function(t){var e=this;return new Promise((function(n){e.addItemToPoll((function(){return t.isFencePassed()}),(function(){return n()}))}))},t.prototype.pollItems=function(){for(var t=function(t){for(var e=0;e<t.length;++e){if(!t[e]())break}return e-1}(this.itemsToPoll.map((function(t){return t.isDoneFn}))),e=0;e<=t;++e){(0,this.itemsToPoll[e].resolveFn)()}this.itemsToPoll=this.itemsToPoll.slice(t+1)},t.prototype.addItemToPoll=function(t,e){var n=this;this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),this.itemsToPoll.length>1||F((function(){return n.pollItems(),0===n.itemsToPoll.length}))},t.prototype.bindTextureToFrameBuffer=function(t){this.throwIfDisposed(),Ce(this.gl,this.debug,t,this.framebuffer),this.debug&&Re(this.gl)},t.prototype.unbindTextureToFrameBuffer=function(){null!=this.outputTexture?(Ce(this.gl,this.debug,this.outputTexture,this.framebuffer),this.debug&&Re(this.gl)):Ee(this.gl,this.debug,this.framebuffer)},t.prototype.downloadMatrixDriver=function(t,e){this.bindTextureToFrameBuffer(t);var n=e();return this.unbindTextureToFrameBuffer(),n},t.prototype.setOutputMatrixTextureDriver=function(t,e,n){this.throwIfDisposed();var r=this.gl;Ce(r,this.debug,t,this.framebuffer),this.debug&&Re(r),this.outputTexture=t,Jt(r,this.debug,(function(){return r.viewport(0,0,e,n)})),Jt(r,this.debug,(function(){return r.scissor(0,0,e,n)}))},t.prototype.setOutputMatrixWriteRegionDriver=function(t,e,n,r){var o=this;this.throwIfDisposed(),Jt(this.gl,this.debug,(function(){return o.gl.scissor(t,e,n,r)}))},t.prototype.throwIfDisposed=function(){if(this.disposed)throw new Error(\"Attempted to use disposed GPGPUContext.\")},t.prototype.throwIfNoProgram=function(){if(null==this.program)throw new Error(\"No GPU program is currently set.\")},t}();function Pi(t,e){if(t.length!==e.length)throw Error(\"Binary was compiled with \"+t.length+\" inputs, but was executed with \"+e.length+\" inputs\");t.forEach((function(t,n){var r=t.logicalShape,o=e[n],a=o.shape;if(!S(r,a))throw Error(\"Binary was compiled with different shapes than the current args. Shapes \"+r+\" and \"+a+\" must match\");if(!t.isUniform||!o.isUniform){var i=t.texShape,s=o.isUniform?null:o.texData.texShape;if(!S(i,s))throw Error(\"Binary was compiled with different texture shapes than the current args. Shape \"+i+\" and \"+s+\" must match\")}}))}var Li=function(t,e,n){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var r=n.filterWidth,o=n.inChannels,a=n.strideWidth,i=n.strideHeight,s=n.padInfo,u=n.outWidth,c=n.dilationWidth,l=n.dilationHeight,h=n.dataFormat,f=s.left,d=s.top,p=o*r,v=ua(),m=\"channelsLast\"===h,g=m?0:1,y=m?1:2,x=\"\",b=0;b<=1;b++)for(var w=0;w<=1;w++)x+=\"\\n          blockIndex = rc.y + \"+w+\";\\n          pos = rc.x + \"+b+\";\\n\\n          if(blockIndex < \"+t[1]+\" && pos < \"+t[0]+\") {\\n            offsetY = int(blockIndex / (\"+u+\")) * \"+i+\" - \"+d+\";\\n            d0 = offsetY + \"+l+\" * (pos / \"+p+\");\\n\\n            if(d0 < \"+e[g]+\" && d0 >= 0) {\\n\\n              offsetX = int(mod(float(blockIndex), \"+u+\".) * \"+a+\". - \"+f+\".);\\n              d1 = offsetX + \"+c+\" * (int(mod(float(pos), \"+p+\".) / \"+o+\".));\\n\\n              if(d1 < \"+e[y]+\" && d1 >= 0) {\\n\\n                ch = int(mod(float(pos), \"+o+\".));\\n\\n                if (\"+m+\") {\\n                  innerDims = vec2(d1, ch);\\n                  result[\"+(2*b+w)+\"] = getChannel(\\n                    getA(d0, int(innerDims.x),\\n                    int(innerDims.y)), innerDims);\\n                } else {\\n                  innerDims = vec2(d0, d1);\\n                  result[\"+(2*b+w)+\"] = getChannel(\\n                    getA(ch, int(innerDims.x),\\n                    int(innerDims.y)), innerDims);\\n                }\\n              }\\n            }\\n          }\\n        \";this.userCode=\"\\n      void main() {\\n        ivec2 rc = getOutputCoords();\\n\\n        vec4 result = vec4(0);\\n\\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\\n        vec2 innerDims;\\n\\n        \"+x+\"\\n\\n        \"+v.output+\" = result;\\n      }\\n    \"},Wi=function(t,e,n,r,o){this.variableNames=[\"x\"],this.outputShape=[];var a,i=e,s=t[3]-1;this.outputShape=t;var u=\"float(\"+n+\") + float(\"+r+\") * sum\";a=.5===o?\"inversesqrt(\"+u+\")\":1===o?\"1.0/(\"+u+\")\":\"exp(log(\"+u+\") * float(-\"+o+\"));\",this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int r = coords[1];\\n        int c = coords[2];\\n        int d = coords[3];\\n        float x = getX(b, r, c, d);\\n        float sum = 0.0;\\n        for (int j = -\"+i+\"; j <= \"+i+\"; j++) {\\n          int idx = d + j;\\n          if (idx >= 0 && idx <=  \"+s+\") {\\n            float z = getX(b, r, c, idx);\\n            sum += z * z;\\n          }\\n        }\\n        float val = x * \"+a+\";\\n        setOutput(val);\\n      }\\n    \"},Ui=function(t,e,n,r,o){this.variableNames=[\"inputImage\",\"outputImage\",\"dy\"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=r,this.beta=o,this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int r = coords[1];\\n        int c = coords[2];\\n\\n        float result = 0.0;\\n        for (int d = 0; d < \"+this.depth+\"; ++d) {\\n          int depthBegin = int(max(0.0, float(d - \"+e+\")));\\n          int depthEnd = int(min(float(\"+this.depth+\"),\\n              float(d + \"+e+\" + 1)));\\n\\n          const int MIN_DEPTH_BEGIN = 0;\\n          const int MAX_DEPTH_END = \"+this.depth+\";\\n\\n          float norm = 0.0;\\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\\n            if (k < depthBegin){\\n              continue;\\n            }\\n            else if (k >= depthBegin && k < depthEnd) {\\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\\n            }\\n            else {\\n              break;\\n            }\\n          }\\n\\n          norm = float(\"+r+\") * norm + float(\"+n+\");\\n\\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\\n            if (k < depthBegin){\\n              continue;\\n            }\\n            else if (k >= depthBegin && k < depthEnd){\\n              float dyi = -2.0 * float(\"+r+\")\\n                * float(\"+o+\")\\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\\n                / norm;\\n              if (k == d) {\\n                dyi += pow(norm, -1.0 * \"+o+\");\\n              }\\n              if (k == coords[3]) {\\n                dyi *= getDy(b, r, c, d);\\n                result += dyi;\\n              }\\n            }\\n            else {\\n              break;\\n            }\\n          }\\n      }\\n      setOutput(result);\\n      }\\n    \"},Vi=function(t,e,n,r,o){this.variableNames=[\"x\"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;var a,i=e,s=t[3]-1;this.outputShape=t;var u=\"float(\"+n+\") + float(\"+r+\") * sum\";a=.5===o?\"inversesqrt(\"+u+\")\":1===o?\"1.0/(\"+u+\")\":\"exp(log(\"+u+\") * float(-\"+o+\"));\",this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords.x;\\n        int r = coords.y;\\n        int c = coords.z;\\n        int d = coords.w;\\n\\n        bool hasNextCol = d < \"+this.outputShape[3]+\";\\n        bool hasNextRow = c < \"+this.outputShape[2]+\";\\n\\n        vec4 sum = vec4(0.);\\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\\n\\n        vec4 xAtOutputCoords = vec4(\\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\\n          hasNextCol ?\\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\\n          hasNextRow ?\\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\\n        );\\n\\n        int firstChannel = d - \"+i+\";\\n        vec2 cache = vec2(0.);\\n        if(firstChannel >= 0){\\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\\n            if(hasNextRow){\\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\\n            }\\n        }\\n\\n        ivec2 depth = ivec2(d, d + 1);\\n        for (int j = - \"+i+\"; j <= \"+i+\"; j++) {\\n          ivec2 idx = depth + j;\\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(\"+s+\"));\\n\\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\\n\\n          if(depthInRange || depthPlusOneInRange){\\n            vec4 z = vec4(0.);\\n            vec4 xFragAtCurrentDepth;\\n            z.xz = cache.xy;\\n            if(depthPlusOneInRange && hasNextCol){\\n              xFragAtCurrentDepth = idx.y != d ?\\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\\n              if(hasNextRow){\\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\\n              }\\n            }\\n            cache.xy = z.yw;\\n            sum += z * z;\\n          }\\n        }\\n        vec4 result = xAtOutputCoords * \"+a+\";\\n        setOutput(result);\\n      }\\n    \"},zi=function(t){this.variableNames=[\"dy\",\"maxPos\"],this.outputShape=t.inShape;var e=t.strideHeight,n=t.strideWidth,r=t.dilationHeight,o=t.effectiveFilterHeight,a=t.effectiveFilterWidth,i=o-1-t.padInfo.top,s=a-1-t.padInfo.left,u=o*a-1;this.userCode=\"\\n      const ivec2 pads = ivec2(\"+i+\", \"+s+\");\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n\\n        ivec2 dyRCCorner = coords.yz - pads;\\n        int dyRCorner = dyRCCorner.x;\\n        int dyCCorner = dyRCCorner.y;\\n\\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n        for (int wR = 0; wR < \"+o+\";\\n          wR += \"+r+\") {\\n          float dyR = float(dyRCorner + wR) / \"+e+\".0;\\n\\n          if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 || fract(dyR) > 0.0) {\\n            continue;\\n          }\\n          int idyR = int(dyR);\\n\\n          for (int wC = 0; wC < \"+a+\"; wC++) {\\n            float dyC = float(dyCCorner + wC) / \"+n+\".0;\\n\\n            if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                fract(dyC) > 0.0) {\\n              continue;\\n            }\\n            int idyC = int(dyC);\\n\\n            float dyValue = getDy(b, idyR, idyC, d);\\n            int maxPosValue = \"+u+\" - int(getMaxPos(b, idyR, idyC, d));\\n\\n            // Get the current value, check it against the value from the\\n            // position matrix.\\n            int curPosValue = wR * \"+a+\" + wC;\\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\\n\\n            dotProd += dyValue * mask;\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},Gi=function(t){this.variableNames=[\"dy\",\"maxPos\"],this.outputShape=t.inShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.dilationDepth,a=t.dilationHeight,i=t.dilationWidth,s=t.effectiveFilterDepth,u=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=s-1-t.padInfo.front,h=u-1-t.padInfo.top,f=c-1-t.padInfo.left,d=s*u*c-1;this.userCode=\"\\n      const ivec3 pads = ivec3(\"+l+\", \"+h+\", \"+f+\");\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int ch = coords.u;\\n\\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\\n        int dyDCorner = dyCorner.x;\\n        int dyRCorner = dyCorner.y;\\n        int dyCCorner = dyCorner.z;\\n\\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\\n        // dx(xD, xR, xC, ch).\\n        // ? = to be determined. : = across all values in that axis.\\n        float dotProd = 0.0;\\n\\n        for (int wD = 0; wD < \"+s+\";\\n           wD += \"+o+\") {\\n          float dyD = float(dyDCorner + wD) / \"+e+\".0;\\n\\n          if (dyD < 0.0 || dyD >= \"+t.outDepth+\".0 || fract(dyD) > 0.0) {\\n            continue;\\n          }\\n          int idyD = int(dyD);\\n\\n          for (int wR = 0; wR < \"+u+\";\\n              wR += \"+a+\") {\\n            float dyR = float(dyRCorner + wR) / \"+n+\".0;\\n\\n            if (dyR < 0.0 || dyR >= \"+t.outHeight+\".0 ||\\n                fract(dyR) > 0.0) {\\n              continue;\\n            }\\n            int idyR = int(dyR);\\n\\n            for (int wC = 0; wC < \"+c+\";\\n                wC += \"+i+\") {\\n              float dyC = float(dyCCorner + wC) / \"+r+\".0;\\n\\n              if (dyC < 0.0 || dyC >= \"+t.outWidth+\".0 ||\\n                  fract(dyC) > 0.0) {\\n                continue;\\n              }\\n              int idyC = int(dyC);\\n\\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\\n              int maxPosValue = \"+d+\" -\\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\\n\\n              // Get the current value, check it against the value from the\\n              // position matrix.\\n              int curPosValue =\\n                  wD * \"+u+\" * \"+c+\" +\\n                  wR * \"+c+\" + wC;\\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\\n\\n              dotProd += dyValue * mask;\\n            }\\n          }\\n        }\\n        setOutput(dotProd);\\n      }\\n    \"},Hi=function(t,e,n,r,o,a,i){void 0===n&&(n=!1),void 0===r&&(r=!1),void 0===o&&(o=!1),void 0===a&&(a=null),void 0===i&&(i=!1),this.variableNames=[\"matrixA\",\"matrixB\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;var s=n?t[1]:t[2],u=Math.ceil(s/2),c=n?\"i * 2, rc.y\":\"rc.y, i * 2\",l=r?\"rc.z, i * 2\":\"i * 2, rc.z\",h=n?[\"a.xxyy\",\"a.zzww\"]:[\"a.xxzz\",\"a.yyww\"],f=r?[\"b.xzxz\",\"b.ywyw\"]:[\"b.xyxy\",\"b.zwzw\"],d=\"\",p=\"\";a&&(d=i?\"vec4 activation(vec4 a) {\\n          vec4 b = getPreluActivationWeightsAtOutCoords();\\n          \"+a+\"\\n        }\":\"vec4 activation(vec4 x) {\\n          \"+a+\"\\n        }\",p=\"result = activation(result);\");var v=o?\"result += getBiasAtOutCoords();\":\"\";o&&this.variableNames.push(\"bias\"),i&&this.variableNames.push(\"preluActivationWeights\"),this.userCode=\"\\n      \"+d+\"\\n\\n      const float sharedDimension = \"+u+\".0;\\n\\n      vec4 dot2x2ARowBCol(ivec3 rc) {\\n        vec4 result = vec4(0);\\n        for (int i = 0; i < \"+u+\"; i++) {\\n          vec4 a = getMatrixA(rc.x, \"+c+\");\\n          vec4 b = getMatrixB(rc.x, \"+l+\");\\n\\n          // These swizzled products need to be separately added.\\n          // See: https://github.com/tensorflow/tfjs/issues/1735\\n          result += (\"+h[0]+\" * \"+f[0]+\");\\n          result += (\"+h[1]+\" * \"+f[1]+\");\\n        }\\n        return result;\\n      }\\n\\n      void main() {\\n        ivec3 rc = getOutputCoords();\\n        vec4 result = dot2x2ARowBCol(rc);\\n\\n        \"+v+\"\\n\\n        \"+p+\"\\n\\n        setOutput(result);\\n      }\\n    \"},qi=function(){function t(t,e,n){this.variableNames=[\"probs\"],this.outputShape=[t,n],this.userCode=\"\\n      uniform float seed;\\n\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int batch = coords[0];\\n\\n        float r = random(seed);\\n        float cdf = 0.0;\\n\\n        for (int i = 0; i < \"+(e-1)+\"; i++) {\\n          cdf += getProbs(batch, i);\\n\\n          if (r < cdf) {\\n            setOutput(float(i));\\n            return;\\n          }\\n        }\\n\\n        // If no other event happened, last event happened.\\n        setOutput(float(\"+(e-1)+\"));\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.seedLoc&&(e.seedLoc=n.getUniformLocation(r,\"seed\")),n.gl.uniform1f(e.seedLoc,t)}},t}(),Ki=function(t,e,n,r){this.variableNames=[\"indices\"],this.outputShape=[t,e],this.userCode=\"\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int index = round(getIndices(coords.x));\\n        setOutput(mix(float(\"+r+\"), float(\"+n+\"),\\n                      float(index == coords.y)));\\n      }\\n    \"},ji=function(t){this.variableNames=[\"A\"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=t;var e=t.length;if(0===e)this.userCode=\"\\n        void main() {\\n          setOutput(vec4(getA(), 0., 0., 0.));\\n        }\\n      \";else{var n=sa(\"rc\",e),r=wa(e),o=function(t,e,n){if(1===t)return\"rc > \"+e[0];for(var r=\"\",o=t-2;o<t;o++)r+=n[o]+\" >= \"+e[o],o<t-1&&(r+=\"||\");return r}(e,t,n),a=function(t,e,n,r){if(1===t)return\"\";var o=r.slice(-2);return\"\\n    int r = \"+o[0]+\";\\n    int c = \"+o[1]+\";\\n    int rp1 = r + 1;\\n    int cp1 = c + 1;\\n\\n    bool cEdge = cp1 >= \"+e+\";\\n    bool rEdge = rp1 >= \"+n+\";\\n  \"}(e,t[t.length-1],t[t.length-2],n),i=function(t,e){var n=t.length,r=function(t,e){for(var n=[],r=0;r<=1;r++)for(var o=0;o<=1;o++){for(var a=(0===r?\"r\":\"rp1\")+\", \"+(0===o?\"c\":\"cp1\"),i=2;i<t;i++)a=e[e.length-1-i]+\",\"+a;n.push(a)}return n}(n,e);return 1===n?\"getA(rc),\\n            rc + 1 >= \"+t[0]+\" ? 0. : getA(rc + 1),\\n            0, 0\":\"getA(\"+r[0]+\"),\\n          cEdge ? 0. : getA(\"+r[1]+\"),\\n          rEdge ? 0. : getA(\"+r[2]+\"),\\n          rEdge || cEdge ? 0. : getA(\"+r[3]+\")\"}(t,n);this.userCode=\"\\n        void main() {\\n          \"+r+\" rc = getOutputCoords();\\n\\n          if(\"+o+\") {\\n            setOutput(vec4(0));\\n          } else {\\n            \"+a+\"\\n\\n            setOutput(vec4(\"+i+\"));\\n          }\\n        }\\n      \"}};var Xi=function(t,e,n){this.variableNames=[\"x\"],this.outputShape=e.map((function(e,n){return e[0]+t[n]+e[1]}));var r=t.length,o=wa(r),a=e.map((function(t){return t[0]})).join(\",\"),i=e.map((function(e,n){return e[0]+t[n]})).join(\",\"),s=[\"coords[0]\",\"coords[1]\",\"coords[2]\",\"coords[3]\"].slice(0,r);this.userCode=1!==r?\"\\n      \"+o+\" start = \"+o+\"(\"+a+\");\\n      \"+o+\" end = \"+o+\"(\"+i+\");\\n\\n      void main() {\\n        \"+o+\" outC = getOutputCoords();\\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\\n          setOutput(float(\"+n+\"));\\n        } else {\\n          \"+o+\" coords = outC - start;\\n          setOutput(getX(\"+s+\"));\\n        }\\n      }\\n    \":\"\\n        int start = \"+a+\";\\n        int end = \"+i+\";\\n\\n        void main() {\\n          int outC = getOutputCoords();\\n          if (outC < start || outC >= end) {\\n            setOutput(float(\"+n+\"));\\n          } else {\\n            setOutput(getX(outC - start));\\n          }\\n        }\\n      \"},Yi=function(t,e,n){this.variableNames=[\"x\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.map((function(e,n){return e[0]+t[n]+e[1]}));for(var r=t.length,o=wa(r),a=e.map((function(t){return t[0]})).join(\",\"),i=e.map((function(e,n){return e[0]+t[n]})).join(\",\"),s=sa(\"rc\",r),u=sa(\"source\",r),c=s[r-1]+\" < \"+this.outputShape[r-1],l=1===r?\"source\":\"vec2(\"+u.slice(-2).join()+\")\",h=[o+\" rc = outputLoc;\",s[r-1]+\" += 1;\\n       if(\"+c+\") {\\n      \",1===r?\"\":\"}\\n       rc = outputLoc;\\n       \"+s[r-2]+\" += 1;\\n       if(\"+s[r-2]+\" < \"+this.outputShape[r-2]+\") {\",1===r?\"\":\"  \"+s[r-1]+\" += 1;\\n         if(\"+c+\") {\"],f=1===r?\"rc < start || rc >= end\":\"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))\",d=\"\",p=0,v=1===r?2:4;p<v;p++)d+=\"\\n        \"+h[p]+\"\\n        if (\"+f+\") {\\n          result[\"+p+\"] = float(\"+n+\");\\n        } else {\\n          \"+o+\" source = rc - start;\\n          result[\"+p+\"] = getChannel(getX(\"+u.join()+\"), \"+l+\");\\n        }\\n      \";d+=1===r?\"} \":\"}}\",this.userCode=\"\\n      const \"+o+\" start = \"+o+\"(\"+a+\");\\n      const \"+o+\" end = \"+o+\"(\"+i+\");\\n\\n      void main() {\\n        \"+o+\" outputLoc = getOutputCoords();\\n        vec4 result = vec4(0.);\\n        \"+d+\"\\n        setOutput(result);\\n      }\\n    \"},$i=function(t,e,n){if(this.variableNames=[\"x\"],\"avg\"===e&&n)throw new Error(\"Cannot compute positions for average pool.\");var r=t.filterWidth,o=t.strideHeight,a=t.strideWidth,i=t.dilationHeight,s=t.dilationWidth,u=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=t.padInfo.top,h=t.padInfo.left;this.outputShape=t.outShape;var f=\"avg\"===e,d=\"0.0\";if(f||(d=\"-1.0 / 1e-20\"),n)this.userCode=\"\\n        const ivec2 strides = ivec2(\"+o+\", \"+a+\");\\n        const ivec2 pads = ivec2(\"+l+\", \"+h+\");\\n\\n        void main() {\\n          ivec4 coords = getOutputCoords();\\n          int batch = coords[0];\\n          int d = coords[3];\\n\\n          ivec2 xRCCorner = coords.yz * strides - pads;\\n          int xRCorner = xRCCorner.x;\\n          int xCCorner = xRCCorner.y;\\n\\n          // max/min x(?, ?, d) to get y(yR, yC, d).\\n          // ? = to be determined\\n          float minMaxValue = 0.0;\\n          float minMaxValueFound = 0.0;\\n          int minMaxPosition = 0;\\n          float avgValue = 0.0;\\n\\n          for (int wR = 0; wR < \"+u+\";\\n              wR += \"+i+\") {\\n            int xR = xRCorner + wR;\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int wC = 0; wC < \"+c+\";\\n                wC += \"+s+\") {\\n              int xC = xCCorner + wC;\\n\\n              if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                continue;\\n              }\\n\\n              float value = getX(batch, xR, xC, d);\\n\\n              // If a min / max value has already been found, use it. If not,\\n              // use the current value.\\n              float currMinMaxValue = mix(\\n                  value, minMaxValue, minMaxValueFound);\\n              if (value >= currMinMaxValue) {\\n                minMaxValue = value;\\n                minMaxValueFound = 1.0;\\n                minMaxPosition = wR * \"+c+\" + wC;\\n              }\\n            }\\n          }\\n          setOutput(float(minMaxPosition));\\n        }\\n      \";else{var p=e+\"(\"+e+\"(\"+e+\"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])\";\"avg\"===e&&(p=\"avgValue / count\");var v=4*Math.floor(r/4),m=r%4,g=\"\\n      if (\"+f+\") {\\n        avgValue += dot(values, ones);\\n      } else {\\n        minMaxValue = max(values, minMaxValue);\\n      }\\n    \";this.userCode=\"\\n      const ivec2 strides = ivec2(\"+o+\", \"+a+\");\\n      const ivec2 pads = ivec2(\"+l+\", \"+h+\");\\n      const float initializationValue = \"+d+\";\\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\\n\\n      float count = 0.0;\\n\\n      float getValue(int batch, int xR, int xC, int d) {\\n        if (xC < 0 || xC >= \"+t.inWidth+\") {\\n          return initializationValue;\\n        }\\n        count += 1.0;\\n        return getX(batch, xR, xC, d);\\n      }\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int d = coords[3];\\n\\n        ivec2 xRCCorner = coords.yz * strides - pads;\\n        int xRCorner = xRCCorner.x;\\n        int xCCorner = xRCCorner.y;\\n\\n        // max/min x(?, ?, d) to get y(yR, yC, d).\\n        // ? = to be determined\\n        vec4 minMaxValue = vec4(\"+d+\");\\n        float avgValue = 0.0;\\n        count = 0.0;\\n\\n        for (int wR = 0; wR < \"+u+\";\\n            wR += \"+i+\") {\\n          int xR = xRCorner + wR;\\n\\n          if (xR < 0 || xR >= \"+t.inHeight+\") {\\n            continue;\\n          }\\n\\n          for (int wC = 0; wC < \"+v+\"; wC += 4) {\\n            int xC = xCCorner + wC * \"+s+\";\\n\\n            vec4 values = vec4(\\n              getValue(batch, xR, xC, d),\\n              getValue(batch, xR, xC + \"+s+\", d),\\n              getValue(batch, xR, xC + 2 * \"+s+\", d),\\n              getValue(batch, xR, xC + 3 * \"+s+\", d)\\n            );\\n\\n            \"+g+\"\\n          }\\n\\n          int xC = xCCorner + \"+v+\";\\n          if (\"+(1===m)+\") {\\n            vec4 values = vec4(\\n              getValue(batch, xR, xC, d),\\n              initializationValue,\\n              initializationValue,\\n              initializationValue\\n            );\\n\\n            \"+g+\"\\n          } else if (\"+(2===m)+\") {\\n            vec4 values = vec4(\\n              getValue(batch, xR, xC, d),\\n              getValue(batch, xR, xC + \"+s+\", d),\\n              initializationValue,\\n              initializationValue\\n            );\\n\\n            \"+g+\"\\n          } else if (\"+(3===m)+\") {\\n            vec4 values = vec4(\\n              getValue(batch, xR, xC, d),\\n              getValue(batch, xR, xC + \"+s+\", d),\\n              getValue(batch, xR, xC + 2 * \"+s+\", d),\\n              initializationValue\\n            );\\n\\n            \"+g+\"\\n          }\\n        }\\n        setOutput(\"+p+\");\\n      }\\n    \"}},Qi=function(t,e,n){if(this.variableNames=[\"x\"],\"avg\"===e&&n)throw new Error(\"Cannot compute positions for average pool.\");var r=t.filterWidth,o=t.strideDepth,a=t.strideHeight,i=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,d=t.padInfo.front,p=t.padInfo.top,v=t.padInfo.left;this.outputShape=t.outShape;var m=\"avg\"===e,g=\"0.0\";if(m||(g=\"-1.0 / 1e-20\"),n)this.userCode=\"\\n        const ivec3 strides =\\n            ivec3(\"+o+\", \"+a+\", \"+i+\");\\n        const ivec3 pads = ivec3(\"+d+\", \"+p+\", \"+v+\");\\n\\n        void main() {\\n          ivec5 coords = getOutputCoords();\\n          int batch = coords.x;\\n          int ch = coords.u;\\n\\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\\n          int xDCorner = xCorner.x;\\n          int xRCorner = xCorner.y;\\n          int xCCorner = xCorner.z;\\n\\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\\n          // ? = to be determined\\n          float minMaxValue = 0.0;\\n          float minMaxValueFound = 0.0;\\n          int minMaxPosition = 0;\\n\\n          for (int wD = 0; wD < \"+l+\";\\n              wD += \"+s+\") {\\n            int xD = xDCorner + wD;\\n\\n            if (xD < 0 || xD >= \"+t.inDepth+\") {\\n              continue;\\n            }\\n\\n            for (int wR = 0; wR < \"+h+\";\\n                wR += \"+u+\") {\\n              int xR = xRCorner + wR;\\n\\n              if (xR < 0 || xR >= \"+t.inHeight+\") {\\n                continue;\\n              }\\n\\n              for (int wC = 0; wC < \"+f+\";\\n                  wC += \"+c+\") {\\n                int xC = xCCorner + wC;\\n\\n                if (xC < 0 || xC >= \"+t.inWidth+\") {\\n                  continue;\\n                }\\n\\n                float value = getX(batch, xD, xR, xC, ch);\\n\\n                // If a min / max value has already been found, use it. If not,\\n                // use the current value.\\n                float currMinMaxValue = mix(\\n                    value, minMaxValue, minMaxValueFound);\\n                if (value >= currMinMaxValue) {\\n                  minMaxValue = value;\\n                  minMaxValueFound = 1.0;\\n                  minMaxPosition =\\n                      wD * \"+h+\" * \"+f+\" +\\n                      wR * \"+f+\" + wC;;\\n                }\\n              }\\n            }\\n          }\\n          setOutput(float(minMaxPosition));\\n        }\\n      \";else{var y=e+\"(\"+e+\"(\"+e+\"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])\";\"avg\"===e&&(y=\"avgValue / count\");var x=4*Math.floor(r/4),b=r%4,w=\"\\n      if (\"+m+\") {\\n        avgValue += dot(values, ones);\\n      } else {\\n        minMaxValue = max(values, minMaxValue);\\n      }\\n    \";this.userCode=\"\\n      const ivec3 strides =\\n        ivec3(\"+o+\", \"+a+\", \"+i+\");\\n      const ivec3 pads = ivec3(\"+d+\", \"+p+\", \"+v+\");\\n      const float initializationValue = \"+g+\";\\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\\n\\n      float count = 0.0;\\n\\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\\n        if (xC < 0 || xC >= \"+t.inWidth+\") {\\n          return initializationValue;\\n        }\\n        count += 1.0;\\n        return getX(batch, xD, xR, xC, ch);\\n      }\\n\\n      void main() {\\n        ivec5 coords = getOutputCoords();\\n        int batch = coords.x;\\n        int ch = coords.u;\\n\\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\\n        int xDCorner = xCorner.x;\\n        int xRCorner = xCorner.y;\\n        int xCCorner = xCorner.z;\\n\\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\\n        // ? = to be determined\\n        vec4 minMaxValue = vec4(\"+g+\");\\n        float avgValue = 0.0;\\n        count = 0.0;\\n\\n        for (int wD = 0; wD < \"+l+\";\\n            wD += \"+s+\") {\\n          int xD = xDCorner + wD;\\n\\n          if (xD < 0 || xD >= \"+t.inDepth+\") {\\n            continue;\\n          }\\n\\n          for (int wR = 0; wR < \"+h+\";\\n            wR += \"+u+\") {\\n            int xR = xRCorner + wR;\\n\\n            if (xR < 0 || xR >= \"+t.inHeight+\") {\\n              continue;\\n            }\\n\\n            for (int wC = 0; wC < \"+x+\"; wC += 4) {\\n              int xC = xCCorner + wC * \"+c+\";\\n\\n              vec4 values = vec4(\\n                getValue(batch, xD, xR, xC, ch),\\n                getValue(batch, xD, xR, xC + \"+c+\", ch),\\n                getValue(batch, xD, xR, xC + 2 * \"+c+\", ch),\\n                getValue(batch, xD, xR, xC + 3 * \"+c+\", ch)\\n              );\\n\\n              \"+w+\"\\n            }\\n\\n            int xC = xCCorner + \"+x+\";\\n            if (\"+(1===b)+\") {\\n              vec4 values = vec4(\\n                getValue(batch, xD, xR, xC, ch),\\n                initializationValue,\\n                initializationValue,\\n                initializationValue\\n              );\\n\\n              \"+w+\"\\n            } else if (\"+(2===b)+\") {\\n              vec4 values = vec4(\\n                getValue(batch, xD, xR, xC, ch),\\n                getValue(batch, xD, xR, xC + \"+c+\", ch),\\n                initializationValue,\\n                initializationValue\\n              );\\n\\n              \"+w+\"\\n            } else if (\"+(3===b)+\") {\\n              vec4 values = vec4(\\n                getValue(batch, xD, xR, xC, ch),\\n                getValue(batch, xD, xR, xC + \"+c+\", ch),\\n                getValue(batch, xD, xR, xC + 2 * \"+c+\", ch),\\n                initializationValue\\n              );\\n\\n              \"+w+\"\\n            }\\n          }\\n          setOutput(\"+y+\");\\n        }\\n      }\\n    \"}},Ji=function(t,e){this.variableNames=[\"x\"];var n=t.windowSize,r=t.batchSize,o=t.inSize,a=Math.ceil(o/n);this.outputShape=[r,a];var i=\"0.0\",s=\"\";\"prod\"===e?i=\"1.0\":\"min\"===e?(i=\"1.0 / 1e-20\",s=\"min\"):\"max\"===e&&(i=\"-1.0 / 1e-20\",s=\"max\");var u=e+\"(\"+e+\"(\"+e+\"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])\";\"sum\"===e?u=\"sumValue\":\"prod\"===e?u=\"prodValue\":\"all\"===e?u=\"allValue\":\"any\"===e&&(u=\"anyValue\");var c=4*Math.floor(n/4),l=n%4,h=\"\\n      if (\"+(\"sum\"===e)+\") {\\n        sumValue += dot(values, ones);\\n      } else if (\"+(\"prod\"===e)+\") {\\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\\n        prodValue *= tmp[0] * tmp[1];\\n      } else {\\n        minMaxValue = \"+s+\"(values, minMaxValue);\\n      }\\n    \",f=\"vec4\";\"all\"===e?(i=\"1.0\",h=\"\\n        bool reducedAllValue = all(values);\\n        float floatedReducedAllValue = float(reducedAllValue);\\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\\n      \",f=\"bvec4\"):\"any\"===e&&(i=\"0.0\",h=\"\\n        bool reducedAnyValue = any(values);\\n        float floatedReducedAnyValue = float(reducedAnyValue);\\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\\n      \",f=\"bvec4\");var d=\"\";o%n>0&&(d=\"\\n        if (inIdx < 0 || inIdx >= \"+o+\") {\\n          return initializationValue;\\n        }\\n      \"),this.userCode=\"\\n      const float initializationValue = \"+i+\";\\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\\n\\n      float getValue(int batch, int inIdx) {\\n        \"+d+\"\\n        return getX(batch, inIdx);\\n      }\\n\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int outIdx = coords[1];\\n        int inOffset = outIdx * \"+n+\";\\n\\n        vec4 minMaxValue = vec4(\"+i+\");\\n        float prodValue = 1.0;\\n        float sumValue = 0.0;\\n        float allValue = 1.0;\\n        float anyValue = 0.0;\\n\\n        for (int i = 0; i < \"+c+\"; i += 4) {\\n          int inIdx = inOffset + i;\\n          \"+f+\" values = \"+f+\"(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            getValue(batch, inIdx + 2),\\n            getValue(batch, inIdx + 3)\\n          );\\n\\n          \"+h+\"\\n        }\\n\\n        int inIdx = inOffset + \"+c+\";\\n        if (\"+(1===l)+\") {\\n          \"+f+\" values = \"+f+\"(\\n            getValue(batch, inIdx),\\n            initializationValue,\\n            initializationValue,\\n            initializationValue\\n          );\\n\\n          \"+h+\"\\n        } else if (\"+(2===l)+\") {\\n          \"+f+\" values = \"+f+\"(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            initializationValue,\\n            initializationValue\\n          );\\n\\n          \"+h+\"\\n        } else if (\"+(3===l)+\") {\\n          \"+f+\" values = \"+f+\"(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            getValue(batch, inIdx + 2),\\n            initializationValue\\n          );\\n\\n          \"+h+\"\\n        }\\n        setOutput(\"+u+\");\\n      }\\n    \"},Zi=function(t,e){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var n=\"\",r=0;r<4;r++){var o=\"thisRC = rc;\";r%2==1&&(o+=\"thisRC.z += 1;\"),r>1&&(o+=\"thisRC.y += 1;\"),n+=\"\\n        \"+o+\"\\n        \"+(r>0?\"if(thisRC.y < rows && thisRC.z < cols){\":\"\")+\"\\n          int flatIndex = getFlatIndex(thisRC);\\n\\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\\n\\n          result[\"+r+\"] =\\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\\n        \"+(r>0?\"}\":\"\")+\"\\n      \"}this.userCode=\"\\n      \\n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\\n      \"+ca([\"r\",\"c\",\"d\"],e)+\"\\n      return ivec3(r, c, d);\\n    }\\n  \\n      \"+la(t)+\"\\n\\n      void main() {\\n        ivec3 rc = getOutputCoords();\\n\\n        vec4 result = vec4(0.);\\n\\n        ivec3 thisRC;\\n        int rows = \"+t[1]+\";\\n        int cols = \"+t[2]+\";\\n\\n        \"+n+\"\\n\\n        setOutput(result);\\n      }\\n    \"};var ts=function(t,e,n){this.variableNames=[\"dy\"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],a=r[2],i=t.shape,s=i[1],u=i[2],c=[n&&s>1?o-1:o,n&&u>1?a-1:a],l=[n&&s>1?s-1:s,n&&u>1?u-1:u],h=c[0]/l[0],f=c[1]/l[1],d=1/h,p=1/f,v=2*Math.ceil(d)+2,m=2*Math.ceil(p)+2;this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        int r = coords[1];\\n        int c = coords[2];\\n\\n        float accumulator = 0.0;\\n\\n        const float heightScale = float(\"+h+\");\\n        const float widthScale = float(\"+f+\");\\n\\n        const float invHeightScale = float(\"+d+\");\\n        const float invWidthScale = float(\"+p+\");\\n\\n        const int winHeight = int(\"+v+\");\\n        const int winWidth = int(\"+m+\");\\n\\n        // Compute bounds for where in dy we will look\\n        float startRLerp = floor(float(r) * invHeightScale);\\n        int startDyR = int(startRLerp - float(winHeight / 2));\\n\\n        float startCLerp = floor(float(c) * invWidthScale);\\n        int startDyC = int(startCLerp - float(winWidth / 2));\\n\\n        // Loop over dy\\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\\n          int dyR = dyROffset + startDyR;\\n\\n          // Guard against the window exceeding the bounds of dy\\n          if (dyR < 0 || dyR >= \"+s+\") {\\n            continue;\\n          }\\n\\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\\n            int dyC = dyCOffset + startDyC;\\n\\n            // Guard against the window exceeding the bounds of dy\\n            if (dyC < 0 || dyC >= \"+u+\") {\\n              continue;\\n            }\\n\\n            float dxR = float(dyR) * heightScale;\\n            int topDxRIndex = int(floor(dxR));\\n            int bottomDxRIndex = int(min(ceil(dxR), \"+(o-1)+\".0));\\n            float dxRLerp = dxR - float(topDxRIndex);\\n            float inverseDxRLerp = 1.0 - dxRLerp;\\n\\n            float dxC = float(dyC) * widthScale;\\n            int leftDxCIndex = int(floor(dxC));\\n            int rightDxCIndex = int(min(ceil(dxC), \"+(a-1)+\".0));\\n            float dxCLerp = dxC - float(leftDxCIndex);\\n            float inverseDxCLerp = 1.0 - dxCLerp;\\n\\n            if (r == topDxRIndex && c == leftDxCIndex) {\\n              // topLeft\\n              accumulator +=\\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\\n            }\\n\\n            if (r == topDxRIndex && c == rightDxCIndex) {\\n              // topRight\\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\\n            }\\n\\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\\n              // bottomLeft\\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\\n            }\\n\\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\\n              // bottomRight\\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\\n            }\\n          }\\n        }\\n        // End loop over dy\\n\\n        setOutput(accumulator);\\n      }\\n    \"},es=function(t,e,n,r){this.variableNames=[\"A\"],this.outputShape=[];var o=t[0],a=t[1],i=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode=\"\\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\\n          \"+u[0]/c[0]+\",\\n          \"+u[1]/c[1]+\");\\n      const vec2 inputShapeRC = vec2(\"+a+\".0, \"+i+\".0);\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        ivec2 yRC = coords.yz;\\n\\n        // Fractional source index.\\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\\n\\n        // Compute the four integer indices.\\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\\n        ivec2 sourceCeilRC = ivec2(\\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\\n\\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\\n\\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\\n\\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\\n        float newValue = top + (bottom - top) * fracRC.x;\\n\\n        setOutput(newValue);\\n      }\\n    \"},ns=function(t,e,n,r){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var o=t[0],a=t[1],i=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode=\"\\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\\n          \"+u[0]/c[0]+\",\\n          \"+u[1]/c[1]+\",\\n          \"+u[1]/c[1]+\");\\n      const vec3 inputShapeRC = vec3(\"+a+\".0, \"+i+\".0,\\n                                     \"+i+\".0);\\n\\n      float getAValue(int b, int r, int c, int d) {\\n        return getChannel(getA(b, r, c, d), vec2(c, d));\\n      }\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        // Calculate values for next column in yRC.z.\\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\\n\\n        // Fractional source index.\\n        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;\\n\\n        // Compute the four integer indices.\\n        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);\\n        ivec3 sourceCeilRC = ivec3(\\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\\n\\n        // Should we calculate next column and row elements in 2x2 packed cell.\\n        bool hasNextCol = d < \"+(s-1)+\";\\n        bool hasNextRow = coords.z < \"+(n-1)+\";\\n\\n        // In parallel, construct four corners for all four components in\\n        // packed 2x2 cell.\\n        vec4 topLeft = vec4(\\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\\n                     : 0.0,\\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\\n                     : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\\n\\n        vec4 bottomLeft = vec4(\\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\\n                     : 0.0,\\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\\n                     : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\\n\\n        vec4 topRight = vec4(\\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\\n                     : 0.0,\\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\\n                     : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\\n\\n        vec4 bottomRight = vec4(\\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\\n                     : 0.0,\\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\\n                     : 0.0,\\n          (hasNextRow && hasNextCol) ?\\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\\n\\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\\n\\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\\n        vec4 newValue = mix(top, bottom, fracRC.x);\\n\\n        setOutput(newValue);\\n      }\\n    \"},rs=function(t,e,n){this.variableNames=[\"dy\"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],a=r[2],i=t.shape,s=i[1],u=i[2],c=[n&&s>1?o-1:o,n&&u>1?a-1:a],l=[n&&s>1?s-1:s,n&&u>1?u-1:u],h=c[0]/l[0],f=c[1]/l[1],d=1/h,p=1/f,v=2*Math.ceil(d)+2,m=2*Math.ceil(p)+2;this.userCode=\"\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        int r = coords[1];\\n        int c = coords[2];\\n\\n        float accumulator = 0.0;\\n\\n        const float heightScale = float(\"+h+\");\\n        const float widthScale = float(\"+f+\");\\n\\n        const float invHeightScale = float(\"+d+\");\\n        const float invWidthScale = float(\"+p+\");\\n\\n        const int winHeight = int(\"+v+\");\\n        const int winWidth = int(\"+m+\");\\n\\n        // Compute bounds for where in dy we will look\\n        float startRLerp = floor(float(r) * invHeightScale);\\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\\n\\n        float startCLerp = floor(float(c) * invWidthScale);\\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\\n\\n        // Loop over dy\\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\\n          int dyR = dyROffset + startDyR;\\n\\n          // Guard against the window exceeding the bounds of dy\\n          if (dyR < 0 || dyR >= \"+s+\") {\\n            continue;\\n          }\\n\\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\\n            int dyC = dyCOffset + startDyC;\\n\\n            // Guard against the window exceeding the bounds of dy\\n            if (dyC < 0 || dyC >= \"+u+\") {\\n              continue;\\n            }\\n\\n            float sourceFracRow =\\n              float(\"+c[0]+\") *\\n                (float(dyR) / float(\"+l[0]+\"));\\n\\n            float sourceFracCol =\\n                float(\"+c[1]+\") *\\n                  (float(dyC) / float(\"+l[1]+\"));\\n\\n            int sourceNearestRow = int(min(\\n                float(int(\"+o+\") - 1),\\n                \"+n+\" ? float(round(sourceFracRow)) :\\n                                  float(floor(sourceFracRow))));\\n\\n            int sourceNearestCol = int(min(\\n                float(int(\"+a+\") - 1),\\n                \"+n+\" ? float(round(sourceFracCol)) :\\n                                  float(floor(sourceFracCol))));\\n\\n            if (r == sourceNearestRow && c == sourceNearestCol) {\\n              accumulator += getDy(b, dyR, dyC, d);\\n            }\\n          }\\n        }\\n        // End loop over dy\\n\\n        setOutput(accumulator);\\n      }\\n    \"},os=function(t,e,n,r){this.variableNames=[\"A\"],this.outputShape=[];var o=t[0],a=t[1],i=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&e>1?a-1:a,r&&n>1?i-1:i],c=[r&&e>1?e-1:e,r&&n>1?n-1:n],l=r?\"0.5\":\"0.0\";this.userCode=\"\\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\\n          \"+u[0]/c[0]+\",\\n          \"+u[1]/c[1]+\");\\n      const vec2 inputShapeRC = vec2(\"+a+\".0, \"+i+\".0);\\n\\n      void main() {\\n        ivec4 coords = getOutputCoords();\\n        int b = coords[0];\\n        int d = coords[3];\\n        ivec2 yRC = coords.yz;\\n\\n        // Fractional source index.\\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\\n\\n        // Compute the coordinators of nearest neighbor point.\\n        ivec2 sourceNearestRC = ivec2(\\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + \"+l+\")));\\n\\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\\n\\n        setOutput(newValue);\\n      }\\n    \"},as=function(t,e){this.variableNames=[\"x\"];var n=t.length;if(n>4)throw new Error(\"WebGL backend: Reverse of rank-\"+n+\" tensor is not yet supported\");if(this.outputShape=t,1!==n){var r=t.map((function(n,r){return function(n){return-1!==e.indexOf(n)&&1!==t[n]?t[n]+\" - coords[\"+n+\"] - 1\":\"coords[\"+n+\"]\"}(r)})).join(\",\"),o=wa(n);this.userCode=\"\\n      void main() {\\n        \"+o+\" coords = getOutputCoords();\\n        setOutput(getX(\"+r+\"));\\n      }\\n    \"}else this.userCode=\"\\n        void main() {\\n          int coord = getOutputCoords();\\n          setOutput(getX(\"+t[0]+\" - coord - 1));\\n        }\\n      \"},is=function(t,e){this.variableNames=[\"x\"],this.packedInputs=!0,this.packedOutput=!0;var n=t.length;if(n>4)throw new Error(\"WebGL backend: Reverse of rank-\"+n+\" tensor is not yet supported\");this.outputShape=t;var r=sa(\"rc\",n),o=r[n-1]+\" + 1 < \"+this.outputShape[n-1],a=r[n-2]+\" + 1 < \"+this.outputShape[n-2],i=wa(n);function s(n){var r=t.map((function(r,o){return function(n,r){return-1!==e.indexOf(n)&&1!==t[n]?t[n]+\" - \"+r[n]+\" - 1\":\"\"+r[n]}(o,n)}));return\"getChannel(getX(\"+r.join(\",\")+\"), vec2(\"+r.slice(-2).join(\",\")+\"))\"}this.userCode=1===n?\"\\n        void main(){\\n          int rc = getOutputCoords();\\n          vec4 result = vec4(0.);\\n          result.r = getChannel(getX(\"+t[0]+\" - rc - 1),\\n            \"+t[0]+\" - rc - 1);\\n          if(\"+o+\"){\\n              result.g = getChannel(getX(\"+t[0]+\" - (rc  + 1) - 1),\\n                \"+t[0]+\" - (rc  + 1) - 1);\\n          }\\n          setOutput(result);\\n        }\\n      \":\"\\n        void main() {\\n          \"+i+\" rc = getOutputCoords();\\n          vec4 result = vec4(0.);\\n          result.r = \"+function(t){return s(t)}(r.slice())+\";\\n          if(\"+o+\"){\\n            result.g = \"+function(t){return t[n-1]=\"(\"+t[n-1]+\" + 1)\",s(t)}(r.slice())+\";\\n          }\\n          if(\"+a+\") {\\n            result.b = \"+function(t){return t[n-2]=\"(\"+t[n-2]+\" + 1)\",s(t)}(r.slice())+\";\\n            if(\"+o+\") {\\n              result.a = \"+function(t){return t[n-1]=\"(\"+t[n-1]+\" + 1)\",t[n-2]=\"(\"+t[n-2]+\" + 1)\",s(t)}(r.slice())+\";\\n            }\\n          }\\n          setOutput(result);\\n        }\\n    \"},ss=function(t,e,n,r,o,a,i){void 0===i&&(i=!0),this.variableNames=[\"updates\",\"indices\",\"defaultValue\"],this.outputShape=a;var s=wa(o.length),u=wa(a.length),c=\"\";1===n?c=\"i\":2===n&&(c=\"i, j\");var l=\"getIndices(\"+c+\")\",h=\"\";1===r?h=\"i\":2===r&&(h=\"i, coords[1]\");var f=\"getUpdates(\"+h+\")\",d=e>1?\"strides[j]\":\"strides\";this.userCode=\"\\n        \"+s+\" strides = \"+s+\"(\"+o+\");\\n\\n        void main() {\\n          \"+u+\" coords = getOutputCoords();\\n          float sum = 0.0;\\n          bool found = false;\\n          for (int i = 0; i < \"+t+\"; i++) {\\n            int flattenedIndex = 0;\\n            for (int j = 0; j < \"+e+\"; j++) {\\n              int index = round(\"+l+\");\\n              flattenedIndex += index * \"+d+\";\\n            }\\n            if (flattenedIndex == coords[0]) {\\n              sum += \"+f+\";\\n              found = true;\\n            }\\n          }\\n          setOutput(mix(getDefaultValue(), sum, float(found)));\\n        }\\n      \"},us=function(t,e){this.variableNames=[\"x\",\"segmentIds\"];var n=t.windowSize,r=t.batchSize,o=t.inSize,a=t.numSegments,i=a*Math.ceil(o/n);this.outputShape=[r,i];var s=4*Math.floor(n/4),u=n%4,c=\"\\n        sumValue += dot(values, segFilter);\\n    \",l=\"\";o%n>0&&(l=\"\\n        if (inIdx < 0 || inIdx >= \"+o+\") {\\n          return initializationValue;\\n        }\\n      \");var h=\"\";o%n>0&&(h=\"\\n        if (inIdx < 0 || inIdx >= \"+o+\") {\\n          return -1.0;\\n        }\\n      \"),this.userCode=\"\\n      const float initializationValue = 0.0;\\n\\n      float getValue(int batch, int inIdx) {\\n        \"+l+\"\\n        return getX(batch, inIdx);\\n      }\\n\\n      float getSegmentIdAtIndex(int inIdx) {\\n        \"+h+\"\\n        return getSegmentIds(inIdx);\\n      }\\n\\n      void main() {\\n        ivec2 coords = getOutputCoords();\\n        int batch = coords[0];\\n        int outIdx = coords[1];\\n        int inOffset = int(floor(float(outIdx) / float(\\n          \"+a+\")) * float(\"+n+\"));\\n        int currentSeg = int(mod(float(outIdx), float(\"+a+\")));\\n\\n        float sumValue = 0.0;\\n\\n        for (int i = 0; i < \"+s+\"; i += 4) {\\n          int inIdx = inOffset + i;\\n          vec4 values = vec4(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            getValue(batch, inIdx + 2),\\n            getValue(batch, inIdx + 3)\\n          );\\n\\n          vec4 segFilter = vec4(\\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\\n          );\\n\\n          \"+c+\"\\n        }\\n\\n        int inIdx = inOffset + \"+s+\";\\n        if (\"+(1===u)+\") {\\n          vec4 values = vec4(\\n            getValue(batch, inIdx),\\n            initializationValue,\\n            initializationValue,\\n            initializationValue\\n          );\\n\\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\\n\\n          vec4 segFilter = vec4(\\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\\n            0,\\n            0,\\n            0\\n          );\\n\\n          \"+c+\"\\n        } else if (\"+(2===u)+\") {\\n          vec4 values = vec4(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            initializationValue,\\n            initializationValue\\n          );\\n\\n          vec4 segFilter = vec4(\\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\\n              0,\\n              0\\n          );\\n\\n          \"+c+\"\\n        } else if (\"+(3===u)+\") {\\n          vec4 values = vec4(\\n            getValue(batch, inIdx),\\n            getValue(batch, inIdx + 1),\\n            getValue(batch, inIdx + 2),\\n            initializationValue\\n          );\\n\\n          vec4 segFilter = vec4(\\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\\n            0\\n          );\\n\\n          \"+c+\"\\n        }\\n        setOutput(sumValue);\\n      }\\n    \"},cs=function(t,e,n){var r,o;if(this.variableNames=[\"c\",\"a\",\"b\"],this.outputShape=e,n>4)throw Error(\"Where for rank \"+n+\" is not yet supported\");if(1===n)o=\"resRC\",r=\"resRC\";else{for(var a=[\"resRC.x\",\"resRC.y\",\"resRC.z\",\"resRC.w\"],i=[],s=[],u=0;u<e.length;u++)s.push(\"\"+a[u]),u<t&&i.push(\"\"+a[u]);r=i.join(),o=s.join()}var c=wa(n);this.userCode=\"\\n      void main() {\\n        \"+c+\" resRC = getOutputCoords();\\n        float cVal = getC(\"+r+\");\\n        if (cVal >= 1.0) {\\n          setOutput(getA(\"+o+\"));\\n        } else {\\n          setOutput(getB(\"+o+\"));\\n        }\\n      }\\n    \"},ls=function(){function t(t){this.variableNames=[\"source\"],this.outputShape=t,this.rank=t.length;var e,n=wa(this.rank),r=\"uniform int start[\"+this.rank+\"];\",o=function(t){if(1===t)return\"sourceLoc\";if(t<=6)return hs.slice(0,t).map((function(t){return\"sourceLoc.\"+t})).join(\",\");throw Error(\"Slicing for rank \"+t+\" is not yet supported\")}(this.rank);e=\"\\n        \"+n+\" sourceLoc;\\n        \"+n+\" coords = getOutputCoords();\\n        \"+t.map((function(t,e){return\"sourceLoc.\"+hs[e]+\" = start[\"+e+\"] + coords.\"+hs[e]+\";\"})).join(\"\\n\")+\"\\n      \",this.userCode=\"\\n      \"+r+\"\\n      void main() {\\n        \"+e+\"\\n        setOutput(getSource(\"+o+\"));\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error(\"The rank (\"+this.rank+\") of the program must match the length of start (\"+t.length+\")\");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,\"start\"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t)}},t}(),hs=[\"x\",\"y\",\"z\",\"w\",\"u\",\"v\"];var fs=function(){function t(t){this.variableNames=[\"source\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length;var e=wa(this.rank),n=sa(\"coords\",this.rank),r=sa(\"sourceLoc\",this.rank),o=1===this.rank?\"sourceLoc\":\"vec2(\"+r.slice(-2).join()+\")\",a=\"getChannel(getSource(\"+r.join()+\"), \"+o+\")\",i=\"\\n      result.x = \"+a+\";\\n      if (++\"+n[this.rank-1]+\" < \"+t[this.rank-1]+\") {\\n        ++\"+r[this.rank-1]+\";\\n        result.y = \"+a+\";\\n        --\"+r[this.rank-1]+\";\\n      }\\n    \",s=1===this.rank?\"\":\"\\n      --\"+n[this.rank-1]+\";\\n      if (++\"+n[this.rank-2]+\" < \"+t[this.rank-2]+\") {\\n        ++\"+r[this.rank-2]+\";\\n        result.z = \"+a+\";\\n        if (++\"+n[this.rank-1]+\" < \"+t[this.rank-1]+\") {\\n          ++\"+r[this.rank-1]+\";\\n          result.w = \"+a+\";\\n        }\\n      }\\n    \",u=this.rank<=4?\"sourceLoc = coords +\\n            \"+e+\"(\"+t.map((function(t,e){return\"start[\"+e+\"]\"})).join()+\");\":t.map((function(t,e){return r[e]+\" = \"+n[e]+\" + start[\"+e+\"];\"})).join(\"\\n\");this.userCode=\"\\n      uniform int start[\"+this.rank+\"];\\n      void main() {\\n        \"+e+\" coords = getOutputCoords();\\n        \"+e+\" sourceLoc;\\n        \"+u+\"\\n        vec4 result = vec4(0.);\\n        \"+i+\"\\n        \"+s+\"\\n        setOutput(result);\\n      }\\n    \"}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error(\"The rank (\"+this.rank+\") of the program must match the length of start (\"+t.length+\")\");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,\"start\"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t)}},t}(),ds=function(t,e,n){this.variableNames=[\"x\"],this.outputShape=n;var r=n.length,o=wa(n.length),a=wa(n.length),i=\"\";if(1===r)i=\"coords * strides + begin\";else{var s=0;i=n.map((function(t,e){return s++,1===n.length?\"coords * strides[\"+e+\"] + begin[\"+e+\"]\":\"coords[\"+(s-1)+\"] * strides[\"+e+\"] + begin[\"+e+\"]\"})).join(\",\")}this.userCode=\"\\n      \"+o+\" begin = \"+o+\"(\"+t+\");\\n      \"+o+\" strides = \"+o+\"(\"+e+\");\\n\\n      void main() {\\n        \"+a+\" coords = getOutputCoords();\\n        setOutput(getX(\"+i+\"));\\n      }\\n    \"},ps=function(){function t(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}return t.prototype.acquireTexture=function(t,e,n){var r,o=vs(e,n),a=ms(t,o,n);if(a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]),this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this.log();var i=this.freeTextures[a].shift();return this.usedTextures[a].push(i),i}return this.numUsedTextures++,this.log(),o===Gt.PACKED_2X2_FLOAT32?r=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Gt.PACKED_2X2_FLOAT16?r=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Gt.UNPACKED_FLOAT32?r=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Gt.UNPACKED_FLOAT16?r=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Gt.PACKED_4X1_UNSIGNED_BYTE&&(r=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[a].push(r),r},t.prototype.releaseTexture=function(t,e,n,r){if(null!=this.freeTextures){var o=ms(e,vs(n,r),r);o in this.freeTextures||(this.freeTextures[o]=[]),this.freeTextures[o].push(t),this.numFreeTextures++,this.numUsedTextures--;var a=this.usedTextures[o],i=a.indexOf(t);if(i<0)throw new Error(\"Cannot release a texture that was never provided by this texture manager\");a.splice(i,1),this.log()}},t.prototype.log=function(){if(this.logEnabled){var t=this.numFreeTextures+this.numUsedTextures;console.log(\"Free/Used\",this.numFreeTextures+\" / \"+this.numUsedTextures,\"(\"+t+\")\")}},t.prototype.getNumUsedTextures=function(){return this.numUsedTextures},t.prototype.getNumFreeTextures=function(){return this.numFreeTextures},t.prototype.dispose=function(){var t=this;if(null!=this.freeTextures){for(var e in this.freeTextures)this.freeTextures[e].forEach((function(e){t.gpgpu.deleteMatrixTexture(e)}));for(var e in this.usedTextures)this.usedTextures[e].forEach((function(e){t.gpgpu.deleteMatrixTexture(e)}));this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0}},t}();function vs(t,e){if(t===zt.UPLOAD)return Gt.PACKED_2X2_FLOAT32;if(t===zt.RENDER||null==t)return function(t){return i().getBool(\"WEBGL_RENDER_FLOAT32_ENABLED\")?t?Gt.PACKED_2X2_FLOAT32:Gt.UNPACKED_FLOAT32:t?Gt.PACKED_2X2_FLOAT16:Gt.UNPACKED_FLOAT16}(e);if(t===zt.DOWNLOAD||t===zt.PIXELS)return Gt.PACKED_4X1_UNSIGNED_BYTE;throw new Error(\"Unknown logical texture type \"+t)}function ms(t,e,n){return t[0]+\"_\"+t[1]+\"_\"+e+\"_\"+n}var gs=function(t,e){this.variableNames=[\"A\"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[r]*e[r];this.outputShape=n,this.rank=n.length;var o=wa(this.rank),a=function(t){var e=t.length;if(e>5)throw Error(\"Tile for rank \"+e+\" is not yet supported\");if(1===e)return\"imod(resRC, \"+t[0]+\")\";for(var n=[\"resRC.x\",\"resRC.y\",\"resRC.z\",\"resRC.w\",\"resRC.u\"],r=[],o=0;o<t.length;o++)r.push(\"imod(\"+n[o]+\", \"+t[o]+\")\");return r.join()}(t);this.userCode=\"\\n      void main() {\\n        \"+o+\" resRC = getOutputCoords();\\n        setOutput(getA(\"+a+\"));\\n      }\\n    \"};var ys=function(t,e){this.variableNames=[\"A\"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];this.outputShape=n,this.rank=n.length;var o=wa(this.rank),a=function(t){var e=t.length;if(e>6)throw Error(\"Transpose for rank \"+e+\" is not yet supported\");for(var n=[\"resRC.x\",\"resRC.y\",\"resRC.z\",\"resRC.w\",\"resRC.u\",\"resRC.v\"],r=new Array(e),o=0;o<t.length;o++)r[t[o]]=n[o];return r.join()}(e);this.userCode=\"\\n    void main() {\\n      \"+o+\" resRC = getOutputCoords();\\n      setOutput(getA(\"+a+\"));\\n    }\\n    \"};var xs=function(t,e){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0;for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(\"Packed transpose for rank \"+this.rank+\" is not yet supported.\");var o=wa(this.rank),a=ia(\"rc\",this.rank),i=new Array(this.rank);for(r=0;r<e.length;r++)i[e[r]]=a[r];var s=\"vec2(\"+i.slice(-2).join()+\")\",u=\"++\"+a[this.rank-1]+\" < \"+n[this.rank-1],c=\"getChannel(getA(\"+i.join()+\"), \"+s+\")\";this.userCode=\"\\n    void main() {\\n      \"+o+\" rc = getOutputCoords();\\n      vec4 result = vec4(0.);\\n      result[0] = \"+c+\";\\n      if(\"+u+\") {\\n        result[1] = \"+c+\";\\n      }\\n      --\"+a[this.rank-1]+\";\\n      if(++\"+a[this.rank-2]+\" < \"+n[this.rank-2]+\") {\\n        result[2] = \"+c+\";\\n        if(\"+u+\") {\\n          result[3] = \"+c+\";\\n        }\\n      }\\n      setOutput(result);\\n    }\\n    \"},bs=1.7580993408473768,ws=1.0507009873554805,Cs=function(t,e){this.variableNames=[\"A\"],this.outputShape=t,this.userCode=\"\\n      float unaryOperation(float x) {\\n        \"+e+\"\\n      }\\n\\n      void main() {\\n        float x = getAAtOutCoords();\\n        float y = unaryOperation(x);\\n\\n        setOutput(y);\\n      }\\n    \"},Es=\"if (isnan(x)) return x;\",Rs=\"return x;\",Is=\"return abs(x);\",ks=Es+\"\\n  return (x < 0.0) ? 0.0 : x;\\n\",Ss=Es+\"\\n  return (x < 0.0) ? 0.0 : min(6.0, x);\\n\",As=\"return (x >= 0.0) ? x : (exp(x) - 1.0);\",Ds=\"\\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\\n  // see: https://arxiv.org/abs/1706.02515\\n  float scaleAlpha = \"+bs+\";\\n  float scale = \"+ws+\";\\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\\n\";var Ts=\"return -x;\",Ns=\"return ceil(x);\",Fs=\"return floor(x);\",_s=\"return exp(x);\",Os=\"return exp(x) - 1.0;\",Ms=Es+\"\\n  return sin(x);\\n\",Bs=Es+\"\\n  return cos(x);\\n\",Ps=Es+\"\\n  if (abs(x) > 1.) {\\n    return NAN;\\n  }\\n  return asin(x);\\n\",Ls=Es+\"\\n  if (abs(x) > 1.) {\\n    return NAN;\\n  }\\n  return acos(x);\\n\",Ws=Es+\"\\n  return atan(x);\\n\",Us=Es+\"return log(x + sqrt(x * x + 1.0));\",Vs=Es+\"\\n  if (x < 1.0) return NAN;\\n  return log(x + sqrt(x * x - 1.0));\",zs=Es+\"\\n  if ((x < -1.0) || (x > 1.0)) return NAN;\\n  return (log(1.0 + x) - log(1.0 - x)) / 2.0;\",Gs=\"return x;\",Hs=\"return x;\",qs=\"\\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\\n  bvec4 isNaN = isnan(x);\\n\\n  result.r = isNaN.r ? x.r : result.r;\\n  result.g = isNaN.g ? x.g : result.g;\\n  result.b = isNaN.b ? x.b : result.b;\\n  result.a = isNaN.a ? x.a : result.a;\\n\\n  return result;\\n\",Ks=\"\\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\\n  bvec4 isNaN = isnan(x);\\n\\n  result.r = isNaN.r ? x.r : result.r;\\n  result.g = isNaN.g ? x.g : result.g;\\n  result.b = isNaN.b ? x.b : result.b;\\n  result.a = isNaN.a ? x.a : result.a;\\n\\n  return result;\\n\",js=\"\\n  vec4 result;\\n\\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\\n\\n  return result;\\n\",Xs=function(t,e){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode=\"\\n      vec4 unaryOperation(vec4 x) {\\n        \"+e+\"\\n      }\\n\\n      void main() {\\n        vec4 x = getAAtOutCoords();\\n        vec4 y = unaryOperation(x);\\n\\n        setOutput(y);\\n      }\\n    \"},Ys=function(t){this.variableNames=[\"A\"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=t;var e=t.length,n=sa(\"rc\",e),r=wa(e),o=function(t,e){if(1===t)return\"rc\";for(var n=\"\",r=0;r<t;r++)n+=e[r],r<t-1&&(n+=\",\");return n}(e,n),a=n.slice(-2),i=e<=1?\"rc\":\"vec2(\"+a.join(\",\")+\")\";this.userCode=\"\\n      void main() {\\n        \"+r+\" rc = getOutputCoords();\\n        vec4 packedInput = getA(\"+o+\");\\n\\n        setOutput(getChannel(packedInput, \"+i+\"));\\n      }\\n    \"},$s={};function Qs(t,e){if(void 0===e&&(e=!1),\"linear\"===t)return e?Hs:Rs;if(\"relu\"===t)return e?qs:ks;if(\"elu\"===t)return e?js:As;if(\"relu6\"===t)return e?Ks:Ss;if(\"prelu\"===t)return e?Pa:Ma;throw new Error(\"Activation \"+t+\" has not been implemented for the WebGL backend.\")}var Js=600;var Zs=function(t){function o(e){var n,r=t.call(this)||this;if(r.pendingRead=new WeakMap,r.pendingDisposal=new WeakSet,r.dataRefCount=new WeakMap,r.numBytesInGPU=0,r.uploadWaitMs=0,r.downloadWaitMs=0,r.warnedAboutMemory=!1,r.pendingDeletes=0,r.disposed=!1,!i().getBool(\"HAS_WEBGL\"))throw new Error(\"WebGL is not supported on this device\");if(null==e){var o=jt(i().getNumber(\"WEBGL_VERSION\"));r.binaryCache=(n=i().getNumber(\"WEBGL_VERSION\"))in $s?$s[n]:($s[n]={},$s[n]),r.gpgpu=new Bi(o),r.canvas=o.canvas,r.gpgpuCreatedLocally=!0}else r.gpgpu=e,r.binaryCache={},r.gpgpuCreatedLocally=!1,r.canvas=e.gl.canvas;return r.textureManager=new ps(r.gpgpu),r.numMBBeforeWarning=null==i().global.screen?1024:i().global.screen.height*i().global.screen.width*window.devicePixelRatio*Js/1024/1024,r.texData=new xo(r,Lt),r}return e(o,t),o.prototype.numDataIds=function(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes},o.prototype.write=function(t,e,n){if(i().getBool(\"DEBUG\")&&this.checkNumericalProblems(t),\"complex64\"===n&&null!=t)throw new Error(\"Cannot write to a complex64 dtype. Please use tf.complex(real, imag).\");var r={};return this.texData.set(r,{shape:e,dtype:n,values:t,usage:zt.UPLOAD}),r},o.prototype.move=function(t,e,n,r){if(i().getBool(\"DEBUG\")&&this.checkNumericalProblems(e),\"complex64\"===r)throw new Error(\"Cannot write to a complex64 dtype. Please use tf.complex(real, imag).\");this.texData.set(t,{shape:n,dtype:r,values:e,usage:zt.UPLOAD})},o.prototype.readSync=function(t){var e=this.texData.get(t),n=e.values,r=e.dtype,o=e.complexTensors,a=e.slice,i=e.shape,s=e.isPacked;if(null!=a){var u=void 0;u=s?new Xs(i,Gs):new Cs(i,Gs);var c=this.runWebGLProgram(u,[{dataId:t,shape:i,dtype:r}],r),l=this.readSync(c.dataId);return this.disposeData(c.dataId),l}if(null!=n)return this.convertAndCacheOnCPU(t);if(\"string\"===r)return n;var h,f,d=null!=this.activeTimers;(d&&(h=et()),\"complex64\"===r)?f=Vo(o.real.dataSync(),o.imag.dataSync()):f=this.getValuesFromTexture(t);return d&&(this.downloadWaitMs+=et()-h),this.convertAndCacheOnCPU(t,f)},o.prototype.read=function(t){return n(this,void 0,void 0,(function(){var e,n,o,a,s,u,c,l,h,f,d,p,v,m,g,y,x,b,w,C,E,R;return r(this,(function(r){switch(r.label){case 0:if(this.pendingRead.has(t))return e=this.pendingRead.get(t),[2,new Promise((function(t){return e.push(t)}))];if(n=this.texData.get(t),o=n.values,a=n.shape,s=n.slice,u=n.dtype,c=n.complexTensors,l=n.isPacked,null!=s)return h=void 0,h=l?new Xs(a,Gs):new Cs(a,Gs),f=this.runWebGLProgram(h,[{dataId:t,shape:a,dtype:u}],u),d=this.read(f.dataId),this.disposeData(f.dataId),[2,d];if(null!=o)return[2,this.convertAndCacheOnCPU(t)];if(!i().getBool(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\")&&2===i().getNumber(\"WEBGL_VERSION\"))throw new Error(\"tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.\");return p=null,\"complex64\"!==u&&i().get(\"WEBGL_BUFFER_SUPPORTED\")&&(v=this.decode(t),m=this.texData.get(v.dataId),p=(R=this.gpgpu).createBufferFromTexture.apply(R,[m.texture].concat(Yt(a)))),this.pendingRead.set(t,[]),\"complex64\"===u?[3,2]:[4,this.gpgpu.createAndWaitForFence()];case 1:r.sent(),r.label=2;case 2:return\"complex64\"!==u?[3,4]:[4,Promise.all([c.real.data(),c.imag.data()])];case 3:return y=r.sent(),x=y[0],b=y[1],g=Vo(x,b),[3,5];case 4:null==p?g=this.getValuesFromTexture(t):(w=k(a),g=this.gpgpu.downloadFloat32MatrixFromBuffer(p,w)),r.label=5;case 5:return null!=v&&this.disposeData(v.dataId),C=this.convertAndCacheOnCPU(t,g),E=this.pendingRead.get(t),this.pendingRead.delete(t),E.forEach((function(t){return t(C)})),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t),this.pendingDeletes--),[2,C]}}))}))},o.prototype.checkNumericalProblems=function(t){if(null!=t)for(var e=0;e<t.length;e++){var n=t[e];if(!ee(n)){if(i().getBool(\"WEBGL_RENDER_FLOAT32_CAPABLE\"))throw Error(\"The value \"+n+\" cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'\");throw Error(\"The value \"+n+\" cannot be represented on this device.\")}}},o.prototype.getValuesFromTexture=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,a=n.isPacked,s=k(r);if(i().getBool(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\")){var u=this.decode(t),c=this.texData.get(u.dataId),l=(e=this.gpgpu).downloadMatrixFromPackedTexture.apply(e,[c.texture].concat(Yt(r))).subarray(0,s);return this.disposeData(u.dataId),l}var h=i().getBool(\"WEBGL_PACK\")&&!0===a,f=h?Te(r):r,d=h?new ci(f):new ui(f),p=this.runWebGLProgram(d,[{shape:f,dtype:o,dataId:t}],\"float32\"),v=this.texData.get(p.dataId),m=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(v.texture,v.texShape[0],v.texShape[1]).subarray(0,s);return this.disposeData(p.dataId),m},o.prototype.time=function(t){return n(this,void 0,void 0,(function(){var e,n,o,a,s,u,c;return r(this,(function(r){switch(r.label){case 0:return e=this.activeTimers,n=[],o=!1,null==this.programTimersStack?(this.programTimersStack=n,o=!0):this.activeTimers.push(n),this.activeTimers=n,t(),a=I(this.activeTimers.map((function(t){return t.query}))).filter((function(t){return null!=t})),s=I(this.activeTimers.map((function(t){return t.name}))).filter((function(t){return null!=t})),this.activeTimers=e,o&&(this.programTimersStack=null),u={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\")>0?[4,Promise.all(a)]:[3,2];case 1:return c=r.sent(),u.kernelMs=w(c),u.getExtraProfileInfo=function(){return c.map((function(t,e){return{name:s[e],ms:t}})).map((function(t){return t.name+\": \"+t.ms})).join(\", \")},[3,3];case 2:u.kernelMs={error:\"WebGL query timers are not supported in this environment.\"},r.label=3;case 3:return this.uploadWaitMs=0,this.downloadWaitMs=0,[2,u]}}))}))},o.prototype.memory=function(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU}},o.prototype.startTimer=function(){return i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\")>0?this.gpgpu.beginQuery():{startMs:et(),endMs:null}},o.prototype.endTimer=function(t){return i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\")>0?(this.gpgpu.endQuery(),t):(t.endMs=et(),t)},o.prototype.getQueryTime=function(t){return n(this,void 0,void 0,(function(){var e;return r(this,(function(n){return i().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\")>0?[2,this.gpgpu.waitForQueryAndGetTime(t)]:[2,(e=t).endMs-e.startMs]}))}))},o.prototype.disposeData=function(t){if(!this.pendingDisposal.has(t)){if(this.pendingRead.has(t))return this.pendingDisposal.add(t),void this.pendingDeletes++;if(this.texData.has(t)){this.releaseGPUData(t);var e=this.texData.get(t).complexTensors;null!=e&&(e.real.dispose(),e.imag.dispose()),this.texData.delete(t)}}},o.prototype.releaseGPUData=function(t){var e=this.texData.get(t),n=e.texture,r=e.dtype,o=e.texShape,a=e.usage,i=e.isPacked,s=e.slice,u=s&&s.origDataId||t,c=this.dataRefCount.get(u);c>1?this.dataRefCount.set(u,c-1):(this.dataRefCount.delete(u),null!=n&&(this.numBytesInGPU-=this.computeBytes(o,r),this.textureManager.releaseTexture(n,o,a,i)));var l=this.texData.get(t);l.texture=null,l.texShape=null,l.isPacked=!1,l.slice=null},o.prototype.getTexture=function(t){return this.uploadToGPU(t),this.texData.get(t).texture},o.prototype.getDataInfo=function(t){return this.texData.get(t)},o.prototype.getCPUBackend=function(){return i().getBool(\"WEBGL_CPU_FORWARD\")?(null==this.cpuBackend&&(this.cpuBackend=Lt.findBackend(\"cpu\")),this.cpuBackend):null},o.prototype.shouldExecuteOnCPU=function(t,e){var n=this;return void 0===e&&(e=128),null!=this.getCPUBackend()&&t.every((function(t){return null==n.texData.get(t.dataId).texture&&t.size<e}))},o.prototype.getGPGPUContext=function(){return this.gpgpu},o.prototype.complex=function(t,e){var n=this.makeOutput(t.shape,\"complex64\");return this.texData.get(n.dataId).complexTensors={real:Lt.keep(t.clone()),imag:Lt.keep(e.clone())},n},o.prototype.real=function(t){return this.texData.get(t.dataId).complexTensors.real.clone()},o.prototype.imag=function(t){return this.texData.get(t.dataId).complexTensors.imag.clone()},o.prototype.slice=function(t,e,n){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.slice(t,e,n);if(0===k(n))return Fn([],n,t.dtype);var r=this.texData.get(t.dataId).isPacked,o=io(t.shape,e,n);if(r||!o){var a=i().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")?new fs(n):new ls(n),s=a.getCustomSetupFunc(e);return this.compileAndRun(a,[t],null,s)}return this.uploadToGPU(t.dataId),this.shallowSlice(t,e,n)},o.prototype.shallowSlice=function(t,e,n){var r=this.texData.get(t.dataId),o=this.makeOutput(n,t.dtype),a=this.texData.get(o.dataId);Object.assign(a,r),a.shape=n,a.dtype=t.dtype;var i=so(e,t.strides);r.slice&&(i+=r.slice.flatOffset),a.slice={flatOffset:i,origDataId:r.slice&&r.slice.origDataId||t.dataId};var s=this.dataRefCount.get(a.slice.origDataId)||1;return this.dataRefCount.set(a.slice.origDataId,s+1),o},o.prototype.stridedSlice=function(t,e,n,r){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.stridedSlice(t,e,n,r);var o=ro(e,n,r);if(o.some((function(t){return 0===t})))return Fn([],o);var a=new ds(e,r,o);return this.compileAndRun(a,[t])},o.prototype.reverse=function(t,e){var n=i().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")?new is(t.shape,e):new as(t.shape,e);return this.compileAndRun(n,[t])},o.prototype.concat=function(t,e){if(\"complex64\"===t[0].dtype){var n=t.map((function(t){return Tn(t)})),r=t.map((function(t){return Nn(t)}));return Dn(this.concat(n,e),this.concat(r,e))}if(this.shouldExecuteOnCPU(t))return this.cpuBackend.concat(t,e);if(1===t.length)return t[0];if(t.length>i().getNumber(\"WEBGL_MAX_TEXTURES_IN_SHADER\")){var o=Math.floor(t.length/2),a=this.concat(t.slice(0,o),e),s=this.concat(t.slice(o),e);return this.concat([a,s],e)}if(i().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")&&t[0].rank>1){var u=new Ga(t.map((function(t){return t.shape})),e);return this.compileAndRun(u,t)}var c=Sn(t.map((function(t){return t.shape})),e),l=t.map((function(t){return t.as2D(-1,k(t.shape.slice(e)))})),h=new za(l.map((function(t){return t.shape})));return this.compileAndRun(h,l).reshape(c)},o.prototype.neg=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.neg(t);if(i().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,Ts,t.dtype);var e=new Cs(t.shape,Ts);return this.compileAndRun(e,[t])},o.prototype.batchMatMul=function(t,e,n,r){var o=n?t.shape[2]:t.shape[1],a=r?e.shape[1]:e.shape[2],i=n?t.shape[1]:t.shape[2],s=t.shape[0];if((1===o||1===a)&&i>1e3){n&&(t=t.transpose([0,2,1])),r&&(e=e.transpose([0,2,1]));var u=1===a?t:t.as3D(s,i,1),c=1===a?2:1,l=1===a?e.as3D(s,1,i):e;return this.multiply(u,l).sum(c,!0)}var h=Dt(t.dtype,e.dtype),f=new Hi(t.shape,[s,o,a],n,r);return this.compileAndRun(f,[t,e],h)},o.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,a=t.bias,i=t.activation,s=t.preluActivationWeights,u=r?e.shape[2]:e.shape[1],c=o?n.shape[1]:n.shape[2],l=e.shape[0],h=Dt(e.dtype,n.dtype),f=null!=a,d=null!=s,p=i?Qs(i,!0):null,v=new Hi(e.shape,[l,u,c],r,o,f,p,d),m=[e,n];return a&&m.push(a),s&&m.push(s),this.compileAndRun(v,m,h)},o.prototype.multiply=function(t,e){if(\"complex64\"===t.dtype){var n=this.texData.get(t.dataId),r=this.texData.get(e.dataId),o=new Na(Da,t.shape,e.shape),a=new Na(Ta,t.shape,e.shape),s=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag),this.makeComplexComponentTensorInfo(e,r.complexTensors.real),this.makeComplexComponentTensorInfo(e,r.complexTensors.imag)],u=this.compileAndRun(o,s),c=this.compileAndRun(a,s),l=this.complex(u,c);return u.dispose(),c.dispose(),l}if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.multiply(t,e);if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,Oa,t.dtype);var h=new Ba(Oa,t.shape,e.shape);return this.compileAndRun(h,[t,e],t.dtype)},o.prototype.batchNormalization=function(t,e,n,r,o,a){var s=[t,e,n],u=null;null!=a&&(u=a.shape,s.push(a));var c=null;if(null!=o&&(c=o.shape,s.push(o)),i().getBool(\"WEBGL_PACK_NORMALIZATION\")){var l=new Aa(t.shape,e.shape,n.shape,u,c,r);return this.compileAndRun(l,s)}var h=new Sa(t.shape,e.shape,n.shape,u,c,r);return this.compileAndRun(h,s)},o.prototype.localResponseNormalization4D=function(t,e,n,r,o){var a=i().getBool(\"WEBGL_PACK_NORMALIZATION\")?new Vi(t.shape,e,n,r,o):new Wi(t.shape,e,n,r,o);return this.compileAndRun(a,[t])},o.prototype.LRNGrad=function(t,e,n,r,o,a,i){var s=new Ui(e.shape,r,o,a,i);return this.compileAndRun(s,[e,n,t])},o.prototype.tile=function(t,e){if(\"string\"===t.dtype){var n=this.readSync(t.dataId).map((function(t){return ot(t)}));return ta(dr(t.shape,t.dtype,n),e)}var r=new gs(t.shape,e);return this.compileAndRun(r,[t])},o.prototype.pad=function(t,e,n){var r=i().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")?new Yi(t.shape,e,n):new Xi(t.shape,e,n);return this.compileAndRun(r,[t])},o.prototype.transpose=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.transpose(t,e);var n=i().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\")?new xs(t.shape,e):new ys(t.shape,e);return this.compileAndRun(n,[t])},o.prototype.gather=function(t,e,n){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.gather(t,e,n);var r=new mi(t.shape,e.size,n);return this.compileAndRun(r,[t,e])},o.prototype.batchToSpaceND=function(t,e,n){C(t.rank<=4,(function(){return\"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet\"}));var r=e.reduce((function(t,e){return t*e})),o=zr(t.shape,e,r),a=Gr(o.length,e.length),i=Hr(t.shape,e,r),s=qr(n,e.length),u=Kr(i,n,e.length);return t.reshape(o).transpose(a).reshape(i).slice(s,u)},o.prototype.spaceToBatchND=function(t,e,n){C(t.rank<=4,(function(){return\"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet\"}));var r=e.reduce((function(t,e){return t*e})),o=[[0,0]];o.push.apply(o,n);for(var a=1+e.length;a<t.shape.length;++a)o.push([0,0]);var i=t.pad(o),s=zr(i.shape,e,r,!1),u=Gr(s.length,e.length,!1),c=Hr(i.shape,e,r,!1);return i.reshape(s).transpose(u).reshape(c)},o.prototype.reduce=function(t,e,n){var r=t.shape[0],o=t.shape[1],a=$r(o),i=new Ji({windowSize:a,inSize:o,batchSize:r},e),s=this.compileAndRun(i,[t],n);return 1===s.shape[1]?s:this.reduce(s,e,n)},o.prototype.argReduce=function(t,e,n){void 0===n&&(n=null);var r=t.shape[0],o=t.shape[1];null!=n&&(r=n.shape[0],o=n.shape[1]);var a=$r(o),i=new aa({windowSize:a,inSize:o,batchSize:r},e,null==n),s=[t];null!=n&&s.push(n);var u=this.compileAndRun(i,s,\"int32\");return 1===u.shape[1]?u:this.argReduce(t,e,u)},o.prototype.argReducePacked=function(t,e,n){void 0===n&&(n=null);var r=null!=n?n.shape:t.shape,o=$r(r[r.length-1]),a=new Ra(r,o,e,null==n),i=null==n?[t]:[t,n],s=this.compileAndRun(a,i,\"int32\");return s.rank===t.rank?this.argReducePacked(t,e,s):s},o.prototype.sum=function(t,e){Cn(\"sum\",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o),i=Tt(t.dtype);return this.reduce(a,\"sum\",i).reshape(r)},o.prototype.prod=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.prod(t,e);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o),i=Tt(t.dtype);return this.reduce(a,\"prod\",i).reshape(r)},o.prototype.unsortedSegmentSum=function(t,e,n){var r=0,o=En([r],t.rank),a=t;null!=o&&(a=t.transpose(o),r=In(1,t.rank)[0]);var i=function(t,e,n){for(var r=[],o=t.length,a=0;a<o;a++)a!==e?r.push(t[a]):r.push(n);return r}(a.shape,r,n),s=k([a.shape[r]]),u=a.as2D(-1,s),c=Tt(t.dtype),l=this.segOpCompute(u,\"unsortedSegmentSum\",e,c,n).reshape(i);return null!=o&&(l=l.transpose(Rn(o))),l},o.prototype.segOpCompute=function(t,e,n,r,o){var a=t.shape[0],i=t.shape[1],s=function(t,e){var n,r=!1;for(t<=Yr?(n=t,r=!0):n=Y(t,Math.floor(Math.sqrt(t)));!r;)n>e||n===t?r=!0:n=Y(t,n+1);return n}(i,o),u=new us({windowSize:s,inSize:i,batchSize:a,numSegments:o},e),c=this.compileAndRun(u,[t,n],r);return c.shape[1]===o?c:(n=Kn(0,o).tile([i/s]),this.segOpCompute(c,e,n,r,o))},o.prototype.argMinMaxReduce=function(t,e,n){var r=[e];if(Cn(\"arg\"+n.charAt(0).toUpperCase()+n.slice(1),r,t.rank),!i().getBool(\"WEBGL_PACK_REDUCE\")||t.rank<=2){var o=bn(t.shape,r),a=o[0],s=k(o[1]),u=t.as2D(-1,s);return this.argReduce(u,n).reshape(a)}return this.argReducePacked(t,n)},o.prototype.argMin=function(t,e){return this.argMinMaxReduce(t,e,\"min\")},o.prototype.argMax=function(t,e){return this.argMinMaxReduce(t,e,\"max\")},o.prototype.cumsum=function(t,e,n,r){if(e!==t.rank-1)throw new Error(\"WebGL cumsum shader expects an inner-most axis=\"+(t.rank-1)+\" but got axis=\"+e);var o=new ni(t.shape,n,r);return this.compileAndRun(o,[t])},o.prototype.equal=function(t,e){if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(equal(a, b));\\n\",\"bool\");var n=new Ba(\"return float(a == b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.notEqual=function(t,e){if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(notEqual(a, b));\\n\",\"bool\");var n=new Ba(\"return float(a != b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.less=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.less(t,e);if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(lessThan(a, b));\\n\",\"bool\");var n=new Ba(\"return float(a < b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.lessEqual=function(t,e){if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(lessThanEqual(a, b));\\n\",\"bool\");var n=new Ba(\"return float(a <= b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.greater=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.greater(t,e);if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(greaterThan(a, b));\\n\",\"bool\");var n=new Ba(\"return float(a > b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.greaterEqual=function(t,e){if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(greaterThanEqual(a, b));\\n\",\"bool\");var n=new Ba(\"return float(a >= b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.logicalNot=function(t){var e=new Cs(t.shape,\"return float(!(x >= 1.0));\");return this.compileAndRun(e,[t])},o.prototype.logicalAnd=function(t,e){if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return vec4(\\n    vec4(greaterThanEqual(a, vec4(1.0))) *\\n    vec4(greaterThanEqual(b, vec4(1.0))));\\n\",\"bool\");var n=new Ba(\"return float(a >= 1.0 && b >= 1.0);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.logicalOr=function(t,e){if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  return min(\\n    vec4(greaterThanEqual(a, vec4(1.0))) +\\n    vec4(greaterThanEqual(b, vec4(1.0))),\\n    vec4(1.0));\\n\",\"bool\");var n=new Ba(\"return float(a >= 1.0 || b >= 1.0);\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"bool\")},o.prototype.select=function(t,e,n){var r=new cs(t.rank,e.shape,e.rank);return this.compileAndRun(r,[t,e,n],Dt(e.dtype,n.dtype))},o.prototype.where=function(t){dn(\"tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead\");var e=t.dataSync();return na(t.shape,e)},o.prototype.topk=function(t,e,n){return ea(t.dataSync(),t.shape,t.dtype,e)},o.prototype.min=function(t,e){Cn(\"min\",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o);return this.reduce(a,\"min\",a.dtype).reshape(r)},o.prototype.minimum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.minimum(t,e);var n=i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new La(\"\\n  vec4 result = vec4(min(a, b));\\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new Ba(\"\\n  if (isnan(a)) return a;\\n  if (isnan(b)) return b;\\n\\n  return min(a, b);\\n\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.mod=function(t,e){var n=i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new La(\"\\n  vec4 result = mod(a, b);\\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new Ba(\"if (b == 0.0) return NAN;\\n  return mod(a, b);\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.max=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.max(t,e);Cn(\"max\",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o);return this.reduce(a,\"max\",a.dtype).reshape(r)},o.prototype.maximum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.maximum(t,e);var n=i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new La(\"\\n  vec4 result = vec4(max(a, b));\\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new Ba(\"\\n  if (isnan(a)) return a;\\n  if (isnan(b)) return b;\\n\\n  return max(a, b);\\n\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.all=function(t,e){Cn(\"all\",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o);return this.reduce(a,\"all\",a.dtype).reshape(r)},o.prototype.any=function(t,e){Cn(\"any\",e,t.rank);var n=bn(t.shape,e),r=n[0],o=k(n[1]),a=t.as2D(-1,o);return this.reduce(a,\"any\",a.dtype).reshape(r)},o.prototype.realDivide=function(t,e){if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")){return this.packedBinaryOp(t,e,\"\\n  // vec4 one = vec4(equal(a, b));\\n  // return one + (vec4(1.0) - one) * a / b;\\n  vec4 result = a / b;\\n  if(a.x == b.x) {\\n    result.x = 1.;\\n  }\\n  if(a.y == b.y) {\\n    result.y = 1.;\\n  }\\n  if(a.z == b.z) {\\n    result.z = 1.;\\n  }\\n  if(a.w == b.w) {\\n    result.w = 1.;\\n  }\\n\\n  return result;\\n\",\"float32\",!0)}var n=new Ba(\"\\nif (a == b) {\\n  return 1.0;\\n};\\nreturn a / b;\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"float32\")},o.prototype.floorDiv=function(t,e){if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,\"\\n  ivec4 ia = round(a);\\n  ivec4 ib = round(b);\\n  bvec4 cond = notEqual(ib, ivec4(0));\\n  ivec4 result = ivec4(0);\\n  vec4 s = sign(a) * sign(b);\\n\\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\\n  if (cond[0]) {\\n    result[0] = idiv(ia[0], ib[0], s[0]);\\n  }\\n  if (cond[1]) {\\n    result[1] = idiv(ia[1], ib[1], s[1]);\\n  }\\n  if (cond[2]) {\\n    result[2] = idiv(ia[2], ib[2], s[2]);\\n  }\\n  if (cond[3]) {\\n    result[3] = idiv(ia[3], ib[3], s[3]);\\n  }\\n  return vec4(result);\\n\",\"int32\");var n=new Ba(\"\\n  float s = sign(a) * sign(b);\\n  int ia = round(a);\\n  int ib = round(b);\\n  if (ib != 0) {\\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\\n    return float(idiv(ia, ib, s));\\n  } else {\\n    return NAN;\\n  }\\n\",t.shape,e.shape);return this.compileAndRun(n,[t,e],\"int32\")},o.prototype.add=function(t,e){if(\"complex64\"===t.dtype&&\"complex64\"===e.dtype)return this.complexSeparableBinaryOp(t,e,Fa);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.add(t,e);var n=Dt(t.dtype,e.dtype);if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,Fa,n);var r=new Ba(Fa,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},o.prototype.packedUnaryOp=function(t,e,n){var r=new Xs(t.shape,e);return this.compileAndRun(r,[t],n)},o.prototype.packedBinaryOp=function(t,e,n,r,o){void 0===o&&(o=!1);var a=new La(n,t.shape,e.shape,o);return this.compileAndRun(a,[t,e],r)},o.prototype.complexSeparableBinaryOp=function(t,e,n){var r=this,o=this.texData.get(t.dataId),a=this.texData.get(e.dataId),i=[[o.complexTensors.real,a.complexTensors.real],[o.complexTensors.imag,a.complexTensors.imag]].map((function(o){var a=o[0],i=o[1],s=r.makeComplexComponentTensorInfo(t,a),u=r.makeComplexComponentTensorInfo(e,i),c=new Ba(n,t.shape,e.shape);return r.compileAndRun(c,[s,u],Dt(a.dtype,i.dtype))})),s=i[0],u=i[1],c=this.complex(s,u);return s.dispose(),u.dispose(),c},o.prototype.makeComplexComponentTensorInfo=function(t,e){return{dataId:e.dataId,dtype:e.dtype,shape:t.shape}},o.prototype.addN=function(t){if(1===t.length)return t[0];if(t.length>i().get(\"WEBGL_MAX_TEXTURES_IN_SHADER\")){var e=Math.floor(t.length/2),n=this.addN(t.slice(0,e)),r=this.addN(t.slice(e));return this.addN([n,r])}var o=t.map((function(t){return t.dtype})).reduce((function(t,e){return Dt(t,e)})),a=t.map((function(t){return t.shape})),s=i().getBool(\"WEBGL_PACK\")?new oa(t[0].shape,a):new ra(t[0].shape,a);return this.compileAndRun(s,t,o)},o.prototype.subtract=function(t,e){if(\"complex64\"===t.dtype&&\"complex64\"===e.dtype)return this.complexSeparableBinaryOp(t,e,_a);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.subtract(t,e);var n=Dt(t.dtype,e.dtype);if(i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\"))return this.packedBinaryOp(t,e,_a,t.dtype);var r=new Ba(_a,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},o.prototype.pow=function(t,e){var n=i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new La(\"\\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\\n  vec4 result = multiplier * pow(abs(a), b);\\n\\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\\n  bvec4 isExpZero = equal(b, vec4(0.0));\\n  result.r = isExpZero.r ? 1.0 : result.r;\\n  result.g = isExpZero.g ? 1.0 : result.g;\\n  result.b = isExpZero.b ? 1.0 : result.b;\\n  result.a = isExpZero.a ? 1.0 : result.a;\\n\\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new Ba(\"\\nif(a < 0.0 && floor(b) < b){\\n  return NAN;\\n}\\nif (b == 0.0) {\\n  return 1.0;\\n}\\nreturn (round(mod(b, 2.0)) != 1) ?\\n    pow(abs(a), b) : sign(a) * pow(abs(a), b);\\n\",t.shape,e.shape),r=Dt(t.dtype,e.dtype);return this.compileAndRun(n,[t,e],r)},o.prototype.ceil=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.ceil(t);if(i().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,Ns,t.dtype);var e=new Cs(t.shape,Ns);return this.compileAndRun(e,[t])},o.prototype.floor=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.floor(t);if(i().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,Fs,t.dtype);var e=new Cs(t.shape,Fs);return this.compileAndRun(e,[t])},o.prototype.sign=function(t){var e=new Cs(t.shape,\"\\n  if (isnan(x)) { return 0.0; }\\n  return sign(x);\\n\");return this.compileAndRun(e,[t])},o.prototype.isNaN=function(t){var e=new Cs(t.shape,\"return float(isnan(x));\");return this.compileAndRun(e,[t],\"bool\")},o.prototype.isInf=function(t){var e=new Cs(t.shape,\"return float(isinf(x));\");return this.compileAndRun(e,[t],\"bool\")},o.prototype.isFinite=function(t){var e=new Cs(t.shape,\"return float(!isnan(x) && !isinf(x));\");return this.compileAndRun(e,[t],\"bool\")},o.prototype.round=function(t){var e=new Cs(t.shape,\"\\n  // OpenGL ES does not support round function.\\n  // The algorithm is based on banker's rounding.\\n  float base = floor(x);\\n  if ((x - base) < 0.5) {\\n    return floor(x);\\n  } else if ((x - base) > 0.5) {\\n    return ceil(x);\\n  } else {\\n    if (mod(base, 2.0) == 0.0) {\\n      return base;\\n    } else {\\n      return base + 1.0;\\n    }\\n  }\\n\");return this.compileAndRun(e,[t])},o.prototype.exp=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.exp(t);if(i().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,_s,t.dtype);var e=new Cs(t.shape,_s);return this.compileAndRun(e,[t])},o.prototype.expm1=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.expm1(t);if(i().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,Os,t.dtype);var e=new Cs(t.shape,Os);return this.compileAndRun(e,[t])},o.prototype.softmax=function(t,e){var n=O([e],t.shape),r=this.max(t,n),o=wn(r.shape,n),a=this.subtract(t,r.reshape(o)),i=this.exp(a),s=this.sum(i,n).reshape(o);return this.realDivide(i,s)},o.prototype.log=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.log(t);if(i().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,\"\\n  vec4 result = log(x);\\n  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));\\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\\n\\n  return result;\\n\",t.dtype);var e=new Cs(t.shape,\"if (x < 0.0) return NAN;\\n  return log(x);\");return this.compileAndRun(e,[t])},o.prototype.log1p=function(t){var e=new Cs(t.shape,\"return log(1.0 + x);\");return this.compileAndRun(e,[t])},o.prototype.sqrt=function(t){var e=new Cs(t.shape,\"return sqrt(x);\");return this.compileAndRun(e,[t])},o.prototype.rsqrt=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.rsqrt(t);var e=new Cs(t.shape,\"return inversesqrt(x);\");return this.compileAndRun(e,[t])},o.prototype.reciprocal=function(t){var e=new Cs(t.shape,\"return 1.0 / x;\");return this.compileAndRun(e,[t])},o.prototype.relu=function(t){var e;return e=i().getBool(\"WEBGL_PACK\")?new Xs(t.shape,qs):new Cs(t.shape,ks),this.compileAndRun(e,[t])},o.prototype.relu6=function(t){var e;return e=i().getBool(\"WEBGL_PACK\")?new Xs(t.shape,Ks):new Cs(t.shape,Ss),this.compileAndRun(e,[t])},o.prototype.prelu=function(t,e){var n=i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new La(Pa,t.shape,e.shape):new Ba(Ma,t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.elu=function(t){if(i().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,js,t.dtype);var e=new Cs(t.shape,As);return this.compileAndRun(e,[t])},o.prototype.eluDer=function(t,e){var n=i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new La(\"\\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\\n\",t.shape,e.shape):new Ba(\"return (b >= 1.0) ? a : a * (b + 1.0);\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.selu=function(t){var e=new Cs(t.shape,Ds);return this.compileAndRun(e,[t])},o.prototype.int=function(t){var e=new Cs(t.shape,\"return float(int(x));\");return this.compileAndRun(e,[t],\"int32\")},o.prototype.clip=function(t,e,n){var r,o=(r=i().getBool(\"WEBGL_PACK_CLIP\")?new Ua(t.shape):new Wa(t.shape)).getCustomSetupFunc(e,n);return this.compileAndRun(r,[t],null,o)},o.prototype.abs=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.abs(t);if(i().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\"))return this.packedUnaryOp(t,Is,t.dtype);var e=new Cs(t.shape,Is);return this.compileAndRun(e,[t])},o.prototype.complexAbs=function(t){var e=this.texData.get(t.dataId),n=new Va(t.shape),r=[this.makeComplexComponentTensorInfo(t,e.complexTensors.real),this.makeComplexComponentTensorInfo(t,e.complexTensors.imag)];return this.compileAndRun(n,r)},o.prototype.sigmoid=function(t){var e=new Cs(t.shape,\"return 1.0 / (1.0 + exp(-1.0 * x));\");return this.compileAndRun(e,[t])},o.prototype.softplus=function(t){var e=new Cs(t.shape,\"\\n  float epsilon = 1.1920928955078125e-7;\\n  float threshold = log(epsilon) + 2.0;\\n\\n  bool too_large = x > -threshold;\\n  bool too_small = x < threshold;\\n\\n  float result;\\n  float exp_x = exp(x);\\n\\n  if (too_large){\\n    result = x;\\n  }\\n  else if (too_small){\\n    result = exp_x;\\n  }\\n  else{\\n    result = log(exp_x + 1.0);\\n  }\\n  return result;\\n\");return this.compileAndRun(e,[t])},o.prototype.sin=function(t){var e=new Cs(t.shape,Ms);return this.compileAndRun(e,[t])},o.prototype.cos=function(t){var e=new Cs(t.shape,Bs);return this.compileAndRun(e,[t])},o.prototype.tan=function(t){var e=new Cs(t.shape,\"return tan(x);\");return this.compileAndRun(e,[t])},o.prototype.asin=function(t){var e=new Cs(t.shape,Ps);return this.compileAndRun(e,[t])},o.prototype.acos=function(t){var e=new Cs(t.shape,Ls);return this.compileAndRun(e,[t])},o.prototype.atan=function(t){var e=new Cs(t.shape,Ws);return this.compileAndRun(e,[t])},o.prototype.atan2=function(t,e){var n=i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")?new La(\"\\n  vec4 result = atan(a, b);\\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\\n  \\n  result.r = isNaN.r > 0. ? NAN : result.r;\\n  result.g = isNaN.g > 0. ? NAN : result.g;\\n  result.b = isNaN.b > 0. ? NAN : result.b;\\n  result.a = isNaN.a > 0. ? NAN : result.a;\\n\\n  return result;\\n\",t.shape,e.shape):new Ba(\"\\n  if (isnan(a)) return a;\\n  if (isnan(b)) return b;\\n\\n  return atan(a, b);\\n\",t.shape,e.shape);return this.compileAndRun(n,[t,e])},o.prototype.sinh=function(t){var e=new Cs(t.shape,\"\\n  float e2x = exp(x);\\n  return (e2x - 1.0 / e2x) / 2.0;\\n\");return this.compileAndRun(e,[t])},o.prototype.cosh=function(t){var e=new Cs(t.shape,\"\\n  float e2x = exp(-x);\\n  return (e2x + 1.0 / e2x) / 2.0;\\n\");return this.compileAndRun(e,[t])},o.prototype.tanh=function(t){var e=new Cs(t.shape,\"\\n  float e2x = exp(-2.0 * abs(x));\\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\\n\");return this.compileAndRun(e,[t])},o.prototype.asinh=function(t){var e=new Cs(t.shape,Us);return this.compileAndRun(e,[t])},o.prototype.acosh=function(t){var e=new Cs(t.shape,Vs);return this.compileAndRun(e,[t])},o.prototype.atanh=function(t){var e=new Cs(t.shape,zs);return this.compileAndRun(e,[t])},o.prototype.erf=function(t){var e=new Cs(t.shape,'\\n  // Error function is calculated approximately with elementary function.\\n  // See \"Handbook of Mathematical Functions with Formulas,\\n  // Graphs, and Mathematical Tables\", Abramowitz and Stegun.\\n  float p = 0.3275911;\\n  float a1 = 0.254829592;\\n  float a2 = -0.284496736;\\n  float a3 = 1.421413741;\\n  float a4 = -1.453152027;\\n  float a5 = 1.061405429;\\n\\n  float sign = sign(x);\\n  x = abs(x);\\n  float t = 1.0 / (1.0 + p * x);\\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\\n');return this.compileAndRun(e,[t])},o.prototype.step=function(t,e){var n=new Cs(t.shape,function(t){return void 0===t&&(t=0),Es+\"\\n    return x > 0.0 ? 1.0 : float(\"+t+\");\\n  \"}(e));return this.compileAndRun(n,[t])},o.prototype.conv2dByMatMul=function(t,e,n,r,o,a){var s=t.shape,u=this.texData.get(t.dataId),c=n.inChannels,l=s[0]*s[1]*s[2],h=n.outChannels,f=\"channelsLast\"===n.dataFormat,d=(1===l||1===h)&&c>1e3,p=s[2]%2!=0&&!!u.isPacked;if(d||!i().getBool(\"WEBGL_LAZILY_UNPACK\")||!i().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")||!p){var v=f?s[0]*s[1]*s[2]:s[0]*s[2]*s[3],m=this.reshape(t,[1,v,n.inChannels]),g=this.reshape(e,[1,n.inChannels,n.outChannels]);return this.reshape(this.fusedBatchMatMul({a:m,b:g,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:a}),n.outShape)}var y=f?s[0]*s[1]*(s[2]+1):s[0]*s[2]*(s[3]+1),x={dataId:t.dataId,shape:[1,y,n.inChannels],dtype:t.dtype},b=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,C(_e(u.shape,x.shape),(function(){return\"packed reshape \"+u.shape+\" to \"+x.shape+\" isn't free\"}));var w=this.reshape(e,[1,n.inChannels,n.outChannels]),E=this.fusedBatchMatMul({a:x,b:w,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:a}),R=this.texData.get(E.dataId);return C(R.isPacked,(function(){return\"batchMatMul result is expected to be packed\"})),u.shape=b,R.shape=n.outShape,Lt.makeTensorFromDataId(E.dataId,n.outShape,E.dtype)},o.prototype.conv2dWithIm2Row=function(t,e,n,r,o,a){var i=n.filterWidth,s=n.filterHeight,u=n.inChannels,c=n.outWidth,l=n.outHeight,h=\"channelsLast\"===n.dataFormat,f=i*s*u,d=l*c,p=[f,d],v=t.squeeze([0]),m=e.reshape([1,f,-1]),g=new Li(p,v.shape,n),y=this.compileAndRun(g,[v]).reshape([1,p[0],p[1]]),x=null!=r,b=null!=a,w=o?Qs(o,!0):null,C=new Hi(y.shape,[1,d,n.outChannels],!0,!1,x,w,b),E=[y,m];r&&E.push(r),b&&E.push(a);var R=this.compileAndRun(C,E);return h?R.reshape([1,l,c,n.outChannels]):R.reshape([1,n.outChannels,l,c])},o.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,s=t.preluActivationWeights;if(1===r.filterHeight&&1===r.filterWidth&&1===r.dilationHeight&&1===r.dilationWidth&&1===r.strideHeight&&1===r.strideWidth&&(\"SAME\"===r.padInfo.type||\"VALID\"===r.padInfo.type))return this.conv2dByMatMul(e,n,r,o,a,s);if(i().getBool(\"WEBGL_CONV_IM2COL\")&&1===e.shape[0])return this.conv2dWithIm2Row(e,n,r,o,a,s);var u=null!=o,c=null!=s,l=a?Qs(a,!1):null,h=new Qa(r,u,l,c),f=[e,n];return o&&f.push(o),s&&f.push(s),this.compileAndRun(h,f)},o.prototype.conv2d=function(t,e,n){if(1===n.filterHeight&&1===n.filterWidth&&1===n.dilationHeight&&1===n.dilationWidth&&1===n.strideHeight&&1===n.strideWidth&&(\"SAME\"===n.padInfo.type||\"VALID\"===n.padInfo.type))return this.conv2dByMatMul(t,e,n);if(i().getBool(\"WEBGL_CONV_IM2COL\")&&1===t.shape[0])return this.conv2dWithIm2Row(t,e,n);var r=new Qa(n);return this.compileAndRun(r,[t,e])},o.prototype.conv2dDerInput=function(t,e,n){var r=new Ka(n);return this.compileAndRun(r,[t,e])},o.prototype.conv2dDerFilter=function(t,e,n){var r=new qa(n);return this.compileAndRun(r,[t,e])},o.prototype.fusedDepthwiseConv2D=function(t){var e,n=t.input,r=t.filter,o=t.convInfo,a=t.bias,s=t.activation,u=t.preluActivationWeights,c=i().getBool(\"WEBGL_PACK_DEPTHWISECONV\")&&o.strideWidth<=2&&o.outChannels/o.inChannels==1,l=s?Qs(s,c):null,h=[n,r],f=null!=a,d=null!=u;return f&&h.push(a),d&&h.push(u),c?(e=new ti(o,f,l,d),this.compileAndRun(e,h)):(e=new Za(o,f,l,d),this.compileAndRun(e,h))},o.prototype.depthwiseConv2D=function(t,e,n){var r;return i().getBool(\"WEBGL_PACK_DEPTHWISECONV\")&&n.strideWidth<=2&&n.outChannels/n.inChannels==1?(r=new ti(n),this.compileAndRun(r,[t,e])):(r=new Za(n),this.compileAndRun(r,[t,e]))},o.prototype.depthwiseConv2DDerInput=function(t,e,n){var r=new $a(n);return this.compileAndRun(r,[t,e])},o.prototype.depthwiseConv2DDerFilter=function(t,e,n){var r=new Ya(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3d=function(t,e,n){var r=new Ja(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3dDerInput=function(t,e,n){var r=new Xa(n);return this.compileAndRun(r,[t,e])},o.prototype.conv3dDerFilter=function(t,e,n){var r=new ja(n);return this.compileAndRun(r,[t,e])},o.prototype.maxPool=function(t,e){var n=new $i(e,\"max\",!1);return this.compileAndRun(n,[t])},o.prototype.avgPool=function(t,e){var n=new $i(e,\"avg\",!1);return this.compileAndRun(n,[t],\"float32\")},o.prototype.maxPoolBackprop=function(t,e,n,r){var o=new $i(r,\"max\",!0),a=this.compileAndRun(o,[e]),i=new zi(r),s=this.compileAndRun(i,[t,a],e.dtype);return a.dispose(),s},o.prototype.avgPoolBackprop=function(t,e,n){var r=new Ia(n);return this.compileAndRun(r,[t],e.dtype)},o.prototype.cast=function(t,e){return Po(t,e,this)},o.prototype.unstack=function(t,e){for(var n=t.shape[e],r=new Array(t.rank-1),o=0,a=0;a<t.rank;a++)a!==e&&(r[o++]=t.shape[a]);var i=new Array(t.rank).fill(0),s=t.shape.slice();s[e]=1;var u=new Array(n);for(a=0;a<u.length;a++)i[e]=a,u[a]=this.slice(t,i,s).reshape(r);return u},o.prototype.avgPool3d=function(t,e){var n=new Qi(e,\"avg\",!1);return this.compileAndRun(n,[t],\"float32\")},o.prototype.avgPool3dBackprop=function(t,e,n){var r=new ka(n);return this.compileAndRun(r,[t],e.dtype)},o.prototype.maxPool3d=function(t,e){var n=new Qi(e,\"max\",!1);return this.compileAndRun(n,[t],\"float32\")},o.prototype.maxPool3dBackprop=function(t,e,n,r){var o=new Qi(r,\"max\",!0),a=this.compileAndRun(o,[e]),i=new Gi(r),s=this.compileAndRun(i,[t,a],e.dtype);return a.dispose(),s},o.prototype.reshape=function(t,e){var n=this.texData.get(t.dataId);if(n.isPacked&&!_e(t.shape,e)&&(null===n.texture||!_e(n.shape,e))){var r=this.packedReshape(t,e);return Lt.makeTensorFromDataId(r.dataId,r.shape,r.dtype)}return Lo(t,e)},o.prototype.resizeBilinear=function(t,e,n,r){var o=i().getBool(\"WEBGL_PACK_IMAGE_OPERATIONS\")?new ns(t.shape,e,n,r):new es(t.shape,e,n,r);return this.compileAndRun(o,[t],\"float32\")},o.prototype.resizeBilinearBackprop=function(t,e,n){var r=new ts(t,e,n);return this.compileAndRun(r,[t])},o.prototype.resizeNearestNeighbor=function(t,e,n,r){var o=new os(t.shape,e,n,r);return this.compileAndRun(o,[t])},o.prototype.resizeNearestNeighborBackprop=function(t,e,n){var r=new rs(t,e,n);return this.compileAndRun(r,[t])},o.prototype.multinomial=function(t,e,n,r){var o=e?t:go(t),a=o.shape[0],i=o.shape[1],s=new qi(a,i,n),u=s.getCustomSetupFunc(r);return this.compileAndRun(s,[o],\"int32\",u)},o.prototype.oneHot=function(t,e,n,r){var o=new Ki(t.size,e,n,r);return this.compileAndRun(o,[t])},o.prototype.diag=function(t){var e=new si(t.size);return this.compileAndRun(e,[t])},o.prototype.nonMaxSuppression=function(t,e,n,r,o){return dn(\"tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\"),jo(t.dataSync(),e.dataSync(),n,r,o)},o.prototype.cropAndResize=function(t,e,n,r,o,a){var i=new ei(t.shape,e.shape,r,o,a);return this.compileAndRun(i,[t,e,n],\"float32\")},o.prototype.depthToSpace=function(t,e,n){C(e>1,(function(){return\"blockSize should be > 1 for depthToSpace, but was: \"+e}));var r=t.shape[0],o=\"NHWC\"===n?t.shape[1]:t.shape[2],a=\"NHWC\"===n?t.shape[2]:t.shape[3],i=\"NHWC\"===n?t.shape[3]:t.shape[1],s=o*e,u=a*e,c=i/(e*e),l=new ii(\"NHWC\"===n?[r,s,u,c]:[r,c,s,u],e,n);return this.compileAndRun(l,[t])},o.prototype.split=function(t,e,n){return Zo(t,e,n)},o.prototype.scatterND=function(t,e,n){var r=Zr(0,t,n),o=r.sliceRank,a=r.numUpdates,i=r.sliceSize,s=r.strides,u=r.outputSize,c=[u/i,i],l=t.reshape([a,o]),h=e.reshape([a,i]);if(0===u)return Lo(Fn([]),n);var f=On(0),d=new ss(a,o,l.rank,h.rank,s,c);return this.compileAndRun(d,[h,l,f]).reshape(n)},o.prototype.sparseToDense=function(t,e,n,r){var o=Zr(0,t,n),a=o.sliceRank,i=o.numUpdates,s=o.strides,u=o.outputSize,c=new ss(i,a,t.rank,e.rank,s,[u,1],!1);return this.compileAndRun(c,[e,t,r]).reshape(n)},o.prototype.fft=function(t){return this.fftImpl(t,!1)},o.prototype.ifft=function(t){return this.fftImpl(t,!0)},o.prototype.fftImpl=function(t,e){var n=this.texData.get(t.dataId),r=new pi(fi,t.shape,e),o=new pi(di,t.shape,e),a=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag)],i=this.compileAndRun(r,a),s=this.compileAndRun(o,a),u=this.complex(i,s).as2D(t.shape[0],t.shape[1]);return i.dispose(),s.dispose(),u},o.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=jr(t,e),a=o[0],i=o[1],s=o[2],u=o[3],c=e.reshape([i,r]),l=t.reshape([t.size/s,s]),h=new gi(r,u,[i,s]);return this.compileAndRun(h,[l,c]).reshape(a)},o.prototype.fill=function(t,e,n){if(\"string\"===(n=n||j(e))){var r=P(n,k(t));return r.fill(e),Lt.makeTensor(r,t,n,this)}var o=new vi(t,e),a=o.getCustomSetupFunc(e);return this.compileAndRun(o,[],n,a)},o.prototype.onesLike=function(t){if(\"string\"===t.dtype)throw new Error(\"onesLike is not supported under string dtype\");return this.fill(t.shape,1,t.dtype)},o.prototype.zerosLike=function(t){return this.fill(t.shape,\"string\"===t.dtype?\"\":0,t.dtype)},o.prototype.linspace=function(t,e,n){return Wo(t,e,n)},o.prototype.makeTensorInfo=function(t,e){var n=this.write(null,t,e);return this.texData.get(n).usage=null,{dataId:n,shape:t,dtype:e}},o.prototype.makeOutput=function(t,e){var n=this.makeTensorInfo(t,e).dataId;return Lt.makeTensorFromDataId(n,t,e,this)},o.prototype.unpackTensor=function(t){var e=new Ys(t.shape);return this.runWebGLProgram(e,[t],t.dtype)},o.prototype.packTensor=function(t){var e=new ji(t.shape);return this.runWebGLProgram(e,[t],t.dtype,null,!0)},o.prototype.packedReshape=function(t,e){var n=[Ae(t.shape)].concat(De(t.shape)),r={dtype:t.dtype,shape:n,dataId:t.dataId},o=[Ae(e)].concat(De(e)),a=new Zi(o,n),i=this.runWebGLProgram(a,[r],t.dtype,null,!0);return{dataId:i.dataId,shape:e,dtype:i.dtype}},o.prototype.decode=function(t){var e,n=this.texData.get(t),r=n.isPacked,o=n.shape,a=n.dtype,i=Te(o);e=r?new ai(i):new oi(i);return{dtype:a,shape:o,dataId:this.runWebGLProgram(e,[{shape:i,dtype:a,dataId:t}],a,null,!0).dataId}},o.prototype.runWebGLProgram=function(t,e,n,r,o){var a=this;void 0===o&&(o=!1);var s=this.makeTensorInfo(t.outputShape,n),u=this.texData.get(s.dataId);if(t.packedOutput&&(u.isPacked=!0),t.outPackingScheme===Vt.DENSE){var c=Yt(t.outputShape);u.texShape=c.map((function(t){return 2*t}))}if(null!=t.outTexUsage&&(u.usage=t.outTexUsage),0===k(s.shape))return u.values=B(s.dtype,0),s;var l=[],h=e.map((function(e){if(\"complex64\"===e.dtype)throw new Error(\"GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.\");var n=a.texData.get(e.dataId);if(null==n.texture){if(!t.packedInputs&&k(e.shape)<=i().getNumber(\"WEBGL_SIZE_UPLOAD_UNIFORM\"))return{shape:e.shape,texData:null,isUniform:!0,uniformValues:n.values};t.packedInputs&&(n.isPacked=!0,n.shape=e.shape)}else if(!!n.isPacked!=!!t.packedInputs)e=n.isPacked?a.unpackTensor(e):a.packTensor(e),l.push(e),n=a.texData.get(e.dataId);else if(n.isPacked&&!_e(n.shape,e.shape)){var r=e,o=e.shape;e.shape=n.shape,e=a.packedReshape(e,o),l.push(e),n=a.texData.get(e.dataId),r.shape=o}return a.uploadToGPU(e.dataId),{shape:e.shape,texData:n,isUniform:!1}}));this.uploadToGPU(s.dataId);var f,d={shape:s.shape,texData:u,isUniform:!1},p=function(t,e,n){var r=\"\";e.concat(n).forEach((function(t){var e=null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0,n=t.isUniform?\"uniform\":t.texData.texShape;r+=t.shape+\"_\"+n+\"_\"+e}));var o=t.userCode,a=t.constructor.name;return a+=\"_\"+r+\"_\"+o}(t,h,d),v=this.getAndSaveBinary(p,(function(){return function(t,e,n,r){var o=e.userCode,a=n.map((function(t,n){var r={logicalShape:t.shape,texShape:t.isUniform?null:t.texData.texShape,isUniform:t.isUniform,isPacked:!t.isUniform&&t.texData.isPacked,flatOffset:null};return null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0&&(r.flatOffset=t.texData.slice.flatOffset),{name:e.variableNames[n],shapeInfo:r}})),s=a.map((function(t){return t.shapeInfo})),u={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},c=fa(a,u,o,e.packedInputs),l=t.createProgram(c),h=null,f=t.getUniformLocation(l,\"NAN\",!1);1===i().getNumber(\"WEBGL_VERSION\")&&(h=t.getUniformLocation(l,\"INFINITY\",!1));for(var d={},p=0;p<e.variableNames.length;p++){var v=e.variableNames[p];d[v]=t.getUniformLocation(l,v,!1),d[\"offset\"+v]=t.getUniformLocation(l,\"offset\"+v,!1)}return{program:e,source:c,webGLProgram:l,uniformLocations:d,inShapeInfos:s,outShapeInfo:u,infLoc:h,nanLoc:f}}(a.gpgpu,t,h,d)})),m=null!=this.activeTimers;if(m&&(f=this.startTimer()),function(t,e,n,r,o){Pi(e.inShapeInfos,n),Pi([e.outShapeInfo],[r]);var a=r.texData.texture,s=r.texData.texShape;r.texData.isPacked?t.setOutputPackedMatrixTexture(a,s[0],s[1]):t.setOutputMatrixTexture(a,s[0],s[1]),t.setProgram(e.webGLProgram),1===i().getNumber(\"WEBGL_VERSION\")&&null!==e.infLoc&&t.gl.uniform1f(e.infLoc,1/0),null!==e.nanLoc&&t.gl.uniform1f(e.nanLoc,NaN),n.forEach((function(n,r){var o=e.program.variableNames[r],a=e.uniformLocations[o],i=e.uniformLocations[\"offset\"+o];if(null!=a)if(n.isUniform)if(k(n.shape)<2)t.gl.uniform1f(a,n.uniformValues[0]);else{var s=n.uniformValues;s instanceof Float32Array||(s=new Float32Array(s)),t.gl.uniform1fv(a,s)}else null!=n.texData.slice&&null!=i&&t.gl.uniform1i(i,n.texData.slice.flatOffset),t.setInputMatrixTexture(n.texData.texture,a,r)})),null!=o&&o(t,e.webGLProgram),t.executeProgram()}(this.gpgpu,v,h,d,r),l.forEach((function(t){return a.disposeData(t.dataId)})),m&&(f=this.endTimer(f),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(f)})),!i().getBool(\"WEBGL_LAZILY_UNPACK\")&&u.isPacked&&!1===o){var g=this.unpackTensor(s);return this.disposeData(s.dataId),g}return s},o.prototype.compileAndRun=function(t,e,n,r,o){void 0===o&&(o=!1),n=n||e[0].dtype;var a=this.runWebGLProgram(t,e,n,r,o);return Lt.makeTensorFromDataId(a.dataId,a.shape,a.dtype)},o.prototype.getAndSaveBinary=function(t,e){return t in this.binaryCache||(this.binaryCache[t]=e()),this.binaryCache[t]},o.prototype.getTextureManager=function(){return this.textureManager},o.prototype.dispose=function(){var t=this;if(!this.disposed){if(!i().getBool(\"IS_TEST\"))Object.keys(this.binaryCache).forEach((function(e){t.gpgpu.deleteProgram(t.binaryCache[e].webGLProgram),delete t.binaryCache[e]}));this.textureManager.dispose(),null!=this.canvas&&\"undefined\"!=typeof HTMLCanvasElement&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0}},o.prototype.floatPrecision=function(){var t=this;return null==this.floatPrecisionValue&&(this.floatPrecisionValue=Ze((function(){if(!i().get(\"WEBGL_RENDER_FLOAT32_ENABLED\")){var e=i().getBool(\"DEBUG\");i().set(\"DEBUG\",!1);var n=t.abs(On(1e-8)).dataSync()[0];if(i().set(\"DEBUG\",e),n>0)return 32}return 16}))),this.floatPrecisionValue},o.prototype.epsilon=function(){return 32===this.floatPrecision()?1e-7:1e-4},o.prototype.uploadToGPU=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,a=n.values,i=n.texture,s=n.usage,u=n.isPacked;if(null==i){var c,l=null!=this.activeTimers;l&&(c=et());var h=n.texShape;if(null==h&&(h=Ne(r,u),n.texShape=h),null!=a){var f=Te(r),d=void 0,p=h[1],v=h[0],m=a instanceof Uint8Array;u?(p=(e=$t(h[0],h[1]))[0],v=e[1],d=new hi(f,[v,p],m)):d=new li(f,[v,p],m);var g=this.makeTensorInfo([v,p],o);this.texData.get(g.dataId).usage=m?zt.PIXELS:zt.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId),p,v,a);var y=this.runWebGLProgram(d,[g],o,null,!0),x=this.texData.get(y.dataId);n.texture=x.texture,n.texShape=x.texShape,n.isPacked=x.isPacked,n.usage=x.usage,this.disposeData(g.dataId),this.texData.delete(y.dataId),n.values=null,l&&(this.uploadWaitMs+=et()-c)}else{var b=this.acquireTexture(h,s,o,u);n.texture=b}}},o.prototype.convertAndCacheOnCPU=function(t,e){var n=this.texData.get(t),r=n.dtype;return this.releaseGPUData(t),null!=e&&(n.values=function(t,e){if(\"float32\"===e||\"complex64\"===e)return t;if(\"int32\"===e||\"bool\"===e){for(var n=\"int32\"===e?new Int32Array(t.length):new Uint8Array(t.length),r=0;r<n.length;++r)n[r]=Math.round(t[r]);return n}throw new Error(\"Unknown dtype \"+e)}(e,r)),n.values},o.prototype.acquireTexture=function(t,e,n,r){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>1024*this.numMBBeforeWarning*1024){var o=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(\"High memory usage in GPU: \"+o+\" MB, most likely due to a memory leak\")}return this.textureManager.acquireTexture(t,e,r)},o.prototype.computeBytes=function(t,e){return t[0]*t[1]*z(e)},o}(bo);Wt()&&Lt.registerBackend(\"webgl\",(function(){return new Zs}),2);var tu=An({square_:function(t){var e=mn(t,\"x\",\"square\"),n=[e];return Lt.runKernelFunc((function(t,n){return n([e]),t.square(e)}),{x:e},null,\"Square\",{},n,[])}}),eu=\"SquaredDifference\";var nu=An({squaredDifference_:function(t,e){var n,r=mn(t,\"a\",\"squaredDifference\"),o=mn(e,\"b\",\"squaredDifference\");n=Nt(r,o),r=n[0],o=n[1],Ro(r.shape,o.shape);var a={a:r,b:o},i=[r,o];return Lt.runKernelFunc((function(t,e){var n=t.squaredDifference(r,o);return e([r,o]),n}),a,(function(t,e){var n=e[0],r=e[1],o=On(2);return{a:function(){return t.mul(n.sub(r).mul(o))},b:function(){return t.mul(r.sub(n).mul(o))}}}),eu,{},i,[])}});var ru=An({abs_:function(t){var e=mn(t,\"x\",\"abs\");return\"complex64\"===e.dtype?Lt.runKernelFunc((function(t){return t.complexAbs(e)}),{$x:e}):Lt.runKernelFunc((function(t,n){var r=t.abs(e);return n([e]),r}),{x:e},(function(t,e){var n=e[0];return{x:function(){return t.mul(n.toFloat().step(-1))}}}),\"Abs\")}}),ou=An({acos_:function(t){var e=mn(t,\"x\",\"acos\");return Lt.runKernelFunc((function(t,n){var r=t.acos(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return{$x:function(){return t.divStrict(On(1).sub(n.toFloat().square()).sqrt()).neg()}}}))}}),au=An({acosh_:function(t){var e=mn(t,\"x\",\"acosh\");return Lt.runKernelFunc((function(t,n){var r=t.acosh(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return{$x:function(){return t.divStrict(n.toFloat().square().sub(1).sqrt())}}}))}}),iu=An({asin_:function(t){var e=mn(t,\"x\",\"asin\");return Lt.runKernelFunc((function(t,n){var r=t.asin(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return{$x:function(){return t.divStrict(On(1).sub(n.toFloat().square()).sqrt())}}}))}}),su=An({asinh_:function(t){var e=mn(t,\"x\",\"asinh\");return Lt.runKernelFunc((function(t,n){var r=t.asinh(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return{$x:function(){return t.divStrict(On(1).add(n.toFloat().square()).sqrt())}}}))}}),uu=An({atan_:function(t){var e=mn(t,\"x\",\"atan\");return Lt.runKernelFunc((function(t,n){var r=t.atan(e);return n([e]),r}),{$x:e},(function(t,e){var 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must match input depth for filter \"+u.shape[1]+\".\"})),C(Mo(n,a),(function(){return\"Error in conv1D: Either stride or dilation must be 1. 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Got strides \"+n+\" and dilations '\"+a+\"'\"})),C(\"NDHWC\"===o,(function(){return\"Error in conv3d: got dataFormat of \"+o+\" but only NDHWC is currently supported.\"}));var l=Ao(u.shape,s.shape,n,a,r),h=Lt.runKernelFunc((function(t,e){var n=t.conv3d(u,s,l);return e([u,s]),n}),{x:u,$filter:s},(function(t,e){C(zc(a),(function(){return\"Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '\"+a+\"'\"}));var o=e[0],i=e[1];return{x:function(){return Gc(o.shape,t,i,n,r)},$filter:function(){return function(t,e,n,r,o){var a=t;4===t.rank&&(a=t.as5D(1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]));var i=e;4===i.rank&&(i=e.as5D(1,e.shape[0],e.shape[1],e.shape[2],e.shape[3]));C(5===a.rank,(function(){return\"Error in conv3dDerFilter: input must be rank 5, but got shape \"+a.shape+\".\"})),C(5===i.rank,(function(){return\"Error in conv3dDerFilter: dy must be rank 5, but got shape \"+i.shape+\".\"})),C(5===n.length,(function(){return\"Error in conv3dDerFilter: filterShape must be length 5, but got \"+n+\".\"})),C(a.shape[4]===n[3],(function(){return\"Error in conv3dDerFilter: depth of input \"+a.shape[4]+\") must match input depth in filter (\"+n[3]+\".\"})),C(i.shape[4]===n[4],(function(){return\"Error in conv3dDerFilter: depth of dy (\"+i.shape[4]+\") must match output depth for filter (\"+n[4]+\").\"}));var s=Ao(a.shape,n,r,1,o);return Lt.runKernelFunc((function(t){return t.conv3dDerFilter(a,i,s)}),{x5D:a,dy5D:i})}(o,t,i.shape,n,r)}}}));return c?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}}),jc=An({conv2dDerFilter_:function(t,e,n,r,o,a,i){void 0===a&&(a=\"NHWC\");var s=t;3===t.rank&&(s=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var u=e;3===u.rank&&(u=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),C(4===s.rank,(function(){return\"Error in conv2dDerFilter: input must be rank 4, but got shape \"+s.shape+\".\"})),C(4===u.rank,(function(){return\"Error in conv2dDerFilter: dy must be rank 4, but got shape \"+u.shape+\".\"})),C(4===n.length,(function(){return\"Error in conv2dDerFilter: filterShape must be length 4, but got \"+n+\".\"}));var c=\"NHWC\"===a?s.shape[3]:s.shape[1],l=\"NHWC\"===a?u.shape[3]:u.shape[1];C(c===n[2],(function(){return\"Error in conv2dDerFilter: depth of input \"+c+\") must match input depth in filter (\"+n[2]+\".\"})),C(l===n[3],(function(){return\"Error in conv2dDerFilter: depth of dy (\"+l+\") must match output depth for filter (\"+n[3]+\").\"})),null!=i&&C(A(o),(function(){return\"Error in conv2dDerFilter: pad must be an integer when using, dimRoundingMode \"+i+\" but got pad \"+o+\".\"}));var h=Bo(a),f=So(s.shape,n,r,1,o,i,!1,h);return Lt.runKernelFunc((function(t){return t.conv2dDerFilter(s,u,f)}),{x4D:s,dy4D:u})}}),Xc=An({conv2dDerInput_:Vc}),Yc=An({depthwiseConv2d_:function(t,e,n,r,o,a,i){void 0===o&&(o=\"NHWC\"),void 0===a&&(a=[1,1]);var s=mn(t,\"x\",\"depthwiseConv2d\"),u=mn(e,\"filter\",\"depthwiseConv2d\"),c=s,l=!1;3===s.rank&&(l=!0,c=s.as4D(1,s.shape[0],s.shape[1],s.shape[2])),C(4===c.rank,(function(){return\"Error in depthwiseConv2d: input must be rank 4, but got rank \"+c.rank+\".\"})),C(4===u.rank,(function(){return\"Error in depthwiseConv2d: filter must be rank 4, but got rank \"+u.rank+\".\"})),C(c.shape[3]===u.shape[2],(function(){return\"Error in depthwiseConv2d: number of input channels (\"+c.shape[3]+\") must match the inChannels dimension in filter \"+u.shape[2]+\".\"})),null==a&&(a=[1,1]),C(Mo(n,a),(function(){return\"Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides \"+n+\" and dilations '\"+a+\"'\"})),null!=i&&C(A(r),(function(){return\"Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode \"+i+\" but got pad \"+r+\".\"}));var h=So(c.shape,u.shape,n,a,r,i,!0),f=[c,u],d=Lt.runKernelFunc((function(t,e){var n=t.depthwiseConv2D(c,u,h);return e([c,u]),n}),{x:c,filter:u},(function(t,e){C(Oo(a),(function(){return\"Error in gradient of depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '\"+a+\"'\"}));var n=e[0],r=e[1];return{x:function(){return $c(n.shape,t,r,h)},filter:function(){return Qc(n,t,r.shape,h)}}}),\"DepthwiseConv2dNative\",h,f);return l?d.as3D(d.shape[1],d.shape[2],d.shape[3]):d}}),$c=An({depthwiseConv2dDerInput_:function(t,e,n,r){var o=e,a=!1;3===e.rank&&(a=!0,o=e.as4D(1,e.shape[0],e.shape[1],e.shape[2]));var i=Lt.runKernelFunc((function(t){return t.depthwiseConv2DDerInput(o,n,r)}),{dy4D:o});return a?i.as3D(i.shape[1],i.shape[2],i.shape[3]):i}}),Qc=An({depthwiseConv2dDerFilter_:function(t,e,n,r){var o=t;3===t.rank&&(o=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var a=e;return 3===a.rank&&(a=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),Lt.runKernelFunc((function(t){return t.depthwiseConv2DDerFilter(o,a,r)}),{x4D:o,dy4D:a})}}),Jc=An({separableConv2d_:function(t,e,n,r,o,a,i){void 0===a&&(a=[1,1]),void 0===i&&(i=\"NHWC\");var s=mn(t,\"x\",\"separableConv2d\"),u=mn(e,\"depthwiseFilter\",\"separableConv2d\"),c=mn(n,\"pointwiseFilter\",\"separableConv2d\"),l=s,h=!1;if(3===s.rank&&(h=!0,l=s.as4D(1,s.shape[0],s.shape[1],s.shape[2])),\"NCHW\"===i)throw new Error(\"separableConv2d currently does not support dataFormat NCHW; only NHWC is supported\");C(4===l.rank,(function(){return\"Error in separableConv2d: input must be rank 4, but got rank \"+l.rank+\".\"})),C(4===u.rank,(function(){return\"Error in separableConv2d: depthwise filter must be rank 4, but got rank \"+u.rank+\".\"})),C(4===c.rank,(function(){return\"Error in separableConv2d: pointwise filter must be rank 4, but got rank \"+u.rank+\".\"})),C(1===c.shape[0],(function(){return\"Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got \"+c.shape[0]+\".\"})),C(1===c.shape[1],(function(){return\"Error in separableConv2d: the second dimension of pointwise filter must be 1, but got \"+c.shape[1]+\".\"}));var f=u.shape[2],d=u.shape[3];C(c.shape[2]===f*d,(function(){return\"Error in separableConv2d: the third dimension of pointwise filter must be \"+f*d+\", but got \"+c.shape[2]+\".\"}));var p=Yc(l,u,r,o,i,a),v=qc(p,c,1,\"valid\",i);return h?v.as3D(v.shape[1],v.shape[2],v.shape[3]):v}}),Zc=An({conv2dTranspose_:function(t,e,n,r,o,a){return Vc(n,mn(t,\"x\",\"conv2dTranspose\"),mn(e,\"filter\",\"conv2dTranspose\"),r,o,\"NHWC\",a)}}),tl=An({conv3dTranspose_:function(t,e,n,r,o){return Gc(n,mn(t,\"x\",\"conv3dTranspose\"),mn(e,\"filter\",\"conv3dTranspose\"),r,o)}});var el=An({matMul_:function(t,e,n,r){var o;void 0===n&&(n=!1),void 0===r&&(r=!1);var a=mn(t,\"a\",\"matMul\"),i=mn(e,\"b\",\"matMul\");o=Nt(a,i),a=o[0],i=o[1];var s=n?a.shape[a.rank-2]:a.shape[a.rank-1],u=r?i.shape[i.rank-1]:i.shape[i.rank-2],c=n?a.shape[a.rank-1]:a.shape[a.rank-2],l=r?i.shape[i.rank-2]:i.shape[i.rank-1],h=a.shape.slice(0,-2),f=i.shape.slice(0,-2),d=k(h),p=k(f);C(a.rank>=2&&i.rank>=2&&a.rank===i.rank,(function(){return\"Error in matMul: inputs must have the same rank of at least 2, got ranks \"+a.rank+\" and \"+i.rank+\".\"})),C(S(h,f),(function(){return\"Error in matMul: outer dimensions (\"+h+\") and (\"+f+\") of Tensors with shapes \"+a.shape+\" and \"+i.shape+\" must match.\"})),C(s===u,(function(){return\"Error in matMul: inner shapes (\"+s+\") and (\"+u+\") of Tensors with shapes \"+a.shape+\" and \"+i.shape+\" and transposeA=\"+n+\" and transposeB=\"+r+\" must match.\"}));var v=a.shape.slice(0,-2).concat([c,l]),m=n?a.as3D(d,s,c):a.as3D(d,c,s),g=r?i.as3D(p,l,u):i.as3D(p,u,l),y={transposeA:n,transposeB:r};return Lt.runKernelFunc((function(t,e){var o=t.batchMatMul(m,g,n,r);return e([m,g]),o}),{a:m,b:g},(function(t,e){var o=e,a=o[0],i=o[1];return n||r?!n&&r?{a:function(){return t.matMul(i,!1,!1)},b:function(){return t.matMul(a,!0,!1)}}:n&&!r?{a:function(){return i.matMul(t,!1,!0)},b:function(){return a.matMul(t,!1,!1)}}:{a:function(){return i.matMul(t,!0,!0)},b:function(){return t.matMul(a,!0,!0)}}:{a:function(){return t.matMul(i,!1,!0)},b:function(){return a.matMul(t,!0,!1)}}}),\"BatchMatMul\",y).reshape(v)}}),nl=An({dot_:function(t,e){var n=mn(t,\"t1\",\"dot\"),r=mn(e,\"t2\",\"dot\");C(!(1!==n.rank&&2!==n.rank||1!==r.rank&&2!==r.rank),(function(){return\"Error in dot: inputs must all be rank 1 or 2, but got ranks \"+n.rank+\" and \"+r.rank+\".\"}));var o=1===n.rank?n.size:n.shape[1],a=1===r.rank?r.size:r.shape[0];return C(o===a,(function(){return\"Error in dot: inner dimensions of inputs must match, but got \"+o+\" and \"+a+\".\"})),1===n.rank&&1===r.rank?n.as2D(1,-1).matMul(r.as2D(-1,1)).asScalar():1===n.rank&&2===r.rank?n.as2D(1,-1).matMul(r.as2D(r.shape[0],r.shape[1])).as1D():2===n.rank&&1===r.rank?n.matMul(r.as2D(-1,1)).as1D():n.matMul(r.as2D(r.shape[0],r.shape[1]))}}),rl=An({outerProduct_:function(t,e){var n=mn(t,\"v1\",\"outerProduct\"),r=mn(e,\"v2\",\"outerProduct\");return C(1===n.rank&&1===r.rank,(function(){return\"Error in outerProduct: inputs must be rank 1, but got ranks \"+n.rank+\" and \"+r.rank+\".\"})),n.as2D(-1,1).matMul(r.as2D(1,-1))}});var ol=An({reverse_:function(t,e){var n=mn(t,\"x\",\"reverse\");if(0===n.rank)return n.clone();var r=O(e,n.shape);return Lt.runKernelFunc((function(t){return t.reverse(n,r)}),{$x:n},(function(t){return{$x:function(){return t.reverse(r)}}})).reshapeAs(n)}}),al=An({reverse1d_:function(t){var e=mn(t,\"x\",\"reverse\");return C(1===e.rank,(function(){return\"Error in reverse1D: x must be rank 1 but got rank \"+e.rank+\".\"})),ol(e,0)}}),il=An({reverse2d_:function(t,e){var n=mn(t,\"x\",\"reverse\");return C(2===n.rank,(function(){return\"Error in reverse2D: x must be rank 2 but got rank \"+n.rank+\".\"})),ol(n,e)}}),sl=An({reverse3d_:function(t,e){var n=mn(t,\"x\",\"reverse\");return C(3===n.rank,(function(){return\"Error in reverse3D: x must be rank 3 but got rank \"+n.rank+\".\"})),ol(n,e)}}),ul=An({reverse4d_:function(t,e){var n=mn(t,\"x\",\"reverse\");return C(4===n.rank,(function(){return\"Error in reverse4D: x must be rank 4 but got rank \"+n.rank+\".\"})),ol(n,e)}});function cl(t,e,n,r,o,a){var i=mn(t,\"x\",\"maxPool\"),s=i,u=!1;3===i.rank&&(u=!0,s=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),null==r&&(r=[1,1]),C(4===s.rank,(function(){return\"Error in maxPool: input must be rank 4 but got rank \"+s.rank+\".\"})),C(Mo(n,r),(function(){return\"Error in maxPool: Either strides or dilations must be 1. Got strides \"+n+\" and dilations '\"+r+\"'\"})),null!=a&&C(A(o),(function(){return\"Error in maxPool: pad must be an integer when using, dimRoundingMode \"+a+\" but got pad \"+o+\".\"}));var c=Io(s.shape,e,n,r,o,a);if(1===c.filterWidth&&1===c.filterHeight&&S(c.inShape,c.outShape))return i.clone();var l=[s],h=Lt.runKernelFunc((function(t,e){var n=t.maxPool(s,c);return e([s,n]),n}),{x:s},(function(t,a){var i=a[0],s=a[1];return{x:function(){return function(t,e,n,r,o,a,i,s){var u=mn(t,\"dy\",\"maxPoolBackprop\"),c=mn(e,\"input\",\"maxPoolBackprop\"),l=mn(n,\"output\",\"maxPoolBackprop\");C(c.rank===u.rank,(function(){return\"Rank of input (\"+c.rank+\") does not match rank of dy (\"+u.rank+\")\"})),null==a&&(a=[1,1]);C(Mo(o,a),(function(){return\"Error in maxPoolBackProp: Either strides or dilations must be 1. Got strides \"+o+\" and dilations '\"+a+\"'\"})),C(4===u.rank,(function(){return\"Error in maxPoolBackprop: dy must be rank 4 but got rank \"+u.rank+\".\"})),C(4===c.rank,(function(){return\"Error in maxPoolBackprop: input must be rank 4 but got rank \"+c.rank+\".\"})),null!=s&&C(A(i),(function(){return\"Error in maxPoolBackprop: pad must be an integer when using, dimRoundingMode \"+s+\" but got pad \"+i+\".\"}));var h=Io(c.shape,r,o,a,i,s);return Lt.runKernelFunc((function(t){return t.maxPoolBackprop(u,c,l,h)}),{$dy:u,$input:c})}(t,i,s,e,n,r,o)}}}),\"MaxPool\",c,l);return u?h.as3D(h.shape[1],h.shape[2],h.shape[3]):h}function ll(t,e,n,r,o,a){var i=mn(t,\"x\",\"avgPool\",\"float32\");null==r&&(r=[1,1]),C(Mo(n,r),(function(){return\"Error in avgPool: Either strides or dilations must be 1. Got strides \"+n+\" and dilations '\"+r+\"'\"}));var s=i,u=!1;3===i.rank&&(u=!0,s=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),C(4===s.rank,(function(){return\"Error in avgPool: x must be rank 4 but got rank \"+s.rank+\".\"})),null!=a&&C(A(o),(function(){return\"Error in avgPool: pad must be an integer when using, dimRoundingMode \"+a+\" but got pad \"+o+\".\"}));var c=Io(s.shape,e,n,r,o,a);if(1===c.filterWidth&&1===c.filterHeight&&S(c.inShape,c.outShape))return i.clone();var l=Lt.runKernelFunc((function(t){return t.avgPool(s,c)}),{x:s},(function(t){return{x:function(){return function(t,e,n,r,o,a){var i=mn(t,\"dy\",\"avgPoolBackprop\"),s=mn(e,\"input\",\"avgPoolBackprop\");C(s.rank===i.rank,(function(){return\"Rank of input (\"+s.rank+\") does not match rank of dy (\"+i.rank+\")\"})),null==o&&(o=[1,1]);C(Mo(r,o),(function(){return\"Error in avgPoolBackprop: Either strides or dilations must be 1. Got strides \"+r+\" and dilations '\"+o+\"'\"}));var u=s,c=i,l=!1;3===s.rank&&(l=!0,u=s.as4D(1,s.shape[0],s.shape[1],s.shape[2]),c=i.as4D(1,i.shape[0],i.shape[1],i.shape[2]));C(4===c.rank,(function(){return\"Error in avgPoolBackprop: dy must be rank 4 but got rank \"+c.rank+\".\"})),C(4===u.rank,(function(){return\"Error in avgPoolBackprop: input must be rank 4 but got rank \"+u.rank+\".\"}));var h=Io(u.shape,n,r,o,a),f=Lt.runKernelFunc((function(t){return t.avgPoolBackprop(c,u,h)}),{dy4D:c,input4D:u});if(l)return f.as3D(f.shape[1],f.shape[2],f.shape[3]);return f}(t,s,e,n,r,o)}}}),\"AvgPool\",c);return l=l.cast(i.dtype),u?l.as3D(l.shape[1],l.shape[2],l.shape[3]):l}var hl=An({maxPool_:function(t,e,n,r,o){return cl(t,e,n,1,r,o)}}),fl=An({avgPool_:function(t,e,n,r,o){return ll(t,e,n,1,r,o)}}),dl=An({pool_:function(t,e,n,r,o,a){null==o&&(o=[1,1]),null==a&&(a=1),0===r&&(r=\"valid\");var i=mn(t,\"x\",\"maxPool\"),s=i,u=!1;3===i.rank&&(u=!0,s=i.as4D(1,i.shape[0],i.shape[1],i.shape[2])),C(Mo(a,o),(function(){return\"Error in pool: Either strides or dilations must be 1. Got strides \"+a+\" and dilations '\"+o+\"'\"}));var c,l=Io(s.shape,e,a,o,r),h=[l.dilationHeight,l.dilationWidth];c=\"same\"===r?function(t,e){var n=t.map((function(t,n){return t+(t-1)*(e[n]-1)})).map((function(t){return t-1})),r=n.map((function(t){return Math.floor(t/2)})),o=n.map((function(t,e){return t-r[e]}));return n.map((function(t,e){return[r[e],o[e]]}))}([l.filterHeight,l.filterWidth],h):[[0,0],[0,0]];var f=1===h[0]&&1===h[1],d=function(t,e,n){var r=n.map((function(t){return t[0]})),o=n.map((function(t){return t[1]})),a=t.concat(r,o),i=e.map((function(t,e){return(t-a[e]%t)%t})),s=o.map((function(t,e){return t+i[e]})),u=e.map((function(t,e){return[r[e],s[e]]})),c=e.map((function(t,e){return[0,i[e]]}));return[u,c]}([l.inHeight,l.inWidth],h,c),p=d[0],v=d[1],m=f?r:\"valid\",g=f?s:Mr(s,h,p),y=(\"avg\"===n?function(){return ll(g,e,a,1,m)}:function(){return cl(g,e,a,1,m)})(),x=f?y:vr(y,h,v);return u?x.as3D(x.shape[1],x.shape[2],x.shape[3]):x}}),pl=An({maxPool3d_:function(t,e,n,r,o,a,i){void 0===a&&(a=\"NDHWC\");var s=mn(t,\"x\",\"maxPool3d\"),u=s,c=!1;4===s.rank&&(c=!0,u=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3])),null==i&&(i=[1,1,1]),C(5===u.rank,(function(){return\"Error in maxPool3d: x must be rank 5 but got rank \"+u.rank+\".\"})),C(\"NDHWC\"===a,(function(){return\"Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of \"+a})),C(Mo(n,i),(function(){return\"Error in maxPool3d: Either strides or dilations must be 1. Got strides \"+n+\" and dilations '\"+i+\"'\"})),null!=o&&C(A(r),(function(){return\"Error in maxPool3d: pad must be an integer when using, dimRoundingMode \"+o+\" but got pad \"+r+\".\"}));var l=ko(u.shape,e,n,i,r,o,a),h=Lt.runKernelFunc((function(t,e){var n=t.maxPool3d(u,l);return e([u,n]),n}),{x:u},(function(t,a){var s=a[0],u=a[1];return{x:function(){return function(t,e,n,r,o,a,i,s){var u=mn(t,\"dy\",\"maxPool3dBackprop\"),c=mn(e,\"input\",\"maxPool3dBackprop\"),l=mn(n,\"output\",\"maxPool3dBackprop\"),h=u,f=c,d=l,p=!1;4===c.rank&&(p=!0,h=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]),f=c.as5D(1,c.shape[0],c.shape[1],c.shape[2],c.shape[3]),d=l.as5D(1,l.shape[0],l.shape[1],l.shape[2],l.shape[3]));C(5===h.rank,(function(){return\"Error in maxPool3dBackprop: dy must be rank 5 but got rank \"+h.rank+\".\"})),C(5===f.rank,(function(){return\"Error in maxPool3dBackprop: input must be rank 5 but got rank \"+f.rank+\".\"})),C(5===d.rank,(function(){return\"Error in maxPool3dBackprop: output must be rank 5 but got rank \"+d.rank+\".\"})),null==a&&(a=[1,1,1]);C(Mo(o,a),(function(){return\"Error in maxPool3dBackprop: Either strides or dilations must be 1. 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Array(a.rank-n.length).fill(-1)):n).map((function(t,e){return t>=0?t:(C(-1===t,(function(){return\"Negative size values should be exactly -1 but got \"+t+\" for the slice() size at index \"+e+\".\"})),a.shape[e]-r[e])})),eo(a,r,o);var i=a.shape,s={begin:r,size:o};return Lt.runKernelFunc((function(t){return t.slice(a,r,o)}),{x:a},(function(t){for(var e=[],n=0;n<t.rank;n++)e.push([r[n],i[n]-r[n]-o[n]]);return{x:function(){return t.pad(e)}}}),\"Slice\",s)}}),gl=An({slice1d_:function(t,e,n){var r=mn(t,\"x\",\"slice1d\");return C(1===r.rank,(function(){return\"slice1d expects a rank-1 tensor, but got a rank-\"+r.rank+\" tensor\"})),ml(r,[e],[n])}}),yl=An({slice2d_:function(t,e,n){var r=mn(t,\"x\",\"slice2d\");return C(2===r.rank,(function(){return\"slice2d expects a rank-2 tensor, but got a rank-\"+r.rank+\" tensor\"})),ml(r,e,n)}}),xl=An({slice3d_:function(t,e,n){var r=mn(t,\"x\",\"slice3d\");return C(3===r.rank,(function(){return\"slice3d expects a rank-3 tensor, but got a 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t.any(r,a)}),{$x:r});if(n){var u=wn(s.shape,o);return s.reshape(u)}return s}}),Rl=An({argMax_:function(t,e){void 0===e&&(e=0);var n=mn(t,\"x\",\"argMax\");null==e&&(e=0);var r=O(e,n.shape),o=En(r,n.rank);null!=o&&(n=n.transpose(o),r=In(r.length,n.rank));var a={axis:r[0]},i=[n];return Lt.runKernelFunc((function(t,e){var o=t.argMax(n,r[0]);return e([n]),o}),{x:n},(function(t,e){var n=e[0];return{x:function(){return Xn(n)}}}),\"ArgMax\",a,i)}}),Il=An({argMin_:function(t,e){void 0===e&&(e=0);var n=mn(t,\"x\",\"argMin\");null==e&&(e=0);var r=O(e,n.shape),o=En(r,n.rank);return null!=o&&(n=n.transpose(o),r=In(r.length,n.rank)),Lt.runKernelFunc((function(t,e){var o=t.argMin(n,r[0]);return e([n]),o}),{$x:n},(function(t,e){var n=e[0];return{$x:function(){return Xn(n)}}}))}}),kl=An({logSumExp_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=mn(t,\"x\",\"logSumExp\"),o=O(e,r.shape),a=r.max(o,!0),i=r.sub(a).exp().sum(o).log(),s=a.reshape(i.shape).add(i);if(n){var 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r=mn(t,\"x\",\"min\"),o=r,a=O(e,r.shape),i=a,s=En(i,r.rank);null!=s&&(r=r.transpose(s),i=In(i.length,r.rank));var u=[r],c=Lt.runKernelFunc((function(t,e){var n=t.min(r,i);return e([o,n]),n}),{x:r},(function(t,e){return wl(t,e[1],e[0],a,s)}),\"Min\",{axes:i},u,[!0]);if(n){var l=wn(c.shape,a);c=c.reshape(l)}return c}}),Tl=An({moments_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=O(e,(t=mn(t,\"x\",\"moments\")).shape),o=t.mean(r,n),a=o.shape;n||(a=wn(o.shape,r));var i=t.toFloat().sub(o.reshape(a)).square();return{mean:o,variance:i.mean(r,n)}}}),Nl=An({sum_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=mn(t,\"x\",\"sum\");\"bool\"===r.dtype&&(r=r.toInt());var o=O(e,r.shape);return vo((function(t){var e=En(o,t.rank),r=o,a=t;null!=e&&(a=t.transpose(e),r=In(r.length,t.rank));var i=function(e){var n=t.shape.slice();return o.forEach((function(t){n[t]=1})),e.reshape(n).mul(zn(t.shape,\"float32\"))},s={axes:r},u=Lt.runKernelFunc((function(t){return t.sum(a,r)}),{x:a},(function(t){return{x:function(){return i(t)}}}),\"Sum\",s);if(n){var c=wn(u.shape,o);u=u.reshape(c)}return{value:u,gradFunc:i}}))(r)}}),Fl=An({prod_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=mn(t,\"x\",\"prod\");\"bool\"===r.dtype&&(r=r.toInt());var o=O(e,r.shape),a=En(o,r.rank),i=o,s=r;null!=a&&(s=r.transpose(a),i=In(i.length,r.rank));var u=Lt.runKernelFunc((function(t){return t.prod(s,i)}),{permutedX:s});if(n){var c=wn(u.shape,o);u=u.reshape(c)}return u}});var _l=An({elu_:function(t){var e=mn(t,\"x\",\"elu\");return Lt.runKernelFunc((function(t,n){var r=t.elu(e);return n([r]),r}),{$x:e},(function(t,e){var n=e[0];return{$x:function(){return Lt.runKernelFunc((function(e){return e.eluDer(t,n)}),{dy:t,y:n})}}}))}}),Ol=An({leakyRelu_:function(t,e){void 0===e&&(e=.2);var n=mn(t,\"x\",\"leakyRelu\");return hc(On(e).mul(n),n)}}),Ml=An({prelu_:function(t,e){var n=mn(t,\"x\",\"prelu\"),r=mn(e,\"alpha\",\"prelu\");return Lt.runKernelFunc((function(t,e){var o=t.prelu(n,r);return e([n,r]),o}),{x:n,alpha:r},(function(t,e){var n=e[0],r=e[1],o=n.greater(0);return{x:function(){return ec(o,t,t.mul(r))},alpha:function(){var e=ec(o,Xn(t),t.mul(n)),a=Eo(r.shape,t.shape);return a.length>0&&(e=e.sum(a)),e.reshape(r.shape)}}}),\"Prelu\")}}),Bl=An({relu_:function(t){var e=mn(t,\"x\",\"relu\");return\"bool\"===e.dtype?e.toInt():Lt.runKernelFunc((function(t,n){var r=t.relu(e);return n([e]),r}),{x:e},(function(t,e){var n=e[0];return{x:function(){return t.mulStrict(n.step().toFloat())}}}),\"Relu\")}}),Pl=An({relu6_:function(t){var e=mn(t,\"x\",\"relu6\");return\"bool\"===e.dtype?e.toInt():Lt.runKernelFunc((function(t,n){var r=t.relu6(e);return n([e]),r}),{x:e},(function(t,e){var n=e[0],r=n.lessEqual(6).mul(n.step());return{x:function(){return t.mulStrict(r.toFloat())}}}),\"Relu6\")}}),Ll=An({selu_:function(t){var e=mn(t,\"x\",\"selu\");return Lt.runKernelFunc((function(t,n){var r=t.selu(e);return n([e]),r}),{$x:e},(function(t,e){var n=e[0];return{$x:function(){var e=n.greater(On(0)),r=On(bs),o=On(ws),a=t.mul(o),i=t.mul(r).mul(n.toFloat().exp());return ec(e,a,i)}}}))}});var Wl=An({transpose_:function(t,e){var n=mn(t,\"x\",\"transpose\");if(null==e&&(e=n.shape.map((function(t,e){return e})).reverse()),C(n.rank===e.length,(function(){return\"Error in transpose: rank of input \"+n.rank+\" must match length of perm \"+e+\".\"})),e.forEach((function(t){C(t>=0&&t<n.rank,(function(){return\"All entries in 'perm' must be between 0 and \"+(n.rank-1)+\" but got \"+e}))})),n.rank<=1)return n.clone();var r={perm:e};return Lt.runKernelFunc((function(t){return t.transpose(n,e)}),{x:n},(function(t){var n=Rn(e);return{x:function(){return t.transpose(n)}}}),\"Transpose\",r)}});var Ul=An({localResponseNormalization_:function(t,e,n,r,o){void 0===e&&(e=5),void 0===n&&(n=1),void 0===r&&(r=1),void 0===o&&(o=.5);var a=mn(t,\"x\",\"localResponseNormalization\");C(4===a.rank||3===a.rank,(function(){return\"Error in localResponseNormalization: x must be rank 3 or 4 but got\\n               rank \"+a.rank+\".\"})),C(A(e),(function(){return\"Error in localResponseNormalization: depthRadius must be an integer but got depthRadius \"+e+\".\"}));var i=a,s=!1;3===a.rank&&(s=!0,i=a.as4D(1,a.shape[0],a.shape[1],a.shape[2]));var u=Lt.runKernelFunc((function(t,a){var s=t.localResponseNormalization4D(i,e,n,r,o);return a([i,s]),s}),{x4D:i},(function(t,a){var i=a[0],s=a[1];return{x4D:function(){return Lt.runKernelFunc((function(a){return a.LRNGrad(t,i,s,e,n,r,o)}),{})}}}));return s?u.as3D(u.shape[1],u.shape[2],u.shape[3]):u}});var Vl=An({norm_:function(t,e,n,r){void 0===e&&(e=\"euclidean\"),void 0===n&&(n=null),void 0===r&&(r=!1);var o=function t(e,n,r){void 0===r&&(r=null);if(0===e.rank)return e.abs();if(1!==e.rank&&null===r)return t(e.reshape([-1]),n,r);if(1===e.rank||\"number\"==typeof r||Array.isArray(r)&&1===r.length){if(1===n)return e.abs().sum(r);if(n===1/0)return e.abs().max(r);if(n===-1/0)return e.abs().min(r);if(\"euclidean\"===n||2===n)return e.abs().pow(On(2,\"int32\")).sum(r).sqrt();throw new Error(\"Error in norm: invalid ord value: \"+n)}if(Array.isArray(r)&&2===r.length){if(1===n)return e.abs().sum(r[0]).max(r[1]-1);if(n===1/0)return e.abs().sum(r[1]).max(r[0]);if(n===-1/0)return e.abs().sum(r[1]).min(r[0]);if(\"fro\"===n||\"euclidean\"===n)return e.square().sum(r).sqrt();throw new Error(\"Error in norm: invalid ord value: \"+n)}throw new Error(\"Error in norm: invalid axis: \"+r)}(t=mn(t,\"x\",\"norm\"),e,n),a=o.shape;if(r){var i=O(n,t.shape);a=wn(o.shape,i)}return o.reshape(a)}});var zl=An({basicLSTMCell_:function(t,e,n,r,o,a){var 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0===n&&(n=!1);var r=mn(t,\"images\",\"resizeNearestNeighbor\");C(3===r.rank||4===r.rank,(function(){return\"Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank \"+r.rank+\".\"})),C(2===e.length,(function(){return\"Error in resizeNearestNeighbor: new shape must 2D, but got shape \"+e+\".\"})),C(\"float32\"===r.dtype||\"int32\"===r.dtype,(function(){return\"`images` must have `int32` or `float32` as dtype\"}));var o=r,a=!1;3===r.rank&&(a=!0,o=r.as4D(1,r.shape[0],r.shape[1],r.shape[2]));var i=e[0],s=e[1],u=Lt.runKernelFunc((function(t,e){return e([o]),t.resizeNearestNeighbor(o,i,s,n)}),{batchImages:o},(function(t,e){return{batchImages:function(){return Lt.runKernelFunc((function(r){return r.resizeNearestNeighborBackprop(t,e[0],n)}),{})}}}));return a?u.as3D(u.shape[1],u.shape[2],u.shape[3]):u}}),Dh=An({nonMaxSuppression_:function(t,e,n,r,o){void 0===r&&(r=.5),void 0===o&&(o=Number.NEGATIVE_INFINITY);var a=mn(t,\"boxes\",\"nonMaxSuppression\"),i=mn(e,\"scores\",\"nonMaxSuppression\"),s=kh(a,i,n,r,o);n=s.maxOutputSize,r=s.iouThreshold,o=s.scoreThreshold;var u={maxOutputSize:n,iouThreshold:r,scoreThreshold:o};return Lt.runKernelFunc((function(t){return t.nonMaxSuppression(a,i,n,r,o)}),{boxes:a,scores:i},null,\"NonMaxSuppressionV3\",u)}}),Th=function(t,e,o,a,i){return void 0===a&&(a=.5),void 0===i&&(i=Number.NEGATIVE_INFINITY),n(this,void 0,void 0,(function(){var n,s,u,c,l,h,f;return r(this,(function(r){switch(r.label){case 0:return n=mn(t,\"boxes\",\"nonMaxSuppressionAsync\"),s=mn(e,\"scores\",\"nonMaxSuppressionAsync\"),u=kh(n,s,o,a,i),o=u.maxOutputSize,a=u.iouThreshold,i=u.scoreThreshold,[4,Promise.all([n.data(),s.data()])];case 1:return c=r.sent(),l=c[0],h=c[1],f=jo(l,h,o,a,i),n!==t&&n.dispose(),s!==e&&s.dispose(),[2,f]}}))}))},Nh=An({nonMaxSuppressionWithScore_:function(t,e,n,r,o,a){void 0===r&&(r=.5),void 0===o&&(o=Number.NEGATIVE_INFINITY),void 0===a&&(a=0);var i=mn(t,\"boxes\",\"nonMaxSuppression\"),s=mn(e,\"scores\",\"nonMaxSuppression\"),u=kh(i,s,n,r,o,a),c={maxOutputSize:n=u.maxOutputSize,iouThreshold:r=u.iouThreshold,scoreThreshold:o=u.scoreThreshold,softNmsSigma:a=u.softNmsSigma},l=Lt.runKernel(\"NonMaxSuppressionV5\",{boxes:i,scores:s},c);return{selectedIndices:l[0],selectedScores:l[1]}}}),Fh=function(t,e,o,a,i,s){return void 0===a&&(a=.5),void 0===i&&(i=Number.NEGATIVE_INFINITY),void 0===s&&(s=0),n(this,void 0,void 0,(function(){var n,u,c,l,h,f,d;return r(this,(function(r){switch(r.label){case 0:return n=mn(t,\"boxes\",\"nonMaxSuppressionAsync\"),u=mn(e,\"scores\",\"nonMaxSuppressionAsync\"),c=kh(n,u,o,a,i,s),o=c.maxOutputSize,a=c.iouThreshold,i=c.scoreThreshold,s=c.softNmsSigma,[4,Promise.all([n.data(),u.data()])];case 1:return l=r.sent(),h=l[0],f=l[1],d=Xo(h,f,o,a,i,s),n!==t&&n.dispose(),u!==e&&u.dispose(),[2,d]}}))}))},_h=An({cropAndResize_:function(t,e,n,r,o,a){var i=mn(t,\"image\",\"cropAndResize\"),s=mn(e,\"boxes\",\"cropAndResize\",\"float32\"),u=mn(n,\"boxInd\",\"cropAndResize\",\"int32\");o=o||\"bilinear\",a=a||0;var c=s.shape[0];return C(4===i.rank,(function(){return\"Error in cropAndResize: image must be rank 4,but got rank \"+i.rank+\".\"})),C(2===s.rank&&4===s.shape[1],(function(){return\"Error in cropAndResize: boxes must be have size [\"+c+\",4] but had shape \"+s.shape+\".\"})),C(1===u.rank&&u.shape[0]===c,(function(){return\"Error in cropAndResize: boxInd must be have size [\"+c+\"] but had shape \"+s.shape+\".\"})),C(2===r.length,(function(){return\"Error in cropAndResize: cropSize must be of length 2, but got length \"+r.length+\".\"})),C(r[0]>=1&&r[1]>=1,(function(){return\"cropSize must be atleast [1,1], but was \"+r})),C(\"bilinear\"===o||\"nearest\"===o,(function(){return\"method must be bilinear or nearest, but was \"+o})),Lt.runKernelFunc((function(t,e){return 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and transposeB=\"+s+\" must match.\"}));var R,I,A=d.shape.slice(0,-2).concat([g,y]),D=a?d.as3D(w,v,g):d.as3D(w,g,v),T=s?p.as3D(E,y,m):p.as3D(E,m,y);null!=u&&Ro(A,(R=Nt(R=mn(u,\"bias\",\"fused matMul\"),d)[0]).shape),null!=h&&(I=mn(h,\"prelu weights\",\"fused matMul\"));var N={a:D,b:T};null!=u&&(N.bias=R),null!=h&&(N.preluActivationWeights=I);var F=[D,T];return Lt.runKernelFunc((function(t,e){var n=t.fusedBatchMatMul({a:D,b:T,transposeA:a,transposeB:s,bias:R,activation:l,preluActivationWeights:I});return e([D,T,n]),n}),N,(function(t,e){var n=e[0],r=e[1],o=e[2],i=Bh(t,o,l),c={};return null!=u&&(c={bias:function(){return Ph(R,i)}}),a||s?!a&&s?Object.assign({a:function(){return i.matMul(r,!1,!1)},b:function(){return i.matMul(n,!0,!1)}},c):a&&!s?Object.assign({a:function(){return r.matMul(i,!1,!0)},b:function(){return n.matMul(i,!1,!1)}},c):Object.assign({a:function(){return r.matMul(i,!0,!0)},b:function(){return i.matMul(n,!0,!0)}},c):Object.assign({a:function(){return 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\"+o+\".\"})),C(g.shape[3]===m.shape[2],(function(){return\"Error in conv2d: depth of input (\"+g.shape[3]+\") must match input depth for filter \"+m.shape[2]+\".\"})),C(Mo(r,u),(function(){return\"Error in conv2D: Either strides or dilations must be 1. 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Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. 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Due to automatic garbage collection, the true allocated memory may be less.\"]}},o.prototype.complex=function(t,e){var n=this.makeOutput(null,t.shape,\"complex64\");return this.data.get(n.dataId).complexTensors={real:Lt.keep(t.clone()),imag:Lt.keep(e.clone())},n},o.prototype.real=function(t){return this.data.get(t.dataId).complexTensors.real.clone()},o.prototype.imag=function(t){return this.data.get(t.dataId).complexTensors.imag.clone()},o.prototype.slice=function(t,e,n){if(Hh(t,\"slice\"),io(t.shape,e,n)){var r=so(e,t.strides),o=k(n);return Fn(this.readSync(t.dataId).subarray(r,r+o),n,t.dtype)}for(var a=dr(n,t.dtype),i=this.bufferSync(t),s=0;s<a.size;++s){var u=a.indexToLoc(s).map((function(t,n){return t+e[n]}));a.values[s]=i.get.apply(i,u)}return a.toTensor()},o.prototype.stridedSlice=function(t,e,n,r){Hh(t,\"stridedSlice\");var o=ro(e,n,r);if(o.some((function(t){return 0===t})))return Fn([],o);for(var a=dr(o,t.dtype),i=this.bufferSync(t),s=0;s<a.size;s++){for(var u=a.indexToLoc(s),c=new Array(u.length),l=0;l<c.length;l++)c[l]=u[l]*r[l]+e[l];a.set.apply(a,[i.get.apply(i,c)].concat(u))}return a.toTensor()},o.prototype.diag=function(t){for(var e=this.readSync(t.dataId),n=dr([t.size,t.size],t.dtype),r=n.values,o=0;o<e.length;o++)r[o*t.size+o]=e[o];return n.toTensor()},o.prototype.unstack=function(t,e){for(var n=t.shape[e],r=new Array(t.rank-1),o=0,a=0;a<t.rank;a++)a!==e&&(r[o++]=t.shape[a]);var i=new Array(t.rank).fill(0),s=t.shape.slice();s[e]=1;var u=new Array(n);for(a=0;a<u.length;a++)i[e]=a,u[a]=this.slice(t,i,s).reshape(r);return u},o.prototype.reverse=function(t,e){Hh(t,\"reverse\");for(var n=dr(t.shape,t.dtype),r=this.bufferSync(t),o=function(o){var a=n.indexToLoc(o),i=a.slice();e.forEach((function(e){return i[e]=t.shape[e]-1-i[e]})),n.set.apply(n,[r.get.apply(r,i)].concat(a))},a=0;a<n.size;a++)o(a);return n.toTensor()},o.prototype.concat=function(t,e){var n=this;if(\"complex64\"===t[0].dtype){var r=t.map((function(t){return Tn(t)})),o=t.map((function(t){return Nn(t)}));return Dn(this.concat(r,e),this.concat(o,e))}var a=t.map((function(t){var n=k(t.shape.slice(e));return t.as2D(-1,n)})),i=Sn(a.map((function(t){return t.shape})),1),s=dr(i,t[0].dtype).values;if(1===a[0].shape[0]){var u=0;a.forEach((function(t){s.set(n.readSync(t.dataId),u),u+=t.size}))}else{var c=0;a.forEach((function(t){for(var e=n.readSync(t.dataId),r=0,o=0;o<t.shape[0];++o)for(var a=o*i[1]+c,u=0;u<t.shape[1];++u)s[a+u]=e[r++];c+=t.shape[1]}))}var l=Sn(t.map((function(t){return t.shape})),e);return Fn(s,l,t[0].dtype)},o.prototype.neg=function(t){return Hh(t,\"neg\"),this.multiply(On(-1),t)},o.prototype.add=function(t,e){return\"complex64\"===t.dtype||\"complex64\"===e.dtype?this.broadcastedBinaryComplexOp(t.cast(\"complex64\"),e.cast(\"complex64\"),(function(t,e,n,r){return{real:t+n,imag:e+r}})):this.broadcastedBinaryOp(t,e,Dt(t.dtype,e.dtype),(function(t,e){return t+e}))},o.prototype.addN=function(t){var e=this;Hh(t,\"addN\");for(var n=t.map((function(t){return e.readSync(t.dataId)})),r=dr(t[0].shape,t[0].dtype),o=r.values,a=0;a<t.length;a++)for(var i=n[a],s=0;s<o.length;s++)o[s]+=i[s];return r.toTensor()},o.prototype.softmax=function(t,e){var n=O([e],t.shape),r=this.max(t,n),o=wn(r.shape,n),a=this.subtract(t,r.reshape(o)),i=this.exp(a),s=this.sum(i,n).reshape(o);return this.realDivide(i,s)},o.prototype.subtract=function(t,e){return\"complex64\"===t.dtype||\"complex64\"===e.dtype?this.broadcastedBinaryComplexOp(t.cast(\"complex64\"),e.cast(\"complex64\"),(function(t,e,n,r){return{real:t-n,imag:e-r}})):this.broadcastedBinaryOp(t,e,Dt(t.dtype,e.dtype),(function(t,e){return t-e}))},o.prototype.pow=function(t,e){return Hh([t,e],\"pow\"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return Math.pow(t,e)}))},o.prototype.batchMatMul=function(t,e,n,r){Hh([t,e],\"matMul\");for(var o=n?t.shape[1]:t.shape[2],a=n?t.shape[2]:t.shape[1],i=r?e.shape[1]:e.shape[2],s=t.shape[0],u=this.readSync(t.dataId),c=this.readSync(e.dataId),l=n?[t.strides[0],1,t.strides[1]]:[t.strides[0],t.strides[1],1],h=l[0],f=l[1],d=l[2],p=r?[1,e.strides[1],e.strides[0]]:[e.strides[1],1,e.strides[0]],v=p[0],m=p[1],g=p[2],y=a*i,x=dr([s,a,i],t.dtype),b=x.values,w=this.blockSize,C=0;C<s;C++)for(var E=0;E<a;E+=w)for(var R=0;R<i;R+=w)for(var I=0;I<o;I+=w)for(var k=Math.min(E+w,a),S=Math.min(R+w,i),A=Math.min(I+w,o),D=E;D<k;D++)for(var T=R;T<S;T++){for(var N=0,F=I;F<A;F++)N+=u[C*h+D*f+F*d]*c[F*v+T*m+C*g];b[C*y+(D*i+T)]+=N}return x.toTensor()},o.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,a=t.bias,i=t.activation,s=t.preluActivationWeights,u=this.batchMatMul(e,n,r,o);return a&&(u=this.add(u,a)),i&&(u=qh(this,u,i,s)),u},o.prototype.multiply=function(t,e){return\"complex64\"===t.dtype||\"complex64\"===e.dtype?this.broadcastedBinaryComplexOp(t.cast(\"complex64\"),e.cast(\"complex64\"),(function(t,e,n,r){return{real:t*n-e*r,imag:t*r+e*n}})):this.broadcastedBinaryOp(t,e,Dt(t.dtype,e.dtype),(function(t,e){return t*e}))},o.prototype.realDivide=function(t,e){Hh([t,e],\"realDivide\");return this.broadcastedBinaryOp(t,e,\"float32\",(function(t,e){return t/e}))},o.prototype.floorDiv=function(t,e){Hh([t,e],\"floorDiv\");return this.broadcastedBinaryOp(t,e,\"int32\",(function(t,e){return Math.floor(t/e)}))},o.prototype.sum=function(t,e){Hh(t,\"sum\"),Cn(\"sum\",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,Dt(t.dtype,\"int32\")),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=0,f=0;f<i;++f)h+=u[l+f];s[c]=h}return a},o.prototype.prod=function(t,e){Hh(t,\"sum\");for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,Dt(t.dtype,\"int32\")),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=1,f=0;f<i;++f)h*=u[l+f];s[c]=h}return a},o.prototype.unsortedSegmentSum=function(t,e,n){Hh(t,\"unsortedSegmentSum\");for(var r=[],o=t.rank-e.rank,a=0;a<o;++a)e=e.expandDims(a+1);for(a=0;a<n;++a){var i=On(a,\"int32\"),s=Rc(i,e).asType(\"float32\").mul(t).sum(0);r.push(s)}return Pr(r)},o.prototype.argMin=function(t,e){Hh(t,\"argMin\");var n=[e];Cn(\"argMin\",n,t.rank);for(var r=bn(t.shape,n),o=r[0],a=r[1],i=Gn(o,\"int32\"),s=k(a),u=this.readSync(i.dataId),c=this.readSync(t.dataId),l=0;l<u.length;++l){for(var h=l*s,f=c[h],d=0,p=0;p<s;++p){var v=c[h+p];v<f&&(f=v,d=p)}u[l]=d}return i},o.prototype.argMax=function(t,e){Hh(t,\"argMax\");var n=[e];Cn(\"argMax\",n,t.rank);for(var r=bn(t.shape,n),o=r[0],a=r[1],i=Gn(o,\"int32\"),s=k(a),u=this.readSync(i.dataId),c=this.readSync(t.dataId),l=0;l<u.length;++l){for(var h=l*s,f=c[h],d=0,p=0;p<s;++p){var v=c[h+p];v>f&&(f=v,d=p)}u[l]=d}return i},o.prototype.cumsum=function(t,e,n,r){if(Hh(t,\"cumsum\"),e!==t.rank-1)throw new Error(\"backend.cumsum in CPU expects an inner-most axis=\"+(t.rank-1)+\" but got axis=\"+e);for(var o=Dt(t.dtype,\"int32\"),a=Gn(t.shape,o),i=this.readSync(a.dataId),s=this.readSync(t.dataId),u=t.shape[t.rank-1],c=r?function(t,e){return t+u-e-1}:function(t,e){return t+e},l=0;l<s.length;l+=u)for(var h=0;h<u;h++){var f=c(l,h);if(0===h)i[f]=n?0:s[f];else{var d=c(l,h-1);i[f]=n?s[d]+i[d]:s[f]+i[d]}}return a},o.prototype.equal=function(t,e){return Hh([t,e],\"equal\"),this.broadcastedBinaryOp(t,e,\"bool\",(function(t,e){return t===e?1:0}))},o.prototype.notEqual=function(t,e){return Hh([t,e],\"notEqual\"),this.broadcastedBinaryOp(t,e,\"bool\",(function(t,e){return t!==e?1:0}))},o.prototype.less=function(t,e){return Hh([t,e],\"less\"),this.broadcastedBinaryOp(t,e,\"bool\",(function(t,e){return t<e?1:0}))},o.prototype.lessEqual=function(t,e){return Hh([t,e],\"lessEqual\"),this.broadcastedBinaryOp(t,e,\"bool\",(function(t,e){return t<=e?1:0}))},o.prototype.greater=function(t,e){return Hh([t,e],\"greater\"),this.broadcastedBinaryOp(t,e,\"bool\",(function(t,e){return t>e?1:0}))},o.prototype.greaterEqual=function(t,e){return Hh([t,e],\"greaterEqual\"),this.broadcastedBinaryOp(t,e,\"bool\",(function(t,e){return t>=e?1:0}))},o.prototype.logicalNot=function(t){Hh(t,\"logicalNot\");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)n[r]=e[r]?0:1;return this.makeOutput(n,t.shape,\"bool\")},o.prototype.logicalAnd=function(t,e){return Hh([t,e],\"logicalAnd\"),this.broadcastedBinaryOp(t,e,\"bool\",(function(t,e){return t&&e}))},o.prototype.logicalOr=function(t,e){return Hh([t,e],\"logicalOr\"),this.broadcastedBinaryOp(t,e,\"bool\",(function(t,e){return t||e}))},o.prototype.select=function(t,e,n){Hh([t,e,n],\"select\");for(var r=this.readSync(t.dataId),o=this.readSync(e.dataId),a=this.readSync(n.dataId),i=Gn(e.shape,Dt(e.dtype,n.dtype)),s=this.readSync(i.dataId),u=0,c=0===t.rank||t.rank>1||1===e.rank?1:k(e.shape.slice(1)),l=0;l<r.length;l++)for(var h=0;h<c;h++)1===r[l]?s[u++]=o[l]:s[u++]=a[l];return i},o.prototype.where=function(t){Hh([t],\"where\");var e=this.readSync(t.dataId);return na(t.shape,e)},o.prototype.topk=function(t,e,n){return Hh(t,\"topk\"),ea(this.readSync(t.dataId),t.shape,t.dtype,e)},o.prototype.min=function(t,e){Hh(t,\"min\"),Cn(\"min\",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,t.dtype),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=u[l],f=0;f<i;++f){var d=u[l+f];d<h&&(h=d)}s[c]=h}return a},o.prototype.minimum=function(t,e){return Hh([t,e],\"minimum\"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return Math.min(t,e)}))},o.prototype.mod=function(t,e){return Hh([t,e],\"mod\"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){var n=t%e;return t<0&&e<0||t>=0&&e>=0?n:(n+e)%e}))},o.prototype.max=function(t,e){Hh(t,\"max\"),Cn(\"max\",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,t.dtype),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=u[l],f=0;f<i;++f){var d=u[l+f];d>h&&(h=d)}s[c]=h}return a},o.prototype.maximum=function(t,e){return Hh([t,e],\"maximum\"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return Math.max(t,e)}))},o.prototype.all=function(t,e){Hh(t,\"all\"),Cn(\"all\",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,t.dtype),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=u[l],f=0;f<i;++f){var d=u[l+f];h=h&&d}s[c]=h}return a},o.prototype.any=function(t,e){Hh(t,\"any\"),Cn(\"any\",e,t.rank);for(var n=bn(t.shape,e),r=n[0],o=n[1],a=Gn(r,t.dtype),i=k(o),s=this.readSync(a.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*i,h=u[l],f=0;f<i;++f){var d=u[l+f];h=h||d}s[c]=h}return a},o.prototype.squaredDifference=function(t,e){return Hh([t,e],\"squaredDifference\"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){var n=t-e;return n*n}))},o.prototype.ceil=function(t){Hh(t,\"ceil\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.ceil(e[r]);return this.makeOutput(n,t.shape,\"float32\")},o.prototype.floor=function(t){Hh(t,\"floor\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.floor(e[r]);return this.makeOutput(n,t.shape,\"float32\")},o.prototype.sign=function(t){Hh(t,\"x\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)e[r]<0?n[r]=-1:e[r]>0?n[r]=1:n[r]=0;return this.makeOutput(n,t.shape,\"float32\")},o.prototype.isNaN=function(t){Hh(t,\"x\");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isNaN(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,\"bool\")},o.prototype.isInf=function(t){Hh(t,\"x\");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Math.abs(e[r])===1/0&&(n[r]=1);return this.makeOutput(n,t.shape,\"bool\")},o.prototype.isFinite=function(t){Hh(t,\"x\");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isFinite(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,\"bool\")},o.prototype.round=function(t){Hh(t,\"round\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=Math.floor(e[r]);e[r]-o<.5?n[r]=Math.floor(e[r]):e[r]-o>.5?n[r]=Math.ceil(e[r]):n[r]=o%2==0?o:o+1}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.exp=function(t){Hh(t,\"exp\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.exp(e[r]);return this.makeOutput(n,t.shape,\"float32\")},o.prototype.expm1=function(t){Hh(t,\"expm1\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.expm1(e[r]);return this.makeOutput(n,t.shape,\"float32\")},o.prototype.log=function(t){Hh(t,\"log\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log(o)}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.log1p=function(t){Hh(t,\"log1p\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log1p(o)}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.sqrt=function(t){Hh(t,\"sqrt\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.sqrt(o)}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.rsqrt=function(t){Hh(t,\"rsqrt\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=1/Math.sqrt(o)}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.reciprocal=function(t){Hh(t,\"reciprocal\");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=1/e[r];return this.makeOutput(n,t.shape,\"float32\")},o.prototype.linear=function(t){return t},o.prototype.relu=function(t){Hh(t,\"relu\");for(var e=Gn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.max(0,r[o]);return e},o.prototype.relu6=function(t){Hh(t,\"relu\");for(var e=Gn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.min(Math.max(0,r[o]),6);return e},o.prototype.prelu=function(t,e){return Hh([t,e],\"prelu\"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return t<0?e*t:t}))},o.prototype.elu=function(t){Hh(t,\"elu\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=n[r];e[r]=o>=0?o:Math.exp(o)-1}return this.makeOutput(e,t.shape,\"float32\")},o.prototype.eluDer=function(t,e){Hh([t,e],\"eluDer\");for(var n=new Float32Array(e.size),r=this.readSync(e.dataId),o=this.readSync(t.dataId),a=0;a<r.length;++a){var i=r[a];n[a]=i>=1?o[a]:o[a]*(i+1)}return this.makeOutput(n,e.shape,\"float32\")},o.prototype.selu=function(t){Hh(t,\"selu\");for(var e=bs,n=ws,r=new Float32Array(t.size),o=this.readSync(t.dataId),a=0;a<o.length;++a){var i=o[a];r[a]=i>=0?n*i:e*(Math.exp(i)-1)}return this.makeOutput(r,t.shape,\"float32\")},o.prototype.clip=function(t,e,n){Hh(t,\"clip\");for(var r=new Float32Array(t.size),o=this.readSync(t.dataId),a=0;a<o.length;++a){var i=o[a];r[a]=i>n?n:i<e?e:i}return this.makeOutput(r,t.shape,\"float32\")},o.prototype.abs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.abs(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.complexAbs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<t.size;++r){var o=n[2*r],a=n[2*r+1];e[r]=Math.hypot(o,a)}return this.makeOutput(e,t.shape,\"float32\")},o.prototype.int=function(t){Hh(t,\"int\");for(var e=new Int32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=n[r];return this.makeOutput(e,t.shape,\"int32\")},o.prototype.sigmoid=function(t){Hh(t,\"sigmoid\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=1/(1+Math.exp(-n[r]));return this.makeOutput(e,t.shape,\"float32\")},o.prototype.softplus=function(t){Hh(t,\"softplus\");for(var e=Math.log(1.1920928955078125e-7)+2,n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var a=r[o]>-e,i=r[o]<e,s=Math.exp(r[o]),u=void 0;u=i?s:a?r[o]:Math.log(1+s),n[o]=u}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.sin=function(t){Hh(t,\"sin\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sin(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.cos=function(t){Hh(t,\"cos\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cos(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.tan=function(t){Hh(t,\"tan\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.tan(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.asin=function(t){Hh(t,\"asin\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asin(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.acos=function(t){Hh(t,\"acos\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acos(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.atan=function(t){Hh(t,\"atan\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atan(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.atan2=function(t,e){return Hh([t,e],\"atan2\"),this.broadcastedBinaryOp(t,e,t.dtype,(function(t,e){return Math.atan2(t,e)}))},o.prototype.sinh=function(t){Hh(t,\"sinh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sinh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.cosh=function(t){Hh(t,\"cosh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cosh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.tanh=function(t){Hh(t,\"tanh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=D(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.asinh=function(t){Hh(t,\"asinh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asinh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.acosh=function(t){Hh(t,\"acosh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acosh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.atanh=function(t){Hh(t,\"atanh\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atanh(n[r]);return this.makeOutput(e,t.shape,\"float32\")},o.prototype.erf=function(t){Hh(t,\"erf\");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=Math.sign(n[r]),a=Math.abs(n[r]),i=1/(1+.3275911*a);e[r]=o*(1-((((1.061405429*i-1.453152027)*i+1.421413741)*i-.284496736)*i+.254829592)*i*Math.exp(-a*a))}return this.makeOutput(e,t.shape,\"float32\")},o.prototype.step=function(t,e){void 0===e&&(e=0),Hh(t,\"step\");for(var n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var a=r[o];isNaN(a)?n[o]=NaN:n[o]=a>0?1:e}return this.makeOutput(n,t.shape,\"float32\")},o.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,i=t.preluActivationWeights,s=this.conv2d(e,n,r);return o&&(s=this.add(s,o)),a&&(s=qh(this,s,a,i)),s},o.prototype.conv2d=function(t,e,n){Hh([t,e],\"conv2d\");for(var r=n.filterHeight,o=n.filterWidth,a=n.dilationHeight,i=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,c=\"channelsLast\"===n.dataFormat,l=dr(n.outShape,t.dtype),h=t.strides[0],f=c?t.strides[1]:t.strides[2],d=c?t.strides[2]:1,p=c?1:t.strides[1],v=l.strides[0],m=c?l.strides[1]:l.strides[2],g=c?l.strides[2]:1,y=c?1:l.strides[1],x=this.readSync(t.dataId),b=this.readSync(e.dataId),w=l.values,C=0;C<n.batchSize;++C)for(var E=C*h,R=C*v,I=0;I<n.outHeight;++I)for(var k=R+I*m,S=I*n.strideHeight-u,A=0;A<r;A++){var D=S+A*a;if(!(D<0||D>=n.inHeight))for(var T=A*e.strides[0],N=E+D*f,F=0;F<n.outWidth;++F)for(var _=k+F*g,O=F*n.strideWidth-s,M=0;M<o;M++){var B=O+M*i;if(!(B<0||B>=n.inWidth))for(var P=N+B*d,L=T+M*e.strides[1],W=0;W<n.inChannels;++W){for(var U=x[P+W*p],V=0;V<n.outChannels;++V)w[_+V*y]+=U*b[L+V];L+=n.outChannels}}}return l.toTensor()},o.prototype.conv3d=function(t,e,n){for(var r=n.filterDepth,o=n.filterHeight,a=n.filterWidth,i=n.dilationDepth,s=n.dilationHeight,u=n.dilationWidth,c=n.padInfo.front,l=n.padInfo.left,h=n.padInfo.top,f=dr(n.outShape,t.dtype),d=this.readSync(t.dataId),p=this.readSync(e.dataId),v=f.values,m=0;m<n.batchSize;++m)for(var g=m*t.strides[0],y=m*f.strides[0],x=0;x<n.outDepth;++x)for(var b=y+x*f.strides[1],w=x*n.strideDepth-c,C=0;C<r;C++){var E=w+C*i;if(!(E<0||E>=n.inDepth))for(var R=C*e.strides[0],I=g+E*t.strides[1],k=0;k<n.outHeight;++k)for(var S=b+k*f.strides[2],A=k*n.strideHeight-h,D=0;D<o;D++){var T=A+D*s;if(!(T<0||T>=n.inHeight))for(var N=R+D*e.strides[1],F=I+T*t.strides[2],_=0;_<n.outWidth;++_)for(var O=S+_*n.outChannels,M=_*n.strideWidth-l,B=0;B<a;B++){var P=M+B*u;if(!(P<0||P>=n.inWidth))for(var L=N+B*e.strides[2],W=F+P*n.inChannels,U=L,V=0;V<n.inChannels;++V){for(var z=d[W+V],G=0;G<n.outChannels;++G)v[O+G]+=z*p[U+G];U+=n.outChannels}}}}return f.toTensor()},o.prototype.conv2dDerInput=function(t,e,n){Hh([t,e],\"conv2dDerInput\");for(var r=dr(n.inShape,\"float32\"),o=r.values,a=this.readSync(t.dataId),i=this.readSync(e.dataId),s=e.strides,u=s[0],c=s[1],l=s[2],h=n.batchSize,f=n.filterHeight,d=n.filterWidth,p=n.inChannels,v=n.inHeight,m=n.inWidth,g=n.outChannels,y=n.outHeight,x=n.outWidth,b=n.strideHeight,w=n.strideWidth,C=n.dataFormat,E=f-1-n.padInfo.top,R=d-1-n.padInfo.left,I=\"channelsLast\"===C,k=r.strides[0],S=I?r.strides[1]:r.strides[2],A=I?r.strides[2]:1,D=I?1:r.strides[1],T=t.strides[0],N=I?t.strides[1]:t.strides[2],F=I?t.strides[2]:1,_=I?1:t.strides[1],O=0;O<h;++O)for(var M=0;M<p;++M)for(var B=0;B<v;++B)for(var P=B-E,L=Math.max(0,Math.ceil(P/b)),W=Math.min(y,(f+P)/b),U=0;U<m;++U){for(var V=U-R,z=Math.max(0,Math.ceil(V/w)),G=Math.min(x,(d+V)/w),H=0,q=L;q<W;++q)for(var K=q*b-P,j=z;j<G;++j)for(var X=T*O+N*q+F*j,Y=u*(f-1-K)+c*(d-1-(j*w-V))+l*M,$=0;$<g;++$){H+=a[X+_*$]*i[Y+$]}o[k*O+S*B+A*U+D*M]=H}return r.toTensor()},o.prototype.conv3dDerInput=function(t,e,n){for(var r=dr(n.inShape,\"float32\"),o=r.values,a=r.strides,i=a[0],s=a[1],u=a[2],c=a[3],l=this.readSync(t.dataId),h=t.strides,f=h[0],d=h[1],p=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=n.batchSize,E=n.filterDepth,R=n.filterHeight,I=n.filterWidth,k=n.inChannels,S=n.inDepth,A=n.inHeight,D=n.inWidth,T=n.outChannels,N=n.outDepth,F=n.outHeight,_=n.outWidth,O=n.strideDepth,M=n.strideHeight,B=n.strideWidth,P=E-1-n.padInfo.front,L=R-1-n.padInfo.top,W=I-1-n.padInfo.left,U=0;U<C;++U)for(var V=0;V<k;++V)for(var z=0;z<S;++z)for(var G=z-P,H=Math.max(0,Math.ceil(G/O)),q=Math.min(N,(E+G)/O),K=0;K<A;++K)for(var j=K-L,X=Math.max(0,Math.ceil(j/M)),Y=Math.min(F,(R+j)/M),$=0;$<D;++$){for(var Q=$-W,J=Math.max(0,Math.ceil(Q/B)),Z=Math.min(_,(I+Q)/B),tt=0,et=H;et<q;++et)for(var nt=et*O-G,rt=X;rt<Y;++rt)for(var ot=rt*M-j,at=J;at<Z;++at)for(var it=f*U+d*et+p*rt+v*at,st=y*(E-1-nt)+x*(R-1-ot)+b*(I-1-(at*B-Q))+w*V,ut=0;ut<T;++ut){tt+=l[it+ut]*m[st+ut]}o[i*U+s*z+u*K+c*$+V]=tt}return r.toTensor()},o.prototype.conv2dDerFilter=function(t,e,n){Hh([t,e],\"conv2dDerFilter\");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,s=\"channelsLast\"===n.dataFormat,u=dr(n.filterShape,\"float32\"),c=n.padInfo.left,l=n.padInfo.top,h=this.bufferSync(t),f=this.bufferSync(e),d=0;d<a;++d)for(var p=Math.max(0,Math.ceil((l-d)/r)),v=Math.min(n.outHeight,(n.inHeight+l-d)/r),m=0;m<i;++m)for(var g=Math.max(0,Math.ceil((c-m)/o)),y=Math.min(n.outWidth,(n.inWidth+c-m)/o),x=0;x<n.inChannels;++x)for(var b=0;b<n.outChannels;++b){for(var w=0,C=0;C<n.batchSize;++C)for(var E=p;E<v;++E)for(var R=d+E*r-l,I=g;I<y;++I){var k=m+I*o-c;w+=s?h.get(C,R,k,x)*f.get(C,E,I,b):h.get(C,x,R,k)*f.get(C,b,E,I)}u.set(w,d,m,x,b)}return u.toTensor()},o.prototype.conv3dDerFilter=function(t,e,n){for(var r=n.strideDepth,o=n.strideHeight,a=n.strideWidth,i=n.filterDepth,s=n.filterHeight,u=n.filterWidth,c=dr(n.filterShape,\"float32\"),l=c.values,h=c.strides,f=h[0],d=h[1],p=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=this.readSync(t.dataId),E=t.strides,R=E[0],I=E[1],k=E[2],S=E[3],A=n.padInfo.front,D=n.padInfo.left,T=n.padInfo.top,N=0;N<i;++N)for(var F=Math.max(0,Math.ceil((A-N)/r)),_=Math.min(n.outDepth,(n.inDepth+A-N)/r),O=N*f,M=0;M<s;++M)for(var B=Math.max(0,Math.ceil((T-M)/o)),P=Math.min(n.outHeight,(n.inHeight+T-M)/o),L=M*d+O,W=0;W<u;++W)for(var U=Math.max(0,Math.ceil((D-W)/a)),V=Math.min(n.outWidth,(n.inWidth+D-W)/a),z=W*p+L,G=0;G<n.inChannels;++G)for(var H=G*v+z,q=0;q<n.outChannels;++q){for(var K=0,j=0;j<n.batchSize;++j)for(var X=j*R,Y=j*y,$=F;$<_;++$)for(var Q=(N+$*r-A)*I+X,J=$*x+Y,Z=B;Z<P;++Z)for(var tt=(M+Z*o-T)*k+Q,et=Z*b+J,nt=U;nt<V;++nt){var rt=nt*w+et;K+=C[(W+nt*a-D)*S+tt+G]*m[rt+q]}l[H+q]=K}return c.toTensor()},o.prototype.fusedDepthwiseConv2D=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,a=t.activation,i=t.preluActivationWeights,s=this.depthwiseConv2D(e,n,r);return o&&(s=this.add(s,o)),a&&(s=qh(this,s,a,i)),s},o.prototype.depthwiseConv2D=function(t,e,n){Hh([t,e],\"depthwiseConv2D\");for(var r=n.filterHeight,o=n.filterWidth,a=n.dilationHeight,i=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,c=n.outChannels/n.inChannels,l=dr(n.outShape,t.dtype),h=this.readSync(t.dataId),f=this.readSync(e.dataId),d=l.values,p=0;p<n.batchSize;++p)for(var v=p*t.strides[0],m=p*l.strides[0],g=0;g<n.outHeight;++g)for(var y=m+g*l.strides[1],x=g*n.strideHeight-s,b=0;b<r;++b){var w=x+b*a;if(!(w<0||w>=n.inHeight))for(var C=b*e.strides[0],E=v+w*t.strides[1],R=0;R<n.outWidth;++R)for(var I=y+R*l.strides[2],k=R*n.strideWidth-u,S=0;S<o;++S){var A=k+S*i;if(!(A<0||A>=n.inWidth))for(var D=C+S*e.strides[1],T=E+A*n.inChannels,N=I,F=D,_=0;_<n.inChannels;++_){for(var O=h[T+_],M=0;M<c;++M)d[N+M]+=O*f[F+M];N+=c,F+=c}}}return l.toTensor()},o.prototype.depthwiseConv2DDerInput=function(t,e,n){Hh([t,e],\"depthwiseConv2DDerInput\");for(var r=dr(n.inShape,\"float32\"),o=r.values,a=r.strides,i=a[0],s=a[1],u=a[2],c=this.readSync(t.dataId),l=t.strides,h=l[0],f=l[1],d=l[2],p=this.readSync(e.dataId),v=e.strides,m=v[0],g=v[1],y=v[2],x=n.batchSize,b=n.filterHeight,w=n.filterWidth,C=n.inChannels,E=n.inHeight,R=n.inWidth,I=n.outChannels,k=n.outHeight,S=n.outWidth,A=n.strideHeight,D=n.strideWidth,T=b-1-n.padInfo.top,N=w-1-n.padInfo.left,F=I/C,_=0;_<x;++_)for(var O=0;O<C;++O)for(var M=0;M<E;++M)for(var B=M-T,P=Math.max(0,Math.ceil(B/A)),L=Math.min(k,(b+B)/A),W=0;W<R;++W){for(var U=W-N,V=Math.max(0,Math.ceil(U/D)),z=Math.min(S,(w+U)/D),G=0,H=P;H<L;++H)for(var q=H*A-B,K=V;K<z;++K)for(var j=h*_+f*H+d*K,X=m*(b-1-q)+g*(w-1-(K*D-U))+y*O,Y=0;Y<F;++Y){G+=c[j+(O*F+Y)]*p[X+Y]}o[i*_+s*M+u*W+O]=G}return r.toTensor()},o.prototype.depthwiseConv2DDerFilter=function(t,e,n){Hh([t,e],\"depthwiseConv2DDerFilter\");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,s=dr(n.filterShape,\"float32\"),u=n.padInfo.left,c=n.padInfo.top,l=n.outChannels/n.inChannels,h=this.bufferSync(t),f=this.bufferSync(e),d=0;d<a;++d)for(var p=Math.max(0,Math.ceil((c-d)/r)),v=Math.min(n.outHeight,(n.inHeight+c-d)/r),m=0;m<i;++m)for(var g=Math.max(0,Math.ceil((u-m)/o)),y=Math.min(n.outWidth,(n.inWidth+u-m)/o),x=0;x<n.outChannels;++x){for(var b=Math.trunc(x/l),w=x%l,C=0,E=0;E<n.batchSize;++E)for(var R=p;R<v;++R)for(var I=d+R*r-c,k=g;k<y;++k){var S=m+k*o-u;C+=h.get(E,I,S,b)*f.get(E,R,k,x)}s.set(C,d,m,b,w)}return s.toTensor()},o.prototype.tile=function(t,e){return Hh(t,\"tile\"),ta(this.bufferSync(t),e)},o.prototype.pad=function(t,e,n){Hh(t,\"pad\");var r=e.map((function(e,n){return e[0]+t.shape[n]+e[1]})),o=e.map((function(t){return t[0]})),a=this.bufferSync(t),i=dr(r,t.dtype);0!==n&&i.values.fill(n);for(var s=0;s<t.size;s++){var u=a.indexToLoc(s),c=u.map((function(t,e){return t+o[e]}));i.set.apply(i,[a.get.apply(a,u)].concat(c))}return i.toTensor()},o.prototype.transpose=function(t,e){Hh(t,\"transpose\");for(var n=new Array(t.rank),r=0;r<n.length;r++)n[r]=t.shape[e[r]];var o=this.readSync(t.dataId),a=dr(n,t.dtype),i=this.bufferSync(t);for(r=0;r<t.size;++r){for(var s=i.indexToLoc(r),u=new Array(s.length),c=0;c<u.length;c++)u[c]=s[e[c]];var l=a.locToIndex(u);a.values[l]=o[r]}return a.toTensor()},o.prototype.gather=function(t,e,n){Hh([t,e],\"gather\");var r=t.shape.slice(),o=this.readSync(e.dataId);r[n]=o.length;for(var a=dr(r,t.dtype),i=this.bufferSync(t),s=0;s<a.size;++s){var u=a.indexToLoc(s),c=u.slice();c[n]=o[u[n]];var l=i.locToIndex(c);a.values[s]=i.values[l]}return a.toTensor()},o.prototype.batchToSpaceND=function(t,e,n){Hh([t],\"batchToSpaceND\");var r=e.reduce((function(t,e){return t*e})),o=zr(t.shape,e,r),a=Gr(o.length,e.length),i=Hr(t.shape,e,r),s=qr(n,e.length),u=Kr(i,n,e.length);return t.reshape(o).transpose(a).reshape(i).slice(s,u)},o.prototype.spaceToBatchND=function(t,e,n){Hh([t],\"spaceToBatchND\");var r=e.reduce((function(t,e){return t*e})),o=[[0,0]];o.push.apply(o,n);for(var a=1+e.length;a<t.shape.length;++a)o.push([0,0]);var i=t.pad(o),s=zr(i.shape,e,r,!1),u=Gr(s.length,e.length,!1),c=Hr(i.shape,e,r,!1);return i.reshape(s).transpose(u).reshape(c)},o.prototype.pool=function(t,e,n){Hh(t,\"pool\");for(var r=e.strideHeight,o=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h=\"max\"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=this.readSync(t.dataId),d=dr(e.outShape,t.dtype),p=d.values,v=e.outShape[1]*e.outShape[2]*e.outShape[3],m=e.outShape[2]*e.outShape[3],g=e.outShape[3],y=0;y<e.batchSize;++y)for(var x=y*v,b=y*t.strides[0],w=0;w<e.inChannels;++w)for(var C=0;C<e.outHeight;++C)for(var E=C*r-c,R=Math.max(0,E),I=Math.min(e.inHeight,s+E),k=x+C*m,S=0;S<e.outWidth;++S){for(var A=S*o-l,D=Math.max(0,A),T=Math.min(e.inWidth,u+A),N=h,F=0,_=0,O=R;O<I;O+=a){for(var M=b+O*t.strides[1],B=D;B<T;B+=i){var P=f[M+B*t.strides[2]+w];\"max\"===n&&P>N?N=P:\"avg\"===n&&(F+=P,_++)}if(isNaN(N))break}p[k+S*g+w]=\"avg\"===n?F/_:N}return d.toTensor()},o.prototype.maxPool=function(t,e){return this.pool(t,e,\"max\")},o.prototype.maxPoolPositions=function(t,e){for(var n=dr(e.outShape,\"int32\"),r=e.strideHeight,o=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h=this.bufferSync(t),f=0;f<e.batchSize;++f)for(var d=0;d<e.inChannels;++d)for(var p=0;p<e.outHeight;++p){for(var v=p*r-c,m=v;m<0;)m+=a;for(var g=Math.min(e.inHeight,s+v),y=0;y<e.outWidth;++y){for(var x=y*o-l,b=x;b<0;)b+=i;for(var w=Math.min(e.inWidth,u+x),C=Number.NEGATIVE_INFINITY,E=-1,R=m;R<g;R+=a)for(var I=R-v,k=b;k<w;k+=i){var S=k-x,A=h.get(f,R,k,d);A>C&&(C=A,E=I*u+S)}n.set(E,f,p,y,d)}}return n.toTensor()},o.prototype.maxPoolBackprop=function(t,e,n,r){Hh([e,n],\"maxPoolBackprop\");for(var o=this.maxPoolPositions(e,r),a=r.strideHeight,i=r.strideWidth,s=r.dilationHeight,u=r.dilationWidth,c=r.effectiveFilterHeight,l=r.effectiveFilterWidth,h=l-1-r.padInfo.left,f=c-1-r.padInfo.top,d=dr(e.shape,\"float32\"),p=this.bufferSync(o),v=this.bufferSync(t),m=0;m<r.batchSize;++m)for(var g=0;g<r.inChannels;++g)for(var y=0;y<r.inHeight;++y)for(var x=0;x<r.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=s){var R=(b+E)/a;if(!(R<0||R>=r.outHeight||Math.floor(R)!==R))for(var I=0;I<l;I+=u){var k=(w+I)/i;if(!(k<0||k>=r.outWidth||Math.floor(k)!==k)){var S=c*l-1-p.get(m,R,k,g)===E*l+I?1:0;if(0!==S)C+=v.get(m,R,k,g)*S}}}d.set(C,m,y,x,g)}return d.toTensor()},o.prototype.avgPoolBackprop=function(t,e,n){Hh([t,e],\"avgPoolBackprop\");for(var r=n.strideHeight,o=n.strideWidth,a=n.filterHeight,i=n.filterWidth,s=n.dilationHeight,u=n.dilationWidth,c=n.effectiveFilterHeight,l=n.effectiveFilterWidth,h=l-1-n.padInfo.left,f=c-1-n.padInfo.top,d=dr(e.shape,\"float32\"),p=1/(a*i),v=this.bufferSync(t),m=0;m<n.batchSize;++m)for(var g=0;g<n.inChannels;++g)for(var y=0;y<n.inHeight;++y)for(var x=0;x<n.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=s){var R=(b+E)/r;if(!(R<0||R>=n.outHeight||Math.floor(R)!==R))for(var I=0;I<l;I+=u){var k=(w+I)/o;if(!(k<0||k>=n.outWidth||Math.floor(k)!==k))C+=v.get(m,R,k,g)}}d.set(C*p,m,y,x,g)}return d.toTensor()},o.prototype.pool3d=function(t,e,n){Hh(t,\"pool3d\");for(var r=e.strideDepth,o=e.strideHeight,a=e.strideWidth,i=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,d=e.padInfo.top,p=e.padInfo.left,v=\"max\"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=this.readSync(t.dataId),g=dr(e.outShape,t.dtype),y=g.values,x=e.outShape[1]*e.outShape[2]*e.outShape[3]*e.outShape[4],b=e.outShape[2]*e.outShape[3]*e.outShape[4],w=e.outShape[3]*e.outShape[4],C=e.outShape[4],E=0;E<e.batchSize;++E)for(var R=E*x,I=E*t.strides[0],k=0;k<e.inChannels;++k)for(var S=0;S<e.outDepth;++S){for(var A=S*r-f,D=A;D<0;)D+=i;for(var T=Math.min(e.inDepth,c+A),N=R+S*b,F=0;F<e.outHeight;++F){for(var _=F*o-d,O=_;O<0;)O+=s;for(var M=Math.min(e.inHeight,l+_),B=N+F*w,P=0;P<e.outWidth;++P){for(var L=P*a-p,W=L;W<0;)W+=u;for(var U=Math.min(e.inWidth,h+L),V=B+P*C,z=v,G=0,H=0,q=D;q<T;q+=i){for(var K=I+q*t.strides[1],j=O;j<M;j+=s){for(var X=K+j*t.strides[2],Y=W;Y<U;Y+=u){var $=m[X+Y*t.strides[3]+k];if(\"max\"===n&&$>z?z=$:\"avg\"===n&&(G+=$,H++),isNaN(z))break}if(isNaN(z))break}if(isNaN(z))break}y[V+k]=\"avg\"===n?G/H:z}}}return g.toTensor()},o.prototype.avgPool3d=function(t,e){return Hh(t,\"avgPool3d\"),this.pool3d(t,e,\"avg\").toFloat()},o.prototype.avgPool3dBackprop=function(t,e,n){Hh([t,e],\"avgPool3dBackprop\");for(var r=n.strideDepth,o=n.strideHeight,a=n.strideWidth,i=n.filterDepth,s=n.filterHeight,u=n.filterWidth,c=n.dilationDepth,l=n.dilationHeight,h=n.dilationWidth,f=n.effectiveFilterDepth,d=n.effectiveFilterHeight,p=n.effectiveFilterWidth,v=f-1-n.padInfo.front,m=p-1-n.padInfo.left,g=d-1-n.padInfo.top,y=dr(e.shape,\"float32\"),x=1/(i*s*u),b=this.bufferSync(t),w=0;w<n.batchSize;++w)for(var C=0;C<n.inChannels;++C)for(var E=0;E<n.inDepth;++E)for(var R=0;R<n.inHeight;++R)for(var I=0;I<n.inWidth;++I){for(var k=E-v,S=R-g,A=I-m,D=0,T=0;T<f;T+=c){var N=(k+T)/r;if(!(N<0||N>=n.outDepth||Math.floor(N)!==N))for(var F=0;F<d;F+=l){var _=(S+F)/o;if(!(_<0||_>=n.outHeight||Math.floor(_)!==_))for(var O=0;O<p;O+=h){var M=(A+O)/a;if(!(M<0||M>=n.outWidth||Math.floor(M)!==M))D+=b.get(w,N,_,M,C)}}}y.set(D*x,w,E,R,I,C)}return y.toTensor()},o.prototype.maxPool3d=function(t,e){return Hh(t,\"maxPool3d\"),this.pool3d(t,e,\"max\").toFloat()},o.prototype.maxPool3dPositions=function(t,e){for(var n=dr(e.outShape,\"int32\"),r=e.strideDepth,o=e.strideHeight,a=e.strideWidth,i=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,d=e.padInfo.top,p=e.padInfo.left,v=this.bufferSync(t),m=0;m<e.batchSize;++m)for(var g=0;g<e.inChannels;++g)for(var y=0;y<e.outDepth;++y){for(var x=y*r-f,b=x;b<0;)b+=i;for(var w=Math.min(e.inDepth,c+x),C=0;C<e.outHeight;++C){for(var E=C*o-d,R=E;R<0;)R+=s;for(var I=Math.min(e.inHeight,l+E),k=0;k<e.outWidth;++k){for(var S=k*a-p,A=S;A<0;)A+=u;for(var D=Math.min(e.inWidth,h+S),T=Number.NEGATIVE_INFINITY,N=-1,F=b;F<w;F+=i)for(var _=F-x,O=R;O<I;O+=s)for(var M=O-E,B=A;B<D;B+=u){var P=B-S,L=v.get(m,F,O,B,g);L>=T&&(T=L,N=_*l*h+M*l+P)}n.set(N,m,y,C,k,g)}}}return n.toTensor()},o.prototype.maxPool3dBackprop=function(t,e,n,r){Hh([e,n],\"maxPool3dBackprop\");for(var o=this.maxPool3dPositions(e,r),a=r.strideDepth,i=r.strideHeight,s=r.strideWidth,u=r.dilationDepth,c=r.dilationHeight,l=r.dilationWidth,h=r.effectiveFilterDepth,f=r.effectiveFilterHeight,d=r.effectiveFilterWidth,p=h-1-r.padInfo.front,v=d-1-r.padInfo.left,m=f-1-r.padInfo.top,g=dr(e.shape,\"float32\"),y=this.bufferSync(o),x=this.bufferSync(t),b=0;b<r.batchSize;++b)for(var w=0;w<r.inChannels;++w)for(var C=0;C<r.inDepth;++C)for(var E=0;E<r.inHeight;++E)for(var R=0;R<r.inWidth;++R){for(var I=C-p,k=E-m,S=R-v,A=0,D=0;D<h;D+=u){var T=(I+D)/a;if(!(T<0||T>=r.outDepth||Math.floor(T)!==T))for(var N=0;N<f;N+=c){var F=(k+N)/i;if(!(F<0||F>=r.outHeight||Math.floor(F)!==F))for(var _=0;_<d;_+=l){var O=(S+_)/s;if(!(O<0||O>=r.outWidth||Math.floor(O)!==O)){var M=h*f*d-1-y.get(b,T,F,O,w)===D*f*d+N*d+_?1:0;if(0!==M)A+=x.get(b,T,F,O,w)*M}}}}g.set(A,b,C,E,R,w)}return g.toTensor()},o.prototype.cast=function(t,e){return Po(t,e,this)},o.prototype.reshape=function(t,e){return Lo(t,e)},o.prototype.avgPool=function(t,e){return Hh(t,\"avgPool\"),this.pool(t,e,\"avg\").toFloat()},o.prototype.resizeBilinear=function(t,e,n,r){Hh(t,\"resizeBilinear\");for(var o=t.shape,a=o[0],i=o[1],s=o[2],u=o[3],c=this.readSync(t.dataId),l=new Float32Array(k([a,e,n,u])),h=[r&&e>1?i-1:i,r&&n>1?s-1:s],f=[r&&e>1?e-1:e,r&&n>1?n-1:n],d=0,p=h[0]/f[0],v=h[1]/f[1],m=0;m<a;m++)for(var g=0;g<e;g++)for(var y=p*g,x=Math.floor(y),b=y-x,w=Math.min(i-1,Math.ceil(y)),C=m*t.strides[0]+x*t.strides[1],E=m*t.strides[0]+w*t.strides[1],R=0;R<n;R++)for(var I=v*R,S=Math.floor(I),A=I-S,D=Math.min(s-1,Math.ceil(I)),T=C+S*t.strides[2],N=E+S*t.strides[2],F=C+D*t.strides[2],_=E+D*t.strides[2],O=0;O<u;O++){var M=c[T+O],B=c[N+O],P=M+(c[F+O]-M)*A,L=P+(B+(c[_+O]-B)*A-P)*b;l[d++]=L}return Fn(l,[a,e,n,u])},o.prototype.resizeBilinearBackprop=function(t,e,n){Hh([t,e],\"resizeBilinearBackprop\");for(var r=e.shape,o=r[0],a=r[1],i=r[2],s=r[3],u=t.shape,c=u[1],l=u[2],h=new Float32Array(o*a*i*s),f=[n&&c>1?a-1:a,n&&l>1?i-1:i],d=[n&&c>1?c-1:c,n&&l>1?l-1:l],p=f[0]/d[0],v=f[1]/d[1],m=this.readSync(t.dataId),g=0,y=0;y<o;y++)for(var x=y*e.strides[0],b=0;b<c;b++)for(var w=b*p,C=Math.floor(w),E=Math.min(Math.ceil(w),a-1),R=x+C*e.strides[1],I=x+E*e.strides[1],k=w-C,S=1-k,A=0;A<l;A++)for(var D=A*v,T=Math.floor(D),N=Math.min(Math.ceil(D),i-1),F=D-T,_=1-F,O=R+T*e.strides[2],M=R+N*e.strides[2],B=I+T*e.strides[2],P=I+N*e.strides[2],L=S*_,W=S*F,U=k*_,V=k*F,z=0;z<s;z++){var G=m[g++];h[O+z]+=G*L,h[M+z]+=G*W,h[B+z]+=G*U,h[P+z]+=G*V}return Ln(h,[o,i,a,s],e.dtype)},o.prototype.resizeNearestNeighbor=function(t,e,n,r){Hh(t,\"resizeNearestNeighbor\");for(var o=t.shape,a=o[0],i=o[1],s=o[2],u=o[3],c=this.readSync(t.dataId),l=new Float32Array(a*e*n*u),h=[r&&e>1?i-1:i,r&&n>1?s-1:s],f=[r&&e>1?e-1:e,r&&n>1?n-1:n],d=h[0]/f[0],p=h[1]/f[1],v=0,m=0;m<a;m++)for(var g=m*t.strides[0],y=0;y<e;y++)for(var x=d*y,b=g+Math.min(i-1,r?Math.round(x):Math.floor(x))*t.strides[1],w=0;w<n;w++)for(var C=p*w,E=b+Math.min(s-1,r?Math.round(C):Math.floor(C))*t.strides[2],R=0;R<u;R++){var I=c[E+R];l[v++]=I}return Fn(l,[a,e,n,u],t.dtype)},o.prototype.resizeNearestNeighborBackprop=function(t,e,n){Hh([t,e],\"resizeNearestNeighborBackprop\");for(var r=e.shape,o=r[0],a=r[1],i=r[2],s=r[3],u=t.shape,c=u[1],l=u[2],h=new Float32Array(o*a*i*s),f=this.readSync(t.dataId),d=[n&&c>1?a-1:a,n&&l>1?i-1:i],p=[n&&c>1?c-1:c,n&&l>1?l-1:l],v=d[0]/p[0],m=d[1]/p[1],g=1/v,y=1/m,x=2*Math.ceil(g)+2,b=2*Math.ceil(y)+2,w=0;w<o;w++)for(var C=w*e.strides[0],E=0;E<a;E++)for(var R=C+E*e.strides[1],I=Math.floor(E*g),k=Math.floor(I-x/2),S=0;S<i;S++)for(var A=R+S*e.strides[2],D=Math.floor(S*y),T=Math.floor(D-b/2),N=0;N<s;N++){for(var F=0,_=0;_<x;_++){var O=_+k;if(!(O<0||O>=c)){var M=C+O*t.strides[1],B=O*v;if(E===Math.min(a-1,n?Math.round(B):Math.floor(B)))for(var P=0;P<b;P++){var L=P+T;if(!(L<0||L>=l)){var W=M+L*t.strides[2],U=L*m;S===Math.min(i-1,n?Math.round(U):Math.floor(U))&&(F+=f[W+N])}}}}h[A+N]=F}return Ln(h,e.shape,e.dtype)},o.prototype.batchNormalization=function(t,e,n,r,o,a){Hh([t,e,n,o,a],\"batchNorm\");for(var i=this.readSync(t.dataId),s=this.readSync(e.dataId),u=this.readSync(n.dataId),c=o?this.readSync(o.dataId):new Float32Array([1]),l=a?this.readSync(a.dataId):new Float32Array([0]),h=new Float32Array(i.length),f=l.length,d=c.length,p=u.length,v=s.length,m=0,g=0,y=0,x=0,b=0;b<i.length;++b)h[b]=l[m++]+(i[b]-s[g++])*c[y++]/Math.sqrt(u[x++]+r),m>=f&&(m=0),g>=v&&(g=0),y>=d&&(y=0),x>=p&&(x=0);return Ln(h,t.shape)},o.prototype.localResponseNormalization4D=function(t,e,n,r,o){Hh(t,\"localResponseNormalization4D\");var a=t.shape[3],i=a-1,s=this.readSync(t.dataId),u=t.size,c=new Float32Array(u);function l(t){for(var n=t%a,r=t-n+Math.max(0,n-e),o=t-n+Math.min(n+e,i),u=0;r<=o;r++){var c=s[r];u+=c*c}return u}for(var h=0;h<u;h++){var f=l(h),d=s[h]*Math.pow(n+r*f,-o);c[h]=d}return Ln(c,t.shape)},o.prototype.LRNGrad=function(t,e,n,r,o,a,i){Hh(t,\"LRNGrad\");for(var s=t.shape[3],u=this.readSync(t.dataId),c=this.readSync(e.dataId),l=this.readSync(n.dataId),h=new Float32Array(t.size),f=t.size,d=0;d<f;d++){for(var p=d%s,v=d-p+Math.max(0,p-r),m=d-p+Math.min(s,p+r+1),g=0,y=v;y<m;y++)g+=Math.pow(c[y],2);g=a*g+o;for(y=v;y<m;y++){var x=-2*a*i*c[y]*l[d]/g;d===y&&(x+=Math.pow(g,-i)),x*=u[d],h[y]+=x}}return Ln(h,t.shape)},o.prototype.multinomial=function(t,e,n,r){Hh(t,\"multinomial\");for(var o=e?t:go(t),a=o.shape[0],i=o.shape[1],s=Gn([a,n],\"int32\"),u=this.readSync(s.dataId),c=this.readSync(o.dataId),l=0;l<a;++l){var h=l*i,f=new Float32Array(i-1);f[0]=c[h];for(var d=1;d<f.length;++d)f[d]=f[d-1]+c[h+d];for(var p=cr(r.toString()),v=l*n,m=0;m<n;++m){var g=p();u[v+m]=f.length;for(var y=0;y<f.length;y++)if(g<f[y]){u[v+m]=y;break}}}return s},o.prototype.oneHot=function(t,e,n,r){Hh(t,\"oneHot\");var o=new Float32Array(t.size*e);o.fill(r);for(var a=this.readSync(t.dataId),i=0;i<t.size;++i)a[i]>=0&&a[i]<e&&(o[i*e+a[i]]=n);return Bn(o,[t.size,e],\"int32\")},o.prototype.nonMaxSuppression=function(t,e,n,r,o){return Hh(t,\"nonMaxSuppression\"),jo(this.readSync(t.dataId),this.readSync(e.dataId),n,r,o)},o.prototype.fft=function(t){return this.fftBatch(t,!1)},o.prototype.ifft=function(t){return this.fftBatch(t,!0)},o.prototype.fftBatch=function(t,e){for(var n=t.shape[0],r=t.shape[1],o=dr(t.shape,\"float32\"),a=dr(t.shape,\"float32\"),i=Tn(t).as2D(n,r),s=Nn(t).as2D(n,r),u=0;u<n;u++)for(var c=i.slice([u,0],[1,r]),l=s.slice([u,0],[1,r]),h=Dn(c,l),f=this.readSync(this.fftImpl(h,e).dataId),d=0;d<r;d++){var p=zo(f,d);o.values[u*r+d]=p.real,a.values[u*r+d]=p.imag}return Dn(o.toTensor(),a.toTensor()).as2D(n,r)},o.prototype.fftImpl=function(t,e){var n=t.as1D(),r=n.size;if(this.isExponentOf2(r)){var o=this.fftRadix2(n,r,e).as2D(t.shape[0],t.shape[1]);return e&&(o=Dn(Tn(o).div(On(r)),Nn(o).div(On(r)))),o}var a=this.readSync(t.dataId),i=function(t){for(var e=new Float32Array(t.length/2),n=new Float32Array(t.length/2),r=0;r<t.length;r+=2)e[r/2]=t[r],n[r/2]=t[r+1];return{real:e,imag:n}}(this.fourierTransformByMatmul(a,r,e));return Dn(i.real,i.imag).as2D(t.shape[0],t.shape[1])},o.prototype.isExponentOf2=function(t){return 0==(t&t-1)},o.prototype.fftRadix2=function(t,e,n){if(1===e)return t;var r=this.readSync(t.dataId),o=e/2,a=function(t){for(var e=Math.ceil(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=0;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return{real:n,imag:r}}(r),i=Dn(a.real,a.imag).as1D(),s=function(t){for(var e=Math.floor(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=2;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return{real:n,imag:r}}(r),u=Dn(s.real,s.imag).as1D();i=this.fftRadix2(i,o,n),u=this.fftRadix2(u,o,n);var c=function(t,e){for(var n=new Float32Array(t/2),r=new Float32Array(t/2),o=0;o<Math.ceil(t/2);o++){var a=(e?2:-2)*Math.PI*(o/t);n[o]=Math.cos(a),r[o]=Math.sin(a)}return{real:n,imag:r}}(e,n),l=Dn(c.real,c.imag).mul(u),h=i.add(l),f=i.sub(l),d=Tn(h).concat(Tn(f)),p=Nn(h).concat(Nn(f));return Dn(d,p).as1D()},o.prototype.fourierTransformByMatmul=function(t,e,n){for(var r=new Float32Array(2*e),o=0;o<e;o++){for(var a=0,i=0,s=0;s<e;s++){var u=Ho(o*s,e,n),c=zo(t,s);a+=c.real*u.real-c.imag*u.imag,i+=c.real*u.imag+c.imag*u.real}n&&(a/=e,i/=e),Go(r,a,i,o)}return r},o.prototype.depthToSpace=function(t,e,n){C(\"NHWC\"===n,(function(){return\"Only NHWC dataFormat supported on CPU for depthToSpace. Got \"+n})),C(e>1,(function(){return\"blockSize should be > 1 for depthToSpace, but was: \"+e}));for(var r=t.shape[0],o=t.shape[1],a=t.shape[2],i=t.shape[3],s=o*e,u=a*e,c=i/(e*e),l=this.readSync(t.dataId),h=new Float32Array(r*s*u*c),f=0,d=0;d<r;++d)for(var p=0;p<s;++p)for(var v=Math.floor(p/e),m=p%e,g=0;g<u;++g)for(var y=Math.floor(g/e),x=(m*e+g%e)*c,b=0;b<c;++b){var w=b+x+i*(y+a*(v+o*d));h[f++]=l[w]}return Ln(h,[r,s,u,c])},o.prototype.broadcastedBinaryOp=function(t,e,n,r){var o=Ro(t.shape,e.shape),a=dr(o,n),i=this.readSync(t.dataId),s=this.readSync(e.dataId),u=Co(t.shape,o),c=Co(e.shape,o),l=a.values;if(u.length+c.length===0)for(var h=0;h<l.length;++h)l[h]=r(i[h%i.length],s[h%s.length]);else{var f=this.bufferSync(t),d=this.bufferSync(e),p=function(n){var o=a.indexToLoc(n),h=o.slice(-t.rank);u.forEach((function(t){return h[t]=0}));var p=f.locToIndex(h),v=o.slice(-e.rank);c.forEach((function(t){return v[t]=0}));var m=d.locToIndex(v);l[n]=r(i[p],s[m])};for(h=0;h<l.length;++h)p(h)}return a.toTensor()},o.prototype.broadcastedBinaryComplexOp=function(t,e,n){var r=Ro(t.shape,e.shape),o=dr(r,\"float32\"),a=dr(r,\"float32\"),i=this.readSync(t.dataId),s=this.readSync(e.dataId),u=Co(t.shape,r),c=Co(e.shape,r),l=o.values,h=a.values;if(u.length+c.length===0)for(var f=0;f<l.length;f++){var d=f%i.length,p=f%s.length,v=n(i[2*d],i[2*d+1],s[2*p],s[2*p+1]);l[f]=v.real,h[f]=v.imag}else{var m=this.bufferSync(this.data.get(t.dataId).complexTensors.real),g=this.bufferSync(this.data.get(e.dataId).complexTensors.real),y=function(r){var a=o.indexToLoc(r),f=a.slice(-t.rank);u.forEach((function(t){return f[t]=0}));var d=m.locToIndex(f),p=a.slice(-e.rank);c.forEach((function(t){return p[t]=0}));var v=g.locToIndex(p),y=n(i[2*d],i[2*d+1],s[2*v],s[2*v+1]);l[r]=y.real,h[r]=y.imag};for(f=0;f<l.length;f++)y(f)}return this.complex(o.toTensor(),a.toTensor())},o.prototype.split=function(t,e,n){return Zo(t,e,n)},o.prototype.dispose=function(){},o.prototype.floatPrecision=function(){return 32},o.prototype.epsilon=function(){return 1e-7},o.prototype.cropAndResize=function(t,e,n,r,o,a){for(var i=t.shape,s=i[0],u=i[1],c=i[2],l=i[3],h=e.shape[0],f=r[0],d=r[1],p=dr([h,f,d,l],\"float32\"),v=this.readSync(e.dataId),m=this.readSync(n.dataId),g=this.readSync(t.dataId),y=t.strides,x=p.strides,b=0;b<h;b++){var w=4*b,C=v[w],E=v[w+1],R=v[w+2],I=v[w+3],k=m[b];if(!(k>=s))for(var S=f>1?(R-C)*(u-1)/(f-1):0,A=d>1?(I-E)*(c-1)/(d-1):0,D=0;D<f;D++){var T=f>1?C*(u-1)+D*S:.5*(C+R)*(u-1);if(T<0||T>u-1)for(var N=0;N<d;N++)for(var F=0;F<l;F++){var _=F+N*x[2]+D*x[1]+b*x[0];p.values[_]=a}else if(\"bilinear\"===o){var O=Math.floor(T),M=Math.ceil(T),B=T-O;for(N=0;N<d;N++){if((q=d>1?E*(c-1)+N*A:.5*(E+I)*(c-1))<0||q>c-1)for(F=0;F<l;F++){_=F+N*x[2]+D*x[1]+b*x[0];p.values[_]=a}else{var P=Math.floor(q),L=Math.ceil(q),W=q-P;for(F=0;F<l;F++){var U=g[_=F+P*y[2]+O*y[1]+k*y[0]],V=g[_=F+L*y[2]+O*y[1]+k*y[0]],z=g[_=F+P*y[2]+M*y[1]+k*y[0]],G=U+(V-U)*W,H=z+(g[_=F+L*y[2]+M*y[1]+k*y[0]]-z)*W;_=F+N*x[2]+D*x[1]+b*x[0],p.values[_]=G+(H-G)*B}}}}else for(N=0;N<d;++N){var q;if((q=d>1?E*(c-1)+N*A:.5*(E+I)*(c-1))<0||q>c-1)for(F=0;F<l;F++){_=F+N*x[2]+D*x[1]+b*x[0];p.values[_]=a}else{var K=Math.round(q),j=Math.round(T);for(F=0;F<l;F++){var X=F+K*y[2]+j*y[1]+k*y[0],Y=F+N*x[2]+D*x[1]+b*x[0];p.values[Y]=g[X]}}}}}return p.toTensor()},o.prototype.sparseToDense=function(t,e,n,r){var o=Zr(0,t,n),a=o.sliceRank,i=o.numUpdates,s=o.sliceSize,u=o.strides,c=o.outputSize;return this.scatter(t,e,n,c,s,i,a,u,r,!1)},o.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=jr(t,e),a=o[0],i=o[1],s=o[2],u=o[3];if(0===i)return Fn([],a,t.dtype);for(var c=new gt([i,s],t.dtype),l=this.readSync(e.dataId),h=this.readSync(t.dataId),f=0;f<i;f++){for(var d=[],p=0,v=0;v<r;v++){var m=l[f*r+v];p+=m*u[v],d.push(m)}if(p<0||p>=t.size/s)throw new Error(\"Invalid indices: \"+d+\" does not index into \"+t.shape);for(var g=0;g<s;g++)c.values[f*s+g]=h[p*s+g]}return c.toTensor().reshape(a)},o.prototype.scatterND=function(t,e,n){var r=Zr(0,t,n),o=r.sliceRank,a=r.numUpdates,i=r.sliceSize,s=r.strides,u=r.outputSize,c=On(0);return this.scatter(t,e,n,u,i,a,o,s,c,!0)},o.prototype.fill=function(t,e,n){var r=P(n=n||j(e),k(t));return r.fill(e),Lt.makeTensor(r,t,n,this)},o.prototype.onesLike=function(t){if(\"string\"===t.dtype)throw new Error(\"onesLike is not supported for string tensors\");return this.fill(t.shape,1,t.dtype)},o.prototype.zerosLike=function(t){var e=P(t.dtype,k(t.shape));return this.makeOutput(e,t.shape,t.dtype)},o.prototype.linspace=function(t,e,n){return Wo(t,e,n)},o.prototype.scatter=function(t,e,n,r,o,a,i,s,u,c){var l=[r/o,o],h=this.readSync(t.dataId),f=this.readSync(e.dataId);if(0===r)return Fn([],n,e.dtype);var d=new gt(l,e.dtype);d.values.fill(this.readSync(u.dataId)[0]);for(var p=0;p<a;p++){for(var v=[],m=0,g=0;g<i;g++){var y=h[p*i+g];v.push(y),m+=y*s[g]}if(m<0||m>=r/o)throw new Error(\"Invalid indices: \"+v+\" does not index into \"+n);for(var x=0;x<o;x++)c?d.values[m*o+x]+=f[p*o+x]:d.values[m*o+x]=0===e.rank?f[0]:f[p*o+x]}return d.toTensor().reshape(n)},o}(bo);Lt.registerBackend(\"cpu\",(function(){return new Kh}),1);for(var jh=0,Xh=[{kernelName:\"NonMaxSuppressionV5\",backendName:\"cpu\",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=t.attrs,o=e,a=o.boxes,i=o.scores,s=r,u=s.maxOutputSize,c=s.iouThreshold,l=s.scoreThreshold,h=s.softNmsSigma,f=n;Hh(a,\"NonMaxSuppressionWithScore\");var d=Xo(f.data.get(a.dataId).values,f.data.get(i.dataId).values,u,c,l,h);return[d.selectedIndices,d.selectedScores]}},{kernelName:\"Square\",backendName:\"cpu\",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e.x,o=n;Hh(r,\"square\");for(var a=o.data.get(r.dataId).values,i=new Float32Array(a.length),s=0;s<a.length;++s){var 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depth = coords[2];\\n\\n        vec4 result = vec4(0.);\\n\\n        for(int row=0; row<=1; row++) {\\n          for(int col=0; col<=1; col++) {\\n            texC = coords[1] + row;\\n            depth = coords[2] + col;\\n\\n            vec2 uv = (vec2(texC, texR) + halfCR) /\\n                       vec2(\"+r+\".0, \"+n+\".0);\\n            vec4 values = \"+e.texture2D+\"(A, uv);\\n            float value;\\n            if (depth == 0) {\\n              value = values.r;\\n            } else if (depth == 1) {\\n              value = values.g;\\n            } else if (depth == 2) {\\n              value = values.b;\\n            } else if (depth == 3) {\\n              value = values.a;\\n            }\\n\\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\\n          }\\n        }\\n\\n        \"+e.output+\" = result;\\n      }\\n    \"};for(var Jh=0,Zh=[{kernelName:\"FromPixels\",backendName:\"webgl\",kernelFunc:function(t){var 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h=r.sent(),o&&l?[4,yf.getManager(u).removeModel(c)]:[3,3];case 2:r.sent(),r.label=3;case 3:return[4,s.save(h)];case 4:return f=r.sent(),!o||l?[3,6]:[4,yf.getManager(u).removeModel(c)];case 5:r.sent(),r.label=6;case 6:return[2,f.modelArtifactsInfo]}}))}))}var wf=\"models_store\",Cf=\"model_info_store\";function Ef(){if(!i().getBool(\"IS_BROWSER\"))throw new Error(\"Failed to obtain IndexedDB factory because the current environmentis not a web browser.\");var t=window||self,e=t.indexedDB||t.mozIndexedDB||t.webkitIndexedDB||t.msIndexedDB||t.shimIndexedDB;if(null==e)throw new Error(\"The current browser does not appear to support IndexedDB.\");return e}function Rf(t){var e=t.result;e.createObjectStore(wf,{keyPath:\"modelPath\"}),e.createObjectStore(Cf,{keyPath:\"modelPath\"})}var If=function(){function t(t){if(this.indexedDB=Ef(),null==t||!t)throw new Error(\"For IndexedDB, modelPath must not be null, undefined or empty.\");this.modelPath=t}return t.prototype.save=function(t){return n(this,void 0,void 0,(function(){return r(this,(function(e){if(t.modelTopology instanceof ArrayBuffer)throw new Error(\"BrowserLocalStorage.save() does not support saving model topology in binary formats yet.\");return[2,this.databaseAction(this.modelPath,t)]}))}))},t.prototype.load=function(){return n(this,void 0,void 0,(function(){return r(this,(function(t){return[2,this.databaseAction(this.modelPath)]}))}))},t.prototype.databaseAction=function(t,e){var n=this;return new Promise((function(t,r){var o=n.indexedDB.open(\"tensorflowjs\",1);o.onupgradeneeded=function(){return Rf(o)},o.onsuccess=function(){var a=o.result;if(null==e){var i=a.transaction(wf,\"readonly\"),s=i.objectStore(wf).get(n.modelPath);s.onsuccess=function(){if(null==s.result)return a.close(),r(new Error(\"Cannot find model with path '\"+n.modelPath+\"' in IndexedDB.\"));t(s.result.modelArtifacts)},s.onerror=function(t){return a.close(),r(s.error)},i.oncomplete=function(){return a.close()}}else{var u,c=vf(e),l=a.transaction(Cf,\"readwrite\"),h=l.objectStore(Cf),f=h.put({modelPath:n.modelPath,modelArtifactsInfo:c});f.onsuccess=function(){var o=(u=a.transaction(wf,\"readwrite\")).objectStore(wf).put({modelPath:n.modelPath,modelArtifacts:e,modelArtifactsInfo:c});o.onsuccess=function(){return t({modelArtifactsInfo:c})},o.onerror=function(t){var e=(h=l.objectStore(Cf)).delete(n.modelPath);e.onsuccess=function(){return a.close(),r(o.error)},e.onerror=function(t){return a.close(),r(o.error)}}},f.onerror=function(t){return a.close(),r(f.error)},l.oncomplete=function(){null==u?a.close():u.oncomplete=function(){return a.close()}}}},o.onerror=function(t){return r(o.error)}}))},t.URL_SCHEME=\"indexeddb://\",t}(),kf=function(t){return i().getBool(\"IS_BROWSER\")&&!Array.isArray(t)&&t.startsWith(If.URL_SCHEME)?(e=t.slice(If.URL_SCHEME.length),new If(e)):null;var e};mf.registerSaveRouter(kf),mf.registerLoadRouter(kf);var Sf=function(){function t(){this.indexedDB=Ef()}return t.prototype.listModels=function(){return n(this,void 0,void 0,(function(){var t=this;return r(this,(function(e){return[2,new Promise((function(e,n){var r=t.indexedDB.open(\"tensorflowjs\",1);r.onupgradeneeded=function(){return Rf(r)},r.onsuccess=function(){var t=r.result,o=t.transaction(Cf,\"readonly\"),a=o.objectStore(Cf).getAll();a.onsuccess=function(){for(var t={},n=0,r=a.result;n<r.length;n++){var o=r[n];t[o.modelPath]=o.modelArtifactsInfo}e(t)},a.onerror=function(e){return t.close(),n(a.error)},o.oncomplete=function(){return t.close()}},r.onerror=function(t){return n(r.error)}}))]}))}))},t.prototype.removeModel=function(t){return n(this,void 0,void 0,(function(){var e=this;return r(this,(function(n){var r;return t=(r=t).startsWith(If.URL_SCHEME)?r.slice(If.URL_SCHEME.length):r,[2,new Promise((function(n,r){var o=e.indexedDB.open(\"tensorflowjs\",1);o.onupgradeneeded=function(){return Rf(o)},o.onsuccess=function(){var e,a=o.result,i=a.transaction(Cf,\"readwrite\"),s=i.objectStore(Cf),u=s.get(t);u.onsuccess=function(){if(null==u.result)return a.close(),r(new Error(\"Cannot find model with path '\"+t+\"' in IndexedDB.\"));var o=s.delete(t),i=function(){var o=(e=a.transaction(wf,\"readwrite\")).objectStore(wf).delete(t);o.onsuccess=function(){return n(u.result.modelArtifactsInfo)},o.onerror=function(t){return r(u.error)}};o.onsuccess=i,o.onerror=function(t){return i(),a.close(),r(u.error)}},u.onerror=function(t){return a.close(),r(u.error)},i.oncomplete=function(){null==e?a.close():e.oncomplete=function(){return a.close()}}},o.onerror=function(t){return r(o.error)}}))]}))}))},t}();if(i().getBool(\"IS_BROWSER\"))try{yf.registerManager(If.URL_SCHEME,new Sf)}catch(t){}var Af=\"/\",Df=\"tensorflowjs_models\",Tf=\"info\",Nf=\"model_topology\",Ff=\"weight_specs\",_f=\"weight_data\",Of=\"model_metadata\";function Mf(t){return{info:[Df,t,Tf].join(Af),topology:[Df,t,Nf].join(Af),weightSpecs:[Df,t,Ff].join(Af),weightData:[Df,t,_f].join(Af),modelMetadata:[Df,t,Of].join(Af)}}function Bf(t){var e=t.split(Af);if(e.length<3)throw new Error(\"Invalid key format: \"+t);return e.slice(1,e.length-1).join(Af)}var Pf=function(){function t(t){if(!i().getBool(\"IS_BROWSER\")||\"undefined\"==typeof window||void 0===window.localStorage)throw new Error(\"The current environment does not support local storage.\");if(this.LS=window.localStorage,null==t||!t)throw new Error(\"For local storage, modelPath must not be null, undefined or empty.\");this.modelPath=t,this.keys=Mf(this.modelPath)}return t.prototype.save=function(t){return n(this,void 0,void 0,(function(){var e,n,o;return r(this,(function(r){if(t.modelTopology instanceof ArrayBuffer)throw new Error(\"BrowserLocalStorage.save() does not support saving model topology in binary formats 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modelTopologyBytes=\"+o.modelTopologyBytes+\", weightSpecsBytes=\"+o.weightSpecsBytes+\", weightDataBytes=\"+o.weightDataBytes+\".\")}return[2]}))}))},t.prototype.load=function(){return n(this,void 0,void 0,(function(){var t,e,n,o,a,i,s;return r(this,(function(r){if(null==(t=JSON.parse(this.LS.getItem(this.keys.info))))throw new Error(\"In local storage, there is no model with name '\"+this.modelPath+\"'\");if(\"JSON\"!==t.modelTopologyType)throw new Error(\"BrowserLocalStorage does not support loading non-JSON model topology yet.\");if(e={},null==(n=JSON.parse(this.LS.getItem(this.keys.topology))))throw new Error(\"In local storage, the topology of model '\"+this.modelPath+\"' is missing.\");if(e.modelTopology=n,null==(o=JSON.parse(this.LS.getItem(this.keys.weightSpecs))))throw new Error(\"In local storage, the weight specs of model '\"+this.modelPath+\"' are missing.\");if(e.weightSpecs=o,null!=(a=this.LS.getItem(this.keys.modelMetadata))&&(i=JSON.parse(a),e.format=i.format,e.generatedBy=i.generatedBy,e.convertedBy=i.convertedBy,e.userDefinedMetadata=i.userDefinedMetadata),null==(s=this.LS.getItem(this.keys.weightData)))throw new Error(\"In local storage, the binary weight values of model '\"+this.modelPath+\"' are missing.\");return e.weightData=function(t){if(hf){var e=Buffer.from(t,\"base64\");return e.buffer.slice(e.byteOffset,e.byteOffset+e.byteLength)}for(var n=atob(t),r=new Uint8Array(n.length),o=0;o<n.length;++o)r.set([n.charCodeAt(o)],o);return r.buffer}(s),[2,e]}))}))},t.URL_SCHEME=\"localstorage://\",t}(),Lf=function(t){return i().getBool(\"IS_BROWSER\")&&!Array.isArray(t)&&t.startsWith(Pf.URL_SCHEME)?(e=t.slice(Pf.URL_SCHEME.length),new Pf(e)):null;var e};mf.registerSaveRouter(Lf),mf.registerLoadRouter(Lf);var Wf=function(){function t(){C(i().getBool(\"IS_BROWSER\"),(function(){return\"Current environment is not a web 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n=JSON.parse(this.LS.getItem(e.info)),this.LS.removeItem(e.info),this.LS.removeItem(e.topology),this.LS.removeItem(e.weightSpecs),this.LS.removeItem(e.weightData),[2,n]}))}))},t}();if(i().getBool(\"IS_BROWSER\"))try{yf.registerManager(Pf.URL_SCHEME,new Wf)}catch(t){}var Uf=\"model\",Vf=\".json\",zf=\".weights.bin\";function Gf(t){return new Promise((function(t){return setTimeout(t)})).then(t)}var Hf=function(){function t(e){if(!i().getBool(\"IS_BROWSER\"))throw new Error(\"browserDownloads() cannot proceed because the current environment is not a browser.\");e.startsWith(t.URL_SCHEME)&&(e=e.slice(t.URL_SCHEME.length)),null!=e&&0!==e.length||(e=Uf),this.modelTopologyFileName=e+Vf,this.weightDataFileName=e+zf}return t.prototype.save=function(t){return n(this,void 0,void 0,(function(){var e,n,o,a,i,s;return r(this,(function(r){switch(r.label){case 0:if(\"undefined\"==typeof document)throw new Error(\"Browser downloads are not supported in this environment since `document` is not present\");if(e=window.URL.createObjectURL(new Blob([t.weightData],{type:\"application/octet-stream\"})),!(t.modelTopology instanceof ArrayBuffer))return[3,1];throw new Error(\"BrowserDownloads.save() does not support saving model topology in binary formats yet.\");case 1:return n=[{paths:[\"./\"+this.weightDataFileName],weights:t.weightSpecs}],o={modelTopology:t.modelTopology,format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,weightsManifest:n},a=window.URL.createObjectURL(new Blob([JSON.stringify(o)],{type:\"application/json\"})),(i=null==this.jsonAnchor?document.createElement(\"a\"):this.jsonAnchor).download=this.modelTopologyFileName,i.href=a,[4,Gf((function(){return i.dispatchEvent(new MouseEvent(\"click\"))}))];case 2:return r.sent(),null==t.weightData?[3,4]:((s=null==this.weightDataAnchor?document.createElement(\"a\"):this.weightDataAnchor).download=this.weightDataFileName,s.href=e,[4,Gf((function(){return s.dispatchEvent(new MouseEvent(\"click\"))}))]);case 3:r.sent(),r.label=4;case 4:return[2,{modelArtifactsInfo:vf(t)}]}}))}))},t.URL_SCHEME=\"downloads://\",t}(),qf=function(){function t(t){if(null==t||t.length<1)throw new Error(\"When calling browserFiles, at least 1 file is required, but received \"+t);this.files=t}return t.prototype.load=function(){return n(this,void 0,void 0,(function(){var t,e,n=this;return r(this,(function(r){return t=this.files[0],e=this.files.slice(1),[2,new Promise((function(r,o){var a=new FileReader;a.onload=function(a){var i=JSON.parse(a.target.result),s=i.modelTopology;if(null!=s){0===e.length&&r({modelTopology:s});var u=i.weightsManifest;if(null!=u){var c;try{c=n.checkManifestAndWeightFiles(u,e)}catch(t){return void o(t)}var l=[],h=[],f=[];u.forEach((function(t){t.paths.forEach((function(t){h.push(t),f.push(null)})),l.push.apply(l,t.weights)})),u.forEach((function(t){t.paths.forEach((function(t){var e=new FileReader;e.onload=function(e){var n=e.target.result,o=h.indexOf(t);f[o]=n,-1===f.indexOf(null)&&r({modelTopology:s,weightSpecs:l,weightData:df(f),format:i.format,generatedBy:i.generatedBy,convertedBy:i.convertedBy,userDefinedMetadata:i.userDefinedMetadata})},e.onerror=function(e){return o(\"Failed to weights data from file of path '\"+t+\"'.\")},e.readAsArrayBuffer(c[t])}))}))}else o(new Error(\"weightManifest field is missing from file \"+t.name))}else o(new Error(\"modelTopology field is missing from file \"+t.name))},a.onerror=function(e){return o(\"Failed to read model topology and weights manifest JSON from file '\"+t.name+\"'. BrowserFiles supports loading Keras-style tf.Model artifacts only.\")},a.readAsText(t)}))]}))}))},t.prototype.checkManifestAndWeightFiles=function(t,e){for(var n=[],r=e.map((function(t){return pf(t.name)})),o={},a=0,i=t;a<i.length;a++){i[a].paths.forEach((function(t){var a=pf(t);if(-1!==n.indexOf(a))throw new Error(\"Duplicate file basename found in weights manifest: '\"+a+\"'\");if(n.push(a),-1===r.indexOf(a))throw new Error(\"Weight file with basename '\"+a+\"' is not provided.\");o[t]=e[r.indexOf(a)]}))}if(n.length!==e.length)throw new Error(\"Mismatch in the number of files in weights manifest (\"+n.length+\") and the number of weight files provided (\"+e.length+\").\");return o},t}();function Kf(t,e,n,r){!function(t){C(null!=t&&Array.isArray(t)&&t.length>0,(function(){return\"promises must be a none empty array\"}))}(t),function(t,e){C(t>=0&&t<=1,(function(){return\"Progress fraction must be in range [0, 1], but got startFraction \"+t})),C(e>=0&&e<=1,(function(){return\"Progress fraction must be in range [0, 1], but got endFraction \"+e})),C(e>=t,(function(){return\"startFraction must be no more than endFraction, but got startFraction \"+t+\" and endFraction \"+e}))}(n=null==n?0:n,r=null==r?1:r);var o=0;return Promise.all(t.map((function(a){return a.then((function(a){var i=n+ ++o/t.length*(r-n);return e(i),a})),a})))}function jf(t,e){return n(this,void 0,void 0,(function(){var n,o,a,s,u,c,l,h,f;return r(this,(function(r){switch(r.label){case 0:return null==e&&(e={}),n=null==e.fetchFunc?i().platform.fetch:e.fetchFunc,o=t.map((function(t){return n(t,e.requestInit,{isBinary:!0})})),a=0,s=.5,null!=e.onProgress?[3,2]:[4,Promise.all(o)];case 1:return u=r.sent(),[3,4];case 2:return[4,Kf(o,e.onProgress,a,s)];case 3:u=r.sent(),r.label=4;case 4:return c=u.map((function(t){return t.arrayBuffer()})),l=.5,h=1,null!=e.onProgress?[3,6]:[4,Promise.all(c)];case 5:return f=r.sent(),[3,8];case 6:return[4,Kf(c,e.onProgress,l,h)];case 7:f=r.sent(),r.label=8;case 8:return[2,f]}}))}))}function Xf(t){var e=this;return function(o,a,i){return void 0===a&&(a=\"\"),n(e,void 0,void 0,(function(){var e,n,s,u,c,l,h,f,d,p;return r(this,(function(r){switch(r.label){case 0:if(e=o.map((function(){return!1})),n={},s=null!=i?i.map((function(){return!1})):[],u=[],o.forEach((function(t,r){var o=0;t.weights.forEach((function(t){var a=\"quantization\"in t?t.quantization.dtype:t.dtype,c=sf[a]*k(t.shape),l=function(){e[r]=!0,null==n[r]&&(n[r]=[]),n[r].push({manifestEntry:t,groupOffset:o,sizeBytes:c})};null!=i?i.forEach((function(e,n){e===t.name&&(l(),s[n]=!0)})):l(),u.push(t.name),o+=c}))})),!s.every((function(t){return t})))throw c=i.filter((function(t,e){return!s[e]})),new Error(\"Could not find weights in manifest with names: \"+c.join(\", \")+\". \\nManifest JSON has weights with names: \"+u.join(\", \")+\".\");return l=e.reduce((function(t,e,n){return e&&t.push(n),t}),[]),h=[],l.forEach((function(t){o[t].paths.forEach((function(t){var e=a+(a.endsWith(\"/\")?\"\":\"/\")+t;h.push(e)}))})),[4,t(h)];case 1:return f=r.sent(),d={},p=0,l.forEach((function(t){for(var e=o[t].paths.length,r=0,a=0;a<e;a++)r+=f[p+a].byteLength;for(var i=new ArrayBuffer(r),s=new Uint8Array(i),u=0,c=0;c<e;c++){var l=new Uint8Array(f[p+c]);s.set(l,u),u+=l.byteLength}n[t].forEach((function(t){var e=cf(i.slice(t.groupOffset,t.groupOffset+t.sizeBytes),[t.manifestEntry]);for(var n in e)d[n]=e[n]})),p+=e})),[2,d]}}))}))}}mf.registerSaveRouter((function(t){return i().getBool(\"IS_BROWSER\")&&!Array.isArray(t)&&t.startsWith(Hf.URL_SCHEME)?function(t){void 0===t&&(t=\"model\");return new Hf(t)}(t.slice(Hf.URL_SCHEME.length)):null}));var Yf=function(){function t(t,e){if(this.DEFAULT_METHOD=\"POST\",null==e&&(e={}),this.weightPathPrefix=e.weightPathPrefix,this.onProgress=e.onProgress,null!=e.fetchFunc?(C(\"function\"==typeof e.fetchFunc,(function(){return\"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)\"})),this.fetch=e.fetchFunc):this.fetch=i().platform.fetch,C(null!=t&&t.length>0,(function(){return\"URL path for http must not be null, undefined or empty.\"})),Array.isArray(t)&&C(2===t.length,(function(){return\"URL paths for http must have a length of 2, (actual length is \"+t.length+\").\"})),this.path=t,null!=e.requestInit&&null!=e.requestInit.body)throw new Error(\"requestInit is expected to have no pre-existing body, but has one.\");this.requestInit=e.requestInit||{}}return t.prototype.save=function(t){return n(this,void 0,void 0,(function(){var e,n,o,a;return r(this,(function(r){switch(r.label){case 0:if(t.modelTopology instanceof ArrayBuffer)throw new Error(\"BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.\");return(e=Object.assign({method:this.DEFAULT_METHOD},this.requestInit)).body=new FormData,n=[{paths:[\"./model.weights.bin\"],weights:t.weightSpecs}],o={modelTopology:t.modelTopology,format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,userDefinedMetadata:t.userDefinedMetadata,weightsManifest:n},e.body.append(\"model.json\",new Blob([JSON.stringify(o)],{type:\"application/json\"}),\"model.json\"),null!=t.weightData&&e.body.append(\"model.weights.bin\",new Blob([t.weightData],{type:\"application/octet-stream\"}),\"model.weights.bin\"),[4,this.fetch(this.path,e)];case 1:if((a=r.sent()).ok)return[2,{modelArtifactsInfo:vf(t),responses:[a]}];throw new Error(\"BrowserHTTPRequest.save() failed due to HTTP response status \"+a.status+\".\")}}))}))},t.prototype.load=function(){return n(this,void 0,void 0,(function(){var t,e,n,o,a,i,s,u,c,l,h,f;return r(this,(function(r){switch(r.label){case 0:return[4,this.fetch(this.path,this.requestInit)];case 1:if(!(t=r.sent()).ok)throw new Error(\"Request to \"+this.path+\" failed with status code \"+t.status+\". Please verify this URL points to the model JSON of the model to load.\");r.label=2;case 2:return r.trys.push([2,4,,5]),[4,t.json()];case 3:return e=r.sent(),[3,5];case 4:throw r.sent(),n=\"Failed to parse model JSON of response from \"+this.path+\".\",this.path.endsWith(\".pb\")?n+=\" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.\":n+=\" Please make sure the server is serving valid JSON for this request.\",new Error(n);case 5:if(o=e.modelTopology,a=e.weightsManifest,i=e.generatedBy,s=e.convertedBy,u=e.format,c=e.userDefinedMetadata,null==o&&null==a)throw new Error(\"The JSON from HTTP path \"+this.path+\" contains neither model topology or manifest for weights.\");return null==a?[3,7]:[4,this.loadWeights(a)];case 6:f=r.sent(),l=f[0],h=f[1],r.label=7;case 7:return[2,{modelTopology:o,weightSpecs:l,weightData:h,userDefinedMetadata:c,generatedBy:i,convertedBy:s,format:u}]}}))}))},t.prototype.loadWeights=function(t){return n(this,void 0,void 0,(function(){var e,n,o,a,i,s,u,c,l,h,f;return r(this,(function(r){switch(r.label){case 0:for(e=Array.isArray(this.path)?this.path[1]:this.path,n=function(t){var e=t.lastIndexOf(\"/\"),n=t.lastIndexOf(\"?\"),r=t.substring(0,e),o=n>e?t.substring(n):\"\";return[r+\"/\",o]}(e),o=n[0],a=n[1],i=this.weightPathPrefix||o,s=[],u=0,c=t;u<c.length;u++)l=c[u],s.push.apply(s,l.weights);return h=[],t.forEach((function(t){t.paths.forEach((function(t){h.push(i+t+a)}))})),[4,jf(h,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress})];case 1:return f=r.sent(),[2,[s,df(f)]]}}))}))},t.URL_SCHEME_REGEX=/^https?:\\/\\//,t}();function $f(t){return null!=t.match(Yf.URL_SCHEME_REGEX)}var Qf=function(t,e){if(\"undefined\"==typeof fetch)return null;return(Array.isArray(t)?t.every((function(t){return $f(t)})):$f(t))?Jf(t,{onProgress:e}):null};function Jf(t,e){return new Yf(t,e)}mf.registerSaveRouter(Qf),mf.registerLoadRouter(Qf);var Zf=function(){function t(t){this.modelArtifacts=t}return t.prototype.load=function(){return n(this,void 0,void 0,(function(){return r(this,(function(t){return[2,this.modelArtifacts]}))}))},t}(),td=function(){function t(t){this.saveHandler=t}return t.prototype.save=function(t){return n(this,void 0,void 0,(function(){return r(this,(function(e){return[2,this.saveHandler(t)]}))}))},t}();var ed=Object.freeze({browserFiles:function(t){return new qf(t)},browserHTTPRequest:function(t,e){return Jf(t,e)},concatenateArrayBuffers:df,decodeWeights:cf,encodeWeights:function(t,e){return n(this,void 0,void 0,(function(){var o,a,i,s,u,c=this;return r(this,(function(l){switch(l.label){case 0:for(o=[],a=[],i=Array.isArray(t)?t.map((function(t){return t.name})):Object.keys(t),s=function(s){var u=i[s],l=Array.isArray(t)?t[s].tensor:t[u];if(\"float32\"!==l.dtype&&\"int32\"!==l.dtype&&\"bool\"!==l.dtype&&\"string\"!==l.dtype)throw new Error(\"Unsupported dtype in weight '\"+u+\"': \"+l.dtype);var h={name:u,shape:l.shape,dtype:l.dtype};if(\"string\"===l.dtype){var f=new Promise((function(t){return n(c,void 0,void 0,(function(){var e,n,o,a,i,s,u;return r(this,(function(r){switch(r.label){case 0:return[4,l.bytes()];case 1:for(e=r.sent(),n=e.reduce((function(t,e){return t+e.length}),0)+uf*e.length,o=new Uint8Array(n),a=0,i=0;i<e.length;i++)s=e[i],u=new Uint8Array(new Uint32Array([s.length]).buffer),o.set(u,a),a+=uf,o.set(s,a),a+=s.length;return t(o),[2]}}))}))}));a.push(f)}else a.push(l.data());null!=e&&(h.group=e),o.push(h)},u=0;u<i.length;++u)s(u);return[4,Promise.all(a)];case 1:return[2,{data:lf(l.sent()),specs:o}]}}))}))},fromMemory:function(t,e,n,r){return 1===arguments.length?null!=t.modelTopology||null!=t.weightSpecs?new Zf(t):(console.warn(\"Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release.\"),new Zf({modelTopology:t})):(console.warn(\"Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release.\"),new Zf({modelTopology:t,weightSpecs:e,weightData:n,trainingConfig:r}))},getLoadHandlers:function(t,e){return mf.getLoadHandlers(t,e)},getModelArtifactsInfoForJSON:vf,getSaveHandlers:function(t){return mf.getSaveHandlers(t)},http:Jf,isHTTPScheme:$f,loadWeights:function(t,e,o,a){return void 0===e&&(e=\"\"),n(this,void 0,void 0,(function(){return r(this,(function(n){return[2,Xf((function(t){return jf(t,{requestInit:a})}))(t,e,o)]}))}))},registerLoadRouter:function(t){return mf.registerLoadRouter(t)},registerSaveRouter:function(t){return mf.registerSaveRouter(t)},weightsLoaderFactory:Xf,withSaveHandler:function(t){return new td(t)},copyModel:function(t,e){return n(this,void 0,void 0,(function(){return r(this,(function(n){return!1,[2,bf(t,e,!1)]}))}))},listModels:function(){return n(this,void 0,void 0,(function(){var t,e,n,o,a,i,s;return r(this,(function(r){switch(r.label){case 0:t=yf.getSchemes(),e={},n=0,o=t,r.label=1;case 1:return n<o.length?(a=o[n],[4,yf.getManager(a).listModels()]):[3,4];case 2:for(s in i=r.sent())e[a+gf+s]=i[s];r.label=3;case 3:return n++,[3,1];case 4:return[2,e]}}))}))},moveModel:function(t,e){return n(this,void 0,void 0,(function(){return r(this,(function(n){return!0,[2,bf(t,e,!0)]}))}))},removeModel:function(t){return n(this,void 0,void 0,(function(){var e;return r(this,(function(n){return e=xf(t),[2,yf.getManager(e.scheme).removeModel(e.path)]}))}))}});var nd,rd=An({confusionMatrix_:function(t,e,n){var r=mn(t,\"labels\",\"confusionMatrix\"),o=mn(e,\"predictions\",\"confusionMatrix\");C(null==n||n>0&&Number.isInteger(n),(function(){return\"If provided, numClasses must be a positive integer, but got \"+n})),C(1===r.rank,(function(){return\"Expected the rank of labels to be 1, but got \"+r.rank})),C(1===o.rank,(function(){return\"Expected the rank of predictions to be 1, but got \"+o.rank})),C(r.shape[0]===o.shape[0],(function(){return\"Mismatch in the number of examples: \"+r.shape[0]+\" vs. \"+o.shape[0]+\". Labels and predictions should have the same number of elements.\"})),C(n>0&&Number.isInteger(n),(function(){return\"numClasses is required to be a positive integer, but got \"+n}));var a=Rr(r.asType(\"int32\"),n),i=Rr(o.asType(\"int32\"),n);return a.transpose().matMul(i).asType(\"int32\")}}),od=Object.freeze({confusionMatrix:rd});var ad=An({fromPixels_:function(t,e){if(void 0===e&&(e=3),e>4)throw new Error(\"Cannot construct Tensor with more than 4 channels from pixels.\");if(null==t)throw new Error(\"pixels passed to tf.browser.fromPixels() can not be null\");var n=!1,r=!1,o=!1,a=!1,i=!1;if(t.data instanceof Uint8Array)n=!0;else if(\"undefined\"!=typeof ImageData&&t instanceof ImageData)r=!0;else if(\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement)o=!0;else if(\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement)a=!0;else{if(null==t.getContext)throw new Error(\"pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was \"+t.constructor.name);i=!0}if(o){if(o&&t.readyState<2)throw new Error(\"The video element has not loaded data yet. 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Actual: \"+o+\". Expected: \"+a)}if(Array.isArray(t)&&Array.isArray(e)){var i=pn(t),s=pn(e);if(!S(i,s))throw new Error(\"Arrays have different shapes. Actual: [\"+i+\"]. Expected: [\"+s+\"]\")}var u=V(t)?t:I(t),c=V(e)?e:I(e);if(u.length!==c.length)throw new Error(\"Arrays have different lengths actual: \"+u.length+\" vs expected: \"+c.length+\".\\nActual:   \"+u+\".\\nExpected: \"+c+\".\");for(var l=0;l<c.length;++l){var h=u[l],f=c[l];if(!n(h,f))throw new Error(\"Arrays differ: actual[\"+l+\"] = \"+h+\", expected[\"+l+\"] = \"+f+\".\\nActual:   \"+u+\".\\nExpected: \"+c+\".\")}}function vd(t,e,n){return!isFinite(t)&&!isFinite(e)||!(isNaN(t)||isNaN(e)||Math.abs(t-e)>n)}var md=Object.freeze({TEST_EPSILON_FLOAT16:fd,expectArraysClose:function(t,e,n){return null==n&&(n=dd()),pd(t,e,(function(t,e){return vd(t,e,n)}))},testEpsilon:dd,expectPromiseToFail:function(t,e){t().then((function(){return e.fail()}),(function(){return e()}))},expectArraysEqual:function(t,e){var n=\"string\"==typeof e||\"number\"==typeof e||\"boolean\"==typeof e?[e]:e;return H(t)||H(t[0])||H(e)||H(e[0])?pd(t,n,(function(t,e){return t==e})):pd(t,e,(function(t,e){return vd(t,e,0)}))},expectNumbersClose:function(t,e,n){if(null==n&&(n=dd()),!vd(t,e,n))throw new Error(\"Numbers differ: actual === \"+t+\", expected === \"+e)},expectValuesInRange:function(t,e,n){for(var r=0;r<t.length;r++)if(t[r]<e||t[r]>n)throw new Error(\"Value out of range:\"+t[r]+\" low: \"+e+\", high: \"+n)},expectArrayBuffersEqual:function(t,e){expect(new Float32Array(t)).toEqual(new Float32Array(e))}}),gd=\"1.7.0\";var yd=Object.freeze({gpgpu_util:Mi,webgl_util:Ge,forceHalfFloat:function(){i().set(\"WEBGL_FORCE_F16_TEXTURES\",!0)},MathBackendWebGL:Zs,setWebGLContext:Kt,GPGPUContext:Bi}),xd=function(t){function o(){return null!==t&&t.apply(this,arguments)||this}return e(o,t),o.prototype.minimize=function(t,e,n){void 0===e&&(e=!1);var r=this.computeGradients(t,n),o=r.value,a=r.grads;if(null!=n){var i=n.map((function(t){return{name:t.name,tensor:a[t.name]}}));this.applyGradients(i)}else this.applyGradients(a);return tn(a),e?o:(o.dispose(),null)},Object.defineProperty(o.prototype,\"iterations\",{get:function(){return null==this.iterations_&&(this.iterations_=0),this.iterations_},enumerable:!0,configurable:!0}),o.prototype.incrementIterations=function(){this.iterations_=this.iterations+1},o.prototype.computeGradients=function(t,e){return po(t,e)},o.prototype.dispose=function(){null!=this.iterations_&&tn(this.iterations_)},o.prototype.saveIterations=function(){return n(this,void 0,void 0,(function(){return r(this,(function(t){return null==this.iterations_&&(this.iterations_=0),[2,{name:\"iter\",tensor:On(this.iterations_,\"int32\")}]}))}))},o.prototype.getWeights=function(){return n(this,void 0,void 0,(function(){return r(this,(function(t){throw new Error(\"getWeights() is not implemented for this optimizer yet.\")}))}))},o.prototype.setWeights=function(t){return n(this,void 0,void 0,(function(){return r(this,(function(t){throw new Error(\"setWeights() is not implemented for this optimizer class 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Xn(o).variable(!1)}))}),null==e.accumulatedUpdates[r]&&(e.accumulatedUpdates[r]={originalName:n+\"/accum_var\",variable:Ze((function(){return Xn(o).variable(!1)}))});var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var i=e.accumulatedGrads[r].variable,s=e.accumulatedUpdates[r].variable;Ze((function(){var t=i.mul(e.rho).add(a.square().mul(1-e.rho)),n=s.add(e.epsilon).sqrt().div(i.add(e.epsilon).sqrt()).mul(a),r=s.mul(e.rho).add(n.square().mul(1-e.rho));i.assign(t),s.assign(r);var u=n.mul(-e.learningRate).add(o);o.assign(u)}))}})),this.incrementIterations()},o.prototype.dispose=function(){null!=this.accumulatedUpdates&&(tn(this.accumulatedGrads.map((function(t){return t.variable}))),tn(this.accumulatedUpdates.map((function(t){return t.variable}))))},o.prototype.getWeights=function(){return n(this,void 0,void 0,(function(){var t;return r(this,(function(e){switch(e.label){case 0:return t=this.accumulatedGrads.concat(this.accumulatedUpdates),[4,this.saveIterations()];case 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e=this;(Array.isArray(t)?t.map((function(t){return t.name})):Object.keys(t)).forEach((function(n,r){var o=Lt.registeredVariables[n];if(null==e.accumulatedGrads[r]){e.accumulatedGrads[r]={originalName:n+\"/accumulator\",variable:Ze((function(){return Hn(o.shape,e.initialAccumulatorValue).variable(!1)}))}}var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var i=e.accumulatedGrads[r].variable;Ze((function(){var t=i.add(a.square());i.assign(t);var n=a.div(t.add(Lt.backend.epsilon()).sqrt()).mul(-e.learningRate).add(o);o.assign(n)}))}})),this.incrementIterations()},o.prototype.dispose=function(){null!=this.accumulatedGrads&&tn(this.accumulatedGrads.map((function(t){return t.variable})))},o.prototype.getWeights=function(){return n(this,void 0,void 0,(function(){return r(this,(function(t){switch(t.label){case 0:return[4,this.saveIterations()];case 1:return[2,[t.sent()].concat(this.accumulatedGrads.map((function(t){return{name:t.originalName,tensor:t.variable}})))]}}))}))},o.prototype.setWeights=function(t){return n(this,void 0,void 0,(function(){return r(this,(function(e){switch(e.label){case 0:return[4,this.extractIterations(t)];case 1:return t=e.sent(),!1,this.accumulatedGrads=t.map((function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}})),[2]}}))}))},o.prototype.getConfig=function(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}},o.fromConfig=function(t,e){return new t(e.learningRate,e.initialAccumulatorValue)},o.className=\"Adagrad\",o}(xd);cd(wd);var Cd=function(t){function o(e,n,r,o){void 0===o&&(o=null);var a=t.call(this)||this;return a.learningRate=e,a.beta1=n,a.beta2=r,a.epsilon=o,a.accumulatedFirstMoment=[],a.accumulatedSecondMoment=[],Ze((function(){a.accBeta1=On(n).variable(),a.accBeta2=On(r).variable()})),null==o&&(a.epsilon=Lt.backend.epsilon()),a}return e(o,t),o.prototype.applyGradients=function(t){var e=this,n=Array.isArray(t)?t.map((function(t){return t.name})):Object.keys(t);Ze((function(){var r=Cc(1,e.accBeta1),o=Cc(1,e.accBeta2);n.forEach((function(n,a){var i=Lt.registeredVariables[n];null==e.accumulatedFirstMoment[a]&&(e.accumulatedFirstMoment[a]={originalName:n+\"/m\",variable:Ze((function(){return Xn(i).variable(!1)}))}),null==e.accumulatedSecondMoment[a]&&(e.accumulatedSecondMoment[a]={originalName:n+\"/v\",variable:Ze((function(){return Xn(i).variable(!1)}))});var s=Array.isArray(t)?t[a].tensor:t[n];if(null!=s){var u=e.accumulatedFirstMoment[a].variable,c=e.accumulatedSecondMoment[a].variable,l=u.mul(e.beta1).add(s.mul(1-e.beta1)),h=c.mul(e.beta2).add(s.square().mul(1-e.beta2)),f=l.div(r),d=h.div(o);u.assign(l),c.assign(h);var p=f.div(d.sqrt().add(e.epsilon)).mul(-e.learningRate).add(i);i.assign(p)}})),e.accBeta1.assign(e.accBeta1.mul(e.beta1)),e.accBeta2.assign(e.accBeta2.mul(e.beta2))})),this.incrementIterations()},o.prototype.dispose=function(){this.accBeta1.dispose(),this.accBeta2.dispose(),null!=this.accumulatedFirstMoment&&tn(this.accumulatedFirstMoment.map((function(t){return t.variable}))),null!=this.accumulatedSecondMoment&&tn(this.accumulatedSecondMoment.map((function(t){return t.variable})))},o.prototype.getWeights=function(){return n(this,void 0,void 0,(function(){var t;return r(this,(function(e){switch(e.label){case 0:return t=this.accumulatedFirstMoment.concat(this.accumulatedSecondMoment),[4,this.saveIterations()];case 1:return[2,[e.sent()].concat(t.map((function(t){return{name:t.originalName,tensor:t.variable}})))]}}))}))},o.prototype.setWeights=function(t){return n(this,void 0,void 0,(function(){var e,n=this;return r(this,(function(r){switch(r.label){case 0:return[4,this.extractIterations(t)];case 1:return t=r.sent(),Ze((function(){n.accBeta1.assign(xc(n.beta1,n.iterations_+1)),n.accBeta2.assign(xc(n.beta2,n.iterations_+1))})),e=t.length/2,!1,this.accumulatedFirstMoment=t.slice(0,e).map((function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}})),this.accumulatedSecondMoment=t.slice(e,2*e).map((function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}})),[2]}}))}))},o.prototype.getConfig=function(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}},o.fromConfig=function(t,e){return new t(e.learningRate,e.beta1,e.beta2,e.epsilon)},o.className=\"Adam\",o}(xd);cd(Cd);var Ed=function(t){function o(e,n,r,o,a){void 0===o&&(o=null),void 0===a&&(a=0);var i=t.call(this)||this;return i.learningRate=e,i.beta1=n,i.beta2=r,i.epsilon=o,i.decay=a,i.accumulatedFirstMoment=[],i.accumulatedWeightedInfNorm=[],Ze((function(){i.iteration=On(0).variable(),i.accBeta1=On(n).variable()})),null==o&&(i.epsilon=Lt.backend.epsilon()),i}return e(o,t),o.prototype.applyGradients=function(t){var e=this,n=Array.isArray(t)?t.map((function(t){return t.name})):Object.keys(t);Ze((function(){var r=Cc(1,e.accBeta1),o=sc(-e.learningRate,e.iteration.mul(e.decay).add(1));n.forEach((function(n,a){var i=Lt.registeredVariables[n];null==e.accumulatedFirstMoment[a]&&(e.accumulatedFirstMoment[a]={originalName:n+\"/m\",variable:Xn(i).variable(!1)}),null==e.accumulatedWeightedInfNorm[a]&&(e.accumulatedWeightedInfNorm[a]={originalName:n+\"/v\",variable:Xn(i).variable(!1)});var s=Array.isArray(t)?t[a].tensor:t[n];if(null!=s){var u=e.accumulatedFirstMoment[a].variable,c=e.accumulatedWeightedInfNorm[a].variable,l=u.mul(e.beta1).add(s.mul(1-e.beta1)),h=c.mul(e.beta2),f=s.abs(),d=h.maximum(f);u.assign(l),c.assign(d);var p=o.div(r).mul(l.div(d.add(e.epsilon))).add(i);i.assign(p)}})),e.iteration.assign(e.iteration.add(1)),e.accBeta1.assign(e.accBeta1.mul(e.beta1))})),this.incrementIterations()},o.prototype.dispose=function(){this.accBeta1.dispose(),this.iteration.dispose(),null!=this.accumulatedFirstMoment&&tn(this.accumulatedFirstMoment.map((function(t){return t.variable}))),null!=this.accumulatedWeightedInfNorm&&tn(this.accumulatedWeightedInfNorm.map((function(t){return t.variable})))},o.prototype.getWeights=function(){return n(this,void 0,void 0,(function(){return r(this,(function(t){throw new Error(\"getWeights() is not implemented for Adamax yet.\")}))}))},o.prototype.setWeights=function(t){return n(this,void 0,void 0,(function(){return r(this,(function(t){throw new Error(\"setWeights() is not implemented for Adamax yet.\")}))}))},o.prototype.getConfig=function(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}},o.fromConfig=function(t,e){return new t(e.learningRate,e.beta1,e.beta2,e.epsilon,e.decay)},o.className=\"Adamax\",o}(xd);cd(Ed);var Rd=function(t){function o(e){var n=t.call(this)||this;return n.learningRate=e,n.setLearningRate(e),n}return e(o,t),o.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map((function(t){return t.name})):Object.keys(t)).forEach((function(n,r){var o=Array.isArray(t)?t[r].tensor:t[n];if(null!=o){var a=Lt.registeredVariables[n];Ze((function(){var t=e.c.mul(o).add(a);a.assign(t)}))}})),this.incrementIterations()},o.prototype.setLearningRate=function(t){this.learningRate=t,null!=this.c&&this.c.dispose(),this.c=en(On(-t))},o.prototype.dispose=function(){this.c.dispose()},o.prototype.getWeights=function(){return n(this,void 0,void 0,(function(){return r(this,(function(t){switch(t.label){case 0:return[4,this.saveIterations()];case 1:return[2,[t.sent()]]}}))}))},o.prototype.setWeights=function(t){return n(this,void 0,void 0,(function(){return r(this,(function(e){switch(e.label){case 0:return[4,this.extractIterations(t)];case 1:if(0!==(t=e.sent()).length)throw new Error(\"SGD optimizer does not have settable weights.\");return[2]}}))}))},o.prototype.getConfig=function(){return{learningRate:this.learningRate}},o.fromConfig=function(t,e){return new t(e.learningRate)},o.className=\"SGD\",o}(xd);cd(Rd);var Id=function(t){function o(e,n,r){void 0===r&&(r=!1);var o=t.call(this,e)||this;return o.learningRate=e,o.momentum=n,o.useNesterov=r,o.accumulations=[],o.m=On(o.momentum),o}return e(o,t),o.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map((function(t){return t.name})):Object.keys(t)).forEach((function(n,r){var o=Lt.registeredVariables[n];if(null==e.accumulations[r]){e.accumulations[r]={originalName:n+\"/momentum\",variable:Ze((function(){return Xn(o).variable(!1)}))}}var a=e.accumulations[r].variable,i=Array.isArray(t)?t[r].tensor:t[n];null!=i&&Ze((function(){var t,n=e.m.mul(a).add(i);t=e.useNesterov?e.c.mul(i.add(n.mul(e.m))).add(o):e.c.mul(n).add(o),a.assign(n),o.assign(t)}))})),this.incrementIterations()},o.prototype.dispose=function(){this.m.dispose(),null!=this.accumulations&&tn(this.accumulations.map((function(t){return t.variable})))},o.prototype.setMomentum=function(t){this.momentum=t},o.prototype.getWeights=function(){return n(this,void 0,void 0,(function(){return r(this,(function(t){switch(t.label){case 0:return[4,this.saveIterations()];case 1:return[2,[t.sent()].concat(this.accumulations.map((function(t){return{name:t.originalName,tensor:t.variable}})))]}}))}))},o.prototype.setWeights=function(t){return n(this,void 0,void 0,(function(){return r(this,(function(e){switch(e.label){case 0:return[4,this.extractIterations(t)];case 1:return t=e.sent(),!1,this.accumulations=t.map((function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}})),[2]}}))}))},o.prototype.getConfig=function(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}},o.fromConfig=function(t,e){return new t(e.learningRate,e.momentum,e.useNesterov)},o.className=\"Momentum\",o}(Rd);cd(Id);var kd=function(t){function o(e,n,r,o,a){void 0===n&&(n=.9),void 0===r&&(r=0),void 0===o&&(o=null),void 0===a&&(a=!1);var i=t.call(this)||this;if(i.learningRate=e,i.decay=n,i.momentum=r,i.epsilon=o,i.accumulatedMeanSquares=[],i.accumulatedMoments=[],i.accumulatedMeanGrads=[],i.centered=a,null==o&&(i.epsilon=Lt.backend.epsilon()),null==e)throw new Error(\"learningRate for RMSPropOptimizer must be defined.\");return i}return e(o,t),o.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map((function(t){return t.name})):Object.keys(t)).forEach((function(n,r){var o=Lt.registeredVariables[n];null==e.accumulatedMeanSquares[r]&&(e.accumulatedMeanSquares[r]={originalName:n+\"/rms\",variable:Ze((function(){return Xn(o).variable(!1)}))}),null==e.accumulatedMoments[r]&&(e.accumulatedMoments[r]={originalName:n+\"/momentum\",variable:Ze((function(){return Xn(o).variable(!1)}))}),null==e.accumulatedMeanGrads[r]&&e.centered&&(e.accumulatedMeanGrads[r]={originalName:n+\"/mg\",variable:Ze((function(){return Xn(o).variable(!1)}))});var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var i=e.accumulatedMeanSquares[r].variable,s=e.accumulatedMoments[r].variable;Ze((function(){var t=i.mul(e.decay).add(a.square().mul(1-e.decay));if(e.centered){var n=e.accumulatedMeanGrads[r].variable,u=n.mul(e.decay).add(a.mul(1-e.decay)),c=s.mul(e.momentum).add(a.mul(e.learningRate).div(t.sub(u.square().add(e.epsilon)).sqrt()));i.assign(t),n.assign(u),s.assign(c);var l=o.sub(c);o.assign(l)}else{var h=i.mul(e.decay).add(a.square().mul(1-e.decay));c=s.mul(e.momentum).add(a.mul(e.learningRate).div(h.add(e.epsilon).sqrt()));i.assign(h),s.assign(c);l=o.sub(c);o.assign(l)}}))}})),this.incrementIterations()},o.prototype.dispose=function(){null!=this.accumulatedMeanSquares&&tn(this.accumulatedMeanSquares.map((function(t){return t.variable}))),null!=this.accumulatedMeanGrads&&this.centered&&tn(this.accumulatedMeanGrads.map((function(t){return t.variable}))),null!=this.accumulatedMoments&&tn(this.accumulatedMoments.map((function(t){return t.variable})))},o.prototype.getWeights=function(){return n(this,void 0,void 0,(function(){var t;return r(this,(function(e){switch(e.label){case 0:return t=this.accumulatedMeanSquares.concat(this.accumulatedMoments),this.centered&&t.push.apply(t,this.accumulatedMeanGrads),[4,this.saveIterations()];case 1:return[2,[e.sent()].concat(t.map((function(t){return{name:t.originalName,tensor:t.variable}})))]}}))}))},o.prototype.setWeights=function(t){return n(this,void 0,void 0,(function(){var e;return r(this,(function(n){switch(n.label){case 0:return[4,this.extractIterations(t)];case 1:return t=n.sent(),e=this.centered?t.length/3:t.length/2,!1,this.accumulatedMeanSquares=t.slice(0,e).map((function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}})),this.accumulatedMoments=t.slice(e,2*e).map((function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}})),this.centered&&(this.accumulatedMeanGrads=t.slice(2*e,3*e).map((function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}))),[2]}}))}))},o.prototype.getConfig=function(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}},o.fromConfig=function(t,e){return new t(e.learningRate,e.decay,e.momentum,e.epsilon,e.centered)},o.className=\"RMSProp\",o}(xd);cd(kd);var Sd=function(){function t(){}return t.sgd=function(t){return new Rd(t)},t.momentum=function(t,e,n){return void 0===n&&(n=!1),new Id(t,e,n)},t.rmsprop=function(t,e,n,r,o){return void 0===e&&(e=.9),void 0===n&&(n=0),void 0===r&&(r=null),void 0===o&&(o=!1),new kd(t,e,n,r,o)},t.adam=function(t,e,n,r){return void 0===t&&(t=.001),void 0===e&&(e=.9),void 0===n&&(n=.999),void 0===r&&(r=null),new Cd(t,e,n,r)},t.adadelta=function(t,e,n){return void 0===t&&(t=.001),void 0===e&&(e=.95),void 0===n&&(n=null),new bd(t,e,n)},t.adamax=function(t,e,n,r,o){return void 0===t&&(t=.002),void 0===e&&(e=.9),void 0===n&&(n=.999),void 0===r&&(r=null),void 0===o&&(o=0),new Ed(t,e,n,r,o)},t.adagrad=function(t,e){return void 0===e&&(e=.1),new wd(t,e)},t}(),Ad={sgd:Sd.sgd,momentum:Sd.momentum,adadelta:Sd.adadelta,adagrad:Sd.adagrad,rmsprop:Sd.rmsprop,adamax:Sd.adamax,adam:Sd.adam},Dd=\"undefined\"!=typeof requestAnimationFrame?requestAnimationFrame:\"undefined\"!=typeof setImmediate?setImmediate:function(t){return t()};function Td(){return new Promise((function(t){return Dd((function(){return t()}))}))}wt.prototype.squaredDifference=function(t){return nu(this,t)},xt=Gh;export{bd as AdadeltaOptimizer,wd as AdagradOptimizer,Cd as AdamOptimizer,Ed as AdamaxOptimizer,xo as DataStorage,s as ENV,o as Environment,bo as KernelBackend,Id as MomentumOptimizer,xd as Optimizer,kd as RMSPropOptimizer,Ct as Rank,ch as Reduction,Rd as SGDOptimizer,wt as Tensor,gt as TensorBuffer,St as Variable,ru as abs,ou as acos,au as acosh,rc as add,oc as addN,ac as addStrict,Cl as all,El as any,Rl as argMax,Il as argMin,iu as asin,su as asinh,uu as atan,ic as atan2,cu as atanh,fl as avgPool,vl as avgPool3d,hn as backend,Uo as backend_util,zl as basicLSTMCell,ju as batchNorm,Xu as batchNorm2d,Yu as batchNorm3d,$u as batchNorm4d,Ku as batchNormalization,Gu as batchNormalization2d,Hu as batchNormalization3d,qu as batchNormalization4d,vr as batchToSpaceND,Uc as booleanMaskAsync,mr as broadcastTo,id as browser,dr as buffer,gr as cast,lu as ceil,hu as clipByValue,yr as clone,Dn as complex,Yn as concat,$n as concat1d,Qn as concat2d,Jn as concat3d,Zn as concat4d,Hc as conv1d,qc as conv2d,Zc as conv2dTranspose,Kc as conv3d,tl as conv3dTranspose,fu as cos,du as cosh,xr as cumsum,vo as customGrad,Xe as deprecationWarn,br as depthToSpace,Yc as depthwiseConv2d,eh as diag,je as disableDeprecationWarnings,tn as dispose,Ye as disposeVariables,sc as div,uc as divNoNan,cc as divStrict,nl as dot,nh as dropout,_l as elu,Ke as enableDebugMode,qe as enableProdMode,$e as engine,i as env,Rc as equal,Ic as equalStrict,pu as erf,vu as exp,wr as expandDims,mu as expm1,Cr as eye,Xl as fft,Hn as fill,un as findBackend,cn as findBackendFactory,gu as floor,lc as floorDiv,ih as frame,zh as fused,Lc as gather,th as gatherND,Xr as gather_util,an as getBackend,h as getGradient,l as getKernel,f as getKernelsForBackend,co as grad,lo as grads,kc as greater,Sc as greaterEqual,Ac as greaterEqualStrict,Dc as greaterStrict,ah as hammingWindow,oh as hannWindow,Yl as ifft,Nn as imag,Oh as image,lh as inTopKAsync,ed as io,Ql as irfft,Du as isFinite,Au as isInf,Su as isNaN,en as keep,Ol as leakyRelu,Tc as less,Nc as lessEqual,Fc as lessEqualStrict,_c as lessStrict,Ih as linalg,qn as linspace,Ul as localResponseNormalization,yu as log,xu as log1p,bu as logSigmoid,yo as logSoftmax,kl as logSumExp,Qu as logicalAnd,Ju as logicalNot,Zu as logicalOr,tc as logicalXor,bh as losses,el as matMul,od as math,Sl as max,hl as maxPool,pl as maxPool3d,hc as maximum,fc as maximumStrict,Al as mean,Qe as memory,Dl as min,dc as minimum,pc as minimumStrict,vc as mod,mc as modStrict,Tl as moments,Hl as movingAverage,gc as mul,yc as mulStrict,Gl as multiRNNCell,Er as multinomial,wu as neg,Td as nextFrame,Vl as norm,Oc as notEqual,Mc as notEqualStrict,Rr as oneHot,zn as ones,jn as onesLike,An as op,rl as outerProduct,Ir as pad,kr as pad1d,Sr as pad2d,Ar as pad3d,Dr as pad4d,dl as pool,xc as pow,bc as powStrict,Ml as prelu,pr as print,Fl as prod,Je as profile,Tr as rand,Fr as randomGamma,Nr as randomNormal,_r as randomUniform,Kn as range,on as ready,Tn as real,Cu as reciprocal,ln as registerBackend,p as registerGradient,d as registerKernel,Bl as relu,Pl as relu6,sn as removeBackend,Or as reshape,ol as reverse,al as reverse1d,il as reverse2d,sl as reverse3d,ul as reverse4d,$l as rfft,Eu as round,Ru as rsqrt,On as scalar,jl as scatterND,to as scatter_util,Ll as selu,Jc as separableConv2d,ld as serialization,rn as setBackend,fn as setPlatform,Vr as setdiff1dAsync,Iu as sigmoid,ku as sign,uh as signal,Tu as sin,Nu as sinh,ml as slice,gl as slice1d,yl as slice2d,xl as slice3d,bl as slice4d,uo as slice_util,go as softmax,Fu as softplus,Mr as spaceToBatchND,Zl as sparseToDense,Jl as spectral,tr as split,_u as sqrt,tu as square,nu as squaredDifference,wc as squaredDifferenceStrict,Br as squeeze,Pr as stack,Ou as step,sh as stft,ql as stridedSlice,Cc as sub,Ec as subStrict,Nl as sum,Tt as sumOutType,Mu as tan,Bu as tanh,Fn as tensor,Mn as tensor1d,Bn as tensor2d,Pn as tensor3d,Ln as tensor4d,Wn as tensor5d,Un as tensor6d,Mt as tensor_util,md as test_util,Ze as tidy,Lr as tile,nn as time,Kl as topk,Ad as train,Wl as transpose,Wr as truncatedNormal,m as unregisterGradient,v as unregisterKernel,Wc as unsortedSegmentSum,Ur as unstack,st as util,ho as valueAndGrad,fo as valueAndGrads,Vn as variable,po as variableGrads,gd as version_core,yd as webgl,ec as where,nc as whereAsync,Gn as zeros,Xn as zerosLike};\n//# sourceMappingURL=tf-core.esm.js.map\n","import { Point } from '../classes';\r\n\r\nexport function drawContour(\r\n  ctx: CanvasRenderingContext2D,\r\n  points: Point[],\r\n  isClosed: boolean = false\r\n) {\r\n  ctx.beginPath()\r\n\r\n  points.slice(1).forEach(({ x, y }, prevIdx) => {\r\n    const from = points[prevIdx]\r\n    ctx.moveTo(from.x, from.y)\r\n    ctx.lineTo(x, y)\r\n  })\r\n\r\n  if (isClosed) {\r\n    const from = points[points.length - 1]\r\n    const to = points[0]\r\n    if (!from || !to) {\r\n      return\r\n    }\r\n\r\n    ctx.moveTo(from.x, from.y)\r\n    ctx.lineTo(to.x, to.y)\r\n  }\r\n\r\n  ctx.stroke()\r\n}","import { isValidNumber } from '../utils';\r\n\r\nexport interface IDimensions {\r\n  width: number\r\n  height: number\r\n}\r\n\r\nexport class Dimensions implements IDimensions {\r\n\r\n  private _width: number\r\n  private _height: number\r\n\r\n  constructor(width: number, height: number) {\r\n    if (!isValidNumber(width) || !isValidNumber(height)) {\r\n      throw new Error(`Dimensions.constructor - expected width and height to be valid numbers, instead have ${JSON.stringify({ width, height })}`)\r\n    }\r\n\r\n    this._width = width\r\n    this._height = height\r\n  }\r\n\r\n  public get width(): number { return this._width }\r\n  public get height(): number { return this._height }\r\n\r\n  public reverse(): Dimensions {\r\n    return new Dimensions(1 / this.width, 1 / this.height)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Point } from '../classes';\r\nimport { Dimensions, IDimensions } from '../classes/Dimensions';\r\n\r\nexport function isTensor(tensor: any, dim: number) {\r\n  return tensor instanceof tf.Tensor && tensor.shape.length === dim\r\n}\r\n\r\nexport function isTensor1D(tensor: any): tensor is tf.Tensor1D {\r\n  return isTensor(tensor, 1)\r\n}\r\n\r\nexport function isTensor2D(tensor: any): tensor is tf.Tensor2D {\r\n  return isTensor(tensor, 2)\r\n}\r\n\r\nexport function isTensor3D(tensor: any): tensor is tf.Tensor3D {\r\n  return isTensor(tensor, 3)\r\n}\r\n\r\nexport function isTensor4D(tensor: any): tensor is tf.Tensor4D {\r\n  return isTensor(tensor, 4)\r\n}\r\n\r\nexport function isFloat(num: number) {\r\n  return num % 1 !== 0\r\n}\r\n\r\nexport function isEven(num: number) {\r\n  return num % 2 === 0\r\n}\r\n\r\nexport function round(num: number, prec: number = 2) {\r\n  const f = Math.pow(10, prec)\r\n  return Math.floor(num * f) / f\r\n}\r\n\r\nexport function isDimensions(obj: any): boolean {\r\n  return obj && obj.width && obj.height\r\n}\r\n\r\nexport function computeReshapedDimensions({ width, height }: IDimensions, inputSize: number) {\r\n  const scale = inputSize / Math.max(height, width)\r\n  return new Dimensions(Math.round(width * scale), Math.round(height * scale))\r\n}\r\n\r\nexport function getCenterPoint(pts: Point[]): Point {\r\n  return pts.reduce((sum, pt) => sum.add(pt), new Point(0, 0))\r\n    .div(new Point(pts.length, pts.length))\r\n}\r\n\r\nexport function range(num: number, start: number, step: number): number[] {\r\n  return Array(num).fill(0).map((_, i) => start + (i * step))\r\n}\r\n\r\nexport function isValidNumber(num: any) {\r\n  return !!num && num !== Infinity && num !== -Infinity && !isNaN(num) || num === 0\r\n}\r\n\r\nexport function isValidProbablitiy(num: any) {\r\n  return isValidNumber(num) && 0 <= num && num <= 1.0\r\n}","export interface IPoint {\r\n  x: number\r\n  y: number\r\n}\r\n\r\nexport class Point implements IPoint {\r\n  private _x: number\r\n  private _y: number\r\n\r\n  constructor(x: number, y: number) {\r\n    this._x = x\r\n    this._y = y\r\n  }\r\n\r\n  get x(): number { return this._x }\r\n  get y(): number { return this._y }\r\n\r\n  public add(pt: IPoint): Point {\r\n    return new Point(this.x + pt.x, this.y + pt.y)\r\n  }\r\n\r\n  public sub(pt: IPoint): Point {\r\n    return new Point(this.x - pt.x, this.y - pt.y)\r\n  }\r\n\r\n  public mul(pt: IPoint): Point {\r\n    return new Point(this.x * pt.x, this.y * pt.y)\r\n  }\r\n\r\n  public div(pt: IPoint): Point {\r\n    return new Point(this.x / pt.x, this.y / pt.y)\r\n  }\r\n\r\n  public abs(): Point {\r\n    return new Point(Math.abs(this.x), Math.abs(this.y))\r\n  }\r\n\r\n  public magnitude(): number {\r\n    return Math.sqrt(Math.pow(this.x, 2) + Math.pow(this.y, 2))\r\n  }\r\n\r\n  public floor(): Point {\r\n    return new Point(Math.floor(this.x), Math.floor(this.y))\r\n  }\r\n}","import { isDimensions, isValidNumber } from '../utils';\r\nimport { IBoundingBox } from './BoundingBox';\r\nimport { IDimensions } from './Dimensions';\r\nimport { Point } from './Point';\r\nimport { IRect } from './Rect';\r\n\r\nexport class Box<BoxType = any> implements IBoundingBox, IRect {\r\n\r\n  public static isRect(rect: any): boolean {\r\n    return !!rect && [rect.x, rect.y, rect.width, rect.height].every(isValidNumber)\r\n  }\r\n\r\n  public static assertIsValidBox(box: any, callee: string, allowNegativeDimensions: boolean = false) {\r\n    if (!Box.isRect(box)) {\r\n      throw new Error(`${callee} - invalid box: ${JSON.stringify(box)}, expected object with properties x, y, width, height`)\r\n    }\r\n\r\n    if (!allowNegativeDimensions && (box.width < 0 || box.height < 0)) {\r\n      throw new Error(`${callee} - width (${box.width}) and height (${box.height}) must be positive numbers`)\r\n    }\r\n  }\r\n\r\n  private _x: number\r\n  private _y: number\r\n  private _width: number\r\n  private _height: number\r\n\r\n  constructor(_box: IBoundingBox | IRect, allowNegativeDimensions: boolean = true) {\r\n    const box = (_box || {}) as any\r\n\r\n    const isBbox = [box.left, box.top, box.right, box.bottom].every(isValidNumber)\r\n    const isRect = [box.x, box.y, box.width, box.height].every(isValidNumber)\r\n\r\n    if (!isRect && !isBbox) {\r\n      throw new Error(`Box.constructor - expected box to be IBoundingBox | IRect, instead have ${JSON.stringify(box)}`)\r\n    }\r\n\r\n    const [x, y, width, height] = isRect\r\n      ? [box.x, box.y, box.width, box.height]\r\n      : [box.left, box.top, box.right - box.left, box.bottom - box.top]\r\n\r\n    Box.assertIsValidBox({ x, y, width, height }, 'Box.constructor', allowNegativeDimensions)\r\n\r\n    this._x = x\r\n    this._y = y\r\n    this._width = width\r\n    this._height = height\r\n  }\r\n\r\n  public get x(): number { return this._x }\r\n  public get y(): number { return this._y }\r\n  public get width(): number { return this._width }\r\n  public get height(): number { return this._height }\r\n  public get left(): number { return this.x }\r\n  public get top(): number { return this.y }\r\n  public get right(): number { return this.x + this.width }\r\n  public get bottom(): number { return this.y + this.height }\r\n  public get area(): number { return this.width * this.height }\r\n  public get topLeft(): Point { return new Point(this.left, this.top) }\r\n  public get topRight(): Point { return new Point(this.right, this.top) }\r\n  public get bottomLeft(): Point { return new Point(this.left, this.bottom) }\r\n  public get bottomRight(): Point { return new Point(this.right, this.bottom) }\r\n\r\n  public round(): Box<BoxType> {\r\n    const [x, y, width, height] = [this.x, this.y, this.width, this.height]\r\n      .map(val => Math.round(val))\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public floor(): Box<BoxType> {\r\n    const [x, y, width, height] = [this.x, this.y, this.width, this.height]\r\n      .map(val => Math.floor(val))\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public toSquare(): Box<BoxType> {\r\n    let { x, y, width, height } = this\r\n    const diff = Math.abs(width - height)\r\n    if (width < height) {\r\n      x -= (diff / 2)\r\n      width += diff\r\n    }\r\n    if (height < width) {\r\n      y -= (diff / 2)\r\n      height += diff\r\n    }\r\n\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public rescale(s: IDimensions | number): Box<BoxType> {\r\n    const scaleX = isDimensions(s) ? (s as IDimensions).width : s as number\r\n    const scaleY = isDimensions(s) ? (s as IDimensions).height : s as number\r\n    return new Box({\r\n      x: this.x * scaleX,\r\n      y: this.y * scaleY,\r\n      width: this.width * scaleX,\r\n      height: this.height * scaleY\r\n    })\r\n  }\r\n\r\n  public pad(padX: number, padY: number): Box<BoxType> {\r\n    let [x, y, width, height] = [\r\n      this.x - (padX / 2),\r\n      this.y - (padY / 2),\r\n      this.width + padX,\r\n      this.height + padY\r\n    ]\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public clipAtImageBorders(imgWidth: number, imgHeight: number): Box<BoxType> {\r\n    const { x, y, right, bottom } = this\r\n    const clippedX = Math.max(x, 0)\r\n    const clippedY = Math.max(y, 0)\r\n\r\n    const newWidth = right - clippedX\r\n    const newHeight = bottom - clippedY\r\n    const clippedWidth = Math.min(newWidth, imgWidth - clippedX)\r\n    const clippedHeight = Math.min(newHeight, imgHeight - clippedY)\r\n\r\n    return (new Box({ x: clippedX, y: clippedY, width: clippedWidth, height: clippedHeight})).floor()\r\n  }\r\n\r\n  public shift(sx: number, sy: number): Box<BoxType> {\r\n    const { width, height } = this\r\n    const x = this.x + sx\r\n    const y = this.y + sy\r\n\r\n    return new Box({ x, y, width, height })\r\n  }\r\n\r\n  public padAtBorders(imageHeight: number, imageWidth: number) {\r\n    const w = this.width + 1\r\n    const h = this.height + 1\r\n\r\n    let dx = 1\r\n    let dy = 1\r\n    let edx = w\r\n    let edy = h\r\n\r\n    let x = this.left\r\n    let y = this.top\r\n    let ex = this.right\r\n    let ey = this.bottom\r\n\r\n    if (ex > imageWidth) {\r\n      edx = -ex + imageWidth + w\r\n      ex = imageWidth\r\n    }\r\n    if (ey > imageHeight) {\r\n      edy = -ey + imageHeight + h\r\n      ey = imageHeight\r\n    }\r\n    if (x < 1) {\r\n      edy = 2 - x\r\n      x = 1\r\n    }\r\n    if (y < 1) {\r\n      edy = 2 - y\r\n      y = 1\r\n    }\r\n\r\n    return { dy, edy, dx, edx, y, ey, x, ex, w, h }\r\n  }\r\n\r\n  public calibrate(region: Box) {\r\n    return new Box({\r\n      left: this.left + (region.left * this.width),\r\n      top: this.top + (region.top * this.height),\r\n      right: this.right + (region.right * this.width),\r\n      bottom: this.bottom + (region.bottom * this.height)\r\n    }).toSquare().round()\r\n  }\r\n}","import { Box } from './Box';\r\n\r\nexport interface IBoundingBox {\r\n  left: number\r\n  top: number\r\n  right: number\r\n  bottom: number\r\n}\r\n\r\nexport class BoundingBox extends Box<BoundingBox> implements IBoundingBox {\r\n  constructor(left: number, top: number, right: number, bottom: number, allowNegativeDimensions: boolean = false) {\r\n    super({ left, top, right, bottom }, allowNegativeDimensions)\r\n  }\r\n}","import { Box } from './Box';\r\nimport { Dimensions, IDimensions } from './Dimensions';\r\nimport { IRect, Rect } from './Rect';\r\n\r\nexport class ObjectDetection {\r\n  private _score: number\r\n  private _classScore: number\r\n  private _className: string\r\n  private _box: Rect\r\n  private _imageDims: Dimensions\r\n\r\n  constructor(\r\n    score: number,\r\n    classScore: number,\r\n    className: string,\r\n    relativeBox: IRect,\r\n    imageDims: IDimensions\r\n  ) {\r\n    this._imageDims = new Dimensions(imageDims.width, imageDims.height)\r\n    this._score = score\r\n    this._classScore = classScore\r\n    this._className = className\r\n    this._box = new Box(relativeBox).rescale(this._imageDims)\r\n  }\r\n\r\n  public get score(): number { return this._score }\r\n  public get classScore(): number { return this._classScore }\r\n  public get className(): string { return this._className }\r\n  public get box(): Box { return this._box }\r\n  public get imageDims(): Dimensions { return this._imageDims }\r\n  public get imageWidth(): number { return this.imageDims.width }\r\n  public get imageHeight(): number { return this.imageDims.height }\r\n  public get relativeBox(): Box { return new Box(this._box).rescale(this.imageDims.reverse()) }\r\n\r\n  public forSize(width: number, height: number): ObjectDetection {\r\n    return new ObjectDetection(\r\n      this.score,\r\n      this.classScore,\r\n      this.className,\r\n      this.relativeBox,\r\n      { width, height}\r\n    )\r\n  }\r\n}","import { Box } from './Box';\r\nimport { IDimensions } from './Dimensions';\r\nimport { ObjectDetection } from './ObjectDetection';\r\nimport { Rect } from './Rect';\r\n\r\nexport interface IFaceDetecion {\r\n  score: number\r\n  box: Box\r\n}\r\n\r\nexport class FaceDetection extends ObjectDetection implements IFaceDetecion {\r\n  constructor(\r\n    score: number,\r\n    relativeBox: Rect,\r\n    imageDims: IDimensions\r\n  ) {\r\n    super(score, score, '', relativeBox, imageDims)\r\n  }\r\n\r\n  public forSize(width: number, height: number): FaceDetection {\r\n    const { score, relativeBox, imageDims } = super.forSize(width, height)\r\n    return new FaceDetection(score, relativeBox, imageDims)\r\n  }\r\n}","import { Box } from '../classes/Box';\r\n\r\nexport function iou(box1: Box, box2: Box, isIOU: boolean = true) {\r\n  const width = Math.max(0.0, Math.min(box1.right, box2.right) - Math.max(box1.left, box2.left))\r\n  const height = Math.max(0.0, Math.min(box1.bottom, box2.bottom) - Math.max(box1.top, box2.top))\r\n  const interSection = width * height\r\n\r\n  return isIOU\r\n    ? interSection / (box1.area + box2.area - interSection)\r\n    : interSection / Math.min(box1.area, box2.area)\r\n}","import { BoundingBox, IPoint } from '../classes';\r\n\r\nexport function minBbox(pts: IPoint[]): BoundingBox {\r\n  const xs = pts.map(pt => pt.x)\r\n  const ys = pts.map(pt => pt.y)\r\n  const minX = xs.reduce((min, x) => x < min ? x : min, Infinity)\r\n  const minY = ys.reduce((min, y) => y < min ? y : min, Infinity)\r\n  const maxX = xs.reduce((max, x) => max < x ? x : max, 0)\r\n  const maxY = ys.reduce((max, y) => max < y ? y : max, 0)\r\n\r\n  return new BoundingBox(minX, minY, maxX, maxY)\r\n}\r\n","import { Box } from '../classes/Box';\r\nimport { iou } from './iou';\r\n\r\nexport function nonMaxSuppression(\r\n  boxes: Box[],\r\n  scores: number[],\r\n  iouThreshold: number,\r\n  isIOU: boolean = true\r\n): number[] {\r\n\r\n  let indicesSortedByScore = scores\r\n    .map((score, boxIndex) => ({ score, boxIndex }))\r\n    .sort((c1, c2) => c1.score - c2.score)\r\n    .map(c => c.boxIndex)\r\n\r\n  const pick: number[] = []\r\n\r\n  while(indicesSortedByScore.length > 0) {\r\n    const curr = indicesSortedByScore.pop() as number\r\n    pick.push(curr)\r\n\r\n    const indices = indicesSortedByScore\r\n\r\n    const outputs: number[] = []\r\n    for (let i = 0; i < indices.length; i++) {\r\n      const idx = indices[i]\r\n\r\n      const currBox = boxes[curr]\r\n      const idxBox = boxes[idx]\r\n\r\n      outputs.push(iou(currBox, idxBox, isIOU))\r\n    }\r\n\r\n    indicesSortedByScore = indicesSortedByScore.filter(\r\n      (_, j) => outputs[j] <= iouThreshold\r\n    )\r\n  }\r\n\r\n  return pick\r\n\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function normalize(x: tf.Tensor4D, meanRgb: number[]): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const [r, g, b] = meanRgb\r\n    const avg_r = tf.fill([...x.shape.slice(0, 3), 1], r)\r\n    const avg_g = tf.fill([...x.shape.slice(0, 3), 1], g)\r\n    const avg_b = tf.fill([...x.shape.slice(0, 3), 1], b)\r\n    const avg_rgb = tf.concat([avg_r, avg_g, avg_b], 3)\r\n\r\n    return tf.sub(x, avg_rgb)\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\n/**\r\n * Pads the smaller dimension of an image tensor with zeros, such that width === height.\r\n *\r\n * @param imgTensor The image tensor.\r\n * @param isCenterImage (optional, default: false) If true, add an equal amount of padding on\r\n * both sides of the minor dimension oof the image.\r\n * @returns The padded tensor with width === height.\r\n */\r\nexport function padToSquare(\r\n  imgTensor: tf.Tensor4D,\r\n  isCenterImage: boolean = false\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n\r\n    const [height, width] = imgTensor.shape.slice(1)\r\n    if (height === width) {\r\n      return imgTensor\r\n    }\r\n\r\n    const dimDiff = Math.abs(height - width)\r\n    const paddingAmount = Math.round(dimDiff * (isCenterImage ? 0.5 : 1))\r\n    const paddingAxis = height > width ? 2 : 1\r\n\r\n    const createPaddingTensor = (paddingAmount: number): tf.Tensor => {\r\n      const paddingTensorShape = imgTensor.shape.slice()\r\n      paddingTensorShape[paddingAxis] = paddingAmount\r\n      return tf.fill(paddingTensorShape, 0)\r\n    }\r\n\r\n    const paddingTensorAppend = createPaddingTensor(paddingAmount)\r\n    const remainingPaddingAmount = dimDiff - (paddingTensorAppend.shape[paddingAxis] as number)\r\n\r\n    const paddingTensorPrepend = isCenterImage && remainingPaddingAmount\r\n      ? createPaddingTensor(remainingPaddingAmount)\r\n      : null\r\n\r\n    const tensorsToStack = [\r\n      paddingTensorPrepend,\r\n      imgTensor,\r\n      paddingTensorAppend\r\n    ]\r\n      .filter(t => !!t)\r\n      .map((t: tf.Tensor) => t.toFloat()) as tf.Tensor4D[]\r\n    return tf.concat(tensorsToStack, paddingAxis)\r\n  })\r\n}","export function shuffleArray(inputArray: any[]) {\r\n  const array = inputArray.slice()\r\n  for (let i = array.length - 1; i > 0; i--) {\r\n      const j = Math.floor(Math.random() * (i + 1))\r\n      const x = array[i]\r\n      array[i] = array[j]\r\n      array[j] = x\r\n  }\r\n  return array\r\n}","export * from './iou'\r\nexport * from './minBbox'\r\nexport * from './nonMaxSuppression'\r\nexport * from './normalize'\r\nexport * from './padToSquare'\r\nexport * from './shuffleArray'\r\n\r\nexport function sigmoid(x: number) {\r\n  return 1 / (1 + Math.exp(-x))\r\n}\r\n\r\nexport function inverseSigmoid(x: number) {\r\n  return Math.log(x / (1 - x))\r\n}","import { Box } from './Box';\r\n\r\nexport interface IRect {\r\n  x: number\r\n  y: number\r\n  width: number\r\n  height: number\r\n}\r\n\r\nexport class Rect extends Box<Rect> implements IRect {\r\n  constructor(x: number, y: number, width: number, height: number, allowNegativeDimensions: boolean = false) {\r\n    super({ x, y, width, height }, allowNegativeDimensions)\r\n  }\r\n}","import { minBbox } from '../ops';\r\nimport { getCenterPoint } from '../utils';\r\nimport { IBoundingBox } from './BoundingBox';\r\nimport { Box } from './Box';\r\nimport { Dimensions, IDimensions } from './Dimensions';\r\nimport { FaceDetection } from './FaceDetection';\r\nimport { Point } from './Point';\r\nimport { IRect, Rect } from './Rect';\r\n\r\n// face alignment constants\r\nconst relX = 0.5\r\nconst relY = 0.43\r\nconst relScale = 0.45\r\n\r\nexport interface IFaceLandmarks {\r\n  positions: Point[]\r\n  shift: Point\r\n}\r\n\r\nexport class FaceLandmarks implements IFaceLandmarks {\r\n  protected _shift: Point\r\n  protected _positions: Point[]\r\n  protected _imgDims: Dimensions\r\n\r\n  constructor(\r\n    relativeFaceLandmarkPositions: Point[],\r\n    imgDims: IDimensions,\r\n    shift: Point = new Point(0, 0)\r\n  ) {\r\n    const { width, height } = imgDims\r\n    this._imgDims = new Dimensions(width, height)\r\n    this._shift = shift\r\n    this._positions = relativeFaceLandmarkPositions.map(\r\n      pt => pt.mul(new Point(width, height)).add(shift)\r\n    )\r\n  }\r\n\r\n  public get shift(): Point { return new Point(this._shift.x, this._shift.y) }\r\n  public get imageWidth(): number { return this._imgDims.width }\r\n  public get imageHeight(): number { return this._imgDims.height }\r\n  public get positions(): Point[] { return this._positions }\r\n  public get relativePositions(): Point[] {\r\n    return this._positions.map(\r\n      pt => pt.sub(this._shift).div(new Point(this.imageWidth, this.imageHeight))\r\n    )\r\n  }\r\n\r\n  public forSize<T extends FaceLandmarks>(width: number, height: number): T {\r\n    return new (this.constructor as any)(\r\n      this.relativePositions,\r\n      { width, height }\r\n    )\r\n  }\r\n\r\n  public shiftBy<T extends FaceLandmarks>(x: number, y: number): T {\r\n    return new (this.constructor as any)(\r\n      this.relativePositions,\r\n      this._imgDims,\r\n      new Point(x, y)\r\n    )\r\n  }\r\n\r\n  public shiftByPoint<T extends FaceLandmarks>(pt: Point): T {\r\n    return this.shiftBy(pt.x, pt.y)\r\n  }\r\n\r\n  /**\r\n   * Aligns the face landmarks after face detection from the relative positions of the faces\r\n   * bounding box, or it's current shift. This function should be used to align the face images\r\n   * after face detection has been performed, before they are passed to the face recognition net.\r\n   * This will make the computed face descriptor more accurate.\r\n   *\r\n   * @param detection (optional) The bounding box of the face or the face detection result. If\r\n   * no argument was passed the position of the face landmarks are assumed to be relative to\r\n   * it's current shift.\r\n   * @returns The bounding box of the aligned face.\r\n   */\r\n  public align(\r\n    detection?: FaceDetection | IRect | IBoundingBox | null,\r\n    options: { useDlibAlignment?: boolean, minBoxPadding?: number } = { }\r\n  ): Box {\r\n    if (detection) {\r\n      const box = detection instanceof FaceDetection\r\n        ? detection.box.floor()\r\n        : new Box(detection)\r\n\r\n      return this.shiftBy(box.x, box.y).align(null, options)\r\n    }\r\n\r\n    const { useDlibAlignment, minBoxPadding } = Object.assign({}, { useDlibAlignment: false, minBoxPadding: 0.2 }, options)\r\n\r\n    if (useDlibAlignment) {\r\n      return this.alignDlib()\r\n    }\r\n\r\n    return this.alignMinBbox(minBoxPadding)\r\n  }\r\n\r\n  private alignDlib(): Box {\r\n\r\n    const centers = this.getRefPointsForAlignment()\r\n\r\n    const [leftEyeCenter, rightEyeCenter, mouthCenter] = centers\r\n    const distToMouth = (pt: Point) => mouthCenter.sub(pt).magnitude()\r\n    const eyeToMouthDist = (distToMouth(leftEyeCenter) + distToMouth(rightEyeCenter)) / 2\r\n\r\n    const size = Math.floor(eyeToMouthDist / relScale)\r\n\r\n    const refPoint = getCenterPoint(centers)\r\n    // TODO: pad in case rectangle is out of image bounds\r\n    const x = Math.floor(Math.max(0, refPoint.x - (relX * size)))\r\n    const y = Math.floor(Math.max(0, refPoint.y - (relY * size)))\r\n\r\n    return new Rect(x, y, Math.min(size, this.imageWidth + x), Math.min(size, this.imageHeight + y))\r\n  }\r\n\r\n  private alignMinBbox(padding: number): Box {\r\n    const box = minBbox(this.positions)\r\n    return box.pad(box.width * padding, box.height * padding)\r\n  }\r\n\r\n  protected getRefPointsForAlignment(): Point[] {\r\n    throw new Error('getRefPointsForAlignment not implemented by base class')\r\n  }\r\n}","import { getCenterPoint } from '../utils';\r\nimport { FaceLandmarks } from './FaceLandmarks';\r\nimport { Point } from './Point';\r\n\r\n\r\nexport class FaceLandmarks5 extends FaceLandmarks {\r\n\r\n  protected getRefPointsForAlignment(): Point[] {\r\n    const pts = this.positions\r\n    return [\r\n      pts[0],\r\n      pts[1],\r\n      getCenterPoint([pts[3], pts[4]])\r\n    ]\r\n  }\r\n}","import { getCenterPoint } from '../utils';\r\nimport { FaceLandmarks } from './FaceLandmarks';\r\nimport { Point } from './Point';\r\n\r\nexport class FaceLandmarks68 extends FaceLandmarks {\r\n  public getJawOutline(): Point[] {\r\n    return this.positions.slice(0, 17)\r\n  }\r\n\r\n  public getLeftEyeBrow(): Point[] {\r\n    return this.positions.slice(17, 22)\r\n  }\r\n\r\n  public getRightEyeBrow(): Point[] {\r\n    return this.positions.slice(22, 27)\r\n  }\r\n\r\n  public getNose(): Point[] {\r\n    return this.positions.slice(27, 36)\r\n  }\r\n\r\n  public getLeftEye(): Point[] {\r\n    return this.positions.slice(36, 42)\r\n  }\r\n\r\n  public getRightEye(): Point[] {\r\n    return this.positions.slice(42, 48)\r\n  }\r\n\r\n  public getMouth(): Point[] {\r\n    return this.positions.slice(48, 68)\r\n  }\r\n\r\n  protected getRefPointsForAlignment(): Point[] {\r\n    return [\r\n      this.getLeftEye(),\r\n      this.getRightEye(),\r\n      this.getMouth()\r\n    ].map(getCenterPoint)\r\n  }\r\n}","import { round } from '../utils';\r\n\r\nexport interface IFaceMatch {\r\n  label: string\r\n  distance: number\r\n}\r\n\r\nexport class FaceMatch implements IFaceMatch {\r\n  private _label: string\r\n  private _distance: number\r\n\r\n  constructor(label: string, distance: number) {\r\n    this._label = label\r\n    this._distance = distance\r\n  }\r\n\r\n  public get label(): string { return this._label }\r\n  public get distance(): number { return this._distance }\r\n\r\n  public toString(withDistance: boolean = true): string {\r\n    return `${this.label}${withDistance ? ` (${round(this.distance)})` : ''}`\r\n  }\r\n}","import { isValidNumber } from '../utils';\r\nimport { IBoundingBox } from './BoundingBox';\r\nimport { Box } from './Box';\r\nimport { IRect } from './Rect';\r\n\r\nexport class LabeledBox extends Box<LabeledBox> {\r\n\r\n  public static assertIsValidLabeledBox(box: any, callee: string) {\r\n    Box.assertIsValidBox(box, callee)\r\n\r\n    if (!isValidNumber(box.label)) {\r\n      throw new Error(`${callee} - expected property label (${box.label}) to be a number`)\r\n    }\r\n  }\r\n\r\n  private _label: number\r\n\r\n  constructor(box: IBoundingBox | IRect | any, label: number) {\r\n    super(box)\r\n    this._label = label\r\n  }\r\n\r\n  public get label(): number { return this._label }\r\n\r\n}","export class LabeledFaceDescriptors {\r\n  private _label: string\r\n  private _descriptors: Float32Array[]\r\n\r\n  constructor(label: string, descriptors: Float32Array[]) {\r\n    if (!(typeof label === 'string')) {\r\n      throw new Error('LabeledFaceDescriptors - constructor expected label to be a string')\r\n    }\r\n\r\n    if (!Array.isArray(descriptors) || descriptors.some(desc => !(desc instanceof Float32Array))) {\r\n      throw new Error('LabeledFaceDescriptors - constructor expected descriptors to be an array of Float32Array')\r\n    }\r\n\r\n    this._label = label\r\n    this._descriptors = descriptors\r\n  }\r\n\r\n  public get label(): string { return this._label }\r\n  public get descriptors(): Float32Array[] { return this._descriptors }\r\n\r\n  public toJSON(): any {\r\n    return {\r\n      label: this.label,\r\n      descriptors: this.descriptors.map((d) => Array.from(d))\r\n    };\r\n  }\r\n\r\n  public static fromJSON(json: any): LabeledFaceDescriptors {\r\n    const descriptors = json.descriptors.map((d: any) => {\r\n      return new Float32Array(d);\r\n    });\r\n    return new LabeledFaceDescriptors(json.label, descriptors);\r\n  }\r\n\r\n}","import { isValidProbablitiy } from '../utils';\r\nimport { IBoundingBox } from './BoundingBox';\r\nimport { LabeledBox } from './LabeledBox';\r\nimport { IRect } from './Rect';\r\n\r\nexport class PredictedBox extends LabeledBox {\r\n\r\n  public static assertIsValidPredictedBox(box: any, callee: string) {\r\n    LabeledBox.assertIsValidLabeledBox(box, callee)\r\n\r\n    if (\r\n      !isValidProbablitiy(box.score)\r\n      || !isValidProbablitiy(box.classScore)\r\n    ) {\r\n      throw new Error(`${callee} - expected properties score (${box.score}) and (${box.classScore}) to be a number between [0, 1]`)\r\n    }\r\n  }\r\n\r\n  private _score: number\r\n  private _classScore: number\r\n\r\n  constructor(box: IBoundingBox | IRect | any, label: number, score: number, classScore: number) {\r\n    super(box, label)\r\n    this._score = score\r\n    this._classScore = classScore\r\n  }\r\n\r\n  public get score(): number { return this._score }\r\n  public get classScore(): number { return this._classScore }\r\n\r\n}","import { FaceDetection } from '../classes/FaceDetection';\r\n\r\nexport type WithFaceDetection<TSource> = TSource & {\r\n  detection: FaceDetection\r\n}\r\n\r\nexport function isWithFaceDetection(obj: any): obj is WithFaceDetection<{}> {\r\n  return obj['detection'] instanceof FaceDetection\r\n}\r\n\r\nexport function extendWithFaceDetection<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  detection: FaceDetection\r\n): WithFaceDetection<TSource> {\r\n\r\n  const extension = { detection }\r\n  return Object.assign({}, sourceObj, extension)\r\n}\r\n","import { Environment } from './types';\r\n\r\nexport function createBrowserEnv(): Environment {\r\n\r\n  const fetch = window['fetch'] || function() {\r\n    throw new Error('fetch - missing fetch implementation for browser environment')\r\n  }\r\n\r\n  const readFile = function() {\r\n    throw new Error('readFile - filesystem not available for browser environment')\r\n  }\r\n\r\n  return {\r\n    Canvas: HTMLCanvasElement,\r\n    CanvasRenderingContext2D: CanvasRenderingContext2D,\r\n    Image: HTMLImageElement,\r\n    ImageData: ImageData,\r\n    Video: HTMLVideoElement,\r\n    createCanvasElement: () => document.createElement('canvas'),\r\n    createImageElement: () => document.createElement('img'),\r\n    fetch,\r\n    readFile\r\n  }\r\n}","import { FileSystem } from './types';\r\n\r\nexport function createFileSystem(fs?: any): FileSystem {\r\n\r\n  let requireFsError = ''\r\n\r\n  if (!fs) {\r\n    try {\r\n      fs = require('fs')\r\n    } catch (err) {\r\n      requireFsError = err.toString()\r\n    }\r\n  }\r\n\r\n  const readFile = fs\r\n    ? function(filePath: string) {\r\n      return new Promise<Buffer>((res, rej) => {\r\n        fs.readFile(filePath, function(err: any, buffer: Buffer) {\r\n          return err ? rej(err) : res(buffer)\r\n        })\r\n      })\r\n    }\r\n    : function() {\r\n      throw new Error(`readFile - failed to require fs in nodejs environment with error: ${requireFsError}`)\r\n    }\r\n\r\n  return {\r\n    readFile\r\n  }\r\n}","import { createFileSystem } from './createFileSystem';\r\nimport { Environment } from './types';\r\n\r\nexport function createNodejsEnv(): Environment {\r\n\r\n  const Canvas = global['Canvas'] || global['HTMLCanvasElement']\r\n  const Image = global['Image'] || global['HTMLImageElement']\r\n\r\n  const createCanvasElement = function() {\r\n    if (Canvas) {\r\n      return new Canvas()\r\n    }\r\n    throw new Error('createCanvasElement - missing Canvas implementation for nodejs environment')\r\n  }\r\n\r\n  const createImageElement = function() {\r\n    if (Image) {\r\n      return new Image()\r\n    }\r\n    throw new Error('createImageElement - missing Image implementation for nodejs environment')\r\n  }\r\n\r\n  const fetch = global['fetch'] || function() {\r\n    throw new Error('fetch - missing fetch implementation for nodejs environment')\r\n  }\r\n\r\n  const fileSystem = createFileSystem()\r\n\r\n  return {\r\n    Canvas: Canvas || class {},\r\n    CanvasRenderingContext2D: global['CanvasRenderingContext2D'] || class {},\r\n    Image: Image || class {},\r\n    ImageData: global['ImageData'] || class {},\r\n    Video: global['HTMLVideoElement'] || class {},\r\n    createCanvasElement,\r\n    createImageElement,\r\n    fetch,\r\n    ...fileSystem\r\n  }\r\n}","export function isBrowser(): boolean {\r\n  return typeof window === 'object'\r\n    && typeof document !== 'undefined'\r\n    && typeof HTMLImageElement !== 'undefined'\r\n    && typeof HTMLCanvasElement !== 'undefined'\r\n    && typeof HTMLVideoElement !== 'undefined'\r\n    && typeof ImageData !== 'undefined'\r\n    && typeof CanvasRenderingContext2D !== 'undefined'\r\n}","export function isNodejs(): boolean {\r\n  return typeof global === 'object'\r\n    && typeof require === 'function'\r\n    && typeof module !== 'undefined'\r\n    // issues with gatsby.js: module.exports is undefined\r\n    // && !!module.exports\r\n    && typeof process !== 'undefined' && !!process.version\r\n}","import { createBrowserEnv } from './createBrowserEnv';\r\nimport { createFileSystem } from './createFileSystem';\r\nimport { createNodejsEnv } from './createNodejsEnv';\r\nimport { isBrowser } from './isBrowser';\r\nimport { isNodejs } from './isNodejs';\r\nimport { Environment } from './types';\r\n\r\nlet environment: Environment | null\r\n\r\nfunction getEnv(): Environment {\r\n  if (!environment) {\r\n    throw new Error('getEnv - environment is not defined, check isNodejs() and isBrowser()')\r\n  }\r\n  return environment\r\n}\r\n\r\nfunction setEnv(env: Environment) {\r\n  environment = env\r\n}\r\n\r\nfunction initialize() {\r\n  // check for isBrowser() first to prevent electron renderer process\r\n  // to be initialized with wrong environment due to isNodejs() returning true\r\n  if (isBrowser()) {\r\n    setEnv(createBrowserEnv())\r\n  }\r\n  if (isNodejs()) {\r\n    setEnv(createNodejsEnv())\r\n  }\r\n}\r\n\r\nfunction monkeyPatch(env: Partial<Environment>) {\r\n  if (!environment) {\r\n    initialize()\r\n  }\r\n\r\n  if (!environment) {\r\n    throw new Error('monkeyPatch - environment is not defined, check isNodejs() and isBrowser()')\r\n  }\r\n\r\n  const { Canvas = environment.Canvas, Image = environment.Image } = env\r\n  environment.Canvas = Canvas\r\n  environment.Image = Image\r\n  environment.createCanvasElement = env.createCanvasElement || (() => new Canvas())\r\n  environment.createImageElement = env.createImageElement || (() => new Image())\r\n\r\n  environment.ImageData = env.ImageData || environment.ImageData\r\n  environment.Video = env.Video || environment.Video\r\n  environment.fetch = env.fetch || environment.fetch\r\n  environment.readFile = env.readFile || environment.readFile\r\n}\r\n\r\nexport const env = {\r\n  getEnv,\r\n  setEnv,\r\n  initialize,\r\n  createBrowserEnv,\r\n  createFileSystem,\r\n  createNodejsEnv,\r\n  monkeyPatch,\r\n  isBrowser,\r\n  isNodejs\r\n}\r\n\r\ninitialize()\r\n\r\nexport * from './types'\r\n","import { env } from '../env';\r\n\r\nexport function resolveInput(arg: string | any) {\r\n  if (!env.isNodejs() && typeof arg === 'string') {\r\n    return document.getElementById(arg)\r\n  }\r\n  return arg\r\n}","import { env } from '../env';\r\nimport { resolveInput } from './resolveInput';\r\n\r\nexport function getContext2dOrThrow(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D): CanvasRenderingContext2D {\r\n\r\n  const { Canvas, CanvasRenderingContext2D } = env.getEnv()\r\n\r\n  if (canvasArg instanceof CanvasRenderingContext2D) {\r\n    return canvasArg\r\n  }\r\n\r\n  const canvas = resolveInput(canvasArg)\r\n\r\n  if (!(canvas instanceof Canvas)) {\r\n    throw new Error('resolveContext2d - expected canvas to be of instance of Canvas')\r\n  }\r\n\r\n  const ctx = canvas.getContext('2d')\r\n  if (!ctx) {\r\n    throw new Error('resolveContext2d - canvas 2d context is null')\r\n  }\r\n\r\n  return ctx\r\n}","import { IDimensions, IPoint } from '../classes';\r\nimport { getContext2dOrThrow } from '../dom/getContext2dOrThrow';\r\nimport { resolveInput } from '../dom/resolveInput';\r\n\r\nexport enum AnchorPosition {\r\n  TOP_LEFT = 'TOP_LEFT',\r\n  TOP_RIGHT = 'TOP_RIGHT',\r\n  BOTTOM_LEFT = 'BOTTOM_LEFT',\r\n  BOTTOM_RIGHT = 'BOTTOM_RIGHT'\r\n}\r\n\r\nexport interface IDrawTextFieldOptions {\r\n  anchorPosition?: AnchorPosition\r\n  backgroundColor?: string\r\n  fontColor?: string\r\n  fontSize?: number\r\n  fontStyle?: string\r\n  padding?: number\r\n}\r\n\r\nexport class DrawTextFieldOptions implements IDrawTextFieldOptions {\r\n  public anchorPosition: AnchorPosition\r\n  public backgroundColor: string\r\n  public fontColor: string\r\n  public fontSize: number\r\n  public fontStyle: string\r\n  public padding: number\r\n\r\n  constructor(options: IDrawTextFieldOptions = {}) {\r\n    const { anchorPosition, backgroundColor, fontColor, fontSize, fontStyle, padding } = options\r\n    this.anchorPosition = anchorPosition || AnchorPosition.TOP_LEFT\r\n    this.backgroundColor = backgroundColor || 'rgba(0, 0, 0, 0.5)'\r\n    this.fontColor = fontColor || 'rgba(255, 255, 255, 1)'\r\n    this.fontSize = fontSize || 14\r\n    this.fontStyle = fontStyle || 'Georgia'\r\n    this.padding = padding || 4\r\n  }\r\n}\r\n\r\nexport class DrawTextField {\r\n  public text: string[]\r\n  public anchor : IPoint\r\n  public options: DrawTextFieldOptions\r\n\r\n  constructor(\r\n    text: string | string[] | DrawTextField,\r\n    anchor: IPoint,\r\n    options: IDrawTextFieldOptions = {}\r\n  ) {\r\n    this.text = typeof text === 'string'\r\n      ? [text]\r\n      : (text instanceof DrawTextField ? text.text : text)\r\n    this.anchor = anchor\r\n    this.options = new DrawTextFieldOptions(options)\r\n  }\r\n\r\n  measureWidth(ctx: CanvasRenderingContext2D): number {\r\n    const { padding } = this.options\r\n    return this.text.map(l => ctx.measureText(l).width).reduce((w0, w1) => w0 < w1 ? w1 : w0, 0) + (2 * padding)\r\n  }\r\n\r\n  measureHeight(): number {\r\n    const { fontSize, padding } = this.options\r\n    return this.text.length * fontSize + (2 * padding)\r\n  }\r\n\r\n  getUpperLeft(ctx: CanvasRenderingContext2D, canvasDims?: IDimensions): IPoint {\r\n    const { anchorPosition } = this.options\r\n    const isShiftLeft = anchorPosition === AnchorPosition.BOTTOM_RIGHT || anchorPosition === AnchorPosition.TOP_RIGHT\r\n    const isShiftTop = anchorPosition === AnchorPosition.BOTTOM_LEFT || anchorPosition === AnchorPosition.BOTTOM_RIGHT\r\n\r\n    const textFieldWidth = this.measureWidth(ctx)\r\n    const textFieldHeight = this.measureHeight()\r\n    const x = (isShiftLeft ? this.anchor.x - textFieldWidth : this.anchor.x)\r\n    const y = isShiftTop ? this.anchor.y - textFieldHeight : this.anchor.y\r\n\r\n    // adjust anchor if text box exceeds canvas borders\r\n    if (canvasDims) {\r\n      const { width, height } = canvasDims\r\n      const newX = Math.max(Math.min(x, width - textFieldWidth), 0)\r\n      const newY = Math.max(Math.min(y, height - textFieldHeight), 0)\r\n      return { x: newX, y: newY }\r\n    }\r\n    return { x, y }\r\n  }\r\n\r\n  draw(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D) {\r\n    const canvas = resolveInput(canvasArg)\r\n    const ctx = getContext2dOrThrow(canvas)\r\n\r\n    const { backgroundColor, fontColor, fontSize, fontStyle, padding } = this.options\r\n\r\n    ctx.font = `${fontSize}px ${fontStyle}`\r\n    const maxTextWidth = this.measureWidth(ctx)\r\n    const textHeight = this.measureHeight()\r\n\r\n    ctx.fillStyle = backgroundColor\r\n    const upperLeft = this.getUpperLeft(ctx, canvas)\r\n    ctx.fillRect(upperLeft.x, upperLeft.y, maxTextWidth, textHeight)\r\n\r\n    ctx.fillStyle = fontColor;\r\n    this.text.forEach((textLine, i) => {\r\n      const x = padding + upperLeft.x\r\n      const y = padding + upperLeft.y + ((i + 1) * fontSize)\r\n      ctx.fillText(textLine, x, y)\r\n    })\r\n  }\r\n}","import { Box, IBoundingBox, IRect } from '../classes';\r\nimport { getContext2dOrThrow } from '../dom/getContext2dOrThrow';\r\nimport { AnchorPosition, DrawTextField, DrawTextFieldOptions, IDrawTextFieldOptions } from './DrawTextField';\r\n\r\nexport interface IDrawBoxOptions {\r\n  boxColor?: string\r\n  lineWidth?: number\r\n  drawLabelOptions?: IDrawTextFieldOptions\r\n  label?: string\r\n}\r\n\r\nexport class DrawBoxOptions {\r\n  public boxColor: string\r\n  public lineWidth: number\r\n  public drawLabelOptions: DrawTextFieldOptions\r\n  public label?: string\r\n\r\n  constructor(options: IDrawBoxOptions = {}) {\r\n    const { boxColor, lineWidth, label, drawLabelOptions } = options\r\n    this.boxColor = boxColor || 'rgba(0, 0, 255, 1)'\r\n    this.lineWidth = lineWidth || 2\r\n    this.label = label\r\n\r\n    const defaultDrawLabelOptions = {\r\n      anchorPosition: AnchorPosition.BOTTOM_LEFT,\r\n      backgroundColor: this.boxColor\r\n    }\r\n    this.drawLabelOptions = new DrawTextFieldOptions(Object.assign({}, defaultDrawLabelOptions, drawLabelOptions))\r\n  }\r\n}\r\n\r\nexport class DrawBox {\r\n  public box: Box\r\n  public options: DrawBoxOptions\r\n\r\n  constructor(\r\n    box: IBoundingBox | IRect,\r\n    options: IDrawBoxOptions = {}\r\n  ) {\r\n    this.box = new Box(box)\r\n    this.options = new DrawBoxOptions(options)\r\n  }\r\n\r\n  draw(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D) {\r\n    const ctx = getContext2dOrThrow(canvasArg)\r\n\r\n    const { boxColor, lineWidth } = this.options\r\n\r\n    const { x, y, width, height } = this.box\r\n    ctx.strokeStyle = boxColor\r\n    ctx.lineWidth = lineWidth\r\n    ctx.strokeRect(x, y, width, height)\r\n\r\n    const { label } = this.options\r\n    if (label) {\r\n      new DrawTextField([label], { x: x - (lineWidth / 2), y }, this.options.drawLabelOptions).draw(canvasArg)\r\n    }\r\n  }\r\n}","import { Box, IBoundingBox, IRect } from '../classes';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { isWithFaceDetection, WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { round } from '../utils';\r\nimport { DrawBox } from './DrawBox';\r\n\r\nexport type TDrawDetectionsInput = IRect | IBoundingBox | FaceDetection | WithFaceDetection<{}>\r\n\r\nexport function drawDetections(\r\n  canvasArg: string | HTMLCanvasElement,\r\n  detections: TDrawDetectionsInput | Array<TDrawDetectionsInput>\r\n) {\r\n  const detectionsArray = Array.isArray(detections) ? detections : [detections]\r\n\r\n  detectionsArray.forEach(det => {\r\n    const score = det instanceof FaceDetection\r\n      ? det.score\r\n      : (isWithFaceDetection(det) ? det.detection.score : undefined)\r\n\r\n    const box = det instanceof FaceDetection\r\n      ? det.box\r\n      : (isWithFaceDetection(det) ? det.detection.box : new Box(det))\r\n\r\n    const label = score ? `${round(score)}` : undefined\r\n    new DrawBox(box, { label }).draw(canvasArg)\r\n  })\r\n}","import { env } from '../env';\r\n\r\nexport function isMediaLoaded(media: HTMLImageElement | HTMLVideoElement) : boolean {\r\n\r\n  const { Image, Video } = env.getEnv()\r\n\r\n  return (media instanceof Image && media.complete)\r\n    || (media instanceof Video && media.readyState >= 3)\r\n}\r\n","import { env } from '../env';\r\nimport { isMediaLoaded } from './isMediaLoaded';\r\n\r\nexport function awaitMediaLoaded(media: HTMLImageElement | HTMLVideoElement | HTMLCanvasElement) {\r\n\r\n  return new Promise((resolve, reject) => {\r\n    if (media instanceof env.getEnv().Canvas || isMediaLoaded(media)) {\r\n      return resolve()\r\n    }\r\n\r\n    function onLoad(e: Event) {\r\n      if (!e.currentTarget) return\r\n      e.currentTarget.removeEventListener('load', onLoad)\r\n      e.currentTarget.removeEventListener('error', onError)\r\n      resolve(e)\r\n    }\r\n\r\n    function onError(e: Event) {\r\n      if (!e.currentTarget) return\r\n      e.currentTarget.removeEventListener('load', onLoad)\r\n      e.currentTarget.removeEventListener('error', onError)\r\n      reject(e)\r\n    }\r\n\r\n    media.addEventListener('load', onLoad)\r\n    media.addEventListener('error', onError)\r\n  })\r\n}","import { env } from '../env';\r\n\r\nexport function bufferToImage(buf: Blob): Promise<HTMLImageElement> {\r\n  return new Promise((resolve, reject) => {\r\n    if (!(buf instanceof Blob)) {\r\n      return reject('bufferToImage - expected buf to be of type: Blob')\r\n    }\r\n\r\n    const reader = new FileReader()\r\n    reader.onload = () => {\r\n      if (typeof reader.result !== 'string') {\r\n        return reject('bufferToImage - expected reader.result to be a string, in onload')\r\n      }\r\n\r\n      const img = env.getEnv().createImageElement()\r\n      img.onload = () => resolve(img)\r\n      img.onerror = reject\r\n      img.src = reader.result\r\n    }\r\n    reader.onerror = reject\r\n    reader.readAsDataURL(buf)\r\n  })\r\n}","import { Dimensions, IDimensions } from '../classes/Dimensions';\r\nimport { env } from '../env';\r\n\r\nexport function getMediaDimensions(input: HTMLImageElement | HTMLCanvasElement | HTMLVideoElement | IDimensions): Dimensions {\r\n\r\n  const { Image, Video } = env.getEnv()\r\n\r\n  if (input instanceof Image) {\r\n    return new Dimensions(input.naturalWidth, input.naturalHeight)\r\n  }\r\n  if (input instanceof Video) {\r\n    return new Dimensions(input.videoWidth, input.videoHeight)\r\n  }\r\n  return new Dimensions(input.width, input.height)\r\n}\r\n","import { IDimensions } from '../classes/Dimensions';\r\nimport { env } from '../env';\r\nimport { getContext2dOrThrow } from './getContext2dOrThrow';\r\nimport { getMediaDimensions } from './getMediaDimensions';\r\nimport { isMediaLoaded } from './isMediaLoaded';\r\n\r\nexport function createCanvas({ width, height }: IDimensions): HTMLCanvasElement {\r\n\r\n  const { createCanvasElement } = env.getEnv()\r\n  const canvas = createCanvasElement()\r\n  canvas.width = width\r\n  canvas.height = height\r\n  return canvas\r\n}\r\n\r\nexport function createCanvasFromMedia(media: HTMLImageElement | HTMLVideoElement | ImageData, dims?: IDimensions): HTMLCanvasElement {\r\n\r\n  const { ImageData } = env.getEnv()\r\n\r\n  if (!(media instanceof ImageData) && !isMediaLoaded(media)) {\r\n    throw new Error('createCanvasFromMedia - media has not finished loading yet')\r\n  }\r\n\r\n  const { width, height } = dims || getMediaDimensions(media)\r\n  const canvas = createCanvas({ width, height })\r\n\r\n  if (media instanceof ImageData) {\r\n    getContext2dOrThrow(canvas).putImageData(media, 0, 0)\r\n  } else {\r\n    getContext2dOrThrow(canvas).drawImage(media, 0, 0, width, height)\r\n  }\r\n  return canvas\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { env } from '../env';\r\nimport { isTensor4D } from '../utils';\r\n\r\nexport async function imageTensorToCanvas(\r\n  imgTensor: tf.Tensor,\r\n  canvas?: HTMLCanvasElement\r\n): Promise<HTMLCanvasElement> {\r\n\r\n  const targetCanvas = canvas || env.getEnv().createCanvasElement()\r\n\r\n  const [height, width, numChannels] = imgTensor.shape.slice(isTensor4D(imgTensor) ? 1 : 0)\r\n  const imgTensor3D = tf.tidy(() => imgTensor.as3D(height, width, numChannels).toInt())\r\n  await tf.browser.toPixels(imgTensor3D, targetCanvas)\r\n\r\n  imgTensor3D.dispose()\r\n\r\n  return targetCanvas\r\n}","import { env } from '../env';\r\n\r\nexport function isMediaElement(input: any) {\r\n\r\n  const { Image, Canvas, Video } = env.getEnv()\r\n\r\n  return input instanceof Image\r\n    || input instanceof Canvas\r\n    || input instanceof Video\r\n}","import { env } from '../env';\r\nimport { createCanvas, createCanvasFromMedia } from './createCanvas';\r\nimport { getContext2dOrThrow } from './getContext2dOrThrow';\r\nimport { getMediaDimensions } from './getMediaDimensions';\r\n\r\nexport function imageToSquare(input: HTMLImageElement | HTMLCanvasElement, inputSize: number, centerImage: boolean = false) {\r\n\r\n  const { Image, Canvas } = env.getEnv()\r\n\r\n  if (!(input instanceof Image || input instanceof Canvas)) {\r\n    throw new Error('imageToSquare - expected arg0 to be HTMLImageElement | HTMLCanvasElement')\r\n  }\r\n\r\n  const dims = getMediaDimensions(input)\r\n  const scale = inputSize / Math.max(dims.height, dims.width)\r\n  const width = scale * dims.width\r\n  const height = scale * dims.height\r\n\r\n  const targetCanvas = createCanvas({ width: inputSize, height: inputSize })\r\n  const inputCanvas = input instanceof Canvas ? input : createCanvasFromMedia(input)\r\n\r\n  const offset = Math.abs(width - height) / 2\r\n  const dx = centerImage && width < height ? offset : 0\r\n  const dy = centerImage && height < width ? offset : 0\r\n  getContext2dOrThrow(targetCanvas).drawImage(inputCanvas, dx, dy, width, height)\r\n\r\n  return targetCanvas\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Dimensions } from '../classes/Dimensions';\r\nimport { env } from '../env';\r\nimport { padToSquare } from '../ops/padToSquare';\r\nimport { computeReshapedDimensions, isTensor3D, isTensor4D, range } from '../utils';\r\nimport { createCanvasFromMedia } from './createCanvas';\r\nimport { imageToSquare } from './imageToSquare';\r\nimport { TResolvedNetInput } from './types';\r\n\r\nexport class NetInput {\r\n  private _imageTensors: Array<tf.Tensor3D | tf.Tensor4D> = []\r\n  private _canvases: HTMLCanvasElement[] = []\r\n  private _batchSize: number\r\n  private _treatAsBatchInput: boolean = false\r\n\r\n  private _inputDimensions: number[][] = []\r\n  private _inputSize: number\r\n\r\n  constructor(\r\n    inputs: Array<TResolvedNetInput>,\r\n    treatAsBatchInput: boolean = false\r\n  ) {\r\n    if (!Array.isArray(inputs)) {\r\n      throw new Error(`NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have ${inputs}`)\r\n    }\r\n\r\n    this._treatAsBatchInput = treatAsBatchInput\r\n    this._batchSize = inputs.length\r\n\r\n    inputs.forEach((input, idx) => {\r\n\r\n      if (isTensor3D(input)) {\r\n        this._imageTensors[idx] = input\r\n        this._inputDimensions[idx] = input.shape\r\n        return\r\n      }\r\n\r\n      if (isTensor4D(input)) {\r\n        const batchSize = input.shape[0]\r\n        if (batchSize !== 1) {\r\n          throw new Error(`NetInput - tf.Tensor4D with batchSize ${batchSize} passed, but not supported in input array`)\r\n        }\r\n\r\n        this._imageTensors[idx] = input\r\n        this._inputDimensions[idx] = input.shape.slice(1)\r\n        return\r\n      }\r\n\r\n      const canvas = input instanceof env.getEnv().Canvas ? input : createCanvasFromMedia(input)\r\n      this._canvases[idx] = canvas\r\n      this._inputDimensions[idx] = [canvas.height, canvas.width, 3]\r\n    })\r\n  }\r\n\r\n  public get imageTensors(): Array<tf.Tensor3D | tf.Tensor4D> {\r\n    return this._imageTensors\r\n  }\r\n\r\n  public get canvases(): HTMLCanvasElement[] {\r\n    return this._canvases\r\n  }\r\n\r\n  public get isBatchInput(): boolean {\r\n    return this.batchSize > 1 || this._treatAsBatchInput\r\n  }\r\n\r\n  public get batchSize(): number {\r\n    return this._batchSize\r\n  }\r\n\r\n  public get inputDimensions(): number[][] {\r\n    return this._inputDimensions\r\n  }\r\n\r\n  public get inputSize(): number | undefined {\r\n    return this._inputSize\r\n  }\r\n\r\n  public get reshapedInputDimensions(): Dimensions[] {\r\n    return range(this.batchSize, 0, 1).map(\r\n      (_, batchIdx) => this.getReshapedInputDimensions(batchIdx)\r\n    )\r\n  }\r\n\r\n  public getInput(batchIdx: number): tf.Tensor3D  | tf.Tensor4D | HTMLCanvasElement {\r\n    return this.canvases[batchIdx] || this.imageTensors[batchIdx]\r\n  }\r\n\r\n  public getInputDimensions(batchIdx: number): number[] {\r\n    return this._inputDimensions[batchIdx]\r\n  }\r\n\r\n  public getInputHeight(batchIdx: number): number {\r\n    return this._inputDimensions[batchIdx][0]\r\n  }\r\n\r\n  public getInputWidth(batchIdx: number): number {\r\n    return this._inputDimensions[batchIdx][1]\r\n  }\r\n\r\n  public getReshapedInputDimensions(batchIdx: number): Dimensions {\r\n    if (typeof this.inputSize !== 'number') {\r\n      throw new Error('getReshapedInputDimensions - inputSize not set, toBatchTensor has not been called yet')\r\n    }\r\n\r\n    const width = this.getInputWidth(batchIdx)\r\n    const height = this.getInputHeight(batchIdx)\r\n    return computeReshapedDimensions({ width, height }, this.inputSize)\r\n  }\r\n\r\n  /**\r\n   * Create a batch tensor from all input canvases and tensors\r\n   * with size [batchSize, inputSize, inputSize, 3].\r\n   *\r\n   * @param inputSize Height and width of the tensor.\r\n   * @param isCenterImage (optional, default: false) If true, add an equal amount of padding on\r\n   * both sides of the minor dimension oof the image.\r\n   * @returns The batch tensor.\r\n   */\r\n  public toBatchTensor(inputSize: number, isCenterInputs: boolean = true): tf.Tensor4D {\r\n\r\n    this._inputSize = inputSize\r\n\r\n    return tf.tidy(() => {\r\n\r\n      const inputTensors = range(this.batchSize, 0, 1).map(batchIdx => {\r\n        const input = this.getInput(batchIdx)\r\n\r\n        if (input instanceof tf.Tensor) {\r\n          let imgTensor = isTensor4D(input) ? input : input.expandDims<tf.Rank.R4>()\r\n          imgTensor = padToSquare(imgTensor, isCenterInputs)\r\n\r\n          if (imgTensor.shape[1] !== inputSize || imgTensor.shape[2] !== inputSize) {\r\n            imgTensor = tf.image.resizeBilinear(imgTensor, [inputSize, inputSize])\r\n          }\r\n\r\n          return imgTensor.as3D(inputSize, inputSize, 3)\r\n        }\r\n\r\n        if (input instanceof env.getEnv().Canvas) {\r\n          return tf.browser.fromPixels(imageToSquare(input, inputSize, isCenterInputs))\r\n        }\r\n\r\n        throw new Error(`toBatchTensor - at batchIdx ${batchIdx}, expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have ${input}`)\r\n      })\r\n\r\n      const batchTensor = tf.stack(inputTensors.map(t => t.toFloat())).as4D(this.batchSize, inputSize, inputSize, 3)\r\n\r\n      return batchTensor\r\n    })\r\n  }\r\n}","import { isTensor3D, isTensor4D } from '../utils';\r\nimport { awaitMediaLoaded } from './awaitMediaLoaded';\r\nimport { isMediaElement } from './isMediaElement';\r\nimport { NetInput } from './NetInput';\r\nimport { resolveInput } from './resolveInput';\r\nimport { TNetInput } from './types';\r\n\r\n/**\r\n * Validates the input to make sure, they are valid net inputs and awaits all media elements\r\n * to be finished loading.\r\n *\r\n * @param input The input, which can be a media element or an array of different media elements.\r\n * @returns A NetInput instance, which can be passed into one of the neural networks.\r\n */\r\nexport async function toNetInput(inputs: TNetInput): Promise<NetInput> {\r\n  if (inputs instanceof NetInput) {\r\n    return inputs\r\n  }\r\n\r\n  let inputArgArray = Array.isArray(inputs)\r\n      ? inputs\r\n      : [inputs]\r\n\r\n  if (!inputArgArray.length) {\r\n    throw new Error('toNetInput - empty array passed as input')\r\n  }\r\n\r\n  const getIdxHint = (idx: number) => Array.isArray(inputs) ? ` at input index ${idx}:` : ''\r\n\r\n  const inputArray = inputArgArray.map(resolveInput)\r\n\r\n  inputArray.forEach((input, i) => {\r\n    if (!isMediaElement(input) && !isTensor3D(input) && !isTensor4D(input)) {\r\n\r\n      if (typeof inputArgArray[i] === 'string') {\r\n        throw new Error(`toNetInput -${getIdxHint(i)} string passed, but could not resolve HTMLElement for element id ${inputArgArray[i]}`)\r\n      }\r\n\r\n      throw new Error(`toNetInput -${getIdxHint(i)} expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id`)\r\n    }\r\n\r\n    if (isTensor4D(input)) {\r\n      // if tf.Tensor4D is passed in the input array, the batch size has to be 1\r\n      const batchSize = input.shape[0]\r\n      if (batchSize !== 1) {\r\n        throw new Error(`toNetInput -${getIdxHint(i)} tf.Tensor4D with batchSize ${batchSize} passed, but not supported in input array`)\r\n      }\r\n    }\r\n  })\r\n\r\n  // wait for all media elements being loaded\r\n  await Promise.all(\r\n    inputArray.map(input => isMediaElement(input) && awaitMediaLoaded(input))\r\n  )\r\n\r\n  return new NetInput(inputArray, Array.isArray(inputs))\r\n}","import { FaceDetection } from '../classes/FaceDetection';\r\nimport { Rect } from '../classes/Rect';\r\nimport { env } from '../env';\r\nimport { createCanvas } from './createCanvas';\r\nimport { getContext2dOrThrow } from './getContext2dOrThrow';\r\nimport { imageTensorToCanvas } from './imageTensorToCanvas';\r\nimport { toNetInput } from './toNetInput';\r\nimport { TNetInput } from './types';\r\n\r\n/**\r\n * Extracts the image regions containing the detected faces.\r\n *\r\n * @param input The image that face detection has been performed on.\r\n * @param detections The face detection results or face bounding boxes for that image.\r\n * @returns The Canvases of the corresponding image region for each detected face.\r\n */\r\nexport async function extractFaces(\r\n  input: TNetInput,\r\n  detections: Array<FaceDetection | Rect>\r\n): Promise<HTMLCanvasElement[]> {\r\n\r\n  const { Canvas } = env.getEnv()\r\n\r\n  let canvas = input as HTMLCanvasElement\r\n\r\n  if (!(input instanceof Canvas)) {\r\n    const netInput = await toNetInput(input)\r\n\r\n    if (netInput.batchSize > 1) {\r\n      throw new Error('extractFaces - batchSize > 1 not supported')\r\n    }\r\n\r\n    const tensorOrCanvas = netInput.getInput(0)\r\n    canvas = tensorOrCanvas instanceof Canvas\r\n      ? tensorOrCanvas\r\n      : await imageTensorToCanvas(tensorOrCanvas)\r\n  }\r\n\r\n  const ctx = getContext2dOrThrow(canvas)\r\n  const boxes = detections.map(\r\n    det => det instanceof FaceDetection\r\n      ? det.forSize(canvas.width, canvas.height).box.floor()\r\n      : det\r\n  )\r\n    .map(box => box.clipAtImageBorders(canvas.width, canvas.height))\r\n\r\n  return boxes.map(({ x, y, width, height }) => {\r\n    const faceImg = createCanvas({ width, height })\r\n    getContext2dOrThrow(faceImg)\r\n      .putImageData(ctx.getImageData(x, y, width, height), 0, 0)\r\n    return faceImg\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Rect } from '../classes';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { isTensor3D, isTensor4D } from '../utils';\r\n\r\n/**\r\n * Extracts the tensors of the image regions containing the detected faces.\r\n * Useful if you want to compute the face descriptors for the face images.\r\n * Using this method is faster then extracting a canvas for each face and\r\n * converting them to tensors individually.\r\n *\r\n * @param imageTensor The image tensor that face detection has been performed on.\r\n * @param detections The face detection results or face bounding boxes for that image.\r\n * @returns Tensors of the corresponding image region for each detected face.\r\n */\r\nexport async function extractFaceTensors(\r\n  imageTensor: tf.Tensor3D | tf.Tensor4D,\r\n  detections: Array<FaceDetection | Rect>\r\n): Promise<tf.Tensor3D[]> {\r\n\r\n  if (!isTensor3D(imageTensor) && !isTensor4D(imageTensor)) {\r\n    throw new Error('extractFaceTensors - expected image tensor to be 3D or 4D')\r\n  }\r\n\r\n  if (isTensor4D(imageTensor) && imageTensor.shape[0] > 1) {\r\n    throw new Error('extractFaceTensors - batchSize > 1 not supported')\r\n  }\r\n\r\n  return tf.tidy(() => {\r\n    const [imgHeight, imgWidth, numChannels] = imageTensor.shape.slice(isTensor4D(imageTensor) ? 1 : 0)\r\n\r\n    const boxes = detections.map(\r\n      det => det instanceof FaceDetection\r\n        ? det.forSize(imgWidth, imgHeight).box\r\n        : det\r\n    )\r\n      .map(box => box.clipAtImageBorders(imgWidth, imgHeight))\r\n\r\n    const faceTensors = boxes.map(({ x, y, width, height }) =>\r\n      tf.slice3d(imageTensor.as3D(imgHeight, imgWidth, numChannels), [y, x, 0], [height, width, numChannels])\r\n    )\r\n\r\n    return faceTensors\r\n  })\r\n}","import { env } from '../env';\r\n\r\nexport async function fetchOrThrow(\r\n  url: string,\r\n  init?: RequestInit\r\n): Promise<Response> {\r\n\r\n  const fetch = env.getEnv().fetch\r\n  const res = await fetch(url, init)\r\n  if (!(res.status < 400)) {\r\n    throw new Error(`failed to fetch: (${res.status}) ${res.statusText}, from url: ${res.url}`)\r\n  }\r\n  return res\r\n}","import { bufferToImage } from './bufferToImage';\r\nimport { fetchOrThrow } from './fetchOrThrow';\r\n\r\nexport async function fetchImage(uri: string): Promise<HTMLImageElement> {\r\n  const res = await fetchOrThrow(uri)\r\n  const blob = await (res).blob()\r\n\r\n  if (!blob.type.startsWith('image/')) {\r\n    throw new Error(`fetchImage - expected blob type to be of type image/*, instead have: ${blob.type}, for url: ${res.url}`)\r\n  }\r\n  return bufferToImage(blob)\r\n}\r\n","import { fetchOrThrow } from './fetchOrThrow';\r\n\r\nexport async function fetchJson<T>(uri: string): Promise<T> {\r\n  return (await fetchOrThrow(uri)).json()\r\n}\r\n","import { fetchOrThrow } from './fetchOrThrow';\r\n\r\nexport async function fetchNetWeights(uri: string): Promise<Float32Array> {\r\n  return new Float32Array(await (await fetchOrThrow(uri)).arrayBuffer())\r\n}\r\n","export function getModelUris(uri: string | undefined, defaultModelName: string) {\r\n  const defaultManifestFilename = `${defaultModelName}-weights_manifest.json`\r\n\r\n  if (!uri) {\r\n    return {\r\n      modelBaseUri: '',\r\n      manifestUri: defaultManifestFilename\r\n    }\r\n  }\r\n\r\n  if (uri === '/') {\r\n    return {\r\n      modelBaseUri: '/',\r\n      manifestUri: `/${defaultManifestFilename}`\r\n    }\r\n  }\r\n  const protocol = uri.startsWith('http://') ? 'http://' : uri.startsWith('https://') ? 'https://' : '';\r\n  uri = uri.replace(protocol, '');\r\n\r\n  const parts = uri.split('/').filter(s => s)\r\n\r\n  const manifestFile = uri.endsWith('.json')\r\n    ? parts[parts.length - 1]\r\n    : defaultManifestFilename\r\n\r\n  let modelBaseUri = protocol + (uri.endsWith('.json') ? parts.slice(0, parts.length - 1) : parts).join('/')\r\n  modelBaseUri = uri.startsWith('/') ? `/${modelBaseUri}` : modelBaseUri\r\n\r\n  return {\r\n    modelBaseUri,\r\n    manifestUri: modelBaseUri === '/' ? `/${manifestFile}` : `${modelBaseUri}/${manifestFile}`\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { getModelUris } from '../common/getModelUris';\r\nimport { fetchJson } from './fetchJson';\r\n\r\nexport async function loadWeightMap(\r\n  uri: string | undefined,\r\n  defaultModelName: string,\r\n): Promise<tf.NamedTensorMap> {\r\n  const { manifestUri, modelBaseUri } = getModelUris(uri, defaultModelName)\r\n\r\n  const manifest = await fetchJson<tf.io.WeightsManifestConfig>(manifestUri)\r\n\r\n  return tf.io.loadWeights(manifest, modelBaseUri)\r\n}","import { IDimensions } from '../classes';\r\nimport { getMediaDimensions } from './getMediaDimensions';\r\n\r\nexport function matchDimensions(input: IDimensions, reference: IDimensions, useMediaDimensions: boolean = false) {\r\n  const { width, height } = useMediaDimensions\r\n    ? getMediaDimensions(reference)\r\n    : reference\r\n  input.width = width\r\n  input.height = height\r\n  return { width, height }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ParamMapping } from './common';\r\nimport { getModelUris } from './common/getModelUris';\r\nimport { loadWeightMap } from './dom';\r\nimport { env } from './env';\r\n\r\nexport abstract class NeuralNetwork<TNetParams> {\r\n\r\n  protected _params: TNetParams | undefined = undefined\r\n  protected _paramMappings: ParamMapping[] = []\r\n\r\n  constructor(protected _name: string) {}\r\n\r\n  public get params(): TNetParams | undefined { return this._params }\r\n  public get paramMappings(): ParamMapping[] { return this._paramMappings }\r\n  public get isLoaded(): boolean { return !!this.params }\r\n\r\n  public getParamFromPath(paramPath: string): tf.Tensor {\r\n    const { obj, objProp } = this.traversePropertyPath(paramPath)\r\n    return obj[objProp]\r\n  }\r\n\r\n  public reassignParamFromPath(paramPath: string, tensor: tf.Tensor) {\r\n    const { obj, objProp } = this.traversePropertyPath(paramPath)\r\n    obj[objProp].dispose()\r\n    obj[objProp] = tensor\r\n  }\r\n\r\n  public getParamList() {\r\n    return this._paramMappings.map(({ paramPath }) => ({\r\n      path: paramPath,\r\n      tensor: this.getParamFromPath(paramPath)\r\n    }))\r\n  }\r\n\r\n  public getTrainableParams() {\r\n    return this.getParamList().filter(param => param.tensor instanceof tf.Variable)\r\n  }\r\n\r\n  public getFrozenParams() {\r\n    return this.getParamList().filter(param => !(param.tensor instanceof tf.Variable))\r\n  }\r\n\r\n  public variable() {\r\n    this.getFrozenParams().forEach(({ path, tensor }) => {\r\n      this.reassignParamFromPath(path, tensor.variable())\r\n    })\r\n  }\r\n\r\n  public freeze() {\r\n    this.getTrainableParams().forEach(({ path, tensor: variable }) => {\r\n      const tensor = tf.tensor(variable.dataSync())\r\n      variable.dispose()\r\n      this.reassignParamFromPath(path, tensor)\r\n    })\r\n  }\r\n\r\n  public dispose(throwOnRedispose: boolean = true) {\r\n    this.getParamList().forEach(param => {\r\n      if (throwOnRedispose && param.tensor.isDisposed) {\r\n        throw new Error(`param tensor has already been disposed for path ${param.path}`)\r\n      }\r\n      param.tensor.dispose()\r\n    })\r\n    this._params = undefined\r\n  }\r\n\r\n  public serializeParams(): Float32Array {\r\n    return new Float32Array(\r\n      this.getParamList()\r\n        .map(({ tensor }) => Array.from(tensor.dataSync()) as number[])\r\n        .reduce((flat, arr) => flat.concat(arr))\r\n    )\r\n  }\r\n\r\n  public async load(weightsOrUrl: Float32Array | string | undefined): Promise<void> {\r\n    if (weightsOrUrl instanceof Float32Array) {\r\n      this.extractWeights(weightsOrUrl)\r\n      return\r\n    }\r\n\r\n    await this.loadFromUri(weightsOrUrl)\r\n  }\r\n\r\n  public async loadFromUri(uri: string | undefined) {\r\n    if (uri && typeof uri !== 'string') {\r\n      throw new Error(`${this._name}.loadFromUri - expected model uri`)\r\n    }\r\n\r\n    const weightMap = await loadWeightMap(uri, this.getDefaultModelName())\r\n    this.loadFromWeightMap(weightMap)\r\n  }\r\n\r\n  public async loadFromDisk(filePath: string | undefined) {\r\n    if (filePath && typeof filePath !== 'string') {\r\n      throw new Error(`${this._name}.loadFromDisk - expected model file path`)\r\n    }\r\n\r\n    const { readFile } = env.getEnv()\r\n\r\n    const { manifestUri, modelBaseUri } = getModelUris(filePath, this.getDefaultModelName())\r\n\r\n    const fetchWeightsFromDisk = (filePaths: string[]) => Promise.all(\r\n      filePaths.map(filePath => readFile(filePath).then(buf => buf.buffer))\r\n    )\r\n    const loadWeights = tf.io.weightsLoaderFactory(fetchWeightsFromDisk)\r\n\r\n    const manifest = JSON.parse((await readFile(manifestUri)).toString())\r\n    const weightMap = await loadWeights(manifest, modelBaseUri)\r\n\r\n    this.loadFromWeightMap(weightMap)\r\n  }\r\n\r\n  public loadFromWeightMap(weightMap: tf.NamedTensorMap) {\r\n    const {\r\n      paramMappings,\r\n      params\r\n    } = this.extractParamsFromWeigthMap(weightMap)\r\n\r\n    this._paramMappings = paramMappings\r\n    this._params = params\r\n  }\r\n\r\n  public extractWeights(weights: Float32Array) {\r\n    const {\r\n      paramMappings,\r\n      params\r\n    } = this.extractParams(weights)\r\n\r\n    this._paramMappings = paramMappings\r\n    this._params = params\r\n  }\r\n\r\n  private traversePropertyPath(paramPath: string) {\r\n    if (!this.params) {\r\n      throw new Error(`traversePropertyPath - model has no loaded params`)\r\n    }\r\n\r\n    const result = paramPath.split('/').reduce((res: { nextObj: any, obj?: any, objProp?: string }, objProp) => {\r\n      if (!res.nextObj.hasOwnProperty(objProp)) {\r\n        throw new Error(`traversePropertyPath - object does not have property ${objProp}, for path ${paramPath}`)\r\n      }\r\n\r\n      return { obj: res.nextObj, objProp, nextObj: res.nextObj[objProp] }\r\n    }, { nextObj: this.params })\r\n\r\n    const { obj, objProp } = result\r\n    if (!obj || !objProp || !(obj[objProp] instanceof tf.Tensor)) {\r\n      throw new Error(`traversePropertyPath - parameter is not a tensor, for path ${paramPath}`)\r\n    }\r\n\r\n    return { obj, objProp }\r\n  }\r\n\r\n  protected abstract getDefaultModelName(): string\r\n  protected abstract extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): { params: TNetParams, paramMappings: ParamMapping[] }\r\n  protected abstract extractParams(weights: Float32Array): { params: TNetParams, paramMappings: ParamMapping[] }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { SeparableConvParams } from './types';\r\n\r\nexport function depthwiseSeparableConv(\r\n  x: tf.Tensor4D,\r\n  params: SeparableConvParams,\r\n  stride: [number, number]\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    let out = tf.separableConv2d(x, params.depthwise_filter, params.pointwise_filter, stride, 'same')\r\n    out = tf.add(out, params.bias)\r\n    return out\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, SeparableConvParams } from '../common';\r\nimport { depthwiseSeparableConv } from '../common/depthwiseSeparableConv';\r\nimport { DenseBlock3Params, DenseBlock4Params } from './types';\r\n\r\nexport function denseBlock3(\r\n  x: tf.Tensor4D,\r\n  denseBlockParams: DenseBlock3Params,\r\n  isFirstLayer: boolean = false\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const out1 = tf.relu(\r\n      isFirstLayer\r\n        ? tf.add(\r\n          tf.conv2d(x, (denseBlockParams.conv0 as ConvParams).filters, [2, 2], 'same'),\r\n          denseBlockParams.conv0.bias\r\n        )\r\n        : depthwiseSeparableConv(x, denseBlockParams.conv0 as SeparableConvParams, [2, 2])\r\n    ) as tf.Tensor4D\r\n    const out2 = depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1])\r\n\r\n    const in3 = tf.relu(tf.add(out1, out2)) as tf.Tensor4D\r\n    const out3 = depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1])\r\n\r\n    return tf.relu(tf.add(out1, tf.add(out2, out3))) as tf.Tensor4D\r\n  })\r\n}\r\n\r\nexport function denseBlock4(\r\n  x: tf.Tensor4D,\r\n  denseBlockParams: DenseBlock4Params,\r\n  isFirstLayer: boolean = false,\r\n  isScaleDown: boolean = true\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const out1 = tf.relu(\r\n      isFirstLayer\r\n        ? tf.add(\r\n          tf.conv2d(x, (denseBlockParams.conv0 as ConvParams).filters, isScaleDown ? [2, 2] : [1, 1], 'same'),\r\n          denseBlockParams.conv0.bias\r\n        )\r\n        : depthwiseSeparableConv(x, denseBlockParams.conv0 as SeparableConvParams, isScaleDown ? [2, 2] : [1, 1])\r\n    ) as tf.Tensor4D\r\n    const out2 = depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1])\r\n\r\n    const in3 = tf.relu(tf.add(out1, out2)) as tf.Tensor4D\r\n    const out3 = depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1])\r\n\r\n    const in4 = tf.relu(tf.add(out1, tf.add(out2, out3))) as tf.Tensor4D\r\n    const out4 = depthwiseSeparableConv(in4, denseBlockParams.conv3, [1, 1])\r\n\r\n    return tf.relu(tf.add(out1, tf.add(out2, tf.add(out3, out4)))) as tf.Tensor4D\r\n  })\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams } from './types';\r\n\r\nexport function convLayer(\r\n  x: tf.Tensor4D,\r\n  params: ConvParams,\r\n  padding: 'valid' | 'same' = 'same',\r\n  withRelu: boolean = false\r\n): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const out = tf.add(\r\n      tf.conv2d(x, params.filters, [1, 1], padding),\r\n      params.bias\r\n    ) as tf.Tensor4D\r\n\r\n    return withRelu ? tf.relu(out) : out\r\n  })\r\n}","import { ParamMapping } from './types';\r\n\r\nexport function disposeUnusedWeightTensors(weightMap: any, paramMappings: ParamMapping[]) {\r\n  Object.keys(weightMap).forEach(path => {\r\n    if (!paramMappings.some(pm => pm.originalPath === path)) {\r\n      weightMap[path].dispose()\r\n    }\r\n  })\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, ExtractWeightsFunction, ParamMapping } from './types';\r\n\r\nexport function extractConvParamsFactory(\r\n  extractWeights: ExtractWeightsFunction,\r\n  paramMappings: ParamMapping[]\r\n) {\r\n\r\n  return function(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    filterSize: number,\r\n    mappedPrefix: string\r\n  ): ConvParams {\r\n\r\n    const filters = tf.tensor4d(\r\n      extractWeights(channelsIn * channelsOut * filterSize * filterSize),\r\n      [filterSize, filterSize, channelsIn, channelsOut]\r\n    )\r\n    const bias = tf.tensor1d(extractWeights(channelsOut))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/filters` },\r\n      { paramPath: `${mappedPrefix}/bias` }\r\n    )\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ExtractWeightsFunction, FCParams, ParamMapping } from './types';\r\n\r\n\r\nexport function extractFCParamsFactory(\r\n  extractWeights: ExtractWeightsFunction,\r\n  paramMappings: ParamMapping[]\r\n) {\r\n\r\n  return function(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    mappedPrefix: string\r\n  ): FCParams {\r\n\r\n    const fc_weights = tf.tensor2d(extractWeights(channelsIn * channelsOut), [channelsIn, channelsOut])\r\n    const fc_bias = tf.tensor1d(extractWeights(channelsOut))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/weights` },\r\n      { paramPath: `${mappedPrefix}/bias` }\r\n    )\r\n\r\n    return {\r\n      weights: fc_weights,\r\n      bias: fc_bias\r\n    }\r\n  }\r\n\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport type ExtractWeightsFunction = (numWeights: number) => Float32Array\r\n\r\nexport type ParamMapping = {\r\n  originalPath?: string\r\n  paramPath: string\r\n}\r\n\r\nexport type ConvParams = {\r\n  filters: tf.Tensor4D\r\n  bias: tf.Tensor1D\r\n}\r\n\r\nexport type FCParams = {\r\n  weights: tf.Tensor2D\r\n  bias: tf.Tensor1D\r\n}\r\n\r\nexport class SeparableConvParams {\r\n  constructor(\r\n    public depthwise_filter: tf.Tensor4D,\r\n    public pointwise_filter: tf.Tensor4D,\r\n    public bias: tf.Tensor1D\r\n  ) {}\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ExtractWeightsFunction, ParamMapping, SeparableConvParams } from './types';\r\n\r\nexport function extractSeparableConvParamsFactory(\r\n  extractWeights: ExtractWeightsFunction,\r\n  paramMappings: ParamMapping[]\r\n) {\r\n\r\n  return function(channelsIn: number, channelsOut: number, mappedPrefix: string): SeparableConvParams {\r\n    const depthwise_filter = tf.tensor4d(extractWeights(3 * 3 * channelsIn), [3, 3, channelsIn, 1])\r\n    const pointwise_filter = tf.tensor4d(extractWeights(channelsIn * channelsOut), [1, 1, channelsIn, channelsOut])\r\n    const bias = tf.tensor1d(extractWeights(channelsOut))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/depthwise_filter` },\r\n      { paramPath: `${mappedPrefix}/pointwise_filter` },\r\n      { paramPath: `${mappedPrefix}/bias` }\r\n    )\r\n\r\n    return new SeparableConvParams(\r\n      depthwise_filter,\r\n      pointwise_filter,\r\n      bias\r\n    )\r\n  }\r\n\r\n}\r\n\r\nexport function loadSeparableConvParamsFactory(\r\n  extractWeightEntry: <T>(originalPath: string, paramRank: number) => T\r\n) {\r\n\r\n  return function (prefix: string): SeparableConvParams {\r\n    const depthwise_filter = extractWeightEntry<tf.Tensor4D>(`${prefix}/depthwise_filter`, 4)\r\n    const pointwise_filter = extractWeightEntry<tf.Tensor4D>(`${prefix}/pointwise_filter`, 4)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n\r\n    return new SeparableConvParams(\r\n      depthwise_filter,\r\n      pointwise_filter,\r\n      bias\r\n    )\r\n  }\r\n\r\n}\r\n","import { isTensor } from '../utils';\r\nimport { ParamMapping } from './types';\r\n\r\nexport function extractWeightEntryFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  return function<T> (originalPath: string, paramRank: number, mappedPath?: string): T {\r\n    const tensor = weightMap[originalPath]\r\n\r\n    if (!isTensor(tensor, paramRank)) {\r\n      throw new Error(`expected weightMap[${originalPath}] to be a Tensor${paramRank}D, instead have ${tensor}`)\r\n    }\r\n\r\n    paramMappings.push(\r\n      { originalPath, paramPath: mappedPath || originalPath }\r\n    )\r\n\r\n    return tensor\r\n  }\r\n\r\n}\r\n","export function extractWeightsFactory(weights: Float32Array) {\r\n  let remainingWeights = weights\r\n\r\n  function extractWeights(numWeights: number): Float32Array {\r\n    const ret = remainingWeights.slice(0, numWeights)\r\n    remainingWeights = remainingWeights.slice(numWeights)\r\n    return ret\r\n  }\r\n\r\n  function getRemainingWeights(): Float32Array {\r\n    return remainingWeights\r\n  }\r\n\r\n  return {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  }\r\n}","import {\r\n  extractConvParamsFactory,\r\n  extractSeparableConvParamsFactory,\r\n  ExtractWeightsFunction,\r\n  ParamMapping,\r\n} from '../common';\r\nimport { DenseBlock3Params, DenseBlock4Params } from './types';\r\n\r\nexport function extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  const extractConvParams = extractConvParamsFactory(extractWeights, paramMappings)\r\n  const extractSeparableConvParams = extractSeparableConvParamsFactory(extractWeights, paramMappings)\r\n\r\n  function extractDenseBlock3Params(channelsIn: number, channelsOut: number, mappedPrefix: string, isFirstLayer: boolean = false): DenseBlock3Params {\r\n\r\n    const conv0 = isFirstLayer\r\n      ? extractConvParams(channelsIn, channelsOut, 3, `${mappedPrefix}/conv0`)\r\n      : extractSeparableConvParams(channelsIn, channelsOut, `${mappedPrefix}/conv0`)\r\n    const conv1 = extractSeparableConvParams(channelsOut, channelsOut, `${mappedPrefix}/conv1`)\r\n    const conv2 = extractSeparableConvParams(channelsOut, channelsOut, `${mappedPrefix}/conv2`)\r\n\r\n    return { conv0, conv1, conv2 }\r\n  }\r\n\r\n  function extractDenseBlock4Params(channelsIn: number, channelsOut: number, mappedPrefix: string, isFirstLayer: boolean = false): DenseBlock4Params {\r\n\r\n    const { conv0, conv1, conv2 } = extractDenseBlock3Params(channelsIn, channelsOut, mappedPrefix, isFirstLayer)\r\n    const conv3 = extractSeparableConvParams(channelsOut, channelsOut, `${mappedPrefix}/conv3`)\r\n\r\n    return { conv0, conv1, conv2, conv3 }\r\n  }\r\n\r\n  return {\r\n    extractDenseBlock3Params,\r\n    extractDenseBlock4Params\r\n  }\r\n\r\n}","import { extractWeightsFactory, ParamMapping } from '../common';\r\nimport { extractorsFactory } from './extractorsFactory';\r\nimport { FaceFeatureExtractorParams } from './types';\r\n\r\n\r\nexport function extractParams(weights: Float32Array): { params: FaceFeatureExtractorParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const {\r\n    extractDenseBlock4Params\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const dense0 = extractDenseBlock4Params(3, 32, 'dense0', true)\r\n  const dense1 = extractDenseBlock4Params(32, 64, 'dense1')\r\n  const dense2 = extractDenseBlock4Params(64, 128, 'dense2')\r\n  const dense3 = extractDenseBlock4Params(128, 256, 'dense3')\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { dense0, dense1, dense2, dense3 }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams } from './types';\r\n\r\nexport function loadConvParamsFactory(extractWeightEntry: <T>(originalPath: string, paramRank: number) => T) {\r\n  return function(prefix: string): ConvParams {\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/filters`, 4)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n\r\n    return { filters, bias }\r\n  }\r\n}","import { extractWeightEntryFactory, loadSeparableConvParamsFactory, ParamMapping } from '../common';\r\nimport { loadConvParamsFactory } from '../common/loadConvParamsFactory';\r\nimport { DenseBlock3Params, DenseBlock4Params } from './types';\r\n\r\nexport function loadParamsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  const extractConvParams = loadConvParamsFactory(extractWeightEntry)\r\n  const extractSeparableConvParams = loadSeparableConvParamsFactory(extractWeightEntry)\r\n\r\n  function extractDenseBlock3Params(prefix: string, isFirstLayer: boolean = false): DenseBlock3Params {\r\n    const conv0 = isFirstLayer\r\n      ? extractConvParams(`${prefix}/conv0`)\r\n      : extractSeparableConvParams(`${prefix}/conv0`)\r\n    const conv1 = extractSeparableConvParams(`${prefix}/conv1`)\r\n    const conv2 = extractSeparableConvParams(`${prefix}/conv2`)\r\n\r\n    return { conv0, conv1, conv2 }\r\n  }\r\n\r\n  function extractDenseBlock4Params(prefix: string, isFirstLayer: boolean = false): DenseBlock4Params {\r\n    const conv0 = isFirstLayer\r\n      ? extractConvParams(`${prefix}/conv0`)\r\n      : extractSeparableConvParams(`${prefix}/conv0`)\r\n    const conv1 = extractSeparableConvParams(`${prefix}/conv1`)\r\n    const conv2 = extractSeparableConvParams(`${prefix}/conv2`)\r\n    const conv3 = extractSeparableConvParams(`${prefix}/conv3`)\r\n\r\n    return { conv0, conv1, conv2, conv3 }\r\n  }\r\n\r\n  return {\r\n    extractDenseBlock3Params,\r\n    extractDenseBlock4Params\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, ParamMapping } from '../common';\r\nimport { loadParamsFactory } from './loadParamsFactory';\r\nimport { FaceFeatureExtractorParams } from './types';\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: FaceFeatureExtractorParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractDenseBlock4Params\r\n  } = loadParamsFactory(weightMap, paramMappings)\r\n\r\n  const params = {\r\n    dense0: extractDenseBlock4Params('dense0', true),\r\n    dense1: extractDenseBlock4Params('dense1'),\r\n    dense2: extractDenseBlock4Params('dense2'),\r\n    dense3: extractDenseBlock4Params('dense3')\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { normalize } from '../ops';\r\nimport { denseBlock4 } from './denseBlock';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { FaceFeatureExtractorParams, IFaceFeatureExtractor } from './types';\r\n\r\nexport class FaceFeatureExtractor extends NeuralNetwork<FaceFeatureExtractorParams> implements IFaceFeatureExtractor<FaceFeatureExtractorParams> {\r\n\r\n  constructor() {\r\n    super('FaceFeatureExtractor')\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor4D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('FaceFeatureExtractor - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(112, true)\r\n      const meanRgb = [122.782, 117.001, 104.298]\r\n      const normalized = normalize(batchTensor, meanRgb).div(tf.scalar(255)) as tf.Tensor4D\r\n\r\n      let out = denseBlock4(normalized, params.dense0, true)\r\n      out = denseBlock4(out, params.dense1)\r\n      out = denseBlock4(out, params.dense2)\r\n      out = denseBlock4(out, params.dense3)\r\n      out = tf.avgPool(out, [7, 7], [2, 2], 'valid')\r\n\r\n      return out\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor4D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_feature_extractor_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FCParams } from './types';\r\n\r\nexport function fullyConnectedLayer(\r\n  x: tf.Tensor2D,\r\n  params: FCParams\r\n): tf.Tensor2D {\r\n  return tf.tidy(() =>\r\n    tf.add(\r\n      tf.matMul(x, params.weights),\r\n      params.bias\r\n    )\r\n  )\r\n}","import { extractFCParamsFactory, extractWeightsFactory, ParamMapping } from '../common';\r\nimport { NetParams } from './types';\r\n\r\nexport function extractParams(weights: Float32Array, channelsIn: number, channelsOut: number): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const extractFCParams = extractFCParamsFactory(extractWeights, paramMappings)\r\n\r\n  const fc = extractFCParams(channelsIn, channelsOut, 'fc')\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { fc }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, extractWeightEntryFactory, FCParams, ParamMapping } from '../common';\r\nimport { NetParams } from './types';\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractFcParams(prefix: string): FCParams {\r\n    const weights = extractWeightEntry<tf.Tensor2D>(`${prefix}/weights`, 2)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n    return { weights, bias }\r\n  }\r\n\r\n  const params = {\r\n    fc: extractFcParams('fc')\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function seperateWeightMaps(weightMap: tf.NamedTensorMap) {\r\n\r\n  const featureExtractorMap: tf.NamedTensorMap = {}\r\n  const classifierMap: tf.NamedTensorMap = {}\r\n\r\n  Object.keys(weightMap).forEach(key => {\r\n    const map = key.startsWith('fc') ? classifierMap : featureExtractorMap\r\n    map[key] = weightMap[key]\r\n  })\r\n\r\n  return { featureExtractorMap, classifierMap }\r\n\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { fullyConnectedLayer } from '../common/fullyConnectedLayer';\r\nimport { NetInput } from '../dom';\r\nimport {\r\n  FaceFeatureExtractorParams,\r\n  IFaceFeatureExtractor,\r\n  TinyFaceFeatureExtractorParams,\r\n} from '../faceFeatureExtractor/types';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { NetParams } from './types';\r\nimport { seperateWeightMaps } from './util';\r\n\r\nexport abstract class FaceProcessor<\r\n  TExtractorParams extends FaceFeatureExtractorParams | TinyFaceFeatureExtractorParams\r\n>\r\n  extends NeuralNetwork<NetParams> {\r\n\r\n  protected _faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>\r\n\r\n  constructor(_name: string, faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>) {\r\n    super(_name)\r\n    this._faceFeatureExtractor = faceFeatureExtractor\r\n  }\r\n\r\n  public get faceFeatureExtractor(): IFaceFeatureExtractor<TExtractorParams> {\r\n    return this._faceFeatureExtractor\r\n  }\r\n\r\n  protected abstract getDefaultModelName(): string\r\n  protected abstract getClassifierChannelsIn(): number\r\n  protected abstract getClassifierChannelsOut(): number\r\n\r\n  public runNet(input: NetInput | tf.Tensor4D): tf.Tensor2D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error(`${this._name} - load model before inference`)\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const bottleneckFeatures = input instanceof NetInput\r\n        ? this.faceFeatureExtractor.forwardInput(input)\r\n        : input\r\n      return fullyConnectedLayer(bottleneckFeatures.as2D(bottleneckFeatures.shape[0], -1), params.fc)\r\n    })\r\n  }\r\n\r\n  public dispose(throwOnRedispose: boolean = true) {\r\n    this.faceFeatureExtractor.dispose(throwOnRedispose)\r\n    super.dispose(throwOnRedispose)\r\n  }\r\n\r\n  public loadClassifierParams(weights: Float32Array) {\r\n    const { params, paramMappings } = this.extractClassifierParams(weights)\r\n    this._params = params\r\n    this._paramMappings = paramMappings\r\n  }\r\n\r\n  public extractClassifierParams(weights: Float32Array) {\r\n    return extractParams(weights, this.getClassifierChannelsIn(), this.getClassifierChannelsOut())\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n\r\n    const { featureExtractorMap, classifierMap } = seperateWeightMaps(weightMap)\r\n\r\n    this.faceFeatureExtractor.loadFromWeightMap(featureExtractorMap)\r\n\r\n    return extractParamsFromWeigthMap(classifierMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n\r\n    const cIn = this.getClassifierChannelsIn()\r\n    const cOut = this.getClassifierChannelsOut()\r\n    const classifierWeightSize = (cOut * cIn ) + cOut\r\n\r\n    const featureExtractorWeights = weights.slice(0, weights.length - classifierWeightSize)\r\n    const classifierWeights = weights.slice(weights.length - classifierWeightSize)\r\n\r\n    this.faceFeatureExtractor.extractWeights(featureExtractorWeights)\r\n    return this.extractClassifierParams(classifierWeights)\r\n  }\r\n}","export const FACE_EXPRESSION_LABELS = ['neutral', 'happy', 'sad', 'angry', 'fearful', 'disgusted', 'surprised']\r\n\r\nexport class FaceExpressions {\r\n  public neutral: number\r\n  public happy: number\r\n  public sad: number\r\n  public angry: number\r\n  public fearful: number\r\n  public disgusted: number\r\n  public surprised: number\r\n\r\n  constructor(probabilities: number[] | Float32Array) {\r\n    if (probabilities.length !== 7) {\r\n      throw new Error(`FaceExpressions.constructor - expected probabilities.length to be 7, have: ${probabilities.length}`)\r\n    }\r\n\r\n    FACE_EXPRESSION_LABELS.forEach((expression, idx) => {\r\n      this[expression] = probabilities[idx]\r\n    })\r\n  }\r\n\r\n  asSortedArray() {\r\n    return FACE_EXPRESSION_LABELS\r\n      .map(expression => ({ expression, probability: this[expression] as number }))\r\n      .sort((e0, e1) => e1.probability - e0.probability)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { FaceFeatureExtractor } from '../faceFeatureExtractor/FaceFeatureExtractor';\r\nimport { FaceFeatureExtractorParams } from '../faceFeatureExtractor/types';\r\nimport { FaceProcessor } from '../faceProcessor/FaceProcessor';\r\nimport { FaceExpressions } from './FaceExpressions';\r\n\r\nexport class FaceExpressionNet extends FaceProcessor<FaceFeatureExtractorParams> {\r\n\r\n  constructor(faceFeatureExtractor: FaceFeatureExtractor = new FaceFeatureExtractor()) {\r\n    super('FaceExpressionNet', faceFeatureExtractor)\r\n  }\r\n\r\n  public forwardInput(input: NetInput | tf.Tensor4D): tf.Tensor2D {\r\n    return tf.tidy(() => tf.softmax(this.runNet(input)))\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor2D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async predictExpressions(input: TNetInput) {\r\n    const netInput = await toNetInput(input)\r\n    const out = await this.forwardInput(netInput)\r\n    const probabilitesByBatch = await Promise.all(tf.unstack(out).map(async t => {\r\n      const data = await t.data()\r\n      t.dispose()\r\n      return data\r\n    }))\r\n    out.dispose()\r\n\r\n    const predictionsByBatch = probabilitesByBatch\r\n      .map(probabilites => new FaceExpressions(probabilites as Float32Array))\r\n\r\n    return netInput.isBatchInput\r\n      ? predictionsByBatch\r\n      : predictionsByBatch[0]\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_expression_model'\r\n  }\r\n\r\n  protected getClassifierChannelsIn(): number {\r\n    return 256\r\n  }\r\n\r\n  protected getClassifierChannelsOut(): number {\r\n    return 7\r\n  }\r\n}","import { FaceExpressions } from '../faceExpressionNet/FaceExpressions';\r\n\r\nexport type WithFaceExpressions<TSource> = TSource & {\r\n  expressions: FaceExpressions\r\n}\r\n\r\nexport function isWithFaceExpressions(obj: any): obj is WithFaceExpressions<{}> {\r\n  return obj['expressions'] instanceof FaceExpressions\r\n}\r\n\r\nexport function extendWithFaceExpressions<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  expressions: FaceExpressions\r\n): WithFaceExpressions<TSource> {\r\n\r\n  const extension = { expressions }\r\n  return Object.assign({}, sourceObj, extension)\r\n}","import { IPoint, Point } from '../classes';\r\nimport { FaceExpressions } from '../faceExpressionNet';\r\nimport { isWithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { isWithFaceExpressions, WithFaceExpressions } from '../factories/WithFaceExpressions';\r\nimport { round } from '../utils';\r\nimport { DrawTextField } from './DrawTextField';\r\n\r\nexport type DrawFaceExpressionsInput = FaceExpressions | WithFaceExpressions<{}>\r\n\r\nexport function drawFaceExpressions(\r\n  canvasArg: string | HTMLCanvasElement,\r\n  faceExpressions: DrawFaceExpressionsInput | Array<DrawFaceExpressionsInput>,\r\n  minConfidence = 0.1,\r\n  textFieldAnchor?: IPoint\r\n) {\r\n  const faceExpressionsArray = Array.isArray(faceExpressions) ? faceExpressions : [faceExpressions]\r\n\r\n  faceExpressionsArray.forEach(e => {\r\n    const expr = e instanceof FaceExpressions\r\n      ? e\r\n      : (isWithFaceExpressions(e) ? e.expressions : undefined)\r\n    if (!expr) {\r\n      throw new Error('drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof')\r\n    }\r\n\r\n    const sorted = expr.asSortedArray()\r\n    const resultsToDisplay = sorted.filter(expr => expr.probability > minConfidence)\r\n\r\n    const anchor = isWithFaceDetection(e)\r\n      ? e.detection.box.bottomLeft\r\n      : (textFieldAnchor || new Point(0, 0))\r\n\r\n    const drawTextField = new DrawTextField(\r\n      resultsToDisplay.map(expr => `${expr.expression} (${round(expr.probability)})`),\r\n      anchor\r\n    )\r\n    drawTextField.draw(canvasArg)\r\n  })\r\n}","import { FaceDetection } from '../classes/FaceDetection';\r\nimport { FaceLandmarks } from '../classes/FaceLandmarks';\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { isWithFaceDetection, WithFaceDetection } from './WithFaceDetection';\r\n\r\nexport type WithFaceLandmarks<\r\n  TSource extends WithFaceDetection<{}>,\r\n  TFaceLandmarks extends FaceLandmarks = FaceLandmarks68\r\n> = TSource & {\r\n  landmarks: TFaceLandmarks\r\n  unshiftedLandmarks: TFaceLandmarks\r\n  alignedRect: FaceDetection\r\n}\r\n\r\nexport function isWithFaceLandmarks(obj: any): obj is WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks> {\r\n  return isWithFaceDetection(obj)\r\n    && obj['landmarks'] instanceof FaceLandmarks\r\n    && obj['unshiftedLandmarks'] instanceof FaceLandmarks\r\n    && obj['alignedRect'] instanceof FaceDetection\r\n}\r\n\r\nexport function extendWithFaceLandmarks<\r\n  TSource extends WithFaceDetection<{}>,\r\n  TFaceLandmarks extends FaceLandmarks = FaceLandmarks68\r\n> (\r\n  sourceObj: TSource,\r\n  unshiftedLandmarks: TFaceLandmarks\r\n): WithFaceLandmarks<TSource, TFaceLandmarks> {\r\n\r\n  const { box: shift } = sourceObj.detection\r\n  const landmarks = unshiftedLandmarks.shiftBy<TFaceLandmarks>(shift.x, shift.y)\r\n\r\n  const rect = landmarks.align()\r\n  const { imageDims } = sourceObj.detection\r\n  const alignedRect = new FaceDetection(sourceObj.detection.score, rect.rescale(imageDims.reverse()), imageDims)\r\n\r\n  const extension = {\r\n    landmarks,\r\n    unshiftedLandmarks,\r\n    alignedRect\r\n  }\r\n\r\n  return Object.assign({}, sourceObj, extension)\r\n}","import { IPoint } from '../classes';\r\nimport { FaceLandmarks } from '../classes/FaceLandmarks';\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { getContext2dOrThrow } from '../dom/getContext2dOrThrow';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { isWithFaceLandmarks, WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { drawContour } from './drawContour';\r\n\r\nexport interface IDrawFaceLandmarksOptions {\r\n  drawLines?: boolean\r\n  drawPoints?: boolean\r\n  lineWidth?: number\r\n  pointSize?: number\r\n  lineColor?: string\r\n  pointColor?: string\r\n}\r\n\r\nexport class DrawFaceLandmarksOptions {\r\n  public drawLines: boolean\r\n  public drawPoints: boolean\r\n  public lineWidth: number\r\n  public pointSize: number\r\n  public lineColor: string\r\n  public pointColor: string\r\n\r\n  constructor(options: IDrawFaceLandmarksOptions = {}) {\r\n    const { drawLines = true, drawPoints = true, lineWidth, lineColor, pointSize, pointColor } = options\r\n    this.drawLines = drawLines\r\n    this.drawPoints = drawPoints\r\n    this.lineWidth = lineWidth || 1\r\n    this.pointSize = pointSize || 2\r\n    this.lineColor = lineColor || 'rgba(0, 255, 255, 1)'\r\n    this.pointColor = pointColor || 'rgba(255, 0, 255, 1)'\r\n  }\r\n}\r\n\r\nexport class DrawFaceLandmarks {\r\n  public faceLandmarks: FaceLandmarks\r\n  public options: DrawFaceLandmarksOptions\r\n\r\n  constructor(\r\n    faceLandmarks: FaceLandmarks,\r\n    options: IDrawFaceLandmarksOptions = {}\r\n  ) {\r\n    this.faceLandmarks = faceLandmarks\r\n    this.options = new DrawFaceLandmarksOptions(options)\r\n  }\r\n\r\n  draw(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D) {\r\n    const ctx = getContext2dOrThrow(canvasArg)\r\n\r\n    const { drawLines, drawPoints, lineWidth, lineColor, pointSize, pointColor } = this.options\r\n\r\n    if (drawLines && this.faceLandmarks instanceof FaceLandmarks68) {\r\n      ctx.strokeStyle = lineColor\r\n      ctx.lineWidth = lineWidth\r\n      drawContour(ctx, this.faceLandmarks.getJawOutline())\r\n      drawContour(ctx, this.faceLandmarks.getLeftEyeBrow())\r\n      drawContour(ctx, this.faceLandmarks.getRightEyeBrow())\r\n      drawContour(ctx, this.faceLandmarks.getNose())\r\n      drawContour(ctx, this.faceLandmarks.getLeftEye(), true)\r\n      drawContour(ctx, this.faceLandmarks.getRightEye(), true)\r\n      drawContour(ctx, this.faceLandmarks.getMouth(), true)\r\n    }\r\n\r\n    if (drawPoints) {\r\n      ctx.strokeStyle = pointColor\r\n      ctx.fillStyle = pointColor\r\n\r\n      const drawPoint = (pt: IPoint) => {\r\n        ctx.beginPath()\r\n        ctx.arc(pt.x, pt.y, pointSize, 0, 2 * Math.PI)\r\n        ctx.fill()\r\n      }\r\n      this.faceLandmarks.positions.forEach(drawPoint)\r\n    }\r\n  }\r\n}\r\n\r\nexport type DrawFaceLandmarksInput = FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>>\r\n\r\nexport function drawFaceLandmarks(\r\n  canvasArg: string | HTMLCanvasElement,\r\n  faceLandmarks: DrawFaceLandmarksInput | Array<DrawFaceLandmarksInput>\r\n) {\r\n  const faceLandmarksArray = Array.isArray(faceLandmarks) ? faceLandmarks : [faceLandmarks]\r\n  faceLandmarksArray.forEach(f => {\r\n    const landmarks = f instanceof FaceLandmarks\r\n      ? f\r\n      : (isWithFaceLandmarks(f) ? f.landmarks : undefined)\r\n    if (!landmarks) {\r\n      throw new Error('drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof')\r\n    }\r\n\r\n    new DrawFaceLandmarks(landmarks).draw(canvasArg)\r\n  })\r\n}","import { extractConvParamsFactory, extractSeparableConvParamsFactory, extractWeightsFactory } from '../common';\r\nimport { ExtractWeightsFunction, ParamMapping } from '../common/types';\r\nimport { range } from '../utils';\r\nimport { MainBlockParams, ReductionBlockParams, TinyXceptionParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  const extractConvParams = extractConvParamsFactory(extractWeights, paramMappings)\r\n  const extractSeparableConvParams = extractSeparableConvParamsFactory(extractWeights, paramMappings)\r\n\r\n  function extractReductionBlockParams(channelsIn: number, channelsOut: number, mappedPrefix: string): ReductionBlockParams {\r\n\r\n    const separable_conv0 = extractSeparableConvParams(channelsIn, channelsOut, `${mappedPrefix}/separable_conv0`)\r\n    const separable_conv1 = extractSeparableConvParams(channelsOut, channelsOut, `${mappedPrefix}/separable_conv1`)\r\n    const expansion_conv = extractConvParams(channelsIn, channelsOut, 1, `${mappedPrefix}/expansion_conv`)\r\n\r\n    return { separable_conv0, separable_conv1, expansion_conv }\r\n  }\r\n\r\n  function extractMainBlockParams(channels: number, mappedPrefix: string): MainBlockParams {\r\n\r\n    const separable_conv0 = extractSeparableConvParams(channels, channels, `${mappedPrefix}/separable_conv0`)\r\n    const separable_conv1 = extractSeparableConvParams(channels, channels, `${mappedPrefix}/separable_conv1`)\r\n    const separable_conv2 = extractSeparableConvParams(channels, channels, `${mappedPrefix}/separable_conv2`)\r\n\r\n    return { separable_conv0, separable_conv1, separable_conv2 }\r\n  }\r\n\r\n  return {\r\n    extractConvParams,\r\n    extractSeparableConvParams,\r\n    extractReductionBlockParams,\r\n    extractMainBlockParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(weights: Float32Array, numMainBlocks: number): { params: TinyXceptionParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const {\r\n    extractConvParams,\r\n    extractSeparableConvParams,\r\n    extractReductionBlockParams,\r\n    extractMainBlockParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const entry_flow_conv_in = extractConvParams(3, 32, 3, 'entry_flow/conv_in')\r\n  const entry_flow_reduction_block_0 = extractReductionBlockParams(32, 64, 'entry_flow/reduction_block_0')\r\n  const entry_flow_reduction_block_1 = extractReductionBlockParams(64, 128, 'entry_flow/reduction_block_1')\r\n\r\n  const entry_flow = {\r\n    conv_in: entry_flow_conv_in,\r\n    reduction_block_0: entry_flow_reduction_block_0,\r\n    reduction_block_1: entry_flow_reduction_block_1\r\n  }\r\n\r\n  const middle_flow = {}\r\n  range(numMainBlocks, 0, 1).forEach((idx) => {\r\n    middle_flow[`main_block_${idx}`] = extractMainBlockParams(128, `middle_flow/main_block_${idx}`)\r\n  })\r\n\r\n  const exit_flow_reduction_block = extractReductionBlockParams(128, 256, 'exit_flow/reduction_block')\r\n  const exit_flow_separable_conv = extractSeparableConvParams(256, 512, 'exit_flow/separable_conv')\r\n\r\n  const exit_flow = {\r\n    reduction_block: exit_flow_reduction_block,\r\n    separable_conv: exit_flow_separable_conv\r\n  }\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { entry_flow, middle_flow, exit_flow }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport {\r\n  disposeUnusedWeightTensors,\r\n  extractWeightEntryFactory,\r\n  loadSeparableConvParamsFactory,\r\n  ParamMapping,\r\n} from '../common';\r\nimport { loadConvParamsFactory } from '../common/loadConvParamsFactory';\r\nimport { range } from '../utils';\r\nimport { MainBlockParams, ReductionBlockParams, TinyXceptionParams } from './types';\r\n\r\nfunction loadParamsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  const extractConvParams = loadConvParamsFactory(extractWeightEntry)\r\n  const extractSeparableConvParams = loadSeparableConvParamsFactory(extractWeightEntry)\r\n\r\n  function extractReductionBlockParams(mappedPrefix: string): ReductionBlockParams {\r\n\r\n    const separable_conv0 = extractSeparableConvParams(`${mappedPrefix}/separable_conv0`)\r\n    const separable_conv1 = extractSeparableConvParams(`${mappedPrefix}/separable_conv1`)\r\n    const expansion_conv = extractConvParams(`${mappedPrefix}/expansion_conv`)\r\n\r\n    return { separable_conv0, separable_conv1, expansion_conv }\r\n  }\r\n\r\n  function extractMainBlockParams(mappedPrefix: string): MainBlockParams {\r\n\r\n    const separable_conv0 = extractSeparableConvParams(`${mappedPrefix}/separable_conv0`)\r\n    const separable_conv1 = extractSeparableConvParams(`${mappedPrefix}/separable_conv1`)\r\n    const separable_conv2 = extractSeparableConvParams(`${mappedPrefix}/separable_conv2`)\r\n\r\n    return { separable_conv0, separable_conv1, separable_conv2 }\r\n  }\r\n\r\n  return {\r\n    extractConvParams,\r\n    extractSeparableConvParams,\r\n    extractReductionBlockParams,\r\n    extractMainBlockParams\r\n  }\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap,\r\n  numMainBlocks: number\r\n): { params: TinyXceptionParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvParams,\r\n    extractSeparableConvParams,\r\n    extractReductionBlockParams,\r\n    extractMainBlockParams\r\n  } = loadParamsFactory(weightMap, paramMappings)\r\n\r\n  const entry_flow_conv_in = extractConvParams('entry_flow/conv_in')\r\n  const entry_flow_reduction_block_0 = extractReductionBlockParams('entry_flow/reduction_block_0')\r\n  const entry_flow_reduction_block_1 = extractReductionBlockParams('entry_flow/reduction_block_1')\r\n\r\n  const entry_flow = {\r\n    conv_in: entry_flow_conv_in,\r\n    reduction_block_0: entry_flow_reduction_block_0,\r\n    reduction_block_1: entry_flow_reduction_block_1\r\n  }\r\n\r\n  const middle_flow = {}\r\n  range(numMainBlocks, 0, 1).forEach((idx) => {\r\n    middle_flow[`main_block_${idx}`] = extractMainBlockParams(`middle_flow/main_block_${idx}`)\r\n  })\r\n\r\n  const exit_flow_reduction_block = extractReductionBlockParams('exit_flow/reduction_block')\r\n  const exit_flow_separable_conv = extractSeparableConvParams('exit_flow/separable_conv')\r\n\r\n  const exit_flow = {\r\n    reduction_block: exit_flow_reduction_block,\r\n    separable_conv: exit_flow_separable_conv\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params: { entry_flow, middle_flow, exit_flow }, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, depthwiseSeparableConv } from '../common';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { normalize } from '../ops';\r\nimport { range } from '../utils';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { MainBlockParams, ReductionBlockParams, TinyXceptionParams } from './types';\r\n\r\nfunction conv(x: tf.Tensor4D, params: ConvParams, stride: [number, number]): tf.Tensor4D {\r\n  return tf.add(tf.conv2d(x, params.filters, stride, 'same'), params.bias)\r\n}\r\n\r\nfunction reductionBlock(x: tf.Tensor4D, params: ReductionBlockParams, isActivateInput: boolean = true): tf.Tensor4D {\r\n  let out = isActivateInput ? tf.relu(x) : x\r\n  out = depthwiseSeparableConv(out, params.separable_conv0, [1, 1])\r\n  out = depthwiseSeparableConv(tf.relu(out),  params.separable_conv1, [1, 1])\r\n  out = tf.maxPool(out, [3, 3], [2, 2], 'same')\r\n  out = tf.add(out, conv(x,  params.expansion_conv, [2, 2]))\r\n  return out\r\n}\r\n\r\nfunction mainBlock(x: tf.Tensor4D, params: MainBlockParams): tf.Tensor4D {\r\n  let out = depthwiseSeparableConv(tf.relu(x), params.separable_conv0, [1, 1])\r\n  out = depthwiseSeparableConv(tf.relu(out), params.separable_conv1, [1, 1])\r\n  out = depthwiseSeparableConv(tf.relu(out), params.separable_conv2, [1, 1])\r\n  out = tf.add(out, x)\r\n  return out\r\n}\r\n\r\nexport class TinyXception extends NeuralNetwork<TinyXceptionParams> {\r\n\r\n  private _numMainBlocks: number\r\n\r\n  constructor(numMainBlocks: number) {\r\n    super('TinyXception')\r\n    this._numMainBlocks = numMainBlocks\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor4D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('TinyXception - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(112, true)\r\n      const meanRgb = [122.782, 117.001, 104.298]\r\n      const normalized = normalize(batchTensor, meanRgb).div(tf.scalar(256)) as tf.Tensor4D\r\n\r\n      let out = tf.relu(conv(normalized, params.entry_flow.conv_in, [2, 2]))\r\n      out = reductionBlock(out, params.entry_flow.reduction_block_0, false)\r\n      out = reductionBlock(out, params.entry_flow.reduction_block_1)\r\n\r\n      range(this._numMainBlocks, 0, 1).forEach((idx) => {\r\n        out = mainBlock(out, params.middle_flow[`main_block_${idx}`])\r\n      })\r\n\r\n      out = reductionBlock(out, params.exit_flow.reduction_block)\r\n      out = tf.relu(depthwiseSeparableConv(out, params.exit_flow.separable_conv, [1, 1]))\r\n      return out\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor4D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'tiny_xception_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap, this._numMainBlocks)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights, this._numMainBlocks)\r\n  }\r\n}","import { extractFCParamsFactory, extractWeightsFactory, ParamMapping } from '../common';\r\nimport { NetParams } from './types';\r\n\r\nexport function extractParams(weights: Float32Array): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const extractFCParams = extractFCParamsFactory(extractWeights, paramMappings)\r\n\r\n  const age = extractFCParams(512, 1, 'fc/age')\r\n  const gender = extractFCParams(512, 2, 'fc/gender')\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { fc: { age, gender } }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, extractWeightEntryFactory, FCParams, ParamMapping } from '../common';\r\nimport { NetParams } from './types';\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractFcParams(prefix: string): FCParams {\r\n    const weights = extractWeightEntry<tf.Tensor2D>(`${prefix}/weights`, 2)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n    return { weights, bias }\r\n  }\r\n\r\n  const params = {\r\n    fc: {\r\n      age: extractFcParams('fc/age'),\r\n      gender: extractFcParams('fc/gender')\r\n    }\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FCParams } from '../common';\r\n\r\nexport type AgeAndGenderPrediction = {\r\n  age: number\r\n  gender: Gender\r\n  genderProbability: number\r\n}\r\n\r\nexport enum Gender {\r\n  FEMALE = 'female',\r\n  MALE = 'male'\r\n}\r\n\r\nexport type NetOutput = { age: tf.Tensor1D, gender: tf.Tensor2D }\r\n\r\nexport type NetParams = {\r\n  fc: {\r\n    age: FCParams\r\n    gender: FCParams\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { fullyConnectedLayer } from '../common/fullyConnectedLayer';\r\nimport { seperateWeightMaps } from '../faceProcessor/util';\r\nimport { TinyXception } from '../xception/TinyXception';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { AgeAndGenderPrediction, Gender, NetOutput, NetParams } from './types';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\n\r\nexport class AgeGenderNet extends NeuralNetwork<NetParams> {\r\n\r\n  private _faceFeatureExtractor: TinyXception\r\n\r\n  constructor(faceFeatureExtractor: TinyXception = new TinyXception(2)) {\r\n    super('AgeGenderNet')\r\n    this._faceFeatureExtractor = faceFeatureExtractor\r\n  }\r\n\r\n  public get faceFeatureExtractor(): TinyXception {\r\n    return this._faceFeatureExtractor\r\n  }\r\n\r\n  public runNet(input: NetInput | tf.Tensor4D): NetOutput {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error(`${this._name} - load model before inference`)\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const bottleneckFeatures = input instanceof NetInput\r\n        ? this.faceFeatureExtractor.forwardInput(input)\r\n        : input\r\n\r\n      const pooled = tf.avgPool(bottleneckFeatures, [7, 7], [2, 2], 'valid').as2D(bottleneckFeatures.shape[0], -1)\r\n      const age = fullyConnectedLayer(pooled, params.fc.age).as1D()\r\n      const gender = fullyConnectedLayer(pooled, params.fc.gender)\r\n      return { age, gender }\r\n    })\r\n  }\r\n\r\n  public forwardInput(input: NetInput | tf.Tensor4D): NetOutput {\r\n    return tf.tidy(() => {\r\n      const { age, gender } = this.runNet(input)\r\n      return { age, gender: tf.softmax(gender) }\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<NetOutput> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async predictAgeAndGender(input: TNetInput): Promise<AgeAndGenderPrediction | AgeAndGenderPrediction[]> {\r\n    const netInput = await toNetInput(input)\r\n    const out = await this.forwardInput(netInput)\r\n\r\n    const ages = tf.unstack(out.age)\r\n    const genders = tf.unstack(out.gender)\r\n    const ageAndGenderTensors = ages.map((ageTensor, i) => ({\r\n      ageTensor,\r\n      genderTensor: genders[i]\r\n    }))\r\n\r\n    const predictionsByBatch = await Promise.all(\r\n      ageAndGenderTensors.map(async ({ ageTensor, genderTensor }) => {\r\n        const age = (await ageTensor.data())[0]\r\n        const probMale = (await genderTensor.data())[0]\r\n        const isMale = probMale > 0.5\r\n        const gender = isMale ? Gender.MALE : Gender.FEMALE\r\n        const genderProbability = isMale ? probMale : (1 - probMale)\r\n\r\n        ageTensor.dispose()\r\n        genderTensor.dispose()\r\n        return { age, gender, genderProbability }\r\n      })\r\n    )\r\n    out.age.dispose()\r\n    out.gender.dispose()\r\n\r\n    return netInput.isBatchInput\r\n      ? predictionsByBatch\r\n      : predictionsByBatch[0]\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'age_gender_model'\r\n  }\r\n\r\n  public dispose(throwOnRedispose: boolean = true) {\r\n    this.faceFeatureExtractor.dispose(throwOnRedispose)\r\n    super.dispose(throwOnRedispose)\r\n  }\r\n\r\n  public loadClassifierParams(weights: Float32Array) {\r\n    const { params, paramMappings } = this.extractClassifierParams(weights)\r\n    this._params = params\r\n    this._paramMappings = paramMappings\r\n  }\r\n\r\n  public extractClassifierParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n\r\n    const { featureExtractorMap, classifierMap } = seperateWeightMaps(weightMap)\r\n\r\n    this.faceFeatureExtractor.loadFromWeightMap(featureExtractorMap)\r\n\r\n    return extractParamsFromWeigthMap(classifierMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n\r\n    const classifierWeightSize = (512 * 1 + 1) + (512 * 2 + 2)\r\n\r\n    const featureExtractorWeights = weights.slice(0, weights.length - classifierWeightSize)\r\n    const classifierWeights = weights.slice(weights.length - classifierWeightSize)\r\n\r\n    this.faceFeatureExtractor.extractWeights(featureExtractorWeights)\r\n    return this.extractClassifierParams(classifierWeights)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { IDimensions, Point } from '../classes';\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { FaceFeatureExtractorParams, TinyFaceFeatureExtractorParams } from '../faceFeatureExtractor/types';\r\nimport { FaceProcessor } from '../faceProcessor/FaceProcessor';\r\nimport { isEven } from '../utils';\r\n\r\nexport abstract class FaceLandmark68NetBase<\r\n  TExtractorParams extends FaceFeatureExtractorParams | TinyFaceFeatureExtractorParams\r\n>\r\n  extends FaceProcessor<TExtractorParams> {\r\n\r\n  public postProcess(output: tf.Tensor2D, inputSize: number, originalDimensions: IDimensions[]): tf.Tensor2D {\r\n\r\n    const inputDimensions = originalDimensions.map(({ width, height }) => {\r\n      const scale = inputSize / Math.max(height, width)\r\n      return {\r\n        width: width * scale,\r\n        height: height * scale\r\n      }\r\n    })\r\n\r\n    const batchSize = inputDimensions.length\r\n\r\n    return tf.tidy(() => {\r\n      const createInterleavedTensor = (fillX: number, fillY: number) =>\r\n        tf.stack([\r\n          tf.fill([68], fillX),\r\n          tf.fill([68], fillY)\r\n        ], 1).as2D(1, 136).as1D()\r\n\r\n      const getPadding = (batchIdx: number, cond: (w: number, h: number) => boolean): number => {\r\n        const { width, height } = inputDimensions[batchIdx]\r\n        return cond(width, height) ? Math.abs(width - height) / 2 : 0\r\n      }\r\n      const getPaddingX = (batchIdx: number) => getPadding(batchIdx, (w, h) => w < h)\r\n      const getPaddingY = (batchIdx: number) => getPadding(batchIdx, (w, h) => h < w)\r\n\r\n      const landmarkTensors = output\r\n        .mul(tf.fill([batchSize, 136], inputSize))\r\n        .sub(tf.stack(Array.from(Array(batchSize), (_, batchIdx) =>\r\n          createInterleavedTensor(\r\n            getPaddingX(batchIdx),\r\n            getPaddingY(batchIdx)\r\n          )\r\n        )))\r\n        .div(tf.stack(Array.from(Array(batchSize), (_, batchIdx) =>\r\n          createInterleavedTensor(\r\n            inputDimensions[batchIdx].width,\r\n            inputDimensions[batchIdx].height\r\n          )\r\n        )))\r\n\r\n      return landmarkTensors as tf.Tensor2D\r\n    })\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor2D {\r\n    return tf.tidy(() => {\r\n      const out = this.runNet(input)\r\n      return this.postProcess(\r\n        out,\r\n        input.inputSize as number,\r\n        input.inputDimensions.map(([height, width]) => ({ height, width }))\r\n      )\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor2D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async detectLandmarks(input: TNetInput): Promise<FaceLandmarks68 | FaceLandmarks68[]> {\r\n    const netInput = await toNetInput(input)\r\n    const landmarkTensors = tf.tidy(\r\n      () => tf.unstack(this.forwardInput(netInput))\r\n    )\r\n\r\n    const landmarksForBatch = await Promise.all(landmarkTensors.map(\r\n      async (landmarkTensor, batchIdx) => {\r\n        const landmarksArray = Array.from(await landmarkTensor.data())\r\n        const xCoords = landmarksArray.filter((_, i) => isEven(i))\r\n        const yCoords = landmarksArray.filter((_, i) => !isEven(i))\r\n\r\n        return new FaceLandmarks68(\r\n          Array(68).fill(0).map((_, i) => new Point(xCoords[i], yCoords[i])),\r\n          {\r\n            height: netInput.getInputHeight(batchIdx),\r\n            width : netInput.getInputWidth(batchIdx),\r\n          }\r\n        )\r\n      }\r\n    ))\r\n\r\n    landmarkTensors.forEach(t => t.dispose())\r\n\r\n    return netInput.isBatchInput\r\n      ? landmarksForBatch\r\n      : landmarksForBatch[0]\r\n  }\r\n\r\n  protected getClassifierChannelsOut(): number {\r\n    return 136\r\n  }\r\n}","import { FaceFeatureExtractor } from '../faceFeatureExtractor/FaceFeatureExtractor';\r\nimport { FaceFeatureExtractorParams } from '../faceFeatureExtractor/types';\r\nimport { FaceLandmark68NetBase } from './FaceLandmark68NetBase';\r\n\r\nexport class FaceLandmark68Net extends FaceLandmark68NetBase<FaceFeatureExtractorParams> {\r\n\r\n  constructor(faceFeatureExtractor: FaceFeatureExtractor = new FaceFeatureExtractor()) {\r\n    super('FaceLandmark68Net', faceFeatureExtractor)\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_landmark_68_model'\r\n  }\r\n\r\n  protected getClassifierChannelsIn(): number {\r\n    return 256\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, ParamMapping } from '../common';\r\nimport { loadParamsFactory } from './loadParamsFactory';\r\nimport { TinyFaceFeatureExtractorParams } from './types';\r\n\r\nexport function extractParamsFromWeigthMapTiny(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: TinyFaceFeatureExtractorParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractDenseBlock3Params\r\n  } = loadParamsFactory(weightMap, paramMappings)\r\n\r\n  const params = {\r\n    dense0: extractDenseBlock3Params('dense0', true),\r\n    dense1: extractDenseBlock3Params('dense1'),\r\n    dense2: extractDenseBlock3Params('dense2')\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import { extractWeightsFactory, ParamMapping } from '../common';\r\nimport { extractorsFactory } from './extractorsFactory';\r\nimport { TinyFaceFeatureExtractorParams } from './types';\r\n\r\n\r\n\r\nexport function extractParamsTiny(weights: Float32Array): { params: TinyFaceFeatureExtractorParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const {\r\n    extractDenseBlock3Params\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const dense0 = extractDenseBlock3Params(3, 32, 'dense0', true)\r\n  const dense1 = extractDenseBlock3Params(32, 64, 'dense1')\r\n  const dense2 = extractDenseBlock3Params(64, 128, 'dense2')\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    paramMappings,\r\n    params: { dense0, dense1, dense2 }\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { normalize } from '../ops';\r\nimport { denseBlock3 } from './denseBlock';\r\nimport { extractParamsFromWeigthMapTiny } from './extractParamsFromWeigthMapTiny';\r\nimport { extractParamsTiny } from './extractParamsTiny';\r\nimport { IFaceFeatureExtractor, TinyFaceFeatureExtractorParams } from './types';\r\n\r\nexport class TinyFaceFeatureExtractor extends NeuralNetwork<TinyFaceFeatureExtractorParams> implements IFaceFeatureExtractor<TinyFaceFeatureExtractorParams> {\r\n\r\n  constructor() {\r\n    super('TinyFaceFeatureExtractor')\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor4D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('TinyFaceFeatureExtractor - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(112, true)\r\n      const meanRgb = [122.782, 117.001, 104.298]\r\n      const normalized = normalize(batchTensor, meanRgb).div(tf.scalar(255)) as tf.Tensor4D\r\n\r\n      let out = denseBlock3(normalized, params.dense0, true)\r\n      out = denseBlock3(out, params.dense1)\r\n      out = denseBlock3(out, params.dense2)\r\n      out = tf.avgPool(out, [14, 14], [2, 2], 'valid')\r\n\r\n      return out\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor4D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_feature_extractor_tiny_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMapTiny(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParamsTiny(weights)\r\n  }\r\n}","import { TinyFaceFeatureExtractor } from '../faceFeatureExtractor/TinyFaceFeatureExtractor';\r\nimport { TinyFaceFeatureExtractorParams } from '../faceFeatureExtractor/types';\r\nimport { FaceLandmark68NetBase } from './FaceLandmark68NetBase';\r\n\r\nexport class FaceLandmark68TinyNet extends FaceLandmark68NetBase<TinyFaceFeatureExtractorParams> {\r\n\r\n  constructor(faceFeatureExtractor: TinyFaceFeatureExtractor = new TinyFaceFeatureExtractor()) {\r\n    super('FaceLandmark68TinyNet', faceFeatureExtractor)\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_landmark_68_tiny_model'\r\n  }\r\n\r\n  protected getClassifierChannelsIn(): number {\r\n    return 128\r\n  }\r\n}","import { FaceLandmark68Net } from './FaceLandmark68Net';\r\n\r\nexport * from './FaceLandmark68Net';\r\nexport * from './FaceLandmark68TinyNet';\r\n\r\nexport class FaceLandmarkNet extends FaceLandmark68Net {}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ScaleLayerParams } from './types';\r\n\r\nexport function scale(x: tf.Tensor4D, params: ScaleLayerParams): tf.Tensor4D {\r\n  return tf.add(tf.mul(x, params.weights), params.biases)\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { scale } from './scaleLayer';\r\nimport { ConvLayerParams } from './types';\r\n\r\n\r\nfunction convLayer(\r\n  x: tf.Tensor4D,\r\n  params: ConvLayerParams,\r\n  strides: [number, number],\r\n  withRelu: boolean,\r\n  padding: 'valid' | 'same' = 'same'\r\n): tf.Tensor4D {\r\n  const { filters, bias } = params.conv\r\n\r\n  let out = tf.conv2d(x, filters, strides, padding)\r\n  out = tf.add(out, bias)\r\n  out = scale(out, params.scale)\r\n  return withRelu ? tf.relu(out) : out\r\n}\r\n\r\nexport function conv(x: tf.Tensor4D, params: ConvLayerParams) {\r\n  return convLayer(x, params, [1, 1], true)\r\n}\r\n\r\nexport function convNoRelu(x: tf.Tensor4D, params: ConvLayerParams) {\r\n  return convLayer(x, params, [1, 1], false)\r\n}\r\n\r\nexport function convDown(x: tf.Tensor4D, params: ConvLayerParams) {\r\n  return convLayer(x, params, [2, 2], true, 'valid')\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, extractWeightsFactory, ExtractWeightsFunction, ParamMapping } from '../common';\r\nimport { isFloat } from '../utils';\r\nimport { ConvLayerParams, NetParams, ResidualLayerParams, ScaleLayerParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  function extractFilterValues(numFilterValues: number, numFilters: number, filterSize: number): tf.Tensor4D {\r\n    const weights = extractWeights(numFilterValues)\r\n    const depth = weights.length / (numFilters * filterSize * filterSize)\r\n\r\n    if (isFloat(depth)) {\r\n      throw new Error(`depth has to be an integer: ${depth}, weights.length: ${weights.length}, numFilters: ${numFilters}, filterSize: ${filterSize}`)\r\n    }\r\n\r\n    return tf.tidy(\r\n      () => tf.transpose(\r\n        tf.tensor4d(weights, [numFilters, depth, filterSize, filterSize]),\r\n        [2, 3, 1, 0]\r\n      )\r\n    )\r\n  }\r\n\r\n  function extractConvParams(\r\n    numFilterValues: number,\r\n    numFilters: number,\r\n    filterSize: number,\r\n    mappedPrefix: string\r\n  ): ConvParams {\r\n\r\n    const filters = extractFilterValues(numFilterValues, numFilters, filterSize)\r\n    const bias = tf.tensor1d(extractWeights(numFilters))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/filters` },\r\n      { paramPath: `${mappedPrefix}/bias` }\r\n    )\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractScaleLayerParams(numWeights: number, mappedPrefix: string): ScaleLayerParams {\r\n\r\n    const weights = tf.tensor1d(extractWeights(numWeights))\r\n    const biases = tf.tensor1d(extractWeights(numWeights))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/weights` },\r\n      { paramPath: `${mappedPrefix}/biases` }\r\n    )\r\n\r\n    return {\r\n      weights,\r\n      biases\r\n    }\r\n  }\r\n\r\n  function extractConvLayerParams(\r\n    numFilterValues: number,\r\n    numFilters: number,\r\n    filterSize: number,\r\n    mappedPrefix: string\r\n  ): ConvLayerParams {\r\n\r\n    const conv = extractConvParams(numFilterValues, numFilters, filterSize, `${mappedPrefix}/conv`)\r\n    const scale = extractScaleLayerParams(numFilters, `${mappedPrefix}/scale`)\r\n\r\n    return { conv, scale }\r\n  }\r\n\r\n  function extractResidualLayerParams(\r\n    numFilterValues: number,\r\n    numFilters: number,\r\n    filterSize: number,\r\n    mappedPrefix: string,\r\n    isDown: boolean = false\r\n  ): ResidualLayerParams {\r\n\r\n    const conv1 = extractConvLayerParams((isDown ? 0.5 : 1) * numFilterValues, numFilters, filterSize, `${mappedPrefix}/conv1`)\r\n    const conv2 = extractConvLayerParams(numFilterValues, numFilters, filterSize, `${mappedPrefix}/conv2`)\r\n\r\n    return { conv1, conv2 }\r\n  }\r\n\r\n  return {\r\n    extractConvLayerParams,\r\n    extractResidualLayerParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(weights: Float32Array): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvLayerParams,\r\n    extractResidualLayerParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const conv32_down = extractConvLayerParams(4704, 32, 7, 'conv32_down')\r\n  const conv32_1 = extractResidualLayerParams(9216, 32, 3, 'conv32_1')\r\n  const conv32_2 = extractResidualLayerParams(9216, 32, 3, 'conv32_2')\r\n  const conv32_3 = extractResidualLayerParams(9216, 32, 3, 'conv32_3')\r\n\r\n  const conv64_down = extractResidualLayerParams(36864, 64, 3, 'conv64_down', true)\r\n  const conv64_1 = extractResidualLayerParams(36864, 64, 3, 'conv64_1')\r\n  const conv64_2 = extractResidualLayerParams(36864, 64, 3, 'conv64_2')\r\n  const conv64_3 = extractResidualLayerParams(36864, 64, 3, 'conv64_3')\r\n\r\n  const conv128_down = extractResidualLayerParams(147456, 128, 3, 'conv128_down', true)\r\n  const conv128_1 = extractResidualLayerParams(147456, 128, 3, 'conv128_1')\r\n  const conv128_2 = extractResidualLayerParams(147456, 128, 3, 'conv128_2')\r\n\r\n  const conv256_down = extractResidualLayerParams(589824, 256, 3, 'conv256_down', true)\r\n  const conv256_1 = extractResidualLayerParams(589824, 256, 3, 'conv256_1')\r\n  const conv256_2 = extractResidualLayerParams(589824, 256, 3, 'conv256_2')\r\n  const conv256_down_out = extractResidualLayerParams(589824, 256, 3, 'conv256_down_out')\r\n\r\n  const fc = tf.tidy(\r\n    () => tf.transpose(tf.tensor2d(extractWeights(256 * 128), [128, 256]), [1, 0])\r\n  )\r\n  paramMappings.push({ paramPath: `fc` })\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  const params = {\r\n    conv32_down,\r\n    conv32_1,\r\n    conv32_2,\r\n    conv32_3,\r\n    conv64_down,\r\n    conv64_1,\r\n    conv64_2,\r\n    conv64_3,\r\n    conv128_down,\r\n    conv128_1,\r\n    conv128_2,\r\n    conv256_down,\r\n    conv256_1,\r\n    conv256_2,\r\n    conv256_down_out,\r\n    fc\r\n  }\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { disposeUnusedWeightTensors, extractWeightEntryFactory, ParamMapping } from '../common';\r\nimport { isTensor2D } from '../utils';\r\nimport { ConvLayerParams, NetParams, ResidualLayerParams, ScaleLayerParams } from './types';\r\n\r\nfunction extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractScaleLayerParams(prefix: string): ScaleLayerParams {\r\n\r\n    const weights = extractWeightEntry<tf.Tensor1D>(`${prefix}/scale/weights`, 1)\r\n    const biases = extractWeightEntry<tf.Tensor1D>(`${prefix}/scale/biases`, 1)\r\n\r\n    return { weights, biases }\r\n  }\r\n\r\n  function extractConvLayerParams(prefix: string): ConvLayerParams {\r\n\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/conv/filters`, 4)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/conv/bias`, 1)\r\n    const scale = extractScaleLayerParams(prefix)\r\n\r\n    return { conv: { filters, bias }, scale }\r\n  }\r\n\r\n  function extractResidualLayerParams(prefix: string): ResidualLayerParams {\r\n    return {\r\n      conv1: extractConvLayerParams(`${prefix}/conv1`),\r\n      conv2: extractConvLayerParams(`${prefix}/conv2`)\r\n    }\r\n  }\r\n\r\n  return {\r\n    extractConvLayerParams,\r\n    extractResidualLayerParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvLayerParams,\r\n    extractResidualLayerParams\r\n  } = extractorsFactory(weightMap, paramMappings)\r\n\r\n  const conv32_down = extractConvLayerParams('conv32_down')\r\n  const conv32_1 = extractResidualLayerParams('conv32_1')\r\n  const conv32_2 = extractResidualLayerParams('conv32_2')\r\n  const conv32_3 = extractResidualLayerParams('conv32_3')\r\n\r\n  const conv64_down = extractResidualLayerParams('conv64_down')\r\n  const conv64_1 = extractResidualLayerParams('conv64_1')\r\n  const conv64_2 = extractResidualLayerParams('conv64_2')\r\n  const conv64_3 = extractResidualLayerParams('conv64_3')\r\n\r\n  const conv128_down = extractResidualLayerParams('conv128_down')\r\n  const conv128_1 = extractResidualLayerParams('conv128_1')\r\n  const conv128_2 = extractResidualLayerParams('conv128_2')\r\n\r\n  const conv256_down = extractResidualLayerParams('conv256_down')\r\n  const conv256_1 = extractResidualLayerParams('conv256_1')\r\n  const conv256_2 = extractResidualLayerParams('conv256_2')\r\n  const conv256_down_out = extractResidualLayerParams('conv256_down_out')\r\n\r\n  const fc = weightMap['fc']\r\n  paramMappings.push({ originalPath: 'fc', paramPath: 'fc' })\r\n\r\n  if (!isTensor2D(fc)) {\r\n    throw new Error(`expected weightMap[fc] to be a Tensor2D, instead have ${fc}`)\r\n  }\r\n\r\n  const params = {\r\n    conv32_down,\r\n    conv32_1,\r\n    conv32_2,\r\n    conv32_3,\r\n    conv64_down,\r\n    conv64_1,\r\n    conv64_2,\r\n    conv64_3,\r\n    conv128_down,\r\n    conv128_1,\r\n    conv128_2,\r\n    conv256_down,\r\n    conv256_1,\r\n    conv256_2,\r\n    conv256_down_out,\r\n    fc\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { conv, convDown, convNoRelu } from './convLayer';\r\nimport { ResidualLayerParams } from './types';\r\n\r\nexport function residual(x: tf.Tensor4D, params: ResidualLayerParams): tf.Tensor4D {\r\n  let out = conv(x, params.conv1)\r\n  out = convNoRelu(out, params.conv2)\r\n  out = tf.add(out, x)\r\n  out = tf.relu(out)\r\n  return out\r\n}\r\n\r\nexport function residualDown(x: tf.Tensor4D, params: ResidualLayerParams): tf.Tensor4D {\r\n  let out = convDown(x, params.conv1)\r\n  out = convNoRelu(out, params.conv2)\r\n\r\n  let pooled = tf.avgPool(x, 2, 2, 'valid') as tf.Tensor4D\r\n  const zeros = tf.zeros<tf.Rank.R4>(pooled.shape)\r\n  const isPad = pooled.shape[3] !== out.shape[3]\r\n  const isAdjustShape = pooled.shape[1] !== out.shape[1] || pooled.shape[2] !== out.shape[2]\r\n\r\n  if (isAdjustShape) {\r\n    const padShapeX = [...out.shape] as [number, number, number, number]\r\n    padShapeX[1] = 1\r\n    const zerosW = tf.zeros<tf.Rank.R4>(padShapeX)\r\n    out = tf.concat([out, zerosW], 1)\r\n\r\n    const padShapeY = [...out.shape] as [number, number, number, number]\r\n    padShapeY[2] = 1\r\n    const zerosH = tf.zeros<tf.Rank.R4>(padShapeY)\r\n    out = tf.concat([out, zerosH], 2)\r\n  }\r\n\r\n  pooled = isPad ? tf.concat([pooled, zeros], 3) : pooled\r\n  out = tf.add(pooled, out) as tf.Tensor4D\r\n\r\n  out = tf.relu(out)\r\n  return out\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { normalize } from '../ops';\r\nimport { convDown } from './convLayer';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { residual, residualDown } from './residualLayer';\r\nimport { NetParams } from './types';\r\n\r\n\r\nexport class FaceRecognitionNet extends NeuralNetwork<NetParams> {\r\n\r\n  constructor() {\r\n    super('FaceRecognitionNet')\r\n  }\r\n\r\n  public forwardInput(input: NetInput): tf.Tensor2D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('FaceRecognitionNet - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(150, true).toFloat()\r\n\r\n      const meanRgb = [122.782, 117.001, 104.298]\r\n      const normalized = normalize(batchTensor, meanRgb).div(tf.scalar(256)) as tf.Tensor4D\r\n\r\n      let out = convDown(normalized, params.conv32_down)\r\n      out = tf.maxPool(out, 3, 2, 'valid')\r\n\r\n      out = residual(out, params.conv32_1)\r\n      out = residual(out, params.conv32_2)\r\n      out = residual(out, params.conv32_3)\r\n\r\n      out = residualDown(out, params.conv64_down)\r\n      out = residual(out, params.conv64_1)\r\n      out = residual(out, params.conv64_2)\r\n      out = residual(out, params.conv64_3)\r\n\r\n      out = residualDown(out, params.conv128_down)\r\n      out = residual(out, params.conv128_1)\r\n      out = residual(out, params.conv128_2)\r\n\r\n      out = residualDown(out, params.conv256_down)\r\n      out = residual(out, params.conv256_1)\r\n      out = residual(out, params.conv256_2)\r\n      out = residualDown(out, params.conv256_down_out)\r\n\r\n      const globalAvg = out.mean([1, 2]) as tf.Tensor2D\r\n      const fullyConnected = tf.matMul(globalAvg, params.fc)\r\n\r\n      return fullyConnected\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput): Promise<tf.Tensor2D> {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async computeFaceDescriptor(input: TNetInput): Promise<Float32Array|Float32Array[]> {\r\n    const netInput = await toNetInput(input)\r\n\r\n    const faceDescriptorTensors = tf.tidy(\r\n      () => tf.unstack(this.forwardInput(netInput))\r\n    )\r\n\r\n    const faceDescriptorsForBatch = await Promise.all(faceDescriptorTensors.map(\r\n      t => t.data()\r\n    )) as Float32Array[]\r\n\r\n    faceDescriptorTensors.forEach(t => t.dispose())\r\n\r\n    return netInput.isBatchInput\r\n      ? faceDescriptorsForBatch\r\n      : faceDescriptorsForBatch[0]\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'face_recognition_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n}","import { FaceRecognitionNet } from './FaceRecognitionNet';\r\n\r\nexport * from './FaceRecognitionNet';\r\n\r\nexport function createFaceRecognitionNet(weights: Float32Array) {\r\n  const net = new FaceRecognitionNet()\r\n  net.extractWeights(weights)\r\n  return net\r\n}","export type WithFaceDescriptor<TSource> = TSource & {\r\n  descriptor: Float32Array\r\n}\r\n\r\nexport function extendWithFaceDescriptor<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  descriptor: Float32Array\r\n): WithFaceDescriptor<TSource> {\r\n\r\n  const extension = { descriptor }\r\n  return Object.assign({}, sourceObj, extension)\r\n}\r\n\r\n","export type WithAge<TSource> = TSource & {\r\n  age: number\r\n}\r\n\r\nexport function isWithAge(obj: any): obj is WithAge<{}> {\r\n  return typeof obj['age'] === 'number'\r\n}\r\n\r\nexport function extendWithAge<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  age: number\r\n): WithAge<TSource> {\r\n\r\n  const extension = { age }\r\n  return Object.assign({}, sourceObj, extension)\r\n}","import { Gender } from '../ageGenderNet/types';\r\nimport { isValidProbablitiy } from '../utils';\r\n\r\nexport type WithGender<TSource> = TSource & {\r\n  gender: Gender\r\n  genderProbability: number\r\n}\r\n\r\nexport function isWithGender(obj: any): obj is WithGender<{}> {\r\n  return (obj['gender'] === Gender.MALE || obj['gender'] === Gender.FEMALE)\r\n    && isValidProbablitiy(obj['genderProbability'])\r\n}\r\n\r\nexport function extendWithGender<\r\n  TSource\r\n> (\r\n  sourceObj: TSource,\r\n  gender: Gender,\r\n  genderProbability: number\r\n): WithGender<TSource> {\r\n\r\n  const extension = { gender, genderProbability }\r\n  return Object.assign({}, sourceObj, extension)\r\n}","export interface IMtcnnOptions {\r\n  minFaceSize?: number\r\n  scaleFactor?: number\r\n  maxNumScales?: number\r\n  scoreThresholds?: number[]\r\n  scaleSteps?: number[]\r\n}\r\n\r\nexport class MtcnnOptions {\r\n  protected _name: string = 'MtcnnOptions'\r\n\r\n  private _minFaceSize: number\r\n  private _scaleFactor: number\r\n  private _maxNumScales: number\r\n  private _scoreThresholds: number[]\r\n  private _scaleSteps: number[] | undefined\r\n\r\n  constructor({ minFaceSize, scaleFactor, maxNumScales, scoreThresholds, scaleSteps }: IMtcnnOptions = {}) {\r\n    this._minFaceSize = minFaceSize || 20\r\n    this._scaleFactor = scaleFactor || 0.709\r\n    this._maxNumScales = maxNumScales || 10\r\n    this._scoreThresholds = scoreThresholds || [0.6, 0.7, 0.7]\r\n    this._scaleSteps = scaleSteps\r\n\r\n    if (typeof this._minFaceSize !== 'number' || this._minFaceSize < 0) {\r\n      throw new Error(`${this._name} - expected minFaceSize to be a number > 0`)\r\n    }\r\n\r\n    if (typeof this._scaleFactor !== 'number' || this._scaleFactor <= 0 || this._scaleFactor >= 1) {\r\n      throw new Error(`${this._name} - expected scaleFactor to be a number between 0 and 1`)\r\n    }\r\n\r\n    if (typeof this._maxNumScales !== 'number' || this._maxNumScales < 0) {\r\n      throw new Error(`${this._name} - expected maxNumScales to be a number > 0`)\r\n    }\r\n\r\n    if (\r\n      !Array.isArray(this._scoreThresholds)\r\n        || this._scoreThresholds.length !== 3\r\n        || this._scoreThresholds.some(th => typeof th !== 'number')\r\n    ) {\r\n      throw new Error(`${this._name} - expected scoreThresholds to be an array of numbers of length 3`)\r\n    }\r\n\r\n    if (\r\n      this._scaleSteps\r\n        && (!Array.isArray(this._scaleSteps) || this._scaleSteps.some(th => typeof th !== 'number'))\r\n    ) {\r\n      throw new Error(`${this._name} - expected scaleSteps to be an array of numbers`)\r\n    }\r\n  }\r\n\r\n  get minFaceSize(): number { return this._minFaceSize }\r\n  get scaleFactor(): number { return this._scaleFactor }\r\n  get maxNumScales(): number { return this._maxNumScales }\r\n  get scoreThresholds(): number[] { return this._scoreThresholds }\r\n  get scaleSteps(): number[] | undefined { return this._scaleSteps }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ExtractWeightsFunction, ParamMapping, ConvParams, extractWeightsFactory } from '../common';\r\nimport { MobileNetV1, NetParams, PointwiseConvParams, PredictionLayerParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  function extractDepthwiseConvParams(numChannels: number, mappedPrefix: string): MobileNetV1.DepthwiseConvParams {\r\n\r\n    const filters = tf.tensor4d(extractWeights(3 * 3 * numChannels), [3, 3, numChannels, 1])\r\n    const batch_norm_scale = tf.tensor1d(extractWeights(numChannels))\r\n    const batch_norm_offset = tf.tensor1d(extractWeights(numChannels))\r\n    const batch_norm_mean = tf.tensor1d(extractWeights(numChannels))\r\n    const batch_norm_variance = tf.tensor1d(extractWeights(numChannels))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/filters` },\r\n      { paramPath: `${mappedPrefix}/batch_norm_scale` },\r\n      { paramPath: `${mappedPrefix}/batch_norm_offset` },\r\n      { paramPath: `${mappedPrefix}/batch_norm_mean` },\r\n      { paramPath: `${mappedPrefix}/batch_norm_variance` }\r\n    )\r\n\r\n    return {\r\n      filters,\r\n      batch_norm_scale,\r\n      batch_norm_offset,\r\n      batch_norm_mean,\r\n      batch_norm_variance\r\n    }\r\n  }\r\n\r\n  function extractConvParams(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    filterSize: number,\r\n    mappedPrefix: string,\r\n    isPointwiseConv?: boolean\r\n  ): ConvParams {\r\n\r\n    const filters = tf.tensor4d(\r\n      extractWeights(channelsIn * channelsOut * filterSize * filterSize),\r\n      [filterSize, filterSize, channelsIn, channelsOut]\r\n    )\r\n    const bias = tf.tensor1d(extractWeights(channelsOut))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/filters` },\r\n      { paramPath: `${mappedPrefix}/${isPointwiseConv ? 'batch_norm_offset' : 'bias'}` }\r\n    )\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractPointwiseConvParams(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    filterSize: number,\r\n    mappedPrefix: string\r\n  ): PointwiseConvParams {\r\n\r\n    const {\r\n      filters,\r\n      bias\r\n    } = extractConvParams(channelsIn, channelsOut, filterSize, mappedPrefix, true)\r\n\r\n    return {\r\n      filters,\r\n      batch_norm_offset: bias\r\n    }\r\n  }\r\n\r\n  function extractConvPairParams(\r\n    channelsIn: number,\r\n    channelsOut: number,\r\n    mappedPrefix: string\r\n  ): MobileNetV1.ConvPairParams {\r\n\r\n    const depthwise_conv = extractDepthwiseConvParams(channelsIn, `${mappedPrefix}/depthwise_conv`)\r\n    const pointwise_conv = extractPointwiseConvParams(channelsIn, channelsOut, 1, `${mappedPrefix}/pointwise_conv`)\r\n\r\n    return { depthwise_conv, pointwise_conv }\r\n  }\r\n\r\n  function extractMobilenetV1Params(): MobileNetV1.Params {\r\n\r\n    const conv_0 = extractPointwiseConvParams(3, 32, 3, 'mobilenetv1/conv_0')\r\n\r\n    const conv_1 = extractConvPairParams(32, 64, 'mobilenetv1/conv_1')\r\n    const conv_2 = extractConvPairParams(64, 128, 'mobilenetv1/conv_2')\r\n    const conv_3 = extractConvPairParams(128, 128, 'mobilenetv1/conv_3')\r\n    const conv_4 = extractConvPairParams(128, 256, 'mobilenetv1/conv_4')\r\n    const conv_5 = extractConvPairParams(256, 256, 'mobilenetv1/conv_5')\r\n    const conv_6 = extractConvPairParams(256, 512, 'mobilenetv1/conv_6')\r\n    const conv_7 = extractConvPairParams(512, 512, 'mobilenetv1/conv_7')\r\n    const conv_8 = extractConvPairParams(512, 512, 'mobilenetv1/conv_8')\r\n    const conv_9 = extractConvPairParams(512, 512, 'mobilenetv1/conv_9')\r\n    const conv_10 = extractConvPairParams(512, 512, 'mobilenetv1/conv_10')\r\n    const conv_11 = extractConvPairParams(512, 512, 'mobilenetv1/conv_11')\r\n    const conv_12 = extractConvPairParams(512, 1024, 'mobilenetv1/conv_12')\r\n    const conv_13 = extractConvPairParams(1024, 1024, 'mobilenetv1/conv_13')\r\n\r\n    return {\r\n      conv_0,\r\n      conv_1,\r\n      conv_2,\r\n      conv_3,\r\n      conv_4,\r\n      conv_5,\r\n      conv_6,\r\n      conv_7,\r\n      conv_8,\r\n      conv_9,\r\n      conv_10,\r\n      conv_11,\r\n      conv_12,\r\n      conv_13\r\n    }\r\n  }\r\n\r\n  function extractPredictionLayerParams(): PredictionLayerParams {\r\n    const conv_0 = extractPointwiseConvParams(1024, 256, 1, 'prediction_layer/conv_0')\r\n    const conv_1 = extractPointwiseConvParams(256, 512, 3, 'prediction_layer/conv_1')\r\n    const conv_2 = extractPointwiseConvParams(512, 128, 1, 'prediction_layer/conv_2')\r\n    const conv_3 = extractPointwiseConvParams(128, 256, 3, 'prediction_layer/conv_3')\r\n    const conv_4 = extractPointwiseConvParams(256, 128, 1, 'prediction_layer/conv_4')\r\n    const conv_5 = extractPointwiseConvParams(128, 256, 3, 'prediction_layer/conv_5')\r\n    const conv_6 = extractPointwiseConvParams(256, 64, 1, 'prediction_layer/conv_6')\r\n    const conv_7 = extractPointwiseConvParams(64, 128, 3, 'prediction_layer/conv_7')\r\n\r\n    const box_encoding_0_predictor = extractConvParams(512, 12, 1, 'prediction_layer/box_predictor_0/box_encoding_predictor')\r\n    const class_predictor_0 = extractConvParams(512, 9, 1, 'prediction_layer/box_predictor_0/class_predictor')\r\n    const box_encoding_1_predictor = extractConvParams(1024, 24, 1, 'prediction_layer/box_predictor_1/box_encoding_predictor')\r\n    const class_predictor_1 = extractConvParams(1024, 18, 1, 'prediction_layer/box_predictor_1/class_predictor')\r\n    const box_encoding_2_predictor = extractConvParams(512, 24, 1, 'prediction_layer/box_predictor_2/box_encoding_predictor')\r\n    const class_predictor_2 = extractConvParams(512, 18, 1, 'prediction_layer/box_predictor_2/class_predictor')\r\n    const box_encoding_3_predictor = extractConvParams(256, 24, 1, 'prediction_layer/box_predictor_3/box_encoding_predictor')\r\n    const class_predictor_3 = extractConvParams(256, 18, 1, 'prediction_layer/box_predictor_3/class_predictor')\r\n    const box_encoding_4_predictor = extractConvParams(256, 24, 1, 'prediction_layer/box_predictor_4/box_encoding_predictor')\r\n    const class_predictor_4 = extractConvParams(256, 18, 1, 'prediction_layer/box_predictor_4/class_predictor')\r\n    const box_encoding_5_predictor = extractConvParams(128, 24, 1, 'prediction_layer/box_predictor_5/box_encoding_predictor')\r\n    const class_predictor_5 = extractConvParams(128, 18, 1, 'prediction_layer/box_predictor_5/class_predictor')\r\n\r\n    const box_predictor_0 = {\r\n      box_encoding_predictor: box_encoding_0_predictor,\r\n      class_predictor: class_predictor_0\r\n    }\r\n    const box_predictor_1 = {\r\n      box_encoding_predictor: box_encoding_1_predictor,\r\n      class_predictor: class_predictor_1\r\n    }\r\n    const box_predictor_2 = {\r\n      box_encoding_predictor: box_encoding_2_predictor,\r\n      class_predictor: class_predictor_2\r\n    }\r\n    const box_predictor_3 = {\r\n      box_encoding_predictor: box_encoding_3_predictor,\r\n      class_predictor: class_predictor_3\r\n    }\r\n    const box_predictor_4 = {\r\n      box_encoding_predictor: box_encoding_4_predictor,\r\n      class_predictor: class_predictor_4\r\n    }\r\n    const box_predictor_5 = {\r\n      box_encoding_predictor: box_encoding_5_predictor,\r\n      class_predictor: class_predictor_5\r\n    }\r\n\r\n    return {\r\n      conv_0,\r\n      conv_1,\r\n      conv_2,\r\n      conv_3,\r\n      conv_4,\r\n      conv_5,\r\n      conv_6,\r\n      conv_7,\r\n      box_predictor_0,\r\n      box_predictor_1,\r\n      box_predictor_2,\r\n      box_predictor_3,\r\n      box_predictor_4,\r\n      box_predictor_5\r\n    }\r\n  }\r\n\r\n  return {\r\n    extractMobilenetV1Params,\r\n    extractPredictionLayerParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(weights: Float32Array): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const {\r\n    extractMobilenetV1Params,\r\n    extractPredictionLayerParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const mobilenetv1 = extractMobilenetV1Params()\r\n  const prediction_layer = extractPredictionLayerParams()\r\n  const extra_dim = tf.tensor3d(\r\n    extractWeights(5118 * 4),\r\n    [1, 5118, 4]\r\n  )\r\n  const output_layer = {\r\n    extra_dim\r\n  }\r\n\r\n  paramMappings.push({ paramPath: 'output_layer/extra_dim' })\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return {\r\n    params: {\r\n      mobilenetv1,\r\n      prediction_layer,\r\n      output_layer\r\n    },\r\n    paramMappings\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, disposeUnusedWeightTensors, extractWeightEntryFactory, ParamMapping } from '../common';\r\nimport { isTensor3D } from '../utils';\r\nimport { BoxPredictionParams, MobileNetV1, NetParams, PointwiseConvParams, PredictionLayerParams } from './types';\r\n\r\nfunction extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractPointwiseConvParams(prefix: string, idx: number, mappedPrefix: string): PointwiseConvParams {\r\n\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/Conv2d_${idx}_pointwise/weights`, 4, `${mappedPrefix}/filters`)\r\n    const batch_norm_offset = extractWeightEntry<tf.Tensor1D>(`${prefix}/Conv2d_${idx}_pointwise/convolution_bn_offset`, 1, `${mappedPrefix}/batch_norm_offset`)\r\n\r\n    return { filters, batch_norm_offset }\r\n  }\r\n\r\n  function extractConvPairParams(idx: number): MobileNetV1.ConvPairParams {\r\n\r\n    const mappedPrefix = `mobilenetv1/conv_${idx}`\r\n    const prefixDepthwiseConv = `MobilenetV1/Conv2d_${idx}_depthwise`\r\n    const mappedPrefixDepthwiseConv = `${mappedPrefix}/depthwise_conv`\r\n    const mappedPrefixPointwiseConv = `${mappedPrefix}/pointwise_conv`\r\n\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefixDepthwiseConv}/depthwise_weights`, 4, `${mappedPrefixDepthwiseConv}/filters`)\r\n    const batch_norm_scale = extractWeightEntry<tf.Tensor1D>(`${prefixDepthwiseConv}/BatchNorm/gamma`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_scale`)\r\n    const batch_norm_offset = extractWeightEntry<tf.Tensor1D>(`${prefixDepthwiseConv}/BatchNorm/beta`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_offset`)\r\n    const batch_norm_mean = extractWeightEntry<tf.Tensor1D>(`${prefixDepthwiseConv}/BatchNorm/moving_mean`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_mean`)\r\n    const batch_norm_variance = extractWeightEntry<tf.Tensor1D>(`${prefixDepthwiseConv}/BatchNorm/moving_variance`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_variance`)\r\n\r\n    return {\r\n      depthwise_conv: {\r\n        filters,\r\n        batch_norm_scale,\r\n        batch_norm_offset,\r\n        batch_norm_mean,\r\n        batch_norm_variance\r\n      },\r\n      pointwise_conv: extractPointwiseConvParams('MobilenetV1', idx, mappedPrefixPointwiseConv)\r\n    }\r\n  }\r\n\r\n  function extractMobilenetV1Params(): MobileNetV1.Params {\r\n    return {\r\n      conv_0: extractPointwiseConvParams('MobilenetV1', 0, 'mobilenetv1/conv_0'),\r\n      conv_1: extractConvPairParams(1),\r\n      conv_2: extractConvPairParams(2),\r\n      conv_3: extractConvPairParams(3),\r\n      conv_4: extractConvPairParams(4),\r\n      conv_5: extractConvPairParams(5),\r\n      conv_6: extractConvPairParams(6),\r\n      conv_7: extractConvPairParams(7),\r\n      conv_8: extractConvPairParams(8),\r\n      conv_9: extractConvPairParams(9),\r\n      conv_10: extractConvPairParams(10),\r\n      conv_11: extractConvPairParams(11),\r\n      conv_12: extractConvPairParams(12),\r\n      conv_13: extractConvPairParams(13)\r\n    }\r\n  }\r\n\r\n  function extractConvParams(prefix: string, mappedPrefix: string): ConvParams {\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/weights`, 4, `${mappedPrefix}/filters`)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/biases`, 1, `${mappedPrefix}/bias`)\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractBoxPredictorParams(idx: number): BoxPredictionParams {\r\n\r\n    const box_encoding_predictor = extractConvParams(\r\n      `Prediction/BoxPredictor_${idx}/BoxEncodingPredictor`,\r\n      `prediction_layer/box_predictor_${idx}/box_encoding_predictor`\r\n    )\r\n    const class_predictor = extractConvParams(\r\n      `Prediction/BoxPredictor_${idx}/ClassPredictor`,\r\n      `prediction_layer/box_predictor_${idx}/class_predictor`\r\n    )\r\n\r\n    return { box_encoding_predictor, class_predictor }\r\n  }\r\n\r\n  function extractPredictionLayerParams(): PredictionLayerParams {\r\n    return {\r\n      conv_0: extractPointwiseConvParams('Prediction', 0, 'prediction_layer/conv_0'),\r\n      conv_1: extractPointwiseConvParams('Prediction', 1, 'prediction_layer/conv_1'),\r\n      conv_2: extractPointwiseConvParams('Prediction', 2, 'prediction_layer/conv_2'),\r\n      conv_3: extractPointwiseConvParams('Prediction', 3, 'prediction_layer/conv_3'),\r\n      conv_4: extractPointwiseConvParams('Prediction', 4, 'prediction_layer/conv_4'),\r\n      conv_5: extractPointwiseConvParams('Prediction', 5, 'prediction_layer/conv_5'),\r\n      conv_6: extractPointwiseConvParams('Prediction', 6, 'prediction_layer/conv_6'),\r\n      conv_7: extractPointwiseConvParams('Prediction', 7, 'prediction_layer/conv_7'),\r\n      box_predictor_0: extractBoxPredictorParams(0),\r\n      box_predictor_1: extractBoxPredictorParams(1),\r\n      box_predictor_2: extractBoxPredictorParams(2),\r\n      box_predictor_3: extractBoxPredictorParams(3),\r\n      box_predictor_4: extractBoxPredictorParams(4),\r\n      box_predictor_5: extractBoxPredictorParams(5)\r\n    }\r\n  }\r\n\r\n  return {\r\n    extractMobilenetV1Params,\r\n    extractPredictionLayerParams\r\n  }\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractMobilenetV1Params,\r\n    extractPredictionLayerParams\r\n  } = extractorsFactory(weightMap, paramMappings)\r\n\r\n  const extra_dim = weightMap['Output/extra_dim']\r\n  paramMappings.push({ originalPath: 'Output/extra_dim', paramPath: 'output_layer/extra_dim' })\r\n\r\n  if (!isTensor3D(extra_dim)) {\r\n    throw new Error(`expected weightMap['Output/extra_dim'] to be a Tensor3D, instead have ${extra_dim}`)\r\n  }\r\n\r\n  const params = {\r\n    mobilenetv1: extractMobilenetV1Params(),\r\n    prediction_layer: extractPredictionLayerParams(),\r\n    output_layer: {\r\n      extra_dim\r\n    }\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { PointwiseConvParams } from './types';\r\n\r\nexport function pointwiseConvLayer(\r\n  x: tf.Tensor4D,\r\n  params: PointwiseConvParams,\r\n  strides: [number, number]\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    let out = tf.conv2d(x, params.filters, strides, 'same')\r\n    out = tf.add(out, params.batch_norm_offset)\r\n    return tf.clipByValue(out, 0, 6)\r\n\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { pointwiseConvLayer } from './pointwiseConvLayer';\r\nimport { MobileNetV1 } from './types';\r\n\r\nconst epsilon = 0.0010000000474974513\r\n\r\nfunction depthwiseConvLayer(\r\n  x: tf.Tensor4D,\r\n  params: MobileNetV1.DepthwiseConvParams,\r\n  strides: [number, number]\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    let out = tf.depthwiseConv2d(x, params.filters, strides, 'same')\r\n    out = tf.batchNorm<tf.Rank.R4>(\r\n      out,\r\n      params.batch_norm_mean,\r\n      params.batch_norm_variance,\r\n      params.batch_norm_offset,\r\n      params.batch_norm_scale,\r\n      epsilon\r\n    )\r\n    return tf.clipByValue(out, 0, 6)\r\n\r\n  })\r\n}\r\n\r\nfunction getStridesForLayerIdx(layerIdx: number): [number, number] {\r\n  return [2, 4, 6, 12].some(idx => idx === layerIdx) ? [2, 2] : [1, 1]\r\n}\r\n\r\nexport function mobileNetV1(x: tf.Tensor4D, params: MobileNetV1.Params) {\r\n  return tf.tidy(() => {\r\n\r\n    let conv11 = null\r\n    let out = pointwiseConvLayer(x, params.conv_0, [2, 2])\r\n\r\n    const convPairParams = [\r\n      params.conv_1,\r\n      params.conv_2,\r\n      params.conv_3,\r\n      params.conv_4,\r\n      params.conv_5,\r\n      params.conv_6,\r\n      params.conv_7,\r\n      params.conv_8,\r\n      params.conv_9,\r\n      params.conv_10,\r\n      params.conv_11,\r\n      params.conv_12,\r\n      params.conv_13\r\n    ]\r\n\r\n    convPairParams.forEach((param, i) => {\r\n      const layerIdx = i + 1\r\n      const depthwiseConvStrides = getStridesForLayerIdx(layerIdx)\r\n      out = depthwiseConvLayer(out, param.depthwise_conv, depthwiseConvStrides)\r\n      out = pointwiseConvLayer(out, param.pointwise_conv, [1, 1])\r\n      if (layerIdx === 11) {\r\n        conv11 = out\r\n      }\r\n    })\r\n\r\n    if (conv11 === null) {\r\n      throw new Error('mobileNetV1 - output of conv layer 11 is null')\r\n    }\r\n\r\n    return {\r\n      out,\r\n      conv11: conv11 as any\r\n    }\r\n\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core'\r\n\r\nexport function nonMaxSuppression(\r\n  boxes: tf.Tensor2D,\r\n  scores: number[],\r\n  maxOutputSize: number,\r\n  iouThreshold: number,\r\n  scoreThreshold: number\r\n): number[] {\r\n\r\n  const numBoxes = boxes.shape[0]\r\n  const outputSize = Math.min(\r\n    maxOutputSize,\r\n    numBoxes\r\n  )\r\n\r\n  const candidates = scores\r\n    .map((score, boxIndex) => ({ score, boxIndex }))\r\n    .filter(c => c.score > scoreThreshold)\r\n    .sort((c1, c2) => c2.score - c1.score)\r\n\r\n  const suppressFunc = (x: number) => x <= iouThreshold ? 1 : 0\r\n\r\n  const selected: number[] = []\r\n\r\n  candidates.forEach(c => {\r\n    if (selected.length >= outputSize) {\r\n      return\r\n    }\r\n    const originalScore = c.score\r\n\r\n    for (let j = selected.length - 1; j >= 0; --j) {\r\n      const iou = IOU(boxes, c.boxIndex, selected[j])\r\n      if (iou === 0.0) {\r\n        continue\r\n      }\r\n      c.score *= suppressFunc(iou)\r\n      if (c.score <= scoreThreshold) {\r\n        break\r\n      }\r\n    }\r\n\r\n    if (originalScore === c.score) {\r\n      selected.push(c.boxIndex)\r\n    }\r\n  })\r\n\r\n  return selected\r\n}\r\n\r\nfunction IOU(boxes: tf.Tensor2D, i: number, j: number) {\r\n  const boxesData = boxes.arraySync()\r\n  const yminI = Math.min(boxesData[i][0], boxesData[i][2])\r\n  const xminI = Math.min(boxesData[i][1], boxesData[i][3])\r\n  const ymaxI = Math.max(boxesData[i][0], boxesData[i][2])\r\n  const xmaxI = Math.max(boxesData[i][1], boxesData[i][3])\r\n  const yminJ = Math.min(boxesData[j][0], boxesData[j][2])\r\n  const xminJ = Math.min(boxesData[j][1], boxesData[j][3])\r\n  const ymaxJ = Math.max(boxesData[j][0], boxesData[j][2])\r\n  const xmaxJ = Math.max(boxesData[j][1], boxesData[j][3])\r\n  const areaI = (ymaxI - yminI) * (xmaxI - xminI)\r\n  const areaJ = (ymaxJ - yminJ) * (xmaxJ - xminJ)\r\n  if (areaI <= 0 || areaJ <= 0) {\r\n    return 0.0\r\n  }\r\n  const intersectionYmin = Math.max(yminI, yminJ)\r\n  const intersectionXmin = Math.max(xminI, xminJ)\r\n  const intersectionYmax = Math.min(ymaxI, ymaxJ)\r\n  const intersectionXmax = Math.min(xmaxI, xmaxJ)\r\n  const intersectionArea =\r\n      Math.max(intersectionYmax - intersectionYmin, 0.0) *\r\n      Math.max(intersectionXmax - intersectionXmin, 0.0)\r\n  return intersectionArea / (areaI + areaJ - intersectionArea)\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { OutputLayerParams } from './types';\r\n\r\n\r\nfunction getCenterCoordinatesAndSizesLayer(x: tf.Tensor2D) {\r\n  const vec = tf.unstack(tf.transpose(x, [1, 0]))\r\n\r\n  const sizes = [\r\n    tf.sub(vec[2], vec[0]),\r\n    tf.sub(vec[3], vec[1])\r\n  ]\r\n\r\n  const centers = [\r\n    tf.add(vec[0], tf.div(sizes[0], tf.scalar(2))),\r\n    tf.add(vec[1], tf.div(sizes[1], tf.scalar(2)))\r\n  ]\r\n\r\n  return {\r\n    sizes,\r\n    centers\r\n  }\r\n}\r\n\r\nfunction decodeBoxesLayer(x0: tf.Tensor2D, x1: tf.Tensor2D) {\r\n  const {\r\n    sizes,\r\n    centers\r\n  } = getCenterCoordinatesAndSizesLayer(x0)\r\n\r\n  const vec = tf.unstack(tf.transpose(x1, [1, 0]))\r\n\r\n  const div0_out = tf.div(tf.mul(tf.exp(tf.div(vec[2], tf.scalar(5))), sizes[0]), tf.scalar(2))\r\n  const add0_out = tf.add(tf.mul(tf.div(vec[0], tf.scalar(10)), sizes[0]), centers[0])\r\n\r\n  const div1_out = tf.div(tf.mul(tf.exp(tf.div(vec[3], tf.scalar(5))), sizes[1]), tf.scalar(2))\r\n  const add1_out = tf.add(tf.mul(tf.div(vec[1], tf.scalar(10)), sizes[1]), centers[1])\r\n\r\n  return tf.transpose(\r\n    tf.stack([\r\n      tf.sub(add0_out, div0_out),\r\n      tf.sub(add1_out, div1_out),\r\n      tf.add(add0_out, div0_out),\r\n      tf.add(add1_out, div1_out)\r\n    ]),\r\n    [1, 0]\r\n  )\r\n}\r\n\r\nexport function outputLayer(\r\n  boxPredictions: tf.Tensor4D,\r\n  classPredictions: tf.Tensor4D,\r\n  params: OutputLayerParams\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    const batchSize = boxPredictions.shape[0]\r\n\r\n    let boxes = decodeBoxesLayer(\r\n      tf.reshape(tf.tile(params.extra_dim, [batchSize, 1, 1]), [-1, 4]) as tf.Tensor2D,\r\n      tf.reshape(boxPredictions, [-1, 4]) as tf.Tensor2D\r\n    )\r\n    boxes = tf.reshape(\r\n      boxes,\r\n      [batchSize, (boxes.shape[0] / batchSize), 4]\r\n    )\r\n\r\n    const scoresAndClasses = tf.sigmoid(tf.slice(classPredictions, [0, 0, 1], [-1, -1, -1]))\r\n    let scores = tf.slice(scoresAndClasses, [0, 0, 0], [-1, -1, 1]) as tf.Tensor\r\n\r\n    scores = tf.reshape(\r\n      scores,\r\n      [batchSize, scores.shape[1] as number]\r\n    )\r\n\r\n    const boxesByBatch = tf.unstack(boxes) as tf.Tensor2D[]\r\n    const scoresByBatch = tf.unstack(scores) as tf.Tensor1D[]\r\n\r\n    return {\r\n      boxes: boxesByBatch,\r\n      scores: scoresByBatch\r\n    }\r\n\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { convLayer } from '../common';\r\nimport { BoxPredictionParams } from './types';\r\n\r\n\r\nexport function boxPredictionLayer(\r\n  x: tf.Tensor4D,\r\n  params: BoxPredictionParams\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    const batchSize = x.shape[0]\r\n\r\n    const boxPredictionEncoding = tf.reshape(\r\n      convLayer(x, params.box_encoding_predictor),\r\n      [batchSize, -1, 1, 4]\r\n    )\r\n    const classPrediction = tf.reshape(\r\n      convLayer(x, params.class_predictor),\r\n      [batchSize, -1, 3]\r\n    )\r\n\r\n    return {\r\n      boxPredictionEncoding,\r\n      classPrediction\r\n    }\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { boxPredictionLayer } from './boxPredictionLayer';\r\nimport { pointwiseConvLayer } from './pointwiseConvLayer';\r\nimport { PredictionLayerParams } from './types';\r\n\r\nexport function predictionLayer(\r\n  x: tf.Tensor4D,\r\n  conv11: tf.Tensor4D,\r\n  params: PredictionLayerParams\r\n) {\r\n  return tf.tidy(() => {\r\n\r\n    const conv0 = pointwiseConvLayer(x, params.conv_0, [1, 1])\r\n    const conv1 = pointwiseConvLayer(conv0, params.conv_1, [2, 2])\r\n    const conv2 = pointwiseConvLayer(conv1, params.conv_2, [1, 1])\r\n    const conv3 = pointwiseConvLayer(conv2, params.conv_3, [2, 2])\r\n    const conv4 = pointwiseConvLayer(conv3, params.conv_4, [1, 1])\r\n    const conv5 = pointwiseConvLayer(conv4, params.conv_5, [2, 2])\r\n    const conv6 = pointwiseConvLayer(conv5, params.conv_6, [1, 1])\r\n    const conv7 = pointwiseConvLayer(conv6, params.conv_7, [2, 2])\r\n\r\n    const boxPrediction0 = boxPredictionLayer(conv11, params.box_predictor_0)\r\n    const boxPrediction1 = boxPredictionLayer(x, params.box_predictor_1)\r\n    const boxPrediction2 = boxPredictionLayer(conv1, params.box_predictor_2)\r\n    const boxPrediction3 = boxPredictionLayer(conv3, params.box_predictor_3)\r\n    const boxPrediction4 = boxPredictionLayer(conv5, params.box_predictor_4)\r\n    const boxPrediction5 = boxPredictionLayer(conv7, params.box_predictor_5)\r\n\r\n    const boxPredictions = tf.concat([\r\n      boxPrediction0.boxPredictionEncoding,\r\n      boxPrediction1.boxPredictionEncoding,\r\n      boxPrediction2.boxPredictionEncoding,\r\n      boxPrediction3.boxPredictionEncoding,\r\n      boxPrediction4.boxPredictionEncoding,\r\n      boxPrediction5.boxPredictionEncoding\r\n    ], 1) as tf.Tensor4D\r\n\r\n    const classPredictions = tf.concat([\r\n      boxPrediction0.classPrediction,\r\n      boxPrediction1.classPrediction,\r\n      boxPrediction2.classPrediction,\r\n      boxPrediction3.classPrediction,\r\n      boxPrediction4.classPrediction,\r\n      boxPrediction5.classPrediction\r\n    ], 1) as tf.Tensor4D\r\n\r\n    return {\r\n      boxPredictions,\r\n      classPredictions\r\n    }\r\n  })\r\n}","export interface ISsdMobilenetv1Options {\r\n  minConfidence?: number\r\n  maxResults?: number\r\n}\r\n\r\nexport class SsdMobilenetv1Options {\r\n  protected _name: string = 'SsdMobilenetv1Options'\r\n\r\n  private _minConfidence: number\r\n  private _maxResults: number\r\n\r\n  constructor({ minConfidence, maxResults }: ISsdMobilenetv1Options = {}) {\r\n    this._minConfidence = minConfidence || 0.5\r\n    this._maxResults = maxResults || 100\r\n\r\n    if (typeof this._minConfidence !== 'number' || this._minConfidence <= 0 || this._minConfidence >= 1) {\r\n      throw new Error(`${this._name} - expected minConfidence to be a number between 0 and 1`)\r\n    }\r\n\r\n    if (typeof this._maxResults !== 'number') {\r\n      throw new Error(`${this._name} - expected maxResults to be a number`)\r\n    }\r\n  }\r\n\r\n  get minConfidence(): number { return this._minConfidence }\r\n  get maxResults(): number { return this._maxResults }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Rect } from '../classes';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { mobileNetV1 } from './mobileNetV1';\r\nimport { nonMaxSuppression } from './nonMaxSuppression';\r\nimport { outputLayer } from './outputLayer';\r\nimport { predictionLayer } from './predictionLayer';\r\nimport { ISsdMobilenetv1Options, SsdMobilenetv1Options } from './SsdMobilenetv1Options';\r\nimport { NetParams } from './types';\r\n\r\n\r\nexport class SsdMobilenetv1 extends NeuralNetwork<NetParams> {\r\n\r\n  constructor() {\r\n    super('SsdMobilenetv1')\r\n  }\r\n\r\n  public forwardInput(input: NetInput) {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('SsdMobilenetv1 - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n      const batchTensor = input.toBatchTensor(512, false).toFloat()\r\n\r\n      const x = tf.sub(tf.mul(batchTensor, tf.scalar(0.007843137718737125)), tf.scalar(1)) as tf.Tensor4D\r\n      const features = mobileNetV1(x, params.mobilenetv1)\r\n\r\n      const {\r\n        boxPredictions,\r\n        classPredictions\r\n      } = predictionLayer(features.out, features.conv11, params.prediction_layer)\r\n\r\n      return outputLayer(boxPredictions, classPredictions, params.output_layer)\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput) {\r\n    return this.forwardInput(await toNetInput(input))\r\n  }\r\n\r\n  public async locateFaces(\r\n    input: TNetInput,\r\n    options: ISsdMobilenetv1Options = {}\r\n  ): Promise<FaceDetection[]> {\r\n\r\n    const { maxResults, minConfidence } = new SsdMobilenetv1Options(options)\r\n\r\n    const netInput = await toNetInput(input)\r\n\r\n    const {\r\n      boxes: _boxes,\r\n      scores: _scores\r\n    } = this.forwardInput(netInput)\r\n\r\n\r\n    // TODO batches\r\n    const boxes = _boxes[0]\r\n    const scores = _scores[0]\r\n    for (let i = 1; i < _boxes.length; i++) {\r\n      _boxes[i].dispose()\r\n      _scores[i].dispose()\r\n    }\r\n\r\n    // TODO find a better way to filter by minConfidence\r\n    const scoresData = Array.from(await scores.data())\r\n\r\n    const iouThreshold = 0.5\r\n    const indices = nonMaxSuppression(\r\n      boxes,\r\n      scoresData,\r\n      maxResults,\r\n      iouThreshold,\r\n      minConfidence\r\n    )\r\n\r\n    const reshapedDims = netInput.getReshapedInputDimensions(0)\r\n    const inputSize = netInput.inputSize as number\r\n    const padX = inputSize / reshapedDims.width\r\n    const padY = inputSize / reshapedDims.height\r\n\r\n    const boxesData = boxes.arraySync()\r\n    const results = indices\r\n      .map(idx => {\r\n        const [top, bottom] = [\r\n          Math.max(0, boxesData[idx][0]),\r\n          Math.min(1.0, boxesData[idx][2])\r\n        ].map(val => val * padY)\r\n        const [left, right] = [\r\n          Math.max(0, boxesData[idx][1]),\r\n          Math.min(1.0, boxesData[idx][3])\r\n        ].map(val => val * padX)\r\n        return new FaceDetection(\r\n          scoresData[idx],\r\n          new Rect(\r\n            left,\r\n            top,\r\n            right - left,\r\n            bottom - top\r\n          ),\r\n          {\r\n            height: netInput.getInputHeight(0),\r\n            width: netInput.getInputWidth(0)\r\n          }\r\n        )\r\n      })\r\n\r\n    boxes.dispose()\r\n    scores.dispose()\r\n\r\n    return results\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'ssd_mobilenetv1_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n}","import { SsdMobilenetv1 } from './SsdMobilenetv1';\r\n\r\nexport * from './SsdMobilenetv1';\r\nexport * from './SsdMobilenetv1Options';\r\n\r\nexport function createSsdMobilenetv1(weights: Float32Array) {\r\n  const net = new SsdMobilenetv1()\r\n  net.extractWeights(weights)\r\n  return net\r\n}\r\n\r\nexport function createFaceDetectionNet(weights: Float32Array) {\r\n  return createSsdMobilenetv1(weights)\r\n}\r\n\r\n// alias for backward compatibily\r\nexport class FaceDetectionNet extends SsdMobilenetv1 {}","import { Point } from '../classes';\r\n\r\nexport const IOU_THRESHOLD = 0.4\r\n\r\nexport const BOX_ANCHORS = [\r\n  new Point(0.738768, 0.874946),\r\n  new Point(2.42204, 2.65704),\r\n  new Point(4.30971, 7.04493),\r\n  new Point(10.246, 4.59428),\r\n  new Point(12.6868, 11.8741)\r\n]\r\n\r\nexport const BOX_ANCHORS_SEPARABLE = [\r\n  new Point(1.603231, 2.094468),\r\n  new Point(6.041143, 7.080126),\r\n  new Point(2.882459, 3.518061),\r\n  new Point(4.266906, 5.178857),\r\n  new Point(9.041765, 10.66308)\r\n]\r\n\r\nexport const MEAN_RGB_SEPARABLE: [number, number, number] = [117.001, 114.697, 97.404]\r\n\r\nexport const DEFAULT_MODEL_NAME = 'tiny_yolov2_model'\r\nexport const DEFAULT_MODEL_NAME_SEPARABLE_CONV = 'tiny_yolov2_separable_conv_model'","import { Point } from '../classes/Point';\r\n\r\nexport type TinyYolov2Config = {\r\n  withSeparableConvs: boolean\r\n  iouThreshold: number\r\n  anchors: Point[]\r\n  classes: string[]\r\n  meanRgb?: [number, number, number]\r\n  withClassScores?: boolean,\r\n  filterSizes?: number[]\r\n  isFirstLayerConv2d?: boolean\r\n}\r\n\r\nconst isNumber = (arg: any) => typeof arg === 'number'\r\n\r\nexport function validateConfig(config: any) {\r\n  if (!config) {\r\n    throw new Error(`invalid config: ${config}`)\r\n  }\r\n\r\n  if (typeof config.withSeparableConvs !== 'boolean') {\r\n    throw new Error(`config.withSeparableConvs has to be a boolean, have: ${config.withSeparableConvs}`)\r\n  }\r\n\r\n  if (!isNumber(config.iouThreshold) || config.iouThreshold < 0 || config.iouThreshold > 1.0) {\r\n    throw new Error(`config.iouThreshold has to be a number between [0, 1], have: ${config.iouThreshold}`)\r\n  }\r\n\r\n  if (\r\n    !Array.isArray(config.classes)\r\n    || !config.classes.length\r\n    || !config.classes.every((c: any) => typeof c === 'string')\r\n  ) {\r\n\r\n    throw new Error(`config.classes has to be an array class names: string[], have: ${JSON.stringify(config.classes)}`)\r\n  }\r\n\r\n  if (\r\n    !Array.isArray(config.anchors)\r\n    || !config.anchors.length\r\n    || !config.anchors.map((a: any) => a || {}).every((a: any) => isNumber(a.x) && isNumber(a.y))\r\n  ) {\r\n\r\n    throw new Error(`config.anchors has to be an array of { x: number, y: number }, have: ${JSON.stringify(config.anchors)}`)\r\n  }\r\n\r\n  if (config.meanRgb && (\r\n    !Array.isArray(config.meanRgb)\r\n    || config.meanRgb.length !== 3\r\n    || !config.meanRgb.every(isNumber)\r\n  )) {\r\n\r\n    throw new Error(`config.meanRgb has to be an array of shape [number, number, number], have: ${JSON.stringify(config.meanRgb)}`)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function leaky(x: tf.Tensor4D): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n    const min = tf.mul(x, tf.scalar(0.10000000149011612))\r\n    return tf.add(tf.relu(tf.sub(x, min)), min)\r\n    //return tf.maximum(x, min)\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { leaky } from './leaky';\r\nimport { ConvWithBatchNorm } from './types';\r\n\r\nexport function convWithBatchNorm(x: tf.Tensor4D, params: ConvWithBatchNorm): tf.Tensor4D  {\r\n  return tf.tidy(() => {\r\n    let out = tf.pad(x, [[0, 0], [1, 1], [1, 1], [0, 0]]) as tf.Tensor4D\r\n\r\n    out = tf.conv2d(out, params.conv.filters, [1, 1], 'valid')\r\n    out = tf.sub(out, params.bn.sub)\r\n    out = tf.mul(out, params.bn.truediv)\r\n    out = tf.add(out, params.conv.bias)\r\n\r\n    return leaky(out)\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { SeparableConvParams } from '../common/types';\r\nimport { leaky } from './leaky';\r\n\r\nexport function depthwiseSeparableConv(x: tf.Tensor4D, params: SeparableConvParams): tf.Tensor4D  {\r\n  return tf.tidy(() => {\r\n    let out = tf.pad(x, [[0, 0], [1, 1], [1, 1], [0, 0]]) as tf.Tensor4D\r\n\r\n    out = tf.separableConv2d(out, params.depthwise_filter, params.pointwise_filter, [1, 1], 'valid')\r\n    out = tf.add(out, params.bias)\r\n\r\n    return leaky(out)\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { extractConvParamsFactory } from '../common';\r\nimport { extractSeparableConvParamsFactory } from '../common/extractSeparableConvParamsFactory';\r\nimport { extractWeightsFactory } from '../common/extractWeightsFactory';\r\nimport { ExtractWeightsFunction, ParamMapping } from '../common/types';\r\nimport { TinyYolov2Config } from './config';\r\nimport { BatchNorm, ConvWithBatchNorm, TinyYolov2NetParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  const extractConvParams = extractConvParamsFactory(extractWeights, paramMappings)\r\n\r\n  function extractBatchNormParams(size: number, mappedPrefix: string): BatchNorm {\r\n\r\n    const sub = tf.tensor1d(extractWeights(size))\r\n    const truediv = tf.tensor1d(extractWeights(size))\r\n\r\n    paramMappings.push(\r\n      { paramPath: `${mappedPrefix}/sub` },\r\n      { paramPath: `${mappedPrefix}/truediv` }\r\n    )\r\n\r\n    return { sub, truediv }\r\n  }\r\n\r\n  function extractConvWithBatchNormParams(channelsIn: number, channelsOut: number, mappedPrefix: string): ConvWithBatchNorm {\r\n\r\n    const conv = extractConvParams(channelsIn, channelsOut, 3, `${mappedPrefix}/conv`)\r\n    const bn = extractBatchNormParams(channelsOut, `${mappedPrefix}/bn`)\r\n\r\n    return { conv, bn }\r\n  }\r\n  const extractSeparableConvParams = extractSeparableConvParamsFactory(extractWeights, paramMappings)\r\n\r\n  return {\r\n    extractConvParams,\r\n    extractConvWithBatchNormParams,\r\n    extractSeparableConvParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(\r\n  weights: Float32Array,\r\n  config: TinyYolov2Config,\r\n  boxEncodingSize: number,\r\n  filterSizes: number[]\r\n): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvParams,\r\n    extractConvWithBatchNormParams,\r\n    extractSeparableConvParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  let params: TinyYolov2NetParams\r\n\r\n  if (config.withSeparableConvs) {\r\n    const [s0, s1, s2, s3, s4, s5, s6, s7, s8] = filterSizes\r\n\r\n    const conv0 = config.isFirstLayerConv2d\r\n      ? extractConvParams(s0, s1, 3, 'conv0')\r\n      : extractSeparableConvParams(s0, s1, 'conv0')\r\n    const conv1 = extractSeparableConvParams(s1, s2, 'conv1')\r\n    const conv2 = extractSeparableConvParams(s2, s3, 'conv2')\r\n    const conv3 = extractSeparableConvParams(s3, s4, 'conv3')\r\n    const conv4 = extractSeparableConvParams(s4, s5, 'conv4')\r\n    const conv5 = extractSeparableConvParams(s5, s6, 'conv5')\r\n    const conv6 = s7 ? extractSeparableConvParams(s6, s7, 'conv6') : undefined\r\n    const conv7 = s8 ? extractSeparableConvParams(s7, s8, 'conv7') : undefined\r\n    const conv8 = extractConvParams(s8 || s7 || s6, 5 * boxEncodingSize, 1, 'conv8')\r\n    params = { conv0, conv1, conv2, conv3, conv4, conv5, conv6, conv7, conv8 }\r\n  } else {\r\n    const [s0, s1, s2, s3, s4, s5, s6, s7, s8] = filterSizes\r\n    const conv0 = extractConvWithBatchNormParams(s0, s1, 'conv0',)\r\n    const conv1 = extractConvWithBatchNormParams(s1, s2, 'conv1')\r\n    const conv2 = extractConvWithBatchNormParams(s2, s3, 'conv2')\r\n    const conv3 = extractConvWithBatchNormParams(s3, s4, 'conv3')\r\n    const conv4 = extractConvWithBatchNormParams(s4, s5, 'conv4')\r\n    const conv5 = extractConvWithBatchNormParams(s5, s6, 'conv5')\r\n    const conv6 = extractConvWithBatchNormParams(s6, s7, 'conv6')\r\n    const conv7 = extractConvWithBatchNormParams(s7, s8, 'conv7')\r\n    const conv8 = extractConvParams(s8, 5 * boxEncodingSize, 1, 'conv8')\r\n    params = { conv0, conv1, conv2, conv3, conv4, conv5, conv6, conv7, conv8 }\r\n  }\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n\r\n  return { params, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams } from '../common';\r\nimport { disposeUnusedWeightTensors } from '../common/disposeUnusedWeightTensors';\r\nimport { loadSeparableConvParamsFactory } from '../common/extractSeparableConvParamsFactory';\r\nimport { extractWeightEntryFactory } from '../common/extractWeightEntryFactory';\r\nimport { ParamMapping } from '../common/types';\r\nimport { TinyYolov2Config } from './config';\r\nimport { BatchNorm, ConvWithBatchNorm, TinyYolov2NetParams } from './types';\r\n\r\nfunction extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractBatchNormParams(prefix: string): BatchNorm {\r\n    const sub = extractWeightEntry<tf.Tensor1D>(`${prefix}/sub`, 1)\r\n    const truediv = extractWeightEntry<tf.Tensor1D>(`${prefix}/truediv`, 1)\r\n    return { sub, truediv }\r\n  }\r\n\r\n  function extractConvParams(prefix: string): ConvParams {\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/filters`, 4)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractConvWithBatchNormParams(prefix: string): ConvWithBatchNorm {\r\n    const conv = extractConvParams(`${prefix}/conv`)\r\n    const bn = extractBatchNormParams(`${prefix}/bn`)\r\n    return { conv, bn }\r\n  }\r\n\r\n  const extractSeparableConvParams = loadSeparableConvParamsFactory(extractWeightEntry)\r\n\r\n  return {\r\n    extractConvParams,\r\n    extractConvWithBatchNormParams,\r\n    extractSeparableConvParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap,\r\n  config: TinyYolov2Config\r\n): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractConvParams,\r\n    extractConvWithBatchNormParams,\r\n    extractSeparableConvParams\r\n  } = extractorsFactory(weightMap, paramMappings)\r\n\r\n  let params: TinyYolov2NetParams\r\n\r\n  if (config.withSeparableConvs) {\r\n    const numFilters = (config.filterSizes && config.filterSizes.length || 9)\r\n    params = {\r\n      conv0: config.isFirstLayerConv2d ? extractConvParams('conv0') : extractSeparableConvParams('conv0'),\r\n      conv1: extractSeparableConvParams('conv1'),\r\n      conv2: extractSeparableConvParams('conv2'),\r\n      conv3: extractSeparableConvParams('conv3'),\r\n      conv4: extractSeparableConvParams('conv4'),\r\n      conv5: extractSeparableConvParams('conv5'),\r\n      conv6: numFilters > 7 ? extractSeparableConvParams('conv6') : undefined,\r\n      conv7: numFilters > 8 ? extractSeparableConvParams('conv7') : undefined,\r\n      conv8: extractConvParams('conv8')\r\n    }\r\n  } else {\r\n    params = {\r\n      conv0: extractConvWithBatchNormParams('conv0'),\r\n      conv1: extractConvWithBatchNormParams('conv1'),\r\n      conv2: extractConvWithBatchNormParams('conv2'),\r\n      conv3: extractConvWithBatchNormParams('conv3'),\r\n      conv4: extractConvWithBatchNormParams('conv4'),\r\n      conv5: extractConvWithBatchNormParams('conv5'),\r\n      conv6: extractConvWithBatchNormParams('conv6'),\r\n      conv7: extractConvWithBatchNormParams('conv7'),\r\n      conv8: extractConvParams('conv8')\r\n    }\r\n  }\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params, paramMappings }\r\n}","export enum TinyYolov2SizeType {\r\n  XS = 224,\r\n  SM = 320,\r\n  MD = 416,\r\n  LG = 608\r\n}\r\n\r\nexport interface ITinyYolov2Options {\r\n  inputSize?: number\r\n  scoreThreshold?: number\r\n}\r\n\r\nexport class TinyYolov2Options {\r\n  protected _name: string = 'TinyYolov2Options'\r\n\r\n  private _inputSize: number\r\n  private _scoreThreshold: number\r\n\r\n  constructor({ inputSize, scoreThreshold }: ITinyYolov2Options = {}) {\r\n    this._inputSize = inputSize || 416\r\n    this._scoreThreshold = scoreThreshold || 0.5\r\n\r\n    if (typeof this._inputSize !== 'number' || this._inputSize % 32 !== 0) {\r\n      throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`)\r\n    }\r\n\r\n    if (typeof this._scoreThreshold !== 'number' || this._scoreThreshold <= 0 || this._scoreThreshold >= 1) {\r\n      throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)\r\n    }\r\n  }\r\n\r\n  get inputSize(): number { return this._inputSize }\r\n  get scoreThreshold(): number { return this._scoreThreshold }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { BoundingBox } from '../classes/BoundingBox';\r\nimport { Dimensions } from '../classes/Dimensions';\r\nimport { ObjectDetection } from '../classes/ObjectDetection';\r\nimport { convLayer } from '../common';\r\nimport { ConvParams, SeparableConvParams } from '../common/types';\r\nimport { toNetInput } from '../dom';\r\nimport { NetInput } from '../dom/NetInput';\r\nimport { TNetInput } from '../dom/types';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { sigmoid } from '../ops';\r\nimport { nonMaxSuppression } from '../ops/nonMaxSuppression';\r\nimport { normalize } from '../ops/normalize';\r\nimport { TinyYolov2Config, validateConfig } from './config';\r\nimport { convWithBatchNorm } from './convWithBatchNorm';\r\nimport { depthwiseSeparableConv } from './depthwiseSeparableConv';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { leaky } from './leaky';\r\nimport { ITinyYolov2Options, TinyYolov2Options } from './TinyYolov2Options';\r\nimport { DefaultTinyYolov2NetParams, MobilenetParams, TinyYolov2NetParams } from './types';\r\n\r\nexport class TinyYolov2Base extends NeuralNetwork<TinyYolov2NetParams> {\r\n\r\n  public static DEFAULT_FILTER_SIZES = [\r\n    3, 16, 32, 64, 128, 256, 512, 1024, 1024\r\n  ]\r\n\r\n  private _config: TinyYolov2Config\r\n\r\n  constructor(config: TinyYolov2Config) {\r\n    super('TinyYolov2')\r\n    validateConfig(config)\r\n    this._config = config\r\n  }\r\n\r\n  public get config(): TinyYolov2Config {\r\n    return this._config\r\n  }\r\n\r\n  public get withClassScores(): boolean {\r\n    return this.config.withClassScores || this.config.classes.length > 1\r\n  }\r\n\r\n  public get boxEncodingSize(): number {\r\n    return 5 + (this.withClassScores ? this.config.classes.length : 0)\r\n  }\r\n\r\n  public runTinyYolov2(x: tf.Tensor4D, params: DefaultTinyYolov2NetParams): tf.Tensor4D {\r\n\r\n    let out = convWithBatchNorm(x, params.conv0)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv1)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv2)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv3)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv4)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convWithBatchNorm(out, params.conv5)\r\n    out = tf.maxPool(out, [2, 2], [1, 1], 'same')\r\n    out = convWithBatchNorm(out, params.conv6)\r\n    out = convWithBatchNorm(out, params.conv7)\r\n\r\n    return convLayer(out, params.conv8, 'valid', false)\r\n  }\r\n\r\n  public runMobilenet(x: tf.Tensor4D, params: MobilenetParams): tf.Tensor4D {\r\n\r\n    let out = this.config.isFirstLayerConv2d\r\n      ? leaky(convLayer(x, params.conv0 as ConvParams, 'valid', false))\r\n      : depthwiseSeparableConv(x, params.conv0 as SeparableConvParams)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv1)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv2)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv3)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv4)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = depthwiseSeparableConv(out, params.conv5)\r\n    out = tf.maxPool(out, [2, 2], [1, 1], 'same')\r\n    out = params.conv6 ? depthwiseSeparableConv(out, params.conv6) : out\r\n    out = params.conv7 ? depthwiseSeparableConv(out, params.conv7) : out\r\n\r\n    return convLayer(out, params.conv8, 'valid', false)\r\n  }\r\n\r\n  public forwardInput(input: NetInput, inputSize: number): tf.Tensor4D {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('TinyYolov2 - load model before inference')\r\n    }\r\n\r\n    return tf.tidy(() => {\r\n\r\n      let batchTensor = input.toBatchTensor(inputSize, false).toFloat()\r\n      batchTensor = this.config.meanRgb\r\n        ? normalize(batchTensor, this.config.meanRgb)\r\n        : batchTensor\r\n      batchTensor = batchTensor.div(tf.scalar(256)) as tf.Tensor4D\r\n\r\n      return this.config.withSeparableConvs\r\n        ? this.runMobilenet(batchTensor, params as MobilenetParams)\r\n        : this.runTinyYolov2(batchTensor, params as DefaultTinyYolov2NetParams)\r\n    })\r\n  }\r\n\r\n  public async forward(input: TNetInput, inputSize: number): Promise<tf.Tensor4D> {\r\n    return await this.forwardInput(await toNetInput(input), inputSize)\r\n  }\r\n\r\n  public async detect(input: TNetInput, forwardParams: ITinyYolov2Options = {}): Promise<ObjectDetection[]> {\r\n\r\n    const { inputSize, scoreThreshold } = new TinyYolov2Options(forwardParams)\r\n\r\n    const netInput = await toNetInput(input)\r\n    const out = await this.forwardInput(netInput, inputSize)\r\n    const out0 = tf.tidy(() => tf.unstack(out)[0].expandDims()) as tf.Tensor4D\r\n\r\n    const inputDimensions = {\r\n      width: netInput.getInputWidth(0),\r\n      height: netInput.getInputHeight(0)\r\n    }\r\n\r\n    const results = await this.extractBoxes(out0, netInput.getReshapedInputDimensions(0), scoreThreshold)\r\n    out.dispose()\r\n    out0.dispose()\r\n\r\n    const boxes = results.map(res => res.box)\r\n    const scores = results.map(res => res.score)\r\n    const classScores = results.map(res => res.classScore)\r\n    const classNames = results.map(res => this.config.classes[res.label])\r\n\r\n    const indices = nonMaxSuppression(\r\n      boxes.map(box => box.rescale(inputSize)),\r\n      scores,\r\n      this.config.iouThreshold,\r\n      true\r\n    )\r\n\r\n    const detections = indices.map(idx =>\r\n      new ObjectDetection(\r\n        scores[idx],\r\n        classScores[idx],\r\n        classNames[idx],\r\n        boxes[idx],\r\n        inputDimensions\r\n      )\r\n    )\r\n\r\n    return detections\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return ''\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap, this.config)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    const filterSizes = this.config.filterSizes || TinyYolov2Base.DEFAULT_FILTER_SIZES\r\n\r\n    const numFilters = filterSizes ? filterSizes.length : undefined\r\n    if (numFilters !== 7 && numFilters !== 8 && numFilters !== 9) {\r\n      throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${numFilters} filterSizes in config`)\r\n    }\r\n    return extractParams(weights, this.config, this.boxEncodingSize, filterSizes)\r\n  }\r\n\r\n  protected async extractBoxes(\r\n    outputTensor: tf.Tensor4D,\r\n    inputBlobDimensions: Dimensions,\r\n    scoreThreshold?: number\r\n  ) {\r\n\r\n    const { width, height } = inputBlobDimensions\r\n    const inputSize = Math.max(width, height)\r\n    const correctionFactorX = inputSize / width\r\n    const correctionFactorY = inputSize / height\r\n\r\n    const numCells = outputTensor.shape[1]\r\n    const numBoxes = this.config.anchors.length\r\n\r\n    const [boxesTensor, scoresTensor, classScoresTensor] = tf.tidy(() => {\r\n      const reshaped = outputTensor.reshape([numCells, numCells, numBoxes, this.boxEncodingSize])\r\n\r\n      const boxes = reshaped.slice([0, 0, 0, 0], [numCells, numCells, numBoxes, 4])\r\n      const scores = reshaped.slice([0, 0, 0, 4], [numCells, numCells, numBoxes, 1])\r\n      const classScores = this.withClassScores\r\n        ? tf.softmax(reshaped.slice([0, 0, 0, 5], [numCells, numCells, numBoxes, this.config.classes.length]), 3)\r\n        : tf.scalar(0)\r\n      return [boxes, scores, classScores]\r\n    })\r\n\r\n    const results = []\r\n\r\n    const scoresData = await scoresTensor.array()\r\n    const boxesData = await boxesTensor.array()\r\n    for (let row = 0; row < numCells; row ++) {\r\n      for (let col = 0; col < numCells; col ++) {\r\n        for (let anchor = 0; anchor < numBoxes; anchor ++) {\r\n\r\n          const score = sigmoid(scoresData[row][col][anchor][0]);\r\n          if (!scoreThreshold || score > scoreThreshold) {\r\n            const ctX = ((col + sigmoid(boxesData[row][col][anchor][0])) / numCells) * correctionFactorX\r\n            const ctY = ((row + sigmoid(boxesData[row][col][anchor][1])) / numCells) * correctionFactorY\r\n            const width = ((Math.exp(boxesData[row][col][anchor][2]) * this.config.anchors[anchor].x) / numCells) * correctionFactorX\r\n            const height = ((Math.exp(boxesData[row][col][anchor][3]) * this.config.anchors[anchor].y) / numCells) * correctionFactorY\r\n\r\n            const x = (ctX - (width / 2))\r\n            const y = (ctY - (height / 2))\r\n\r\n            const pos = { row, col, anchor }\r\n            const { classScore, label } = this.withClassScores\r\n              ? await this.extractPredictedClass(classScoresTensor as tf.Tensor4D, pos)\r\n              : { classScore: 1, label: 0 }\r\n\r\n            results.push({\r\n              box: new BoundingBox(x, y, x + width, y + height),\r\n              score: score,\r\n              classScore: score * classScore,\r\n              label,\r\n              ...pos\r\n            })\r\n          }\r\n        }\r\n      }\r\n    }\r\n\r\n    boxesTensor.dispose()\r\n    scoresTensor.dispose()\r\n    classScoresTensor.dispose()\r\n\r\n    return results\r\n  }\r\n\r\n  private async extractPredictedClass(classesTensor: tf.Tensor4D, pos: { row: number, col: number, anchor: number },) {\r\n    const { row, col, anchor } = pos\r\n    const classesData = await classesTensor.array()\r\n    return Array(this.config.classes.length).fill(0)\r\n      .map((_, i) => classesData[row][col][anchor][i])\r\n      .map((classScore, label) => ({\r\n        classScore,\r\n        label\r\n      }))\r\n      .reduce((max, curr) => max.classScore > curr.classScore ? max : curr)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FaceDetection, Point } from '../classes';\r\nimport { ParamMapping } from '../common/types';\r\nimport { TNetInput } from '../dom/types';\r\nimport {\r\n  BOX_ANCHORS,\r\n  BOX_ANCHORS_SEPARABLE,\r\n  DEFAULT_MODEL_NAME,\r\n  DEFAULT_MODEL_NAME_SEPARABLE_CONV,\r\n  IOU_THRESHOLD,\r\n  MEAN_RGB_SEPARABLE,\r\n} from './const';\r\nimport { TinyYolov2Base } from './TinyYolov2Base';\r\nimport { ITinyYolov2Options } from './TinyYolov2Options';\r\nimport { TinyYolov2NetParams } from './types';\r\n\r\nexport class TinyYolov2 extends TinyYolov2Base {\r\n\r\n  constructor(withSeparableConvs: boolean = true) {\r\n    const config = Object.assign({}, {\r\n      withSeparableConvs,\r\n      iouThreshold: IOU_THRESHOLD,\r\n      classes: ['face']\r\n    },\r\n    withSeparableConvs\r\n      ? {\r\n        anchors: BOX_ANCHORS_SEPARABLE,\r\n        meanRgb: MEAN_RGB_SEPARABLE\r\n      }\r\n      : {\r\n        anchors: BOX_ANCHORS,\r\n        withClassScores: true\r\n      }\r\n    )\r\n\r\n    super(config)\r\n  }\r\n\r\n  public get withSeparableConvs(): boolean {\r\n    return this.config.withSeparableConvs\r\n  }\r\n\r\n  public get anchors(): Point[] {\r\n    return this.config.anchors\r\n  }\r\n\r\n  public async locateFaces(input: TNetInput, forwardParams: ITinyYolov2Options): Promise<FaceDetection[]> {\r\n    const objectDetections = await this.detect(input, forwardParams)\r\n    return objectDetections.map(det => new FaceDetection(det.score, det.relativeBox, { width: det.imageWidth, height: det.imageHeight }))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return this.withSeparableConvs ? DEFAULT_MODEL_NAME_SEPARABLE_CONV : DEFAULT_MODEL_NAME\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {\r\n    return super.extractParamsFromWeigthMap(weightMap)\r\n  }\r\n}","import { TinyYolov2 } from './TinyYolov2';\r\n\r\nexport * from './TinyYolov2Options';\r\n\r\nexport * from './config'\r\nexport * from './types'\r\n\r\nexport { TinyYolov2 }\r\n\r\nexport function createTinyYolov2(weights: Float32Array, withSeparableConvs: boolean = true) {\r\n  const net = new TinyYolov2(withSeparableConvs)\r\n  net.extractWeights(weights)\r\n  return net\r\n}","import { ITinyYolov2Options, TinyYolov2Options } from '../tinyYolov2';\r\n\r\nexport interface ITinyFaceDetectorOptions extends ITinyYolov2Options {}\r\n\r\nexport class TinyFaceDetectorOptions extends TinyYolov2Options {\r\n  protected _name: string = 'TinyFaceDetectorOptions'\r\n}","export class ComposableTask<T> {\r\n\r\n  public async then(\r\n    onfulfilled: (value: T) => T | PromiseLike<T>\r\n  ): Promise<T> {\r\n    return onfulfilled(await this.run())\r\n  }\r\n\r\n  public async run(): Promise<T> {\r\n    throw new Error('ComposableTask - run is not implemented')\r\n  }\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { extractFaces, extractFaceTensors, TNetInput } from '../dom';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { isWithFaceLandmarks, WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\n\r\nexport async function extractAllFacesAndComputeResults<TSource extends WithFaceDetection<{}>, TResult>(\r\n  parentResults: TSource[],\r\n  input: TNetInput,\r\n  computeResults: (faces: Array<HTMLCanvasElement | tf.Tensor3D>) => Promise<TResult>,\r\n  extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null,\r\n  getRectForAlignment: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection = ({ alignedRect }) => alignedRect\r\n) {\r\n  const faceBoxes = parentResults.map(parentResult =>\r\n    isWithFaceLandmarks(parentResult)\r\n      ? getRectForAlignment(parentResult)\r\n      : parentResult.detection\r\n  )\r\n  const faces: Array<HTMLCanvasElement | tf.Tensor3D> = extractedFaces || (\r\n    input instanceof tf.Tensor\r\n      ? await extractFaceTensors(input, faceBoxes)\r\n      : await extractFaces(input, faceBoxes)\r\n  )\r\n\r\n  const results = await computeResults(faces)\r\n\r\n  faces.forEach(f => f instanceof tf.Tensor && f.dispose())\r\n\r\n  return results\r\n}\r\n\r\nexport async function extractSingleFaceAndComputeResult<TSource extends WithFaceDetection<{}>, TResult>(\r\n  parentResult: TSource,\r\n  input: TNetInput,\r\n  computeResult: (face: HTMLCanvasElement | tf.Tensor3D) => Promise<TResult>,\r\n  extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null,\r\n  getRectForAlignment?: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection\r\n) {\r\n  return extractAllFacesAndComputeResults<TSource, TResult>(\r\n    [parentResult],\r\n    input,\r\n    async faces => computeResult(faces[0]),\r\n    extractedFaces,\r\n    getRectForAlignment\r\n  )\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function bgrToRgbTensor(tensor: tf.Tensor4D): tf.Tensor4D {\r\n  return tf.tidy(\r\n    () => tf.stack(tf.unstack(tensor, 3).reverse(), 3)\r\n  ) as tf.Tensor4D\r\n}","export const CELL_STRIDE = 2\r\nexport const CELL_SIZE = 12","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport {\r\n  extractConvParamsFactory,\r\n  extractFCParamsFactory,\r\n  extractWeightsFactory,\r\n  ExtractWeightsFunction,\r\n  ParamMapping,\r\n} from '../common';\r\nimport { NetParams, ONetParams, PNetParams, RNetParams, SharedParams } from './types';\r\n\r\nfunction extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]) {\r\n\r\n  const extractConvParams = extractConvParamsFactory(extractWeights, paramMappings)\r\n  const extractFCParams = extractFCParamsFactory(extractWeights, paramMappings)\r\n\r\n  function extractPReluParams(size: number, paramPath: string): tf.Tensor1D {\r\n    const alpha = tf.tensor1d(extractWeights(size))\r\n    paramMappings.push({ paramPath })\r\n    return alpha\r\n  }\r\n\r\n  function extractSharedParams(numFilters: number[], mappedPrefix: string, isRnet: boolean = false): SharedParams {\r\n\r\n    const conv1 = extractConvParams(numFilters[0], numFilters[1], 3, `${mappedPrefix}/conv1`)\r\n    const prelu1_alpha = extractPReluParams(numFilters[1], `${mappedPrefix}/prelu1_alpha`)\r\n    const conv2 = extractConvParams(numFilters[1], numFilters[2], 3, `${mappedPrefix}/conv2`)\r\n    const prelu2_alpha = extractPReluParams(numFilters[2], `${mappedPrefix}/prelu2_alpha`)\r\n    const conv3 = extractConvParams(numFilters[2], numFilters[3], isRnet ? 2 : 3, `${mappedPrefix}/conv3`)\r\n    const prelu3_alpha = extractPReluParams(numFilters[3], `${mappedPrefix}/prelu3_alpha`)\r\n\r\n    return { conv1, prelu1_alpha, conv2, prelu2_alpha, conv3, prelu3_alpha }\r\n  }\r\n\r\n  function extractPNetParams(): PNetParams {\r\n\r\n    const sharedParams = extractSharedParams([3, 10, 16, 32], 'pnet')\r\n    const conv4_1 = extractConvParams(32, 2, 1, 'pnet/conv4_1')\r\n    const conv4_2 = extractConvParams(32, 4, 1, 'pnet/conv4_2')\r\n\r\n    return { ...sharedParams, conv4_1, conv4_2 }\r\n  }\r\n\r\n  function extractRNetParams(): RNetParams {\r\n\r\n    const sharedParams = extractSharedParams([3, 28, 48, 64], 'rnet', true)\r\n    const fc1 = extractFCParams(576, 128, 'rnet/fc1')\r\n    const prelu4_alpha = extractPReluParams(128, 'rnet/prelu4_alpha')\r\n    const fc2_1 = extractFCParams(128, 2, 'rnet/fc2_1')\r\n    const fc2_2 = extractFCParams(128, 4, 'rnet/fc2_2')\r\n\r\n    return { ...sharedParams, fc1, prelu4_alpha, fc2_1, fc2_2 }\r\n  }\r\n\r\n  function extractONetParams(): ONetParams {\r\n\r\n    const sharedParams = extractSharedParams([3, 32, 64, 64], 'onet')\r\n    const conv4 = extractConvParams(64, 128, 2, 'onet/conv4')\r\n    const prelu4_alpha = extractPReluParams(128, 'onet/prelu4_alpha')\r\n    const fc1 = extractFCParams(1152, 256, 'onet/fc1')\r\n    const prelu5_alpha = extractPReluParams(256, 'onet/prelu5_alpha')\r\n    const fc2_1 = extractFCParams(256, 2, 'onet/fc2_1')\r\n    const fc2_2 = extractFCParams(256, 4, 'onet/fc2_2')\r\n    const fc2_3 = extractFCParams(256, 10, 'onet/fc2_3')\r\n\r\n    return { ...sharedParams, conv4, prelu4_alpha, fc1, prelu5_alpha, fc2_1, fc2_2, fc2_3 }\r\n  }\r\n\r\n  return {\r\n    extractPNetParams,\r\n    extractRNetParams,\r\n    extractONetParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParams(weights: Float32Array): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const {\r\n    extractWeights,\r\n    getRemainingWeights\r\n  } = extractWeightsFactory(weights)\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractPNetParams,\r\n    extractRNetParams,\r\n    extractONetParams\r\n  } = extractorsFactory(extractWeights, paramMappings)\r\n\r\n  const pnet = extractPNetParams()\r\n  const rnet = extractRNetParams()\r\n  const onet = extractONetParams()\r\n\r\n  if (getRemainingWeights().length !== 0) {\r\n    throw new Error(`weights remaing after extract: ${getRemainingWeights().length}`)\r\n  }\r\n\r\n  return { params: { pnet, rnet, onet }, paramMappings }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { ConvParams, disposeUnusedWeightTensors, extractWeightEntryFactory, FCParams, ParamMapping } from '../common';\r\nimport { NetParams, ONetParams, PNetParams, RNetParams, SharedParams } from './types';\r\n\r\nfunction extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {\r\n\r\n  const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)\r\n\r\n  function extractConvParams(prefix: string): ConvParams {\r\n    const filters = extractWeightEntry<tf.Tensor4D>(`${prefix}/weights`, 4, `${prefix}/filters`)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n\r\n    return { filters, bias }\r\n  }\r\n\r\n  function extractFCParams(prefix: string): FCParams {\r\n    const weights = extractWeightEntry<tf.Tensor2D>(`${prefix}/weights`, 2)\r\n    const bias = extractWeightEntry<tf.Tensor1D>(`${prefix}/bias`, 1)\r\n\r\n    return { weights, bias }\r\n  }\r\n\r\n  function extractPReluParams(paramPath: string): tf.Tensor1D {\r\n    return extractWeightEntry<tf.Tensor1D>(paramPath, 1)\r\n  }\r\n\r\n  function extractSharedParams(prefix: string): SharedParams {\r\n\r\n    const conv1 = extractConvParams(`${prefix}/conv1`)\r\n    const prelu1_alpha = extractPReluParams(`${prefix}/prelu1_alpha`)\r\n    const conv2 = extractConvParams(`${prefix}/conv2`)\r\n    const prelu2_alpha = extractPReluParams(`${prefix}/prelu2_alpha`)\r\n    const conv3 = extractConvParams(`${prefix}/conv3`)\r\n    const prelu3_alpha = extractPReluParams(`${prefix}/prelu3_alpha`)\r\n\r\n    return { conv1, prelu1_alpha, conv2, prelu2_alpha, conv3, prelu3_alpha }\r\n  }\r\n\r\n  function extractPNetParams(): PNetParams {\r\n\r\n    const sharedParams = extractSharedParams('pnet')\r\n    const conv4_1 = extractConvParams('pnet/conv4_1')\r\n    const conv4_2 = extractConvParams('pnet/conv4_2')\r\n\r\n    return { ...sharedParams, conv4_1, conv4_2 }\r\n  }\r\n\r\n  function extractRNetParams(): RNetParams {\r\n\r\n    const sharedParams = extractSharedParams('rnet')\r\n    const fc1 = extractFCParams('rnet/fc1')\r\n    const prelu4_alpha = extractPReluParams('rnet/prelu4_alpha')\r\n    const fc2_1 = extractFCParams('rnet/fc2_1')\r\n    const fc2_2 = extractFCParams('rnet/fc2_2')\r\n\r\n    return { ...sharedParams, fc1, prelu4_alpha, fc2_1, fc2_2 }\r\n  }\r\n\r\n  function extractONetParams(): ONetParams {\r\n\r\n    const sharedParams = extractSharedParams('onet')\r\n    const conv4 = extractConvParams('onet/conv4')\r\n    const prelu4_alpha = extractPReluParams('onet/prelu4_alpha')\r\n    const fc1 = extractFCParams('onet/fc1')\r\n    const prelu5_alpha = extractPReluParams('onet/prelu5_alpha')\r\n    const fc2_1 = extractFCParams('onet/fc2_1')\r\n    const fc2_2 = extractFCParams('onet/fc2_2')\r\n    const fc2_3 = extractFCParams('onet/fc2_3')\r\n\r\n    return { ...sharedParams, conv4, prelu4_alpha, fc1, prelu5_alpha, fc2_1, fc2_2, fc2_3 }\r\n  }\r\n\r\n  return {\r\n    extractPNetParams,\r\n    extractRNetParams,\r\n    extractONetParams\r\n  }\r\n\r\n}\r\n\r\nexport function extractParamsFromWeigthMap(\r\n  weightMap: tf.NamedTensorMap\r\n): { params: NetParams, paramMappings: ParamMapping[] } {\r\n\r\n  const paramMappings: ParamMapping[] = []\r\n\r\n  const {\r\n    extractPNetParams,\r\n    extractRNetParams,\r\n    extractONetParams\r\n  } = extractorsFactory(weightMap, paramMappings)\r\n\r\n  const pnet = extractPNetParams()\r\n  const rnet = extractRNetParams()\r\n  const onet = extractONetParams()\r\n\r\n  disposeUnusedWeightTensors(weightMap, paramMappings)\r\n\r\n  return { params: { pnet, rnet, onet }, paramMappings }\r\n}","export function getSizesForScale(scale: number, [height, width]: number[]) {\r\n  return {\r\n    height: Math.floor(height * scale),\r\n    width: Math.floor(width * scale)\r\n  }\r\n}","import { CELL_SIZE } from './config'\r\n\r\nexport function pyramidDown(minFaceSize: number, scaleFactor: number, dims: number[]): number[] {\r\n\r\n  const [height, width] = dims\r\n  const m = CELL_SIZE / minFaceSize\r\n\r\n  const scales = []\r\n\r\n  let minLayer = Math.min(height, width) * m\r\n  let exp = 0\r\n  while (minLayer >= 12) {\r\n    scales.push(m * Math.pow(scaleFactor, exp))\r\n    minLayer = minLayer * scaleFactor\r\n    exp += 1\r\n  }\r\n\r\n  return scales\r\n}","import { Box } from '../classes';\r\n\r\nexport class MtcnnBox extends Box<MtcnnBox> {\r\n  constructor(left: number, top: number, right: number, bottom: number) {\r\n    super({ left, top, right, bottom }, true)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function normalize(x: tf.Tensor4D): tf.Tensor4D {\r\n  return tf.tidy(\r\n    () => tf.mul(tf.sub(x, tf.scalar(127.5)), tf.scalar(0.0078125))\r\n  )\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nexport function prelu<T extends tf.Tensor>(x: T, alpha: tf.Tensor1D): T {\r\n  return tf.tidy(() =>\r\n    tf.add(\r\n      tf.relu(x),\r\n      tf.mul(alpha, tf.neg(tf.relu(tf.neg(x))))\r\n    )\r\n  )\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { convLayer } from '../common';\r\nimport { prelu } from './prelu';\r\nimport { SharedParams } from './types';\r\n\r\nexport function sharedLayer(x: tf.Tensor4D, params: SharedParams, isPnet: boolean = false) {\r\n  return tf.tidy(() => {\r\n\r\n    let out = convLayer(x, params.conv1, 'valid')\r\n    out = prelu<tf.Tensor4D>(out, params.prelu1_alpha)\r\n    out = tf.maxPool(out, isPnet ? [2, 2]: [3, 3], [2, 2], 'same')\r\n    out = convLayer(out, params.conv2, 'valid')\r\n    out = prelu<tf.Tensor4D>(out, params.prelu2_alpha)\r\n    out = isPnet ? out : tf.maxPool(out, [3, 3], [2, 2], 'valid')\r\n    out = convLayer(out, params.conv3, 'valid')\r\n    out = prelu<tf.Tensor4D>(out, params.prelu3_alpha)\r\n\r\n    return out\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { convLayer } from '../common';\r\nimport { sharedLayer } from './sharedLayers';\r\nimport { PNetParams } from './types';\r\n\r\nexport function PNet(x: tf.Tensor4D, params: PNetParams): { prob: tf.Tensor4D, regions: tf.Tensor4D } {\r\n  return tf.tidy(() => {\r\n\r\n    let out = sharedLayer(x, params, true)\r\n    const conv = convLayer(out, params.conv4_1, 'valid')\r\n    const max = tf.expandDims(tf.max(conv, 3), 3)\r\n    const prob = tf.softmax(tf.sub(conv, max), 3) as tf.Tensor4D\r\n    const regions = convLayer(out, params.conv4_2, 'valid')\r\n\r\n    return { prob, regions }\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { BoundingBox, Point } from '../classes';\r\nimport { nonMaxSuppression } from '../ops';\r\nimport { CELL_SIZE, CELL_STRIDE } from './config';\r\nimport { getSizesForScale } from './getSizesForScale';\r\nimport { MtcnnBox } from './MtcnnBox';\r\nimport { normalize } from './normalize';\r\nimport { PNet } from './PNet';\r\nimport { PNetParams } from './types';\r\n\r\nfunction rescaleAndNormalize(x: tf.Tensor4D, scale: number): tf.Tensor4D {\r\n  return tf.tidy(() => {\r\n\r\n    const { height, width } = getSizesForScale(scale, x.shape.slice(1))\r\n    const resized = tf.image.resizeBilinear(x, [height, width])\r\n    const normalized = normalize(resized)\r\n\r\n    return (tf.transpose(normalized, [0, 2, 1, 3]) as tf.Tensor4D)\r\n  })\r\n}\r\n\r\nfunction extractBoundingBoxes(\r\n  scoresTensor: tf.Tensor2D,\r\n  regionsTensor: tf.Tensor3D,\r\n  scale: number,\r\n  scoreThreshold: number\r\n) {\r\n\r\n  // TODO: fix this!, maybe better to use tf.gather here\r\n  const indices: Point[] = []\r\n  const scoresData = scoresTensor.arraySync();\r\n  for (let y = 0; y < scoresTensor.shape[0]; y++) {\r\n    for (let x = 0; x < scoresTensor.shape[1]; x++) {\r\n      if (scoresData[y][x] >= scoreThreshold) {\r\n        indices.push(new Point(x, y))\r\n      }\r\n    }\r\n  }\r\n\r\n  const boundingBoxes = indices.map(idx => {\r\n    const cell = new BoundingBox(\r\n      Math.round((idx.y * CELL_STRIDE + 1) / scale),\r\n      Math.round((idx.x * CELL_STRIDE + 1) / scale),\r\n      Math.round((idx.y * CELL_STRIDE + CELL_SIZE) / scale),\r\n      Math.round((idx.x * CELL_STRIDE + CELL_SIZE) / scale)\r\n    )\r\n\r\n    const score = scoresData[idx.y][idx.x]\r\n\r\n    const regionsData = regionsTensor.arraySync()\r\n    const region = new MtcnnBox(\r\n      regionsData[idx.y][idx.x][0],\r\n      regionsData[idx.y][idx.x][1],\r\n      regionsData[idx.y][idx.x][2],\r\n      regionsData[idx.y][idx.x][3]\r\n    )\r\n\r\n    return {\r\n      cell,\r\n      score,\r\n      region\r\n    }\r\n  })\r\n\r\n  return boundingBoxes\r\n}\r\n\r\nexport function stage1(\r\n  imgTensor: tf.Tensor4D,\r\n  scales: number[],\r\n  scoreThreshold: number,\r\n  params: PNetParams,\r\n  stats: any\r\n) {\r\n  stats.stage1 = []\r\n\r\n  const pnetOutputs = scales.map((scale) => tf.tidy(() => {\r\n    const statsForScale: any = { scale }\r\n    const resized = rescaleAndNormalize(imgTensor, scale)\r\n\r\n    let ts = Date.now()\r\n    const { prob, regions } = PNet(resized, params)\r\n    statsForScale.pnet = Date.now() - ts\r\n\r\n    const scoresTensor = tf.unstack(tf.unstack(prob, 3)[1])[0] as tf.Tensor2D\r\n    const regionsTensor = tf.unstack(regions)[0] as tf.Tensor3D\r\n\r\n    return {\r\n      scoresTensor,\r\n      regionsTensor,\r\n      scale,\r\n      statsForScale\r\n    }\r\n  }))\r\n\r\n  const boxesForScale = pnetOutputs.map(({ scoresTensor, regionsTensor, scale, statsForScale }) => {\r\n    const boundingBoxes = extractBoundingBoxes(\r\n      scoresTensor,\r\n      regionsTensor,\r\n      scale,\r\n      scoreThreshold\r\n    )\r\n\r\n    scoresTensor.dispose()\r\n    regionsTensor.dispose()\r\n\r\n    if (!boundingBoxes.length) {\r\n      stats.stage1.push(statsForScale)\r\n      return []\r\n    }\r\n\r\n    let ts = Date.now()\r\n    const indices = nonMaxSuppression(\r\n      boundingBoxes.map(bbox => bbox.cell),\r\n      boundingBoxes.map(bbox => bbox.score),\r\n      0.5\r\n    )\r\n    statsForScale.nms = Date.now() - ts\r\n    statsForScale.numBoxes = indices.length\r\n\r\n    stats.stage1.push(statsForScale)\r\n    return indices.map(boxIdx => boundingBoxes[boxIdx])\r\n  })\r\n\r\n  const allBoxes = boxesForScale.reduce(\r\n    (all, boxes) => all.concat(boxes), []\r\n  )\r\n\r\n  let finalBoxes: BoundingBox[] = []\r\n  let finalScores: number[] = []\r\n\r\n  if (allBoxes.length > 0) {\r\n    let ts = Date.now()\r\n    const indices = nonMaxSuppression(\r\n      allBoxes.map(bbox => bbox.cell),\r\n      allBoxes.map(bbox => bbox.score),\r\n      0.7\r\n    )\r\n    stats.stage1_nms = Date.now() - ts\r\n\r\n    finalScores = indices.map(idx => allBoxes[idx].score)\r\n    finalBoxes = indices\r\n      .map(idx => allBoxes[idx])\r\n      .map(({ cell, region }) =>\r\n        new BoundingBox(\r\n          cell.left + (region.left * cell.width),\r\n          cell.top + (region.top * cell.height),\r\n          cell.right + (region.right * cell.width),\r\n          cell.bottom + (region.bottom * cell.height)\r\n        ).toSquare().round()\r\n      )\r\n\r\n  }\r\n\r\n  return {\r\n    boxes: finalBoxes,\r\n    scores: finalScores\r\n  }\r\n\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Box, IDimensions } from '../classes';\r\nimport { createCanvas, createCanvasFromMedia, getContext2dOrThrow } from '../dom';\r\nimport { env } from '../env';\r\nimport { normalize } from './normalize';\r\n\r\nexport async function extractImagePatches(\r\n  img: HTMLCanvasElement,\r\n  boxes: Box[],\r\n  { width, height }: IDimensions\r\n): Promise<tf.Tensor4D[]> {\r\n\r\n\r\n  const imgCtx = getContext2dOrThrow(img)\r\n\r\n  const bitmaps = await Promise.all(boxes.map(async box => {\r\n    // TODO: correct padding\r\n    const { y, ey, x, ex } = box.padAtBorders(img.height, img.width)\r\n\r\n    const fromX = x - 1\r\n    const fromY = y - 1\r\n    const imgData = imgCtx.getImageData(fromX, fromY, (ex - fromX), (ey - fromY))\r\n\r\n    return env.isNodejs() ? createCanvasFromMedia(imgData) : createImageBitmap(imgData)\r\n  }))\r\n\r\n  const imagePatchesDatas: number[][] = []\r\n\r\n  bitmaps.forEach(bmp => {\r\n    const patch = createCanvas({ width, height })\r\n    const patchCtx = getContext2dOrThrow(patch)\r\n    patchCtx.drawImage(bmp, 0, 0, width, height)\r\n    const { data } = patchCtx.getImageData(0, 0, width, height)\r\n\r\n    const currData = []\r\n    // RGBA -> BGR\r\n    for(let i = 0; i < data.length; i+=4) {\r\n      currData.push(data[i + 2])\r\n      currData.push(data[i + 1])\r\n      currData.push(data[i])\r\n    }\r\n    imagePatchesDatas.push(currData)\r\n  })\r\n\r\n\r\n  return imagePatchesDatas.map(data => {\r\n    const t = tf.tidy(() => {\r\n      const imagePatchTensor = tf.transpose(\r\n        tf.tensor4d(data, [1, width, height, 3]),\r\n        [0, 2, 1, 3]\r\n      ).toFloat() as tf.Tensor4D\r\n\r\n      return normalize(imagePatchTensor)\r\n    })\r\n    return t\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { fullyConnectedLayer } from '../common/fullyConnectedLayer';\r\nimport { prelu } from './prelu';\r\nimport { sharedLayer } from './sharedLayers';\r\nimport { RNetParams } from './types';\r\n\r\nexport function RNet(x: tf.Tensor4D, params: RNetParams): { scores: tf.Tensor1D, regions: tf.Tensor2D } {\r\n  return tf.tidy(() => {\r\n\r\n    const convOut = sharedLayer(x, params)\r\n    const vectorized = tf.reshape(convOut, [convOut.shape[0], params.fc1.weights.shape[0]]) as tf.Tensor2D\r\n    const fc1 = fullyConnectedLayer(vectorized, params.fc1)\r\n    const prelu4 = prelu<tf.Tensor2D>(fc1, params.prelu4_alpha)\r\n    const fc2_1 = fullyConnectedLayer(prelu4, params.fc2_1)\r\n    const max = tf.expandDims(tf.max(fc2_1, 1), 1)\r\n    const prob = tf.softmax(tf.sub(fc2_1, max), 1) as tf.Tensor2D\r\n    const regions = fullyConnectedLayer(prelu4, params.fc2_2)\r\n\r\n    const scores = tf.unstack(prob, 1)[1] as tf.Tensor1D\r\n    return { scores, regions }\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Box } from '../classes';\r\nimport { nonMaxSuppression } from '../ops';\r\nimport { extractImagePatches } from './extractImagePatches';\r\nimport { MtcnnBox } from './MtcnnBox';\r\nimport { RNet } from './RNet';\r\nimport { RNetParams } from './types';\r\n\r\nexport async function stage2(\r\n  img: HTMLCanvasElement,\r\n  inputBoxes: Box[],\r\n  scoreThreshold: number,\r\n  params: RNetParams,\r\n  stats: any\r\n) {\r\n\r\n  let ts = Date.now()\r\n  const rnetInputs = await extractImagePatches(img, inputBoxes, { width: 24, height: 24 })\r\n  stats.stage2_extractImagePatches = Date.now() - ts\r\n\r\n  ts = Date.now()\r\n  const rnetOuts = rnetInputs.map(\r\n    rnetInput => {\r\n      const out = RNet(rnetInput, params)\r\n      rnetInput.dispose()\r\n      return out\r\n    }\r\n  )\r\n  stats.stage2_rnet = Date.now() - ts\r\n\r\n  const scoresTensor = rnetOuts.length > 1\r\n    ? tf.concat(rnetOuts.map(out => out.scores))\r\n    : rnetOuts[0].scores\r\n  const scores = Array.from(await scoresTensor.data())\r\n  scoresTensor.dispose()\r\n\r\n  const indices = scores\r\n    .map((score, idx) => ({ score, idx }))\r\n    .filter(c => c.score > scoreThreshold)\r\n    .map(({ idx }) => idx)\r\n\r\n  const filteredBoxes = indices.map(idx => inputBoxes[idx])\r\n  const filteredScores = indices.map(idx => scores[idx])\r\n\r\n  let finalBoxes: Box[] = []\r\n  let finalScores: number[] = []\r\n\r\n  if (filteredBoxes.length > 0) {\r\n    ts = Date.now()\r\n    const indicesNms = nonMaxSuppression(\r\n      filteredBoxes,\r\n      filteredScores,\r\n      0.7\r\n    )\r\n    stats.stage2_nms = Date.now() - ts\r\n\r\n    const regions = indicesNms.map(idx =>{\r\n        const regionsData = rnetOuts[indices[idx]].regions.arraySync()\r\n        return new MtcnnBox(\r\n          regionsData[0][0],\r\n          regionsData[0][1],\r\n          regionsData[0][2],\r\n          regionsData[0][3]\r\n        )\r\n      }\r\n    )\r\n\r\n    finalScores = indicesNms.map(idx => filteredScores[idx])\r\n    finalBoxes = indicesNms.map((idx, i) => filteredBoxes[idx].calibrate(regions[i]))\r\n  }\r\n\r\n  rnetOuts.forEach(t => {\r\n    t.regions.dispose()\r\n    t.scores.dispose()\r\n  })\r\n\r\n  return {\r\n    boxes: finalBoxes,\r\n    scores: finalScores\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { convLayer } from '../common';\r\nimport { fullyConnectedLayer } from '../common/fullyConnectedLayer';\r\nimport { prelu } from './prelu';\r\nimport { sharedLayer } from './sharedLayers';\r\nimport { ONetParams } from './types';\r\n\r\nexport function ONet(x: tf.Tensor4D, params: ONetParams): { scores: tf.Tensor1D, regions: tf.Tensor2D, points: tf.Tensor2D } {\r\n  return tf.tidy(() => {\r\n\r\n    let out = sharedLayer(x, params)\r\n    out = tf.maxPool(out, [2, 2], [2, 2], 'same')\r\n    out = convLayer(out, params.conv4, 'valid')\r\n    out = prelu<tf.Tensor4D>(out, params.prelu4_alpha)\r\n\r\n    const vectorized = tf.reshape(out, [out.shape[0], params.fc1.weights.shape[0]]) as tf.Tensor2D\r\n    const fc1 = fullyConnectedLayer(vectorized, params.fc1)\r\n    const prelu5 = prelu<tf.Tensor2D>(fc1, params.prelu5_alpha)\r\n    const fc2_1 = fullyConnectedLayer(prelu5, params.fc2_1)\r\n    const max = tf.expandDims(tf.max(fc2_1, 1), 1)\r\n\r\n    const prob = tf.softmax(tf.sub(fc2_1, max), 1) as tf.Tensor2D\r\n    const regions = fullyConnectedLayer(prelu5, params.fc2_2)\r\n    const points = fullyConnectedLayer(prelu5, params.fc2_3)\r\n\r\n    const scores = tf.unstack(prob, 1)[1] as tf.Tensor1D\r\n    return { scores, regions, points }\r\n  })\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { BoundingBox, Box, Point } from '../classes';\r\nimport { nonMaxSuppression } from '../ops';\r\nimport { extractImagePatches } from './extractImagePatches';\r\nimport { MtcnnBox } from './MtcnnBox';\r\nimport { ONet } from './ONet';\r\nimport { ONetParams } from './types';\r\n\r\nexport async function stage3(\r\n  img: HTMLCanvasElement,\r\n  inputBoxes: BoundingBox[],\r\n  scoreThreshold: number,\r\n  params: ONetParams,\r\n  stats: any\r\n) {\r\n\r\n  let ts = Date.now()\r\n  const onetInputs = await extractImagePatches(img, inputBoxes, { width: 48, height: 48 })\r\n  stats.stage3_extractImagePatches = Date.now() - ts\r\n\r\n  ts = Date.now()\r\n  const onetOuts = onetInputs.map(\r\n    onetInput => {\r\n      const out = ONet(onetInput, params)\r\n      onetInput.dispose()\r\n      return out\r\n    }\r\n  )\r\n  stats.stage3_onet = Date.now() - ts\r\n\r\n  const scoresTensor = onetOuts.length > 1\r\n    ? tf.concat(onetOuts.map(out => out.scores))\r\n    : onetOuts[0].scores\r\n  const scores = Array.from(await scoresTensor.data())\r\n  scoresTensor.dispose()\r\n\r\n  const indices = scores\r\n    .map((score, idx) => ({ score, idx }))\r\n    .filter(c => c.score > scoreThreshold)\r\n    .map(({ idx }) => idx)\r\n\r\n  const filteredRegions = indices.map(idx => {\r\n    const regionsData = onetOuts[idx].regions.arraySync();\r\n    return new MtcnnBox(\r\n      regionsData[0][0],\r\n      regionsData[0][1],\r\n      regionsData[0][2],\r\n      regionsData[0][3]\r\n  )})\r\n  const filteredBoxes = indices\r\n    .map((idx, i) => inputBoxes[idx].calibrate(filteredRegions[i]))\r\n  const filteredScores = indices.map(idx => scores[idx])\r\n\r\n  let finalBoxes: Box[] = []\r\n  let finalScores: number[] = []\r\n  let points: Point[][] = []\r\n\r\n  if (filteredBoxes.length > 0) {\r\n\r\n    ts = Date.now()\r\n    const indicesNms = nonMaxSuppression(\r\n      filteredBoxes,\r\n      filteredScores,\r\n      0.7,\r\n      false\r\n    )\r\n    stats.stage3_nms = Date.now() - ts\r\n\r\n    finalBoxes = indicesNms.map(idx => filteredBoxes[idx])\r\n    finalScores = indicesNms.map(idx => filteredScores[idx])\r\n    points = indicesNms.map((idx, i) =>\r\n      Array(5).fill(0).map((_, ptIdx) =>{\r\n          const pointsData = onetOuts[idx].points.arraySync()\r\n          return new Point(\r\n            ((pointsData[0][ptIdx] * (finalBoxes[i].width + 1)) + finalBoxes[i].left) ,\r\n            ((pointsData[0][ptIdx+5] * (finalBoxes[i].height + 1)) + finalBoxes[i].top)\r\n          )\r\n        }\r\n      )\r\n    )\r\n  }\r\n\r\n  onetOuts.forEach(t => {\r\n    t.regions.dispose()\r\n    t.scores.dispose()\r\n    t.points.dispose()\r\n  })\r\n\r\n  return {\r\n    boxes: finalBoxes,\r\n    scores: finalScores,\r\n    points\r\n  }\r\n\r\n}\r\n","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { Point, Rect } from '../classes';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { FaceLandmarks5 } from '../classes/FaceLandmarks5';\r\nimport { NetInput, TNetInput, toNetInput } from '../dom';\r\nimport { extendWithFaceDetection, extendWithFaceLandmarks } from '../factories';\r\nimport { NeuralNetwork } from '../NeuralNetwork';\r\nimport { bgrToRgbTensor } from './bgrToRgbTensor';\r\nimport { CELL_SIZE } from './config';\r\nimport { extractParams } from './extractParams';\r\nimport { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';\r\nimport { getSizesForScale } from './getSizesForScale';\r\nimport { IMtcnnOptions, MtcnnOptions } from './MtcnnOptions';\r\nimport { pyramidDown } from './pyramidDown';\r\nimport { stage1 } from './stage1';\r\nimport { stage2 } from './stage2';\r\nimport { stage3 } from './stage3';\r\nimport { MtcnnResult, NetParams } from './types';\r\n\r\nexport class Mtcnn extends NeuralNetwork<NetParams> {\r\n\r\n  constructor() {\r\n    super('Mtcnn')\r\n  }\r\n\r\n  public async load(weightsOrUrl: Float32Array | string | undefined): Promise<void> {\r\n    console.warn('mtcnn is deprecated and will be removed soon')\r\n    return super.load(weightsOrUrl)\r\n  }\r\n\r\n  public async loadFromDisk(filePath: string | undefined) {\r\n    console.warn('mtcnn is deprecated and will be removed soon')\r\n    return super.loadFromDisk(filePath)\r\n  }\r\n\r\n  public async forwardInput(\r\n    input: NetInput,\r\n    forwardParams: IMtcnnOptions = {}\r\n  ): Promise<{ results: MtcnnResult[], stats: any }> {\r\n\r\n    const { params } = this\r\n\r\n    if (!params) {\r\n      throw new Error('Mtcnn - load model before inference')\r\n    }\r\n\r\n    const inputCanvas = input.canvases[0]\r\n\r\n    if (!inputCanvas) {\r\n      throw new Error('Mtcnn - inputCanvas is not defined, note that passing tensors into Mtcnn.forwardInput is not supported yet.')\r\n    }\r\n\r\n    const stats: any = {}\r\n\r\n    const tsTotal = Date.now()\r\n\r\n    const imgTensor = tf.tidy(() =>\r\n      bgrToRgbTensor(\r\n        tf.expandDims(tf.browser.fromPixels(inputCanvas)).toFloat() as tf.Tensor4D\r\n      )\r\n    )\r\n\r\n    const onReturn = (results: any) => {\r\n      // dispose tensors on return\r\n      imgTensor.dispose()\r\n      stats.total = Date.now() - tsTotal\r\n      return results\r\n    }\r\n\r\n    const [height, width] = imgTensor.shape.slice(1)\r\n\r\n    const {\r\n      minFaceSize,\r\n      scaleFactor,\r\n      maxNumScales,\r\n      scoreThresholds,\r\n      scaleSteps\r\n    } = new MtcnnOptions(forwardParams)\r\n\r\n    const scales = (scaleSteps || pyramidDown(minFaceSize, scaleFactor, [height, width]))\r\n      .filter(scale => {\r\n        const sizes = getSizesForScale(scale, [height, width])\r\n        return Math.min(sizes.width, sizes.height) > CELL_SIZE\r\n      })\r\n      .slice(0, maxNumScales)\r\n\r\n    stats.scales = scales\r\n    stats.pyramid = scales.map(scale => getSizesForScale(scale, [height, width]))\r\n\r\n    let ts = Date.now()\r\n    const out1 = await stage1(imgTensor, scales, scoreThresholds[0], params.pnet, stats)\r\n    stats.total_stage1 = Date.now() - ts\r\n\r\n    if (!out1.boxes.length) {\r\n      return onReturn({ results: [], stats })\r\n    }\r\n\r\n    stats.stage2_numInputBoxes = out1.boxes.length\r\n    // using the inputCanvas to extract and resize the image patches, since it is faster\r\n    // than doing this on the gpu\r\n    ts = Date.now()\r\n    const out2 = await stage2(inputCanvas, out1.boxes, scoreThresholds[1], params.rnet, stats)\r\n    stats.total_stage2 = Date.now() - ts\r\n\r\n    if (!out2.boxes.length) {\r\n      return onReturn({ results: [], stats })\r\n    }\r\n\r\n    stats.stage3_numInputBoxes = out2.boxes.length\r\n\r\n    ts = Date.now()\r\n    const out3 = await stage3(inputCanvas, out2.boxes, scoreThresholds[2], params.onet, stats)\r\n    stats.total_stage3 = Date.now() - ts\r\n\r\n    const results = out3.boxes.map((box, idx) => extendWithFaceLandmarks(\r\n      extendWithFaceDetection<{}>(\r\n        {},\r\n        new FaceDetection(\r\n          out3.scores[idx],\r\n          new Rect(\r\n            box.left / width,\r\n            box.top / height,\r\n            box.width / width,\r\n            box.height / height\r\n          ),\r\n          {\r\n            height,\r\n            width\r\n          }\r\n        )\r\n      ),\r\n      new FaceLandmarks5(\r\n        out3.points[idx].map(pt => pt.sub(new Point(box.left, box.top)).div(new Point(box.width, box.height))),\r\n        { width: box.width, height: box.height }\r\n      )\r\n    ))\r\n\r\n    return onReturn({ results, stats })\r\n  }\r\n\r\n  public async forward(\r\n    input: TNetInput,\r\n    forwardParams: IMtcnnOptions = {}\r\n  ): Promise<MtcnnResult[]> {\r\n    return (\r\n      await this.forwardInput(\r\n        await toNetInput(input),\r\n        forwardParams\r\n      )\r\n    ).results\r\n  }\r\n\r\n  public async forwardWithStats(\r\n    input: TNetInput,\r\n    forwardParams: IMtcnnOptions = {}\r\n  ): Promise<{ results: MtcnnResult[], stats: any }> {\r\n    return this.forwardInput(\r\n      await toNetInput(input),\r\n      forwardParams\r\n    )\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'mtcnn_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {\r\n    return extractParamsFromWeigthMap(weightMap)\r\n  }\r\n\r\n  protected extractParams(weights: Float32Array) {\r\n    return extractParams(weights)\r\n  }\r\n}","import { Point } from '../classes'\r\n\r\nexport const IOU_THRESHOLD = 0.4\r\n\r\nexport const BOX_ANCHORS = [\r\n  new Point(1.603231, 2.094468),\r\n  new Point(6.041143, 7.080126),\r\n  new Point(2.882459, 3.518061),\r\n  new Point(4.266906, 5.178857),\r\n  new Point(9.041765, 10.66308)\r\n]\r\n\r\nexport const MEAN_RGB: [number, number, number] = [117.001, 114.697, 97.404]","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FaceDetection, Point } from '../classes';\r\nimport { ParamMapping } from '../common';\r\nimport { TNetInput } from '../dom';\r\nimport { ITinyYolov2Options } from '../tinyYolov2';\r\nimport { TinyYolov2Base } from '../tinyYolov2/TinyYolov2Base';\r\nimport { TinyYolov2NetParams } from '../tinyYolov2/types';\r\nimport { BOX_ANCHORS, IOU_THRESHOLD, MEAN_RGB } from './const';\r\n\r\nexport class TinyFaceDetector extends TinyYolov2Base {\r\n\r\n  constructor() {\r\n    const config = {\r\n      withSeparableConvs: true,\r\n      iouThreshold: IOU_THRESHOLD,\r\n      classes: ['face'],\r\n      anchors: BOX_ANCHORS,\r\n      meanRgb: MEAN_RGB,\r\n      isFirstLayerConv2d: true,\r\n      filterSizes: [3, 16, 32, 64, 128, 256, 512]\r\n    }\r\n\r\n    super(config)\r\n  }\r\n\r\n  public get anchors(): Point[] {\r\n    return this.config.anchors\r\n  }\r\n\r\n  public async locateFaces(input: TNetInput, forwardParams: ITinyYolov2Options): Promise<FaceDetection[]> {\r\n    const objectDetections = await this.detect(input, forwardParams)\r\n    return objectDetections.map(det => new FaceDetection(det.score, det.relativeBox, { width: det.imageWidth, height: det.imageHeight }))\r\n  }\r\n\r\n  protected getDefaultModelName(): string {\r\n    return 'tiny_face_detector_model'\r\n  }\r\n\r\n  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {\r\n    return super.extractParamsFromWeigthMap(weightMap)\r\n  }\r\n}","import { AgeGenderNet } from '../ageGenderNet/AgeGenderNet';\r\nimport { AgeAndGenderPrediction } from '../ageGenderNet/types';\r\nimport { FaceDetection } from '../classes/FaceDetection';\r\nimport { FaceLandmarks5 } from '../classes/FaceLandmarks5';\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { TNetInput } from '../dom';\r\nimport { FaceExpressionNet } from '../faceExpressionNet/FaceExpressionNet';\r\nimport { FaceExpressions } from '../faceExpressionNet/FaceExpressions';\r\nimport { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';\r\nimport { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';\r\nimport { FaceRecognitionNet } from '../faceRecognitionNet/FaceRecognitionNet';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { Mtcnn } from '../mtcnn/Mtcnn';\r\nimport { MtcnnOptions } from '../mtcnn/MtcnnOptions';\r\nimport { SsdMobilenetv1 } from '../ssdMobilenetv1/SsdMobilenetv1';\r\nimport { SsdMobilenetv1Options } from '../ssdMobilenetv1/SsdMobilenetv1Options';\r\nimport { TinyFaceDetector } from '../tinyFaceDetector/TinyFaceDetector';\r\nimport { TinyFaceDetectorOptions } from '../tinyFaceDetector/TinyFaceDetectorOptions';\r\nimport { ITinyYolov2Options, TinyYolov2 } from '../tinyYolov2';\r\n\r\nexport const nets = {\r\n  ssdMobilenetv1: new SsdMobilenetv1(),\r\n  tinyFaceDetector: new TinyFaceDetector(),\r\n  tinyYolov2: new TinyYolov2(),\r\n  mtcnn: new Mtcnn(),\r\n  faceLandmark68Net: new FaceLandmark68Net(),\r\n  faceLandmark68TinyNet: new FaceLandmark68TinyNet(),\r\n  faceRecognitionNet: new FaceRecognitionNet(),\r\n  faceExpressionNet: new FaceExpressionNet(),\r\n  ageGenderNet: new AgeGenderNet()\r\n}\r\n\r\n/**\r\n * Attempts to detect all faces in an image using SSD Mobilenetv1 Network.\r\n *\r\n * @param input The input image.\r\n * @param options (optional, default: see SsdMobilenetv1Options constructor for default parameters).\r\n * @returns Bounding box of each face with score.\r\n */\r\nexport const ssdMobilenetv1 = (input: TNetInput, options: SsdMobilenetv1Options): Promise<FaceDetection[]> =>\r\n  nets.ssdMobilenetv1.locateFaces(input, options)\r\n\r\n/**\r\n * Attempts to detect all faces in an image using the Tiny Face Detector.\r\n *\r\n * @param input The input image.\r\n * @param options (optional, default: see TinyFaceDetectorOptions constructor for default parameters).\r\n * @returns Bounding box of each face with score.\r\n */\r\nexport const tinyFaceDetector = (input: TNetInput, options: TinyFaceDetectorOptions): Promise<FaceDetection[]> =>\r\n  nets.tinyFaceDetector.locateFaces(input, options)\r\n\r\n/**\r\n * Attempts to detect all faces in an image using the Tiny Yolov2 Network.\r\n *\r\n * @param input The input image.\r\n * @param options (optional, default: see TinyYolov2Options constructor for default parameters).\r\n * @returns Bounding box of each face with score.\r\n */\r\nexport const tinyYolov2 = (input: TNetInput, options: ITinyYolov2Options): Promise<FaceDetection[]> =>\r\n  nets.tinyYolov2.locateFaces(input, options)\r\n\r\n/**\r\n * Attempts to detect all faces in an image and the 5 point face landmarks\r\n * of each detected face using the MTCNN Network.\r\n *\r\n * @param input The input image.\r\n * @param options (optional, default: see MtcnnOptions constructor for default parameters).\r\n * @returns Bounding box of each face with score and 5 point face landmarks.\r\n */\r\nexport const mtcnn = (input: TNetInput, options: MtcnnOptions): Promise<WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks5>[]> =>\r\n  nets.mtcnn.forward(input, options)\r\n\r\n/**\r\n * Detects the 68 point face landmark positions of the face shown in an image.\r\n *\r\n * @param inputs The face image extracted from the bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns 68 point face landmarks or array thereof in case of batch input.\r\n */\r\nexport const detectFaceLandmarks = (input: TNetInput): Promise<FaceLandmarks68 | FaceLandmarks68[]> =>\r\n  nets.faceLandmark68Net.detectLandmarks(input)\r\n\r\n/**\r\n * Detects the 68 point face landmark positions of the face shown in an image\r\n * using a tinier version of the 68 point face landmark model, which is slightly\r\n * faster at inference, but also slightly less accurate.\r\n *\r\n * @param inputs The face image extracted from the bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns 68 point face landmarks or array thereof in case of batch input.\r\n */\r\nexport const detectFaceLandmarksTiny = (input: TNetInput): Promise<FaceLandmarks68 | FaceLandmarks68[]>  =>\r\n  nets.faceLandmark68TinyNet.detectLandmarks(input)\r\n\r\n/**\r\n * Computes a 128 entry vector (face descriptor / face embeddings) from the face shown in an image,\r\n * which uniquely represents the features of that persons face. The computed face descriptor can\r\n * be used to measure the similarity between faces, by computing the euclidean distance of two\r\n * face descriptors.\r\n *\r\n * @param inputs The face image extracted from the aligned bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns Face descriptor with 128 entries or array thereof in case of batch input.\r\n */\r\nexport const computeFaceDescriptor = (input: TNetInput): Promise<Float32Array | Float32Array[]>  =>\r\n  nets.faceRecognitionNet.computeFaceDescriptor(input)\r\n\r\n\r\n/**\r\n * Recognizes the facial expressions from a face image.\r\n *\r\n * @param inputs The face image extracted from the bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns Facial expressions with corresponding probabilities or array thereof in case of batch input.\r\n */\r\nexport const recognizeFaceExpressions = (input: TNetInput): Promise<FaceExpressions | FaceExpressions[]> =>\r\n  nets.faceExpressionNet.predictExpressions(input)\r\n\r\n/**\r\n * Predicts age and gender from a face image.\r\n *\r\n * @param inputs The face image extracted from the bounding box of a face. Can\r\n * also be an array of input images, which will be batch processed.\r\n * @returns Predictions with age, gender and gender probability or array thereof in case of batch input.\r\n */\r\nexport const predictAgeAndGender = (input: TNetInput): Promise<AgeAndGenderPrediction | AgeAndGenderPrediction[]> =>\r\n  nets.ageGenderNet.predictAgeAndGender(input)\r\n\r\nexport const loadSsdMobilenetv1Model = (url: string) => nets.ssdMobilenetv1.load(url)\r\nexport const loadTinyFaceDetectorModel = (url: string) => nets.tinyFaceDetector.load(url)\r\nexport const loadMtcnnModel = (url: string) => nets.mtcnn.load(url)\r\nexport const loadTinyYolov2Model = (url: string) => nets.tinyYolov2.load(url)\r\nexport const loadFaceLandmarkModel = (url: string) => nets.faceLandmark68Net.load(url)\r\nexport const loadFaceLandmarkTinyModel = (url: string) => nets.faceLandmark68TinyNet.load(url)\r\nexport const loadFaceRecognitionModel = (url: string) => nets.faceRecognitionNet.load(url)\r\nexport const loadFaceExpressionModel = (url: string) => nets.faceExpressionNet.load(url)\r\nexport const loadAgeGenderModel = (url: string) => nets.ageGenderNet.load(url)\r\n\r\n// backward compatibility\r\nexport const loadFaceDetectionModel = loadSsdMobilenetv1Model\r\nexport const locateFaces = ssdMobilenetv1\r\nexport const detectLandmarks = detectFaceLandmarks","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { TNetInput } from '../dom';\r\nimport { FaceExpressions } from '../faceExpressionNet/FaceExpressions';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { extendWithFaceExpressions, WithFaceExpressions } from '../factories/WithFaceExpressions';\r\nimport { WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';\r\nimport { extractAllFacesAndComputeResults, extractSingleFaceAndComputeResult } from './extractFacesAndComputeResults';\r\nimport { nets } from './nets';\r\nimport {\r\n  PredictAllAgeAndGenderTask,\r\n  PredictAllAgeAndGenderWithFaceAlignmentTask,\r\n  PredictSingleAgeAndGenderTask,\r\n  PredictSingleAgeAndGenderWithFaceAlignmentTask,\r\n} from './PredictAgeAndGenderTask';\r\n\r\nexport class PredictFaceExpressionsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>,\r\n    protected input: TNetInput,\r\n    protected extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D>\r\n  ) {\r\n    super()\r\n  }\r\n}\r\n\r\nexport class PredictAllFaceExpressionsTask<\r\n  TSource extends WithFaceDetection<{}>\r\n> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource>[], TSource[]> {\r\n\r\n  public async run(): Promise<WithFaceExpressions<TSource>[]> {\r\n\r\n    const parentResults = await this.parentTask\r\n\r\n    const faceExpressionsByFace = await extractAllFacesAndComputeResults<TSource, FaceExpressions[]>(\r\n      parentResults,\r\n      this.input,\r\n      async faces => await Promise.all(faces.map(\r\n        face => nets.faceExpressionNet.predictExpressions(face) as Promise<FaceExpressions>\r\n      )),\r\n      this.extractedFaces\r\n    )\r\n\r\n    return parentResults.map(\r\n      (parentResult, i) => extendWithFaceExpressions<TSource>(parentResult, faceExpressionsByFace[i])\r\n    )\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictSingleFaceExpressionsTask<\r\n  TSource extends WithFaceDetection<{}>\r\n>  extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource> | undefined, TSource | undefined> {\r\n\r\n  public async run(): Promise<WithFaceExpressions<TSource> | undefined> {\r\n\r\n    const parentResult = await this.parentTask\r\n    if (!parentResult) {\r\n      return\r\n    }\r\n\r\n    const faceExpressions = await extractSingleFaceAndComputeResult<TSource, FaceExpressions>(\r\n      parentResult,\r\n      this.input,\r\n      face => nets.faceExpressionNet.predictExpressions(face) as Promise<FaceExpressions>,\r\n      this.extractedFaces\r\n    )\r\n\r\n    return extendWithFaceExpressions(parentResult, faceExpressions)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictAllFaceExpressionsWithFaceAlignmentTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends PredictAllFaceExpressionsTask<TSource> {\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptors() {\r\n    return new ComputeAllFaceDescriptorsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictSingleFaceExpressionsWithFaceAlignmentTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends PredictSingleFaceExpressionsTask<TSource> {\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptor() {\r\n    return new ComputeSingleFaceDescriptorTask(this, this.input)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { AgeAndGenderPrediction } from '../ageGenderNet/types';\r\nimport { TNetInput } from '../dom';\r\nimport { extendWithAge, WithAge } from '../factories/WithAge';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { extendWithGender, WithGender } from '../factories/WithGender';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';\r\nimport { extractAllFacesAndComputeResults, extractSingleFaceAndComputeResult } from './extractFacesAndComputeResults';\r\nimport { nets } from './nets';\r\nimport {\r\n  PredictAllFaceExpressionsTask,\r\n  PredictAllFaceExpressionsWithFaceAlignmentTask,\r\n  PredictSingleFaceExpressionsTask,\r\n  PredictSingleFaceExpressionsWithFaceAlignmentTask,\r\n} from './PredictFaceExpressionsTask';\r\n\r\nexport class PredictAgeAndGenderTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>,\r\n    protected input: TNetInput,\r\n    protected extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D>\r\n  ) {\r\n    super()\r\n  }\r\n}\r\n\r\nexport class PredictAllAgeAndGenderTask<\r\n  TSource extends WithFaceDetection<{}>\r\n> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>>[], TSource[]> {\r\n\r\n  public async run(): Promise<WithAge<WithGender<TSource>>[]> {\r\n\r\n    const parentResults = await this.parentTask\r\n\r\n    const ageAndGenderByFace = await extractAllFacesAndComputeResults<TSource, AgeAndGenderPrediction[]>(\r\n      parentResults,\r\n      this.input,\r\n      async faces => await Promise.all(faces.map(\r\n        face => nets.ageGenderNet.predictAgeAndGender(face) as Promise<AgeAndGenderPrediction>\r\n      )),\r\n      this.extractedFaces\r\n    )\r\n\r\n    return parentResults.map((parentResult, i) => {\r\n      const { age, gender, genderProbability } = ageAndGenderByFace[i]\r\n      return extendWithAge(extendWithGender(parentResult, gender, genderProbability), age)\r\n    })\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictSingleAgeAndGenderTask<\r\n  TSource extends WithFaceDetection<{}>\r\n>  extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>> | undefined, TSource | undefined> {\r\n\r\n  public async run(): Promise<WithAge<WithGender<TSource>> | undefined> {\r\n\r\n    const parentResult = await this.parentTask\r\n    if (!parentResult) {\r\n      return\r\n    }\r\n\r\n    const { age, gender, genderProbability } = await extractSingleFaceAndComputeResult<TSource, AgeAndGenderPrediction>(\r\n      parentResult,\r\n      this.input,\r\n      face => nets.ageGenderNet.predictAgeAndGender(face) as Promise<AgeAndGenderPrediction>,\r\n      this.extractedFaces\r\n    )\r\n\r\n    return extendWithAge(extendWithGender(parentResult, gender, genderProbability), age)\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictAllAgeAndGenderWithFaceAlignmentTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends PredictAllAgeAndGenderTask<TSource> {\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptors() {\r\n    return new ComputeAllFaceDescriptorsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class PredictSingleAgeAndGenderWithFaceAlignmentTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends PredictSingleAgeAndGenderTask<TSource> {\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptor() {\r\n    return new ComputeSingleFaceDescriptorTask(this, this.input)\r\n  }\r\n}","import { TNetInput } from '../dom';\r\nimport { extendWithFaceDescriptor, WithFaceDescriptor } from '../factories/WithFaceDescriptor';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { extractAllFacesAndComputeResults, extractSingleFaceAndComputeResult } from './extractFacesAndComputeResults';\r\nimport { nets } from './nets';\r\nimport {\r\n  PredictAllAgeAndGenderWithFaceAlignmentTask,\r\n  PredictSingleAgeAndGenderWithFaceAlignmentTask,\r\n} from './PredictAgeAndGenderTask';\r\nimport {\r\n  PredictAllFaceExpressionsWithFaceAlignmentTask,\r\n  PredictSingleFaceExpressionsWithFaceAlignmentTask,\r\n} from './PredictFaceExpressionsTask';\r\n\r\nexport class ComputeFaceDescriptorsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>,\r\n    protected input: TNetInput\r\n  ) {\r\n    super()\r\n  }\r\n}\r\n\r\nexport class ComputeAllFaceDescriptorsTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource>[], TSource[]> {\r\n\r\n  public async run(): Promise<WithFaceDescriptor<TSource>[]> {\r\n\r\n    const parentResults = await this.parentTask\r\n\r\n    const descriptors = await extractAllFacesAndComputeResults<TSource, Float32Array[]>(\r\n      parentResults,\r\n      this.input,\r\n      faces => Promise.all(faces.map(face =>\r\n        nets.faceRecognitionNet.computeFaceDescriptor(face) as Promise<Float32Array>\r\n      )),\r\n      null,\r\n      parentResult => parentResult.landmarks.align(null, { useDlibAlignment: true })\r\n    )\r\n\r\n    return descriptors.map((descriptor, i) => extendWithFaceDescriptor<TSource>(parentResults[i], descriptor))\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class ComputeSingleFaceDescriptorTask<\r\n  TSource extends WithFaceLandmarks<WithFaceDetection<{}>>\r\n> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource> | undefined, TSource | undefined> {\r\n\r\n  public async run(): Promise<WithFaceDescriptor<TSource> | undefined> {\r\n\r\n    const parentResult = await this.parentTask\r\n    if (!parentResult) {\r\n      return\r\n    }\r\n    const descriptor = await extractSingleFaceAndComputeResult<TSource, Float32Array>(\r\n      parentResult,\r\n      this.input,\r\n      face => nets.faceRecognitionNet.computeFaceDescriptor(face) as Promise<Float32Array>,\r\n      null,\r\n      parentResult => parentResult.landmarks.align(null, { useDlibAlignment: true })\r\n    )\r\n\r\n    return extendWithFaceDescriptor(parentResult, descriptor)\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n}","import * as tf from '@tensorflow/tfjs-core';\r\n\r\nimport { FaceLandmarks68 } from '../classes/FaceLandmarks68';\r\nimport { extractFaces, extractFaceTensors, TNetInput } from '../dom';\r\nimport { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';\r\nimport { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';\r\nimport { WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { extendWithFaceLandmarks, WithFaceLandmarks } from '../factories/WithFaceLandmarks';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';\r\nimport { nets } from './nets';\r\nimport {\r\n  PredictAllAgeAndGenderWithFaceAlignmentTask,\r\n  PredictSingleAgeAndGenderWithFaceAlignmentTask,\r\n} from './PredictAgeAndGenderTask';\r\nimport {\r\n  PredictAllFaceExpressionsWithFaceAlignmentTask,\r\n  PredictSingleFaceExpressionsWithFaceAlignmentTask,\r\n} from './PredictFaceExpressionsTask';\r\n\r\nexport class DetectFaceLandmarksTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>,\r\n    protected input: TNetInput,\r\n    protected useTinyLandmarkNet: boolean\r\n  ) {\r\n    super()\r\n  }\r\n\r\n  protected get landmarkNet(): FaceLandmark68Net | FaceLandmark68TinyNet {\r\n    return this.useTinyLandmarkNet\r\n      ? nets.faceLandmark68TinyNet\r\n      : nets.faceLandmark68Net\r\n  }\r\n}\r\n\r\nexport class DetectAllFaceLandmarksTask<\r\n  TSource extends WithFaceDetection<{}>\r\n> extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource>[], TSource[]> {\r\n\r\n  public async run(): Promise<WithFaceLandmarks<TSource>[]> {\r\n\r\n    const parentResults = await this.parentTask\r\n    const detections = parentResults.map(res => res.detection)\r\n\r\n    const faces: Array<HTMLCanvasElement | tf.Tensor3D> = this.input instanceof tf.Tensor\r\n      ? await extractFaceTensors(this.input, detections)\r\n      : await extractFaces(this.input, detections)\r\n\r\n    const faceLandmarksByFace = await Promise.all(faces.map(\r\n      face => this.landmarkNet.detectLandmarks(face)\r\n    )) as FaceLandmarks68[]\r\n\r\n    faces.forEach(f => f instanceof tf.Tensor && f.dispose())\r\n\r\n    return parentResults.map((parentResult, i) =>\r\n      extendWithFaceLandmarks<TSource>(parentResult, faceLandmarksByFace[i])\r\n    )\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptors() {\r\n    return new ComputeAllFaceDescriptorsTask(this, this.input)\r\n  }\r\n}\r\n\r\nexport class DetectSingleFaceLandmarksTask<\r\n  TSource extends WithFaceDetection<{}>\r\n>  extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource> | undefined, TSource | undefined> {\r\n\r\n  public async run(): Promise<WithFaceLandmarks<TSource> | undefined> {\r\n\r\n    const parentResult = await this.parentTask\r\n    if (!parentResult) {\r\n      return\r\n    }\r\n\r\n    const { detection } = parentResult\r\n    const faces: Array<HTMLCanvasElement | tf.Tensor3D> = this.input instanceof tf.Tensor\r\n      ? await extractFaceTensors(this.input, [detection])\r\n      : await extractFaces(this.input, [detection])\r\n\r\n    const landmarks = await this.landmarkNet.detectLandmarks(faces[0]) as FaceLandmarks68\r\n\r\n    faces.forEach(f => f instanceof tf.Tensor && f.dispose())\r\n\r\n    return extendWithFaceLandmarks<TSource>(parentResult, landmarks)\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input)\r\n  }\r\n\r\n  withFaceDescriptor() {\r\n    return new ComputeSingleFaceDescriptorTask(this, this.input)\r\n  }\r\n}","import { FaceDetection } from '../classes/FaceDetection';\r\nimport { TNetInput } from '../dom';\r\nimport { extendWithFaceDetection, WithFaceDetection } from '../factories/WithFaceDetection';\r\nimport { MtcnnOptions } from '../mtcnn/MtcnnOptions';\r\nimport { SsdMobilenetv1Options } from '../ssdMobilenetv1/SsdMobilenetv1Options';\r\nimport { TinyFaceDetectorOptions } from '../tinyFaceDetector/TinyFaceDetectorOptions';\r\nimport { TinyYolov2Options } from '../tinyYolov2';\r\nimport { ComposableTask } from './ComposableTask';\r\nimport { DetectAllFaceLandmarksTask, DetectSingleFaceLandmarksTask } from './DetectFaceLandmarksTasks';\r\nimport { nets } from './nets';\r\nimport { PredictAllAgeAndGenderTask, PredictSingleAgeAndGenderTask } from './PredictAgeAndGenderTask';\r\nimport { PredictAllFaceExpressionsTask, PredictSingleFaceExpressionsTask } from './PredictFaceExpressionsTask';\r\nimport { FaceDetectionOptions } from './types';\r\n\r\nexport class DetectFacesTaskBase<TReturn> extends ComposableTask<TReturn> {\r\n  constructor(\r\n    protected input: TNetInput,\r\n    protected options: FaceDetectionOptions = new SsdMobilenetv1Options()\r\n  ) {\r\n    super()\r\n  }\r\n}\r\n\r\nexport class DetectAllFacesTask extends DetectFacesTaskBase<FaceDetection[]> {\r\n\r\n  public async run(): Promise<FaceDetection[]> {\r\n\r\n    const { input, options } = this\r\n\r\n    if (options instanceof MtcnnOptions) {\r\n      return (await nets.mtcnn.forward(input, options))\r\n        .map(result => result.detection)\r\n    }\r\n\r\n    const faceDetectionFunction = options instanceof TinyFaceDetectorOptions\r\n      ? (input: TNetInput) => nets.tinyFaceDetector.locateFaces(input, options)\r\n      : (\r\n        options instanceof SsdMobilenetv1Options\r\n          ? (input: TNetInput) => nets.ssdMobilenetv1.locateFaces(input, options)\r\n          : (\r\n            options instanceof TinyYolov2Options\r\n              ? (input: TNetInput) => nets.tinyYolov2.locateFaces(input, options)\r\n              : null\r\n          )\r\n      )\r\n\r\n    if (!faceDetectionFunction) {\r\n      throw new Error('detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | MtcnnOptions | TinyYolov2Options')\r\n    }\r\n\r\n    return faceDetectionFunction(input)\r\n  }\r\n\r\n  private runAndExtendWithFaceDetections(): Promise<WithFaceDetection<{}>[]> {\r\n    return new Promise<WithFaceDetection<{}>[]>(async res => {\r\n      const detections = await this.run()\r\n      return res(detections.map(detection => extendWithFaceDetection({}, detection)))\r\n    })\r\n  }\r\n\r\n  withFaceLandmarks(useTinyLandmarkNet: boolean = false) {\r\n    return new DetectAllFaceLandmarksTask(\r\n      this.runAndExtendWithFaceDetections(),\r\n      this.input,\r\n      useTinyLandmarkNet\r\n    )\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictAllFaceExpressionsTask (\r\n      this.runAndExtendWithFaceDetections(),\r\n      this.input\r\n    )\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictAllAgeAndGenderTask(\r\n      this.runAndExtendWithFaceDetections(),\r\n      this.input\r\n    )\r\n  }\r\n}\r\n\r\nexport class DetectSingleFaceTask extends DetectFacesTaskBase<FaceDetection | undefined> {\r\n\r\n  public async run(): Promise<FaceDetection | undefined> {\r\n    const faceDetections = await new DetectAllFacesTask(this.input, this.options);\r\n    let faceDetectionWithHighestScore = faceDetections[0];\r\n    faceDetections.forEach(faceDetection => {\r\n      if (faceDetection.score > faceDetectionWithHighestScore.score) {\r\n        faceDetectionWithHighestScore = faceDetection;\r\n      }\r\n    });\r\n    return faceDetectionWithHighestScore;\r\n  }\r\n\r\n  private runAndExtendWithFaceDetection(): Promise<WithFaceDetection<{}>> {\r\n    return new Promise<WithFaceDetection<{}>>(async res => {\r\n      const detection = await this.run()\r\n      return res(detection ? extendWithFaceDetection<{}>({}, detection) : undefined)\r\n    })\r\n  }\r\n\r\n  withFaceLandmarks(useTinyLandmarkNet: boolean = false) {\r\n    return new DetectSingleFaceLandmarksTask(\r\n      this.runAndExtendWithFaceDetection(),\r\n      this.input,\r\n      useTinyLandmarkNet\r\n    )\r\n  }\r\n\r\n  withFaceExpressions() {\r\n    return new PredictSingleFaceExpressionsTask(\r\n      this.runAndExtendWithFaceDetection(),\r\n      this.input\r\n    )\r\n  }\r\n\r\n  withAgeAndGender() {\r\n    return new PredictSingleAgeAndGenderTask(\r\n      this.runAndExtendWithFaceDetection(),\r\n      this.input\r\n    )\r\n  }\r\n}","import { TNetInput } from '../dom';\r\nimport { SsdMobilenetv1Options } from '../ssdMobilenetv1/SsdMobilenetv1Options';\r\nimport { DetectAllFacesTask, DetectSingleFaceTask } from './DetectFacesTasks';\r\nimport { FaceDetectionOptions } from './types';\r\n\r\nexport function detectSingleFace(\r\n  input: TNetInput,\r\n  options: FaceDetectionOptions = new SsdMobilenetv1Options()\r\n): DetectSingleFaceTask {\r\n  return new DetectSingleFaceTask(input, options)\r\n}\r\n\r\nexport function detectAllFaces(\r\n  input: TNetInput,\r\n  options: FaceDetectionOptions = new SsdMobilenetv1Options()\r\n): DetectAllFacesTask {\r\n  return new DetectAllFacesTask(input, options)\r\n}","import { TNetInput } from '../dom';\r\nimport { WithFaceDescriptor, WithFaceDetection, WithFaceLandmarks } from '../factories';\r\nimport { IMtcnnOptions, MtcnnOptions } from '../mtcnn/MtcnnOptions';\r\nimport { SsdMobilenetv1Options } from '../ssdMobilenetv1';\r\nimport { ITinyYolov2Options, TinyYolov2Options } from '../tinyYolov2';\r\nimport { detectAllFaces } from './detectFaces';\r\n\r\n// export allFaces API for backward compatibility\r\n\r\nexport async function allFacesSsdMobilenetv1(\r\n  input: TNetInput,\r\n  minConfidence?: number\r\n): Promise<WithFaceDescriptor<WithFaceLandmarks<WithFaceDetection<{}>>>[]> {\r\n  console.warn('allFacesSsdMobilenetv1 is deprecated and will be removed soon, use the high level api instead')\r\n  return await detectAllFaces(input, new SsdMobilenetv1Options(minConfidence ? { minConfidence } : {}))\r\n    .withFaceLandmarks()\r\n    .withFaceDescriptors()\r\n}\r\n\r\nexport async function allFacesTinyYolov2(\r\n  input: TNetInput,\r\n  forwardParams: ITinyYolov2Options = {}\r\n): Promise<WithFaceDescriptor<WithFaceLandmarks<WithFaceDetection<{}>>>[]> {\r\n  console.warn('allFacesTinyYolov2 is deprecated and will be removed soon, use the high level api instead')\r\n  return await detectAllFaces(input, new TinyYolov2Options(forwardParams))\r\n    .withFaceLandmarks()\r\n    .withFaceDescriptors()\r\n}\r\n\r\nexport async function allFacesMtcnn(\r\n  input: TNetInput,\r\n  forwardParams: IMtcnnOptions = {}\r\n): Promise<WithFaceDescriptor<WithFaceLandmarks<WithFaceDetection<{}>>>[]> {\r\n  console.warn('allFacesMtcnn is deprecated and will be removed soon, use the high level api instead')\r\n  return await detectAllFaces(input, new MtcnnOptions(forwardParams))\r\n    .withFaceLandmarks()\r\n    .withFaceDescriptors()\r\n}\r\n\r\nexport const allFaces = allFacesSsdMobilenetv1\r\n","export function euclideanDistance(arr1: number[] | Float32Array, arr2: number[] | Float32Array) {\r\n  if (arr1.length !== arr2.length)\r\n    throw new Error('euclideanDistance: arr1.length !== arr2.length')\r\n\r\n  const desc1 = Array.from(arr1)\r\n  const desc2 = Array.from(arr2)\r\n\r\n  return Math.sqrt(\r\n    desc1\r\n      .map((val, i) => val - desc2[i])\r\n      .reduce((res, diff) => res + Math.pow(diff, 2), 0)\r\n  )\r\n}","import { FaceMatch } from '../classes/FaceMatch';\r\nimport { LabeledFaceDescriptors } from '../classes/LabeledFaceDescriptors';\r\nimport { euclideanDistance } from '../euclideanDistance';\r\nimport { WithFaceDescriptor } from '../factories';\r\n\r\nexport class FaceMatcher {\r\n\r\n  private _labeledDescriptors: LabeledFaceDescriptors[]\r\n  private _distanceThreshold: number\r\n\r\n  constructor(\r\n    inputs: LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>,\r\n    distanceThreshold: number = 0.6\r\n  ) {\r\n\r\n    this._distanceThreshold = distanceThreshold\r\n\r\n    const inputArray = Array.isArray(inputs) ? inputs : [inputs]\r\n\r\n    if (!inputArray.length) {\r\n      throw new Error(`FaceRecognizer.constructor - expected atleast one input`)\r\n    }\r\n\r\n    let count = 1\r\n    const createUniqueLabel = () => `person ${count++}`\r\n\r\n    this._labeledDescriptors = inputArray.map((desc) => {\r\n      if (desc instanceof LabeledFaceDescriptors) {\r\n        return desc\r\n      }\r\n\r\n      if (desc instanceof Float32Array) {\r\n        return new LabeledFaceDescriptors(createUniqueLabel(), [desc])\r\n      }\r\n\r\n      if (desc.descriptor && desc.descriptor instanceof Float32Array) {\r\n        return new LabeledFaceDescriptors(createUniqueLabel(), [desc.descriptor])\r\n      }\r\n\r\n      throw new Error(`FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>`)\r\n    })\r\n  }\r\n\r\n  public get labeledDescriptors(): LabeledFaceDescriptors[] { return this._labeledDescriptors }\r\n  public get distanceThreshold(): number { return this._distanceThreshold }\r\n\r\n  public computeMeanDistance(queryDescriptor: Float32Array, descriptors: Float32Array[]): number {\r\n    return descriptors\r\n      .map(d => euclideanDistance(d, queryDescriptor))\r\n      .reduce((d1, d2) => d1 + d2, 0)\r\n        / (descriptors.length || 1)\r\n  }\r\n\r\n  public matchDescriptor(queryDescriptor: Float32Array): FaceMatch {\r\n    return this.labeledDescriptors\r\n      .map(({ descriptors, label }) => new FaceMatch(\r\n          label,\r\n          this.computeMeanDistance(queryDescriptor, descriptors)\r\n      ))\r\n      .reduce((best, curr) => best.distance < curr.distance ? best : curr)\r\n  }\r\n\r\n  public findBestMatch(queryDescriptor: Float32Array): FaceMatch {\r\n    const bestMatch = this.matchDescriptor(queryDescriptor)\r\n    return bestMatch.distance < this.distanceThreshold\r\n      ? bestMatch\r\n      : new FaceMatch('unknown', bestMatch.distance)\r\n  }\r\n\r\n  public toJSON(): any {\r\n    return {\r\n      distanceThreshold: this.distanceThreshold,\r\n      labeledDescriptors: this.labeledDescriptors.map((ld) => ld.toJSON())\r\n    };\r\n  }\r\n\r\n  public static fromJSON(json: any): FaceMatcher {\r\n    const labeledDescriptors = json.labeledDescriptors\r\n      .map((ld: any) => LabeledFaceDescriptors.fromJSON(ld));\r\n    return new FaceMatcher(labeledDescriptors, json.distanceThreshold);\r\n  }\r\n\r\n}","import { Mtcnn } from './Mtcnn';\r\n\r\nexport * from './Mtcnn';\r\nexport * from './MtcnnOptions';\r\n\r\nexport function createMtcnn(weights: Float32Array) {\r\n  const net = new Mtcnn()\r\n  net.extractWeights(weights)\r\n  return net\r\n}","import { TinyFaceDetector } from './TinyFaceDetector';\r\n\r\nexport * from './TinyFaceDetector';\r\nexport * from './TinyFaceDetectorOptions';\r\n\r\nexport function createTinyFaceDetector(weights: Float32Array) {\r\n  const net = new TinyFaceDetector()\r\n  net.extractWeights(weights)\r\n  return net\r\n}","import { Dimensions, IDimensions } from './classes';\r\nimport { FaceDetection } from './classes/FaceDetection';\r\nimport { FaceLandmarks } from './classes/FaceLandmarks';\r\nimport { extendWithFaceDetection, isWithFaceDetection } from './factories/WithFaceDetection';\r\nimport { extendWithFaceLandmarks, isWithFaceLandmarks } from './factories/WithFaceLandmarks';\r\n\r\nexport function resizeResults<T>(results: T, dimensions: IDimensions): T {\r\n\r\n  const { width, height } = new Dimensions(dimensions.width, dimensions.height)\r\n\r\n  if (width <= 0 || height <= 0) {\r\n    throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({ width, height })}`)\r\n  }\r\n\r\n  if (Array.isArray(results)) {\r\n    return results.map(obj => resizeResults(obj, { width, height })) as any as T\r\n  }\r\n\r\n  if (isWithFaceLandmarks(results)) {\r\n    const resizedDetection = results.detection.forSize(width, height)\r\n    const resizedLandmarks = results.unshiftedLandmarks.forSize(resizedDetection.box.width, resizedDetection.box.height)\r\n\r\n    return extendWithFaceLandmarks(extendWithFaceDetection(results, resizedDetection), resizedLandmarks)\r\n  }\r\n\r\n  if (isWithFaceDetection(results)) {\r\n    return extendWithFaceDetection(results, results.detection.forSize(width, height))\r\n  }\r\n\r\n  if (results instanceof FaceLandmarks || results instanceof FaceDetection) {\r\n    return (results as any).forSize(width, height)\r\n  }\r\n\r\n  return 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diff --git a/dist/face-api.min.js b/dist/face-api.min.js
index 6ee48a68..93ca07ec 100644
--- a/dist/face-api.min.js
+++ b/dist/face-api.min.js
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t(e,n,r){if(null!=e)if(e instanceof vt)n.push(e);else if(o=e,Array.isArray(o)||"object"==typeof o){var o,i=e;for(var a in i){var s=i[a];r.has(s)||(r.add(s),t(s,n,r))}}}(t,e,new Set),e}var Pt,Bt=Object.freeze({makeTypesMatch:Nt,assertTypesMatch:Mt,isTensorInList:function(t,e){for(var n=0;n<e.length;n++)if(e[n].id===t.id)return!0;return!1},getTensorsInContainer:Ot}),Lt=(Ut.prototype.dispose=function(){for(var t in this.registeredVariables)this.registeredVariables[t].dispose()},Ut),Wt=(zt.prototype.ready=function(){return y(this,void 0,void 0,function(){var e,n,r;return R(this,function(t){switch(t.label){case 0:if(null!=this.pendingBackendInit)return[2,this.pendingBackendInit.then(function(){})];if(null!=this.backendInstance)return[2];e=this.getSortedBackends(),n=0,t.label=1;case 1:return n<e.length?(r=e[n],[4,this.initializeBackend(r).success]):[3,5];case 2:return t.sent()?[4,this.setBackend(r)]:[3,4];case 3:return t.sent(),[2];case 4:return n++,[3,1];case 5:throw new Error("Could not initialize any backends, all backend initializations failed.")}})})},Object.defineProperty(zt.prototype,"backend",{get:function(){if(null!=this.pendingBackendInit)throw new Error("Backend '"+this.backendName+"' has not yet been initialized. Make sure to await tf.ready() before calling other methods");if(null==this.backendInstance){var t=this.initializeBackendsAndReturnBest(),e=t.name;if(t.asyncInit)throw new Error("The highest priority backend '"+e+"' has not yet been initialized. Make sure to await tf.ready() before calling other methods");this.setBackend(e)}return this.backendInstance},enumerable:!0,configurable:!0}),zt.prototype.backendNames=function(){return Object.keys(this.registryFactory)},zt.prototype.findBackend=function(t){if(!(t in this.registry)){if(!(t in this.registryFactory))return null;if(this.initializeBackend(t).asyncInit)return null}return this.registry[t]},zt.prototype.findBackendFactory=function(t){return t in this.registryFactory?this.registryFactory[t].factory:null},zt.prototype.registerBackend=function(t,e,n){return void 0===n&&(n=1),t in this.registryFactory?(console.warn(t+" backend was already registered. Reusing existing backend factory."),!1):(this.registryFactory[t]={factory:e,priority:n},!0)},zt.prototype.setBackend=function(o){return y(this,void 0,void 0,function(){var e,n,r;return R(this,function(t){switch(t.label){case 0:if(null==this.registryFactory[o])throw new Error("Backend name '"+o+"' not found in registry");return this.backendName=o,null!=this.registry[o]?[3,4]:(this.backendInstance=null,e=this.initializeBackend(o),n=e.success,e.asyncInit?[4,n]:[3,2]);case 1:return r=t.sent(),[3,3];case 2:r=n,t.label=3;case 3:if(!r)return[2,!1];t.label=4;case 4:return this.backendInstance=this.registry[o],this.setupRegisteredKernels(),this.profiler=new nt(this.backendInstance),[2,!0]}})})},zt.prototype.setupRegisteredKernels=function(){var e=this;a(this.backendName).forEach(function(t){null!=t.setupFunc&&t.setupFunc(e.backendInstance)})},zt.prototype.disposeRegisteredKernels=function(e){var n=this;a(e).forEach(function(t){null!=t.disposeFunc&&t.disposeFunc(n.registry[e])})},zt.prototype.initializeBackend=function(e){var n=this,t=this.registryFactory[e];if(null==t)throw new Error("Cannot initialize backend "+e+", no registration found.");try{var r=t.factory();if(Promise.resolve(r)!==r)return this.registry[e]=r,{success:!0,asyncInit:!1};var o=++this.pendingBackendInitId,i=r.then(function(t){return!(o<n.pendingBackendInitId||(n.registry[e]=t,n.pendingBackendInit=null))}).catch(function(t){return!(o<n.pendingBackendInitId||(n.pendingBackendInit=null,console.warn("Initialization of backend "+e+" failed"),console.warn(t.stack||t.message),1))});return{success:this.pendingBackendInit=i,asyncInit:!0}}catch(n){return console.warn("Initialization of backend "+e+" failed"),console.warn(n.stack||n.message),{success:!1,asyncInit:!1}}},zt.prototype.removeBackend=function(t){if(!(t in this.registryFactory))throw new Error(t+" backend not found in registry");this.backendName===t&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)},zt.prototype.getSortedBackends=function(){var n=this;if(0===Object.keys(this.registryFactory).length)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort(function(t,e){return n.registryFactory[e].priority-n.registryFactory[t].priority})},zt.prototype.initializeBackendsAndReturnBest=function(){for(var t=this.getSortedBackends(),e=0;e<t.length;e++){var n=t[e],r=this.initializeBackend(n),o=r.success,i=r.asyncInit;if(i||o)return{name:n,asyncInit:i}}throw new Error("Could not initialize any backends, all backend initializations failed.")},zt.prototype.moveData=function(t,e){var n=this.state.tensorInfo.get(e),r=n.backend,o=this.readSync(e);r.disposeData(e),(n.backend=t).move(e,o,n.shape,n.dtype),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++},zt.prototype.tidy=function(t,e){var n,r=this,o=null;if(null==e){if("function"!=typeof t)throw new Error("Please provide a function to tidy()");e=t}else{if("string"!=typeof t&&!(t instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if("function"!=typeof e)throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");o=t}return this.scopedRun(function(){return r.startScope(o)},function(){return r.endScope(n)},function(){return(n=e())instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n})},zt.prototype.scopedRun=function(t,e,n){t();try{var r=n();return e(),r}catch(t){throw e(),t}},zt.prototype.nextTensorId=function(){return zt.nextTensorId++},zt.prototype.nextVariableId=function(){return zt.nextVariableId++},zt.prototype.clone=function(t){var e=this.makeTensorFromDataId(t.dataId,t.shape,t.dtype),n={x:t};return this.addTapeNode(this.state.activeScope.name,n,[e],function(t){return{x:function(){return t.toFloat()}}},[]),e},zt.prototype.runKernel=function(t,e,n,r,o){return this.runKernelFunc(null,e,null,t,n,r,o)},zt.prototype.shouldCheckForMemLeaks=function(){return this.ENV.getBool("IS_TEST")},zt.prototype.checkKernelForMemLeak=function(t,e,n){var r=this.backend.numDataIds(),o=0;n.forEach(function(t){o+="complex64"===t.dtype?3:1});var i=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],a=r-e-o-i;if(0<a)throw new Error("Backend '"+this.backendName+"' has an internal memory leak ("+a+" data ids) after running '"+t+"'")},zt.prototype.runKernelFunc=function(n,o,t,e,i,a,s){var r,u=this;function c(t){f&&(h=t.map(function(t){return u.keep(u.clone(t))}))}void 0===a&&(a=[]),void 0===s&&(s=[]);var l,h=[],f=this.isTapeOn(),p=null!=this.state.activeScope?this.state.activeScope.name:"",d=this.state.numBytes,v=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);var m,g=x(e,this.backendName);return l=null!=g?function(){var t=u.backend.numDataIds();m=g.kernelFunc({inputs:o,attrs:i,backend:u.backend});var e=Array.isArray(m)?m:[m];u.shouldCheckForMemLeaks()&&u.checkKernelForMemLeak(p,t,e);var n=e.map(function(t){var e=t.dataId,n=t.shape,r=t.dtype;return u.makeTensorFromDataId(e,n,r)}),r=n.filter(function(t,e){return s[e]});return c(a.slice().concat(r)),n}:function(){var t=u.backend.numDataIds();m=u.tidy(function(){return n(u.backend,c)});var e=Array.isArray(m)?m:[m];return u.shouldCheckForMemLeaks()&&u.checkKernelForMemLeak(p,t,e),e},this.scopedRun(function(){return u.state.kernelDepth++},function(){return u.state.kernelDepth--},function(){r=u.ENV.getBool("DEBUG")?u.profiler.profileKernel(p,o,function(){return l()}):l()}),f&&this.addTapeNode(p,o,r,t,h),this.state.profiling&&this.state.activeProfile.kernels.push({name:p,bytesAdded:this.state.numBytes-d,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-v,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(o).map(function(t){return o[t].shape}),outputShapes:r.map(function(t){return t.shape})}),Array.isArray(m)?r:r[0]},zt.prototype.makeTensor=function(t,e,n,r){if(null==t)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;var o=t;"string"===n&&z(t[0])&&(o=t.map(function(t){return Z(t)}));var i=r.write(o,e,n),a=new vt(e,n,i,this.nextTensorId());if(this.incRef(a,r),"string"===n){var s=this.state.tensorInfo.get(i),u=W(o);this.state.numBytes+=u-s.bytes,s.bytes=u}return a},zt.prototype.makeTensorFromDataId=function(t,e,n,r){var o=new vt(e,n=n||"float32",t,this.nextTensorId());return this.incRef(o,r),o},zt.prototype.makeVariable=function(t,e,n,r){void 0===e&&(e=!0),n=n||this.nextVariableId().toString(),null!=r&&r!==t.dtype&&(t=t.asType(r));var o=new St(t,e,n,this.nextTensorId());if(null!=this.state.registeredVariables[o.name])throw new Error("Variable with name "+o.name+" was already registered");return this.state.registeredVariables[o.name]=o,this.incRef(o,this.backend),o},zt.prototype.incRef=function(t,e){var n=this.state.tensorInfo.has(t.dataId)?this.state.tensorInfo.get(t.dataId).refCount:0;if(this.state.numTensors++,"string"===t.dtype&&this.state.numStringTensors++,0===n){this.state.numDataBuffers++;var r=0;"complex64"!==t.dtype&&"string"!==t.dtype&&(r=t.size*O(t.dtype)),this.state.tensorInfo.set(t.dataId,{backend:e||this.backend,dtype:t.dtype,shape:t.shape,bytes:r,refCount:0}),this.state.numBytes+=r}this.state.tensorInfo.get(t.dataId).refCount++,t instanceof St||this.track(t)},zt.prototype.disposeTensor=function(t){if(this.state.tensorInfo.has(t.dataId)){this.state.numTensors--,"string"===t.dtype&&this.state.numStringTensors--;var e=this.state.tensorInfo.get(t.dataId);e.refCount<=1?("complex64"!==t.dtype&&(this.state.numBytes-=e.bytes),this.state.numDataBuffers--,e.backend.disposeData(t.dataId),this.state.tensorInfo.delete(t.dataId)):this.state.tensorInfo.get(t.dataId).refCount--}},zt.prototype.disposeVariables=function(){for(var t in this.state.registeredVariables){var e=this.state.registeredVariables[t];this.disposeVariable(e)}},zt.prototype.disposeVariable=function(t){this.disposeTensor(t),null!=this.state.registeredVariables[t.name]&&delete this.state.registeredVariables[t.name]},zt.prototype.memory=function(){var t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,0<this.state.numStringTensors&&(t.unreliable=!0,null==t.reasons&&(t.reasons=[]),t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),t},zt.prototype.profile=function(r){return y(this,void 0,void 0,function(){var e,n;return R(this,function(t){return this.state.profiling=!0,e=this.state.numBytes,n=this.state.numTensors,this.state.activeProfile.kernels=[],this.state.activeProfile.result=r(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max.apply(Math,this.state.activeProfile.kernels.map(function(t){return t.totalBytesSnapshot})),this.state.activeProfile.newBytes=this.state.numBytes-e,this.state.activeProfile.newTensors=this.state.numTensors-n,[2,this.state.activeProfile]})})},zt.prototype.isTapeOn=function(){return 0<this.state.gradientDepth&&0===this.state.kernelDepth},zt.prototype.addTapeNode=function(t,e,o,n,r){var i=this,a={id:this.state.nextTapeNodeId++,name:t,inputs:e,outputs:o,saved:r};null!=n&&(a.gradient=function(t){return t=t.map(function(t,e){if(null!=t)return t;var n=o[e],r=Y(n.size,n.dtype);return i.makeTensor(r,n.shape,n.dtype)}),n(1<t.length?t:t[0],r)}),this.state.activeTape.push(a)},zt.prototype.keep=function(t){return t.kept=!0,t},zt.prototype.startTape=function(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++},zt.prototype.endTape=function(){this.state.gradientDepth--},zt.prototype.startScope=function(t){var e={track:[],name:"unnamed scope",id:this.state.nextScopeId++};t&&(e.name=t),this.state.scopeStack.push(e),this.state.activeScope=e},zt.prototype.endScope=function(t){for(var e=this,n=Ot(t),r=new Set(n.map(function(t){return t.id})),o=0;o<this.state.activeScope.track.length;o++){var i=this.state.activeScope.track[o];i.kept||r.has(i.id)||i.dispose()}var a=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],n.forEach(function(t){t.kept||t.scopeId!==a.id||e.track(t)})},zt.prototype.gradients=function(t,o,i,e){var u=this;if(void 0===e&&(e=!1),P(0<o.length,function(){return"gradients() received an empty list of xs."}),null!=i&&"float32"!==i.dtype)throw new Error("dy must have 'float32' dtype, but has '"+i.dtype+"'");var a=this.scopedRun(function(){return u.startTape()},function(){return u.endTape()},function(){return u.tidy("forward",t)});P(a instanceof vt,function(){return"The result y returned by f() must be a tensor."});var s=function(t,e,n){for(var r={},o={},i=0;i<e.length;i++)r[e[i].id]=!0;for(i=0;i<t.length;i++){var a=(d=t[i]).inputs;for(var s in a){for(var u=a[s],c=!1,l=0;l<e.length;l++)if(r[u.id]){d.outputs.forEach(function(t){return r[t.id]=!0}),c=!0,o[d.id]=!0;break}if(c)break}}var h={};h[n.id]=!0;var f={};for(i=t.length-1;0<=i;i--)for(a=(d=t[i]).inputs,l=0;l<d.outputs.length;l++)if(h[d.outputs[l].id]){for(var s in a)h[a[s].id]=!0,f[d.id]=!0;break}var p=[];for(i=0;i<t.length;i++){var d;if(o[(d=t[i]).id]&&f[d.id]){var v={};for(var s in d.inputs){var m=d.inputs[s];r[m.id]&&(v[s]=m)}var g=Object.assign({},d);g.inputs=v,g.outputs=d.outputs,p.push(g)}}return p}(this.state.activeTape,o,a);if(!e&&0===s.length&&0<o.length)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",function(){var t,e,n={};n[a.id]=null==i?(e=$(L(t=a.shape),"float32"),Vt.makeTensor(e,t,"float32")):i,function(a,s){for(var t=function(t){var o=s[t],n=[];if(o.outputs.forEach(function(t){var e=a[t.id];null!=e?n.push(e):n.push(null)}),null==o.gradient)throw new Error("Cannot compute gradient: gradient function not found for "+o.name+".");function e(t){if(!(t in i))throw new Error("Cannot backprop through input "+t+". Available gradients found: "+Object.keys(i)+".");var e=function(t){return u.tidy(t)}(function(){return i[t]()});if("float32"!==e.dtype)throw new Error("Error in gradient for op "+o.name+". The gradient of input "+t+" must have 'float32' dtype, but has '"+e.dtype+"'");var n=o.inputs[t];if(!D(e.shape,n.shape))throw new Error("Error in gradient for op "+o.name+". The gradient of input '"+t+"' has shape '"+e.shape+"', which does not match the shape of the input '"+n.shape+"'");if(null==a[n.id])a[n.id]=e;else{var r=a[n.id];a[n.id]=r.add(e),r.dispose()}}var i=o.gradient(n);for(var r in o.inputs)e(r)},e=s.length-1;0<=e;e--)t(e)}(n,s);var r=o.map(function(t){return n[t.id]});return 0===u.state.gradientDepth&&(u.state.activeTape.forEach(function(t){for(var e=0,n=t.saved;e<n.length;e++)n[e].dispose()}),u.state.activeTape=null),{value:a,grads:r}})},zt.prototype.customGrad=function(r){var e=this;return P(H(r),function(){return"The f passed in customGrad(f) must be a function."}),function(){for(var i,a=[],t=0;t<arguments.length;t++)a[t]=arguments[t];P(a.every(function(t){return t instanceof vt}),function(){return"The args passed in customGrad(f)(x1, x2,...) must all be tensors"});var n={};return a.forEach(function(t,e){n[e]=t}),e.runKernelFunc(function(t,e){return P((i=r.apply(void 0,a.concat([e]))).value instanceof vt,function(){return"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"}),P(H(i.gradFunc),function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."}),i.value},n,function(t,e){var n=i.gradFunc(t,e),r=Array.isArray(n)?n:[n];P(r.length===a.length,function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."}),P(r.every(function(t){return t instanceof vt}),function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors."});var o={};return r.forEach(function(t,e){o[e]=function(){return t}}),o})}},zt.prototype.readSync=function(t){return this.state.tensorInfo.get(t).backend.readSync(t)},zt.prototype.read=function(t){return this.state.tensorInfo.get(t).backend.read(t)},zt.prototype.time=function(r){return y(this,void 0,void 0,function(){var e,n;return R(this,function(t){switch(t.label){case 0:return e=J(),[4,this.backend.time(r)];case 1:return(n=t.sent()).wallMs=J()-e,[2,n]}})})},zt.prototype.track=function(t){return null!=this.state.activeScope&&(t.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(t)),t},Object.defineProperty(zt.prototype,"registeredVariables",{get:function(){return this.state.registeredVariables},enumerable:!0,configurable:!0}),zt.prototype.reset=function(){for(var t in this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new Lt,this.registry)this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null},zt.nextTensorId=0,zt.nextVariableId=0,zt);function zt(t){this.ENV=t,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Lt}function Ut(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null}}var Vt=function(){var t,e=function(){if(null==Pt){var t=void 0;if("undefined"!=typeof window)t=window;else if("undefined"!=typeof global)t=global;else if("undefined"!=typeof process)t=process;else{if("undefined"==typeof self)throw new Error("Could not find a global object");t=self}Pt=t}return Pt}();if(null==e._tfengine){var n=new o(e);e._tfengine=new Wt(n)}return t=e._tfengine.ENV,i=t,ht=function(){return e._tfengine},e._tfengine}();function Gt(){return"undefined"!=typeof window&&null!=window.document||"undefined"!=typeof WorkerGlobalScope}var Ht=_();Ht.registerFlag("DEBUG",function(){return!1},function(t){t&&console.warn("Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. This significantly impacts performance.")}),Ht.registerFlag("IS_BROWSER",function(){return Gt()}),Ht.registerFlag("IS_NODE",function(){return"undefined"!=typeof process&&void 0!==process.versions&&void 0!==process.versions.node}),Ht.registerFlag("IS_CHROME",function(){return"undefined"!=typeof navigator&&null!=navigator&&null!=navigator.userAgent&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor)}),Ht.registerFlag("PROD",function(){return!1}),Ht.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",function(){return Ht.getBool("DEBUG")}),Ht.registerFlag("DEPRECATION_WARNINGS_ENABLED",function(){return!0}),Ht.registerFlag("IS_TEST",function(){return!1});var qt,jt,Kt,Xt,$t,Yt,Jt={},Qt={alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!0};function Zt(t,e){Jt[t]=e}function te(t){t in Jt||(Jt[t]=function(e){if(1!==e&&2!==e)throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");var 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r=rn(t,"x","depthToSpace"),o="NHWC"===n?r.shape[1]:r.shape[2],i="NHWC"===n?r.shape[2]:r.shape[3],a="NHWC"===n?r.shape[3]:r.shape[1];return P(0<=o*e,function(){return"Negative dimension size caused by overflow when multiplying\n      "+o+" and "+e+"  for depthToSpace with input shape\n      "+r.shape}),P(0<=i*e,function(){return"Negative dimension size caused by overflow when multiplying\n      "+i+" and "+e+" for depthToSpace with input shape\n          "+r.shape}),P(a%(e*e)==0,function(){return"Dimension size must be evenly divisible by "+e*e+" but is "+a+" for depthToSpace with input shape "+r.shape}),Vt.runKernelFunc(function(t){return t.depthToSpace(r,e,n)},{$x:r})}}),pr=mn({expandDims_:function(t,e){void 0===e&&(e=0);var n=rn(t,"x","expandDims",null);P(e<=n.rank,function(){return"Axis must be <= rank of the tensor"});var r=n.shape.slice();return e<0&&(P(-(n.rank+1)<=e,function(){return"Axis must be in the interval ["+-(n.rank+1)+", 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0===r&&(r=0),e<2)throw new Error("Error in oneHot: depth must be >=2, but it is "+e);var o=rn(t,"indices","oneHot","int32"),i=o.shape.concat([e]);return o=o.flatten(),Vt.runKernelFunc(function(t){return t.oneHot(o,e,n,r)},{$indices:o},function(t){return{$indices:function(){return Tn(o.shape,"float32")}}}).reshape(i)}}),gr=mn({pad_:function(t,n,e){void 0===e&&(e=0);var r=rn(t,"x","pad");if(0===r.rank)throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");var o={paddings:n,constantValue:e};return Vt.runKernelFunc(function(t){return t.pad(r,n,e)},{x:r},function(t){var e=n.map(function(t){return t[0]});return{x:function(){return t.slice(e,r.shape)}}},"PadV2",o)}}),yr=mn({pad1d_:function(t,e,n){return void 0===n&&(n=0),P(2===e.length,function(){return"Invalid number of paddings. Must be length of 2."}),gr(t,[e],n)}}),xr=mn({pad2d_:function(t,e,n){return void 0===n&&(n=0),P(2===e.length&&2===e[0].length&&2===e[1].length,function(){return"Invalid number of paddings. Must be length of 2 each."}),gr(t,e,n)}}),br=mn({pad3d_:function(t,e,n){return void 0===n&&(n=0),P(3===e.length&&2===e[0].length&&2===e[1].length&&2===e[2].length,function(){return"Invalid number of paddings. Must be length of 2 each."}),gr(t,e,n)}}),wr=mn({pad4d_:function(t,e,n){return void 0===n&&(n=0),P(4===e.length&&2===e[0].length&&2===e[1].length&&2===e[2].length&&2===e[3].length,function(){return"Invalid number of paddings. Must be length of 2 each."}),gr(t,e,n)}}),Cr=mn({rand_:function(t,e,n){var r=L(t),o=null;if(null==n||"float32"===n)o=new Float32Array(r);else if("int32"===n)o=new Int32Array(r);else{if("bool"!==n)throw new Error("Unknown data type "+n);o=new Uint8Array(r)}for(var i=0;i<r;i++)o[i]=e();return Vt.makeTensor(o,t,n)}}),Er=mn({randomNormal_:function(t,e,n,r,o){if(void 0===e&&(e=0),void 0===n&&(n=1),null!=r&&"bool"===r)throw new Error("Unsupported data type "+r);for(var i=new Qn(e,n,r,!1,o),a=or(t,r),s=0;s<a.values.length;s++)a.values[s]=i.nextValue();return a.toTensor()}}),_r=mn({randomGamma_:function(t,e,n,r,o){if(void 0===n&&(n=1),void 0===r&&(r="float32"),null==n&&(n=1),null==r&&(r="float32"),"float32"!==r&&"int32"!==r)throw new Error("Unsupported data type "+r);for(var i=new Zn(e,n,r,o),a=or(t,r),s=0;s<a.values.length;s++)a.values[s]=i.nextValue();return a.toTensor()}}),Ir=mn({randomUniform_:function(t,e,n,r,o){void 0===e&&(e=0),void 0===n&&(n=1),void 0===r&&(r="float32");for(var i=or(t,r),a=new tr(e,n,null,o),s=0;s<i.values.length;s++)i.values[s]=a.nextValue();return i.toTensor()}}),Rr=mn({reshape_:function(t,e){var n=rn(t,"x","reshape",null);e=C(e,n.size),P(n.size===L(e),function(){return"new shape and old shape must have the same number of elements."});var r={shape:e};return Vt.runKernelFunc(function(t){return t.reshape(n,e)},{x:n},function(t){return{x:function(){return t.reshape(n.shape)}}},"Reshape",r)}}),kr=mn({spaceToBatchND_:function(t,r,o){var e=rn(t,"x","spaceToBatchND");return P(e.rank>=1+r.length,function(){return"input rank "+e.rank+" should be > than [blockShape] "+r.length}),P(o.length===r.length,function(){return"paddings.shape[0] "+o.length+" must be equal to [blockShape] "+r.length}),P(e.shape.reduce(function(t,e,n){return 0<n&&n<=r.length?t&&(e+o[n-1][0]+o[n-1][1])%r[n-1]==0:t},!0),function(){return"input spatial dimensions "+e.shape.slice(1)+" with paddings "+o.toString()+" must be divisible by blockShapes "+r.toString()}),Vt.runKernelFunc(function(t){return t.spaceToBatchND(e,r,o)},{$x:e},function(t){return{$x:function(){return t.batchToSpaceND(r,o)}}})}}),Sr=mn({squeeze_:function(t,e){var n=rn(t,"x","squeeze");return Rr(n,k(n.shape,e).newShape)}}),Dr=mn({stack_:function(t,e){void 0===e&&(e=0);var n=on(t,"tensors","stack");if(P(1<=n.length,function(){return"Pass at least one tensor to tf.stack"}),1===n.length)return n[0].expandDims(e);var r=n[0].rank,o=n[0].shape,i=n[0].dtype;P(e<=r,function(){return"Axis must be <= rank of the tensor"}),n.forEach(function(t){b(o,t.shape,"All tensors passed to stack must have matching shapes")}),n.forEach(function(t){P(i===t.dtype,function(){return"All tensors passed to stack must have matching dtypes"})});var a=n.map(function(t){return t.expandDims(e)});return Bn(a,e)}}),Ar=mn({tile_:function(t,s){var r=rn(t,"x","tile",null);return P(r.rank===s.length,function(){return"Error in transpose: rank of input "+r.rank+" must match length of reps 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e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,i=o[0],a=o[1],s=Lo();if(null!=o&&D(e,o))return"\n      vec4 "+r+"(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2("+a+".0, "+i+".0);\n\n        return "+s.texture2D+"("+n+", uv);\n      }\n    ";var u=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],c=Math.ceil(e[1]/2);return"\n    vec4 "+r+"(int row, int col) {\n      vec2 uv = packedUVfrom2D("+c+", "+u[0]+", "+u[1]+", row, col);\n      return "+s.texture2D+"("+n+", uv);\n    }\n  "}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape,i=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];if(1===e[0]){var a=e.slice(1),s=jo(t,a);return"\n        "+p(s)+"\n        vec4 "+r+"(int b, int row, int col) {\n          return "+r+"("+Ko(["b","row","col"],[1,2])+");\n        }\n      "}var u=i[0],c=i[1],l=Math.ceil(e[2]/2),h=l*Math.ceil(e[1]/2),f=Lo();return"\n    vec4 "+r+"(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        "+u+", "+c+", "+h+", "+l+", b, row, col);\n      return "+f.texture2D+"("+n+", uv);\n    }\n  "}(t);default:return function(t){for(var e=t.shapeInfo.logicalShape,n=e.length,r=t.name,o="get"+r.charAt(0).toUpperCase()+r.slice(1),i=t.shapeInfo.texShape,a=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],s=a[0],u=a[1],c=Math.ceil(e[n-1]/2),l=c*Math.ceil(e[n-2]/2),h="int b, int row, int col",f="b * "+l+" + (row / 2) * "+c+" + (col / 2)",p=2;p<n-1;p++)h="int b"+p+", "+h,l*=e[n-p-1],f="b"+p+" * "+l+" + "+f;var d=Lo();return"\n    vec4 "+o+"("+h+") {\n      int index = "+f+";\n      int texR = index / "+u+";\n      int texC = index - texR * "+u+";\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+u+", "+s+");\n      return "+d.texture2D+"("+r+", uv);\n    }\n  "}(t)}}(t):function y(t){var e=t.shapeInfo.logicalShape;switch(e.length){case 0:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return"float "+n+"() {return "+e+";}";var r=t.shapeInfo.texShape,o=r[0],i=r[1];if(1===o&&1===i)return"\n      float "+n+"() {\n        return sampleTexture("+e+", halfCR);\n      }\n    ";var a=t.shapeInfo.texShape,s=a[0],u=a[1],c=Go(e);return"\n    float "+n+"() {\n      vec2 uv = uvFromFlat("+s+", "+u+", "+c+");\n      return sampleTexture("+e+", uv);\n    }\n  "}(t);case 1:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return"\n      float "+n+"(int index) {\n        "+Ho(t)+"\n      }\n    ";var r=t.shapeInfo.texShape,o=r[0],i=r[1];if(1===i&&1===o)return"\n      float "+n+"(int index) {\n        return sampleTexture("+e+", halfCR);\n      }\n    ";var a=Go(e);return 1===i?"\n      float "+n+"(int index) {\n        vec2 uv = vec2(0.5, (float(index + "+a+") + 0.5) / "+o+".0);\n        return sampleTexture("+e+", uv);\n      }\n    ":1===o?"\n      float "+n+"(int index) {\n        vec2 uv = vec2((float(index + "+a+") + 0.5) / "+i+".0, 0.5);\n        return sampleTexture("+e+", uv);\n      }\n    ":"\n    float "+n+"(int index) {\n      vec2 uv = uvFromFlat("+o+", "+i+", index + "+a+");\n      return sampleTexture("+e+", uv);\n    }\n  "}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape;if(null!=o&&D(e,o)){var i=o[0],a=o[1];return"\n    float "+r+"(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2("+a+".0, "+i+".0);\n      return sampleTexture("+n+", uv);\n    }\n  "}var s=k(e),u=s.newShape,c=s.keptDims,l=u;if(l.length<e.length){var h=jo(t,l);return"\n      "+y(h)+"\n      float "+r+"(int row, int col) {\n        return "+r+"("+Ko(["row","col"],c)+");\n      }\n    "}if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col) {\n        int index = round(dot(vec2(row, col), vec2("+e[1]+", 1)));\n        "+Ho(t)+"\n      }\n    ";var f=o[0],p=o[1],d=Go(n);return 1===p?"\n    float "+r+"(int row, int col) {\n      float index = dot(vec3(row, col, "+d+"), vec3("+e[1]+", 1, 1));\n      vec2 uv = vec2(0.5, (index + 0.5) / "+f+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ":1===f?"\n    float "+r+"(int row, int col) {\n      float index = dot(vec3(row, col, "+d+"), vec3("+e[1]+", 1, 1));\n      vec2 uv = vec2((index + 0.5) / "+p+".0, 0.5);\n      return sampleTexture("+n+", uv);\n    }\n  ":"\n  float "+r+"(int row, int col) {\n    // Explicitly use integer operations as dot() only works on floats.\n    int index = row * "+e[1]+" + col + "+d+";\n    vec2 uv = uvFromFlat("+f+", "+p+", index);\n    return sampleTexture("+n+", uv);\n  }\n"}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[1]*e[2],i=e[2],a=k(e),s=a.newShape,u=a.keptDims,c=s;if(c.length<e.length){var l=jo(t,c);return"\n        "+y(l)+"\n        float "+r+"(int row, int col, int depth) {\n          return "+r+"("+Ko(["row","col","depth"],u)+");\n        }\n      "}if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col, int depth) {\n        int index = round(dot(vec3(row, col, depth),\n                          vec3("+o+", "+i+", 1)));\n        "+Ho(t)+"\n      }\n    ";var h=t.shapeInfo.texShape,f=h[0],p=h[1],d=t.shapeInfo.flatOffset;if(p===o&&null==d)return"\n        float "+r+"(int row, int col, int depth) {\n          float texR = float(row);\n          float texC = dot(vec2(col, depth), vec2("+i+", 1));\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2("+p+".0, "+f+".0);\n          return sampleTexture("+n+", uv);\n        }\n      ";if(p===i&&null==d)return"\n    float "+r+"(int row, int col, int depth) {\n      float texR = dot(vec2(row, col), vec2("+e[1]+", 1));\n      float texC = float(depth);\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+p+".0, "+f+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ";var v=Go(n);return"\n      float "+r+"(int row, int col, int depth) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * "+o+" + col * "+i+" + depth + "+v+";\n        vec2 uv = uvFromFlat("+f+", "+p+", index);\n        return sampleTexture("+n+", uv);\n      }\n  "}(t);case 4:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[3],i=e[2]*o,a=e[1]*i,s=k(e),u=s.newShape,c=s.keptDims;if(u.length<e.length){var l=jo(t,u);return"\n      "+y(l)+"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        return "+r+"("+Ko(["row","col","depth","depth2"],c)+");\n      }\n    "}if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        int index = round(dot(vec4(row, col, depth, depth2),\n                          vec4("+a+", "+i+", "+o+", 1)));\n        "+Ho(t)+"\n      }\n    ";var h=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,p=f[0],d=f[1];if(d===a&&null==h)return"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3("+i+", "+o+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+d+".0, "+p+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(d===o&&null==h)return"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3("+e[1]*e[2]+", "+e[2]+", 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+d+".0, "+p+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var v=Go(n);return"\n    float "+r+"(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+a+" + col * "+i+" +\n          depth * "+o+" + depth2;\n      vec2 uv = uvFromFlat("+p+", "+d+", index + "+v+");\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);case 5:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[4],i=e[3]*o,a=e[2]*i,s=e[1]*a,u=k(e),c=u.newShape,l=u.keptDims;if(c.length<e.length){var h=jo(t,c);return"\n      "+y(h)+"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        return "+r+"("+Ko(["row","col","depth","depth2","depth3"],l)+");\n      }\n    "}if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        float index = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+s+", "+a+", "+i+", "+o+")) +\n          depth3;\n        "+Ho(t)+"\n      }\n    ";var f=t.shapeInfo.flatOffset,p=t.shapeInfo.texShape,d=p[0],v=p[1];if(v===s&&null==f)return"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n                         vec4("+a+", "+i+", "+o+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+v+".0, "+d+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(v===o&&null==f)return"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        float texR = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+e[1]*e[2]*e[3]+",\n               "+e[2]*e[3]+", "+e[3]+", 1));\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+v+".0, "+d+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var m=Go(n);return"\n    float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+s+" + col * "+a+" + depth * "+i+" +\n          depth2 * "+o+" + depth3 + "+m+";\n      vec2 uv = uvFromFlat("+d+", "+v+", index);\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);case 6:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=k(e),i=o.newShape,a=o.keptDims;if(i.length<e.length){var s=jo(t,i);return"\n      "+y(s)+"\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        return "+r+"("+Ko(["row","col","depth","depth2","depth3","depth4"],a)+");\n      }\n    "}var u=e[5],c=e[4]*u,l=e[3]*c,h=e[2]*l,f=e[1]*h;if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n        int index = round(dot(\n          vec4(row, col, depth, depth2),\n          vec4("+f+", "+h+", "+l+", "+c+")) +\n          dot(\n            vec2(depth3, depth4),\n            vec2("+u+", 1)));\n        "+Ho(t)+"\n      }\n    ";var p=t.shapeInfo.flatOffset,d=t.shapeInfo.texShape,v=d[0],m=d[1];if(m===f&&null==p)return"\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n          vec4("+h+", "+l+", "+c+", "+u+")) +\n               float(depth4);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+m+".0, "+v+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(m===u&&null==p)return"\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        float texR = dot(vec4(row, col, depth, depth2),\n          vec4("+e[1]*e[2]*e[3]*e[4]+",\n               "+e[2]*e[3]*e[4]+",\n               "+e[3]*e[4]+",\n               "+e[4]+")) + float(depth3);\n        int texC = depth4;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+m+".0, "+v+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var g=Go(n);return"\n    float "+r+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+f+" + col * "+h+" + depth * "+l+" +\n          depth2 * "+c+" + depth3 * "+u+" + depth4 + "+g+";\n      vec2 uv = uvFromFlat("+v+", "+m+", index);\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);default:throw new Error(e.length+"-D input sampling is not yet supported")}}(t);var o=t.shapeInfo.logicalShape,i=e.logicalShape;return o.length<=i.length&&(r+=n?function(t,e){var n,r=t.name,o=r.charAt(0).toUpperCase()+r.slice(1),i="get"+o+"AtOutCoords",a=t.shapeInfo.logicalShape.length,s=e.logicalShape.length,u=io(t.shapeInfo.logicalShape,e.logicalShape),c=qo(s),l=s-a,h=["x","y","z","w","u","v"];n=0===a?"":s<2&&1<=u.length?"coords = 0;":u.map(function(t){return"coords."+h[t+l]+" = 0;"}).join("\n");var f;f=s<2&&0<a?"coords":t.shapeInfo.logicalShape.map(function(t,e){return"coords."+h[e+l]}).join(", ");var p="return outputValue;",d=1===L(t.shapeInfo.logicalShape),v=1===L(e.logicalShape);if(1!==a||d||v){if(d&&!v)p=1===s?"\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\n      ":"\n        return vec4(outputValue.x);\n      ";else if(u.length){var m=a-2,g=a-1;-1<u.indexOf(m)&&-1<u.indexOf(g)?p="return vec4(outputValue.x);":-1<u.indexOf(m)?p="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":-1<u.indexOf(g)&&(p="return vec4(outputValue.xx, outputValue.zz);")}}else p="\n      return vec4(outputValue.xy, outputValue.xy);\n    ";return"\n    vec4 "+i+"() {\n      "+c+" coords = getOutputCoords();\n      "+n+"\n      vec4 outputValue = get"+o+"("+f+");\n      "+p+"\n    }\n  "}(t,e):function(t,e){var n=t.name,r=n.charAt(0).toUpperCase()+n.slice(1),o="get"+r+"AtOutCoords",i=e.texShape,a=t.shapeInfo.texShape,s=t.shapeInfo.logicalShape.length,u=e.logicalShape.length;if(!t.shapeInfo.isUniform&&s===u&&null==t.shapeInfo.flatOffset&&D(a,i))return"\n      float "+o+"() {\n        return sampleTexture("+n+", resultUV);\n      }\n    ";var c=qo(u),l=io(t.shapeInfo.logicalShape,e.logicalShape),h=u-s,f=["x","y","z","w","u","v"];return"\n    float "+o+"() {\n      "+c+" coords = getOutputCoords();\n      "+(0===s?"":u<2&&1<=l.length?"coords = 0;":l.map(function(t){return"coords."+f[t+h]+" = 0;"}).join("\n"))+"\n      return get"+r+"("+(u<2&&0<s?"coords":t.shapeInfo.logicalShape.map(function(t,e){return"coords."+f[e+h]}).join(", "))+");\n    }\n  "}(t,e)),r}(t,e,r)}).join("\n"),l=e.texShape,h=Lo(),f="\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return "+h.texture2D+"(textureSampler, uv).r;\n    }\n  ",p=(s=h).version+"\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    "+s.varyingFs+" vec2 resultUV;\n    "+s.defineOutput+"\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    uniform float NAN;\n    "+s.defineSpecialNaN+"\n    "+s.defineSpecialInf+"\n    "+s.defineRound+"\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    int idiv(int a, int b, float sign) {\n      int res = a / b;\n      int mod = imod(a, b);\n      if (sign < 0. && mod != 0) {\n        res -= 1;\n      }\n      return res;\n    }\n\n    //Based on the work of Dave Hoskins\n    //https://www.shadertoy.com/view/4djSRW\n    #define HASHSCALE1 443.8975\n    float random(float seed){\n      vec2 p = resultUV * seed;\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n      p3 += dot(p3, p3.yzx + 19.19);\n      return fract((p3.x + p3.y) * p3.z);\n    }\n\n    \nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n    \nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n    \nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n  ";return a=e.isPacked?(i=function(t,e){switch(t.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return n=e,1===(r=[Math.ceil(n[0]/2),Math.ceil(n[1]/2)])[0]?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * "+r[1]+".0);\n      }\n    ":1===r[1]?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * "+r[0]+".0);\n      }\n    ":"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+r[0]+", "+r[1]+"));\n      return 2 * (resTexRC.x * "+r[1]+" + resTexRC.y);\n    }\n  ";case 2:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(D(t,e))return"\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2("+n[0]+", "+n[1]+"));\n      }\n    ";var r=Math.ceil(t[1]/2);return"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec2(r, c);\n    }\n  "}(t,e);case 3:return o=t,i=e,a=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],u=(s=Math.ceil(o[2]/2))*Math.ceil(o[1]/2),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+a[0]+", "+a[1]+"));\n      int index = resTexRC.x * "+a[1]+" + resTexRC.y;\n\n      int b = index / "+u+";\n      index -= b * "+u+";\n\n      int r = 2 * (index / "+s+");\n      int c = imod(index, "+s+") * 2;\n\n      return ivec3(b, r, c);\n    }\n  ";default:return function(t,e){for(var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],r=Math.ceil(t[t.length-1]/2),o=r*Math.ceil(t[t.length-2]/2),i=o,a="",s="b, r, c",u=2;u<t.length-1;u++)a="\n      int b"+u+" = index / "+(i*=t[t.length-u-1])+";\n      index -= b"+u+" * "+i+";\n    "+a,s="b"+u+", "+s;return"\n    ivec"+t.length+" getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n\n      "+a+"\n\n      int b = index / "+o+";\n      index -= b * "+o+";\n\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec"+t.length+"("+s+");\n    }\n  "}(t,e)}var n,r,o,i,a,s,u}(e.logicalShape,l),"\n    void setOutput(vec4 val) {\n      "+h.output+" = val;\n    }\n  "):(i=function(t,e){switch(t.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return 1===(l=e)[0]?"\n      int getOutputCoords() {\n        return int(resultUV.x * "+l[1]+".0);\n      }\n    ":1===l[1]?"\n      int getOutputCoords() {\n        return int(resultUV.y * "+l[0]+".0);\n      }\n    ":"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+l[0]+", "+l[1]+"));\n      return resTexRC.x * "+l[1]+" + resTexRC.y;\n    }\n  ";case 2:return D(u=t,c=e)?"\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2("+c[0]+", "+c[1]+"));\n      }\n    ":1===u[1]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+c[0]+", "+c[1]+"));\n        int index = resTexRC.x * "+c[1]+" + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ":1===u[0]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+c[0]+", "+c[1]+"));\n        int index = resTexRC.x * "+c[1]+" + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ":"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+c[0]+", "+c[1]+"));\n      int index = resTexRC.x * "+c[1]+" + resTexRC.y;\n      int r = index / "+u[1]+";\n      int c = index - r * "+u[1]+";\n      return ivec2(r, c);\n    }\n  ";case 3:return h=e,f=Wo(["r","c","d"],t),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+h[0]+", "+h[1]+"));\n      int index = resTexRC.x * "+h[1]+" + resTexRC.y;\n      "+f+"\n      return ivec3(r, c, d);\n    }\n  ";case 4:return a=e,s=Wo(["r","c","d","d2"],t),"\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+a[0]+", "+a[1]+"));\n      int index = resTexRC.x * "+a[1]+" + resTexRC.y;\n      "+s+"\n      return ivec4(r, c, d, d2);\n    }\n  ";case 5:return o=e,i=Wo(["r","c","d","d2","d3"],t),"\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2("+o[0]+",\n                             "+o[1]+"));\n\n      int index = resTexRC.x * "+o[1]+" + resTexRC.y;\n\n      "+i+"\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  ";case 6:return n=e,r=Wo(["r","c","d","d2","d3","d4"],t),"\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n\n      "+r+"\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  ";default:throw new Error(t.length+"-D output sampling is not yet supported")}var n,r,o,i,a,s,u,c,l,h,f}(e.logicalShape,l),"\n    void setOutput(float val) {\n      "+h.output+" = vec4(val, 0, 0, 0);\n    }\n  "),r&&(p+="\n  float getChannel(vec4 frag, vec2 innerDims) {\n    vec2 modCoord = mod(innerDims, 2.);\n    return modCoord.x == 0. ?\n      (modCoord.y == 0. ? frag.r : frag.g) :\n      (modCoord.y == 0. ? frag.b : frag.a);\n  }\n  float getChannel(vec4 frag, int dim) {\n    float modCoord = mod(float(dim), 2.);\n    return modCoord == 0. ? frag.r : frag.g;\n  }\n"),[p,f,a,u,i,c,n].join("\n")}function Go(t){return"offset"+t}function Ho(t){var e=t.name,n=L(t.shapeInfo.logicalShape);return n<2?"return "+e+";":"\n    for (int i = 0; i < "+n+"; i++) {\n      if (i == index) {\n        return "+e+"[i];\n      }\n    }\n  "}function qo(t){if(t<=1)return"int";if(2===t)return"ivec2";if(3===t)return"ivec3";if(4===t)return"ivec4";if(5===t)return"ivec5";if(6===t)return"ivec6";throw Error("GPU for rank "+t+" is not yet supported")}function jo(t,e){var n=JSON.parse(JSON.stringify(t));return n.shapeInfo.logicalShape=e,n}function Ko(e,t){return t.map(function(t){return e[t]}).join(", ")}var Xo=function(t,e,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,P(2<t.length,function(){return"Packed arg"+(n.charAt(0).toUpperCase()+n.slice(1))+" supports only inputs with rank above 2."});var o=t[t.length-1],i=Math.ceil(o/e);this.outputShape=t.slice(0,-1),1<i&&this.outputShape.push(i),r||this.variableNames.push("bestIndicesA");var a,s,u=this.outputShape,c=u.length,l=qo(c),h=Bo("coords",c);if(1===i){var f=qo(s=c+1);a="\n        "+f+" sourceLocR = "+f+"("+h.join()+", 0);\n        ++"+h[c-1]+";\n        "+f+" sourceLocG = "+f+"("+h.join()+", 0);\n        ++"+h[c-2]+";\n        "+f+" sourceLocA = "+f+"("+h.join()+", 0);\n        --"+h[c-1]+";\n        "+f+" sourceLocB = "+f+"("+h.join()+", 0);\n        --"+h[c-2]+";"}else a="\n        "+l+" sourceLocR = coords;\n        ++"+h[(s=c)-1]+";\n        "+l+" sourceLocG = coords;\n        ++"+h[c-2]+";\n        "+l+" sourceLocA = coords;\n        --"+h[c-1]+";\n        "+l+" sourceLocB = coords;\n        --"+h[c-2]+";";var p=["x","y","z","w","u","v"].slice(0,s),d="."+p[s-1],v=p.map(function(t){return"int "+t}),m=Bo("sourceLocR",s-1).concat("inIdx.r"),g=Bo("sourceLocG",s-1).concat("inIdx.g"),y=Bo("sourceLocB",s-1).concat("inIdx.b"),x=Bo("sourceLocA",s-1).concat("inIdx.a"),b="max"===n?"greaterThan":"lessThan",w=r?"":"\n          inIdx = round(vec4(getBestIndicesAChannel("+m.join()+"),\n                             getBestIndicesAChannel("+g.join()+"),\n                             getBestIndicesAChannel("+y.join()+"),\n                             getBestIndicesAChannel("+x.join()+")));",C="vec4(\n            getAChannel("+m.join()+"),\n            hasNextCol ? getAChannel("+g.join()+") : 0.,\n            hasNextRow ? getAChannel("+y.join()+") : 0.,\n            hasNextRow && hasNextCol ? getAChannel("+x.join()+") : 0.)",E=r?"":"\n      float getBestIndicesAChannel("+v.join()+") {\n        return getChannel(getBestIndicesA("+p.join()+"),\n                                          vec2("+p.slice(-2).join()+"));\n      }";this.userCode="\n      float getAChannel("+v.join()+") {\n        return getChannel(getA("+p.join()+"),\n                               vec2("+p.slice(-2).join()+"));\n      }\n      "+E+"\n      void main() {\n        "+l+" coords = getOutputCoords();\n        bool hasNextCol = "+h[c-1]+" < "+(u[c-1]-1)+";\n        bool hasNextRow = "+h[c-2]+" < "+(u[c-2]-1)+";\n        "+a+"\n        ivec4 srcIdx = ivec4(sourceLocR"+d+", sourceLocG"+d+",\n          sourceLocB"+d+", sourceLocA"+d+") * "+e+";\n        ivec4 inIdx = srcIdx;\n        vec4 bestIndex = vec4(inIdx);\n        vec4 bestValue = "+C+";\n\n        for (int i = 0; i < "+e+"; i++) {\n          inIdx = srcIdx;\n          "+w+"\n          vec4 candidate = "+C+";\n          bvec4 nan = isnan(candidate);\n          bvec4 replace = bvec4(\n            vec4("+b+"(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\n                           replace.y  ? candidate.y : bestValue.y,\n                           replace.z  ? candidate.z : bestValue.z,\n                           replace.w  ? candidate.w : bestValue.w);\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n          srcIdx++;\n        }\n        setOutput(bestIndex);\n      }\n    "},$o=function(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,i=t.dilationHeight,a=t.dilationWidth,s=t.effectiveFilterHeight,u=t.effectiveFilterWidth,c=s-1-t.padInfo.top,l=u-1-t.padInfo.left,h=1/(e*n);this.userCode="\n      const ivec2 pads = ivec2("+c+", "+l+");\n      const float avgMultiplier = float("+h+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+s+";\n            wR += "+i+") {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+u+";\n            wC+= "+a+") {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Yo=function(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,i=t.strideHeight,a=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,p=l-1-t.padInfo.front,d=h-1-t.padInfo.top,v=f-1-t.padInfo.left,m=1/(e*n*r);this.userCode="\n      const ivec3 pads = ivec3("+p+", "+d+", "+v+");\n      const float avgMultiplier = float("+m+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+l+";\n            wD += "+s+") {\n          float dyD = float(dyDCorner + wD) / "+o+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+h+";\n              wR += "+u+") {\n            float dyR = float(dyRCorner + wR) / "+i+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+f+";\n                wC += "+c+") {\n              float dyC = float(dyCCorner + wC) / "+a+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Jo=function(t,e,n,r,o,i){this.outputShape=[],this.variableNames=["x","mean","variance"],so(t,e),so(t,n);var a="0.0";null!=r&&(so(t,r),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");var s="1.0";null!=o&&(so(t,o),this.variableNames.push("scale"),s="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = "+a+";\n        float scale = "+s+";\n        float inv = scale * inversesqrt(variance + float("+i+"));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    "},Qo=function(t,e,n,r,o,i){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],so(t,e),so(t,n);var a="vec4(0.0)";null!=r&&(so(t,r),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");var s="vec4(1.0)";null!=o&&(so(t,o),this.variableNames.push("scale"),s="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        vec4 offset = "+a+";\n        vec4 scale = "+s+";\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4("+i+"));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    "},Zo=function(t,e,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=so(e,n),this.userCode="\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        "+t+"\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    "},ti="return a + b;",ei="return a - b;",ni="return a * b;",ri="return (a < 0.) ? b * a : a;",oi=function(t,e,n){this.variableNames=["A","B"],this.outputShape=so(e,n),this.userCode="\n      float binaryOperation(float a, float b) {\n        "+t+"\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    "},ii="\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n",ai=function(t,e,n,r){void 0===r&&(r=!1),this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=so(e,n);var o=this.outputShape.length,i="";if(r)if(0===o||1===L(this.outputShape))i="\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        ";else if(i="\n          "+qo(o)+" coords = getOutputCoords();\n        ",1===o)i+="\n            result.y = (coords + 1) >= "+this.outputShape[0]+" ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          ";else{var a=Bo("coords",o);i+="\n            bool nextRowOutOfBounds =\n              ("+a[o-2]+" + 1) >= "+this.outputShape[o-2]+";\n            bool nextColOutOfBounds =\n              ("+a[o-1]+" + 1) >= "+this.outputShape[o-1]+";\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          "}this.userCode="\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        "+t+"\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        "+i+"\n\n        setOutput(result);\n      }\n    "},si=(pi.prototype.getCustomSetupFunc=function(n,r){var o=this;return function(t,e){null==o.minLoc&&(o.minLoc=t.getUniformLocationNoThrow(e,"minVal"),o.maxLoc=t.getUniformLocationNoThrow(e,"maxVal")),t.gl.uniform1f(o.minLoc,n),t.gl.uniform1f(o.maxLoc,r)}},pi),ui=(fi.prototype.getCustomSetupFunc=function(n,r){var o=this;return function(t,e){null==o.minLoc&&(o.minLoc=t.getUniformLocationNoThrow(e,"minVal"),o.maxLoc=t.getUniformLocationNoThrow(e,"maxVal")),t.gl.uniform1f(o.minLoc,n),t.gl.uniform1f(o.maxLoc,r)}},fi),ci=function(t){this.variableNames=["real","imag"],this.outputShape=t,this.userCode="\n      void main() {\n        float re = abs(getRealAtOutCoords());\n        float im = abs(getImagAtOutCoords());\n        float mx = max(re, im);\n\n        // sadly the length function in glsl is not underflow-safe\n        // (at least not on Intel GPUs). So the safe solution is\n        // to ensure underflow-safety in all cases.\n        setOutput(\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\n        );\n      }\n    "},li=function(t){this.outputShape=[],this.outputShape=vn(t,1),this.variableNames=t.map(function(t,e){return"T"+e});var e=new Array(t.length-1);e[0]=t[0][1];for(var n=1;n<e.length;n++)e[n]=e[n-1]+t[n][1];var r=["if (yC < "+e[0]+") setOutput(getT0(yR, yC));"];for(n=1;n<e.length;n++){var o=e[n-1];r.push("else if (yC < "+e[n]+") setOutput(getT"+n+"(yR, yC-"+o+"));")}var i=e.length,a=e[e.length-1];r.push("else setOutput(getT"+i+"(yR, yC-"+a+"));"),this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        "+r.join("\n        ")+"\n      }\n    "},hi=function(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=vn(t,e);var n=this.outputShape,r=n.length,o=qo(r),i=Bo("coords",r),a=["x","y","z","w","u","v"].slice(0,r);this.variableNames=t.map(function(t,e){return"T"+e});var s=new Array(t.length-1);s[0]=t[0][e];for(var u=1;u<s.length;u++)s[u]=s[u-1]+t[u][e];var c=a[e],l=a.slice(-2),h=a.join(),f="if ("+c+" < "+s[0]+") {\n        return getChannel(\n            getT0("+h+"), vec2("+l.join()+"));\n        }";for(u=1;u<s.length;u++){var p=s[u-1];f+="\n        if ("+c+" < "+s[u]+"  && "+c+" >= "+s[u-1]+") {\n          return getChannel(\n            getT"+u+"("+di(a,c,p)+"),\n            vec2("+di(l,c,p)+"));\n        }"}var d=s.length,v=s[s.length-1];f+="\n        return getChannel(\n          getT"+d+"("+di(a,c,v)+"),\n          vec2("+di(l,c,v)+"));",this.userCode="\n      float getValue("+a.map(function(t){return"int "+t})+") {\n        "+f+"\n      }\n\n      void main() {\n        "+o+" coords = getOutputCoords();\n        vec4 result = vec4(getValue("+i+"), 0., 0., 0.);\n\n        "+i[r-1]+" = "+i[r-1]+" + 1;\n        if ("+i[r-1]+" < "+n[r-1]+") {\n          result.g = getValue("+i+");\n        }\n\n        "+i[r-2]+" = "+i[r-2]+" + 1;\n        if ("+i[r-2]+" < "+n[r-2]+") {\n          result.a = getValue("+i+");\n        }\n\n        "+i[r-1]+" = "+i[r-1]+" - 1;\n        if ("+i[r-2]+" < "+n[r-2]+" &&\n            "+i[r-1]+" < "+n[r-1]+") {\n          result.b = getValue("+i+");\n        }\n        setOutput(result);\n      }\n    "};function fi(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        vec4 value = getAAtOutCoords();\n\n        if (any(isnan(value))) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\n      }\n    "}function pi(t){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    "}function di(t,e,n){var r=t.indexOf(e);return t.map(function(t,e){return e===r?t+" - "+n:t}).join()}var vi=function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,i="channelsLast"===t.dataFormat;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+o+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              if ("+i+") {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},mi=function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,i="channelsLast"===t.dataFormat,a=e-1-t.padInfo.top,s=n-1-t.padInfo.left,u=i?1:2,c=i?2:3,l=i?3:1;this.userCode="\n      const ivec2 pads = ivec2("+a+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords["+l+"];\n\n        ivec2 dyCorner = ivec2(coords["+u+"], coords["+c+"]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n\n              if ("+i+") {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},gi=function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.padInfo.front,i=t.padInfo.top,a=t.padInfo.left;this.userCode="\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yF = 0; yF < "+t.outDepth+"; yF++) {\n            int xF = wF + yF * "+e+" - "+o+";\n\n            if (xF < 0 || xF >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n              int xR = wR + yR * "+n+" - "+i+";\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n                int xC = wC + yC * "+r+" - "+a+";\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},yi=function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,i=t.strideHeight,a=t.strideWidth,s=e-1-t.padInfo.front,u=n-1-t.padInfo.top,c=r-1-t.padInfo.left;this.userCode="\n      const ivec3 pads = ivec3("+s+", "+u+", "+c+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+e+"; wF++) {\n          float dyF = float(dyFCorner + wF) / "+o+".0;\n\n          if (dyF < 0.0 || dyF >= "+t.outDepth+".0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = "+e+" - 1 - wF;\n\n          for (int wR = 0; wR < "+n+"; wR++) {\n            float dyR = float(dyRCorner + wR) / "+i+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = "+n+" - 1 - wR;\n\n            for (int wC = 0; wC < "+r+"; wC++) {\n              float dyC = float(dyCCorner + wC) / "+a+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = "+r+" - 1 - wC;\n\n              for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},xi=function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,i=t.outChannels/t.inChannels;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * "+i+" + dm;\n\n        float dotProd = 0.0;\n\n        // TO DO: Vec4 over the batch size\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+o+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},bi=function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,i=e-1-t.padInfo.top,a=n-1-t.padInfo.left,s=t.outChannels/t.inChannels;this.userCode="\n      const ivec2 pads = ivec2("+i+", "+a+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < "+s+"; dm++) {\n              int d2 = d1 * "+s+" + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},wi=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.outputShape=t.outShape;var o=t.padInfo.top,i=t.padInfo.left,a=t.strideHeight,s=t.strideWidth,u=t.dilationHeight,c=t.dilationWidth,l=t.filterHeight,h=t.filterWidth,f=4*Math.floor(t.inChannels/4),p=t.inChannels%4,d="channelsLast"===t.dataFormat,v=d?1:2,m=d?2:3,g=d?3:1,y="",x="";n&&(y=r?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"\n          float activation(float x) {\n            "+n+"\n          }\n        ",x="result = activation(result);");var b=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+y+"\n\n      const ivec2 strides = ivec2("+a+", "+s+");\n      const ivec2 pads = ivec2("+o+", "+i+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords["+g+"];\n\n        ivec2 xRCCorner =\n            ivec2(coords["+v+"], coords["+m+"]) * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+l+"; wR++) {\n          int xR = xRCorner + wR * "+u+";\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+h+"; wC++) {\n            int xC = xCCorner + wC * "+c+";\n\n            if (xC < 0 || xC >= "+t.inWidth+") {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < "+f+"; d1 += 4) {\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              if ("+d+") {\n                vec4 xValues = vec4(\n                  getX(batch, xR, xC, d1),\n                  getX(batch, xR, xC, d1 + 1),\n                  getX(batch, xR, xC, d1 + 2),\n                  getX(batch, xR, xC, d1 + 3)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec4 xValues = vec4(\n                  getX(batch, d1, xR, xC),\n                  getX(batch, d1 + 1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if ("+(1==p)+") {\n\n              if ("+d+") {\n                dotProd +=\n                    getX(batch, xR, xC, "+f+") *\n                    getW(wR, wC, "+f+", d2);\n              } else {\n                dotProd +=\n                    getX(batch, "+f+", xR, xC) *\n                    getW(wR, wC, "+f+", d2);\n              }\n\n            } else if ("+(2==p)+") {\n              vec2 wValues = vec2(\n                getW(wR, wC, "+f+", d2),\n                getW(wR, wC, "+f+" + 1, d2)\n              );\n\n              if ("+d+") {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, "+f+"),\n                  getX(batch, xR, xC, "+f+" + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, "+f+", xR, xC),\n                  getX(batch, "+f+" + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if ("+(3==p)+") {\n              vec3 wValues = vec3(\n                getW(wR, wC, "+f+", d2),\n                getW(wR, wC, "+f+" + 1, d2),\n                getW(wR, wC, "+f+" + 2, d2)\n              );\n\n              if ("+d+") {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, "+f+"),\n                  getX(batch, xR, xC, "+f+" + 1),\n                  getX(batch, xR, xC, "+f+" + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, "+f+", xR, xC),\n                  getX(batch, "+f+" + 1, xR, xC),\n                  getX(batch, "+f+" + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        "+b+"\n        "+x+"\n        setOutput(result);\n      }\n    "},Ci=function(t){this.variableNames=["x","W"],this.outputShape=t.outShape;var e=t.padInfo.front,n=t.padInfo.top,r=t.padInfo.left,o=t.strideDepth,i=t.strideHeight,a=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.filterDepth,h=t.filterHeight,f=t.filterWidth,p=4*Math.floor(t.inChannels/4),d=t.inChannels%4;this.userCode="\n      const ivec3 strides = ivec3("+o+", "+i+", "+a+");\n      const ivec3 pads = ivec3("+e+", "+n+", "+r+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+l+"; wF++) {\n          int xF = xFCorner + wF * "+s+";\n\n          if (xF < 0 || xF >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+h+"; wR++) {\n            int xR = xRCorner + wR * "+u+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+f+"; wC++) {\n              int xC = xCCorner + wC * "+c+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < "+p+"; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if ("+(1==d)+") {\n                dotProd +=\n                  getX(batch, xF, xR, xC, "+p+") *\n                  getW(wF, wR, wC, "+p+", d2);\n              } else if ("+(2==d)+") {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, "+p+"),\n                  getX(batch, xF, xR, xC, "+p+" + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, "+p+", d2),\n                  getW(wF, wR, wC, "+p+" + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if ("+(3==d)+") {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, "+p+"),\n                  getX(batch, xF, xR, xC, "+p+" + 1),\n                  getX(batch, xF, xR, xC, "+p+" + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, "+p+", d2),\n                  getW(wF, wR, wC, "+p+" + 1, d2),\n                  getW(wF, wR, wC, "+p+" + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Ei=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.outputShape=t.outShape;var o=t.inHeight,i=t.inWidth,a=t.padInfo.top,s=t.padInfo.left,u=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,p=t.filterWidth,d=t.outChannels/t.inChannels,v="",m="";n&&(v=r?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"\n          float activation(float x) {\n            "+n+"\n          }\n        ",m="result = activation(result);");var g=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+v+"\n\n      const ivec2 strides = ivec2("+u+", "+c+");\n      const ivec2 pads = ivec2("+a+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / "+d+";\n        int q = d2 - d1 * "+d+";\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < "+f+"; wR++) {\n          int xR = xRCorner + wR * "+l+";\n\n          if (xR < 0 || xR >= "+o+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+p+"; wC++) {\n            int xC = xCCorner + wC * "+h+";\n\n            if (xC < 0 || xC >= "+i+") {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n\n        float result = dotProd;\n        "+g+"\n        "+m+"\n        setOutput(result);\n      }\n    "},_i=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.outShape;for(var o=t.inHeight,i=t.inWidth,a=t.padInfo.top,s=t.padInfo.left,u=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,p=t.filterWidth,d=p,v="int xR; int xC; int xCOffset;",m=0;m<f;m++)for(var g=0;g<p;g++)v+="\n          vec4 xTexelR"+m+"C"+2*g+" = vec4(0.);\n          vec4 wR"+m+"C"+g+" = vec4(0.);\n          vec4 xR"+m+"C"+g+" = vec4(0.);";for(m=0;m<f;m++)for(var y=0;y<d;y++){if(v+="\n          xR = xRCorner + "+m*l+";\n          xC = xCCorner + "+(g=2*y)*h+";\n        ",1===c){if(g<p&&(v+=s%2==1?"\n                xCOffset = xC + 1;\n                if(xR >= 0 && xR < "+o+" && xCOffset >= 0 && xCOffset < "+i+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                xCOffset = xC + 1 - 2;\n                if(xR >= 0 && xR < "+o+" && xCOffset >= 0 && xCOffset < "+i+") {\n                  vec4 previous = getX(batch, xR, xCOffset, d1);\n                  xR"+m+"C"+g+" = vec4(previous.zw, xTexelR"+m+"C"+g+".xy);\n                } else {\n                  xR"+m+"C"+g+" = vec4(0, 0, xTexelR"+m+"C"+g+".xy);\n                }\n              ":"\n                if(xR >= 0 && xR < "+o+" && xC >= 0 && xC < "+i+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                xR"+m+"C"+g+" = xTexelR"+m+"C"+g+";\n              ",g+1<p)){var x=s%2==0?E(h):h;h%2==0&&s%2==1||h%2!=0&&s%2!=1?(v+="\n                  xCOffset = xC + "+s%2+" + "+x+";\n\n                  if(xR >= 0 && xR < "+o+" &&\n                    xCOffset >= 0 && xCOffset < "+i+") {\n                    xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n                ",1<h&&(v+="\n                    xCOffset -= 2;\n                    if(xR >= 0 && xR < "+o+" &&\n                      xCOffset >= 0 && xCOffset < "+i+") {\n                      xTexelR"+m+"C"+g+" = getX(batch, xR, xCOffset, d1);\n                    } else {\n                      xTexelR"+m+"C"+g+" = vec4(0.);\n                    }\n                  "),v+="\n                  xR"+m+"C"+(g+1)+" = vec4(\n                    xTexelR"+m+"C"+g+".zw, xTexelR"+m+"C"+(g+2)+".xy);\n                "):v+="\n                  xCOffset = xC + "+x+";\n\n                  if(xR >= 0 && xR < "+o+" &&\n                    xCOffset >= 0 && xCOffset < "+i+") {\n                    xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n\n                  xR"+m+"C"+(g+1)+" = xTexelR"+m+"C"+(g+2)+";\n                "}}else g<p&&(v+="\n              if(xR >= 0 && xR < "+o+") {\n            ",s%2==1?(v+="\n                xCOffset = xC + 1 - "+c+";\n                if(xCOffset >= 0 && xCOffset < "+i+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < "+i+") {\n                  xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xC + 1, d1);\n                } else {\n                  xTexelR"+m+"C"+(g+2)+" = vec4(0.);\n                }\n\n                xR"+m+"C"+g+" = vec4(\n                  xTexelR"+m+"C"+g+".zw, xTexelR"+m+"C"+(g+2)+".zw);\n              ",g+1<p&&(v+="\n                  vec4 final = vec4(0.);\n                  xCOffset = xC + 1 + "+c+";\n                  if(xCOffset >= 0 && xCOffset < "+i+") {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xR"+m+"C"+(g+1)+" = vec4(xTexelR"+m+"C"+(g+2)+".xy, final.xy);\n                ")):(v+="\n                if(xC >= 0 && xC < "+i+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                xCOffset = xC + "+c+";\n                if(xCOffset >= 0 && xCOffset < "+i+") {\n                  xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+m+"C"+(g+2)+" = vec4(0.);\n                }\n\n                xR"+m+"C"+g+" = vec4(\n                  xTexelR"+m+"C"+g+".xy, xTexelR"+m+"C"+(g+2)+".xy);\n              ",g+1<p&&(v+="\n                  xR"+m+"C"+(g+1)+" = vec4(\n                    xTexelR"+m+"C"+g+".zw, xTexelR"+m+"C"+(g+2)+".zw);\n                ")),v+="}");g<p&&(v+="\n            vec4 wTexelR"+m+"C"+g+" = getW("+m+", "+g+", d1, q);\n            wR"+m+"C"+g+" = vec4(wTexelR"+m+"C"+g+".xz, wTexelR"+m+"C"+g+".xz);\n          ",g+1<p&&(v+="\n              vec4 wTexelR"+m+"C"+(g+1)+" = getW("+m+", "+(g+1)+", d1, q);\n              wR"+m+"C"+(g+1)+" =\n                vec4(wTexelR"+m+"C"+(g+1)+".xz, wTexelR"+m+"C"+(g+1)+".xz);"))}for(m=0;m<f;m++)for(g=0;g<p;g++)v+="dotProd += xR"+m+"C"+g+" * wR"+m+"C"+g+";";var b="",w="";n&&(b=r?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"vec4 activation(vec4 x) {\n          "+n+"\n        }",w="result = activation(result);");var C=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+b+"\n\n      const ivec2 strides = ivec2("+u+", "+c+");\n      const ivec2 pads = ivec2("+a+", "+s+");\n\n      void main() {\n\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2;\n        int q = 0;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        vec4 dotProd = vec4(0.);\n\n        "+v+"\n\n        vec4 result = dotProd;\n        "+C+"\n        "+w+"\n        setOutput(result);\n      }\n    "},Ii=function(t,e,n,r,o){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];var i=t[0],a=t[1],s=t[2],u=t[3],c=e[0],l=n[0],h=n[1];this.outputShape=[c,l,h,u];var f="bilinear"===r?1:0,p=[a-1+".0",s-1+".0"],d=p[0],v=p[1],m=1<l?[""+(a-1)/(l-1),"(y2-y1) * height_ratio","y1*"+d+" + float(y)*(height_scale)"]:["0.0","0.0","0.5 * (y1+y2) * "+d],g=m[0],y=m[1],x=m[2],b=1<h?[""+(s-1)/(h-1),"(x2-x1) * width_ratio","x1*"+v+" + float(x)*(width_scale)"]:["0.0","0.0","0.5 * (x1+x2) * "+v],w=b[0],C=b[1],E=b[2];this.userCode="\n      const float height_ratio = float("+g+");\n      const float width_ratio = float("+w+");\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n        float x2 = getBoxes(b,3);\n\n        // get image in batch index\n        int bInd = round(getBoxInd(b));\n        if(bInd < 0 || bInd >= "+i+") {\n          return;\n        }\n\n        float height_scale = "+y+";\n        float width_scale = "+C+";\n\n        float in_y = "+x+";\n        if( in_y < 0.0 || in_y > "+d+" ) {\n          setOutput(float("+o+"));\n          return;\n        }\n        float in_x = "+E+";\n        if( in_x < 0.0 || in_x > "+v+" ) {\n          setOutput(float("+o+"));\n          return;\n        }\n\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\n        if("+f+" == 1) {\n          // Compute the four integer indices.\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    "},Ri=function(t,e,n){this.variableNames=["x"];var r=(this.outputShape=t).length,o=t[t.length-1],i=n?"<":">";this.userCode="\n      int getIndex(int i) {\n        "+(n?"return "+o+" -i - 1;":"return i;")+"\n      }\n\n      void main() {\n        "+qo(r)+" coords = getOutputCoords();\n        int end = "+ki(r,"coords")+";\n        float val = 0.0;\n        for (int i = "+o+" - 1; i >= 0; i -= 1) {\n          int idx = getIndex(i);\n          if (idx "+i+" end) {\n            continue;\n          }\n          if (idx == end && "+e+") {\n            continue;\n          }\n          "+ki(r,"coords")+" = idx;\n          val += getX("+function(t,e){if(1===r)return e;if(2===r)return e+".x, "+e+".y";if(3===r)return"coords.x, coords.y, coords.z";if(4===r)return"coords.x, coords.y, coords.z, coords.w";throw Error("Cumulative sum for rank "+r+" is not yet supported")}(0,"coords")+");\n        }\n        setOutput(val);\n      }\n    "};function ki(t,e){if(1===t)return""+e;if(2===t)return e+".y";if(3===t)return e+".z";if(4===t)return e+".w";throw Error("Cumulative sum for rank "+t+" is not yet supported")}var Si=function(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=qt.DENSE;var e=ne(t),n=Lo();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+Wo(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getA(rc.x, rc.y, rc.z);\n        }\n\n        "+n.output+" = result;\n      }\n    "},Di=function(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=qt.DENSE;var e=ne(t),n=Lo();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+Wo(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\n        }\n\n        "+n.output+" = result;\n      }\n    "},Ai=(zi.prototype.getHeightCoordString=function(){return"NHWC"===this.dataFormat?"coords[1]":"coords[2]"},zi.prototype.getWidthCoordString=function(){return"NHWC"===this.dataFormat?"coords[2]":"coords[3]"},zi.prototype.getDepthCoordString=function(){return"NHWC"===this.dataFormat?"coords[3]":"coords[1]"},zi.prototype.getOutputDepthSize=function(){return"NHWC"===this.dataFormat?this.outputShape[3]:this.outputShape[1]},zi.prototype.getInputSamplingString=function(){return"NHWC"===this.dataFormat?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"},zi),Ti=function(t){this.variableNames=["X"],this.outputShape=[t,t],this.userCode="\n      void main() {\n          ivec2 coords = getOutputCoords();\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\n          setOutput(val);\n      }\n    "},Fi=function(t){this.variableNames=["A"],this.outTexUsage=jt.DOWNLOAD;var e=Lo();this.outputShape=t,this.userCode="\n      "+Uo+"\n\n      void main() {\n        float x = getAAtOutCoords();\n        "+e.output+" = encode_float(x);\n      }\n    "},Ni=function(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=jt.DOWNLOAD;var e=Lo();this.outputShape=t,this.userCode="\n      "+Uo+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n        "+e.output+" = encode_float(x);\n      }\n    "},Mi=function(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"];var r=Lo(),o=e[0],i=e[1];this.outputShape=t;var a="result";n&&(a="floor(result * 255. + 0.5)"),this.userCode="\n      "+zo(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        int flatIndex = getFlatIndex(coords);\n        int offset = imod(flatIndex, 4);\n\n        flatIndex = idiv(flatIndex, 4, 1.);\n        \n        int r = flatIndex / "+i+";\n        int c = imod(flatIndex, "+i+");\n        vec2 uv = (vec2(c, r) + halfCR) / vec2("+i+".0, "+o+".0);\n        vec4 values = "+r.texture2D+"(A, uv);\n\n        float result;\n\n        if(offset == 0) {\n          result = values[0];\n        } else if(offset == 1) {\n          result = values[1];\n        } else if(offset == 2) {\n          result = values[2];\n        } else {\n          result = values[3];\n        }\n\n        "+r.output+" = vec4("+a+", 0., 0., 0.);\n      }\n    "},Oi=function(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var r=Lo(),o=e[0],i=e[1];this.outputShape=t;var a="",s="result";n&&(s="floor(result * 255. + 0.5)");for(var u=0;u<=1;u++)for(var c=0;c<=1;c++){var l=2*u+c;a+="\n          localCoords = coords;\n          if(localCoords[2] + "+c+" < "+t[2]+") {\n            localCoords[2] += "+c+";\n            if(localCoords[1] + "+u+" < "+t[1]+") {\n              localCoords[1] += "+u+";\n\n              flatIndex = getFlatIndex(localCoords);\n              offset = imod(flatIndex, 4);\n\n              flatIndex = idiv(flatIndex, 4, 1.);\n\n              r = flatIndex / "+i+";\n              c = imod(flatIndex, "+i+");\n              uv = (vec2(c, r) + halfCR) / vec2("+i+".0, "+o+".0);\n              values = "+r.texture2D+"(A, uv);\n\n              if(offset == 0) {\n                result["+l+"] = values[0];\n              } else if(offset == 1) {\n                result["+l+"] = values[1];\n              } else if(offset == 2) {\n                result["+l+"] = values[2];\n              } else {\n                result["+l+"] = values[3];\n              }\n            }\n          }\n        "}this.userCode="\n      "+zo(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        vec4 result = vec4(0.);\n        int flatIndex, r, c, offset;\n        ivec3 localCoords;\n        vec2 uv;\n        vec4 values;\n\n        "+a+"\n\n        "+r.output+" = "+s+";\n      }\n    "},Pi=function(t,e,n){this.variableNames=["real","imag"];var r=e[1];this.outputShape=e;var o=n?"2.0 * "+Math.PI:"-2.0 * "+Math.PI,i=n?r+".0":"1.0";this.userCode="\n      const float exponentMultiplier = "+o+";\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        "+t+"\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float("+r+");\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < "+r+"; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / "+i+";\n        }\n\n        return result;\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        setOutput(mulMatDFT(coords[0], coords[1]));\n      }\n    "},Bi=(Wi.prototype.getCustomSetupFunc=function(n){var r=this;return function(t,e){null==r.valueLoc&&(r.valueLoc=t.getUniformLocationNoThrow(e,"value")),t.gl.uniform1f(r.valueLoc,n)}},Wi),Li=function(t,e,n){this.variableNames=["A","indices"];var r=t.slice();r[n]=e,this.outputShape=r,this.rank=r.length;var o=qo(this.rank),i=function(t,e){var n=t.length;if(4<n)throw Error("Gather for rank "+n+" is not yet supported");if(1===n)return"int(getIndices(resRC))";for(var r=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],i=0;i<t.length;i++)i===e?o.push("int(getIndices("+r[i]+"))"):o.push(""+r[i]);return o.join()}(t,n);this.userCode="\n      void main() {\n        "+o+" resRC = getOutputCoords();\n        setOutput(getA("+i+"));\n      }\n    "};function Wi(t,e){this.outputShape=[],this.variableNames=["x"],this.outputShape=t,this.userCode="\n      uniform float value;\n      void main() {\n        // Input can be obtained from uniform value.\n        setOutput(value);\n      }\n    "}function zi(t,e,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=t,this.blockSize=e,this.dataFormat=n,this.userCode="\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = "+this.getHeightCoordString()+";\n      int w = "+this.getWidthCoordString()+";\n      int d = "+this.getDepthCoordString()+";\n\n      int in_h = h / "+e+";\n      int offset_h = imod(h, "+e+");\n      int in_w = w / "+e+";\n      int offset_w = imod(w, "+e+");\n      int offset_d = (offset_h * "+e+" + offset_w) *\n        "+this.getOutputDepthSize()+";\n      int in_d = d + offset_d;\n\n      float result = "+this.getInputSamplingString()+";\n      setOutput(result);\n    }\n  "}var Ui=function(t,e,n){this.sliceDim=t,this.strides=e,this.variableNames=["x","indices"],this.outputShape=n;var r=qo(e.length),o=qo(n.length),i=1<this.sliceDim?"strides[j]":"strides";this.userCode="\n        "+r+" strides = "+r+"("+this.strides+");\n         void main() {\n          "+o+" coords = getOutputCoords();\n          int flattenIndex = 0;\n          for (int j = 0; j < "+this.sliceDim+"; j++) {\n            int index = round(getIndices(coords[0], j));\n            flattenIndex += index * "+i+";\n          }\n          setOutput(getX(flattenIndex, coords[1]));\n        }\n      "};function Vi(t,e){var n=Lo();return ce(t,e,n.version+"\n    precision highp float;\n    "+n.attribute+" vec3 clipSpacePos;\n    "+n.attribute+" vec2 uv;\n    "+n.varyingVs+" vec2 resultUV;\n\n    void main() {\n      gl_Position = vec4(clipSpacePos, 1);\n      resultUV = uv;\n    }")}function Gi(t,e){return ge(t,e,new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]))}function Hi(t,e){return ye(t,e,new Uint16Array([0,1,2,2,1,3]))}function qi(t,e,n,r,o,i,a){be(n,r);var s=xe(t,e),u=t.TEXTURE_2D;return ie(t,e,function(){return t.bindTexture(u,s)}),ie(t,e,function(){return t.texParameteri(u,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE)}),ie(t,e,function(){return t.texParameteri(u,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE)}),ie(t,e,function(){return t.texParameteri(u,t.TEXTURE_MIN_FILTER,t.NEAREST)}),ie(t,e,function(){return t.texParameteri(u,t.TEXTURE_MAG_FILTER,t.NEAREST)}),ie(t,e,function(){return t.texImage2D(u,0,o,n,r,0,i,a,null)}),ie(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)}),s}function ji(t,e,n,r,o){var i=ee(n,r);return qi(t,e,i[0],i[1],o.internalFormatFloat,o.textureFormatFloat,t.FLOAT)}function Ki(t,e,n,r,o){var i=ee(n,r);return qi(t,e,i[0],i[1],o.internalFormatHalfFloat,o.textureFormatFloat,o.textureTypeHalfFloat)}function Xi(t,e,n,r,o){var i=ee(n,r);return qi(t,e,i[0],i[1],t.RGBA,t.RGBA,t.UNSIGNED_BYTE)}function $i(t,e,n,r,o){var i=re(n,r);return qi(t,e,i[0],i[1],o.internalFormatPackedFloat,t.RGBA,t.FLOAT)}function Yi(t,e,n,r,o){var i=re(n,r);return qi(t,e,i[0],i[1],o.internalFormatPackedHalfFloat,t.RGBA,o.textureTypeHalfFloat)}function Ji(t,e,n,r){return ie(t,e,function(){return t.bindBuffer(t.ARRAY_BUFFER,r)}),Ce(t,e,n,"clipSpacePos",r,3,20,0)&&Ce(t,e,n,"uv",r,2,20,12)}function Qi(t,e,n,r,o,i,a){var s,u,c;ie(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),c=i instanceof Uint8Array?(s=new Uint8Array(r*o*4),u=t.UNSIGNED_BYTE,t.RGBA):(s=new Float32Array(r*o*4),u=t.FLOAT,a.internalFormatPackedFloat),s.set(i),ie(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,c,r,o,0,t.RGBA,u,s)}),ie(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)})}function Zi(t,e,n,r){ie(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),r.data instanceof Uint8Array?ie(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,r.width,r.height,0,t.RGBA,t.UNSIGNED_BYTE,r.data)}):ie(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,r)}),ie(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)})}function ta(t,e,n,r,o){var i=t.createBuffer();ie(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,i)});var a=16*n*r;return ie(t,e,function(){return t.bufferData(t.PIXEL_PACK_BUFFER,a,t.STREAM_READ)}),ie(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,0)}),ie(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,null)}),i}function ea(t,e,n){var r=t,o=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,e),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,o),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),o}function na(t,e,n,r,o){var i=ee(n,r),a=i[0],s=i[1],u=new Uint8Array(n*r*4);return ie(t,e,function(){return t.readPixels(0,0,a,s,o.downloadTextureFormat,t.UNSIGNED_BYTE,u)}),new Float32Array(u.buffer)}function ra(t,e,n,r,o,i,a,s){var u,c=t,l=new Float32Array((u=re(i,a))[0]*u[1]*4);return c.bindBuffer(c.PIXEL_PACK_BUFFER,e),c.getBufferSubData(c.PIXEL_PACK_BUFFER,0,l),c.bindBuffer(c.PIXEL_PACK_BUFFER,null),l}function oa(t,e,n,r){var o=new Float32Array(n*r*4);return ie(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,o)}),o}var ia=Object.freeze({createVertexShader:Vi,createVertexBuffer:Gi,createIndexBuffer:Hi,createFloat32MatrixTexture:ji,createFloat16MatrixTexture:Ki,createUnsignedBytesMatrixTexture:Xi,createPackedMatrixTexture:$i,createFloat16PackedMatrixTexture:Yi,bindVertexProgramAttributeStreams:Ji,uploadDenseMatrixToTexture:Qi,uploadPixelDataToTexture:Zi,createBufferFromOutputTexture:ta,downloadFloat32MatrixFromBuffer:ea,downloadByteEncodedFloatMatrixFromOutputTexture:na,downloadPackedMatrixFromBuffer:ra,downloadMatrixFromPackedOutputTexture:oa}),aa=(Object.defineProperty(sa.prototype,"debug",{get:function(){return _().getBool("DEBUG")},enumerable:!0,configurable:!0}),sa.prototype.dispose=function(){var t=this;if(!this.disposed){null!=this.program&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),null!=this.outputTexture&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");var e=this.gl;ie(e,this.debug,function(){return e.finish()}),ie(e,this.debug,function(){return e.bindFramebuffer(e.FRAMEBUFFER,null)}),ie(e,this.debug,function(){return e.deleteFramebuffer(t.framebuffer)}),ie(e,this.debug,function(){return e.bindBuffer(e.ARRAY_BUFFER,null)}),ie(e,this.debug,function(){return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)}),ie(e,this.debug,function(){return e.deleteBuffer(t.indexBuffer)}),this.disposed=!0}},sa.prototype.createFloat32MatrixTexture=function(t,e){return this.throwIfDisposed(),ji(this.gl,this.debug,t,e,this.textureConfig)},sa.prototype.createFloat16MatrixTexture=function(t,e){return this.throwIfDisposed(),Ki(this.gl,this.debug,t,e,this.textureConfig)},sa.prototype.createUnsignedBytesMatrixTexture=function(t,e){return this.throwIfDisposed(),Xi(this.gl,this.debug,t,e,this.textureConfig)},sa.prototype.uploadPixelDataToTexture=function(t,e){this.throwIfDisposed(),Zi(this.gl,this.debug,t,e)},sa.prototype.uploadDenseMatrixToTexture=function(t,e,n,r){this.throwIfDisposed(),Qi(this.gl,this.debug,t,e,n,r,this.textureConfig)},sa.prototype.createFloat16PackedMatrixTexture=function(t,e){return this.throwIfDisposed(),Yi(this.gl,this.debug,t,e,this.textureConfig)},sa.prototype.createPackedMatrixTexture=function(t,e){return this.throwIfDisposed(),$i(this.gl,this.debug,t,e,this.textureConfig)},sa.prototype.deleteMatrixTexture=function(t){var e=this;this.throwIfDisposed(),this.outputTexture===t&&(Se(this.gl,this.debug,this.framebuffer),this.outputTexture=null),ie(this.gl,this.debug,function(){return e.gl.deleteTexture(t)})},sa.prototype.downloadByteEncodedFloatMatrixFromOutputTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return na(r.gl,r.debug,e,n,r.textureConfig)})},sa.prototype.downloadPackedMatrixFromBuffer=function(t,e,n,r,o,i){return ra(this.gl,t,0,0,0,o,i,this.textureConfig)},sa.prototype.downloadFloat32MatrixFromBuffer=function(t,e){return ea(this.gl,t,e)},sa.prototype.createBufferFromTexture=function(t,e,n){this.bindTextureToFrameBuffer(t);var r=ta(this.gl,this.debug,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r},sa.prototype.createAndWaitForFence=function(){var t=this.createFence(this.gl);return this.pollFence(t)},sa.prototype.createFence=function(t){var e,n,r=this;if(_().getBool("WEBGL_FENCE_API_ENABLED")){var o=t,i=o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE,0);t.flush(),n=function(){var t=o.clientWaitSync(i,0,0);return t===o.ALREADY_SIGNALED||t===o.CONDITION_SATISFIED},e=i}else n=0<_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?(e=this.beginQuery(),this.endQuery(),function(){return r.isQueryAvailable(e,_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}):function(){return!0};return{query:e,isFencePassed:n}},sa.prototype.downloadMatrixFromPackedTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return oa(r.gl,r.debug,e,n)})},sa.prototype.createProgram=function(t){this.throwIfDisposed();var e=this.gl,n=le(e,this.debug,t),r=Vi(e,this.debug),o=de(e,this.debug);return ie(e,this.debug,function(){return e.attachShader(o,r)}),ie(e,this.debug,function(){return e.attachShader(o,n)}),ve(e,this.debug,o),this.debug&&me(e,this.debug,o),this.vertexAttrsAreBound||(this.setProgram(o),this.vertexAttrsAreBound=Ji(e,this.debug,this.program,this.vertexBuffer)),o},sa.prototype.deleteProgram=function(t){var e=this;this.throwIfDisposed(),t===this.program&&(this.program=null),null!=t&&ie(this.gl,this.debug,function(){return e.gl.deleteProgram(t)})},sa.prototype.setProgram=function(t){var e=this;this.throwIfDisposed(),this.program=t,null!=this.program&&this.debug&&me(this.gl,this.debug,this.program),ie(this.gl,this.debug,function(){return e.gl.useProgram(t)})},sa.prototype.getUniformLocation=function(t,e,n){return void 0===n&&(n=!0),this.throwIfDisposed(),n?_e(this.gl,this.debug,t,e):Ie(this.gl,t,e)},sa.prototype.getAttributeLocation=function(t,e){var n=this;return this.throwIfDisposed(),ie(this.gl,this.debug,function(){return n.gl.getAttribLocation(t,e)})},sa.prototype.getUniformLocationNoThrow=function(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)},sa.prototype.setInputMatrixTexture=function(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),Re(this.gl,this.debug,this.program,t,e,n)},sa.prototype.setOutputMatrixTexture=function(t,e,n){this.setOutputMatrixTextureDriver(t,n,e)},sa.prototype.setOutputPackedMatrixTexture=function(t,e,n){this.throwIfDisposed();var r=re(e,n),o=r[0],i=r[1];this.setOutputMatrixTextureDriver(t,o,i)},sa.prototype.setOutputMatrixWriteRegion=function(t,e,n,r){this.setOutputMatrixWriteRegionDriver(n,t,r,e)},sa.prototype.setOutputPackedMatrixWriteRegion=function(t,e,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")},sa.prototype.debugValidate=function(){null!=this.program&&me(this.gl,this.debug,this.program),De(this.gl)},sa.prototype.executeProgram=function(){this.throwIfDisposed(),this.throwIfNoProgram();var t=this.gl;this.debug&&this.debugValidate(),ie(t,this.debug,function(){return t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0)})},sa.prototype.blockUntilAllProgramsCompleted=function(){var t=this;this.throwIfDisposed(),ie(this.gl,this.debug,function(){return t.gl.finish()})},sa.prototype.getQueryTimerExtension=function(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=ue(this.gl,this.debug,2===_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension},sa.prototype.getQueryTimerExtensionWebGL2=function(){return this.getQueryTimerExtension()},sa.prototype.getQueryTimerExtensionWebGL1=function(){return this.getQueryTimerExtension()},sa.prototype.beginQuery=function(){if(2===_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var t=this.gl,e=this.getQueryTimerExtensionWebGL2(),n=t.createQuery();return t.beginQuery(e.TIME_ELAPSED_EXT,n),n}var r=this.getQueryTimerExtensionWebGL1(),o=r.createQueryEXT();return r.beginQueryEXT(r.TIME_ELAPSED_EXT,o),o},sa.prototype.endQuery=function(){if(2!==_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var t=this.getQueryTimerExtensionWebGL1();t.endQueryEXT(t.TIME_ELAPSED_EXT)}else{var e=this.gl,n=this.getQueryTimerExtensionWebGL2();e.endQuery(n.TIME_ELAPSED_EXT)}},sa.prototype.waitForQueryAndGetTime=function(n){return y(this,void 0,void 0,function(){var e=this;return R(this,function(t){switch(t.label){case 0:return[4,w(function(){return e.disposed||e.isQueryAvailable(n,_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))})];case 1:return t.sent(),[2,this.getQueryTime(n,_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))]}})})},sa.prototype.getQueryTime=function(t,e){if(0===e)return null;if(2===e){var n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}var r=this.getQueryTimerExtensionWebGL1();return r.getQueryObjectEXT(t,r.QUERY_RESULT_EXT)/1e6},sa.prototype.isQueryAvailable=function(t,e){if(0===e)return!0;if(2!==e)return o=(r=this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(t,r.QUERY_RESULT_AVAILABLE_EXT),null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint;var n=this.gl,r=this.getQueryTimerExtensionWebGL2(),o=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint},sa.prototype.pollFence=function(e){var n=this;return new Promise(function(t){n.addItemToPoll(function(){return e.isFencePassed()},function(){return t()})})},sa.prototype.pollItems=function(){for(var t=function(t){for(var e=0;e<t.length&&t[e]();++e);return e-1}(this.itemsToPoll.map(function(t){return t.isDoneFn})),e=0;e<=t;++e)(0,this.itemsToPoll[e].resolveFn)();this.itemsToPoll=this.itemsToPoll.slice(t+1)},sa.prototype.addItemToPoll=function(t,e){var n=this;this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),1<this.itemsToPoll.length||w(function(){return n.pollItems(),0===n.itemsToPoll.length})},sa.prototype.bindTextureToFrameBuffer=function(t){this.throwIfDisposed(),ke(this.gl,this.debug,t,this.framebuffer),this.debug&&De(this.gl)},sa.prototype.unbindTextureToFrameBuffer=function(){null!=this.outputTexture?(ke(this.gl,this.debug,this.outputTexture,this.framebuffer),this.debug&&De(this.gl)):Se(this.gl,this.debug,this.framebuffer)},sa.prototype.downloadMatrixDriver=function(t,e){this.bindTextureToFrameBuffer(t);var n=e();return this.unbindTextureToFrameBuffer(),n},sa.prototype.setOutputMatrixTextureDriver=function(t,e,n){this.throwIfDisposed();var r=this.gl;ke(r,this.debug,t,this.framebuffer),this.debug&&De(r),this.outputTexture=t,ie(r,this.debug,function(){return r.viewport(0,0,e,n)}),ie(r,this.debug,function(){return r.scissor(0,0,e,n)})},sa.prototype.setOutputMatrixWriteRegionDriver=function(t,e,n,r){var o=this;this.throwIfDisposed(),ie(this.gl,this.debug,function(){return o.gl.scissor(t,e,n,r)})},sa.prototype.throwIfDisposed=function(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")},sa.prototype.throwIfNoProgram=function(){if(null==this.program)throw new Error("No GPU program is currently set.")},sa);function sa(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];var e=_().getNumber("WEBGL_VERSION");null!=t?Zt(e,this.gl=t):this.gl=te(e);var n="WEBGL_color_buffer_float";if(1===_().getNumber("WEBGL_VERSION")){if(this.textureFloatExtension=ue(this.gl,this.debug,"OES_texture_float"),Ve(this.gl,"OES_texture_half_float"))this.textureHalfFloatExtension=ue(this.gl,this.debug,"OES_texture_half_float");else if(_().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Ve(this.gl,"EXT_color_buffer_half_float"))this.colorBufferHalfFloatExtension=ue(this.gl,this.debug,"EXT_color_buffer_half_float");else if(_().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Ve(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else{if(!Ve(this.gl,"EXT_color_buffer_half_float"))throw new Error("GL context does not support color renderable floats");this.colorBufferHalfFloatExtension=this.gl.getExtension("EXT_color_buffer_half_float")}this.vertexBuffer=Gi(this.gl,this.debug),this.indexBuffer=Hi(this.gl,this.debug),this.framebuffer=we(this.gl,this.debug),this.textureConfig=oe(this.gl,this.textureHalfFloatExtension)}function ua(t,s){if(t.length!==s.length)throw Error("Binary was compiled with "+t.length+" inputs, but was executed with "+s.length+" inputs");t.forEach(function(t,e){var n=t.logicalShape,r=s[e],o=r.shape;if(!D(n,o))throw Error("Binary was compiled with different shapes than the current args. Shapes "+n+" and "+o+" must match");if(!t.isUniform||!r.isUniform){var i=t.texShape,a=r.isUniform?null:r.texData.texShape;if(!D(i,a))throw Error("Binary was compiled with different texture shapes than the current args. Shape "+i+" and "+a+" must match")}})}var ca=function(t,e,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var r=n.filterWidth,o=n.inChannels,i=n.strideWidth,a=n.strideHeight,s=n.padInfo,u=n.outWidth,c=n.dilationWidth,l=n.dilationHeight,h=n.dataFormat,f=s.left,p=s.top,d=o*r,v=Lo(),m="channelsLast"===h,g=m?0:1,y=m?1:2,x="",b=0;b<=1;b++)for(var w=0;w<=1;w++)x+="\n          blockIndex = rc.y + "+w+";\n          pos = rc.x + "+b+";\n\n          if(blockIndex < "+t[1]+" && pos < "+t[0]+") {\n            offsetY = int(blockIndex / ("+u+")) * "+a+" - "+p+";\n            d0 = offsetY + "+l+" * (pos / "+d+");\n\n            if(d0 < "+e[g]+" && d0 >= 0) {\n\n              offsetX = int(mod(float(blockIndex), "+u+".) * "+i+". - "+f+".);\n              d1 = offsetX + "+c+" * (int(mod(float(pos), "+d+".) / "+o+".));\n\n              if(d1 < "+e[y]+" && d1 >= 0) {\n\n                ch = int(mod(float(pos), "+o+".));\n\n                if ("+m+") {\n                  innerDims = vec2(d1, ch);\n                  result["+(2*b+w)+"] = getChannel(\n                    getA(d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result["+(2*b+w)+"] = getChannel(\n                    getA(ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        ";this.userCode="\n      void main() {\n        ivec2 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        "+x+"\n\n        "+v.output+" = result;\n      }\n    "},la=function(t,e,n,r,o){this.variableNames=["x"],this.outputShape=[];var i,a=e,s=t[3]-1;this.outputShape=t;var u="float("+n+") + float("+r+") * sum";i=.5===o?"inversesqrt("+u+")":1===o?"1.0/("+u+")":"exp(log("+u+") * float(-"+o+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -"+a+"; j <= "+a+"; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  "+s+") {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * "+i+";\n        setOutput(val);\n      }\n    "},ha=function(t,e,n,r,o){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=r,this.beta=o,this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < "+this.depth+"; ++d) {\n          int depthBegin = int(max(0.0, float(d - "+e+")));\n          int depthEnd = int(min(float("+this.depth+"),\n              float(d + "+e+" + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = "+this.depth+";\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float("+r+") * norm + float("+n+");\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float("+r+")\n                * float("+o+")\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * "+o+");\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    "},fa=function(t,e,n,r,o){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;var i,a=e,s=t[3]-1;this.outputShape=t;var u="float("+n+") + float("+r+") * sum";i=.5===o?"inversesqrt("+u+")":1===o?"1.0/("+u+")":"exp(log("+u+") * float(-"+o+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < "+this.outputShape[3]+";\n        bool hasNextRow = c < "+this.outputShape[2]+";\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - "+a+";\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - "+a+"; j <= "+a+"; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2("+s+"));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * "+i+";\n        setOutput(result);\n      }\n    "},pa=function(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideHeight,n=t.strideWidth,r=t.dilationHeight,o=t.effectiveFilterHeight,i=t.effectiveFilterWidth,a=o-1-t.padInfo.top,s=i-1-t.padInfo.left,u=o*i-1;this.userCode="\n      const ivec2 pads = ivec2("+a+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+o+";\n          wR += "+r+") {\n          float dyR = float(dyRCorner + wR) / "+e+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+i+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+n+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = "+u+" - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * "+i+" + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},da=function(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.dilationDepth,i=t.dilationHeight,a=t.dilationWidth,s=t.effectiveFilterDepth,u=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=s-1-t.padInfo.front,h=u-1-t.padInfo.top,f=c-1-t.padInfo.left,p=s*u*c-1;this.userCode="\n      const ivec3 pads = ivec3("+l+", "+h+", "+f+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+s+";\n           wD += "+o+") {\n          float dyD = float(dyDCorner + wD) / "+e+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+u+";\n              wR += "+i+") {\n            float dyR = float(dyRCorner + wR) / "+n+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+c+";\n                wC += "+a+") {\n              float dyC = float(dyCCorner + wC) / "+r+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = "+p+" -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * "+u+" * "+c+" +\n                  wR * "+c+" + wC;\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n              dotProd += dyValue * mask;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},va=function(t,e,n,r,o,i,a){void 0===n&&(n=!1),void 0===r&&(r=!1),void 0===o&&(o=!1),void 0===i&&(i=null),void 0===a&&(a=!1),this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;var s=n?t[1]:t[2],u=Math.ceil(s/2),c=n?"i * 2, rc.y":"rc.y, i * 2",l=r?"rc.z, i * 2":"i * 2, rc.z",h=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],p="",d="";i&&(p=a?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          "+i+"\n        }":"vec4 activation(vec4 x) {\n          "+i+"\n        }",d="result = activation(result);");var v=o?"result += getBiasAtOutCoords();":"";o&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+p+"\n\n      const float sharedDimension = "+u+".0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < "+u+"; i++) {\n          vec4 a = getMatrixA(rc.x, "+c+");\n          vec4 b = getMatrixB(rc.x, "+l+");\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += ("+h[0]+" * "+f[0]+");\n          result += ("+h[1]+" * "+f[1]+");\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        "+v+"\n\n        "+d+"\n\n        setOutput(result);\n      }\n    "},ma=(xa.prototype.getCustomSetupFunc=function(n){var r=this;return function(t,e){null==r.seedLoc&&(r.seedLoc=t.getUniformLocation(e,"seed")),t.gl.uniform1f(r.seedLoc,n)}},xa),ga=function(t,e,n,r){this.variableNames=["indices"],this.outputShape=[t,e],this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float("+r+"), float("+n+"),\n                      float(index == coords.y)));\n      }\n    "},ya=function(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var e,n,r,o,i=(this.outputShape=t).length;if(0===i)this.userCode="\n        void main() {\n          setOutput(vec4(getA(), 0., 0., 0.));\n        }\n      ";else{var a=Bo("rc",i),s=qo(i),u=function(t,e,n){if(1===t)return"rc > "+e[0];for(var r="",o=t-2;o<t;o++)r+=n[o]+" >= "+e[o],o<t-1&&(r+="||");return r}(i,t,a),c=function(t,e,n){if(1===t)return"";var r=a.slice(-2);return"\n    int r = "+r[0]+";\n    int c = "+r[1]+";\n    int rp1 = r + 1;\n    int cp1 = c + 1;\n\n    bool cEdge = cp1 >= "+e+";\n    bool rEdge = rp1 >= "+n+";\n  "}(i,t[t.length-1],t[t.length-2]),l=(n=a,r=(e=t).length,o=function(t,e){for(var n=[],r=0;r<=1;r++)for(var o=0;o<=1;o++){for(var i=(0===r?"r":"rp1")+", "+(0===o?"c":"cp1"),a=2;a<t;a++)i=e[e.length-1-a]+","+i;n.push(i)}return n}(r,n),1===r?"getA(rc),\n            rc + 1 >= "+e[0]+" ? 0. : getA(rc + 1),\n            0, 0":"getA("+o[0]+"),\n          cEdge ? 0. : getA("+o[1]+"),\n          rEdge ? 0. : getA("+o[2]+"),\n          rEdge || cEdge ? 0. : getA("+o[3]+")");this.userCode="\n        void main() {\n          "+s+" rc = getOutputCoords();\n\n          if("+u+") {\n            setOutput(vec4(0));\n          } else {\n            "+c+"\n\n            setOutput(vec4("+l+"));\n          }\n        }\n      "}};function xa(t,e,n){this.variableNames=["probs"],this.outputShape=[t,n],this.userCode="\n      uniform float seed;\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < "+(e-1)+"; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float("+(e-1)+"));\n      }\n    "}var ba=function(n,t,e){this.variableNames=["x"],this.outputShape=t.map(function(t,e){return t[0]+n[e]+t[1]});var r=n.length,o=qo(r),i=t.map(function(t){return t[0]}).join(","),a=t.map(function(t,e){return t[0]+n[e]}).join(","),s=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);this.userCode=1!==r?"\n      "+o+" start = "+o+"("+i+");\n      "+o+" end = "+o+"("+a+");\n\n      void main() {\n        "+o+" outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(float("+e+"));\n        } else {\n          "+o+" coords = outC - start;\n          setOutput(getX("+s+"));\n        }\n      }\n    ":"\n        int start = "+i+";\n        int end = "+a+";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(float("+e+"));\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      "},wa=function(n,t,e){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map(function(t,e){return t[0]+n[e]+t[1]});for(var r=n.length,o=qo(r),i=t.map(function(t){return t[0]}).join(","),a=t.map(function(t,e){return t[0]+n[e]}).join(","),s=Bo("rc",r),u=Bo("source",r),c=s[r-1]+" < "+this.outputShape[r-1],l=1===r?"source":"vec2("+u.slice(-2).join()+")",h=[o+" rc = outputLoc;",s[r-1]+" += 1;\n       if("+c+") {\n      ",1===r?"":"}\n       rc = outputLoc;\n       "+s[r-2]+" += 1;\n       if("+s[r-2]+" < "+this.outputShape[r-2]+") {",1===r?"":"  "+s[r-1]+" += 1;\n         if("+c+") {"],f=1===r?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="",d=0,v=1===r?2:4;d<v;d++)p+="\n        "+h[d]+"\n        if ("+f+") {\n          result["+d+"] = float("+e+");\n        } else {\n          "+o+" source = rc - start;\n          result["+d+"] = getChannel(getX("+u.join()+"), "+l+");\n        }\n      ";p+=1===r?"} ":"}}",this.userCode="\n      const "+o+" start = "+o+"("+i+");\n      const "+o+" end = "+o+"("+a+");\n\n      void main() {\n        "+o+" outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        "+p+"\n        setOutput(result);\n      }\n    "},Ca=function(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,o=t.strideHeight,i=t.strideWidth,a=t.dilationHeight,s=t.dilationWidth,u=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=t.padInfo.top,h=t.padInfo.left;this.outputShape=t.outShape;var f="avg"===e,p="0.0";if(f||(p="-1.0 / 1e-20"),n)this.userCode="\n        const ivec2 strides = ivec2("+o+", "+i+");\n        const ivec2 pads = ivec2("+l+", "+h+");\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < "+u+";\n              wR += "+a+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+c+";\n                wC += "+s+") {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value >= currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = wR * "+c+" + wC;\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else{var d=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(d="avgValue / count");var v=4*Math.floor(r/4),m=r%4,g="\n      if ("+f+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec2 strides = ivec2("+o+", "+i+");\n      const ivec2 pads = ivec2("+l+", "+h+");\n      const float initializationValue = "+p+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+p+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < "+u+";\n            wR += "+a+") {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+v+"; wC += 4) {\n            int xC = xCCorner + wC * "+s+";\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              getValue(batch, xR, xC + 2 * "+s+", d),\n              getValue(batch, xR, xC + 3 * "+s+", d)\n            );\n\n            "+g+"\n          }\n\n          int xC = xCCorner + "+v+";\n          if ("+(1==m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            "+g+"\n          } else if ("+(2==m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              initializationValue,\n              initializationValue\n            );\n\n            "+g+"\n          } else if ("+(3==m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              getValue(batch, xR, xC + 2 * "+s+", d),\n              initializationValue\n            );\n\n            "+g+"\n          }\n        }\n        setOutput("+d+");\n      }\n    "}},Ea=function(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,o=t.strideDepth,i=t.strideHeight,a=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,p=t.padInfo.front,d=t.padInfo.top,v=t.padInfo.left;this.outputShape=t.outShape;var m="avg"===e,g="0.0";if(m||(g="-1.0 / 1e-20"),n)this.userCode="\n        const ivec3 strides =\n            ivec3("+o+", "+i+", "+a+");\n        const ivec3 pads = ivec3("+p+", "+d+", "+v+");\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < "+l+";\n              wD += "+s+") {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int wR = 0; wR < "+h+";\n                wR += "+u+") {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int wC = 0; wC < "+f+";\n                  wC += "+c+") {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value >= currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;\n                  minMaxPosition =\n                      wD * "+h+" * "+f+" +\n                      wR * "+f+" + wC;;\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else{var y=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(y="avgValue / count");var x=4*Math.floor(r/4),b=r%4,w="\n      if ("+m+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec3 strides =\n        ivec3("+o+", "+i+", "+a+");\n      const ivec3 pads = ivec3("+p+", "+d+", "+v+");\n      const float initializationValue = "+g+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+g+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < "+l+";\n            wD += "+s+") {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+h+";\n            wR += "+u+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+x+"; wC += 4) {\n              int xC = xCCorner + wC * "+c+";\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+c+", ch),\n                getValue(batch, xD, xR, xC + 3 * "+c+", ch)\n              );\n\n              "+w+"\n            }\n\n            int xC = xCCorner + "+x+";\n            if ("+(1==b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(2==b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(3==b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+c+", ch),\n                initializationValue\n              );\n\n              "+w+"\n            }\n          }\n          setOutput("+y+");\n        }\n      }\n    "}},_a=function(t,e){this.variableNames=["x"];var n=t.windowSize,r=t.batchSize,o=t.inSize,i=Math.ceil(o/n);this.outputShape=[r,i];var a="0.0",s="";"prod"===e?a="1.0":"min"===e?(a="1.0 / 1e-20",s="min"):"max"===e&&(a="-1.0 / 1e-20",s="max");var u=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"sum"===e?u="sumValue":"prod"===e?u="prodValue":"all"===e?u="allValue":"any"===e&&(u="anyValue");var c=4*Math.floor(n/4),l=n%4,h="\n      if ("+("sum"===e)+") {\n        sumValue += dot(values, ones);\n      } else if ("+("prod"===e)+") {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = "+s+"(values, minMaxValue);\n      }\n    ",f="vec4";"all"===e?(a="1.0",h="\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      ",f="bvec4"):"any"===e&&(a="0.0",h="\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      ",f="bvec4");var p="";0<o%n&&(p="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return initializationValue;\n        }\n      "),this.userCode="\n      const float initializationValue = "+a+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        "+p+"\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * "+n+";\n\n        vec4 minMaxValue = vec4("+a+");\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < "+c+"; i += 4) {\n          int inIdx = inOffset + i;\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          "+h+"\n        }\n\n        int inIdx = inOffset + "+c+";\n        if ("+(1==l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          "+h+"\n        } else if ("+(2==l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          "+h+"\n        } else if ("+(3==l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          "+h+"\n        }\n        setOutput("+u+");\n      }\n    "},Ia=function(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var n="",r=0;r<4;r++){var o="thisRC = rc;";r%2==1&&(o+="thisRC.z += 1;"),1<r&&(o+="thisRC.y += 1;"),n+="\n        "+o+"\n        "+(0<r?"if(thisRC.y < rows && thisRC.z < cols){":"")+"\n          int flatIndex = getFlatIndex(thisRC);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result["+r+"] =\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n        "+(0<r?"}":"")+"\n      "}this.userCode="\n      \n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      "+Wo(["r","c","d"],e)+"\n      return ivec3(r, c, d);\n    }\n  \n      "+zo(t)+"\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.);\n\n        ivec3 thisRC;\n        int rows = "+t[1]+";\n        int cols = "+t[2]+";\n\n        "+n+"\n\n        setOutput(result);\n      }\n    "},Ra=function(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],i=r[2],a=t.shape,s=a[1],u=a[2],c=[n&&1<s?o-1:o,n&&1<u?i-1:i],l=[n&&1<s?s-1:s,n&&1<u?u-1:u],h=c[0]/l[0],f=c[1]/l[1],p=1/h,d=1/f,v=2*Math.ceil(p)+2,m=2*Math.ceil(d)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+h+");\n        const float widthScale = float("+f+");\n\n        const float invHeightScale = float("+p+");\n        const float invWidthScale = float("+d+");\n\n        const int winHeight = int("+v+");\n        const int winWidth = int("+m+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+s+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+u+") {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), "+(o-1)+".0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), "+(i-1)+".0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    "},ka=function(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var o=t[0],i=t[1],a=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&1<e?i-1:i,r&&1<n?a-1:a],c=[r&&1<e?e-1:e,r&&1<n?n-1:n];this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/c[0]+",\n          "+u[1]/c[1]+");\n      const vec2 inputShapeRC = vec2("+i+".0, "+a+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    "},Sa=function(t,e,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var o=t[0],i=t[1],a=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&1<e?i-1:i,r&&1<n?a-1:a],c=[r&&1<e?e-1:e,r&&1<n?n-1:n];this.userCode="\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          "+u[0]/c[0]+",\n          "+u[1]/c[1]+",\n          "+u[1]/c[1]+");\n      const vec3 inputShapeRC = vec3("+i+".0, "+a+".0,\n                                     "+a+".0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < "+(s-1)+";\n        bool hasNextRow = coords.z < "+(n-1)+";\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    "},Da=function(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],i=r[2],a=t.shape,s=a[1],u=a[2],c=[n&&1<s?o-1:o,n&&1<u?i-1:i],l=[n&&1<s?s-1:s,n&&1<u?u-1:u],h=c[0]/l[0],f=c[1]/l[1],p=1/h,d=1/f,v=2*Math.ceil(p)+2,m=2*Math.ceil(d)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+h+");\n        const float widthScale = float("+f+");\n\n        const float invHeightScale = float("+p+");\n        const float invWidthScale = float("+d+");\n\n        const int winHeight = int("+v+");\n        const int winWidth = int("+m+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+s+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+u+") {\n              continue;\n            }\n\n            float sourceFracRow =\n              float("+c[0]+") *\n                (float(dyR) / float("+l[0]+"));\n\n            float sourceFracCol =\n                float("+c[1]+") *\n                  (float(dyC) / float("+l[1]+"));\n\n            int sourceNearestRow = int(min(\n                float(int("+o+") - 1),\n                "+n+" ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int("+i+") - 1),\n                "+n+" ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    "},Aa=function(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var o=t[0],i=t[1],a=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&1<e?i-1:i,r&&1<n?a-1:a],c=[r&&1<e?e-1:e,r&&1<n?n-1:n],l=r?"0.5":"0.0";this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/c[0]+",\n          "+u[1]/c[1]+");\n      const vec2 inputShapeRC = vec2("+i+".0, "+a+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + "+l+")));\n\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    "},Ta=function(r,o){this.variableNames=["x"];var t=r.length;if(4<t)throw new Error("WebGL backend: Reverse of rank-"+t+" tensor is not yet supported");if(this.outputShape=r,1!==t){var e=r.map(function(t,e){return n=e,-1!==o.indexOf(n)&&1!==r[n]?r[n]+" - coords["+n+"] - 1":"coords["+n+"]";var n}).join(","),n=qo(t);this.userCode="\n      void main() {\n        "+n+" coords = getOutputCoords();\n        setOutput(getX("+e+"));\n      }\n    "}else this.userCode="\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX("+r[0]+" - coord - 1));\n        }\n      "},Fa=function(i,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;var t=i.length;if(4<t)throw new Error("WebGL backend: Reverse of rank-"+t+" tensor is not yet supported");this.outputShape=i;var e,n,r,o=Bo("rc",t),s=o[t-1]+" + 1 < "+this.outputShape[t-1],u=o[t-2]+" + 1 < "+this.outputShape[t-2],c=qo(t);function l(o){var t=i.map(function(t,e){return n=e,r=o,-1!==a.indexOf(n)&&1!==i[n]?i[n]+" - "+r[n]+" - 1":""+r[n];var n,r});return"getChannel(getX("+t.join(",")+"), vec2("+t.slice(-2).join(",")+"))"}this.userCode=1===t?"\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX("+i[0]+" - rc - 1),\n            "+i[0]+" - rc - 1);\n          if("+s+"){\n              result.g = getChannel(getX("+i[0]+" - (rc  + 1) - 1),\n                "+i[0]+" - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      ":"\n        void main() {\n          "+c+" rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = "+l(o.slice())+";\n          if("+s+"){\n            result.g = "+((r=o.slice())[t-1]="("+r[t-1]+" + 1)",l(r))+";\n          }\n          if("+u+") {\n            result.b = "+((n=o.slice())[t-2]="("+n[t-2]+" + 1)",l(n))+";\n            if("+s+") {\n              result.a = "+((e=o.slice())[t-1]="("+e[t-1]+" + 1)",e[t-2]="("+e[t-2]+" + 1)",l(e))+";\n            }\n          }\n          setOutput(result);\n        }\n    "},Na=function(t,e,n,r,o,i,a){this.variableNames=["updates","indices","defaultValue"],this.outputShape=i;var s=qo(o.length),u=qo(i.length),c="";1===n?c="i":2===n&&(c="i, j");var l="getIndices("+c+")",h="";1===r?h="i":2===r&&(h="i, coords[1]");var f="getUpdates("+h+")",p=1<e?"strides[j]":"strides";this.userCode="\n        "+s+" strides = "+s+"("+o+");\n\n        void main() {\n          "+u+" coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < "+t+"; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < "+e+"; j++) {\n              int index = round("+l+");\n              flattenedIndex += index * "+p+";\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += "+f+";\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      "},Ma=function(t,e){this.variableNames=["x","segmentIds"];var n=t.windowSize,r=t.batchSize,o=t.inSize,i=t.numSegments,a=i*Math.ceil(o/n);this.outputShape=[r,a];var s=4*Math.floor(n/4),u=n%4,c="\n        sumValue += dot(values, segFilter);\n    ",l="";0<o%n&&(l="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return initializationValue;\n        }\n      ");var h="";0<o%n&&(h="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return -1.0;\n        }\n      "),this.userCode="\n      const float initializationValue = 0.0;\n\n      float getValue(int batch, int inIdx) {\n        "+l+"\n        return getX(batch, inIdx);\n      }\n\n      float getSegmentIdAtIndex(int inIdx) {\n        "+h+"\n        return getSegmentIds(inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = int(floor(float(outIdx) / float(\n          "+i+")) * float("+n+"));\n        int currentSeg = int(mod(float(outIdx), float("+i+")));\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < "+s+"; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n          );\n\n          "+c+"\n        }\n\n        int inIdx = inOffset + "+s+";\n        if ("+(1==u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            0,\n            0,\n            0\n          );\n\n          "+c+"\n        } else if ("+(2==u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n              0,\n              0\n          );\n\n          "+c+"\n        } else if ("+(3==u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            0\n          );\n\n          "+c+"\n        }\n        setOutput(sumValue);\n      }\n    "},Oa=function(t,e,n){var r,o;if(this.variableNames=["c","a","b"],this.outputShape=e,4<n)throw Error("Where for rank "+n+" is not yet supported");if(1===n)r=o="resRC";else{for(var i=["resRC.x","resRC.y","resRC.z","resRC.w"],a=[],s=[],u=0;u<e.length;u++)s.push(""+i[u]),u<t&&a.push(""+i[u]);r=a.join(),o=s.join()}var c=qo(n);this.userCode="\n      void main() {\n        "+c+" resRC = getOutputCoords();\n        float cVal = getC("+r+");\n        if (cVal >= 1.0) {\n          setOutput(getA("+o+"));\n        } else {\n          setOutput(getB("+o+"));\n        }\n      }\n    "},Pa=(La.prototype.getCustomSetupFunc=function(n){var r=this;if(n.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+n.length+")");return function(t,e){null==r.startLoc&&(r.startLoc=t.getUniformLocationNoThrow(e,"start"),null==r.startLoc)||t.gl.uniform1iv(r.startLoc,n)}},La),Ba=["x","y","z","w","u","v"];function La(t){this.variableNames=["source"],this.outputShape=t,this.rank=t.length;var e,n=qo(this.rank),r="uniform int start["+this.rank+"];",o=function(t){if(1===t)return"sourceLoc";if(t<=6)return Ba.slice(0,t).map(function(t){return"sourceLoc."+t}).join(",");throw Error("Slicing for rank "+t+" is not yet supported")}(this.rank);e="\n        "+n+" sourceLoc;\n        "+n+" coords = getOutputCoords();\n        "+t.map(function(t,e){return"sourceLoc."+Ba[e]+" = start["+e+"] + coords."+Ba[e]+";"}).join("\n")+"\n      ",this.userCode="\n      "+r+"\n      void main() {\n        "+e+"\n        setOutput(getSource("+o+"));\n      }\n    "}var Wa=(Ga.prototype.getCustomSetupFunc=function(n){var r=this;if(n.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+n.length+")");return function(t,e){null==r.startLoc&&(r.startLoc=t.getUniformLocationNoThrow(e,"start"),null==r.startLoc)||t.gl.uniform1iv(r.startLoc,n)}},Ga),za=function(t,e,n){this.variableNames=["x"];var r=(this.outputShape=n).length,o=qo(n.length),i=qo(n.length),a="";if(1===r)a="coords * strides + begin";else{var s=0;a=n.map(function(t,e){return s++,1===n.length?"coords * strides["+e+"] + begin["+e+"]":"coords["+(s-1)+"] * strides["+e+"] + begin["+e+"]"}).join(",")}this.userCode="\n      "+o+" begin = "+o+"("+t+");\n      "+o+" strides = "+o+"("+e+");\n\n      void main() {\n        "+i+" coords = getOutputCoords();\n        setOutput(getX("+a+"));\n      }\n    "},Ua=(Va.prototype.acquireTexture=function(t,e,n){var r,o=Ha(e,n),i=qa(t,o,n);if(i in this.freeTextures||(this.freeTextures[i]=[]),i in this.usedTextures||(this.usedTextures[i]=[]),0<this.freeTextures[i].length){this.numFreeTextures--,this.numUsedTextures++,this.log();var a=this.freeTextures[i].shift();return this.usedTextures[i].push(a),a}return this.numUsedTextures++,this.log(),o===Kt.PACKED_2X2_FLOAT32?r=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Kt.PACKED_2X2_FLOAT16?r=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Kt.UNPACKED_FLOAT32?r=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Kt.UNPACKED_FLOAT16?r=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Kt.PACKED_4X1_UNSIGNED_BYTE&&(r=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[i].push(r),r},Va.prototype.releaseTexture=function(t,e,n,r){if(null!=this.freeTextures){var o=qa(e,Ha(n,r),r);o in this.freeTextures||(this.freeTextures[o]=[]),this.freeTextures[o].push(t),this.numFreeTextures++,this.numUsedTextures--;var i=this.usedTextures[o],a=i.indexOf(t);if(a<0)throw new Error("Cannot release a texture that was never provided by this texture manager");i.splice(a,1),this.log()}},Va.prototype.log=function(){if(this.logEnabled){var t=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",this.numFreeTextures+" / "+this.numUsedTextures,"("+t+")")}},Va.prototype.getNumUsedTextures=function(){return this.numUsedTextures},Va.prototype.getNumFreeTextures=function(){return this.numFreeTextures},Va.prototype.dispose=function(){var e=this;if(null!=this.freeTextures){for(var t in this.freeTextures)this.freeTextures[t].forEach(function(t){e.gpgpu.deleteMatrixTexture(t)});for(var t in this.usedTextures)this.usedTextures[t].forEach(function(t){e.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0}},Va);function Va(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}function Ga(t){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length;var e=qo(this.rank),n=Bo("coords",this.rank),r=Bo("sourceLoc",this.rank),o=1===this.rank?"sourceLoc":"vec2("+r.slice(-2).join()+")",i="getChannel(getSource("+r.join()+"), "+o+")",a="\n      result.x = "+i+";\n      if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n        ++"+r[this.rank-1]+";\n        result.y = "+i+";\n        --"+r[this.rank-1]+";\n      }\n    ",s=1===this.rank?"":"\n      --"+n[this.rank-1]+";\n      if (++"+n[this.rank-2]+" < "+t[this.rank-2]+") {\n        ++"+r[this.rank-2]+";\n        result.z = "+i+";\n        if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n          ++"+r[this.rank-1]+";\n          result.w = "+i+";\n        }\n      }\n    ",u=this.rank<=4?"sourceLoc = coords +\n            "+e+"("+t.map(function(t,e){return"start["+e+"]"}).join()+");":t.map(function(t,e){return r[e]+" = "+n[e]+" + start["+e+"];"}).join("\n");this.userCode="\n      uniform int start["+this.rank+"];\n      void main() {\n        "+e+" coords = getOutputCoords();\n        "+e+" sourceLoc;\n        "+u+"\n        vec4 result = vec4(0.);\n        "+a+"\n        "+s+"\n        setOutput(result);\n      }\n    "}function Ha(t,e){if(t===jt.UPLOAD)return Kt.PACKED_2X2_FLOAT32;if(t===jt.RENDER||null==t)return n=e,_().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?n?Kt.PACKED_2X2_FLOAT32:Kt.UNPACKED_FLOAT32:n?Kt.PACKED_2X2_FLOAT16:Kt.UNPACKED_FLOAT16;var n;if(t===jt.DOWNLOAD||t===jt.PIXELS)return Kt.PACKED_4X1_UNSIGNED_BYTE;throw new Error("Unknown logical texture type "+t)}function qa(t,e,n){return t[0]+"_"+t[1]+"_"+e+"_"+n}var ja=function(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[r]*e[r];this.outputShape=n,this.rank=n.length;var o=qo(this.rank),i=function(t){var e=t.length;if(5<e)throw Error("Tile for rank "+e+" is not yet supported");if(1===e)return"imod(resRC, "+t[0]+")";for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[],o=0;o<t.length;o++)r.push("imod("+n[o]+", "+t[o]+")");return r.join()}(t);this.userCode="\n      void main() {\n        "+o+" resRC = getOutputCoords();\n        setOutput(getA("+i+"));\n      }\n    "},Ka=function(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];this.outputShape=n,this.rank=n.length;var o=qo(this.rank),i=function(t){var e=t.length;if(6<e)throw Error("Transpose for rank "+e+" is not yet supported");for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(e),o=0;o<t.length;o++)r[t[o]]=n[o];return r.join()}(e);this.userCode="\n    void main() {\n      "+o+" resRC = getOutputCoords();\n      setOutput(getA("+i+"));\n    }\n    "},Xa=function(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];if(this.outputShape=n,this.rank=n.length,6<this.rank)throw Error("Packed transpose for rank "+this.rank+" is not yet supported.");var o=qo(this.rank),i=Po("rc",this.rank),a=new Array(this.rank);for(r=0;r<e.length;r++)a[e[r]]=i[r];var s="vec2("+a.slice(-2).join()+")",u="++"+i[this.rank-1]+" < "+n[this.rank-1],c="getChannel(getA("+a.join()+"), "+s+")";this.userCode="\n    void main() {\n      "+o+" rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = "+c+";\n      if("+u+") {\n        result[1] = "+c+";\n      }\n      --"+i[this.rank-1]+";\n      if(++"+i[this.rank-2]+" < "+n[this.rank-2]+") {\n        result[2] = "+c+";\n        if("+u+") {\n          result[3] = "+c+";\n        }\n      }\n      setOutput(result);\n    }\n    "},$a=1.7580993408473768,Ya=1.0507009873554805,Ja=function(t,e){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      float unaryOperation(float x) {\n        "+e+"\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    "},Qa="if (isnan(x)) return x;",Za="return abs(x);",ts=Qa+"\n  return (x < 0.0) ? 0.0 : x;\n",es=Qa+"\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n",ns="return (x >= 0.0) ? x : (exp(x) - 1.0);",rs="return -x;",os="return ceil(x);",is="return floor(x);",as="return exp(x);",ss="return exp(x) - 1.0;",us="return x;",cs="\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",ls="\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",hs="\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n",fs=function(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode="\n      vec4 unaryOperation(vec4 x) {\n        "+e+"\n      }\n\n      void main() {\n        vec4 x = getAAtOutCoords();\n        vec4 y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    "},ps=function(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1;var e=(this.outputShape=t).length,n=Bo("rc",e),r=qo(e),o=function(t,e){if(1===t)return"rc";for(var n="",r=0;r<t;r++)n+=e[r],r<t-1&&(n+=",");return n}(e,n),i=n.slice(-2),a=e<=1?"rc":"vec2("+i.join(",")+")";this.userCode="\n      void main() {\n        "+r+" rc = getOutputCoords();\n        vec4 packedInput = getA("+o+");\n\n        setOutput(getChannel(packedInput, "+a+"));\n      }\n    "},ds={};function vs(t,e){if(void 0===e&&(e=!1),"linear"===t)return"return x;";if("relu"===t)return e?cs:ts;if("elu"===t)return e?hs:ns;if("relu6"===t)return e?ls:es;if("prelu"===t)return e?ii:ri;throw new Error("Activation "+t+" has not been implemented for the WebGL backend.")}var ms,gs=(t(ys,ms=eo),ys.prototype.numDataIds=function(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes},ys.prototype.write=function(t,e,n){if(_().getBool("DEBUG")&&this.checkNumericalProblems(t),"complex64"===n&&null!=t)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");var r={};return this.texData.set(r,{shape:e,dtype:n,values:t,usage:jt.UPLOAD}),r},ys.prototype.move=function(t,e,n,r){if(_().getBool("DEBUG")&&this.checkNumericalProblems(e),"complex64"===r)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:r,values:e,usage:jt.UPLOAD})},ys.prototype.readSync=function(t){var e=this.texData.get(t),n=e.values,r=e.dtype,o=e.complexTensors,i=e.slice,a=e.shape,s=e.isPacked;if(null!=i){var u;u=s?new fs(a,us):new Ja(a,us);var c=this.runWebGLProgram(u,[{dataId:t,shape:a,dtype:r}],r),l=this.readSync(c.dataId);return this.disposeData(c.dataId),l}if(null!=n)return this.convertAndCacheOnCPU(t);if("string"===r)return n;var h,f,p=null!=this.activeTimers;return p&&(h=J()),f="complex64"===r?Io(o.real.dataSync(),o.imag.dataSync()):this.getValuesFromTexture(t),p&&(this.downloadWaitMs+=J()-h),this.convertAndCacheOnCPU(t,f)},ys.prototype.read=function(E){return y(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p,d,v,m,g,y,x,b,w,C;return R(this,function(t){switch(t.label){case 0:if(this.pendingRead.has(E))return e=this.pendingRead.get(E),[2,new Promise(function(t){return e.push(t)})];if(n=this.texData.get(E),r=n.values,o=n.shape,i=n.slice,a=n.dtype,s=n.complexTensors,u=n.isPacked,null!=i)return c=u?new fs(o,us):new Ja(o,us),l=this.runWebGLProgram(c,[{dataId:E,shape:o,dtype:a}],a),h=this.read(l.dataId),this.disposeData(l.dataId),[2,h];if(null!=r)return[2,this.convertAndCacheOnCPU(E)];if(!_().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&2===_().getNumber("WEBGL_VERSION"))throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");return f=null,"complex64"!==a&&_().get("WEBGL_BUFFER_SUPPORTED")&&(p=this.decode(E),d=this.texData.get(p.dataId),f=(C=this.gpgpu).createBufferFromTexture.apply(C,[d.texture].concat(ne(o)))),this.pendingRead.set(E,[]),"complex64"===a?[3,2]:[4,this.gpgpu.createAndWaitForFence()];case 1:t.sent(),t.label=2;case 2:return"complex64"!==a?[3,4]:[4,Promise.all([s.real.data(),s.imag.data()])];case 3:return m=t.sent(),g=m[0],y=m[1],v=Io(g,y),[3,5];case 4:v=null==f?this.getValuesFromTexture(E):(x=L(o),this.gpgpu.downloadFloat32MatrixFromBuffer(f,x)),t.label=5;case 5:return null!=p&&this.disposeData(p.dataId),b=this.convertAndCacheOnCPU(E,v),w=this.pendingRead.get(E),this.pendingRead.delete(E),w.forEach(function(t){return t(b)}),this.pendingDisposal.has(E)&&(this.pendingDisposal.delete(E),this.disposeData(E),this.pendingDeletes--),[2,b]}})})},ys.prototype.checkNumericalProblems=function(t){if(null!=t)for(var e=0;e<t.length;e++){var n=t[e];if(!ae(n)){if(_().getBool("WEBGL_RENDER_FLOAT32_CAPABLE"))throw Error("The value "+n+" cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'");throw Error("The value "+n+" cannot be represented on this device.")}}},ys.prototype.getValuesFromTexture=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,i=n.isPacked,a=L(r);if(_().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){var s=this.decode(t),u=this.texData.get(s.dataId),c=(e=this.gpgpu).downloadMatrixFromPackedTexture.apply(e,[u.texture].concat(ne(r))).subarray(0,a);return this.disposeData(s.dataId),c}var l=_().getBool("WEBGL_PACK")&&!0===i,h=l?Oe(r):r,f=l?new Ni(h):new Fi(h),p=this.runWebGLProgram(f,[{shape:h,dtype:o,dataId:t}],"float32"),d=this.texData.get(p.dataId),v=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(d.texture,d.texShape[0],d.texShape[1]).subarray(0,a);return this.disposeData(p.dataId),v},ys.prototype.time=function(u){return y(this,void 0,void 0,function(){var e,n,r,o,i,a,s;return R(this,function(t){switch(t.label){case 0:return e=this.activeTimers,r=!(n=[]),null==this.programTimersStack?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,u(),o=d(this.activeTimers.map(function(t){return t.query})).filter(function(t){return null!=t}),i=d(this.activeTimers.map(function(t){return t.name})).filter(function(t){return null!=t}),this.activeTimers=e,r&&(this.programTimersStack=null),[4,Promise.all(o)];case 1:return a=t.sent(),s={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:f(a),getExtraProfileInfo:function(){return a.map(function(t,e){return{name:i[e],ms:t}}).map(function(t){return t.name+": "+t.ms}).join(", ")},wallMs:null},this.uploadWaitMs=0,this.downloadWaitMs=0,[2,s]}})})},ys.prototype.memory=function(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU}},ys.prototype.startTimer=function(){return 0<_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?this.gpgpu.beginQuery():{startMs:J(),endMs:null}},ys.prototype.endTimer=function(t){return 0<_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?this.gpgpu.endQuery():t.endMs=J(),t},ys.prototype.getQueryTime=function(n){return y(this,void 0,void 0,function(){var e;return R(this,function(t){return 0<_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?[2,this.gpgpu.waitForQueryAndGetTime(n)]:[2,(e=n).endMs-e.startMs]})})},ys.prototype.disposeData=function(t){if(!this.pendingDisposal.has(t)){if(this.pendingRead.has(t))return this.pendingDisposal.add(t),void this.pendingDeletes++;if(this.texData.has(t)){this.releaseGPUData(t);var e=this.texData.get(t).complexTensors;null!=e&&(e.real.dispose(),e.imag.dispose()),this.texData.delete(t)}}},ys.prototype.releaseGPUData=function(t){var e=this.texData.get(t),n=e.texture,r=e.dtype,o=e.texShape,i=e.usage,a=e.isPacked,s=e.slice,u=s&&s.origDataId||t,c=this.dataRefCount.get(u);1<c?this.dataRefCount.set(u,c-1):(this.dataRefCount.delete(u),null!=n&&(this.numBytesInGPU-=this.computeBytes(o,r),this.textureManager.releaseTexture(n,o,i,a)));var l=this.texData.get(t);l.texture=null,l.texShape=null,l.isPacked=!1,l.slice=null},ys.prototype.getTexture=function(t){return this.uploadToGPU(t),this.texData.get(t).texture},ys.prototype.getDataInfo=function(t){return this.texData.get(t)},ys.prototype.getCPUBackend=function(){return _().getBool("WEBGL_CPU_FORWARD")?(null==this.cpuBackend&&(this.cpuBackend=Vt.findBackend("cpu")),this.cpuBackend):null},ys.prototype.shouldExecuteOnCPU=function(t,e){var n=this;return void 0===e&&(e=128),null!=this.getCPUBackend()&&t.every(function(t){return null==n.texData.get(t.dataId).texture&&t.size<e})},ys.prototype.getGPGPUContext=function(){return this.gpgpu},ys.prototype.complex=function(t,e){var n=this.makeOutput(t.shape,"complex64");return this.texData.get(n.dataId).complexTensors={real:Vt.keep(t.clone()),imag:Vt.keep(e.clone())},n},ys.prototype.real=function(t){return this.texData.get(t.dataId).complexTensors.real.clone()},ys.prototype.imag=function(t){return this.texData.get(t.dataId).complexTensors.imag.clone()},ys.prototype.slice=function(t,e,n){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.slice(t,e,n);if(0===L(n))return bn([],n,t.dtype);var r=this.texData.get(t.dataId).isPacked,o=jr(t.shape,e,n);if(!r&&o)return this.uploadToGPU(t.dataId),this.shallowSlice(t,e,n);var i=_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Wa(n):new Pa(n),a=i.getCustomSetupFunc(e);return this.compileAndRun(i,[t],null,a)},ys.prototype.shallowSlice=function(t,e,n){var r=this.texData.get(t.dataId),o=this.makeOutput(n,t.dtype),i=this.texData.get(o.dataId);Object.assign(i,r),i.shape=n,i.dtype=t.dtype;var a=Kr(e,t.strides);r.slice&&(a+=r.slice.flatOffset),i.slice={flatOffset:a,origDataId:r.slice&&r.slice.origDataId||t.dataId};var s=this.dataRefCount.get(i.slice.origDataId)||1;return this.dataRefCount.set(i.slice.origDataId,s+1),o},ys.prototype.stridedSlice=function(t,e,n,r){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.stridedSlice(t,e,n,r);var o=Gr(e,n,r);if(o.some(function(t){return 0===t}))return bn([],o);var i=new za(e,r,o);return this.compileAndRun(i,[t])},ys.prototype.reverse=function(t,e){var n=_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Fa(t.shape,e):new Ta(t.shape,e);return this.compileAndRun(n,[t])},ys.prototype.concat=function(t,e){if("complex64"===t[0].dtype){var n=t.map(function(t){return yn(t)}),r=t.map(function(t){return xn(t)});return gn(this.concat(n,e),this.concat(r,e))}if(this.shouldExecuteOnCPU(t))return this.cpuBackend.concat(t,e);if(1===t.length)return t[0];if(t.length>_().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){var o=Math.floor(t.length/2),i=this.concat(t.slice(0,o),e),a=this.concat(t.slice(o),e);return this.concat([i,a],e)}if(_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&1<t[0].rank){var s=new hi(t.map(function(t){return t.shape}),e);return this.compileAndRun(s,t)}var u=vn(t.map(function(t){return t.shape}),e),c=t.map(function(t){return t.as2D(-1,L(t.shape.slice(e)))}),l=new li(c.map(function(t){return t.shape}));return this.compileAndRun(l,c).reshape(u)},ys.prototype.neg=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.neg(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,rs,t.dtype);var e=new Ja(t.shape,rs);return this.compileAndRun(e,[t])},ys.prototype.batchMatMul=function(t,e,n,r){var o=n?t.shape[2]:t.shape[1],i=r?e.shape[1]:e.shape[2],a=n?t.shape[1]:t.shape[2],s=t.shape[0];if((1===o||1===i)&&1e3<a){n&&(t=t.transpose([0,2,1])),r&&(e=e.transpose([0,2,1]));var u=1===i?t:t.as3D(s,a,1),c=1===i?2:1,l=1===i?e.as3D(s,1,a):e;return this.multiply(u,l).sum(c,!0)}var h=Tt(t.dtype,e.dtype),f=new va(t.shape,[s,o,i],n,r);return this.compileAndRun(f,[t,e],h)},ys.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,i=t.bias,a=t.activation,s=t.preluActivationWeights,u=r?e.shape[2]:e.shape[1],c=o?n.shape[1]:n.shape[2],l=e.shape[0],h=Tt(e.dtype,n.dtype),f=null!=i,p=null!=s,d=a?vs(a,!0):null,v=new va(e.shape,[l,u,c],r,o,f,d,p),m=[e,n];return i&&m.push(i),s&&m.push(s),this.compileAndRun(v,m,h)},ys.prototype.multiply=function(t,e){if("complex64"===t.dtype){var n=this.texData.get(t.dataId),r=this.texData.get(e.dataId),o=new Zo("return areal * breal - aimag * bimag;",t.shape,e.shape),i=new Zo("return areal * bimag + aimag * breal;",t.shape,e.shape),a=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag),this.makeComplexComponentTensorInfo(e,r.complexTensors.real),this.makeComplexComponentTensorInfo(e,r.complexTensors.imag)],s=this.compileAndRun(o,a),u=this.compileAndRun(i,a),c=this.complex(s,u);return s.dispose(),u.dispose(),c}if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.multiply(t,e);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,ni,t.dtype);var l=new oi(ni,t.shape,e.shape);return this.compileAndRun(l,[t,e],t.dtype)},ys.prototype.batchNormalization=function(t,e,n,r,o,i){var a=[t,e,n],s=null;null!=i&&(s=i.shape,a.push(i));var u=null;if(null!=o&&(u=o.shape,a.push(o)),_().getBool("WEBGL_PACK_NORMALIZATION")){var c=new Qo(t.shape,e.shape,n.shape,s,u,r);return this.compileAndRun(c,a)}var l=new Jo(t.shape,e.shape,n.shape,s,u,r);return this.compileAndRun(l,a)},ys.prototype.localResponseNormalization4D=function(t,e,n,r,o){var i=_().getBool("WEBGL_PACK_NORMALIZATION")?new fa(t.shape,e,n,r,o):new la(t.shape,e,n,r,o);return this.compileAndRun(i,[t])},ys.prototype.LRNGrad=function(t,e,n,r,o,i,a){var s=new ha(e.shape,r,o,i,a);return this.compileAndRun(s,[e,n,t])},ys.prototype.tile=function(t,e){if("string"===t.dtype){var n=this.readSync(t.dataId).map(function(t){return tt(t)});return Ao(or(t.shape,t.dtype,n),e)}var r=new ja(t.shape,e);return this.compileAndRun(r,[t])},ys.prototype.pad=function(t,e,n){var r=_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new wa(t.shape,e,n):new ba(t.shape,e,n);return this.compileAndRun(r,[t])},ys.prototype.transpose=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.transpose(t,e);var n=_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Xa(t.shape,e):new Ka(t.shape,e);return this.compileAndRun(n,[t])},ys.prototype.gather=function(t,e,n){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.gather(t,e,n);var r=new Li(t.shape,e.size,n);return this.compileAndRun(r,[t,e])},ys.prototype.batchToSpaceND=function(t,e,n){P(t.rank<=4,function(){return"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet"});var r=e.reduce(function(t,e){return t*e}),o=Nr(t.shape,e,r),i=Mr(o.length,e.length),a=Or(t.shape,e,r),s=Pr(n,e.length),u=Br(a,n,e.length);return t.reshape(o).transpose(i).reshape(a).slice(s,u)},ys.prototype.spaceToBatchND=function(t,e,n){P(t.rank<=4,function(){return"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet"});var r=e.reduce(function(t,e){return t*e}),o=[[0,0]];o.push.apply(o,n);for(var i=1+e.length;i<t.shape.length;++i)o.push([0,0]);var a=t.pad(o),s=Nr(a.shape,e,r,!1),u=Mr(s.length,e.length,!1),c=Or(a.shape,e,r,!1);return a.reshape(s).transpose(u).reshape(c)},ys.prototype.reduce=function(t,e,n){var r=t.shape[0],o=t.shape[1],i=Wr(o),a=new _a({windowSize:i,inSize:o,batchSize:r},e),s=this.compileAndRun(a,[t],n);return 1===s.shape[1]?s:this.reduce(s,e,n)},ys.prototype.argReduce=function(t,e,n){void 0===n&&(n=null);var r=t.shape[0],o=t.shape[1];null!=n&&(r=n.shape[0],o=n.shape[1]);var i=Wr(o),a=new Oo({windowSize:i,inSize:o,batchSize:r},e,null==n),s=[t];null!=n&&s.push(n);var u=this.compileAndRun(a,s,"int32");return 1===u.shape[1]?u:this.argReduce(t,e,u)},ys.prototype.argReducePacked=function(t,e,n){void 0===n&&(n=null);var r=null!=n?n.shape:t.shape,o=Wr(r[r.length-1]),i=new Xo(r,o,e,null==n),a=null==n?[t]:[t,n],s=this.compileAndRun(i,a,"int32");return s.rank===t.rank?this.argReducePacked(t,e,s):s},ys.prototype.sum=function(t,e){ln("sum",e,t.rank);var n=un(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o),a=Ft(t.dtype);return this.reduce(i,"sum",a).reshape(r)},ys.prototype.prod=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.prod(t,e);var n=un(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o),a=Ft(t.dtype);return this.reduce(i,"prod",a).reshape(r)},ys.prototype.unsortedSegmentSum=function(t,e,n){var r=0,o=hn([r],t.rank),i=t;null!=o&&(i=t.transpose(o),r=pn(1,t.rank)[0]);var a=function(t,e,n){for(var r=[],o=t.length,i=0;i<o;i++)i!==e?r.push(t[i]):r.push(n);return r}(i.shape,r,n),s=L([i.shape[r]]),u=i.as2D(-1,s),c=Ft(t.dtype),l=this.segOpCompute(u,"unsortedSegmentSum",e,c,n).reshape(a);return null!=o&&(l=l.transpose(fn(o))),l},ys.prototype.segOpCompute=function(t,e,n,r,o){var i=t.shape[0],a=t.shape[1],s=function(t,e){var n,r=!1;for(t<=30?(n=t,r=!0):n=q(t,Math.floor(Math.sqrt(t)));!r;)e<n||n===t?r=!0:n=q(t,n+1);return n}(a,o),u=new Ma({windowSize:s,inSize:a,batchSize:i,numSegments:o},e),c=this.compileAndRun(u,[t,n],r);return c.shape[1]===o?c:(n=Mn(0,o).tile([a/s]),this.segOpCompute(c,e,n,r,o))},ys.prototype.argMinMaxReduce=function(t,e,n){var r=[e];if(ln("arg"+n.charAt(0).toUpperCase()+n.slice(1),r,t.rank),!_().getBool("WEBGL_PACK_REDUCE")||t.rank<=2){var o=un(t.shape,r),i=o[0],a=L(o[1]),s=t.as2D(-1,a);return this.argReduce(s,n).reshape(i)}return this.argReducePacked(t,n)},ys.prototype.argMin=function(t,e){return this.argMinMaxReduce(t,e,"min")},ys.prototype.argMax=function(t,e){return this.argMinMaxReduce(t,e,"max")},ys.prototype.cumsum=function(t,e,n,r){if(e!==t.rank-1)throw new Error("WebGL cumsum shader expects an inner-most axis="+(t.rank-1)+" but got axis="+e);var o=new Ri(t.shape,n,r);return this.compileAndRun(o,[t])},ys.prototype.equal=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(equal(a, b));\n","bool");var n=new oi("return float(a == b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},ys.prototype.notEqual=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(notEqual(a, b));\n","bool");var n=new oi("return float(a != b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},ys.prototype.less=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.less(t,e);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(lessThan(a, b));\n","bool");var n=new oi("return float(a < b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},ys.prototype.lessEqual=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(lessThanEqual(a, b));\n","bool");var n=new oi("return float(a <= b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},ys.prototype.greater=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.greater(t,e);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(greaterThan(a, b));\n","bool");var n=new oi("return float(a > b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},ys.prototype.greaterEqual=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(greaterThanEqual(a, b));\n","bool");var n=new oi("return float(a >= b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},ys.prototype.logicalNot=function(t){var e=new Ja(t.shape,"return float(!(x >= 1.0));");return this.compileAndRun(e,[t])},ys.prototype.logicalAnd=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n","bool");var n=new oi("return float(a >= 1.0 && b >= 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},ys.prototype.logicalOr=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n","bool");var n=new oi("return float(a >= 1.0 || b >= 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},ys.prototype.select=function(t,e,n){var r=new Oa(t.rank,e.shape,e.rank);return this.compileAndRun(r,[t,e,n],Tt(e.dtype,n.dtype))},ys.prototype.where=function(t){tn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");var e=t.dataSync();return Fo(t.shape,e)},ys.prototype.topk=function(t,e,n){return To(t.dataSync(),t.shape,t.dtype,e)},ys.prototype.min=function(t,e){ln("min",e,t.rank);var n=un(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o);return this.reduce(i,"min",i.dtype).reshape(r)},ys.prototype.minimum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.minimum(t,e);var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ai("\n  vec4 result = vec4(min(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new oi("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return min(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},ys.prototype.mod=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ai("\n  vec4 result = mod(a, b);\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new oi("if (b == 0.0) return NAN;\n  return mod(a, b);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},ys.prototype.max=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.max(t,e);ln("max",e,t.rank);var n=un(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o);return this.reduce(i,"max",i.dtype).reshape(r)},ys.prototype.maximum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.maximum(t,e);var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ai("\n  vec4 result = vec4(max(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new oi("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return max(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},ys.prototype.all=function(t,e){ln("all",e,t.rank);var n=un(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o);return this.reduce(i,"all",i.dtype).reshape(r)},ys.prototype.any=function(t,e){ln("any",e,t.rank);var n=un(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o);return this.reduce(i,"any",i.dtype).reshape(r)},ys.prototype.squaredDifference=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ai("return (a - b) * (a - b);",t.shape,e.shape):new oi("return (a - b) * (a - b);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},ys.prototype.realDivide=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n","float32",!0);var n=new oi("\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;",t.shape,e.shape);return this.compileAndRun(n,[t,e],"float32")},ys.prototype.floorDiv=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    result[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    result[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    result[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    result[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4(result);\n","int32");var n=new oi("\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n",t.shape,e.shape);return this.compileAndRun(n,[t,e],"int32")},ys.prototype.add=function(t,e){if("complex64"===t.dtype&&"complex64"===e.dtype)return this.complexSeparableBinaryOp(t,e,ti);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.add(t,e);var n=Tt(t.dtype,e.dtype);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,ti,n);var r=new oi(ti,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},ys.prototype.packedUnaryOp=function(t,e,n){var r=new fs(t.shape,e);return this.compileAndRun(r,[t],n)},ys.prototype.packedBinaryOp=function(t,e,n,r,o){void 0===o&&(o=!1);var i=new ai(n,t.shape,e.shape,o);return this.compileAndRun(i,[t,e],r)},ys.prototype.complexSeparableBinaryOp=function(a,s,u){var c=this,t=this.texData.get(a.dataId),e=this.texData.get(s.dataId),n=[[t.complexTensors.real,e.complexTensors.real],[t.complexTensors.imag,e.complexTensors.imag]].map(function(t){var e=t[0],n=t[1],r=c.makeComplexComponentTensorInfo(a,e),o=c.makeComplexComponentTensorInfo(s,n),i=new oi(u,a.shape,s.shape);return c.compileAndRun(i,[r,o],Tt(e.dtype,n.dtype))}),r=n[0],o=n[1],i=this.complex(r,o);return r.dispose(),o.dispose(),i},ys.prototype.makeComplexComponentTensorInfo=function(t,e){return{dataId:e.dataId,dtype:e.dtype,shape:t.shape}},ys.prototype.addN=function(t){if(1===t.length)return t[0];if(t.length>_().get("WEBGL_MAX_TEXTURES_IN_SHADER")){var e=Math.floor(t.length/2),n=this.addN(t.slice(0,e)),r=this.addN(t.slice(e));return this.addN([n,r])}var o=t.map(function(t){return t.dtype}).reduce(function(t,e){return Tt(t,e)}),i=t.map(function(t){return t.shape}),a=_().getBool("WEBGL_PACK")?new Mo(t[0].shape,i):new No(t[0].shape,i);return this.compileAndRun(a,t,o)},ys.prototype.subtract=function(t,e){if("complex64"===t.dtype&&"complex64"===e.dtype)return this.complexSeparableBinaryOp(t,e,ei);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.subtract(t,e);var n=Tt(t.dtype,e.dtype);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,ei,t.dtype);var r=new oi(ei,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},ys.prototype.pow=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ai("\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new oi("\nif(a < 0.0 && floor(b) < b){\n  return NAN;\n}\nif (b == 0.0) {\n  return 1.0;\n}\nreturn (round(mod(b, 2.0)) != 1) ?\n    pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",t.shape,e.shape),r=Tt(t.dtype,e.dtype);return this.compileAndRun(n,[t,e],r)},ys.prototype.ceil=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.ceil(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,os,t.dtype);var e=new Ja(t.shape,os);return this.compileAndRun(e,[t])},ys.prototype.floor=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.floor(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,is,t.dtype);var e=new Ja(t.shape,is);return this.compileAndRun(e,[t])},ys.prototype.sign=function(t){var e=new Ja(t.shape,"\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n");return this.compileAndRun(e,[t])},ys.prototype.isNaN=function(t){var e=new Ja(t.shape,"return float(isnan(x));");return this.compileAndRun(e,[t],"bool")},ys.prototype.isInf=function(t){var e=new Ja(t.shape,"return float(isinf(x));");return this.compileAndRun(e,[t],"bool")},ys.prototype.isFinite=function(t){var e=new Ja(t.shape,"return float(!isnan(x) && !isinf(x));");return this.compileAndRun(e,[t],"bool")},ys.prototype.round=function(t){var e=new Ja(t.shape,"\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n");return this.compileAndRun(e,[t])},ys.prototype.exp=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.exp(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,as,t.dtype);var e=new Ja(t.shape,as);return this.compileAndRun(e,[t])},ys.prototype.expm1=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.expm1(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,ss,t.dtype);var e=new Ja(t.shape,ss);return this.compileAndRun(e,[t])},ys.prototype.log=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.log(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,"\n  vec4 result = log(x);\n  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\n\n  return result;\n",t.dtype);var e=new Ja(t.shape,"if (x < 0.0) return NAN;\n  return log(x);");return this.compileAndRun(e,[t])},ys.prototype.log1p=function(t){var e=new Ja(t.shape,"return log(1.0 + x);");return this.compileAndRun(e,[t])},ys.prototype.sqrt=function(t){var e=new Ja(t.shape,"return sqrt(x);");return this.compileAndRun(e,[t])},ys.prototype.rsqrt=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.rsqrt(t);var e=new Ja(t.shape,"return inversesqrt(x);");return this.compileAndRun(e,[t])},ys.prototype.reciprocal=function(t){var e=new Ja(t.shape,"return 1.0 / x;");return this.compileAndRun(e,[t])},ys.prototype.relu=function(t){var e;return e=_().getBool("WEBGL_PACK")?new fs(t.shape,cs):new Ja(t.shape,ts),this.compileAndRun(e,[t])},ys.prototype.relu6=function(t){var e;return e=_().getBool("WEBGL_PACK")?new fs(t.shape,ls):new Ja(t.shape,es),this.compileAndRun(e,[t])},ys.prototype.prelu=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ai(ii,t.shape,e.shape):new oi(ri,t.shape,e.shape);return this.compileAndRun(n,[t,e])},ys.prototype.elu=function(t){if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,hs,t.dtype);var e=new Ja(t.shape,ns);return this.compileAndRun(e,[t])},ys.prototype.eluDer=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ai("\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\n",t.shape,e.shape):new oi("return (b >= 1.0) ? a : a * (b + 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},ys.prototype.selu=function(t){var e=new Ja(t.shape,"\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = 1.7580993408473768;\n  float scale = 1.0507009873554805;\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n");return this.compileAndRun(e,[t])},ys.prototype.int=function(t){var e=new Ja(t.shape,"return float(int(x));");return this.compileAndRun(e,[t],"int32")},ys.prototype.clip=function(t,e,n){var r,o=(r=_().getBool("WEBGL_PACK_CLIP")?new ui(t.shape):new si(t.shape)).getCustomSetupFunc(e,n);return this.compileAndRun(r,[t],null,o)},ys.prototype.abs=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.abs(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Za,t.dtype);var e=new Ja(t.shape,Za);return this.compileAndRun(e,[t])},ys.prototype.complexAbs=function(t){var e=this.texData.get(t.dataId),n=new ci(t.shape),r=[this.makeComplexComponentTensorInfo(t,e.complexTensors.real),this.makeComplexComponentTensorInfo(t,e.complexTensors.imag)];return this.compileAndRun(n,r)},ys.prototype.sigmoid=function(t){var e=new Ja(t.shape,"return 1.0 / (1.0 + exp(-1.0 * x));");return this.compileAndRun(e,[t])},ys.prototype.softplus=function(t){var e=new Ja(t.shape,"\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n");return this.compileAndRun(e,[t])},ys.prototype.sin=function(t){var e=new Ja(t.shape,"if (isnan(x)) return x;\n  return sin(x);\n");return this.compileAndRun(e,[t])},ys.prototype.cos=function(t){var e=new Ja(t.shape,"if (isnan(x)) return x;\n  return cos(x);\n");return this.compileAndRun(e,[t])},ys.prototype.tan=function(t){var e=new Ja(t.shape,"return tan(x);");return this.compileAndRun(e,[t])},ys.prototype.asin=function(t){var e=new Ja(t.shape,"if (isnan(x)) return x;\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return asin(x);\n");return this.compileAndRun(e,[t])},ys.prototype.acos=function(t){var e=new Ja(t.shape,"if (isnan(x)) return x;\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return acos(x);\n");return this.compileAndRun(e,[t])},ys.prototype.atan=function(t){var e=new Ja(t.shape,"if (isnan(x)) return x;\n  return atan(x);\n");return this.compileAndRun(e,[t])},ys.prototype.atan2=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ai("\n  vec4 result = atan(a, b);\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new oi("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return atan(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},ys.prototype.sinh=function(t){var e=new Ja(t.shape,"\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},ys.prototype.cosh=function(t){var e=new Ja(t.shape,"\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},ys.prototype.tanh=function(t){var e=new Ja(t.shape,"\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n");return this.compileAndRun(e,[t])},ys.prototype.asinh=function(t){var e=new Ja(t.shape,"if (isnan(x)) return x;return log(x + sqrt(x * x + 1.0));");return this.compileAndRun(e,[t])},ys.prototype.acosh=function(t){var e=new Ja(t.shape,"if (isnan(x)) return x;\n  if (x < 1.0) return NAN;\n  return log(x + sqrt(x * x - 1.0));");return this.compileAndRun(e,[t])},ys.prototype.atanh=function(t){var e=new Ja(t.shape,"if (isnan(x)) return x;\n  if ((x < -1.0) || (x > 1.0)) return NAN;\n  return (log(1.0 + x) - log(1.0 - x)) / 2.0;");return this.compileAndRun(e,[t])},ys.prototype.erf=function(t){var e=new Ja(t.shape,'\n  // Error function is calculated approximately with elementary function.\n  // See "Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables", Abramowitz and Stegun.\n  float p = 0.3275911;\n  float a1 = 0.254829592;\n  float a2 = -0.284496736;\n  float a3 = 1.421413741;\n  float a4 = -1.453152027;\n  float a5 = 1.061405429;\n\n  float sign = sign(x);\n  x = abs(x);\n  float t = 1.0 / (1.0 + p * x);\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\n');return this.compileAndRun(e,[t])},ys.prototype.step=function(t,e){var n,r=new Ja(t.shape,(void 0===(n=e)&&(n=0),Qa+"\n    return x > 0.0 ? 1.0 : float("+n+");\n  "));return this.compileAndRun(r,[t])},ys.prototype.conv2dByMatMul=function(t,e,n,r,o,i){var a=t.shape,s=this.texData.get(t.dataId),u=n.inChannels,c=a[0]*a[1]*a[2],l=n.outChannels,h="channelsLast"===n.dataFormat,f=(1==c||1===l)&&1e3<u,p=a[2]%2!=0&&!!s.isPacked;if(f||!_().getBool("WEBGL_LAZILY_UNPACK")||!_().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!p){var d=h?a[0]*a[1]*a[2]:a[0]*a[2]*a[3],v=this.reshape(t,[1,d,n.inChannels]),m=this.reshape(e,[1,n.inChannels,n.outChannels]);return this.reshape(this.fusedBatchMatMul({a:v,b:m,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:i}),n.outShape)}var g=h?a[0]*a[1]*(a[2]+1):a[0]*a[2]*(a[3]+1),y={dataId:t.dataId,shape:[1,g,n.inChannels],dtype:t.dtype},x=s.shape;s.shape=s.shape.slice(),s.shape[s.shape.length-2]++,P(Le(s.shape,y.shape),function(){return"packed reshape "+s.shape+" to "+y.shape+" isn't free"});var b=this.reshape(e,[1,n.inChannels,n.outChannels]),w=this.fusedBatchMatMul({a:y,b:b,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:i}),C=this.texData.get(w.dataId);return P(C.isPacked,function(){return"batchMatMul result is expected to be packed"}),s.shape=x,C.shape=n.outShape,Vt.makeTensorFromDataId(w.dataId,n.outShape,w.dtype)},ys.prototype.conv2dWithIm2Row=function(t,e,n,r,o,i){var a=n.filterWidth,s=n.filterHeight,u=n.inChannels,c=n.outWidth,l=n.outHeight,h="channelsLast"===n.dataFormat,f=a*s*u,p=l*c,d=[f,p],v=t.squeeze([0]),m=e.reshape([1,f,-1]),g=new ca(d,v.shape,n),y=this.compileAndRun(g,[v]).reshape([1,d[0],d[1]]),x=null!=r,b=null!=i,w=o?vs(o,!0):null,C=new va(y.shape,[1,p,n.outChannels],!0,!1,x,w,b),E=[y,m];r&&E.push(r),b&&E.push(i);var _=this.compileAndRun(C,E);return h?_.reshape([1,l,c,n.outChannels]):_.reshape([1,n.outChannels,l,c])},ys.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,i=t.activation,a=t.preluActivationWeights;if(1===r.filterHeight&&1===r.filterWidth&&1===r.dilationHeight&&1===r.dilationWidth&&1===r.strideHeight&&1===r.strideWidth&&("SAME"===r.padInfo.type||"VALID"===r.padInfo.type))return this.conv2dByMatMul(e,n,r,o,i,a);if(_().getBool("WEBGL_CONV_IM2COL")&&1===e.shape[0])return this.conv2dWithIm2Row(e,n,r,o,i,a);var s=null!=o,u=null!=a,c=i?vs(i,!1):null,l=new wi(r,s,c,u),h=[e,n];return o&&h.push(o),a&&h.push(a),this.compileAndRun(l,h)},ys.prototype.conv2d=function(t,e,n){if(1===n.filterHeight&&1===n.filterWidth&&1===n.dilationHeight&&1===n.dilationWidth&&1===n.strideHeight&&1===n.strideWidth&&("SAME"===n.padInfo.type||"VALID"===n.padInfo.type))return this.conv2dByMatMul(t,e,n);if(_().getBool("WEBGL_CONV_IM2COL")&&1===t.shape[0])return this.conv2dWithIm2Row(t,e,n);var r=new wi(n);return this.compileAndRun(r,[t,e])},ys.prototype.conv2dDerInput=function(t,e,n){var r=new mi(n);return this.compileAndRun(r,[t,e])},ys.prototype.conv2dDerFilter=function(t,e,n){var r=new vi(n);return this.compileAndRun(r,[t,e])},ys.prototype.fusedDepthwiseConv2D=function(t){var e,n=t.input,r=t.filter,o=t.convInfo,i=t.bias,a=t.activation,s=t.preluActivationWeights,u=_().getBool("WEBGL_PACK_DEPTHWISECONV")&&o.strideWidth<=2&&o.outChannels/o.inChannels==1,c=a?vs(a,u):null,l=[n,r],h=null!=i,f=null!=s;return h&&l.push(i),f&&l.push(s),e=u?new _i(o,h,c,f):new Ei(o,h,c,f),this.compileAndRun(e,l)},ys.prototype.depthwiseConv2D=function(t,e,n){var r;return r=_().getBool("WEBGL_PACK_DEPTHWISECONV")&&n.strideWidth<=2&&n.outChannels/n.inChannels==1?new _i(n):new Ei(n),this.compileAndRun(r,[t,e])},ys.prototype.depthwiseConv2DDerInput=function(t,e,n){var r=new bi(n);return this.compileAndRun(r,[t,e])},ys.prototype.depthwiseConv2DDerFilter=function(t,e,n){var r=new xi(n);return this.compileAndRun(r,[t,e])},ys.prototype.conv3d=function(t,e,n){var r=new Ci(n);return this.compileAndRun(r,[t,e])},ys.prototype.conv3dDerInput=function(t,e,n){var r=new yi(n);return this.compileAndRun(r,[t,e])},ys.prototype.conv3dDerFilter=function(t,e,n){var r=new gi(n);return this.compileAndRun(r,[t,e])},ys.prototype.maxPool=function(t,e){var n=new Ca(e,"max",!1);return this.compileAndRun(n,[t])},ys.prototype.avgPool=function(t,e){var n=new Ca(e,"avg",!1);return this.compileAndRun(n,[t],"float32")},ys.prototype.maxPoolBackprop=function(t,e,n,r){var o=new Ca(r,"max",!0),i=this.compileAndRun(o,[e]),a=new pa(r),s=this.compileAndRun(a,[t,i],e.dtype);return i.dispose(),s},ys.prototype.avgPoolBackprop=function(t,e,n){var r=new $o(n);return this.compileAndRun(r,[t],e.dtype)},ys.prototype.cast=function(t,e){return wo(t,e,this)},ys.prototype.unstack=function(t,e){for(var n=t.shape[e],r=new Array(t.rank-1),o=0,i=0;i<t.rank;i++)i!==e&&(r[o++]=t.shape[i]);var a=new Array(t.rank).fill(0),s=t.shape.slice();s[e]=1;var u=new Array(n);for(i=0;i<u.length;i++)u[a[e]=i]=this.slice(t,a,s).reshape(r);return u},ys.prototype.avgPool3d=function(t,e){var n=new Ea(e,"avg",!1);return this.compileAndRun(n,[t],"float32")},ys.prototype.avgPool3dBackprop=function(t,e,n){var r=new Yo(n);return this.compileAndRun(r,[t],e.dtype)},ys.prototype.maxPool3d=function(t,e){var n=new Ea(e,"max",!1);return this.compileAndRun(n,[t],"float32")},ys.prototype.maxPool3dBackprop=function(t,e,n,r){var o=new Ea(r,"max",!0),i=this.compileAndRun(o,[e]),a=new da(r),s=this.compileAndRun(a,[t,i],e.dtype);return i.dispose(),s},ys.prototype.reshape=function(t,e){var n=this.texData.get(t.dataId);if(!n.isPacked||Le(t.shape,e)||null!==n.texture&&Le(n.shape,e))return Co(t,e);var r=this.packedReshape(t,e);return Vt.makeTensorFromDataId(r.dataId,r.shape,r.dtype)},ys.prototype.resizeBilinear=function(t,e,n,r){var o=_().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Sa(t.shape,e,n,r):new ka(t.shape,e,n,r);return this.compileAndRun(o,[t],"float32")},ys.prototype.resizeBilinearBackprop=function(t,e,n){var r=new Ra(t,e,n);return this.compileAndRun(r,[t])},ys.prototype.resizeNearestNeighbor=function(t,e,n,r){var o=new Aa(t.shape,e,n,r);return this.compileAndRun(o,[t])},ys.prototype.resizeNearestNeighborBackprop=function(t,e,n){var r=new Da(t,e,n);return this.compileAndRun(r,[t])},ys.prototype.multinomial=function(t,e,n,r){var o=e?t:Qr(t),i=o.shape[0],a=o.shape[1],s=new ma(i,a,n),u=s.getCustomSetupFunc(r);return this.compileAndRun(s,[o],"int32",u)},ys.prototype.oneHot=function(t,e,n,r){var o=new ga(t.size,e,n,r);return this.compileAndRun(o,[t])},ys.prototype.diag=function(t){var e=new Ti(t.size);return this.compileAndRun(e,[t])},ys.prototype.nonMaxSuppression=function(t,e,n,r,o){return tn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead"),ko(t.dataSync(),e.dataSync(),n,r,o)},ys.prototype.cropAndResize=function(t,e,n,r,o,i){var a=new Ii(t.shape,e.shape,r,o,i);return this.compileAndRun(a,[t,e,n],"float32")},ys.prototype.depthToSpace=function(t,e,n){P(1<e,function(){return"blockSize should be > 1 for depthToSpace, but was: "+e});var r=t.shape[0],o="NHWC"===n?t.shape[1]:t.shape[2],i="NHWC"===n?t.shape[2]:t.shape[3],a="NHWC"===n?t.shape[3]:t.shape[1],s=o*e,u=i*e,c=a/(e*e),l=new Ai("NHWC"===n?[r,s,u,c]:[r,c,s,u],e,n);return this.compileAndRun(l,[t])},ys.prototype.split=function(t,e,n){return Do(t,e,n)},ys.prototype.scatterND=function(t,e,n){var r=zr(0,t,n),o=r.sliceRank,i=r.numUpdates,a=r.sliceSize,s=r.strides,u=r.outputSize,c=[u/a,a],l=t.reshape([i,o]),h=e.reshape([i,a]);if(0===u)return Co(bn([]),n);var f=Cn(0),p=new Na(i,o,l.rank,h.rank,s,c);return this.compileAndRun(p,[h,l,f]).reshape(n)},ys.prototype.sparseToDense=function(t,e,n,r){var o=zr(0,t,n),i=o.sliceRank,a=o.numUpdates,s=o.strides,u=o.outputSize,c=new Na(a,i,t.rank,e.rank,s,[u,1],!1);return this.compileAndRun(c,[e,t,r]).reshape(n)},ys.prototype.fft=function(t){return this.fftImpl(t,!1)},ys.prototype.ifft=function(t){return this.fftImpl(t,!0)},ys.prototype.fftImpl=function(t,e){var n=this.texData.get(t.dataId),r=new Pi("return real * expR - imag * expI;",t.shape,e),o=new Pi("return real * expI + imag * expR;",t.shape,e),i=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag)],a=this.compileAndRun(r,i),s=this.compileAndRun(o,i),u=this.complex(a,s).as2D(t.shape[0],t.shape[1]);return a.dispose(),s.dispose(),u},ys.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=Lr(t,e),i=o[0],a=o[1],s=o[2],u=o[3],c=e.reshape([a,r]),l=t.reshape([t.size/s,s]),h=new Ui(r,u,[a,s]);return this.compileAndRun(h,[l,c]).reshape(i)},ys.prototype.fill=function(t,e,n){if("string"===(n=n||G(e))){var r=A(n,L(t));return r.fill(e),Vt.makeTensor(r,t,n,this)}var o=new Bi(t,e),i=o.getCustomSetupFunc(e);return this.compileAndRun(o,[],n,i)},ys.prototype.onesLike=function(t){if("string"===t.dtype)throw new Error("onesLike is not supported under string dtype");return this.fill(t.shape,1,t.dtype)},ys.prototype.zerosLike=function(t){return this.fill(t.shape,"string"===t.dtype?"":0,t.dtype)},ys.prototype.linspace=function(t,e,n){return Eo(t,e,n)},ys.prototype.makeTensorInfo=function(t,e){var n=this.write(null,t,e);return this.texData.get(n).usage=null,{dataId:n,shape:t,dtype:e}},ys.prototype.makeOutput=function(t,e){var n=this.makeTensorInfo(t,e).dataId;return Vt.makeTensorFromDataId(n,t,e,this)},ys.prototype.unpackTensor=function(t){var e=new ps(t.shape);return this.runWebGLProgram(e,[t],t.dtype)},ys.prototype.packTensor=function(t){var e=new ya(t.shape);return this.runWebGLProgram(e,[t],t.dtype,null,!0)},ys.prototype.packedReshape=function(t,e){var n=[Ne(t.shape)].concat(Me(t.shape)),r={dtype:t.dtype,shape:n,dataId:t.dataId},o=[Ne(e)].concat(Me(e)),i=new Ia(o,n),a=this.runWebGLProgram(i,[r],t.dtype,null,!0);return{dataId:a.dataId,shape:e,dtype:a.dtype}},ys.prototype.decode=function(t){var e,n=this.texData.get(t),r=n.isPacked,o=n.shape,i=n.dtype,a=Oe(o);return e=r?new Di(a):new Si(a),{dtype:i,shape:o,dataId:this.runWebGLProgram(e,[{shape:a,dtype:i,dataId:t}],i,null,!0).dataId}},ys.prototype.runWebGLProgram=function(o,t,e,n,r){var i=this;void 0===r&&(r=!1);var a=this.makeTensorInfo(o.outputShape,e),s=this.texData.get(a.dataId);if(o.packedOutput&&(s.isPacked=!0),o.outPackingScheme===qt.DENSE){var u=ne(o.outputShape);s.texShape=u.map(function(t){return 2*t})}if(null!=o.outTexUsage&&(s.usage=o.outTexUsage),0===L(a.shape))return s.values=S(a.dtype,0),a;var c=[],l=t.map(function(t){if("complex64"===t.dtype)throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");var e=i.texData.get(t.dataId);if(null==e.texture){if(!o.packedInputs&&L(t.shape)<=_().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:t.shape,texData:null,isUniform:!0,uniformValues:e.values};o.packedInputs&&(e.isPacked=!0,e.shape=t.shape)}else if(!!e.isPacked!=!!o.packedInputs)t=e.isPacked?i.unpackTensor(t):i.packTensor(t),c.push(t),e=i.texData.get(t.dataId);else if(e.isPacked&&!Le(e.shape,t.shape)){var n=t,r=t.shape;t.shape=e.shape,t=i.packedReshape(t,r),c.push(t),e=i.texData.get(t.dataId),n.shape=r}return i.uploadToGPU(t.dataId),{shape:t.shape,texData:e,isUniform:!1}});this.uploadToGPU(a.dataId);var h,f={shape:a.shape,texData:s,isUniform:!1},p=function(t,e,n){var r="";l.concat(n).forEach(function(t){var e=null!=t.texData&&null!=t.texData.slice&&0<t.texData.slice.flatOffset,n=t.isUniform?"uniform":t.texData.texShape;r+=t.shape+"_"+n+"_"+e});var o=t.userCode;return t.constructor.name+"_"+r+"_"+o}(o,0,f),d=this.getAndSaveBinary(p,function(){return function(t,r,e,n){var o=r.userCode,i=e.map(function(t,e){var n={logicalShape:t.shape,texShape:t.isUniform?null:t.texData.texShape,isUniform:t.isUniform,isPacked:!t.isUniform&&t.texData.isPacked,flatOffset:null};return null!=t.texData&&null!=t.texData.slice&&0<t.texData.slice.flatOffset&&(n.flatOffset=t.texData.slice.flatOffset),{name:r.variableNames[e],shapeInfo:n}}),a=i.map(function(t){return t.shapeInfo}),s={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},u=Vo(i,s,o,r.packedInputs),c=t.createProgram(u),l=null,h=t.getUniformLocation(c,"NAN",!1);1===_().getNumber("WEBGL_VERSION")&&(l=t.getUniformLocation(c,"INFINITY",!1));for(var f={},p=0;p<r.variableNames.length;p++){var d=r.variableNames[p];f[d]=t.getUniformLocation(c,d,!1),f["offset"+d]=t.getUniformLocation(c,"offset"+d,!1)}return{program:r,source:u,webGLProgram:c,uniformLocations:f,inShapeInfos:a,outShapeInfo:s,infLoc:l,nanLoc:h}}(i.gpgpu,o,l,f)}),v=null!=this.activeTimers;if(v&&(h=this.startTimer()),function(a,s,t,e,n){ua(s.inShapeInfos,t),ua([s.outShapeInfo],[e]);var r=e.texData.texture,o=e.texData.texShape;e.texData.isPacked?a.setOutputPackedMatrixTexture(r,o[0],o[1]):a.setOutputMatrixTexture(r,o[0],o[1]),a.setProgram(s.webGLProgram),1===_().getNumber("WEBGL_VERSION")&&null!==s.infLoc&&a.gl.uniform1f(s.infLoc,1/0),null!==s.nanLoc&&a.gl.uniform1f(s.nanLoc,NaN),t.forEach(function(t,e){var n=s.program.variableNames[e],r=s.uniformLocations[n],o=s.uniformLocations["offset"+n];if(null!=r)if(t.isUniform)if(L(t.shape)<2)a.gl.uniform1f(r,t.uniformValues[0]);else{var i=t.uniformValues;i instanceof Float32Array||(i=new Float32Array(i)),a.gl.uniform1fv(r,i)}else null!=t.texData.slice&&null!=o&&a.gl.uniform1i(o,t.texData.slice.flatOffset),a.setInputMatrixTexture(t.texData.texture,r,e)}),null!=n&&n(a,s.webGLProgram),a.executeProgram()}(this.gpgpu,d,l,f,n),c.forEach(function(t){return i.disposeData(t.dataId)}),v&&(h=this.endTimer(h),this.activeTimers.push({name:o.constructor.name,query:this.getQueryTime(h)})),_().getBool("WEBGL_LAZILY_UNPACK")||!s.isPacked||!1!==r)return a;var m=this.unpackTensor(a);return this.disposeData(a.dataId),m},ys.prototype.compileAndRun=function(t,e,n,r,o){void 0===o&&(o=!1),n=n||e[0].dtype;var i=this.runWebGLProgram(t,e,n,r,o);return Vt.makeTensorFromDataId(i.dataId,i.shape,i.dtype)},ys.prototype.getAndSaveBinary=function(t,e){return t in this.binaryCache||(this.binaryCache[t]=e()),this.binaryCache[t]},ys.prototype.getTextureManager=function(){return this.textureManager},ys.prototype.dispose=function(){this.disposed||(this.textureManager.dispose(),null!=this.canvas&&"undefined"!=typeof HTMLCanvasElement&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)},ys.prototype.floatPrecision=function(){var n=this;return null==this.floatPrecisionValue&&(this.floatPrecisionValue=Je(function(){if(!_().get("WEBGL_RENDER_FLOAT32_ENABLED")){var t=_().getBool("DEBUG");_().set("DEBUG",!1);var e=n.abs(Cn(1e-8)).dataSync()[0];if(_().set("DEBUG",t),0<e)return 32}return 16})),this.floatPrecisionValue},ys.prototype.epsilon=function(){return 32===this.floatPrecision()?1e-7:1e-4},ys.prototype.uploadToGPU=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,i=n.values,a=n.texture,s=n.usage,u=n.isPacked;if(null==a){var c,l=null!=this.activeTimers;l&&(c=J());var h=n.texShape;if(null==h&&(h=Pe(r,u),n.texShape=h),null!=i){var f=Oe(r),p=void 0,d=h[1],v=h[0],m=i instanceof Uint8Array;p=u?(d=(e=re(h[0],h[1]))[0],v=e[1],new Oi(f,[v,d],m)):new Mi(f,[v,d],m);var g=this.makeTensorInfo([v,d],o);this.texData.get(g.dataId).usage=m?jt.PIXELS:jt.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId),d,v,i);var y=this.runWebGLProgram(p,[g],o,null,!0),x=this.texData.get(y.dataId);n.texture=x.texture,n.texShape=x.texShape,n.isPacked=x.isPacked,n.usage=x.usage,this.disposeData(g.dataId),this.texData.delete(y.dataId),n.values=null,l&&(this.uploadWaitMs+=J()-c)}else{var b=this.acquireTexture(h,s,o,u);n.texture=b}}},ys.prototype.convertAndCacheOnCPU=function(t,e){var n=this.texData.get(t),r=n.dtype;return this.releaseGPUData(t),null!=e&&(n.values=function(t,e){if("float32"===e||"complex64"===e)return t;if("int32"!==e&&"bool"!==e)throw new Error("Unknown dtype "+e);for(var n="int32"===e?new Int32Array(t.length):new Uint8Array(t.length),r=0;r<n.length;++r)n[r]=Math.round(t[r]);return n}(e,r)),n.values},ys.prototype.acquireTexture=function(t,e,n,r){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>1024*this.numMBBeforeWarning*1024){var o=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn("High memory usage in GPU: "+o+" MB, most likely due to a memory leak")}return this.textureManager.acquireTexture(t,e,r)},ys.prototype.computeBytes=function(t,e){return t[0]*t[1]*O(e)},ys);function ys(t){var e,n=ms.call(this)||this;if(n.pendingRead=new WeakMap,n.pendingDisposal=new WeakSet,n.dataRefCount=new WeakMap,n.numBytesInGPU=0,n.uploadWaitMs=0,n.downloadWaitMs=0,n.warnedAboutMemory=!1,n.pendingDeletes=0,n.disposed=!1,!_().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(null==t){var r=te(_().getNumber("WEBGL_VERSION"));n.binaryCache=((e=_().getNumber("WEBGL_VERSION"))in ds||(ds[e]={}),ds[e]),n.gpgpu=new aa(r),n.canvas=r.canvas,n.gpgpuCreatedLocally=!0}else n.gpgpu=t,n.binaryCache={},n.gpgpuCreatedLocally=!1,n.canvas=t.gl.canvas;return n.textureManager=new Ua(n.gpgpu),n.numMBBeforeWarning=null==_().global.screen?1024:_().global.screen.height*_().global.screen.width*window.devicePixelRatio*600/1024/1024,n.texData=new to(n,Vt),n}Gt()&&Vt.registerBackend("webgl",function(){return new gs},2);var xs=mn({square_:function(t){var n=rn(t,"x","square"),e=[n];return Vt.runKernelFunc(function(t,e){return e([n]),t.square(n)},{x:n},function(t,e){var n=e[0];return{x:function(){return t.mul(n.toFloat().mul(2))}}},"Square",{},e,[])}}),bs=mn({abs_:function(t){var r=rn(t,"x","abs");return"complex64"===r.dtype?Vt.runKernelFunc(function(t){return t.complexAbs(r)},{$x:r}):Vt.runKernelFunc(function(t,e){var n=t.abs(r);return e([r]),n},{x:r},function(t,e){var n=e[0];return{x:function(){return t.mul(n.toFloat().step(-1))}}},"Abs")}}),ws=mn({acos_:function(t){var r=rn(t,"x","acos");return Vt.runKernelFunc(function(t,e){var n=t.acos(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.divStrict(Cn(1).sub(n.toFloat().square()).sqrt()).neg()}}})}}),Cs=mn({acosh_:function(t){var r=rn(t,"x","acosh");return Vt.runKernelFunc(function(t,e){var n=t.acosh(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.divStrict(n.toFloat().square().sub(1).sqrt())}}})}}),Es=mn({asin_:function(t){var r=rn(t,"x","asin");return Vt.runKernelFunc(function(t,e){var n=t.asin(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.divStrict(Cn(1).sub(n.toFloat().square()).sqrt())}}})}}),_s=mn({asinh_:function(t){var r=rn(t,"x","asinh");return Vt.runKernelFunc(function(t,e){var n=t.asinh(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.divStrict(Cn(1).add(n.toFloat().square()).sqrt())}}})}}),Is=mn({atan_:function(t){var r=rn(t,"x","atan");return Vt.runKernelFunc(function(t,e){var n=t.atan(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.div(n.toFloat().square().add(1))}}})}}),Rs=mn({atanh_:function(t){var r=rn(t,"x","atanh");return Vt.runKernelFunc(function(t,e){var n=t.atanh(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.div(Cn(1).sub(n.toFloat().square()))}}})}}),ks=mn({ceil_:function(t){var e=rn(t,"x","ceil");return Vt.runKernelFunc(function(t){return t.ceil(e)},{$x:e},function(t){return{$x:function(){return Pn(t)}}})}}),Ss=mn({clipByValue_:function(t,r,o){var i=rn(t,"x","clipByValue");P(r<=o,function(){return"Error in clip: min ("+r+") must be less than or equal to max ("+o+")."});var e=[i],n={min:r,max:o};return Vt.runKernelFunc(function(t,e){var n=t.clip(i,r,o);return e([i]),n},{x:i},function(t,e){var n=e[0];return{x:function(){return t.where(n.greaterEqual(r).logicalAnd(n.lessEqual(o)),Pn(t))}}},"ClipByValue",n,e)}}),Ds=mn({cos_:function(t){var r=rn(t,"x","cos");return Vt.runKernelFunc(function(t,e){var n=t.cos(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return n.toFloat().sin().neg().mul(t)}}})}}),As=mn({cosh_:function(t){var r=rn(t,"x","cosh");return Vt.runKernelFunc(function(t,e){var n=t.cosh(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return n.toFloat().sinh().mulStrict(t)}}})}}),Ts=mn({erf_:function(t){var r=rn(t,"x","erf");return P("int32"===r.dtype||"float32"===r.dtype,function(){return"Input dtype must be `int32` or `float32`."}),"int32"===r.dtype&&(r=r.toFloat()),Vt.runKernelFunc(function(t,e){var n=t.erf(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.mul(n.square().neg().exp().mul(2/Math.sqrt(Math.PI)))}}})}}),Fs=mn({exp_:function(t){var r=rn(t,"x","exp");return Vt.runKernelFunc(function(t,e){var n=t.exp(r);return e([n]),n},{$x:r},function(t,e){return{$x:function(){return t.mulStrict(e[0])}}})}}),Ns=mn({expm1_:function(t){var r=rn(t,"x","expm1");return Vt.runKernelFunc(function(t,e){var n=t.expm1(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.mul(n.exp())}}})}}),Ms=mn({floor_:function(t){var e=rn(t,"x","floor");return Vt.runKernelFunc(function(t){return t.floor(e)},{$x:e},function(t){return{$x:function(){return Pn(t)}}})}}),Os=mn({log_:function(t){var r=rn(t,"x","log");return Vt.runKernelFunc(function(t,e){var n=t.log(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.div(n.toFloat())}}})}}),Ps=mn({log1p_:function(t){var r=rn(t,"x","log1p");return Vt.runKernelFunc(function(t,e){var n=t.log1p(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.div(n.add(1))}}})}}),Bs=mn({logSigmoid_:function(t){var r=rn(t,"x","logSigmoid");return Vt.runKernelFunc(function(t,e){var n=t.softplus(r.neg()).neg();return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.mul(n.neg().sigmoid())}}})}}),Ls=mn({neg_:function(t){var e=rn(t,"x","neg");return Vt.runKernelFunc(function(t){return t.neg(e)},{$x:e},function(t){return{$x:function(){return t.neg()}}})}}),Ws=mn({reciprocal_:function(t){var r=rn(t,"x","reciprocal");return Vt.runKernelFunc(function(t,e){var n=t.reciprocal(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.div(n.square().neg())}}})}}),zs=mn({round_:function(t){var e=rn(t,"x","round");return Vt.runKernelFunc(function(t){return t.round(e)},{$x:e},function(t){return{$x:function(){return Pn(t)}}})}}),Us=mn({rsqrt_:function(t){var r=rn(t,"x","rsqrt");return Vt.runKernelFunc(function(t,e){var n=t.rsqrt(r);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return t.div(n.pow(1.5).mul(2)).neg()}}})}}),Vs=mn({sigmoid_:function(t){var r=rn(t,"x","sigmoid");return Vt.runKernelFunc(function(t,e){var n=t.sigmoid(r);return e([n]),n},{x:r},function(t,e){var n=e[0];return{x:function(){return t.mul(n.mul(Cn(1).sub(n)))}}},"Sigmoid")}}),Gs=mn({sign_:function(t){var 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n=t.tanh(r);return e([n]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return Cn(1).sub(n.square()).mulStrict(t)}}})}});function tu(t,e,n,r,o,i){var a,s,u=rn(t,"x","batchNorm"),c=rn(e,"mean","batchNorm"),l=rn(n,"variance","batchNorm");return null!=o&&(a=rn(o,"scale","batchNorm")),null!=r&&(s=rn(r,"offset","batchNorm")),P(2===u.rank,function(){return"Error in batchNorm3D: x must be rank 3 but got rank "+u.rank+"."}),P(2===c.rank||1===c.rank,function(){return"Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank "+c.rank+"."}),P(2===l.rank||1===l.rank,function(){return"Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank "+l.rank+"."}),null!=a&&P(2===a.rank||1===a.rank,function(){return"Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank "+a.rank+"."}),null!=s&&P(2===s.rank||1===s.rank,function(){return"Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank "+s.rank+"."}),ru(u,c,l,s,a,i)}function eu(t,e,n,r,o,i){var a,s,u=rn(t,"x","batchNorm"),c=rn(e,"mean","batchNorm"),l=rn(n,"variance","batchNorm");return null!=o&&(a=rn(o,"scale","batchNorm")),null!=r&&(s=rn(r,"offset","batchNorm")),P(3===u.rank,function(){return"Error in batchNorm3D: x must be rank 3 but got rank "+u.rank+"."}),P(3===c.rank||1===c.rank,function(){return"Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank "+c.rank+"."}),P(3===l.rank||1===l.rank,function(){return"Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank "+l.rank+"."}),null!=a&&P(3===a.rank||1===a.rank,function(){return"Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank "+a.rank+"."}),null!=s&&P(3===s.rank||1===s.rank,function(){return"Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank "+s.rank+"."}),ru(u,c,l,s,a,i)}function nu(t,e,n,r,o,i){var a,s,u=rn(t,"x","batchNorm"),c=rn(e,"mean","batchNorm"),l=rn(n,"variance","batchNorm");return null!=o&&(a=rn(o,"scale","batchNorm")),null!=r&&(s=rn(r,"offset","batchNorm")),P(4===u.rank,function(){return"Error in batchNorm4D: x must be rank 4 but got rank "+u.rank+"."}),P(4===c.rank||1===c.rank,function(){return"Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank "+c.rank+"."}),P(4===l.rank||1===l.rank,function(){return"Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank "+l.rank+"."}),null!=a&&P(4===a.rank||1===a.rank,function(){return"Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank "+a.rank+"."}),null!=s&&P(4===s.rank||1===s.rank,function(){return"Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank "+s.rank+"."}),ru(u,c,l,s,a,i)}function ru(t,e,n,r,o,v){null==v&&(v=.001);var i,a,m,s=rn(t,"x","batchNorm"),u=rn(e,"mean","batchNorm"),c=rn(n,"variance","batchNorm");null!=o&&(i=rn(o,"scale","batchNorm")),null!=r&&(a=rn(r,"offset","batchNorm")),P(u.rank===c.rank,function(){return"Batch normalization gradient requires 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1===o.rank?n.mul(Ar(p.as4D(1,1,1,o.shape[0]),c)).mul(s).reshape(r.shape):n.mul(p).mul(s).reshape(r.shape)},mean:function(){var t=p.mul(Cn(-1)).mul(f);return 1===o.rank&&(t=t.sum(u)),t.reshape(o.shape)},variance:function(){var t=d.mul(h).mul(f);return 1===o.rank&&(t=t.sum(u)),t.reshape(o.shape)},scale:function(){var t=h.mul(p),e=n.mul(t);return 1===o.rank&&(e=e.sum(u)),e.reshape(o.shape)},offset:function(){var t=n;return 1===o.rank&&(t=t.sum(u)),t.reshape(o.shape)}}},"BatchNormalization",{varianceEpsilon:v},l).reshape(s.shape)}function ou(t){return null==t?null:0===t.rank?t.as1D():1===t.rank?t:2===t.rank?t.as4D(1,1,t.shape[0],t.shape[1]):3===t.rank?t.as4D(1,t.shape[0],t.shape[1],t.shape[2]):t}function iu(){Ye("tf.batchNormalization() is going away. 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so(n.shape,r.shape),Vt.runKernelFunc(function(t){return t.logicalAnd(n,r)},{$a:n,$b:r})}}),mu=mn({logicalNot_:function(t){var e=rn(t,"x","logicalNot","bool");return Vt.runKernelFunc(function(t){return t.logicalNot(e)},{$x:e})}}),gu=mn({logicalOr_:function(t,e){var n=rn(t,"a","logicalOr","bool"),r=rn(e,"b","logicalOr","bool");return so(n.shape,r.shape),Vt.runKernelFunc(function(t){return t.logicalOr(n,r)},{$a:n,$b:r})}}),yu=mn({logicalXor_:function(t,e){var n=rn(t,"a","logicalXor","bool"),r=rn(e,"b","logicalXor","bool");return so(n.shape,r.shape),gu(t,e).logicalAnd(vu(t,e).logicalNot())}}),xu=mn({where_:function(t,e,n){var r=rn(e,"a","where"),o=rn(n,"b","where"),i=rn(t,"condition","where","bool");return b(r.shape,o.shape,"Error in where: "),1===i.rank?P(i.shape[0]===r.shape[0],function(){return"The first dimension of `a` must match the size of `condition`."}):b(i.shape,o.shape,"Error in where: "),Vt.runKernelFunc(function(t,e){var n=t.select(i,r,o);return e([i]),n},{$condition:i,$a:r,$b:o},function(t,e){var n=e[0];return{$condition:function(){return Pn(n).toFloat()},$a:function(){return t.mul(n.cast(t.dtype))},$b:function(){return t.mul(n.logicalNot().cast(t.dtype))}}})}}),bu=mn({add_:function(t,e){var n,r=rn(t,"a","add"),o=rn(e,"b","add");n=Nt(r,o),r=n[0],o=n[1];var i=so(r.shape,o.shape);return Vt.runKernelFunc(function(t){return t.add(r,o)},{a:r,b:o},function(n){return{a:function(){var t=n,e=ao(r.shape,i);return 0<e.length&&(t=t.sum(e)),t.reshape(r.shape)},b:function(){var t=n,e=ao(o.shape,i);return 0<e.length&&(t=t.sum(e)),t.reshape(o.shape)}}},"Add")}}),wu=mn({addN_:function(t){P(Array.isArray(t),function(){return"The argument passed to tf.addN() must be a list of tensors"}),P(1<=t.length,function(){return"Must pass at least one tensor to tf.addN(), but got "+t.length});var e=t.map(function(t,e){return rn(t,"tensors"+e,"addN")}),n=e[0];e.forEach(function(t){if(t.dtype!==n.dtype)throw new Error("All tensors passed to tf.addN() must 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0<n.length&&(e=e.sum(n)),e.reshape(i.shape)}}})}}),_u=mn({div_:function(t,e){var n,r=rn(t,"a","div"),o=rn(e,"b","div");if(n=Nt(r,o),r=n[0],o=n[1],"int32"===r.dtype&&"int32"===o.dtype)return ku(r,o);var a=so(r.shape,o.shape);return Vt.runKernelFunc(function(t,e){var n=t.realDivide(r,o);return e([r,o]),n},{a:r,b:o},function(r,t){var o=t[0],i=t[1];return{a:function(){var t=r.div(i.toFloat()),e=ao(o.shape,a);return 0<e.length?t.sum(e).reshape(o.shape):t},b:function(){var t=r.mul(o.toFloat()),e=ao(i.shape,a);0<e.length&&(t=t.sum(e).reshape(i.shape));var n=i.square();return t.div(n.toFloat()).neg()}}},"Div")}}),Iu=mn({divNoNan_:function(t,e){var n,r=rn(t,"a","div"),o=rn(e,"b","div");r=(n=Nt(r,o))[0],o=n[1];var i=_u(r,o),a=Pn(i),s=o.equal(a);return xu(s,a,i)}}),Ru=mn({divStrict_:function(t,e){var n=rn(t,"a","div"),r=rn(e,"b","div");return b(n.shape,r.shape,"Error in divideStrict: "),n.div(r)}}),ku=mn({floorDiv_:function(t,e){var n,r=rn(t,"a","floorDiv"),o=rn(e,"b","floorDiv");n=Nt(r,o),r=n[0],o=n[1];var a=so(r.shape,o.shape);return Vt.runKernelFunc(function(t,e){var n=t.floorDiv(r,o);return e([r,o]),n},{a:r,b:o},function(r,t){var o=t[0],i=t[1];return{a:function(){var t=r.div(i.toFloat()),e=ao(o.shape,a);return 0<e.length?t.sum(e).reshape(o.shape):t},b:function(){var t=r.mul(o.toFloat()),e=ao(i.shape,a);0<e.length&&(t=t.sum(e).reshape(i.shape));var n=i.square();return t.div(n.toFloat()).neg()}}},"FloorDiv")}}),Su=mn({maximum_:function(t,e){var n,r=rn(t,"a","maximum"),o=rn(e,"b","maximum");return n=Nt(r,o),r=n[0],o=n[1],"bool"===r.dtype&&(r=r.toInt(),o=o.toInt()),so(r.shape,o.shape),Vt.runKernelFunc(function(t,e){var n=t.maximum(r,o);return e([r,o]),n},{$a:r,$b:o},function(t,e){var n=e[0],r=e[1];return{$a:function(){return t.mul(n.greaterEqual(r).toFloat())},$b:function(){return t.mul(n.less(r).toFloat())}}})}}),Du=mn({maximumStrict_:function(t,e){var n=rn(t,"a","maximumStrict"),r=rn(e,"b","maximumStrict");return b(n.shape,r.shape,"Error in maximumStrict: "),n.maximum(r)}}),Au=mn({minimum_:function(t,e){var n,r=rn(t,"a","minimum"),o=rn(e,"b","minimum");return n=Nt(r,o),r=n[0],o=n[1],"bool"===r.dtype&&(r=r.toInt(),o=o.toInt()),so(r.shape,o.shape),Vt.runKernelFunc(function(t,e){var n=t.minimum(r,o);return e([r,o]),n},{$a:r,$b:o},function(t,e){var n=e[0],r=e[1];return{$a:function(){return t.mul(n.lessEqual(r).toFloat())},$b:function(){return t.mul(n.greater(r).toFloat())}}})}}),Tu=mn({minimumStrict_:function(t,e){var n=rn(t,"a","minimumStrict"),r=rn(e,"b","minimumStrict");return b(n.shape,r.shape,"Error in minimumStrict: "),n.minimum(r)}}),Fu=mn({mod_:function(t,e){var n,r=rn(t,"a","mod"),o=rn(e,"b","mod");n=Nt(r,o),r=n[0],o=n[1];var i=so(r.shape,o.shape);return Vt.runKernelFunc(function(t,e){var n=t.mod(r,o);return e([r,o]),n},{$a:r,$b:o},function(n,t){var r=t[0],o=t[1];return{$a:function(){var t=ao(r.shape,i);return 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r=rn(t,"base","pow"),o=rn(e,"exp","pow"),u=so(r.shape,o.shape);return t=r.cast(Tt(r.dtype,o.dtype)),e=o.cast(Tt(r.dtype,o.dtype)),Vt.runKernelFunc(function(t,e){var n=t.pow(r,o);return e([r,o,n]),n},{$base:r,$exp:o},function(o,t){var i=t[0],a=t[1],s=t[2];return{$base:function(){var t=a.toFloat(),e=o.mul(t.mul(i.pow(t.sub(Cn(1))))),n=ao(i.shape,u);return 0<n.length&&(e=e.sum(n)),e.reshape(i.shape)},$exp:function(){var t=i.greater(0),e=i.log().where(t,Pn(i)),n=o.mul(s.mul(e)),r=ao(a.shape,u);return 0<r.length&&(n=n.sum(r)),n.reshape(a.shape)}}})}}),Bu=mn({powStrict_:function(t,e){return b(t.shape,e.shape,"Error in powStrict: "),t.pow(e)}}),Lu=mn({squaredDifference_:function(t,e){var n,r=rn(t,"a","squaredDifference"),o=rn(e,"b","squaredDifference");return n=Nt(r,o),r=n[0],o=n[1],so(r.shape,o.shape),Vt.runKernelFunc(function(t,e){var n=t.squaredDifference(r,o);return e([r,o]),n},{$a:r,$b:o},function(t,e){var n=e[0],r=e[1],o=Cn(2);return{$a:function(){return t.mul(n.sub(r).mul(o))},$b:function(){return t.mul(r.sub(n).mul(o))}}})}}),Wu=mn({squaredDifferenceStrict_:function(t,e){var n=rn(t,"a","squaredDifferenceStrict"),r=rn(e,"b","squaredDifferenceStrict");return b(n.shape,r.shape,"Error in squaredDifferenceStrict: "),n.squaredDifference(r)}}),zu=mn({sub_:function(t,e){var n,r=rn(t,"a","sub"),o=rn(e,"b","sub");n=Nt(r,o),r=n[0],o=n[1];var i=so(r.shape,o.shape);return Vt.runKernelFunc(function(t){return t.subtract(r,o)},{a:r,b:o},function(n){return{a:function(){var t=n,e=ao(r.shape,i);return 0<e.length&&(t=t.sum(e)),t.reshape(r.shape)},b:function(){var t=n,e=ao(o.shape,i);return 0<e.length&&(t=t.sum(e)),t.neg().reshape(o.shape)}}},"Sub")}}),Uu=mn({subStrict_:function(t,e){var n=rn(t,"a","subStrict"),r=rn(e,"b","subStrict");return b(n.shape,r.shape,"Error in subStrict: "),n.sub(r)}}),Vu=mn({equal_:function(t,e){var n,r=rn(t,"a","equal"),o=rn(e,"b","equal");return n=Nt(r,o),r=n[0],o=n[1],so(r.shape,o.shape),Vt.runKernelFunc(function(t){return t.equal(r,o)},{$a:r,$b:o})}}),Gu=mn({equalStrict_:function(t,e){var n=rn(t,"a","equalStrict"),r=rn(e,"b","equalStrict");return b(n.shape,r.shape,"Error in equalStrict: "),n.equal(r)}}),Hu=mn({greater_:function(t,e){var n,r=rn(t,"a","greater"),o=rn(e,"b","greater");return n=Nt(r,o),r=n[0],o=n[1],so(r.shape,o.shape),Vt.runKernelFunc(function(t){return t.greater(r,o)},{$a:r,$b:o})}}),qu=mn({greaterEqual_:function(t,e){var n,r=rn(t,"a","greaterEqual"),o=rn(e,"b","greaterEqual");return n=Nt(r,o),r=n[0],o=n[1],so(r.shape,o.shape),Vt.runKernelFunc(function(t,e){var n=t.greaterEqual(r,o);return e([r,o]),n},{$a:r,$b:o},function(t,e){var n=e[0],r=e[1];return{$a:function(){return Pn(n)},$b:function(){return Pn(r)}}})}}),ju=mn({greaterEqualStrict_:function(t,e){var n=rn(t,"a","greaterEqualStrict"),r=rn(e,"b","greaterEqualStrict");return b(n.shape,r.shape,"Error in greaterEqualStrict: "),n.greaterEqual(r)}}),Ku=mn({greaterStrict_:function(t,e){var n=rn(t,"a","greaterStrict"),r=rn(e,"b","greaterStrict");return b(n.shape,r.shape,"Error in greaterStrict: "),n.greater(r)}}),Xu=mn({less_:function(t,e){var n,r=rn(t,"a","less"),o=rn(e,"b","less");return n=Nt(r,o),r=n[0],o=n[1],so(r.shape,o.shape),Vt.runKernelFunc(function(t){return t.less(r,o)},{$a:r,$b:o})}}),$u=mn({lessEqual_:function(t,e){var n,r=rn(t,"a","lessEqual"),o=rn(e,"b","lessEqual");return n=Nt(r,o),r=n[0],o=n[1],so(r.shape,o.shape),Vt.runKernelFunc(function(t){return t.lessEqual(r,o)},{$a:r,$b:o})}}),Yu=mn({lessEqualStrict_:function(t,e){var n=rn(t,"a","lessEqualStrict"),r=rn(e,"b","lessEqualStrict");return b(n.shape,r.shape,"Error in lessEqualStrict: "),n.lessEqual(r)}}),Ju=mn({lessStrict_:function(t,e){var n=rn(t,"a","lessStrict"),r=rn(e,"b","lessStrict");return b(n.shape,r.shape,"Error in lessStrict: "),n.less(r)}}),Qu=mn({notEqual_:function(t,e){var n,r=rn(t,"a","notEqual"),o=rn(e,"b","notEqual");return n=Nt(r,o),r=n[0],o=n[1],so(r.shape,o.shape),Vt.runKernelFunc(function(t){return t.notEqual(r,o)},{$a:r,$b:o})}}),Zu=mn({notEqualStrict_:function(t,e){var n=rn(t,"a","notEqualStrict"),r=rn(e,"b","notEqualStrict");return b(n.shape,r.shape,"Error in notEqualStrict: "),n.notEqual(r)}});function tc(t,e){for(var n=[],r=t;r<e;++r)n.push(r);return n}function ec(t){for(var e=[],n=0;n<t.length;++n)for(var r=0;r<t[n].length;++r)e.push(t[n][r]);return e}function nc(d,v,m){return y(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p;return R(this,function(t){switch(t.label){case 0:for(e=rn(d,"tensor","boolMask"),n=rn(v,"mask","boolMask","bool"),r=null==m?0:m,o=n.rank,i=e.shape,P(0<o,function(){return"mask cannot be scalar"}),b(i.slice(r,r+o),n.shape,"mask's shape must match the first K dimensions of tensor's shape,"),a=1,s=r;s<r+o;s++)a*=i[s];return u=i.slice(0,r).concat([a],i.slice(r+o)),c=e.reshape(u),l=n.reshape([-1]),[4,au(l)];case 1:return h=t.sent(),f=h.squeeze([1]),p=rc(c,f,r),d!==e&&e.dispose(),v!==n&&n.dispose(),f.dispose(),c.dispose(),l.dispose(),h.dispose(),[2,p]}})})}var rc=mn({gather_:function(t,e,g){void 0===g&&(g=0);var y=rn(t,"x","gather"),r=rn(e,"indices","gather","int32");g=I(g,y.shape)[0];var n=function(t,e,n){for(var r=t.shape[n],o=[],i=1,a=1,s=0;s<n;s++)o.push(t.shape[s]),i*=t.shape[s];for(s=0;s<e.rank;s++)o.push(e.shape[s]);for(s=n+1;s<t.rank;s++)o.push(t.shape[s]),a*=t.shape[s];return{batchSize:i,sliceSize:a,dimSize:r,outputShape:o}}(y,r,g);return Vt.runKernelFunc(function(t,e){var n=t.gather(y,r.flatten(),g);return e([r]),n},{$x:y},function(v,t){var m=t[0];return{$x:function(){var t=y.shape,e=m.size,n=t.slice(0,g),r=n.length,o=t.slice(g,t.length).slice(1),i=o.length,a=tc(0,r),s=tc(r+1,r+1+i),u=ec([n,[e],o]),c=v.reshape(u),l=m.reshape([e]),h=ec([[r],a,s]),f=c.transpose(h),p=oc(f,l,y.shape[g]),d=fn(h);return p.transpose(d)}}}).reshape(n.outputShape)}}),oc=mn({unsortedSegmentSum_:function(t,e,r){var o=rn(t,"x","unsortedSegmentSum"),i=rn(e,"segmentIds","unsortedSegmentSum","int32");return P(B(r),function(){return"numSegments must be of dtype int"}),Vt.runKernelFunc(function(t,e){var n=t.unsortedSegmentSum(o,i,r);return e([i]),n},{$x:o},function(t,e){var n=e[0];return{$x:function(){return function(t,e){for(var n=Su(e,Pn(e)),r=rc(t,n),o=qu(e,Cn(0,"int32")),i=r.rank-o.rank,a=0;a<i;++a)o=pr(o,a+1);o=vu(o,An(r.shape,"bool"));var s=Pn(r);return xu(o,r,s)}(t,n)}}})}});function ic(t,e,r,o,i,a,s){void 0===a&&(a="NHWC"),P(t.length===e.rank,function(){return"Length of inShape ("+t.length+") and rank of dy ("+e.rank+") must match"});var n=t,u=e,c=!1;3===e.rank&&(c=!0,u=e.as4D(1,e.shape[0],e.shape[1],e.shape[2]),n=[1,t[0],t[1],t[2]]),P(4===n.length,function(){return"Error in conv2dDerInput: inShape must be length 4, but got length "+n.length+"."}),P(4===u.rank,function(){return"Error in conv2dDerInput: dy must be rank 4, but got rank "+u.rank}),P(4===r.rank,function(){return"Error in conv2dDerInput: filter must be rank 4, but got rank "+r.rank});var l="NHWC"===a?n[3]:n[1],h="NHWC"===a?u.shape[3]:u.shape[1];P(l===r.shape[2],function(){return"Error in conv2dDerInput: depth of input ("+l+") must match input depth for filter "+r.shape[2]+"."}),P(h===r.shape[3],function(){return"Error in conv2dDerInput: depth of output ("+h+") must match output depth for filter "+r.shape[3]+"."}),null!=s&&P(B(i),function(){return"Error in conv2dDerInput: pad must be an integer when using, dimRoundingMode "+s+" but got pad "+i+"."});var f=bo(a),p=lo(n,r.shape,o,1,i,s,!1,f),d=Vt.runKernelFunc(function(t,e){var n=t.conv2dDerInput(u,r,p);return e([r,u]),n},{dy4D:u,filter:r},function(t,e){var n=e[0],r=e[1];return{dy4D:function(){return cc(t,n,o,i,a,1,s)},filter:function(){return hc(t,r,n.shape,o,i,a,s)}}});return c?d.as3D(d.shape[1],d.shape[2],d.shape[3]):d}function ac(t){var e,n="number"==typeof(e=t)?[e,e,e]:2===e.length?[e[0],e[1],1]:e,r=n[0],o=n[1],i=n[2];return 1===r&&1===o&&1===i}function sc(t,e,n,r,o){P(t.length===e.rank,function(){return"Length of inShape ("+t.length+") and rank of dy ("+e.rank+") must match"});var i=t,a=e,s=!1;4===e.rank&&(s=!0,a=e.as5D(1,e.shape[0],e.shape[1],e.shape[2],e.shape[3]),i=[1,t[0],t[1],t[2],t[3]]);var u=i[4],c=a.shape[4];P(5===i.length,function(){return"Error in conv3dDerInput: inShape must be length 5, but got length "+i.length+"."}),P(5===a.rank,function(){return"Error in conv3dDerInput: dy must be rank 5, but got rank "+a.rank}),P(5===n.rank,function(){return"Error in conv3dDerInput: filter must be rank 5, but got rank "+n.rank}),P(u===n.shape[3],function(){return"Error in conv3dDerInput: depth of input ("+u+") must match input depth for filter "+n.shape[3]+"."}),P(c===n.shape[4],function(){return"Error in conv3dDerInput: depth of output ("+c+") must match output depth for filter "+n.shape[4]+"."});var l=ho(i,n.shape,r,1,o),h=Vt.runKernelFunc(function(t){return t.conv3dDerInput(a,n,l)},{dy5D:a});return s?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}var uc=mn({conv1d_:function(t,e,n,r,o,i,a){void 0===o&&(o="NWC"),void 0===i&&(i=1);var s=rn(t,"x","conv1d"),u=rn(e,"filter","conv1d"),c=s,l=!1;2===s.rank&&(l=!0,c=s.as3D(1,s.shape[0],s.shape[1])),P(3===c.rank,function(){return"Error in conv1d: input must be rank 3, but got rank "+c.rank+"."}),P(3===u.rank,function(){return"Error in conv1d: filter must be rank 3, but got rank "+u.rank+"."}),null!=a&&P(B(r),function(){return"Error in conv1d: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+r+"."}),P(c.shape[2]===u.shape[1],function(){return"Error in conv1d: depth of input ("+c.shape[2]+") must match input depth for filter "+u.shape[1]+"."}),P(xo(n,i),function(){return"Error in conv1D: Either stride or dilation must be 1. Got stride "+n+" and dilation '"+i+"'"}),P("NWC"===o,function(){return"Error in conv1d: got dataFormat of "+o+" but only NWC is currently supported."});var h=u.as4D(1,u.shape[0],u.shape[1],u.shape[2]),f=c.as4D(c.shape[0],1,c.shape[1],c.shape[2]),p=cc(f,h,[1,n],r,"NHWC",[1,i],a);return l?p.as2D(p.shape[2],p.shape[3]):p.as3D(p.shape[0],p.shape[2],p.shape[3])}}),cc=mn({conv2d_:function(t,e,i,a,s,u,n){void 0===s&&(s="NHWC"),void 0===u&&(u=[1,1]);var r=rn(t,"x","conv2d"),o=rn(e,"filter","conv2d"),c=r,l=!1;3===r.rank&&(l=!0,c=r.as4D(1,r.shape[0],r.shape[1],r.shape[2])),P(4===c.rank,function(){return"Error in conv2d: input must be rank 4, but got rank "+c.rank+"."}),P(4===o.rank,function(){return"Error in conv2d: filter must be rank 4, but got rank "+o.rank+"."}),null!=n&&P(B(a),function(){return"Error in conv2d: pad must be an integer when using, dimRoundingMode "+n+" but got pad "+a+"."});var h="NHWC"===s?c.shape[3]:c.shape[1];P(h===o.shape[2],function(){return"Error in conv2d: depth of input ("+h+") must match input depth for filter "+o.shape[2]+"."}),P(xo(i,u),function(){return"Error in conv2D: Either strides or dilations must be 1. Got strides "+i+" and dilations '"+u+"'"});var f=bo(s),p=lo(c.shape,o.shape,i,u,a,n,!1,f),d=[o,c],v=Vt.runKernelFunc(function(t,e){var n=t.conv2d(c,o,p);return e([o,c]),n},{x:c,filter:o},function(t,e){var n=e,r=n[0],o=n[1];return P(yo(u),function(){return"Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '"+u+"'"}),{x:function(){return fc(o.shape,t,r,i,a,s)},filter:function(){return hc(o,t,r.shape,i,a,s)}}},"Conv2D",p,d);return l?v.as3D(v.shape[1],v.shape[2],v.shape[3]):v}}),lc=mn({conv3d_:function(t,e,o,i,n,a){void 0===n&&(n="NDHWC"),void 0===a&&(a=[1,1,1]);var r,s=rn(t,"x","conv3d"),u=rn(e,"filter","conv3d"),c=s,l=!1;4===s.rank&&(l=!0,c=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3])),P(5===c.rank,function(){return"Error in conv3d: input must be rank 5, but got rank "+c.rank+"."}),P(5===u.rank,function(){return"Error in conv3d: filter must be rank 5, but got rank "+u.rank+"."}),P(c.shape[4]===u.shape[3],function(){return"Error in conv3d: depth of input ("+c.shape[4]+") must match input depth for filter "+u.shape[3]+"."}),P((r=a,ac(o)||ac(r)),function(){return"Error in conv3D: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+a+"'"}),P("NDHWC"===n,function(){return"Error in conv3d: got dataFormat of "+n+" but only NDHWC is currently supported."});var h=ho(c.shape,u.shape,o,a,i),f=Vt.runKernelFunc(function(t,e){var n=t.conv3d(c,u,h);return e([c,u]),n},{x:c,$filter:u},function(t,e){P(ac(a),function(){return"Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '"+a+"'"});var n=e[0],r=e[1];return{x:function(){return sc(n.shape,t,r,o,i)},$filter:function(){return function(t,e,n,r,o){var i=t;4===t.rank&&(i=t.as5D(1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]));var a=e;4===a.rank&&(a=e.as5D(1,e.shape[0],e.shape[1],e.shape[2],e.shape[3])),P(5===i.rank,function(){return"Error in conv3dDerFilter: input must be rank 5, but got shape "+i.shape+"."}),P(5===a.rank,function(){return"Error in conv3dDerFilter: dy must be rank 5, but got shape "+a.shape+"."}),P(5===n.length,function(){return"Error in conv3dDerFilter: filterShape must be length 5, but got "+n+"."}),P(i.shape[4]===n[3],function(){return"Error in conv3dDerFilter: depth of input "+i.shape[4]+") must match input depth in filter ("+n[3]+"."}),P(a.shape[4]===n[4],function(){return"Error in conv3dDerFilter: depth of dy ("+a.shape[4]+") must match output depth for filter ("+n[4]+")."});var s=ho(i.shape,n,r,1,o);return Vt.runKernelFunc(function(t){return t.conv3dDerFilter(i,a,s)},{x5D:i,dy5D:a})}(n,t,r.shape,o,i)}}});return l?f.as4D(f.shape[1],f.shape[2],f.shape[3],f.shape[4]):f}}),hc=mn({conv2dDerFilter_:function(t,e,n,r,o,i,a){void 0===i&&(i="NHWC");var s=t;3===t.rank&&(s=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var u=e;3===u.rank&&(u=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),P(4===s.rank,function(){return"Error in conv2dDerFilter: input must be rank 4, but got shape "+s.shape+"."}),P(4===u.rank,function(){return"Error in conv2dDerFilter: dy must be rank 4, but got shape "+u.shape+"."}),P(4===n.length,function(){return"Error in conv2dDerFilter: filterShape must be length 4, but got "+n+"."});var c="NHWC"===i?s.shape[3]:s.shape[1],l="NHWC"===i?u.shape[3]:u.shape[1];P(c===n[2],function(){return"Error in conv2dDerFilter: depth of input "+c+") must match input depth in filter ("+n[2]+"."}),P(l===n[3],function(){return"Error in conv2dDerFilter: depth of dy ("+l+") must match output depth for filter ("+n[3]+")."}),null!=a&&P(B(o),function(){return"Error in conv2dDerFilter: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+o+"."});var h=bo(i),f=lo(s.shape,n,r,1,o,a,!1,h);return Vt.runKernelFunc(function(t){return t.conv2dDerFilter(s,u,f)},{x4D:s,dy4D:u})}}),fc=mn({conv2dDerInput_:ic}),pc=mn({depthwiseConv2d_:function(t,e,n,r,o,i,a){void 0===i&&(i=[1,1]);var s=rn(t,"x","depthwiseConv2d"),u=rn(e,"filter","depthwiseConv2d"),c=s,l=!1;3===s.rank&&(l=!0,c=s.as4D(1,s.shape[0],s.shape[1],s.shape[2])),P(4===c.rank,function(){return"Error in depthwiseConv2d: input must be rank 4, but got rank "+c.rank+"."}),P(4===u.rank,function(){return"Error in depthwiseConv2d: filter must be rank 4, but got rank "+u.rank+"."}),P(c.shape[3]===u.shape[2],function(){return"Error in depthwiseConv2d: number of input channels ("+c.shape[3]+") must match the inChannels dimension in filter "+u.shape[2]+"."}),null==i&&(i=[1,1]),P(xo(n,i),function(){return"Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+i+"'"}),null!=a&&P(B(r),function(){return"Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+r+"."});var h=lo(c.shape,u.shape,n,i,r,a,!0),f=[c,u],p=Vt.runKernelFunc(function(t,e){var n=t.depthwiseConv2D(c,u,h);return e([c,u]),n},{x:c,filter:u},function(t,e){P(yo(i),function(){return"Error in gradient of depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '"+i+"'"});var n=e[0],r=e[1];return{x:function(){return dc(n.shape,t,r,h)},filter:function(){return vc(n,t,r.shape,h)}}},"DepthwiseConv2dNative",h,f);return l?p.as3D(p.shape[1],p.shape[2],p.shape[3]):p}}),dc=mn({depthwiseConv2dDerInput_:function(t,e,n,r){var o=e,i=!1;3===e.rank&&(i=!0,o=e.as4D(1,e.shape[0],e.shape[1],e.shape[2]));var a=Vt.runKernelFunc(function(t){return t.depthwiseConv2DDerInput(o,n,r)},{dy4D:o});return i?a.as3D(a.shape[1],a.shape[2],a.shape[3]):a}}),vc=mn({depthwiseConv2dDerFilter_:function(t,e,n,r){var o=t;3===t.rank&&(o=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var i=e;return 3===i.rank&&(i=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),Vt.runKernelFunc(function(t){return t.depthwiseConv2DDerFilter(o,i,r)},{x4D:o,dy4D:i})}}),mc=mn({separableConv2d_:function(t,e,n,r,o,i,a){void 0===i&&(i=[1,1]),void 0===a&&(a="NHWC");var s=rn(t,"x","separableConv2d"),u=rn(e,"depthwiseFilter","separableConv2d"),c=rn(n,"pointwiseFilter","separableConv2d"),l=s,h=!1;if(3===s.rank&&(h=!0,l=s.as4D(1,s.shape[0],s.shape[1],s.shape[2])),"NCHW"===a)throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");P(4===l.rank,function(){return"Error in separableConv2d: input must be rank 4, but got rank "+l.rank+"."}),P(4===u.rank,function(){return"Error in separableConv2d: depthwise filter must be rank 4, but got rank "+u.rank+"."}),P(4===c.rank,function(){return"Error in separableConv2d: pointwise filter must be rank 4, but got rank "+u.rank+"."}),P(1===c.shape[0],function(){return"Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got "+c.shape[0]+"."}),P(1===c.shape[1],function(){return"Error in separableConv2d: the second dimension of pointwise filter must be 1, but got "+c.shape[1]+"."});var f=u.shape[2],p=u.shape[3];P(c.shape[2]===f*p,function(){return"Error in separableConv2d: the third dimension of pointwise filter must be "+f*p+", but got "+c.shape[2]+"."});var d=pc(l,u,r,o,a,i),v=cc(d,c,1,"valid",a);return h?v.as3D(v.shape[1],v.shape[2],v.shape[3]):v}}),gc=mn({conv2dTranspose_:function(t,e,n,r,o,i){return ic(n,rn(t,"x","conv2dTranspose"),rn(e,"filter","conv2dTranspose"),r,o,"NHWC",i)}}),yc=mn({conv3dTranspose_:function(t,e,n,r,o){return sc(n,rn(t,"x","conv3dTranspose"),rn(e,"filter","conv3dTranspose"),r,o)}}),xc=mn({matMul_:function(t,e,i,a){var n;void 0===i&&(i=!1),void 0===a&&(a=!1);var r=rn(t,"a","matMul"),o=rn(e,"b","matMul");n=Nt(r,o),r=n[0],o=n[1];var s=i?r.shape[r.rank-2]:r.shape[r.rank-1],u=a?o.shape[o.rank-1]:o.shape[o.rank-2],c=i?r.shape[r.rank-1]:r.shape[r.rank-2],l=a?o.shape[o.rank-2]:o.shape[o.rank-1],h=r.shape.slice(0,-2),f=o.shape.slice(0,-2),p=L(h),d=L(f);P(2<=r.rank&&2<=o.rank&&r.rank===o.rank,function(){return"Error in matMul: inputs must have the same rank of at least 2, got ranks "+r.rank+" and "+o.rank+"."}),P(D(h,f),function(){return"Error in matMul: outer dimensions ("+h+") and ("+f+") of Tensors with shapes "+r.shape+" and "+o.shape+" must match."}),P(s===u,function(){return"Error in matMul: inner shapes ("+s+") and ("+u+") of Tensors with shapes "+r.shape+" and "+o.shape+" and transposeA="+i+" and transposeB="+a+" must match."});var v=r.shape.slice(0,-2).concat([c,l]),m=i?r.as3D(p,s,c):r.as3D(p,c,s),g=a?o.as3D(d,l,u):o.as3D(d,u,l),y={transposeA:i,transposeB:a};return Vt.runKernelFunc(function(t,e){var n=t.batchMatMul(m,g,i,a);return e([m,g]),n},{a:m,b:g},function(t,e){var n=e,r=n[0],o=n[1];return i||a?!i&&a?{a:function(){return t.matMul(o,!1,!1)},b:function(){return t.matMul(r,!0,!1)}}:i&&!a?{a:function(){return o.matMul(t,!1,!0)},b:function(){return r.matMul(t,!1,!1)}}:{a:function(){return o.matMul(t,!0,!0)},b:function(){return t.matMul(r,!0,!0)}}:{a:function(){return t.matMul(o,!1,!0)},b:function(){return r.matMul(t,!0,!1)}}},"BatchMatMul",y).reshape(v)}}),bc=mn({dot_:function(t,e){var n=rn(t,"t1","dot"),r=rn(e,"t2","dot");P(!(1!==n.rank&&2!==n.rank||1!==r.rank&&2!==r.rank),function(){return"Error in dot: inputs must all be rank 1 or 2, but got ranks "+n.rank+" and "+r.rank+"."});var o=1===n.rank?n.size:n.shape[1],i=1===r.rank?r.size:r.shape[0];return P(o===i,function(){return"Error in dot: inner dimensions of inputs must match, but got "+o+" and "+i+"."}),1===n.rank&&1===r.rank?n.as2D(1,-1).matMul(r.as2D(-1,1)).asScalar():1===n.rank&&2===r.rank?n.as2D(1,-1).matMul(r.as2D(r.shape[0],r.shape[1])).as1D():2===n.rank&&1===r.rank?n.matMul(r.as2D(-1,1)).as1D():n.matMul(r.as2D(r.shape[0],r.shape[1]))}}),wc=mn({outerProduct_:function(t,e){var n=rn(t,"v1","outerProduct"),r=rn(e,"v2","outerProduct");return P(1===n.rank&&1===r.rank,function(){return"Error in outerProduct: inputs must be rank 1, but got ranks "+n.rank+" and "+r.rank+"."}),n.as2D(-1,1).matMul(r.as2D(1,-1))}}),Cc=mn({reverse_:function(t,e){var n=rn(t,"x","reverse");if(0===n.rank)return n.clone();var r=I(e,n.shape);return Vt.runKernelFunc(function(t){return t.reverse(n,r)},{$x:n},function(t){return{$x:function(){return t.reverse(r)}}}).reshapeAs(n)}}),Ec=mn({reverse1d_:function(t){var e=rn(t,"x","reverse");return P(1===e.rank,function(){return"Error in reverse1D: x must be rank 1 but got rank "+e.rank+"."}),Cc(e,0)}}),_c=mn({reverse2d_:function(t,e){var n=rn(t,"x","reverse");return P(2===n.rank,function(){return"Error in reverse2D: x must be rank 2 but got rank "+n.rank+"."}),Cc(n,e)}}),Ic=mn({reverse3d_:function(t,e){var n=rn(t,"x","reverse");return P(3===n.rank,function(){return"Error in reverse3D: x must be rank 3 but got rank "+n.rank+"."}),Cc(n,e)}}),Rc=mn({reverse4d_:function(t,e){var n=rn(t,"x","reverse");return P(4===n.rank,function(){return"Error in reverse4D: x must be rank 4 but got rank "+n.rank+"."}),Cc(n,e)}});function kc(t,r,o,i,a,e){var n=rn(t,"x","maxPool"),s=n,u=!1;3===n.rank&&(u=!0,s=n.as4D(1,n.shape[0],n.shape[1],n.shape[2])),null==i&&(i=[1,1]),P(4===s.rank,function(){return"Error in maxPool: input must be rank 4 but got rank "+s.rank+"."}),P(xo(o,i),function(){return"Error in maxPool: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+i+"'"}),null!=e&&P(B(a),function(){return"Error in maxPool: pad must be an integer when using, dimRoundingMode "+e+" but got pad "+a+"."});var c=uo(s.shape,r,o,i,a,e);if(1===c.filterWidth&&1===c.filterHeight&&D(c.inShape,c.outShape))return n.clone();var l=[s],h=Vt.runKernelFunc(function(t,e){var n=t.maxPool(s,c);return e([s,n]),n},{x:s},function(h,t){var e=t[0],n=t[1];return{x:function(){return function(t,e,n,r,o,i,a){var s=rn(h,"dy","maxPoolBackprop"),u=rn(e,"input","maxPoolBackprop"),c=rn(n,"output","maxPoolBackprop");P(u.rank===s.rank,function(){return"Rank of input ("+u.rank+") does not match rank of dy ("+s.rank+")"}),null==i&&(i=[1,1]),P(xo(o,i),function(){return"Error in maxPoolBackProp: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+i+"'"}),P(4===s.rank,function(){return"Error in maxPoolBackprop: dy must be rank 4 but got rank "+s.rank+"."}),P(4===u.rank,function(){return"Error in maxPoolBackprop: input must be rank 4 but got rank "+u.rank+"."});var l=uo(u.shape,r,o,i,a,void 0);return Vt.runKernelFunc(function(t){return t.maxPoolBackprop(s,u,c,l)},{$dy:s,$input:u})}(0,e,n,r,o,i,a)}}},"MaxPool",c,l);return u?h.as3D(h.shape[1],h.shape[2],h.shape[3]):h}function Sc(t,e,n,r,o,i){var a=rn(t,"x","avgPool","float32");null==r&&(r=[1,1]),P(xo(n,r),function(){return"Error in avgPool: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+r+"'"});var s=a,u=!1;3===a.rank&&(u=!0,s=a.as4D(1,a.shape[0],a.shape[1],a.shape[2])),P(4===s.rank,function(){return"Error in avgPool: x must be rank 4 but got rank "+s.rank+"."}),null!=i&&P(B(o),function(){return"Error in avgPool: pad must be an integer when using, dimRoundingMode "+i+" but got pad "+o+"."});var c=uo(s.shape,e,n,r,o,i);if(1===c.filterWidth&&1===c.filterHeight&&D(c.inShape,c.outShape))return a.clone();var l=Vt.runKernelFunc(function(t){return t.avgPool(s,c)},{x:s},function(p){return{x:function(){return function(t,e,n,r,o,i){var a=rn(p,"dy","avgPoolBackprop"),s=rn(e,"input","avgPoolBackprop");P(s.rank===a.rank,function(){return"Rank of input ("+s.rank+") does not match rank of dy ("+a.rank+")"}),null==o&&(o=[1,1]),P(xo(r,o),function(){return"Error in avgPoolBackprop: Either strides or dilations must be 1. Got strides "+r+" and dilations '"+o+"'"});var u=s,c=a,l=!1;3===s.rank&&(l=!0,u=s.as4D(1,s.shape[0],s.shape[1],s.shape[2]),c=a.as4D(1,a.shape[0],a.shape[1],a.shape[2])),P(4===c.rank,function(){return"Error in avgPoolBackprop: dy must be rank 4 but got rank "+c.rank+"."}),P(4===u.rank,function(){return"Error in avgPoolBackprop: input must be rank 4 but got rank "+u.rank+"."});var h=uo(u.shape,n,r,o,i),f=Vt.runKernelFunc(function(t){return t.avgPoolBackprop(c,u,h)},{dy4D:c,input4D:u});return l?f.as3D(f.shape[1],f.shape[2],f.shape[3]):f}(0,s,e,n,r,o)}}},"AvgPool",c);return l=l.cast(a.dtype),u?l.as3D(l.shape[1],l.shape[2],l.shape[3]):l}var Dc=mn({maxPool_:function(t,e,n,r,o){return kc(t,e,n,1,r,o)}}),Ac=mn({avgPool_:function(t,e,n,r,o){return Sc(t,e,n,1,r,o)}}),Tc=mn({pool_:function(t,e,n,r,o,i){null==o&&(o=[1,1]),null==i&&(i=1),0===r&&(r="valid");var a=rn(t,"x","maxPool"),s=a,u=!1;3===a.rank&&(u=!0,s=a.as4D(1,a.shape[0],a.shape[1],a.shape[2])),P(xo(i,o),function(){return"Error in pool: Either strides or dilations must be 1. Got strides "+i+" and dilations '"+o+"'"});var c,l,h,f,p,d,v=uo(s.shape,e,i,o,r),m=[v.dilationHeight,v.dilationWidth];c="same"===r?(l=[v.filterHeight,v.filterWidth],h=m,f=l.map(function(t,e){return t+(t-1)*(h[e]-1)}).map(function(t){return t-1}),p=f.map(function(t){return Math.floor(t/2)}),d=f.map(function(t,e){return t-p[e]}),f.map(function(t,e){return[p[e],d[e]]})):[[0,0],[0,0]];var g,y,x,b,w,C,E,_,I=1===m[0]&&1===m[1],R=(g=[v.inHeight,v.inWidth],y=m,b=(x=c).map(function(t){return t[0]}),w=x.map(function(t){return t[1]}),C=g.concat(b,w),E=y.map(function(t,e){return(t-C[e]%t)%t}),_=w.map(function(t,e){return t+E[e]}),[y.map(function(t,e){return[b[e],_[e]]}),y.map(function(t,e){return[0,E[e]]})]),k=R[1],S=I?r:"valid",D=I?s:kr(s,m,R[0]),A=("avg"===n?function(){return Sc(D,e,i,1,S)}:function(){return kc(D,e,i,1,S)})(),T=I?A:sr(A,m,k);return u?T.as3D(T.shape[1],T.shape[2],T.shape[3]):T}}),Fc=mn({maxPool3d_:function(t,r,o,i,a,e,s){void 0===e&&(e="NDHWC");var n=rn(t,"x","maxPool3d"),u=n,c=!1;4===n.rank&&(c=!0,u=n.as5D(1,n.shape[0],n.shape[1],n.shape[2],n.shape[3])),null==s&&(s=[1,1,1]),P(5===u.rank,function(){return"Error in maxPool3d: x must be rank 5 but got rank "+u.rank+"."}),P("NDHWC"===e,function(){return"Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of "+e}),P(xo(o,s),function(){return"Error in maxPool3d: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+s+"'"}),null!=a&&P(B(i),function(){return"Error in maxPool3d: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+i+"."});var l=co(u.shape,r,o,s,i,a,e),h=Vt.runKernelFunc(function(t,e){var n=t.maxPool3d(u,l);return e([u,n]),n},{x:u},function(g,t){var e=t[0],n=t[1];return{x:function(){return function(t,e,n,r,o,i,a,s){var u=rn(g,"dy","maxPool3dBackprop"),c=rn(e,"input","maxPool3dBackprop"),l=rn(n,"output","maxPool3dBackprop"),h=u,f=c,p=l,d=!1;4===c.rank&&(d=!0,h=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]),f=c.as5D(1,c.shape[0],c.shape[1],c.shape[2],c.shape[3]),p=l.as5D(1,l.shape[0],l.shape[1],l.shape[2],l.shape[3])),P(5===h.rank,function(){return"Error in maxPool3dBackprop: dy must be rank 5 but got rank "+h.rank+"."}),P(5===f.rank,function(){return"Error in maxPool3dBackprop: input must be rank 5 but got rank "+f.rank+"."}),P(5===p.rank,function(){return"Error in maxPool3dBackprop: output must be rank 5 but got rank "+p.rank+"."}),null==i&&(i=[1,1,1]),P(xo(o,i),function(){return"Error in maxPool3dBackprop: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+i+"'"}),null!=s&&P(B(a),function(){return"Error in maxPool3dBackprop: pad must be an integer when using, dimRoundingMode "+s+" but got pad "+a+"."});var v=co(f.shape,r,o,i,a,s),m=Vt.runKernelFunc(function(t){return t.maxPool3dBackprop(h,f,p,v)},{dy5D:h,input5D:f});return d?m.as4D(m.shape[1],m.shape[2],m.shape[3],m.shape[4]):m}(0,e,n,r,o,s,i,a)}}});return c?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}}),Nc=mn({avgPool3d_:function(t,e,n,r,o,i,a){void 0===i&&(i="NDHWC");var s=rn(t,"x","avgPool3d","float32"),u=s,c=!1;4===s.rank&&(c=!0,u=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3])),null==a&&(a=[1,1,1]),P(5===u.rank,function(){return"Error in avgPool3d: x must be rank 5 but got rank "+u.rank+"."}),P("NDHWC"===i,function(){return"Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of "+i}),P(xo(n,a),function(){return"Error in avgPool3d: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+a+"'"}),null!=o&&P(B(r),function(){return"Error in avgPool3d: pad must be an integer when using, dimRoundingMode "+o+" but got pad "+r+"."});var l=co(u.shape,e,n,a,r,o,i),h=Vt.runKernelFunc(function(t){return t.avgPool3d(u,l)},{x:u},function(d){return{x:function(){return function(t,e,n,r,o,i,a){var s=rn(d,"dy","avgPool3dBackprop"),u=rn(e,"input","avgPool3dBackprop"),c=s,l=u,h=!1;4===u.rank&&(h=!0,c=s.as5D(1,s.shape[0],s.shape[1],s.shape[2],s.shape[3]),l=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3])),P(5===c.rank,function(){return"Error in avgPool3dBackprop: dy must be rank 5 but got rank "+c.rank+"."}),P(5===l.rank,function(){return"Error in avgPool3dBackprop: input must be rank 5 but got rank "+l.rank+"."}),null==o&&(o=[1,1,1]),P(xo(r,o),function(){return"Error in avgPool3dBackprop: Either strides or dilations must be 1. Got strides "+r+" and dilations '"+o+"'"}),null!=a&&P(B(i),function(){return"Error in maxPool3dBackprop: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+i+"."});var f=co(l.shape,n,r,o,i,a),p=Vt.runKernelFunc(function(t){return t.avgPool3dBackprop(c,l,f)},{dy5D:c,input5D:l});return h?p.as4D(p.shape[1],p.shape[2],p.shape[3],p.shape[4]):p}(0,u,e,n,a,r,o)}}});return h=h.cast(u.dtype),c?h.as4D(h.shape[1],h.shape[2],h.shape[3],h.shape[4]):h}}),Mc=mn({slice_:function(t,e,n){var r,o,i=rn(t,"x","slice");if(0===i.rank)throw new Error("Slicing scalar is not possible");(r="number"==typeof e?[e].concat(new Array(i.rank-1).fill(0)):e.length<i.rank?e.concat(new Array(i.rank-e.length).fill(0)):e.slice()).forEach(function(t){P(-1!==t,function(){return"slice() does not support negative begin indexing."})}),o=(o=null==n?new Array(i.rank).fill(-1):"number"==typeof n?[n].concat(new Array(i.rank-1).fill(-1)):n.length<i.rank?n.concat(new Array(i.rank-n.length).fill(-1)):n).map(function(t,e){return 0<=t?t:(P(-1===t,function(){return"Negative size values should be exactly -1 but got "+t+" for the slice() size at index "+e+"."}),i.shape[e]-r[e])}),Ur(i,r,o);var a=i.shape,s={begin:r,size:o};return Vt.runKernelFunc(function(t){return t.slice(i,r,o)},{x:i},function(t){for(var e=[],n=0;n<t.rank;n++)e.push([r[n],a[n]-r[n]-o[n]]);return{x:function(){return t.pad(e)}}},"Slice",s)}}),Oc=mn({slice1d_:function(t,e,n){var r=rn(t,"x","slice1d");return P(1===r.rank,function(){return"slice1d expects a rank-1 tensor, but got a rank-"+r.rank+" tensor"}),Mc(r,[e],[n])}}),Pc=mn({slice2d_:function(t,e,n){var r=rn(t,"x","slice2d");return P(2===r.rank,function(){return"slice2d expects a rank-2 tensor, but got a rank-"+r.rank+" tensor"}),Mc(r,e,n)}}),Bc=mn({slice3d_:function(t,e,n){var r=rn(t,"x","slice3d");return P(3===r.rank,function(){return"slice3d expects a rank-3 tensor, but got a rank-"+r.rank+" tensor"}),Mc(r,e,n)}}),Lc=mn({slice4d_:function(t,e,n){var r=rn(t,"x","slice4d");return P(4===r.rank,function(){return"slice4d expects a rank-4 tensor, but got a rank-"+r.rank+" tensor"}),Mc(r,e,n)}});function Wc(e,n,r,t,o){return n.rank<r.rank&&(n=n.reshape(cn(n.shape,t))),e.rank<r.rank&&(e=e.reshape(cn(e.shape,t))),{x:function(){var t=e.mul(r.equal(n).cast(e.dtype));return null==o?t:t.transpose(o)}}}var zc=mn({all_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=rn(t,"x","all","bool"),o=I(e,r.shape),i=o,a=hn(i,r.rank);null!=a&&(r=r.transpose(a),i=pn(i.length,r.rank));var s=Vt.runKernelFunc(function(t){return t.all(r,i)},{$x:r});if(n){var u=cn(s.shape,o);return s.reshape(u)}return s}}),Uc=mn({any_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=rn(t,"x","any","bool"),o=I(e,r.shape),i=o,a=hn(i,r.rank);null!=a&&(r=r.transpose(a),i=pn(i.length,r.rank));var s=Vt.runKernelFunc(function(t){return t.any(r,i)},{$x:r});if(n){var u=cn(s.shape,o);return s.reshape(u)}return s}}),Vc=mn({argMax_:function(t,e){void 0===e&&(e=0);var r=rn(t,"x","argMax");null==e&&(e=0);var o=I(e,r.shape),n=hn(o,r.rank);null!=n&&(r=r.transpose(n),o=pn(o.length,r.rank));var i={axis:o[0]},a=[r];return Vt.runKernelFunc(function(t,e){var n=t.argMax(r,o[0]);return e([r]),n},{x:r},function(t,e){var n=e[0];return{x:function(){return Pn(n)}}},"ArgMax",i,a)}}),Gc=mn({argMin_:function(t,e){void 0===e&&(e=0);var r=rn(t,"x","argMin");null==e&&(e=0);var o=I(e,r.shape),n=hn(o,r.rank);return null!=n&&(r=r.transpose(n),o=pn(o.length,r.rank)),Vt.runKernelFunc(function(t,e){var n=t.argMin(r,o[0]);return e([r]),n},{$x:r},function(t,e){var n=e[0];return{$x:function(){return Pn(n)}}})}}),Hc=mn({logSumExp_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=rn(t,"x","logSumExp"),o=I(e,r.shape),i=r.max(o,!0),a=r.sub(i).exp().sum(o).log(),s=i.reshape(a.shape).add(a);if(n){var u=cn(s.shape,o);return s.reshape(u)}return s}}),qc=mn({max_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=rn(t,"x","max"),o=r,i=I(e,r.shape),a=i,s=hn(a,r.rank);null!=s&&(r=r.transpose(s),a=pn(a.length,r.rank));var u=[r],c=Vt.runKernelFunc(function(t,e){var n=t.max(r,a);return e([o,n]),n},{x:r},function(t,e){return Wc(t,e[1],e[0],i,s)},"Max",{axes:a},u,[!0]);if(n){var l=cn(c.shape,i);c=c.reshape(l)}return c}}),jc=mn({mean_:function(t,e,r){void 0===e&&(e=null),void 0===r&&(r=!1);var n=rn(t,"x","mean"),o=I(e,n.shape),i=L(un(n.shape,o)[1]);return Yr(function(n){var t=Cn(i);return{value:(t.dtype===n.dtype?n:n.cast(t.dtype)).div(t).sum(e,r),gradFunc:function(t){var e=n.shape.slice();return o.forEach(function(t){e[t]=1}),t.reshape(e).mul(An(n.shape,"float32")).div(i)}}})(n)}}),Kc=mn({min_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=rn(t,"x","min"),o=r,i=I(e,r.shape),a=i,s=hn(a,r.rank);null!=s&&(r=r.transpose(s),a=pn(a.length,r.rank));var u=[r],c=Vt.runKernelFunc(function(t,e){var n=t.min(r,a);return e([o,n]),n},{x:r},function(t,e){return Wc(t,e[1],e[0],i,s)},"Min",{axes:a},u,[!0]);if(n){var l=cn(c.shape,i);c=c.reshape(l)}return c}}),Xc=mn({moments_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=I(e,(t=rn(t,"x","moments")).shape),o=t.mean(r,n),i=o.shape;n||(i=cn(o.shape,r));var a=t.toFloat().sub(o.reshape(i)).square();return{mean:o,variance:a.mean(r,n)}}}),$c=mn({sum_:function(t,e,a){void 0===e&&(e=null),void 0===a&&(a=!1);var n=rn(t,"x","sum");"bool"===n.dtype&&(n=n.toInt());var s=I(e,n.shape);return Yr(function(n){var t=hn(s,n.rank),e=s,r=n;null!=t&&(r=n.transpose(t),e=pn(e.length,n.rank));var o=Vt.runKernelFunc(function(t){return t.sum(r,e)},{permutedX:r});if(a){var i=cn(o.shape,s);o=o.reshape(i)}return{value:o,gradFunc:function(t){var e=n.shape.slice();return s.forEach(function(t){e[t]=1}),t.reshape(e).mul(An(n.shape,"float32"))}}})(n)}}),Yc=mn({prod_:function(t,e,n){void 0===e&&(e=null),void 0===n&&(n=!1);var r=rn(t,"x","prod");"bool"===r.dtype&&(r=r.toInt());var o=I(e,r.shape),i=hn(o,r.rank),a=o,s=r;null!=i&&(s=r.transpose(i),a=pn(a.length,r.rank));var u=Vt.runKernelFunc(function(t){return t.prod(s,a)},{permutedX:s});if(n){var c=cn(u.shape,o);u=u.reshape(c)}return u}}),Jc=mn({elu_:function(t){var r=rn(t,"x","elu");return Vt.runKernelFunc(function(t,e){var n=t.elu(r);return e([n]),n},{$x:r},function(e,t){var n=t[0];return{$x:function(){return Vt.runKernelFunc(function(t){return t.eluDer(e,n)},{dy:e,y:n})}}})}}),Qc=mn({leakyRelu_:function(t,e){void 0===e&&(e=.2);var n=rn(t,"x","leakyRelu");return Su(Cn(e).mul(n),n)}}),Zc=mn({prelu_:function(t,e){var r=rn(t,"x","prelu"),o=rn(e,"alpha","prelu");return Vt.runKernelFunc(function(t,e){var n=t.prelu(r,o);return e([r,o]),n},{x:r,alpha:o},function(n,t){var r=t[0],o=t[1],i=r.greater(0);return{x:function(){return xu(i,n,n.mul(o))},alpha:function(){var t=xu(i,Pn(n),n.mul(r)),e=ao(o.shape,n.shape);return 0<e.length&&(t=t.sum(e)),t.reshape(o.shape)}}},"Prelu")}}),tl=mn({relu_:function(t){var r=rn(t,"x","relu");return"bool"===r.dtype?r.toInt():Vt.runKernelFunc(function(t,e){var n=t.relu(r);return e([r]),n},{x:r},function(t,e){var n=e[0];return{x:function(){return t.mulStrict(n.step().toFloat())}}},"Relu")}}),el=mn({relu6_:function(t){var r=rn(t,"x","relu6");return"bool"===r.dtype?r.toInt():Vt.runKernelFunc(function(t,e){var n=t.relu6(r);return e([r]),n},{x:r},function(t,e){var n=e[0],r=n.lessEqual(6).mul(n.step());return{x:function(){return t.mulStrict(r.toFloat())}}},"Relu6")}}),nl=mn({selu_:function(t){var r=rn(t,"x","selu");return Vt.runKernelFunc(function(t,e){var n=t.selu(r);return e([r]),n},{$x:r},function(i,t){var a=t[0];return{$x:function(){var t=a.greater(Cn(0)),e=Cn($a),n=Cn(Ya),r=i.mul(n),o=i.mul(e).mul(a.toFloat().exp());return xu(t,r,o)}}})}}),rl=mn({transpose_:function(t,n){var e=rn(t,"x","transpose");if(null==n&&(n=e.shape.map(function(t,e){return e}).reverse()),P(e.rank===n.length,function(){return"Error in transpose: rank of input "+e.rank+" must match 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e([r,n]),n},{x4D:r},function(e,t){var n=t[0],r=t[1];return{x4D:function(){return Vt.runKernelFunc(function(t){return t.LRNGrad(e,n,r,o,i,a,s)},{})}}});return n?u.as3D(u.shape[1],u.shape[2],u.shape[3]):u}}),il=mn({norm_:function(t,e,n,r){void 0===e&&(e="euclidean"),void 0===n&&(n=null),void 0===r&&(r=!1);var o=function t(e,n,r){if(void 0===r&&(r=null),0===e.rank)return e.abs();if(1!==e.rank&&null===r)return t(e.reshape([-1]),n,r);if(1===e.rank||"number"==typeof r||Array.isArray(r)&&1===r.length){if(1===n)return e.abs().sum(r);if(n===1/0)return e.abs().max(r);if(n===-1/0)return e.abs().min(r);if("euclidean"===n||2===n)return e.abs().pow(Cn(2,"int32")).sum(r).sqrt();throw new Error("Error in norm: invalid ord value: "+n)}if(Array.isArray(r)&&2===r.length){if(1===n)return e.abs().sum(r[0]).max(r[1]-1);if(n===1/0)return e.abs().sum(r[1]).max(r[0]);if(n===-1/0)return e.abs().sum(r[1]).min(r[0]);if("fro"===n||"euclidean"===n)return e.square().sum(r).sqrt();throw new Error("Error in norm: invalid ord value: "+n)}throw new Error("Error in norm: invalid axis: "+r)}(t=rn(t,"x","norm"),e,n),i=o.shape;if(r){var a=I(n,t.shape);i=cn(o.shape,a)}return o.reshape(i)}}),al=mn({basicLSTMCell_:function(t,e,n,r,o,i){var a=rn(t,"forgetBias","basicLSTMCell"),s=rn(e,"lstmKernel","basicLSTMCell"),u=rn(n,"lstmBias","basicLSTMCell"),c=rn(r,"data","basicLSTMCell"),l=rn(o,"c","basicLSTMCell"),h=rn(i,"h","basicLSTMCell"),f=c.concat(h,1).matMul(s).add(u),p=f.shape[0],d=f.shape[1]/4,v=[p,d],m=f.slice([0,0],v),g=f.slice([0,d],v),y=f.slice([0,2*d],v),x=f.slice([0,3*d],v),b=m.sigmoid().mulStrict(g.tanh()).addStrict(l.mulStrict(a.add(y).sigmoid())),w=b.tanh().mulStrict(x.sigmoid());return[b,w]}}),sl=mn({multiRNNCell_:function(t,e,n,r){for(var o=rn(e,"data","multiRNNCell"),i=on(n,"c","multiRNNCell"),a=on(r,"h","multiRNNCell"),s=o,u=[],c=0;c<t.length;c++){var l=t[c](s,i[c],a[c]);u.push(l[0]),u.push(l[1]),s=l[1]}var h=[],f=[];for(c=0;c<u.length;c+=2)h.push(u[c]),f.push(u[c+1]);return[h,f]}}),ul=mn({movingAverage_:function(t,e,n,r,o){void 0===o&&(o=!0);var i=rn(t,"v","movingAverage"),a=rn(e,"x","movingAverage"),s=rn(n,"decay","movingAverage");Mt(i,a),P(D(i.shape,a.shape),function(){return"Shape mismatch in v and x"});var u=Cn(1),c=u.sub(s),l=a.sub(i).mul(c);if(o){P(null!=r,function(){return"When using zeroDebias: true, step is required."});var h=rn(r,"step","movingAverage");l=l.div(u.sub(Pu(s,h)))}return i.add(l)}}),cl=mn({stridedSlice_:function(t,e,n,r,o,i,a,s,u){if(void 0===o&&(o=0),void 0===i&&(i=0),void 0===a&&(a=0),void 0===s&&(s=0),void 0===u&&(u=0),null==r&&(r=new Array(e.length)),0!==a)throw new Error("ellipsis mask is not yet supported");var c=rn(t,"x","stridedSlice"),l=Vr(s),h=c.shape.slice();l.forEach(function(t){e[t]=0,n[t]=1,h.splice(t,0,1)}),c=c.reshape(h);for(var f=0;f<c.rank;f++)e[f]=Hr(o,e,r,c.shape,f),n[f]=qr(i,n,r,c.shape,f),r[f]=r[f]||1;var p=Vr(u);p.forEach(function(t){n[t]=e[t]+1,r[t]=1});var d=Gr(e,n,r),v=d.filter(function(t,e){return-1===p.indexOf(e)});return r.every(function(t){return 1===t})?Mc(c,e,d).reshape(v):Vt.runKernelFunc(function(t){return t.stridedSlice(c,e,n,r)},{$x:c}).reshape(v)}}),ll=mn({topk_:function(t,e,n){void 0===e&&(e=1),void 0===n&&(n=!0);var r=rn(t,"x","topk");if(0===r.rank)throw new Error("topk() expects the input to be of rank 1 or higher");var o=r.shape[r.shape.length-1];if(o<e)throw new Error("'k' passed to topk() must be <= the last dimension ("+o+") but got "+e);var i=Vt.runKernelFunc(function(t){return t.topk(r,e,n)},{$x:r});return{values:i[0],indices:i[1]}}}),hl=mn({scatterND_:function(t,e,n){var r=rn(t,"indices","scatterND","int32"),o=rn(e,"updates","scatterND");return function(t,e,n){if(e.rank<1)throw new Error("tf.scatterND() expects the indices to be rank 1 or higher, but the rank was "+e.rank+".");if(t.rank<1)throw new Error("tf.scatterND() expects the updates to be rank 1 or higher, but the rank was "+t.rank+".");if("int32"!==e.dtype)throw new Error("The dtype of 'indices' should be int32, but got dtype: "+e.dtype);if(n.length<1)throw new Error("Output rank must be greater or equal to 1, but got shape: "+n);if(0===n.length){if(0===e.size)throw new Error("Indices specified for empty output. indices shape: "+e.shape);if(0===t.size)throw new Error("Updates specified for empty output. updates shape: "+t.shape)}!function(t,e,n){var r=1<e.rank?e.shape[e.rank-1]:1,o=1<e.rank?e.rank-1:1,i="Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: "+n.shape+", indices.shape: "+e.shape+", shape: "+t+", sliceDim: "+r+", and batchDim: "+o+".";if(n.rank<o)throw new Error(i+" update.rank < "+o+". ");if(t.length<r+(n.rank-o))throw new Error(i+" Output shape length < "+(r+(n.rank-o)));if(n.rank!==o+t.length-r)throw new Error(i+" update.rank != "+(o+t.length-r));for(var a=0;a<o;++a)if(n.shape[a]!==e.shape[a])throw new Error(i+" updates.shape["+a+"] ("+n.shape[a]+") != indices.shape["+a+"] ("+e.shape[a]+").");for(a=0;a<n.rank-o;++a)if(n.shape[a+o]!==t[a+r])throw new Error(i+" updates.shape["+(a+o)+"] ("+n.shape[a+o]+") != shape["+(a+o)+"] ("+t[a+o]+")")}(n,e,t)}(o,r,n),Vt.runKernelFunc(function(t){return t.scatterND(r,o,n)},{$indices:r,$updates:o})}}),fl=mn({fft_:function(t){P("complex64"===t.dtype,function(){return"The dtype for tf.spectral.fft() must be complex64 but got "+t.dtype+"."});var e=t.shape[t.shape.length-1],n=t.size/e,r=t.as2D(n,e);return Vt.runKernelFunc(function(t){return t.fft(r)},{input:t}).reshape(t.shape)}}),pl=mn({ifft_:function(t){P("complex64"===t.dtype,function(){return"The dtype for tf.spectral.ifft() must be complex64 but got "+t.dtype+"."});var e=t.shape[t.shape.length-1],n=t.size/e,r=t.as2D(n,e);return Vt.runKernelFunc(function(t){return t.ifft(r)},{input:t}).reshape(t.shape)}}),dl=mn({rfft_:function(t,e){P("float32"===t.dtype,function(){return"The dtype for rfft() must be real value but got "+t.dtype});var n,r=t.shape[t.shape.length-1],o=t.size/r;if(null!=e&&e<r){var i=t.shape.map(function(t){return 0}),a=t.shape.map(function(t){return t});a[t.shape.length-1]=e,n=t.slice(i,a),r=e}else if(null!=e&&r<e){var s=t.shape.map(function(t){return t});s[t.shape.length-1]=e-r,n=t.concat(Tn(s),t.shape.length-1),r=e}else n=t;var u=n.zerosLike(),c=gn(n,u).as2D(o,r),l=fl(c),h=Math.floor(r/2)+1,f=yn(l),p=xn(l),d=f.split([h,r-h],f.shape.length-1),v=p.split([h,r-h],p.shape.length-1),m=n.shape.slice();return m[n.shape.length-1]=h,gn(d[0],v[0]).reshape(m)}}),vl=mn({irfft_:function(t){var e=t.shape[t.shape.length-1],n=t.size/e;if(e<=2){var r=t.as2D(n,e),o=pl(r);return yn(o)}var i=[n,2*(e-1)],a=yn(t).as2D(n,e),s=xn(t).as2D(n,e),u=a.slice([0,1],[n,e-2]).reverse(1),c=s.slice([0,1],[n,e-2]).reverse(1).mul(Cn(-1)),l=a.concat(u,1),h=s.concat(c,1);return r=gn(l,h).as2D(i[0],i[1]),o=pl(r),yn(o)}}),ml=Object.freeze({fft:fl,ifft:pl,rfft:dl,irfft:vl}),gl=mn({sparseToDense_:function(t,e,n,r){void 0===r&&(r=0);var o=rn(t,"sparseIndices","sparseToDense","int32"),i=rn(e,"sparseValues","sparseToDense"),a=rn(r,"defaultValue","sparseToDense",i.dtype);return function(t,e,n,r){if("int32"!==t.dtype)throw new Error("tf.sparseToDense() expects the indices to be int32 type, but the dtype was "+t.dtype+".");if(2<t.rank)throw new Error("sparseIndices should be a scalar, vector, or matrix, but got shape "+t.shape+".");var o=0<t.rank?t.shape[0]:1,i=1<t.rank?t.shape[1]:1;if(n.length!==i)throw new Error("outputShape has incorrect number of elements:, "+n.length+", should be: "+i+".");var a=e.size;if(0!==e.rank&&(1!==e.rank||a!==o))throw new Error("sparseValues has incorrect shape "+e.shape+", should be [] or ["+o+"]");if(e.dtype!==r.dtype)throw new Error("sparseValues.dtype must match defaultValues.dtype")}(o,i,n,a),Vt.runKernelFunc(function(t){return t.sparseToDense(o,i,n,a)},{$sparseIndices:o,$sparseValues:i,$defaultValue:a})}}),yl=mn({gatherND_:function(t,e){var n=rn(e,"indices","gatherND","int32"),r=rn(t,"x","gatherND");return Vt.runKernelFunc(function(t){return t.gatherND(r,n)},{$x:r,$indices:n})}}),xl=mn({diag_:function(t){var e=rn(t,"x","diag").flatten(),n=t.shape.concat(t.shape);return Vt.runKernelFunc(function(t){return t.diag(e)},{$x:e}).reshape(n)}}),bl=mn({dropout_:function(t,e,n,r){var o=rn(t,"x","dropout");if(P("float32"===o.dtype,function(){return"x has to be a floating point tensor since it's going to be scaled, but got a "+o.dtype+" tensor instead."}),P(0<=e&&e<1,function(){return"rate must be a float in the range [0, 1), but got "+e+"."}),0===e)return t instanceof vt?o.clone():o;var i=function(t,e){if(null==e)return t.shape.slice();if(D(t.shape,e))return e;if(t.shape.length!==e.length)return e;for(var n=[],r=0;r<t.shape.length;r++)null==e[r]&&null!=t.shape[r]?n.push(t.shape[r]):n.push(e[r]);return n}(o,n),a=1-e,s=Ir(i,0,1,"float32",r).add(a).floor().div(a);return o.mul(s)}});function wl(t,e,n){for(var r=1-t%2,o=new Float32Array(t),i=0;i<t;++i){var a=2*Math.PI*i/(t+r-1);o[i]=e-n*Math.cos(a)}return En(o,"float32")}function Cl(v,m,g){return void 0===g&&(g=1),y(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p,d;return R(this,function(t){switch(t.label){case 0:return e=rn(v,"predictions","inTopK"),n=rn(m,"targets","inTopK"),P(1<e.rank,function(){return"inTopK() expects the predictions to be of rank 2 or higher, but got "+e.rank}),P(e.rank-1===n.rank,function(){return"predictions rank should be 1 larger than targets rank, but got predictions rank "+e.rank+" and targets rank "+n.rank}),b(e.shape.slice(0,e.shape.length-1),n.shape,"predictions's shape should be align with the targets' shape, 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i;void 0===o&&(o=Il),null==r&&(i=e,r=Math.floor(Math.pow(2,Math.ceil(Math.log(i)/Math.log(2)))));for(var a=kl(t,e,n),s=Mu(a,o(e)),u=[],c=0;c<a.shape[0];c++)u.push(dl(s.slice([c,0],[1,e]),r));return Bn(u)}}),Dl=Object.freeze({hannWindow:Il,hammingWindow:Rl,frame:kl,stft:Sl});(_l=El=El||{})[_l.NONE=0]="NONE",_l[_l.MEAN=1]="MEAN",_l[_l.SUM=2]="SUM",_l[_l.SUM_BY_NONZERO_WEIGHTS=3]="SUM_BY_NONZERO_WEIGHTS";var Al=mn({absoluteDifference_:function(t,e,n,r){void 0===r&&(r=El.SUM_BY_NONZERO_WEIGHTS);var o=rn(t,"labels","absoluteDifference"),i=rn(e,"predictions","absoluteDifference"),a=null;null!=n&&(a=rn(n,"weights","absoluteDifference")),b(o.shape,i.shape,"Error in absoluteDifference: ");var s=o.sub(i).abs();return Tl(s,a,r)}}),Tl=mn({computeWeightedLoss_:function(t,e,n){void 0===n&&(n=El.SUM_BY_NONZERO_WEIGHTS);var r=rn(t,"losses","computeWeightedLoss"),o=null;null!=e&&(o=rn(e,"weights","computeWeightedLoss"));var i=null==o?r:r.mul(o);if(n===El.NONE)return i;if(n===El.SUM)return i.sum();if(n===El.MEAN){if(null==o)return i.mean();var a=r.size/o.size,s=i.sum().div(o.sum());return 1<a?s.div(Cn(a)):s}if(n!==El.SUM_BY_NONZERO_WEIGHTS)throw Error("Unknown reduction: "+n);if(null==o)return i.sum().div(Cn(r.size));var u=o.mul(An(r.shape)).notEqual(Cn(0)).sum().toFloat();return i.sum().div(u)}}),Fl=mn({cosineDistance_:function(t,e,n,r,o){void 0===o&&(o=El.SUM_BY_NONZERO_WEIGHTS);var i=rn(t,"labels","cosineDistance"),a=rn(e,"predictions","cosineDistance"),s=null;null!=r&&(s=rn(r,"weights","cosineDistance")),b(i.shape,a.shape,"Error in cosineDistance: ");var u=Cn(1).sub(i.mul(a).sum(n,!0));return Tl(u,s,o)}}),Nl=mn({hingeLoss_:function(t,e,n,r){void 0===r&&(r=El.SUM_BY_NONZERO_WEIGHTS);var o=rn(t,"labels","hingeLoss"),i=rn(e,"predictions","hingeLoss"),a=null;null!=n&&(a=rn(n,"weights","hingeLoss")),b(o.shape,i.shape,"Error in hingeLoss: ");var s=Cn(1);o=Cn(2).mul(o).sub(s);var u=s.sub(o.mul(i)).relu();return Tl(u,a,r)}}),Ml=mn({huberLoss_:function(t,e,n,r,o){void 0===r&&(r=1),void 0===o&&(o=El.SUM_BY_NONZERO_WEIGHTS);var i=rn(t,"labels","huberLoss"),a=rn(e,"predictions","huberLoss"),s=null;null!=n&&(s=rn(n,"weights","huberLoss")),b(i.shape,a.shape,"Error in huberLoss: ");var u=Cn(r),c=a.sub(i).abs(),l=Au(c,u),h=c.sub(l),f=Cn(.5).mul(l.square()).add(u.mul(h));return Tl(f,s,o)}}),Ol=mn({logLoss_:function(t,e,n,r,o){void 0===r&&(r=1e-7),void 0===o&&(o=El.SUM_BY_NONZERO_WEIGHTS);var i=rn(t,"labels","logLoss"),a=rn(e,"predictions","logLoss"),s=null;null!=n&&(s=rn(n,"weights","logLoss")),b(i.shape,a.shape,"Error in logLoss: ");var u=Cn(1),c=Cn(r),l=i.mul(a.add(c).log()).neg().sub(u.sub(i).mul(u.sub(a).add(c).log()));return Tl(l,s,o)}}),Pl=mn({meanSquaredError_:function(t,e,n,r){void 0===r&&(r=El.SUM_BY_NONZERO_WEIGHTS);var o=rn(t,"labels","meanSquaredError"),i=rn(e,"predictions","meanSquaredError"),a=null;null!=n&&(a=rn(n,"weights","meanSquaredError")),b(o.shape,i.shape,"Error in meanSquaredError: ");var s=o.squaredDifference(i);return Tl(s,a,r)}}),Bl=mn({sigmoidCrossEntropy_:function(t,e,n,r,o){void 0===r&&(r=0),void 0===o&&(o=El.SUM_BY_NONZERO_WEIGHTS);var s=rn(t,"multiClassLabels","sigmoidCrossEntropy"),i=rn(e,"logits","sigmoidCrossEntropy"),a=null;if(null!=n&&(a=rn(n,"weights","sigmoidCrossEntropy")),b(s.shape,i.shape,"Error in sigmoidCrossEntropy: "),0<r){var u=Cn(r),c=Cn(1),l=Cn(.5);s=s.mul(c.sub(u)).add(l.mul(u))}var h=function(t,e){var n=rn(s,"labels","sigmoidCrossEntropyWithLogits"),r=rn(e,"logits","sigmoidCrossEntropyWithLogits");b(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");var o=r.relu(),i=r.mul(n),a=r.abs().neg().exp().log1p();return o.sub(i).add(a)}(0,i);return Tl(h,a,o)}}),Ll=mn({softmaxCrossEntropy_:function(t,e,n,r,o){void 0===r&&(r=0),void 0===o&&(o=El.SUM_BY_NONZERO_WEIGHTS);var i=rn(t,"onehotLabels","softmaxCrossEntropy"),a=rn(e,"logits","softmaxCrossEntropy"),s=null;if(null!=n&&(s=rn(n,"weights","softmaxCrossEntropy")),b(i.shape,a.shape,"Error in softmaxCrossEntropy: "),0<r){var u=Cn(r),c=Cn(1),l=Cn(i.shape[1]);i=i.mul(c.sub(u)).add(u.div(l))}var h=function(t,e,i){if(void 0===i&&(i=-1),-1===i&&(i=e.rank-1),i!==e.rank-1)throw Error("Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank "+e.rank+" and dim was "+i);return Yr(function(t,e,n){var r=e.logSumExp([i],!0),o=e.toFloat().sub(r);return n([t,o]),{value:o.mul(t).neg().sum([i]),gradFunc:function(t,e){var n=e[0],r=e[1],o=cn(t.shape,[i]);return[t.reshape(o).mul(n.toFloat().sub(r.exp())),t.reshape(o).mul(r.exp().sub(n.toFloat()))]}}})(t,e)}(i,a);return Tl(h,s,o)}}),Wl=Object.freeze({get Reduction(){return El},absoluteDifference:Al,computeWeightedLoss:Tl,cosineDistance:Fl,hingeLoss:Nl,huberLoss:Ml,logLoss:Ol,meanSquaredError:Pl,sigmoidCrossEntropy:Bl,softmaxCrossEntropy:Ll});function zl(r,o){return void 0===o&&(o=!1),Vt.tidy(function(){if(2!==r.shape.length)throw new Error("qr2d() requires a 2D Tensor, but got a "+r.shape.length+"D Tensor.");for(var p=r.shape[0],d=r.shape[1],v=dr(p),m=r.clone(),g=_n([[1]],[1,1]),y=g.clone(),t=d<=p?d:p,e=function(f){var t,e=m,n=y,r=v;y=(t=Vt.tidy(function(){var t=m.slice([f,f],[p-f,1]),e=t.norm(),n=m.slice([f,f],[1,1]),r=_n([[-1]]).where(n.greater(0),_n([[1]])),o=n.sub(r.mul(e)),i=t.div(o);y=1===i.shape[0]?g.clone():g.concat(i.slice([1,0],[i.shape[0]-1,i.shape[1]]),0);var a=r.matMul(o).div(e).neg(),s=m.slice([f,0],[p-f,d]),u=a.mul(y);if(0===f)m=s.sub(u.matMul(y.transpose().matMul(s)));else{var c=s.sub(u.matMul(y.transpose().matMul(s)));m=m.slice([0,0],[f,d]).concat(c,0)}var l=v.slice([0,f],[p,v.shape[1]-f]);if(0===f)v=l.sub(l.matMul(y).matMul(u.transpose()));else{var h=l.sub(l.matMul(y).matMul(u.transpose()));v=v.slice([0,0],[p,f]).concat(h,1)}return[y,m,v]}))[0],m=t[1],v=t[2],Qe([e,n,r])},n=0;n<t;++n)e(n);return!o&&d<p&&(v=v.slice([0,0],[p,d]),m=m.slice([0,0],[d,d])),[v,m]})}var Ul=mn({bandPart_:function(t,e,n){if(e%1!=0)throw new Error("bandPart(): numLower must be an integer, got "+e+".");if(n%1!=0)throw new Error("bandPart(): numUpper must be an integer, got "+n+".");var r=rn(t,"a","bandPart");if(r.rank<2)throw new Error("bandPart(): Rank must be at least 2, got "+r.rank+".");var o=r.shape,i=r.shape.slice(-2),a=i[0],s=i[1];if(!(e<=a))throw new Error("bandPart(): numLower ("+e+") must not be greater than the number of rows ("+a+").");if(!(n<=s))throw new Error("bandPart(): numUpper ("+n+") must not be greater than the number of columns ("+s+").");e<0&&(e=a),n<0&&(n=s);var u=Mn(0,a,1,"int32").reshape([-1,1]),c=Mn(0,s,1,"int32"),l=zu(u,c),h=vu(l.lessEqual(Cn(+e,"int32")),l.greaterEqual(Cn(-n,"int32"))),f=Tn([a,s],r.dtype);return Dr(Fr(r.reshape([-1,a,s])).map(function(t){return xu(h,t,f)})).reshape(o)}}),Vl=mn({gramSchmidt_:function(e){var t;if(Array.isArray(e)){t=!1,P(null!=e&&0<e.length,function(){return"Gram-Schmidt process: input must not be null, undefined, or empty"});for(var n=e[0].shape[0],r=function(t){P(e[t].shape[0]===n,function(){return"Gram-Schmidt: Non-unique lengths found in the input vectors: ("+e[t].shape[0]+" vs. "+n+")"})},o=1;o<e.length;++o)r(o)}else t=!0,e=Vn(e,e.shape[0],0).map(function(t){return Sr(t,[0])});P(e.length<=e[0].shape[0],function(){return"Gram-Schmidt: Number of vectors ("+e.length+") exceeds number of dimensions ("+e[0].shape[0]+")."});function i(r){a.push(Vt.tidy(function(){var t=s[r];if(0<r)for(var e=0;e<r;++e){var n=$c(a[e].mulStrict(t)).mul(a[e]);t=t.sub(n)}return t.div(il(t,"euclidean"))}))}var a=[],s=e;for(o=0;o<e.length;++o)i(o);return t?Dr(a,0):a}}),Gl=mn({qr_:function(t,o){if(void 0===o&&(o=!1),t.rank<2)throw new Error("qr() requires input tensor to have a rank >= 2, but got rank "+t.rank);if(2===t.rank)return zl(t,o);var e=t.shape.slice(0,t.shape.length-2).reduce(function(t,e){return t*e}),n=Fr(t.reshape([e,t.shape[t.shape.length-2],t.shape[t.shape.length-1]]),0),i=[],a=[];return n.forEach(function(t){var e=zl(t,o),n=e[0],r=e[1];i.push(n),a.push(r)}),[Dr(i,0).reshape(t.shape),Dr(a,0).reshape(t.shape)]}}),Hl=Object.freeze({bandPart:Ul,gramSchmidt:Vl,qr:Gl});function ql(t,e,n,r,o){null==r&&(r=.5),null==o&&(o=Number.NEGATIVE_INFINITY);var i=t.shape[0];return n=Math.min(n,i),P(0<=r&&r<=1,function(){return"iouThreshold must be in [0, 1], but was '"+r+"'"}),P(2===t.rank,function(){return"boxes must be a 2D tensor, but was of rank '"+t.rank+"'"}),P(4===t.shape[1],function(){return"boxes must have 4 columns, but 2nd dimension was "+t.shape[1]}),P(1===e.rank,function(){return"scores must be a 1D tensor"}),P(e.shape[0]===i,function(){return"scores has incompatible shape with boxes. Expected "+i+", but was "+e.shape[0]}),{maxOutputSize:n,iouThreshold:r,scoreThreshold:o}}function jl(t,e){return!(0<t)||"linear"===e}function Kl(t,e,n){if(null==n||"linear"===n)return t;if("relu"===n)return t.mul(e.step());throw new Error("Gradient for activation "+n+" has not been implemented yet.")}function Xl(t,e){var n=e,r=ao(t.shape,e.shape);return 0<r.length&&(n=n.sum(r)),n.reshape(t.shape)}function $l(t,e,n){if("linear"===e)return t;if("relu"===e)return tl(t);if("elu"===e)return Jc(t);if("relu6"===e)return el(t);if("prelu"===e)return Zc(t,n);throw new Error("Unknown fused activation "+e+".")}var Yl=mn({resizeBilinear_:function(t,e,r){void 0===r&&(r=!1);var n=rn(t,"images","resizeBilinear");P(3===n.rank||4===n.rank,function(){return"Error in resizeBilinear: x must be rank 3 or 4, but got rank "+n.rank+"."}),P(2===e.length,function(){return"Error in resizeBilinear: new shape must 2D, but got shape "+e+"."});var o=n,i=!1;3===n.rank&&(i=!0,o=n.as4D(1,n.shape[0],n.shape[1],n.shape[2]));var a=e[0],s=e[1],u=Vt.runKernelFunc(function(t,e){return e([o]),t.resizeBilinear(o,a,s,r)},{x:o},function(e,n){return{x:function(){return Vt.runKernelFunc(function(t){return t.resizeBilinearBackprop(e,n[0],r)},{})}}},"ResizeBilinear",{alignCorners:r,newHeight:a,newWidth:s});return i?u.as3D(u.shape[1],u.shape[2],u.shape[3]):u}}),Jl=mn({resizeNearestNeighbor_:function(t,e,r){void 0===r&&(r=!1);var n=rn(t,"images","resizeNearestNeighbor");P(3===n.rank||4===n.rank,function(){return"Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank "+n.rank+"."}),P(2===e.length,function(){return"Error in resizeNearestNeighbor: new shape must 2D, but got shape "+e+"."}),P("float32"===n.dtype||"int32"===n.dtype,function(){return"`images` must have `int32` or `float32` as dtype"});var o=n,i=!1;3===n.rank&&(i=!0,o=n.as4D(1,n.shape[0],n.shape[1],n.shape[2]));var a=e[0],s=e[1],u=Vt.runKernelFunc(function(t,e){return e([o]),t.resizeNearestNeighbor(o,a,s,r)},{batchImages:o},function(e,n){return{batchImages:function(){return Vt.runKernelFunc(function(t){return t.resizeNearestNeighborBackprop(e,n[0],r)},{})}}});return i?u.as3D(u.shape[1],u.shape[2],u.shape[3]):u}}),Ql=mn({nonMaxSuppression_:function(t,e,n,r,o){void 0===r&&(r=.5),void 0===o&&(o=Number.NEGATIVE_INFINITY);var i=rn(t,"boxes","nonMaxSuppression"),a=rn(e,"scores","nonMaxSuppression"),s=ql(i,a,n,r,o);n=s.maxOutputSize,r=s.iouThreshold,o=s.scoreThreshold;var u={maxOutputSize:n,iouThreshold:r,scoreThreshold:o};return Vt.runKernelFunc(function(t){return t.nonMaxSuppression(i,a,n,r,o)},{boxes:i,scores:a},null,"NonMaxSuppressionV3",u)}}),Zl=mn({cropAndResize_:function(t,e,n,r,o,i){var a=rn(t,"image","cropAndResize"),s=rn(e,"boxes","cropAndResize","float32"),u=rn(n,"boxInd","cropAndResize","int32");o=o||"bilinear",i=i||0;var c=s.shape[0];return P(4===a.rank,function(){return"Error in cropAndResize: image must be rank 4,but got rank "+a.rank+"."}),P(2===s.rank&&4===s.shape[1],function(){return"Error in cropAndResize: boxes must be have size ["+c+",4] but had shape "+s.shape+"."}),P(1===u.rank&&u.shape[0]===c,function(){return"Error in cropAndResize: boxInd must be have size ["+c+"] but had shape "+s.shape+"."}),P(2===r.length,function(){return"Error in cropAndResize: cropSize must be of length 2, but got length "+r.length+"."}),P(1<=r[0]&&1<=r[1],function(){return"cropSize must be atleast [1,1], but was "+r}),P("bilinear"===o||"nearest"===o,function(){return"method must be bilinear or nearest, but was "+o}),Vt.runKernelFunc(function(t,e){return t.cropAndResize(a,s,u,r,o,i)},{images:a,boxes:s,boxInd:u},null,"CropAndResize",{method:o,extrapolationValue:i,cropSize:r})}}),th=Object.freeze({resizeBilinear:Yl,resizeNearestNeighbor:Jl,nonMaxSuppression:Ql,nonMaxSuppressionAsync:function(u,c,l,h,f){return void 0===h&&(h=.5),void 0===f&&(f=Number.NEGATIVE_INFINITY),y(this,void 0,void 0,function(){var e,n,r,o,i,a,s;return R(this,function(t){switch(t.label){case 0:return e=rn(u,"boxes","nonMaxSuppressionAsync"),n=rn(c,"scores","nonMaxSuppressionAsync"),r=ql(e,n,l,h,f),l=r.maxOutputSize,h=r.iouThreshold,f=r.scoreThreshold,[4,Promise.all([e.data(),n.data()])];case 1:return o=t.sent(),i=o[0],a=o[1],s=ko(i,a,l,h,f),e!==u&&e.dispose(),n!==c&&n.dispose(),[2,s]}})})},cropAndResize:Zl}),eh=mn({fusedMatMul_:function(t){var e,n=t.a,r=t.b,o=t.transposeA,s=void 0!==o&&o,i=t.transposeB,u=void 0!==i&&i,c=t.bias,a=t.activation,l=void 0===a?"linear":a,h=t.preluActivationWeights;if(!1===jl(Vt.state.gradientDepth,l)){var f=xc(n,r,s,u);return null!=c&&(f=bu(f,c)),$l(f,l,h)}var p=rn(n,"a","fused matMul"),d=rn(r,"b","fused matMul");e=Nt(p,d),p=e[0],d=e[1];var v=s?p.shape[p.rank-2]:p.shape[p.rank-1],m=u?d.shape[d.rank-1]:d.shape[d.rank-2],g=s?p.shape[p.rank-1]:p.shape[p.rank-2],y=u?d.shape[d.rank-2]:d.shape[d.rank-1],x=p.shape.slice(0,-2),b=d.shape.slice(0,-2),w=L(x),C=L(b);P(2<=p.rank&&2<=d.rank&&p.rank===d.rank,function(){return"Error in fused matMul: inputs must have the same rank of at least 2, got ranks "+p.rank+" and "+d.rank+"."}),P(D(x,b),function(){return"Error in fused matMul: outer dimensions ("+x+") and ("+b+") of Tensors with shapes "+p.shape+" and "+d.shape+" must match."}),P(v===m,function(){return"Error in fused matMul: inner shapes ("+v+") and ("+m+") of Tensors with shapes "+p.shape+" and "+d.shape+" and transposeA="+s+" and transposeB="+u+" must match."});var E,_,I=p.shape.slice(0,-2).concat([g,y]),R=s?p.as3D(w,v,g):p.as3D(w,g,v),k=u?d.as3D(C,y,m):d.as3D(C,m,y);null!=c&&so(I,(E=Nt(E=rn(c,"bias","fused matMul"),p)[0]).shape),null!=h&&(_=rn(h,"prelu weights","fused matMul"));var S={$a:R,$b:k};return null!=c&&(S.$bias=E),null!=h&&(S.$preluActivationWeights=_),Vt.runKernelFunc(function(t,e){var n=t.fusedBatchMatMul({a:R,b:k,transposeA:s,transposeB:u,bias:E,activation:l,preluActivationWeights:_});return e([R,k,n]),n},S,function(t,e){var n=e[0],r=e[1],o=e[2],i=Kl(t,o,l),a={};return null!=c&&(a={$bias:function(){return Xl(E,i)}}),s||u?!s&&u?Object.assign({$a:function(){return i.matMul(r,!1,!1)},$b:function(){return i.matMul(n,!0,!1)}},a):s&&!u?Object.assign({$a:function(){return r.matMul(i,!1,!0)},$b:function(){return n.matMul(i,!1,!1)}},a):Object.assign({$a:function(){return r.matMul(i,!0,!0)},$b:function(){return i.matMul(n,!0,!0)}},a):Object.assign({$a:function(){return i.matMul(r,!1,!0)},$b:function(){return n.matMul(i,!0,!1)}},a)}).reshape(I)}}),nh=mn({fusedConv2d_:function(t){var e=t.x,n=t.filter,u=t.strides,c=t.pad,r=t.dataFormat,o=void 0===r?"NHWC":r,i=t.dilations,l=void 0===i?[1,1]:i,a=t.dimRoundingMode,h=t.bias,s=t.activation,f=void 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Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. 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o=n?t.shape[1]:t.shape[2],i=n?t.shape[2]:t.shape[1],a=r?e.shape[1]:e.shape[2],s=t.shape[0],u=this.readSync(t.dataId),c=this.readSync(e.dataId),l=n?[t.strides[0],1,t.strides[1]]:[t.strides[0],t.strides[1],1],h=l[0],f=l[1],p=l[2],d=r?[1,e.strides[1],e.strides[0]]:[e.strides[1],1,e.strides[0]],v=d[0],m=d[1],g=d[2],y=i*a,x=or([s,i,a],t.dtype),b=x.values,w=this.blockSize,C=0;C<s;C++)for(var E=0;E<i;E+=w)for(var _=0;_<a;_+=w)for(var I=0;I<o;I+=w)for(var R=Math.min(E+w,i),k=Math.min(_+w,a),S=Math.min(I+w,o),D=E;D<R;D++)for(var A=_;A<k;A++){for(var T=0,F=I;F<S;F++)T+=u[C*h+D*f+F*p]*c[F*v+A*m+C*g];b[C*y+(D*a+A)]+=T}return x.toTensor()},lh.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,i=t.bias,a=t.activation,s=t.preluActivationWeights,u=this.batchMatMul(e,n,r,o);return i&&(u=this.add(u,i)),a&&(u=sh(this,u,a,s)),u},lh.prototype.multiply=function(t,e){return"complex64"===t.dtype||"complex64"===e.dtype?this.broadcastedBinaryComplexOp(t.cast("complex64"),e.cast("complex64"),function(t,e,n,r){return{real:t*n-e*r,imag:t*r+e*n}}):this.broadcastedBinaryOp(t,e,Tt(t.dtype,e.dtype),function(t,e){return t*e})},lh.prototype.realDivide=function(t,e){return ah([t,e],"realDivide"),this.broadcastedBinaryOp(t,e,"float32",function(t,e){return t/e})},lh.prototype.floorDiv=function(t,e){return ah([t,e],"floorDiv"),this.broadcastedBinaryOp(t,e,"int32",function(t,e){return Math.floor(t/e)})},lh.prototype.sum=function(t,e){ah(t,"sum"),ln("sum",e,t.rank);for(var n=un(t.shape,e),r=n[0],o=n[1],i=Tn(r,Tt(t.dtype,"int32")),a=L(o),s=this.readSync(i.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*a,h=0,f=0;f<a;++f)h+=u[l+f];s[c]=h}return i},lh.prototype.prod=function(t,e){ah(t,"sum");for(var n=un(t.shape,e),r=n[0],o=n[1],i=Tn(r,Tt(t.dtype,"int32")),a=L(o),s=this.readSync(i.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*a,h=1,f=0;f<a;++f)h*=u[l+f];s[c]=h}return i},lh.prototype.unsortedSegmentSum=function(t,e,n){ah(t,"unsortedSegmentSum");for(var r=[],o=t.rank-e.rank,i=0;i<o;++i)e=e.expandDims(i+1);for(i=0;i<n;++i){var a=Cn(i,"int32"),s=Vu(a,e).asType("float32").mul(t).sum(0);r.push(s)}return Dr(r)},lh.prototype.argMin=function(t,e){ah(t,"argMin");var n=[e];ln("argMin",n,t.rank);for(var r=un(t.shape,n),o=r[0],i=r[1],a=Tn(o,"int32"),s=L(i),u=this.readSync(a.dataId),c=this.readSync(t.dataId),l=0;l<u.length;++l){for(var h=l*s,f=c[h],p=0,d=0;d<s;++d){var v=c[h+d];v<f&&(f=v,p=d)}u[l]=p}return a},lh.prototype.argMax=function(t,e){ah(t,"argMax");var n=[e];ln("argMax",n,t.rank);for(var r=un(t.shape,n),o=r[0],i=r[1],a=Tn(o,"int32"),s=L(i),u=this.readSync(a.dataId),c=this.readSync(t.dataId),l=0;l<u.length;++l){for(var h=l*s,f=c[h],p=0,d=0;d<s;++d){var v=c[h+d];f<v&&(f=v,p=d)}u[l]=p}return a},lh.prototype.cumsum=function(t,e,n,r){if(ah(t,"cumsum"),e!==t.rank-1)throw new Error("backend.cumsum in CPU expects an inner-most axis="+(t.rank-1)+" but got axis="+e);for(var o=Tt(t.dtype,"int32"),i=Tn(t.shape,o),a=this.readSync(i.dataId),s=this.readSync(t.dataId),u=t.shape[t.rank-1],c=r?function(t,e){return t+u-e-1}:function(t,e){return t+e},l=0;l<s.length;l+=u)for(var h=0;h<u;h++){var f=c(l,h);if(0===h)a[f]=n?0:s[f];else{var p=c(l,h-1);a[f]=n?s[p]+a[p]:s[f]+a[p]}}return i},lh.prototype.equal=function(t,e){return ah([t,e],"equal"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t===e?1:0})},lh.prototype.notEqual=function(t,e){return ah([t,e],"notEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t!==e?1:0})},lh.prototype.less=function(t,e){return ah([t,e],"less"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t<e?1:0})},lh.prototype.lessEqual=function(t,e){return ah([t,e],"lessEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t<=e?1:0})},lh.prototype.greater=function(t,e){return ah([t,e],"greater"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return e<t?1:0})},lh.prototype.greaterEqual=function(t,e){return ah([t,e],"greaterEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return e<=t?1:0})},lh.prototype.logicalNot=function(t){ah(t,"logicalNot");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)n[r]=e[r]?0:1;return this.makeOutput(n,t.shape,"bool")},lh.prototype.logicalAnd=function(t,e){return ah([t,e],"logicalAnd"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t&&e})},lh.prototype.logicalOr=function(t,e){return ah([t,e],"logicalOr"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t||e})},lh.prototype.select=function(t,e,n){ah([t,e,n],"select");for(var r=this.readSync(t.dataId),o=this.readSync(e.dataId),i=this.readSync(n.dataId),a=Tn(e.shape,Tt(e.dtype,n.dtype)),s=this.readSync(a.dataId),u=0,c=0===t.rank||1<t.rank||1===e.rank?1:L(e.shape.slice(1)),l=0;l<r.length;l++)for(var h=0;h<c;h++)1===r[l]?s[u++]=o[l]:s[u++]=i[l];return a},lh.prototype.where=function(t){ah([t],"where");var e=this.readSync(t.dataId);return Fo(t.shape,e)},lh.prototype.topk=function(t,e,n){return ah(t,"topk"),To(this.readSync(t.dataId),t.shape,t.dtype,e)},lh.prototype.min=function(t,e){ah(t,"min"),ln("min",e,t.rank);for(var n=un(t.shape,e),r=n[0],o=n[1],i=Tn(r,t.dtype),a=L(o),s=this.readSync(i.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*a,h=u[l],f=0;f<a;++f){var p=u[l+f];p<h&&(h=p)}s[c]=h}return i},lh.prototype.minimum=function(t,e){return ah([t,e],"minimum"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.min(t,e)})},lh.prototype.mod=function(t,e){return ah([t,e],"mod"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var n=t%e;return t<0&&e<0||0<=t&&0<=e?n:(n+e)%e})},lh.prototype.max=function(t,e){ah(t,"max"),ln("max",e,t.rank);for(var n=un(t.shape,e),r=n[0],o=n[1],i=Tn(r,t.dtype),a=L(o),s=this.readSync(i.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*a,h=u[l],f=0;f<a;++f){var p=u[l+f];h<p&&(h=p)}s[c]=h}return i},lh.prototype.maximum=function(t,e){return ah([t,e],"maximum"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.max(t,e)})},lh.prototype.all=function(t,e){ah(t,"all"),ln("all",e,t.rank);for(var n=un(t.shape,e),r=n[0],o=n[1],i=Tn(r,t.dtype),a=L(o),s=this.readSync(i.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*a,h=u[l],f=0;f<a;++f){var p=u[l+f];h=h&&p}s[c]=h}return i},lh.prototype.any=function(t,e){ah(t,"any"),ln("any",e,t.rank);for(var n=un(t.shape,e),r=n[0],o=n[1],i=Tn(r,t.dtype),a=L(o),s=this.readSync(i.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*a,h=u[l],f=0;f<a;++f){var p=u[l+f];h=h||p}s[c]=h}return i},lh.prototype.squaredDifference=function(t,e){return ah([t,e],"squaredDifference"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var n=t-e;return n*n})},lh.prototype.ceil=function(t){ah(t,"ceil");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.ceil(e[r]);return this.makeOutput(n,t.shape,"float32")},lh.prototype.floor=function(t){ah(t,"floor");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.floor(e[r]);return this.makeOutput(n,t.shape,"float32")},lh.prototype.sign=function(t){ah(t,"x");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)e[r]<0?n[r]=-1:0<e[r]?n[r]=1:n[r]=0;return this.makeOutput(n,t.shape,"float32")},lh.prototype.isNaN=function(t){ah(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isNaN(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},lh.prototype.isInf=function(t){ah(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Math.abs(e[r])===1/0&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},lh.prototype.isFinite=function(t){ah(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isFinite(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},lh.prototype.round=function(t){ah(t,"round");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=Math.floor(e[r]);e[r]-o<.5?n[r]=Math.floor(e[r]):.5<e[r]-o?n[r]=Math.ceil(e[r]):n[r]=o%2==0?o:o+1}return this.makeOutput(n,t.shape,"float32")},lh.prototype.exp=function(t){ah(t,"exp");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.exp(e[r]);return this.makeOutput(n,t.shape,"float32")},lh.prototype.expm1=function(t){ah(t,"expm1");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.expm1(e[r]);return this.makeOutput(n,t.shape,"float32")},lh.prototype.log=function(t){ah(t,"log");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log(o)}return this.makeOutput(n,t.shape,"float32")},lh.prototype.log1p=function(t){ah(t,"log1p");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.log1p(o)}return this.makeOutput(n,t.shape,"float32")},lh.prototype.sqrt=function(t){ah(t,"sqrt");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=Math.sqrt(o)}return this.makeOutput(n,t.shape,"float32")},lh.prototype.rsqrt=function(t){ah(t,"rsqrt");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=e[r];n[r]=1/Math.sqrt(o)}return this.makeOutput(n,t.shape,"float32")},lh.prototype.reciprocal=function(t){ah(t,"reciprocal");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=1/e[r];return this.makeOutput(n,t.shape,"float32")},lh.prototype.linear=function(t){return t},lh.prototype.relu=function(t){ah(t,"relu");for(var e=Tn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.max(0,r[o]);return e},lh.prototype.relu6=function(t){ah(t,"relu");for(var e=Tn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),o=0;o<r.length;++o)n[o]=Math.min(Math.max(0,r[o]),6);return e},lh.prototype.prelu=function(t,e){return ah([t,e],"prelu"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return t<0?e*t:t})},lh.prototype.elu=function(t){ah(t,"elu");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=n[r];e[r]=0<=o?o:Math.exp(o)-1}return this.makeOutput(e,t.shape,"float32")},lh.prototype.eluDer=function(t,e){ah([t,e],"eluDer");for(var n=new Float32Array(e.size),r=this.readSync(e.dataId),o=this.readSync(t.dataId),i=0;i<r.length;++i){var a=r[i];n[i]=1<=a?o[i]:o[i]*(a+1)}return this.makeOutput(n,e.shape,"float32")},lh.prototype.selu=function(t){ah(t,"selu");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=n[r];e[r]=0<=o?1.0507009873554805*o:1.7580993408473768*(Math.exp(o)-1)}return this.makeOutput(e,t.shape,"float32")},lh.prototype.clip=function(t,e,n){ah(t,"clip");for(var r=new Float32Array(t.size),o=this.readSync(t.dataId),i=0;i<o.length;++i){var a=o[i];r[i]=n<a?n:a<e?e:a}return this.makeOutput(r,t.shape,"float32")},lh.prototype.abs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.abs(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.complexAbs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<t.size;++r){var o=n[2*r],i=n[2*r+1];e[r]=Math.hypot(o,i)}return this.makeOutput(e,t.shape,"float32")},lh.prototype.int=function(t){ah(t,"int");for(var e=new Int32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=n[r];return this.makeOutput(e,t.shape,"int32")},lh.prototype.sigmoid=function(t){ah(t,"sigmoid");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=1/(1+Math.exp(-n[r]));return this.makeOutput(e,t.shape,"float32")},lh.prototype.softplus=function(t){ah(t,"softplus");for(var e=Math.log(1.1920928955078125e-7)+2,n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var i,a=r[o]>-e,s=r[o]<e,u=Math.exp(r[o]);i=s?u:a?r[o]:Math.log(1+u),n[o]=i}return this.makeOutput(n,t.shape,"float32")},lh.prototype.sin=function(t){ah(t,"sin");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sin(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.cos=function(t){ah(t,"cos");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cos(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.tan=function(t){ah(t,"tan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.tan(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.asin=function(t){ah(t,"asin");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asin(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.acos=function(t){ah(t,"acos");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acos(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.atan=function(t){ah(t,"atan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atan(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.atan2=function(t,e){return ah([t,e],"atan2"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.atan2(t,e)})},lh.prototype.sinh=function(t){ah(t,"sinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sinh(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.cosh=function(t){ah(t,"cosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cosh(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.tanh=function(t){ah(t,"tanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=v(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.asinh=function(t){ah(t,"asinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asinh(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.acosh=function(t){ah(t,"acosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acosh(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.atanh=function(t){ah(t,"atanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atanh(n[r]);return this.makeOutput(e,t.shape,"float32")},lh.prototype.erf=function(t){ah(t,"erf");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=Math.sign(n[r]),i=Math.abs(n[r]),a=1/(1+.3275911*i);e[r]=o*(1-((((1.061405429*a-1.453152027)*a+1.421413741)*a-.284496736)*a+.254829592)*a*Math.exp(-i*i))}return this.makeOutput(e,t.shape,"float32")},lh.prototype.step=function(t,e){void 0===e&&(e=0),ah(t,"step");for(var n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var i=r[o];isNaN(i)?n[o]=NaN:n[o]=0<i?1:e}return this.makeOutput(n,t.shape,"float32")},lh.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,i=t.activation,a=t.preluActivationWeights,s=this.conv2d(e,n,r);return o&&(s=this.add(s,o)),i&&(s=sh(this,s,i,a)),s},lh.prototype.conv2d=function(t,e,n){ah([t,e],"conv2d");for(var r=n.filterHeight,o=n.filterWidth,i=n.dilationHeight,a=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,c="channelsLast"===n.dataFormat,l=or(n.outShape,t.dtype),h=t.strides[0],f=c?t.strides[1]:t.strides[2],p=c?t.strides[2]:1,d=c?1:t.strides[1],v=l.strides[0],m=c?l.strides[1]:l.strides[2],g=c?l.strides[2]:1,y=c?1:l.strides[1],x=this.readSync(t.dataId),b=this.readSync(e.dataId),w=l.values,C=0;C<n.batchSize;++C)for(var E=C*h,_=C*v,I=0;I<n.outHeight;++I)for(var R=_+I*m,k=I*n.strideHeight-u,S=0;S<r;S++){var D=k+S*i;if(!(D<0||D>=n.inHeight))for(var A=S*e.strides[0],T=E+D*f,F=0;F<n.outWidth;++F)for(var N=R+F*g,M=F*n.strideWidth-s,O=0;O<o;O++){var P=M+O*a;if(!(P<0||P>=n.inWidth))for(var B=T+P*p,L=A+O*e.strides[1],W=0;W<n.inChannels;++W){for(var z=x[B+W*d],U=0;U<n.outChannels;++U)w[N+U*y]+=z*b[L+U];L+=n.outChannels}}}return l.toTensor()},lh.prototype.conv3d=function(t,e,n){for(var r=n.filterDepth,o=n.filterHeight,i=n.filterWidth,a=n.dilationDepth,s=n.dilationHeight,u=n.dilationWidth,c=n.padInfo.front,l=n.padInfo.left,h=n.padInfo.top,f=or(n.outShape,t.dtype),p=this.readSync(t.dataId),d=this.readSync(e.dataId),v=f.values,m=0;m<n.batchSize;++m)for(var g=m*t.strides[0],y=m*f.strides[0],x=0;x<n.outDepth;++x)for(var b=y+x*f.strides[1],w=x*n.strideDepth-c,C=0;C<r;C++){var E=w+C*a;if(!(E<0||E>=n.inDepth))for(var _=C*e.strides[0],I=g+E*t.strides[1],R=0;R<n.outHeight;++R)for(var k=b+R*f.strides[2],S=R*n.strideHeight-h,D=0;D<o;D++){var A=S+D*s;if(!(A<0||A>=n.inHeight))for(var T=_+D*e.strides[1],F=I+A*t.strides[2],N=0;N<n.outWidth;++N)for(var M=k+N*n.outChannels,O=N*n.strideWidth-l,P=0;P<i;P++){var B=O+P*u;if(!(B<0||B>=n.inWidth))for(var L=T+P*e.strides[2],W=F+B*n.inChannels,z=L,U=0;U<n.inChannels;++U){for(var V=p[W+U],G=0;G<n.outChannels;++G)v[M+G]+=V*d[z+G];z+=n.outChannels}}}}return f.toTensor()},lh.prototype.conv2dDerInput=function(t,e,n){ah([t,e],"conv2dDerInput");for(var r=or(n.inShape,"float32"),o=r.values,i=this.readSync(t.dataId),a=this.readSync(e.dataId),s=e.strides,u=s[0],c=s[1],l=s[2],h=n.batchSize,f=n.filterHeight,p=n.filterWidth,d=n.inChannels,v=n.inHeight,m=n.inWidth,g=n.outChannels,y=n.outHeight,x=n.outWidth,b=n.strideHeight,w=n.strideWidth,C=n.dataFormat,E=f-1-n.padInfo.top,_=p-1-n.padInfo.left,I="channelsLast"===C,R=r.strides[0],k=I?r.strides[1]:r.strides[2],S=I?r.strides[2]:1,D=I?1:r.strides[1],A=t.strides[0],T=I?t.strides[1]:t.strides[2],F=I?t.strides[2]:1,N=I?1:t.strides[1],M=0;M<h;++M)for(var O=0;O<d;++O)for(var P=0;P<v;++P)for(var B=P-E,L=Math.max(0,Math.ceil(B/b)),W=Math.min(y,(f+B)/b),z=0;z<m;++z){for(var U=z-_,V=Math.max(0,Math.ceil(U/w)),G=Math.min(x,(p+U)/w),H=0,q=L;q<W;++q)for(var j=q*b-B,K=V;K<G;++K)for(var X=A*M+T*q+F*K,$=u*(f-1-j)+c*(p-1-(K*w-U))+l*O,Y=0;Y<g;++Y)H+=i[X+N*Y]*a[$+Y];o[R*M+k*P+S*z+D*O]=H}return r.toTensor()},lh.prototype.conv3dDerInput=function(t,e,n){for(var r=or(n.inShape,"float32"),o=r.values,i=r.strides,a=i[0],s=i[1],u=i[2],c=i[3],l=this.readSync(t.dataId),h=t.strides,f=h[0],p=h[1],d=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=n.batchSize,E=n.filterDepth,_=n.filterHeight,I=n.filterWidth,R=n.inChannels,k=n.inDepth,S=n.inHeight,D=n.inWidth,A=n.outChannels,T=n.outDepth,F=n.outHeight,N=n.outWidth,M=n.strideDepth,O=n.strideHeight,P=n.strideWidth,B=E-1-n.padInfo.front,L=_-1-n.padInfo.top,W=I-1-n.padInfo.left,z=0;z<C;++z)for(var U=0;U<R;++U)for(var V=0;V<k;++V)for(var G=V-B,H=Math.max(0,Math.ceil(G/M)),q=Math.min(T,(E+G)/M),j=0;j<S;++j)for(var K=j-L,X=Math.max(0,Math.ceil(K/O)),$=Math.min(F,(_+K)/O),Y=0;Y<D;++Y){for(var J=Y-W,Q=Math.max(0,Math.ceil(J/P)),Z=Math.min(N,(I+J)/P),tt=0,et=H;et<q;++et)for(var nt=et*M-G,rt=X;rt<$;++rt)for(var ot=rt*O-K,it=Q;it<Z;++it)for(var at=f*z+p*et+d*rt+v*it,st=y*(E-1-nt)+x*(_-1-ot)+b*(I-1-(it*P-J))+w*U,ut=0;ut<A;++ut)tt+=l[at+ut]*m[st+ut];o[a*z+s*V+u*j+c*Y+U]=tt}return r.toTensor()},lh.prototype.conv2dDerFilter=function(t,e,n){ah([t,e],"conv2dDerFilter");for(var r=n.strideHeight,o=n.strideWidth,i=n.filterHeight,a=n.filterWidth,s="channelsLast"===n.dataFormat,u=or(n.filterShape,"float32"),c=n.padInfo.left,l=n.padInfo.top,h=this.bufferSync(t),f=this.bufferSync(e),p=0;p<i;++p)for(var d=Math.max(0,Math.ceil((l-p)/r)),v=Math.min(n.outHeight,(n.inHeight+l-p)/r),m=0;m<a;++m)for(var g=Math.max(0,Math.ceil((c-m)/o)),y=Math.min(n.outWidth,(n.inWidth+c-m)/o),x=0;x<n.inChannels;++x)for(var b=0;b<n.outChannels;++b){for(var w=0,C=0;C<n.batchSize;++C)for(var E=d;E<v;++E)for(var _=p+E*r-l,I=g;I<y;++I){var R=m+I*o-c;w+=s?h.get(C,_,R,x)*f.get(C,E,I,b):h.get(C,x,_,R)*f.get(C,b,E,I)}u.set(w,p,m,x,b)}return u.toTensor()},lh.prototype.conv3dDerFilter=function(t,e,n){for(var r=n.strideDepth,o=n.strideHeight,i=n.strideWidth,a=n.filterDepth,s=n.filterHeight,u=n.filterWidth,c=or(n.filterShape,"float32"),l=c.values,h=c.strides,f=h[0],p=h[1],d=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=this.readSync(t.dataId),E=t.strides,_=E[0],I=E[1],R=E[2],k=E[3],S=n.padInfo.front,D=n.padInfo.left,A=n.padInfo.top,T=0;T<a;++T)for(var F=Math.max(0,Math.ceil((S-T)/r)),N=Math.min(n.outDepth,(n.inDepth+S-T)/r),M=T*f,O=0;O<s;++O)for(var P=Math.max(0,Math.ceil((A-O)/o)),B=Math.min(n.outHeight,(n.inHeight+A-O)/o),L=O*p+M,W=0;W<u;++W)for(var z=Math.max(0,Math.ceil((D-W)/i)),U=Math.min(n.outWidth,(n.inWidth+D-W)/i),V=W*d+L,G=0;G<n.inChannels;++G)for(var H=G*v+V,q=0;q<n.outChannels;++q){for(var j=0,K=0;K<n.batchSize;++K)for(var X=K*_,$=K*y,Y=F;Y<N;++Y)for(var J=(T+Y*r-S)*I+X,Q=Y*x+$,Z=P;Z<B;++Z)for(var tt=(O+Z*o-A)*R+J,et=Z*b+Q,nt=z;nt<U;++nt){var rt=nt*w+et;j+=C[(W+nt*i-D)*k+tt+G]*m[rt+q]}l[H+q]=j}return c.toTensor()},lh.prototype.fusedDepthwiseConv2D=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,i=t.activation,a=t.preluActivationWeights,s=this.depthwiseConv2D(e,n,r);return o&&(s=this.add(s,o)),i&&(s=sh(this,s,i,a)),s},lh.prototype.depthwiseConv2D=function(t,e,n){ah([t,e],"depthwiseConv2D");for(var r=n.filterHeight,o=n.filterWidth,i=n.dilationHeight,a=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,c=n.outChannels/n.inChannels,l=or(n.outShape,t.dtype),h=this.readSync(t.dataId),f=this.readSync(e.dataId),p=l.values,d=0;d<n.batchSize;++d)for(var v=d*t.strides[0],m=d*l.strides[0],g=0;g<n.outHeight;++g)for(var y=m+g*l.strides[1],x=g*n.strideHeight-s,b=0;b<r;++b){var w=x+b*i;if(!(w<0||w>=n.inHeight))for(var C=b*e.strides[0],E=v+w*t.strides[1],_=0;_<n.outWidth;++_)for(var I=y+_*l.strides[2],R=_*n.strideWidth-u,k=0;k<o;++k){var S=R+k*a;if(!(S<0||S>=n.inWidth))for(var D=C+k*e.strides[1],A=E+S*n.inChannels,T=I,F=D,N=0;N<n.inChannels;++N){for(var M=h[A+N],O=0;O<c;++O)p[T+O]+=M*f[F+O];T+=c,F+=c}}}return l.toTensor()},lh.prototype.depthwiseConv2DDerInput=function(t,e,n){ah([t,e],"depthwiseConv2DDerInput");for(var r=or(n.inShape,"float32"),o=r.values,i=r.strides,a=i[0],s=i[1],u=i[2],c=this.readSync(t.dataId),l=t.strides,h=l[0],f=l[1],p=l[2],d=this.readSync(e.dataId),v=e.strides,m=v[0],g=v[1],y=v[2],x=n.batchSize,b=n.filterHeight,w=n.filterWidth,C=n.inChannels,E=n.inHeight,_=n.inWidth,I=n.outChannels,R=n.outHeight,k=n.outWidth,S=n.strideHeight,D=n.strideWidth,A=b-1-n.padInfo.top,T=w-1-n.padInfo.left,F=I/C,N=0;N<x;++N)for(var M=0;M<C;++M)for(var O=0;O<E;++O)for(var P=O-A,B=Math.max(0,Math.ceil(P/S)),L=Math.min(R,(b+P)/S),W=0;W<_;++W){for(var z=W-T,U=Math.max(0,Math.ceil(z/D)),V=Math.min(k,(w+z)/D),G=0,H=B;H<L;++H)for(var q=H*S-P,j=U;j<V;++j)for(var K=h*N+f*H+p*j,X=m*(b-1-q)+g*(w-1-(j*D-z))+y*M,$=0;$<F;++$)G+=c[K+(M*F+$)]*d[X+$];o[a*N+s*O+u*W+M]=G}return r.toTensor()},lh.prototype.depthwiseConv2DDerFilter=function(t,e,n){ah([t,e],"depthwiseConv2DDerFilter");for(var r=n.strideHeight,o=n.strideWidth,i=n.filterHeight,a=n.filterWidth,s=or(n.filterShape,"float32"),u=n.padInfo.left,c=n.padInfo.top,l=n.outChannels/n.inChannels,h=this.bufferSync(t),f=this.bufferSync(e),p=0;p<i;++p)for(var d=Math.max(0,Math.ceil((c-p)/r)),v=Math.min(n.outHeight,(n.inHeight+c-p)/r),m=0;m<a;++m)for(var g=Math.max(0,Math.ceil((u-m)/o)),y=Math.min(n.outWidth,(n.inWidth+u-m)/o),x=0;x<n.outChannels;++x){for(var b=Math.trunc(x/l),w=x%l,C=0,E=0;E<n.batchSize;++E)for(var _=d;_<v;++_)for(var I=p+_*r-c,R=g;R<y;++R){var k=m+R*o-u;C+=h.get(E,I,k,b)*f.get(E,_,R,x)}s.set(C,p,m,b,w)}return s.toTensor()},lh.prototype.tile=function(t,e){return ah(t,"tile"),Ao(this.bufferSync(t),e)},lh.prototype.pad=function(n,t,e){ah(n,"pad");var r=t.map(function(t,e){return t[0]+n.shape[e]+t[1]}),o=t.map(function(t){return t[0]}),i=this.bufferSync(n),a=or(r,n.dtype);0!==e&&a.values.fill(e);for(var s=0;s<n.size;s++){var u=i.indexToLoc(s),c=u.map(function(t,e){return t+o[e]});a.set.apply(a,[i.get.apply(i,u)].concat(c))}return a.toTensor()},lh.prototype.transpose=function(t,e){ah(t,"transpose");for(var n=new Array(t.rank),r=0;r<n.length;r++)n[r]=t.shape[e[r]];var o=this.readSync(t.dataId),i=or(n,t.dtype),a=this.bufferSync(t);for(r=0;r<t.size;++r){for(var s=a.indexToLoc(r),u=new Array(s.length),c=0;c<u.length;c++)u[c]=s[e[c]];var l=i.locToIndex(u);i.values[l]=o[r]}return i.toTensor()},lh.prototype.gather=function(t,e,n){ah([t,e],"gather");var r=t.shape.slice(),o=this.readSync(e.dataId);r[n]=o.length;for(var i=or(r,t.dtype),a=this.bufferSync(t),s=0;s<i.size;++s){var u=i.indexToLoc(s),c=u.slice();c[n]=o[u[n]];var l=a.locToIndex(c);i.values[s]=a.values[l]}return i.toTensor()},lh.prototype.batchToSpaceND=function(t,e,n){ah([t],"batchToSpaceND");var r=e.reduce(function(t,e){return t*e}),o=Nr(t.shape,e,r),i=Mr(o.length,e.length),a=Or(t.shape,e,r),s=Pr(n,e.length),u=Br(a,n,e.length);return t.reshape(o).transpose(i).reshape(a).slice(s,u)},lh.prototype.spaceToBatchND=function(t,e,n){ah([t],"spaceToBatchND");var r=e.reduce(function(t,e){return t*e}),o=[[0,0]];o.push.apply(o,n);for(var i=1+e.length;i<t.shape.length;++i)o.push([0,0]);var a=t.pad(o),s=Nr(a.shape,e,r,!1),u=Mr(s.length,e.length,!1),c=Or(a.shape,e,r,!1);return a.reshape(s).transpose(u).reshape(c)},lh.prototype.pool=function(t,e,n){ah(t,"pool");for(var r=e.strideHeight,o=e.strideWidth,i=e.dilationHeight,a=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=this.readSync(t.dataId),p=or(e.outShape,t.dtype),d=p.values,v=e.outShape[1]*e.outShape[2]*e.outShape[3],m=e.outShape[2]*e.outShape[3],g=e.outShape[3],y=0;y<e.batchSize;++y)for(var x=y*v,b=y*t.strides[0],w=0;w<e.inChannels;++w)for(var C=0;C<e.outHeight;++C)for(var E=C*r-c,_=Math.max(0,E),I=Math.min(e.inHeight,s+E),R=x+C*m,k=0;k<e.outWidth;++k){for(var S=k*o-l,D=Math.max(0,S),A=Math.min(e.inWidth,u+S),T=h,F=0,N=0,M=_;M<I;M+=i){for(var O=b+M*t.strides[1],P=D;P<A;P+=a){var B=f[O+P*t.strides[2]+w];"max"===n&&T<B?T=B:"avg"===n&&(F+=B,N++)}if(isNaN(T))break}d[R+k*g+w]="avg"===n?F/N:T}return p.toTensor()},lh.prototype.maxPool=function(t,e){return this.pool(t,e,"max")},lh.prototype.maxPoolPositions=function(t,e){for(var n=or(e.outShape,"int32"),r=e.strideHeight,o=e.strideWidth,i=e.dilationHeight,a=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h=this.bufferSync(t),f=0;f<e.batchSize;++f)for(var p=0;p<e.inChannels;++p)for(var d=0;d<e.outHeight;++d){for(var v=d*r-c,m=v;m<0;)m+=i;for(var g=Math.min(e.inHeight,s+v),y=0;y<e.outWidth;++y){for(var x=y*o-l,b=x;b<0;)b+=a;for(var w=Math.min(e.inWidth,u+x),C=Number.NEGATIVE_INFINITY,E=-1,_=m;_<g;_+=i)for(var I=_-v,R=b;R<w;R+=a){var k=R-x,S=h.get(f,_,R,p);C<S&&(C=S,E=I*u+k)}n.set(E,f,d,y,p)}}return n.toTensor()},lh.prototype.maxPoolBackprop=function(t,e,n,r){ah([e,n],"maxPoolBackprop");for(var o=this.maxPoolPositions(e,r),i=r.strideHeight,a=r.strideWidth,s=r.dilationHeight,u=r.dilationWidth,c=r.effectiveFilterHeight,l=r.effectiveFilterWidth,h=l-1-r.padInfo.left,f=c-1-r.padInfo.top,p=or(e.shape,"float32"),d=this.bufferSync(o),v=this.bufferSync(t),m=0;m<r.batchSize;++m)for(var g=0;g<r.inChannels;++g)for(var y=0;y<r.inHeight;++y)for(var x=0;x<r.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=s){var _=(b+E)/i;if(!(_<0||_>=r.outHeight||Math.floor(_)!==_))for(var I=0;I<l;I+=u){var R=(w+I)/a;if(!(R<0||R>=r.outWidth||Math.floor(R)!==R)){var k=c*l-1-d.get(m,_,R,g)===E*l+I?1:0;0!=k&&(C+=v.get(m,_,R,g)*k)}}}p.set(C,m,y,x,g)}return p.toTensor()},lh.prototype.avgPoolBackprop=function(t,e,n){ah([t,e],"avgPoolBackprop");for(var r=n.strideHeight,o=n.strideWidth,i=n.filterHeight,a=n.filterWidth,s=n.dilationHeight,u=n.dilationWidth,c=n.effectiveFilterHeight,l=n.effectiveFilterWidth,h=l-1-n.padInfo.left,f=c-1-n.padInfo.top,p=or(e.shape,"float32"),d=1/(i*a),v=this.bufferSync(t),m=0;m<n.batchSize;++m)for(var g=0;g<n.inChannels;++g)for(var y=0;y<n.inHeight;++y)for(var x=0;x<n.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=s){var _=(b+E)/r;if(!(_<0||_>=n.outHeight||Math.floor(_)!==_))for(var I=0;I<l;I+=u){var R=(w+I)/o;R<0||R>=n.outWidth||Math.floor(R)!==R||(C+=v.get(m,_,R,g))}}p.set(C*d,m,y,x,g)}return p.toTensor()},lh.prototype.pool3d=function(t,e,n){ah(t,"pool3d");for(var r=e.strideDepth,o=e.strideHeight,i=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,p=e.padInfo.top,d=e.padInfo.left,v="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=this.readSync(t.dataId),g=or(e.outShape,t.dtype),y=g.values,x=e.outShape[1]*e.outShape[2]*e.outShape[3]*e.outShape[4],b=e.outShape[2]*e.outShape[3]*e.outShape[4],w=e.outShape[3]*e.outShape[4],C=e.outShape[4],E=0;E<e.batchSize;++E)for(var _=E*x,I=E*t.strides[0],R=0;R<e.inChannels;++R)for(var k=0;k<e.outDepth;++k){for(var S=k*r-f,D=S;D<0;)D+=a;for(var A=Math.min(e.inDepth,c+S),T=_+k*b,F=0;F<e.outHeight;++F){for(var N=F*o-p,M=N;M<0;)M+=s;for(var O=Math.min(e.inHeight,l+N),P=T+F*w,B=0;B<e.outWidth;++B){for(var L=B*i-d,W=L;W<0;)W+=u;for(var z=Math.min(e.inWidth,h+L),U=P+B*C,V=v,G=0,H=0,q=D;q<A;q+=a){for(var j=I+q*t.strides[1],K=M;K<O;K+=s){for(var X=j+K*t.strides[2],$=W;$<z;$+=u){var Y=m[X+$*t.strides[3]+R];if("max"===n&&V<Y?V=Y:"avg"===n&&(G+=Y,H++),isNaN(V))break}if(isNaN(V))break}if(isNaN(V))break}y[U+R]="avg"===n?G/H:V}}}return g.toTensor()},lh.prototype.avgPool3d=function(t,e){return ah(t,"avgPool3d"),this.pool3d(t,e,"avg").toFloat()},lh.prototype.avgPool3dBackprop=function(t,e,n){ah([t,e],"avgPool3dBackprop");for(var r=n.strideDepth,o=n.strideHeight,i=n.strideWidth,a=n.filterDepth,s=n.filterHeight,u=n.filterWidth,c=n.dilationDepth,l=n.dilationHeight,h=n.dilationWidth,f=n.effectiveFilterDepth,p=n.effectiveFilterHeight,d=n.effectiveFilterWidth,v=f-1-n.padInfo.front,m=d-1-n.padInfo.left,g=p-1-n.padInfo.top,y=or(e.shape,"float32"),x=1/(a*s*u),b=this.bufferSync(t),w=0;w<n.batchSize;++w)for(var C=0;C<n.inChannels;++C)for(var E=0;E<n.inDepth;++E)for(var _=0;_<n.inHeight;++_)for(var I=0;I<n.inWidth;++I){for(var R=E-v,k=_-g,S=I-m,D=0,A=0;A<f;A+=c){var T=(R+A)/r;if(!(T<0||T>=n.outDepth||Math.floor(T)!==T))for(var F=0;F<p;F+=l){var N=(k+F)/o;if(!(N<0||N>=n.outHeight||Math.floor(N)!==N))for(var M=0;M<d;M+=h){var O=(S+M)/i;O<0||O>=n.outWidth||Math.floor(O)!==O||(D+=b.get(w,T,N,O,C))}}}y.set(D*x,w,E,_,I,C)}return y.toTensor()},lh.prototype.maxPool3d=function(t,e){return ah(t,"maxPool3d"),this.pool3d(t,e,"max").toFloat()},lh.prototype.maxPool3dPositions=function(t,e){for(var n=or(e.outShape,"int32"),r=e.strideDepth,o=e.strideHeight,i=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,p=e.padInfo.top,d=e.padInfo.left,v=this.bufferSync(t),m=0;m<e.batchSize;++m)for(var g=0;g<e.inChannels;++g)for(var y=0;y<e.outDepth;++y){for(var x=y*r-f,b=x;b<0;)b+=a;for(var w=Math.min(e.inDepth,c+x),C=0;C<e.outHeight;++C){for(var E=C*o-p,_=E;_<0;)_+=s;for(var I=Math.min(e.inHeight,l+E),R=0;R<e.outWidth;++R){for(var k=R*i-d,S=k;S<0;)S+=u;for(var D=Math.min(e.inWidth,h+k),A=Number.NEGATIVE_INFINITY,T=-1,F=b;F<w;F+=a)for(var N=F-x,M=_;M<I;M+=s)for(var O=M-E,P=S;P<D;P+=u){var B=P-k,L=v.get(m,F,M,P,g);A<=L&&(A=L,T=N*l*h+O*l+B)}n.set(T,m,y,C,R,g)}}}return n.toTensor()},lh.prototype.maxPool3dBackprop=function(t,e,n,r){ah([e,n],"maxPool3dBackprop");for(var o=this.maxPool3dPositions(e,r),i=r.strideDepth,a=r.strideHeight,s=r.strideWidth,u=r.dilationDepth,c=r.dilationHeight,l=r.dilationWidth,h=r.effectiveFilterDepth,f=r.effectiveFilterHeight,p=r.effectiveFilterWidth,d=h-1-r.padInfo.front,v=p-1-r.padInfo.left,m=f-1-r.padInfo.top,g=or(e.shape,"float32"),y=this.bufferSync(o),x=this.bufferSync(t),b=0;b<r.batchSize;++b)for(var w=0;w<r.inChannels;++w)for(var C=0;C<r.inDepth;++C)for(var E=0;E<r.inHeight;++E)for(var _=0;_<r.inWidth;++_){for(var I=C-d,R=E-m,k=_-v,S=0,D=0;D<h;D+=u){var A=(I+D)/i;if(!(A<0||A>=r.outDepth||Math.floor(A)!==A))for(var T=0;T<f;T+=c){var F=(R+T)/a;if(!(F<0||F>=r.outHeight||Math.floor(F)!==F))for(var N=0;N<p;N+=l){var M=(k+N)/s;if(!(M<0||M>=r.outWidth||Math.floor(M)!==M)){var O=h*f*p-1-y.get(b,A,F,M,w)===D*f*p+T*p+N?1:0;0!=O&&(S+=x.get(b,A,F,M,w)*O)}}}}g.set(S,b,C,E,_,w)}return g.toTensor()},lh.prototype.cast=function(t,e){return wo(t,e,this)},lh.prototype.reshape=function(t,e){return Co(t,e)},lh.prototype.avgPool=function(t,e){return ah(t,"avgPool"),this.pool(t,e,"avg").toFloat()},lh.prototype.resizeBilinear=function(t,e,n,r){ah(t,"resizeBilinear");for(var o=t.shape,i=o[0],a=o[1],s=o[2],u=o[3],c=this.readSync(t.dataId),l=new Float32Array(L([i,e,n,u])),h=[r&&1<e?a-1:a,r&&1<n?s-1:s],f=[r&&1<e?e-1:e,r&&1<n?n-1:n],p=0,d=h[0]/f[0],v=h[1]/f[1],m=0;m<i;m++)for(var g=0;g<e;g++)for(var y=d*g,x=Math.floor(y),b=y-x,w=Math.min(a-1,Math.ceil(y)),C=m*t.strides[0]+x*t.strides[1],E=m*t.strides[0]+w*t.strides[1],_=0;_<n;_++)for(var I=v*_,R=Math.floor(I),k=I-R,S=Math.min(s-1,Math.ceil(I)),D=C+R*t.strides[2],A=E+R*t.strides[2],T=C+S*t.strides[2],F=E+S*t.strides[2],N=0;N<u;N++){var M=c[D+N],O=c[A+N],P=M+(c[T+N]-M)*k,B=P+(O+(c[F+N]-O)*k-P)*b;l[p++]=B}return bn(l,[i,e,n,u])},lh.prototype.resizeBilinearBackprop=function(t,e,n){ah([t,e],"resizeBilinearBackprop");for(var r=e.shape,o=r[0],i=r[1],a=r[2],s=r[3],u=t.shape,c=u[1],l=u[2],h=new Float32Array(o*i*a*s),f=[n&&1<c?i-1:i,n&&1<l?a-1:a],p=[n&&1<c?c-1:c,n&&1<l?l-1:l],d=f[0]/p[0],v=f[1]/p[1],m=this.readSync(t.dataId),g=0,y=0;y<o;y++)for(var x=y*e.strides[0],b=0;b<c;b++)for(var w=b*d,C=Math.floor(w),E=Math.min(Math.ceil(w),i-1),_=x+C*e.strides[1],I=x+E*e.strides[1],R=w-C,k=1-R,S=0;S<l;S++)for(var D=S*v,A=Math.floor(D),T=Math.min(Math.ceil(D),a-1),F=D-A,N=1-F,M=_+A*e.strides[2],O=_+T*e.strides[2],P=I+A*e.strides[2],B=I+T*e.strides[2],L=k*N,W=k*F,z=R*N,U=R*F,V=0;V<s;V++){var G=m[g++];h[M+V]+=G*L,h[O+V]+=G*W,h[P+V]+=G*z,h[B+V]+=G*U}return Rn(h,[o,a,i,s],e.dtype)},lh.prototype.resizeNearestNeighbor=function(t,e,n,r){ah(t,"resizeNearestNeighbor");for(var o=t.shape,i=o[0],a=o[1],s=o[2],u=o[3],c=this.readSync(t.dataId),l=new Float32Array(i*e*n*u),h=[r&&1<e?a-1:a,r&&1<n?s-1:s],f=[r&&1<e?e-1:e,r&&1<n?n-1:n],p=h[0]/f[0],d=h[1]/f[1],v=0,m=0;m<i;m++)for(var g=m*t.strides[0],y=0;y<e;y++)for(var x=p*y,b=g+Math.min(a-1,r?Math.round(x):Math.floor(x))*t.strides[1],w=0;w<n;w++)for(var C=d*w,E=b+Math.min(s-1,r?Math.round(C):Math.floor(C))*t.strides[2],_=0;_<u;_++){var I=c[E+_];l[v++]=I}return bn(l,[i,e,n,u],t.dtype)},lh.prototype.resizeNearestNeighborBackprop=function(t,e,n){ah([t,e],"resizeNearestNeighborBackprop");for(var r=e.shape,o=r[0],i=r[1],a=r[2],s=r[3],u=t.shape,c=u[1],l=u[2],h=new Float32Array(o*i*a*s),f=this.readSync(t.dataId),p=[n&&1<c?i-1:i,n&&1<l?a-1:a],d=[n&&1<c?c-1:c,n&&1<l?l-1:l],v=p[0]/d[0],m=p[1]/d[1],g=1/v,y=1/m,x=2*Math.ceil(g)+2,b=2*Math.ceil(y)+2,w=0;w<o;w++)for(var C=w*e.strides[0],E=0;E<i;E++)for(var _=C+E*e.strides[1],I=Math.floor(E*g),R=Math.floor(I-x/2),k=0;k<a;k++)for(var S=_+k*e.strides[2],D=Math.floor(k*y),A=Math.floor(D-b/2),T=0;T<s;T++){for(var F=0,N=0;N<x;N++){var M=N+R;if(!(M<0||c<=M)){var O=C+M*t.strides[1],P=M*v;if(E===Math.min(i-1,n?Math.round(P):Math.floor(P)))for(var B=0;B<b;B++){var L=B+A;if(!(L<0||l<=L)){var W=O+L*t.strides[2],z=L*m;k===Math.min(a-1,n?Math.round(z):Math.floor(z))&&(F+=f[W+T])}}}}h[S+T]=F}return Rn(h,e.shape,e.dtype)},lh.prototype.batchNormalization=function(t,e,n,r,o,i){ah([t,e,n,o,i],"batchNorm");for(var a=this.readSync(t.dataId),s=this.readSync(e.dataId),u=this.readSync(n.dataId),c=o?this.readSync(o.dataId):new Float32Array([1]),l=i?this.readSync(i.dataId):new Float32Array([0]),h=new Float32Array(a.length),f=l.length,p=c.length,d=u.length,v=s.length,m=0,g=0,y=0,x=0,b=0;b<a.length;++b)h[b]=l[m++]+(a[b]-s[g++])*c[y++]/Math.sqrt(u[x++]+r),f<=m&&(m=0),v<=g&&(g=0),p<=y&&(y=0),d<=x&&(x=0);return Rn(h,t.shape)},lh.prototype.localResponseNormalization4D=function(t,a,e,n,r){ah(t,"localResponseNormalization4D");var s=t.shape[3],u=s-1,c=this.readSync(t.dataId),o=t.size,i=new Float32Array(o);function l(t){for(var e=t%s,n=t-e+Math.max(0,e-a),r=t-e+Math.min(e+a,u),o=0;n<=r;n++){var i=c[n];o+=i*i}return o}for(var h=0;h<o;h++){var f=l(h),p=c[h]*Math.pow(e+n*f,-r);i[h]=p}return Rn(i,t.shape)},lh.prototype.LRNGrad=function(t,e,n,r,o,i,a){ah(t,"LRNGrad");for(var s=t.shape[3],u=this.readSync(t.dataId),c=this.readSync(e.dataId),l=this.readSync(n.dataId),h=new Float32Array(t.size),f=t.size,p=0;p<f;p++){for(var d=p%s,v=p-d+Math.max(0,d-r),m=p-d+Math.min(s,d+r+1),g=0,y=v;y<m;y++)g+=Math.pow(c[y],2);for(g=i*g+o,y=v;y<m;y++){var x=-2*i*a*c[y]*l[p]/g;p===y&&(x+=Math.pow(g,-a)),x*=u[p],h[y]+=x}}return Rn(h,t.shape)},lh.prototype.multinomial=function(t,e,n,r){ah(t,"multinomial");for(var o=e?t:Qr(t),i=o.shape[0],a=o.shape[1],s=Tn([i,n],"int32"),u=this.readSync(s.dataId),c=this.readSync(o.dataId),l=0;l<i;++l){var h=l*a,f=new Float32Array(a-1);f[0]=c[h];for(var p=1;p<f.length;++p)f[p]=f[p-1]+c[h+p];for(var d=Jn(r.toString()),v=l*n,m=0;m<n;++m){var g=d();u[v+m]=f.length;for(var y=0;y<f.length;y++)if(g<f[y]){u[v+m]=y;break}}}return s},lh.prototype.oneHot=function(t,e,n,r){ah(t,"oneHot");var o=new Float32Array(t.size*e);o.fill(r);for(var i=this.readSync(t.dataId),a=0;a<t.size;++a)0<=i[a]&&i[a]<e&&(o[a*e+i[a]]=n);return _n(o,[t.size,e],"int32")},lh.prototype.nonMaxSuppression=function(t,e,n,r,o){return ah(t,"nonMaxSuppression"),ko(this.readSync(t.dataId),this.readSync(e.dataId),n,r,o)},lh.prototype.fft=function(t){return this.fftBatch(t,!1)},lh.prototype.ifft=function(t){return this.fftBatch(t,!0)},lh.prototype.fftBatch=function(t,e){for(var n=t.shape[0],r=t.shape[1],o=or(t.shape,"float32"),i=or(t.shape,"float32"),a=yn(t).as2D(n,r),s=xn(t).as2D(n,r),u=0;u<n;u++)for(var c=a.slice([u,0],[1,r]),l=s.slice([u,0],[1,r]),h=gn(c,l),f=this.readSync(this.fftImpl(h,e).dataId),p=0;p<r;p++){var d=Ro(f,p);o.values[u*r+p]=d.real,i.values[u*r+p]=d.imag}return gn(o.toTensor(),i.toTensor()).as2D(n,r)},lh.prototype.fftImpl=function(t,e){var n=t.as1D(),r=n.size;if(this.isExponentOf2(r)){var o=this.fftRadix2(n,r,e).as2D(t.shape[0],t.shape[1]);return e&&(o=gn(yn(o).div(Cn(r)),xn(o).div(Cn(r)))),o}var i=this.readSync(t.dataId),a=function(t){for(var e=new Float32Array(t.length/2),n=new Float32Array(t.length/2),r=0;r<t.length;r+=2)e[r/2]=t[r],n[r/2]=t[r+1];return{real:e,imag:n}}(this.fourierTransformByMatmul(i,r,e));return gn(a.real,a.imag).as2D(t.shape[0],t.shape[1])},lh.prototype.isExponentOf2=function(t){return 0==(t&t-1)},lh.prototype.fftRadix2=function(t,e,n){if(1===e)return t;var r=this.readSync(t.dataId),o=e/2,i=function(t){for(var e=Math.ceil(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=0;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return{real:n,imag:r}}(r),a=gn(i.real,i.imag).as1D(),s=function(t){for(var e=Math.floor(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=2;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return{real:n,imag:r}}(r),u=gn(s.real,s.imag).as1D();a=this.fftRadix2(a,o,n),u=this.fftRadix2(u,o,n);var c=function(t,e){for(var n=new Float32Array(t/2),r=new Float32Array(t/2),o=0;o<Math.ceil(t/2);o++){var i=(e?2:-2)*Math.PI*(o/t);n[o]=Math.cos(i),r[o]=Math.sin(i)}return{real:n,imag:r}}(e,n),l=gn(c.real,c.imag).mul(u),h=a.add(l),f=a.sub(l),p=yn(h).concat(yn(f)),d=xn(h).concat(xn(f));return gn(p,d).as1D()},lh.prototype.fourierTransformByMatmul=function(t,e,n){for(var r=new Float32Array(2*e),o=0;o<e;o++){for(var i=0,a=0,s=0;s<e;s++){var u=(d=o*s,v=e,m=(n?2:-2)*Math.PI*(d/v),{real:Math.cos(m),imag:Math.sin(m)}),c=Ro(t,s);i+=c.real*u.real-c.imag*u.imag,a+=c.real*u.imag+c.imag*u.real}n&&(i/=e,a/=e),h=i,f=a,(l=r)[2*(p=o)]=h,l[2*p+1]=f}var l,h,f,p,d,v,m;return r},lh.prototype.depthToSpace=function(t,e,n){P("NHWC"===n,function(){return"Only NHWC dataFormat supported on CPU for depthToSpace. Got "+n}),P(1<e,function(){return"blockSize should be > 1 for depthToSpace, but was: "+e});for(var r=t.shape[0],o=t.shape[1],i=t.shape[2],a=t.shape[3],s=o*e,u=i*e,c=a/(e*e),l=this.readSync(t.dataId),h=new Float32Array(r*s*u*c),f=0,p=0;p<r;++p)for(var d=0;d<s;++d)for(var v=Math.floor(d/e),m=d%e,g=0;g<u;++g)for(var y=Math.floor(g/e),x=(m*e+g%e)*c,b=0;b<c;++b){var w=b+x+a*(y+i*(v+o*p));h[f++]=l[w]}return Rn(h,[r,s,u,c])},lh.prototype.broadcastedBinaryOp=function(a,s,t,u){var e=so(a.shape,s.shape),c=or(e,t),l=this.readSync(a.dataId),h=this.readSync(s.dataId),f=io(a.shape,e),p=io(s.shape,e),d=c.values;if(f.length+p.length===0)for(var n=0;n<d.length;++n)d[n]=u(l[n%l.length],h[n%h.length]);else{var v=this.bufferSync(a),m=this.bufferSync(s),r=function(t){var e=c.indexToLoc(t),n=e.slice(-a.rank);f.forEach(function(t){return n[t]=0});var r=v.locToIndex(n),o=e.slice(-s.rank);p.forEach(function(t){return o[t]=0});var i=m.locToIndex(o);d[t]=u(l[r],h[i])};for(n=0;n<d.length;++n)r(n)}return c.toTensor()},lh.prototype.broadcastedBinaryComplexOp=function(s,u,c){var t=so(s.shape,u.shape),l=or(t,"float32"),e=or(t,"float32"),h=this.readSync(s.dataId),f=this.readSync(u.dataId),p=io(s.shape,t),d=io(u.shape,t),v=l.values,m=e.values;if(p.length+d.length===0)for(var n=0;n<v.length;n++){var r=n%h.length,o=n%f.length,i=c(h[2*r],h[2*r+1],f[2*o],f[2*o+1]);v[n]=i.real,m[n]=i.imag}else{var g=this.bufferSync(this.data.get(s.dataId).complexTensors.real),y=this.bufferSync(this.data.get(u.dataId).complexTensors.real),a=function(t){var e=l.indexToLoc(t),n=e.slice(-s.rank);p.forEach(function(t){return n[t]=0});var r=g.locToIndex(n),o=e.slice(-u.rank);d.forEach(function(t){return o[t]=0});var i=y.locToIndex(o),a=c(h[2*r],h[2*r+1],f[2*i],f[2*i+1]);v[t]=a.real,m[t]=a.imag};for(n=0;n<v.length;n++)a(n)}return this.complex(l.toTensor(),e.toTensor())},lh.prototype.split=function(t,e,n){return Do(t,e,n)},lh.prototype.dispose=function(){},lh.prototype.floatPrecision=function(){return 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y=h[d*a+g];v.push(y),m+=y*s[g]}if(m<0||r/o<=m)throw new Error("Invalid indices: "+v+" does not index into "+n);for(var x=0;x<o;x++)c?p.values[m*o+x]+=f[d*o+x]:p.values[m*o+x]=0===e.rank?f[0]:f[d*o+x]}return p.toTensor().reshape(n)},lh);function lh(){var t=uh.call(this)||this;return t.blockSize=48,t.firstUse=!0,t.data=new to(t,Vt),t}Vt.registerBackend("cpu",function(){return new ch},1),n({kernelName:"Square",backendName:"cpu",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e.x,o=n;ah(r,"square");for(var i=o.data.get(r.dataId).values,a=new Float32Array(i.length),s=0;s<i.length;++s){var u=i[s];a[s]=u*u}return{dataId:o.write(a,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}}),n({kernelName:"Square",backendName:"webgl",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e.x,o=n,i=new Ja(r.shape,"return x * x;");return o.runWebGLProgram(i,[r],r.dtype)}});var hh,fh=function(t){this.variableNames=["A"];var e=Lo(),n=t[0],r=t[1];this.outputShape=t,this.userCode="\n      void main() {\n        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t=[this.x,this.y,this.width,this.height].map(function(t){return Math.round(t)});return new Wp({x:t[0],y:t[1],width:t[2],height:t[3]})},Wp.prototype.floor=function(){var t=[this.x,this.y,this.width,this.height].map(function(t){return Math.floor(t)});return new Wp({x:t[0],y:t[1],width:t[2],height:t[3]})},Wp.prototype.toSquare=function(){var t=this.x,e=this.y,n=this.width,r=this.height,o=Math.abs(n-r);return n<r&&(t-=o/2,n+=o),r<n&&(e-=o/2,r+=o),new Wp({x:t,y:e,width:n,height:r})},Wp.prototype.rescale=function(t){var e=Dp(t)?t.width:t,n=Dp(t)?t.height:t;return new Wp({x:this.x*e,y:this.y*n,width:this.width*e,height:this.height*n})},Wp.prototype.pad=function(t,e){var n=[this.x-t/2,this.y-e/2,this.width+t,this.height+e];return new Wp({x:n[0],y:n[1],width:n[2],height:n[3]})},Wp.prototype.clipAtImageBorders=function(t,e){var n=this.x,r=this.y,o=this.right,i=this.bottom,a=Math.max(n,0),s=Math.max(r,0),u=o-a,c=i-s;return new 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i=o?[n.x,n.y,n.width,n.height]:[n.left,n.top,n.right-n.left,n.bottom-n.top],a=i[0],s=i[1],u=i[2],c=i[3];Wp.assertIsValidBox({x:a,y:s,width:u,height:c},"Box.constructor",e),this._x=a,this._y=s,this._width=u,this._height=c}var zp,Up=(vp(Vp,zp=Lp),Vp);function Vp(t,e,n,r,o){return void 0===o&&(o=!1),zp.call(this,{left:t,top:e,right:n,bottom:r},o)||this}var Gp=(Object.defineProperty(Hp.prototype,"score",{get:function(){return this._score},enumerable:!0,configurable:!0}),Object.defineProperty(Hp.prototype,"classScore",{get:function(){return this._classScore},enumerable:!0,configurable:!0}),Object.defineProperty(Hp.prototype,"className",{get:function(){return this._className},enumerable:!0,configurable:!0}),Object.defineProperty(Hp.prototype,"box",{get:function(){return this._box},enumerable:!0,configurable:!0}),Object.defineProperty(Hp.prototype,"imageDims",{get:function(){return this._imageDims},enumerable:!0,configurable:!0}),Object.defineProperty(Hp.prototype,"imageWidth",{get:function(){return this.imageDims.width},enumerable:!0,configurable:!0}),Object.defineProperty(Hp.prototype,"imageHeight",{get:function(){return this.imageDims.height},enumerable:!0,configurable:!0}),Object.defineProperty(Hp.prototype,"relativeBox",{get:function(){return new Lp(this._box).rescale(this.imageDims.reverse())},enumerable:!0,configurable:!0}),Hp.prototype.forSize=function(t,e){return new Hp(this.score,this.classScore,this.className,this.relativeBox,{width:t,height:e})},Hp);function Hp(t,e,n,r,o){this._imageDims=new bp(o.width,o.height),this._score=t,this._classScore=e,this._className=n,this._box=new Lp(r).rescale(this._imageDims)}var qp,jp=(vp(Kp,qp=Gp),Kp.prototype.forSize=function(t,e){var n=qp.prototype.forSize.call(this,t,e);return new Kp(n.score,n.relativeBox,n.imageDims)},Kp);function Kp(t,e,n){return qp.call(this,t,t,"",e,n)||this}function Xp(t,e,n){void 0===n&&(n=!0);var r=Math.max(0,Math.min(t.right,e.right)-Math.max(t.left,e.left))*Math.max(0,Math.min(t.bottom,e.bottom)-Math.max(t.top,e.top));return n?r/(t.area+e.area-r):r/Math.min(t.area,e.area)}function $p(t){var e=t.map(function(t){return t.x}),n=t.map(function(t){return t.y}),r=e.reduce(function(t,e){return e<t?e:t},1/0),o=n.reduce(function(t,e){return e<t?e:t},1/0),i=e.reduce(function(t,e){return t<e?e:t},0),a=n.reduce(function(t,e){return t<e?e:t},0);return new Up(r,o,i,a)}function Yp(s,t,u,c){void 0===c&&(c=!0);for(var l=t.map(function(t,e){return{score:t,boxIndex:e}}).sort(function(t,e){return t.score-e.score}).map(function(t){return t.boxIndex}),h=[],e=function(){var t=l.pop();h.push(t);for(var e=l,n=[],r=0;r<e.length;r++){var o=e[r],i=s[t],a=s[o];n.push(Xp(i,a,c))}l=l.filter(function(t,e){return n[e]<=u})};0<l.length;)e();return h}function Jp(s,u){return Je(function(){var 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Error("LabeledFaceDescriptors - constructor expected label to be a string");if(!Array.isArray(e)||e.some(function(t){return!(t instanceof Float32Array)}))throw new Error("LabeledFaceDescriptors - constructor expected descriptors to be an array of Float32Array");this._label=t,this._descriptors=e}var yd,xd,bd=(vp(wd,yd=dd),wd.assertIsValidPredictedBox=function(t,e){if(dd.assertIsValidLabeledBox(t,e),!Mp(t.score)||!Mp(t.classScore))throw new Error(e+" - expected properties score ("+t.score+") and ("+t.classScore+") to be a number between [0, 1]")},Object.defineProperty(wd.prototype,"score",{get:function(){return this._score},enumerable:!0,configurable:!0}),Object.defineProperty(wd.prototype,"classScore",{get:function(){return this._classScore},enumerable:!0,configurable:!0}),wd);function wd(t,e,n,r){var o=yd.call(this,t,e)||this;return o._score=n,o._classScore=r,o}function Cd(t){return t.detection instanceof jp}function Ed(t,e){var n={detection:e};return Object.assign({},t,n)}function 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n=this.options.anchorPosition,r=n===Td.BOTTOM_RIGHT||n===Td.TOP_RIGHT,o=n===Td.BOTTOM_LEFT||n===Td.BOTTOM_RIGHT,i=this.measureWidth(t),a=this.measureHeight(),s=r?this.anchor.x-i:this.anchor.x,u=o?this.anchor.y-a:this.anchor.y;if(e){var c=e.width,l=e.height;return{x:Math.max(Math.min(s,c-i),0),y:Math.max(Math.min(u,l-a),0)}}return{x:s,y:u}},Ld.prototype.draw=function(t){var e=Md(t),o=Od(e),n=this.options,r=n.backgroundColor,i=n.fontColor,a=n.fontSize,s=n.fontStyle,u=n.padding;o.font=a+"px "+s;var c=this.measureWidth(o),l=this.measureHeight();o.fillStyle=r;var h=this.getUpperLeft(o,e);o.fillRect(h.x,h.y,c,l),o.fillStyle=i,this.text.forEach(function(t,e){var n=u+h.x,r=u+h.y+(e+1)*a;o.fillText(t,n,r)})},Ld);function Ld(t,e,n){void 0===n&&(n={}),this.text="string"==typeof t?[t]:t instanceof Ld?t.text:t,this.anchor=e,this.options=new Pd(n)}var Wd=function(t){void 0===t&&(t={});var e=t.boxColor,n=t.lineWidth,r=t.label,o=t.drawLabelOptions;this.boxColor=e||"rgba(0, 0, 255, 1)",this.lineWidth=n||2,this.label=r;var i={anchorPosition:Td.BOTTOM_LEFT,backgroundColor:this.boxColor};this.drawLabelOptions=new Pd(Object.assign({},i,o))},zd=(Ud.prototype.draw=function(t){var e=Od(t),n=this.options,r=n.boxColor,o=n.lineWidth,i=this.box,a=i.x,s=i.y,u=i.width,c=i.height;e.strokeStyle=r,e.lineWidth=o,e.strokeRect(a,s,u,c);var l=this.options.label;l&&new Bd([l],{x:a-o/2,y:s},this.options.drawLabelOptions).draw(t)},Ud);function Ud(t,e){void 0===e&&(e={}),this.box=new Lp(t),this.options=new Wd(e)}function Vd(t){var e=Nd.getEnv(),n=e.Image,r=e.Video;return t instanceof n&&t.complete||t instanceof r&&3<=t.readyState}function Gd(t){return new Promise(function(e,n){if(t instanceof Nd.getEnv().Canvas||Vd(t))return e();function r(t){t.currentTarget&&(t.currentTarget.removeEventListener("load",r),t.currentTarget.removeEventListener("error",o),e(t))}function o(t){t.currentTarget&&(t.currentTarget.removeEventListener("load",r),t.currentTarget.removeEventListener("error",o),n(t))}t.addEventListener("load",r),t.addEventListener("error",o)})}function Hd(t){return new Promise(function(e,n){if(!(t instanceof Blob))return n("bufferToImage - expected buf to be of type: Blob");var r=new FileReader;r.onload=function(){if("string"!=typeof r.result)return n("bufferToImage - expected reader.result to be a string, in onload");var t=Nd.getEnv().createImageElement();t.onload=function(){return e(t)},t.onerror=n,t.src=r.result},r.onerror=n,r.readAsDataURL(t)})}function qd(t){var e=Nd.getEnv(),n=e.Image,r=e.Video;return t instanceof n?new bp(t.naturalWidth,t.naturalHeight):t instanceof r?new bp(t.videoWidth,t.videoHeight):new bp(t.width,t.height)}function jd(t){var e=t.width,n=t.height,r=(0,Nd.getEnv().createCanvasElement)();return r.width=e,r.height=n,r}function Kd(t,e){var n=Nd.getEnv().ImageData;if(!(t instanceof n||Vd(t)))throw new Error("createCanvasFromMedia - media has not finished loading yet");var r=e||qd(t),o=r.width,i=r.height,a=jd({width:o,height:i});return t instanceof n?Od(a).putImageData(t,0,0):Od(a).drawImage(t,0,0,o,i),a}function Xd(s,u){return gp(this,void 0,void 0,function(){var e,n,r,o,i,a;return yp(this,function(t){switch(t.label){case 0:return e=u||Nd.getEnv().createCanvasElement(),n=s.shape.slice(Ip(s)?1:0),r=n[0],o=n[1],i=n[2],a=Je(function(){return s.as3D(r,o,i).toInt()}),[4,Rf.toPixels(a,e)];case 1:return t.sent(),a.dispose(),[2,e]}})})}function $d(t){var e=Nd.getEnv(),n=e.Image,r=e.Canvas,o=e.Video;return t instanceof n||t instanceof r||t instanceof o}function Yd(t,e,n){void 0===n&&(n=!1);var r=Nd.getEnv(),o=r.Image,i=r.Canvas;if(!(t instanceof o||t instanceof i))throw new Error("imageToSquare - expected arg0 to be HTMLImageElement | HTMLCanvasElement");var a=qd(t),s=e/Math.max(a.height,a.width),u=s*a.width,c=s*a.height,l=jd({width:e,height:e}),h=t instanceof i?t:Kd(t),f=Math.abs(u-c)/2,p=n&&u<c?f:0,d=n&&c<u?f:0;return Od(l).drawImage(h,p,d,u,c),l}var Jd=(Object.defineProperty(Qd.prototype,"imageTensors",{get:function(){return this._imageTensors},enumerable:!0,configurable:!0}),Object.defineProperty(Qd.prototype,"canvases",{get:function(){return this._canvases},enumerable:!0,configurable:!0}),Object.defineProperty(Qd.prototype,"isBatchInput",{get:function(){return 1<this.batchSize||this._treatAsBatchInput},enumerable:!0,configurable:!0}),Object.defineProperty(Qd.prototype,"batchSize",{get:function(){return this._batchSize},enumerable:!0,configurable:!0}),Object.defineProperty(Qd.prototype,"inputDimensions",{get:function(){return this._inputDimensions},enumerable:!0,configurable:!0}),Object.defineProperty(Qd.prototype,"inputSize",{get:function(){return this._inputSize},enumerable:!0,configurable:!0}),Object.defineProperty(Qd.prototype,"reshapedInputDimensions",{get:function(){var n=this;return Fp(this.batchSize,0,1).map(function(t,e){return n.getReshapedInputDimensions(e)})},enumerable:!0,configurable:!0}),Qd.prototype.getInput=function(t){return this.canvases[t]||this.imageTensors[t]},Qd.prototype.getInputDimensions=function(t){return this._inputDimensions[t]},Qd.prototype.getInputHeight=function(t){return this._inputDimensions[t][0]},Qd.prototype.getInputWidth=function(t){return this._inputDimensions[t][1]},Qd.prototype.getReshapedInputDimensions=function(t){if("number"!=typeof this.inputSize)throw new Error("getReshapedInputDimensions - inputSize not set, toBatchTensor has not been called yet");return Ap({width:this.getInputWidth(t),height:this.getInputHeight(t)},this.inputSize)},Qd.prototype.toBatchTensor=function(r,o){var i=this;return void 0===o&&(o=!0),this._inputSize=r,Je(function(){var t=Fp(i.batchSize,0,1).map(function(t){var e=i.getInput(t);if(e instanceof vt){var n=Ip(e)?e:e.expandDims();return(n=Qp(n,o)).shape[1]===r&&n.shape[2]===r||(n=th.resizeBilinear(n,[r,r])),n.as3D(r,r,3)}if(e instanceof Nd.getEnv().Canvas)return Rf.fromPixels(Yd(e,r,o));throw new Error("toBatchTensor - at batchIdx "+t+", expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have "+e)});return Dr(t.map(function(t){return t.toFloat()})).as4D(i.batchSize,r,r,3)})},Qd);function Qd(t,e){var o=this;if(void 0===e&&(e=!1),this._imageTensors=[],this._canvases=[],this._treatAsBatchInput=!1,this._inputDimensions=[],!Array.isArray(t))throw new Error("NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have "+t);this._treatAsBatchInput=e,this._batchSize=t.length,t.forEach(function(t,e){if(_p(t))return o._imageTensors[e]=t,void(o._inputDimensions[e]=t.shape);if(Ip(t)){var n=t.shape[0];if(1!==n)throw new Error("NetInput - tf.Tensor4D with batchSize "+n+" passed, but not supported in input array");return o._imageTensors[e]=t,void(o._inputDimensions[e]=t.shape.slice(1))}var r=t instanceof Nd.getEnv().Canvas?t:Kd(t);o._canvases[e]=r,o._inputDimensions[e]=[r.height,r.width,3]})}function Zd(n){return gp(this,void 0,void 0,function(){var r,o,e;return yp(this,function(t){switch(t.label){case 0:if(n instanceof Jd)return[2,n];if(!(r=Array.isArray(n)?n:[n]).length)throw new Error("toNetInput - empty array passed as input");return o=function(t){return Array.isArray(n)?" at input index "+t+":":""},(e=r.map(Md)).forEach(function(t,e){if(!$d(t)&&!_p(t)&&!Ip(t)){if("string"==typeof r[e])throw new Error("toNetInput -"+o(e)+" string passed, but could not resolve HTMLElement for element id "+r[e]);throw new Error("toNetInput -"+o(e)+" expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id")}if(Ip(t)){var n=t.shape[0];if(1!==n)throw new Error("toNetInput -"+o(e)+" tf.Tensor4D with batchSize "+n+" passed, but not supported in input array")}}),[4,Promise.all(e.map(function(t){return $d(t)&&Gd(t)}))];case 1:return t.sent(),[2,new Jd(e,Array.isArray(n))]}})})}function tv(s,u){return gp(this,void 0,void 0,function(){var e,n,r,o,i,a;return yp(this,function(t){switch(t.label){case 0:return e=Nd.getEnv().Canvas,(n=s)instanceof e?[3,5]:[4,Zd(s)];case 1:if(1<(r=t.sent()).batchSize)throw new Error("extractFaces - batchSize > 1 not supported");return(o=r.getInput(0))instanceof e?(i=o,[3,4]):[3,2];case 2:return[4,Xd(o)];case 3:i=t.sent(),t.label=4;case 4:n=i,t.label=5;case 5:return a=Od(n),[2,u.map(function(t){return t instanceof jp?t.forSize(n.width,n.height).box.floor():t}).map(function(t){return t.clipAtImageBorders(n.width,n.height)}).map(function(t){var e=t.x,n=t.y,r=t.width,o=t.height,i=jd({width:r,height:o});return Od(i).putImageData(a.getImageData(e,n,r,o),0,0),i})]}})})}function ev(u,e){return gp(this,void 0,void 0,function(){return yp(this,function(t){if(!_p(u)&&!Ip(u))throw new Error("extractFaceTensors - expected image tensor to be 3D or 4D");if(Ip(u)&&1<u.shape[0])throw new Error("extractFaceTensors - batchSize > 1 not supported");return[2,Je(function(){var t=u.shape.slice(Ip(u)?1:0),i=t[0],a=t[1],s=t[2];return e.map(function(t){return t instanceof jp?t.forSize(a,i).box:t}).map(function(t){return t.clipAtImageBorders(a,i)}).map(function(t){var e=t.x,n=t.y,r=t.width,o=t.height;return Bc(u.as3D(i,a,s),[n,e,0],[o,r,s])})})]})})}function nv(n,r){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return[4,(0,Nd.getEnv().fetch)(n,r)];case 1:if(!((e=t.sent()).status<400))throw new Error("failed to fetch: ("+e.status+") "+e.statusText+", from url: "+e.url);return[2,e]}})})}function rv(e){return gp(this,void 0,void 0,function(){return yp(this,function(t){switch(t.label){case 0:return[4,nv(e)];case 1:return[2,t.sent().json()]}})})}function ov(t,e){var n=e+"-weights_manifest.json";if(!t)return{modelBaseUri:"",manifestUri:n};if("/"===t)return{modelBaseUri:"/",manifestUri:"/"+n};var r=t.startsWith("http://")?"http://":t.startsWith("https://")?"https://":"",o=(t=t.replace(r,"")).split("/").filter(function(t){return t}),i=t.endsWith(".json")?o[o.length-1]:n,a=r+(t.endsWith(".json")?o.slice(0,o.length-1):o).join("/");return{modelBaseUri:a=t.startsWith("/")?"/"+a:a,manifestUri:"/"===a?"/"+i:a+"/"+i}}function iv(i,a){return gp(this,void 0,void 0,function(){var e,n,r,o;return yp(this,function(t){switch(t.label){case 0:return e=ov(i,a),n=e.manifestUri,r=e.modelBaseUri,[4,rv(n)];case 1:return o=t.sent(),[2,Cf.loadWeights(o,r)]}})})}var av=(Object.defineProperty(sv.prototype,"params",{get:function(){return this._params},enumerable:!0,configurable:!0}),Object.defineProperty(sv.prototype,"paramMappings",{get:function(){return this._paramMappings},enumerable:!0,configurable:!0}),Object.defineProperty(sv.prototype,"isLoaded",{get:function(){return!!this.params},enumerable:!0,configurable:!0}),sv.prototype.getParamFromPath=function(t){var e=this.traversePropertyPath(t);return e.obj[e.objProp]},sv.prototype.reassignParamFromPath=function(t,e){var n=this.traversePropertyPath(t),r=n.obj,o=n.objProp;r[o].dispose(),r[o]=e},sv.prototype.getParamList=function(){var n=this;return this._paramMappings.map(function(t){var e=t.paramPath;return{path:e,tensor:n.getParamFromPath(e)}})},sv.prototype.getTrainableParams=function(){return this.getParamList().filter(function(t){return t.tensor instanceof St})},sv.prototype.getFrozenParams=function(){return this.getParamList().filter(function(t){return!(t.tensor instanceof St)})},sv.prototype.variable=function(){var r=this;this.getFrozenParams().forEach(function(t){var e=t.path,n=t.tensor;r.reassignParamFromPath(e,n.variable())})},sv.prototype.freeze=function(){var o=this;this.getTrainableParams().forEach(function(t){var e=t.path,n=t.tensor,r=bn(n.dataSync());n.dispose(),o.reassignParamFromPath(e,r)})},sv.prototype.dispose=function(e){void 0===e&&(e=!0),this.getParamList().forEach(function(t){if(e&&t.tensor.isDisposed)throw new Error("param tensor has already been disposed for path "+t.path);t.tensor.dispose()}),this._params=void 0},sv.prototype.serializeParams=function(){return new Float32Array(this.getParamList().map(function(t){var e=t.tensor;return Array.from(e.dataSync())}).reduce(function(t,e){return t.concat(e)}))},sv.prototype.load=function(e){return gp(this,void 0,void 0,function(){return yp(this,function(t){switch(t.label){case 0:return e instanceof Float32Array?(this.extractWeights(e),[2]):[4,this.loadFromUri(e)];case 1:return t.sent(),[2]}})})},sv.prototype.loadFromUri=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:if(n&&"string"!=typeof n)throw new Error(this._name+".loadFromUri - expected model uri");return[4,iv(n,this.getDefaultModelName())];case 1:return e=t.sent(),this.loadFromWeightMap(e),[2]}})})},sv.prototype.loadFromDisk=function(h){return gp(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l;return yp(this,function(t){switch(t.label){case 0:if(h&&"string"!=typeof h)throw new Error(this._name+".loadFromDisk - expected model file path");return e=Nd.getEnv().readFile,n=ov(h,this.getDefaultModelName()),r=n.manifestUri,o=n.modelBaseUri,i=function(t){return Promise.all(t.map(function(t){return e(t).then(function(t){return t.buffer})}))},a=Cf.weightsLoaderFactory(i),c=(u=JSON).parse,[4,e(r)];case 1:return s=c.apply(u,[t.sent().toString()]),[4,a(s,o)];case 2:return l=t.sent(),this.loadFromWeightMap(l),[2]}})})},sv.prototype.loadFromWeightMap=function(t){var e=this.extractParamsFromWeigthMap(t),n=e.paramMappings,r=e.params;this._paramMappings=n,this._params=r},sv.prototype.extractWeights=function(t){var e=this.extractParams(t),n=e.paramMappings,r=e.params;this._paramMappings=n,this._params=r},sv.prototype.traversePropertyPath=function(n){if(!this.params)throw new Error("traversePropertyPath - model has no loaded params");var t=n.split("/").reduce(function(t,e){if(!t.nextObj.hasOwnProperty(e))throw new Error("traversePropertyPath - object does not have property "+e+", for path "+n);return{obj:t.nextObj,objProp:e,nextObj:t.nextObj[e]}},{nextObj:this.params}),e=t.obj,r=t.objProp;if(!(e&&r&&e[r]instanceof vt))throw new Error("traversePropertyPath - parameter is not a tensor, for path "+n);return{obj:e,objProp:r}},sv);function sv(t){this._name=t,this._params=void 0,this._paramMappings=[]}function uv(e,n,r){return Je(function(){var t=mc(e,n.depthwise_filter,n.pointwise_filter,r,"same");return t=bu(t,n.bias)})}function cv(r,o,i){return void 0===i&&(i=!1),Je(function(){var t=tl(i?bu(cc(r,o.conv0.filters,[2,2],"same"),o.conv0.bias):uv(r,o.conv0,[2,2])),e=uv(t,o.conv1,[1,1]),n=uv(tl(bu(t,e)),o.conv2,[1,1]);return tl(bu(t,bu(e,n)))})}function lv(o,i,a,s){return void 0===a&&(a=!1),void 0===s&&(s=!0),Je(function(){var t=tl(a?bu(cc(o,i.conv0.filters,s?[2,2]:[1,1],"same"),i.conv0.bias):uv(o,i.conv0,s?[2,2]:[1,1])),e=uv(t,i.conv1,[1,1]),n=uv(tl(bu(t,e)),i.conv2,[1,1]),r=uv(tl(bu(t,bu(e,n))),i.conv3,[1,1]);return tl(bu(t,bu(e,bu(n,r))))})}function hv(e,n,r,o){return void 0===r&&(r="same"),void 0===o&&(o=!1),Je(function(){var t=bu(cc(e,n.filters,[1,1],r),n.bias);return o?tl(t):t})}function fv(t,n){Object.keys(t).forEach(function(e){n.some(function(t){return t.originalPath===e})||t[e].dispose()})}function pv(a,s){return function(t,e,n,r){var o=Rn(a(t*e*n*n),[n,n,t,e]),i=En(a(e));return s.push({paramPath:r+"/filters"},{paramPath:r+"/bias"}),{filters:o,bias:i}}}function dv(i,a){return function(t,e,n){var r=_n(i(t*e),[t,e]),o=En(i(e));return a.push({paramPath:n+"/weights"},{paramPath:n+"/bias"}),{weights:r,bias:o}}}var vv=function(t,e,n){this.depthwise_filter=t,this.pointwise_filter=e,this.bias=n};function mv(a,s){return function(t,e,n){var r=Rn(a(9*t),[3,3,t,1]),o=Rn(a(t*e),[1,1,t,e]),i=En(a(e));return s.push({paramPath:n+"/depthwise_filter"},{paramPath:n+"/pointwise_filter"},{paramPath:n+"/bias"}),new vv(r,o,i)}}function gv(o){return function(t){var e=o(t+"/depthwise_filter",4),n=o(t+"/pointwise_filter",4),r=o(t+"/bias",1);return new vv(e,n,r)}}function yv(o,i){return function(t,e,n){var r=o[t];if(!Cp(r,e))throw new Error("expected weightMap["+t+"] to be a Tensor"+e+"D, instead have "+r);return i.push({originalPath:t,paramPath:n||t}),r}}function xv(t){var n=t;return{extractWeights:function(t){var e=n.slice(0,t);return n=n.slice(t),e},getRemainingWeights:function(){return n}}}function bv(t,e){var o=pv(t,e),i=mv(t,e);function a(t,e,n,r){return void 0===r&&(r=!1),{conv0:r?o(t,e,3,n+"/conv0"):i(t,e,n+"/conv0"),conv1:i(e,e,n+"/conv1"),conv2:i(e,e,n+"/conv2")}}return{extractDenseBlock3Params:a,extractDenseBlock4Params:function(t,e,n,r){void 0===r&&(r=!1);var o=a(t,e,n,r);return{conv0:o.conv0,conv1:o.conv1,conv2:o.conv2,conv3:i(e,e,n+"/conv3")}}}}function wv(e){return function(t){return{filters:e(t+"/filters",4),bias:e(t+"/bias",1)}}}function Cv(t,e){var n=yv(t,e),r=wv(n),o=gv(n);return{extractDenseBlock3Params:function(t,e){return void 0===e&&(e=!1),{conv0:e?r(t+"/conv0"):o(t+"/conv0"),conv1:o(t+"/conv1"),conv2:o(t+"/conv2")}},extractDenseBlock4Params:function(t,e){return void 0===e&&(e=!1),{conv0:e?r(t+"/conv0"):o(t+"/conv0"),conv1:o(t+"/conv1"),conv2:o(t+"/conv2"),conv3:o(t+"/conv3")}}}}var Ev,_v=(vp(Iv,Ev=av),Iv.prototype.forwardInput=function(e){var n=this.params;if(!n)throw new Error("FaceFeatureExtractor - load model before inference");return Je(function(){var t=lv(Jp(e.toBatchTensor(112,!0),[122.782,117.001,104.298]).div(Cn(255)),n.dense0,!0);return t=lv(t=lv(t=lv(t,n.dense1),n.dense2),n.dense3),t=Ac(t,[7,7],[2,2],"valid")})},Iv.prototype.forward=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},Iv.prototype.getDefaultModelName=function(){return"face_feature_extractor_model"},Iv.prototype.extractParamsFromWeigthMap=function(t){return function(t){var e=[],n=Cv(t,e).extractDenseBlock4Params,r={dense0:n("dense0",!0),dense1:n("dense1"),dense2:n("dense2"),dense3:n("dense3")};return fv(t,e),{params:r,paramMappings:e}}(t)},Iv.prototype.extractParams=function(t){return function(t){var e=[],n=xv(t),r=n.extractWeights,o=n.getRemainingWeights,i=bv(r,e).extractDenseBlock4Params,a=i(3,32,"dense0",!0),s=i(32,64,"dense1"),u=i(64,128,"dense2"),c=i(128,256,"dense3");if(0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{paramMappings:e,params:{dense0:a,dense1:s,dense2:u,dense3:c}}}(t)},Iv);function Iv(){return Ev.call(this,"FaceFeatureExtractor")||this}function Rv(t,e){return Je(function(){return bu(xc(t,e.weights),e.bias)})}function kv(e){var n={},r={};return Object.keys(e).forEach(function(t){(t.startsWith("fc")?r:n)[t]=e[t]}),{featureExtractorMap:n,classifierMap:r}}var Sv,Dv=(vp(Av,Sv=av),Object.defineProperty(Av.prototype,"faceFeatureExtractor",{get:function(){return this._faceFeatureExtractor},enumerable:!0,configurable:!0}),Av.prototype.runNet=function(e){var n=this,r=this.params;if(!r)throw new Error(this._name+" - load model before inference");return Je(function(){var t=e instanceof Jd?n.faceFeatureExtractor.forwardInput(e):e;return Rv(t.as2D(t.shape[0],-1),r.fc)})},Av.prototype.dispose=function(t){void 0===t&&(t=!0),this.faceFeatureExtractor.dispose(t),Sv.prototype.dispose.call(this,t)},Av.prototype.loadClassifierParams=function(t){var e=this.extractClassifierParams(t),n=e.params,r=e.paramMappings;this._params=n,this._paramMappings=r},Av.prototype.extractClassifierParams=function(t){return function(t,e,n){var r=[],o=xv(t),i=o.extractWeights,a=o.getRemainingWeights,s=dv(i,r)(e,n,"fc");if(0!==a().length)throw new Error("weights remaing after extract: "+a().length);return{paramMappings:r,params:{fc:s}}}(t,this.getClassifierChannelsIn(),this.getClassifierChannelsOut())},Av.prototype.extractParamsFromWeigthMap=function(t){var e=kv(t),n=e.featureExtractorMap,r=e.classifierMap;return this.faceFeatureExtractor.loadFromWeightMap(n),function(t){var e,n=[],r=yv(t,n),o={fc:(e="fc",{weights:r(e+"/weights",2),bias:r(e+"/bias",1)})};return fv(t,n),{params:o,paramMappings:n}}(r)},Av.prototype.extractParams=function(t){var e=this.getClassifierChannelsIn(),n=this.getClassifierChannelsOut(),r=n*e+n,o=t.slice(0,t.length-r),i=t.slice(t.length-r);return this.faceFeatureExtractor.extractWeights(o),this.extractClassifierParams(i)},Av);function Av(t,e){var n=Sv.call(this,t)||this;return n._faceFeatureExtractor=e,n}var Tv=["neutral","happy","sad","angry","fearful","disgusted","surprised"],Fv=(Nv.prototype.asSortedArray=function(){var e=this;return Tv.map(function(t){return{expression:t,probability:e[t]}}).sort(function(t,e){return e.probability-t.probability})},Nv);function Nv(n){var r=this;if(7!==n.length)throw new Error("FaceExpressions.constructor - expected probabilities.length to be 7, have: "+n.length);Tv.forEach(function(t,e){r[t]=n[e]})}var Mv,Ov=(vp(Pv,Mv=Dv),Pv.prototype.forwardInput=function(t){var e=this;return Je(function(){return Qr(e.runNet(t))})},Pv.prototype.forward=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},Pv.prototype.predictExpressions=function(a){return gp(this,void 0,void 0,function(){var e,n,r,o,i=this;return yp(this,function(t){switch(t.label){case 0:return[4,Zd(a)];case 1:return e=t.sent(),[4,this.forwardInput(e)];case 2:return n=t.sent(),[4,Promise.all(Fr(n).map(function(n){return gp(i,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return[4,n.data()];case 1:return e=t.sent(),n.dispose(),[2,e]}})})}))];case 3:return r=t.sent(),n.dispose(),o=r.map(function(t){return new Fv(t)}),[2,e.isBatchInput?o:o[0]]}})})},Pv.prototype.getDefaultModelName=function(){return"face_expression_model"},Pv.prototype.getClassifierChannelsIn=function(){return 256},Pv.prototype.getClassifierChannelsOut=function(){return 7},Pv);function Pv(t){return void 0===t&&(t=new _v),Mv.call(this,"FaceExpressionNet",t)||this}function Bv(t){return t.expressions instanceof Fv}function Lv(t,e){var n={expressions:e};return Object.assign({},t,n)}function Wv(t){return Cd(t)&&t.landmarks instanceof rd&&t.unshiftedLandmarks instanceof rd&&t.alignedRect instanceof jp}function zv(t,e){var n=t.detection.box,r=e.shiftBy(n.x,n.y),o=r.align(),i=t.detection.imageDims,a={landmarks:r,unshiftedLandmarks:e,alignedRect:new jp(t.detection.score,o.rescale(i.reverse()),i)};return Object.assign({},t,a)}var Uv=function(t){void 0===t&&(t={});var e=t.drawLines,n=void 0===e||e,r=t.drawPoints,o=void 0===r||r,i=t.lineWidth,a=t.lineColor,s=t.pointSize,u=t.pointColor;this.drawLines=n,this.drawPoints=o,this.lineWidth=i||1,this.pointSize=s||2,this.lineColor=a||"rgba(0, 255, 255, 1)",this.pointColor=u||"rgba(255, 0, 255, 1)"},Vv=(Gv.prototype.draw=function(t){var e=Od(t),n=this.options,r=n.drawLines,o=n.drawPoints,i=n.lineWidth,a=n.lineColor,s=n.pointSize,u=n.pointColor;r&&this.faceLandmarks instanceof cd&&(e.strokeStyle=a,e.lineWidth=i,pp(e,this.faceLandmarks.getJawOutline()),pp(e,this.faceLandmarks.getLeftEyeBrow()),pp(e,this.faceLandmarks.getRightEyeBrow()),pp(e,this.faceLandmarks.getNose()),pp(e,this.faceLandmarks.getLeftEye(),!0),pp(e,this.faceLandmarks.getRightEye(),!0),pp(e,this.faceLandmarks.getMouth(),!0)),o&&(e.strokeStyle=u,e.fillStyle=u,this.faceLandmarks.positions.forEach(function(t){e.beginPath(),e.arc(t.x,t.y,s,0,2*Math.PI),e.fill()}))},Gv);function Gv(t,e){void 0===e&&(e={}),this.faceLandmarks=t,this.options=new Uv(e)}var Hv=Object.freeze({__proto__:null,drawContour:pp,drawDetections:function(o,t){(Array.isArray(t)?t:[t]).forEach(function(t){var e=t instanceof jp?t.score:Cd(t)?t.detection.score:void 0,n=t instanceof jp?t.box:Cd(t)?t.detection.box:new Lp(t),r=e?""+Sp(e):void 0;new zd(n,{label:r}).draw(o)})},drawFaceExpressions:function(o,t,i,a){void 0===i&&(i=.1),(Array.isArray(t)?t:[t]).forEach(function(t){var e=t instanceof Fv?t:Bv(t)?t.expressions:void 0;if(!e)throw new Error("drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof");var n=e.asSortedArray().filter(function(t){return t.probability>i}),r=Cd(t)?t.detection.box.bottomLeft:a||new Pp(0,0);new Bd(n.map(function(t){return t.expression+" ("+Sp(t.probability)+")"}),r).draw(o)})},DrawBoxOptions:Wd,DrawBox:zd,DrawFaceLandmarksOptions:Uv,DrawFaceLandmarks:Vv,drawFaceLandmarks:function(n,t){(Array.isArray(t)?t:[t]).forEach(function(t){var e=t instanceof rd?t:Wv(t)?t.landmarks:void 0;if(!e)throw new Error("drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof");new Vv(e).draw(n)})},get AnchorPosition(){return Td},DrawTextFieldOptions:Pd,DrawTextField:Bd});function qv(t,e){var n=[],r=xv(t),o=r.extractWeights,i=r.getRemainingWeights,a=function(t,e){var r=pv(t,e),o=mv(t,e);return{extractConvParams:r,extractSeparableConvParams:o,extractReductionBlockParams:function(t,e,n){return{separable_conv0:o(t,e,n+"/separable_conv0"),separable_conv1:o(e,e,n+"/separable_conv1"),expansion_conv:r(t,e,1,n+"/expansion_conv")}},extractMainBlockParams:function(t,e){return{separable_conv0:o(t,t,e+"/separable_conv0"),separable_conv1:o(t,t,e+"/separable_conv1"),separable_conv2:o(t,t,e+"/separable_conv2")}}}}(o,n),s=a.extractConvParams,u=a.extractSeparableConvParams,c=a.extractReductionBlockParams,l=a.extractMainBlockParams,h={conv_in:s(3,32,3,"entry_flow/conv_in"),reduction_block_0:c(32,64,"entry_flow/reduction_block_0"),reduction_block_1:c(64,128,"entry_flow/reduction_block_1")},f={};Fp(e,0,1).forEach(function(t){f["main_block_"+t]=l(128,"middle_flow/main_block_"+t)});var p={reduction_block:c(128,256,"exit_flow/reduction_block"),separable_conv:u(256,512,"exit_flow/separable_conv")};if(0!==i().length)throw new Error("weights remaing after extract: "+i().length);return{paramMappings:n,params:{entry_flow:h,middle_flow:f,exit_flow:p}}}function jv(t,e){var n=[],r=function(t,e){var n=yv(t,e),r=wv(n),o=gv(n);return{extractConvParams:r,extractSeparableConvParams:o,extractReductionBlockParams:function(t){return{separable_conv0:o(t+"/separable_conv0"),separable_conv1:o(t+"/separable_conv1"),expansion_conv:r(t+"/expansion_conv")}},extractMainBlockParams:function(t){return{separable_conv0:o(t+"/separable_conv0"),separable_conv1:o(t+"/separable_conv1"),separable_conv2:o(t+"/separable_conv2")}}}}(t,n),o=r.extractConvParams,i=r.extractSeparableConvParams,a=r.extractReductionBlockParams,s=r.extractMainBlockParams,u={conv_in:o("entry_flow/conv_in"),reduction_block_0:a("entry_flow/reduction_block_0"),reduction_block_1:a("entry_flow/reduction_block_1")},c={};Fp(e,0,1).forEach(function(t){c["main_block_"+t]=s("middle_flow/main_block_"+t)});var l={reduction_block:a("exit_flow/reduction_block"),separable_conv:i("exit_flow/separable_conv")};return fv(t,n),{params:{entry_flow:u,middle_flow:c,exit_flow:l},paramMappings:n}}function Kv(t,e,n){return bu(cc(t,e.filters,n,"same"),e.bias)}function Xv(t,e,n){void 0===n&&(n=!0);var r=n?tl(t):t;return r=uv(r,e.separable_conv0,[1,1]),r=uv(tl(r),e.separable_conv1,[1,1]),r=Dc(r,[3,3],[2,2],"same"),r=bu(r,Kv(t,e.expansion_conv,[2,2]))}var $v,Yv,Jv=(vp(Qv,$v=av),Qv.prototype.forwardInput=function(n){var r=this,o=this.params;if(!o)throw new Error("TinyXception - load model before inference");return Je(function(){var t=Jp(n.toBatchTensor(112,!0),[122.782,117.001,104.298]).div(Cn(256)),e=tl(Kv(t,o.entry_flow.conv_in,[2,2]));return e=Xv(e=Xv(e,o.entry_flow.reduction_block_0,!1),o.entry_flow.reduction_block_1),Fp(r._numMainBlocks,0,1).forEach(function(t){e=function(t,e){var n=uv(tl(t),e.separable_conv0,[1,1]);return n=uv(tl(n),e.separable_conv1,[1,1]),n=uv(tl(n),e.separable_conv2,[1,1]),n=bu(n,t)}(e,o.middle_flow["main_block_"+t])}),e=Xv(e,o.exit_flow.reduction_block),e=tl(uv(e,o.exit_flow.separable_conv,[1,1]))})},Qv.prototype.forward=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},Qv.prototype.getDefaultModelName=function(){return"tiny_xception_model"},Qv.prototype.extractParamsFromWeigthMap=function(t){return jv(t,this._numMainBlocks)},Qv.prototype.extractParams=function(t){return qv(t,this._numMainBlocks)},Qv);function Qv(t){var e=$v.call(this,"TinyXception")||this;return e._numMainBlocks=t,e}(Yv=c.Gender||(c.Gender={})).FEMALE="female",Yv.MALE="male";var Zv,tm=(vp(em,Zv=av),Object.defineProperty(em.prototype,"faceFeatureExtractor",{get:function(){return this._faceFeatureExtractor},enumerable:!0,configurable:!0}),em.prototype.runNet=function(n){var r=this,o=this.params;if(!o)throw new Error(this._name+" - load model before inference");return Je(function(){var t=n instanceof Jd?r.faceFeatureExtractor.forwardInput(n):n,e=Ac(t,[7,7],[2,2],"valid").as2D(t.shape[0],-1);return{age:Rv(e,o.fc.age).as1D(),gender:Rv(e,o.fc.gender)}})},em.prototype.forwardInput=function(r){var o=this;return Je(function(){var t=o.runNet(r),e=t.age,n=t.gender;return{age:e,gender:Qr(n)}})},em.prototype.forward=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},em.prototype.predictAgeAndGender=function(s){return gp(this,void 0,void 0,function(){var e,n,r,o,i,a,u=this;return yp(this,function(t){switch(t.label){case 0:return[4,Zd(s)];case 1:return e=t.sent(),[4,this.forwardInput(e)];case 2:return n=t.sent(),r=Fr(n.age),o=Fr(n.gender),i=r.map(function(t,e){return{ageTensor:t,genderTensor:o[e]}}),[4,Promise.all(i.map(function(t){var a=t.ageTensor,s=t.genderTensor;return gp(u,void 0,void 0,function(){var e,n,r,o,i;return yp(this,function(t){switch(t.label){case 0:return[4,a.data()];case 1:return e=t.sent()[0],[4,s.data()];case 2:return n=t.sent()[0],o=(r=.5<n)?c.Gender.MALE:c.Gender.FEMALE,i=r?n:1-n,a.dispose(),s.dispose(),[2,{age:e,gender:o,genderProbability:i}]}})})}))];case 3:return a=t.sent(),n.age.dispose(),n.gender.dispose(),[2,e.isBatchInput?a:a[0]]}})})},em.prototype.getDefaultModelName=function(){return"age_gender_model"},em.prototype.dispose=function(t){void 0===t&&(t=!0),this.faceFeatureExtractor.dispose(t),Zv.prototype.dispose.call(this,t)},em.prototype.loadClassifierParams=function(t){var e=this.extractClassifierParams(t),n=e.params,r=e.paramMappings;this._params=n,this._paramMappings=r},em.prototype.extractClassifierParams=function(t){return function(t){var e=[],n=xv(t),r=n.extractWeights,o=n.getRemainingWeights,i=dv(r,e),a=i(512,1,"fc/age"),s=i(512,2,"fc/gender");if(0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{paramMappings:e,params:{fc:{age:a,gender:s}}}}(t)},em.prototype.extractParamsFromWeigthMap=function(t){var e=kv(t),n=e.featureExtractorMap,r=e.classifierMap;return this.faceFeatureExtractor.loadFromWeightMap(n),function(t){var e=[],n=yv(t,e);function r(t){return{weights:n(t+"/weights",2),bias:n(t+"/bias",1)}}var o={fc:{age:r("fc/age"),gender:r("fc/gender")}};return fv(t,e),{params:o,paramMappings:e}}(r)},em.prototype.extractParams=function(t){var e=t.slice(0,t.length-1539),n=t.slice(t.length-1539);return this.faceFeatureExtractor.extractWeights(e),this.extractClassifierParams(n)},em);function em(t){void 0===t&&(t=new Jv(2));var e=Zv.call(this,"AgeGenderNet")||this;return e._faceFeatureExtractor=t,e}var nm,rm=(vp(om,nm=Dv),om.prototype.postProcess=function(t,o,e){var i=e.map(function(t){var e=t.width,n=t.height,r=o/Math.max(n,e);return{width:e*r,height:n*r}}),a=i.length;return Je(function(){function n(t,e){return Dr([Fn([68],t),Fn([68],e)],1).as2D(1,136).as1D()}function r(t,e){var n=i[t],r=n.width,o=n.height;return e(r,o)?Math.abs(r-o)/2:0}return t.mul(Fn([a,136],o)).sub(Dr(Array.from(Array(a),function(t,e){return n(function(t){return r(t,function(t,e){return t<e})}(e),function(t){return r(t,function(t,e){return e<t})}(e))}))).div(Dr(Array.from(Array(a),function(t,e){return n(i[e].width,i[e].height)})))})},om.prototype.forwardInput=function(e){var n=this;return Je(function(){var t=n.runNet(e);return n.postProcess(t,e.inputSize,e.inputDimensions.map(function(t){return{height:t[0],width:t[1]}}))})},om.prototype.forward=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},om.prototype.detectLandmarks=function(o){return gp(this,void 0,void 0,function(){var u,e,n,r=this;return yp(this,function(t){switch(t.label){case 0:return[4,Zd(o)];case 1:return u=t.sent(),e=Je(function(){return Fr(r.forwardInput(u))}),[4,Promise.all(e.map(function(a,s){return gp(r,void 0,void 0,function(){var e,n,r,o,i;return yp(this,function(t){switch(t.label){case 0:return r=(n=Array).from,[4,a.data()];case 1:return e=r.apply(n,[t.sent()]),o=e.filter(function(t,e){return kp(e)}),i=e.filter(function(t,e){return!kp(e)}),[2,new cd(Array(68).fill(0).map(function(t,e){return new Pp(o[e],i[e])}),{height:u.getInputHeight(s),width:u.getInputWidth(s)})]}})})}))];case 2:return n=t.sent(),e.forEach(function(t){return t.dispose()}),[2,u.isBatchInput?n:n[0]]}})})},om.prototype.getClassifierChannelsOut=function(){return 136},om);function om(){return null!==nm&&nm.apply(this,arguments)||this}var im,am=(vp(sm,im=rm),sm.prototype.getDefaultModelName=function(){return"face_landmark_68_model"},sm.prototype.getClassifierChannelsIn=function(){return 256},sm);function sm(t){return void 0===t&&(t=new _v),im.call(this,"FaceLandmark68Net",t)||this}var um,cm=(vp(lm,um=av),lm.prototype.forwardInput=function(e){var n=this.params;if(!n)throw new Error("TinyFaceFeatureExtractor - load model before inference");return Je(function(){var t=cv(Jp(e.toBatchTensor(112,!0),[122.782,117.001,104.298]).div(Cn(255)),n.dense0,!0);return t=cv(t=cv(t,n.dense1),n.dense2),t=Ac(t,[14,14],[2,2],"valid")})},lm.prototype.forward=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},lm.prototype.getDefaultModelName=function(){return"face_feature_extractor_tiny_model"},lm.prototype.extractParamsFromWeigthMap=function(t){return function(t){var e=[],n=Cv(t,e).extractDenseBlock3Params,r={dense0:n("dense0",!0),dense1:n("dense1"),dense2:n("dense2")};return fv(t,e),{params:r,paramMappings:e}}(t)},lm.prototype.extractParams=function(t){return function(t){var e=[],n=xv(t),r=n.extractWeights,o=n.getRemainingWeights,i=bv(r,e).extractDenseBlock3Params,a=i(3,32,"dense0",!0),s=i(32,64,"dense1"),u=i(64,128,"dense2");if(0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{paramMappings:e,params:{dense0:a,dense1:s,dense2:u}}}(t)},lm);function lm(){return um.call(this,"TinyFaceFeatureExtractor")||this}var hm,fm=(vp(pm,hm=rm),pm.prototype.getDefaultModelName=function(){return"face_landmark_68_tiny_model"},pm.prototype.getClassifierChannelsIn=function(){return 128},pm);function pm(t){return void 0===t&&(t=new cm),hm.call(this,"FaceLandmark68TinyNet",t)||this}var dm,vm=(vp(mm,dm=am),mm);function mm(){return null!==dm&&dm.apply(this,arguments)||this}function gm(t,e,n,r,o){void 0===o&&(o="same");var i=e.conv,a=i.filters,s=i.bias,u=cc(t,a,n,o);return u=function(t,e){return bu(Mu(t,e.weights),e.biases)}(u=bu(u,s),e.scale),r?tl(u):u}function ym(t,e){return gm(t,e,[1,1],!1)}function xm(t,e){return gm(t,e,[2,2],!0,"valid")}function bm(a,s){function o(t,e,n,r){var o=function(t,e,n){var r=a(t),o=r.length/(e*n*n);if(Rp(o))throw new Error("depth has to be an integer: "+o+", weights.length: "+r.length+", numFilters: "+e+", filterSize: "+n);return Je(function(){return rl(Rn(r,[e,o,n,n]),[2,3,1,0])})}(t,e,n),i=En(a(e));return s.push({paramPath:r+"/filters"},{paramPath:r+"/bias"}),{filters:o,bias:i}}function i(t,e,n,r){return{conv:o(t,e,n,r+"/conv"),scale:function(t,e){var n=En(a(t)),r=En(a(t));return s.push({paramPath:e+"/weights"},{paramPath:e+"/biases"}),{weights:n,biases:r}}(e,r+"/scale")}}return{extractConvLayerParams:i,extractResidualLayerParams:function(t,e,n,r,o){return void 0===o&&(o=!1),{conv1:i((o?.5:1)*t,e,n,r+"/conv1"),conv2:i(t,e,n,r+"/conv2")}}}}function wm(t,e){var n=yv(t,e);function r(t){return{conv:{filters:n(t+"/conv/filters",4),bias:n(t+"/conv/bias",1)},scale:function(t){return{weights:n(t+"/scale/weights",1),biases:n(t+"/scale/biases",1)}}(t)}}return{extractConvLayerParams:r,extractResidualLayerParams:function(t){return{conv1:r(t+"/conv1"),conv2:r(t+"/conv2")}}}}function Cm(t,e){var n=function(t,e){return gm(t,e,[1,1],!0)}(t,e.conv1);return n=ym(n,e.conv2),n=bu(n,t),n=tl(n)}function Em(t,e){var n=xm(t,e.conv1);n=ym(n,e.conv2);var r=Ac(t,2,2,"valid"),o=Tn(r.shape),i=r.shape[3]!==n.shape[3];if(r.shape[1]!==n.shape[1]||r.shape[2]!==n.shape[2]){var a=xp(n.shape);a[1]=1;var s=Tn(a),u=xp((n=Bn([n,s],1)).shape);u[2]=1;var c=Tn(u);n=Bn([n,c],2)}return r=i?Bn([r,o],3):r,n=bu(r,n),n=tl(n)}var _m,Im=(vp(Rm,_m=av),Rm.prototype.forwardInput=function(n){var r=this.params;if(!r)throw new Error("FaceRecognitionNet - load model before inference");return Je(function(){var t=xm(Jp(n.toBatchTensor(150,!0).toFloat(),[122.782,117.001,104.298]).div(Cn(256)),r.conv32_down),e=(t=Em(t=Cm(t=Cm(t=Em(t=Cm(t=Cm(t=Em(t=Cm(t=Cm(t=Cm(t=Em(t=Cm(t=Cm(t=Cm(t=Dc(t,3,2,"valid"),r.conv32_1),r.conv32_2),r.conv32_3),r.conv64_down),r.conv64_1),r.conv64_2),r.conv64_3),r.conv128_down),r.conv128_1),r.conv128_2),r.conv256_down),r.conv256_1),r.conv256_2),r.conv256_down_out)).mean([1,2]);return xc(e,r.fc)})},Rm.prototype.forward=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},Rm.prototype.computeFaceDescriptor=function(i){return gp(this,void 0,void 0,function(){var e,n,r,o=this;return yp(this,function(t){switch(t.label){case 0:return[4,Zd(i)];case 1:return e=t.sent(),n=Je(function(){return Fr(o.forwardInput(e))}),[4,Promise.all(n.map(function(t){return t.data()}))];case 2:return r=t.sent(),n.forEach(function(t){return t.dispose()}),[2,e.isBatchInput?r:r[0]]}})})},Rm.prototype.getDefaultModelName=function(){return"face_recognition_model"},Rm.prototype.extractParamsFromWeigthMap=function(t){return function(t){var e=[],n=wm(t,e),r=n.extractConvLayerParams,o=n.extractResidualLayerParams,i=r("conv32_down"),a=o("conv32_1"),s=o("conv32_2"),u=o("conv32_3"),c=o("conv64_down"),l=o("conv64_1"),h=o("conv64_2"),f=o("conv64_3"),p=o("conv128_down"),d=o("conv128_1"),v=o("conv128_2"),m=o("conv256_down"),g=o("conv256_1"),y=o("conv256_2"),x=o("conv256_down_out"),b=t.fc;if(e.push({originalPath:"fc",paramPath:"fc"}),!Ep(b))throw new Error("expected weightMap[fc] to be a Tensor2D, instead have "+b);var w={conv32_down:i,conv32_1:a,conv32_2:s,conv32_3:u,conv64_down:c,conv64_1:l,conv64_2:h,conv64_3:f,conv128_down:p,conv128_1:d,conv128_2:v,conv256_down:m,conv256_1:g,conv256_2:y,conv256_down_out:x,fc:b};return fv(t,e),{params:w,paramMappings:e}}(t)},Rm.prototype.extractParams=function(t){return function(t){var e=xv(t),n=e.extractWeights,r=e.getRemainingWeights,o=[],i=bm(n,o),a=i.extractConvLayerParams,s=i.extractResidualLayerParams,u=a(4704,32,7,"conv32_down"),c=s(9216,32,3,"conv32_1"),l=s(9216,32,3,"conv32_2"),h=s(9216,32,3,"conv32_3"),f=s(36864,64,3,"conv64_down",!0),p=s(36864,64,3,"conv64_1"),d=s(36864,64,3,"conv64_2"),v=s(36864,64,3,"conv64_3"),m=s(147456,128,3,"conv128_down",!0),g=s(147456,128,3,"conv128_1"),y=s(147456,128,3,"conv128_2"),x=s(589824,256,3,"conv256_down",!0),b=s(589824,256,3,"conv256_1"),w=s(589824,256,3,"conv256_2"),C=s(589824,256,3,"conv256_down_out"),E=Je(function(){return rl(_n(n(32768),[128,256]),[1,0])});if(o.push({paramPath:"fc"}),0!==r().length)throw new Error("weights remaing after extract: "+r().length);return{params:{conv32_down:u,conv32_1:c,conv32_2:l,conv32_3:h,conv64_down:f,conv64_1:p,conv64_2:d,conv64_3:v,conv128_down:m,conv128_1:g,conv128_2:y,conv256_down:x,conv256_1:b,conv256_2:w,conv256_down_out:C,fc:E},paramMappings:o}}(t)},Rm);function Rm(){return _m.call(this,"FaceRecognitionNet")||this}function km(t,e){var n={descriptor:e};return Object.assign({},t,n)}function Sm(t,e){var n={age:e};return Object.assign({},t,n)}function Dm(t,e,n){var r={gender:e,genderProbability:n};return Object.assign({},t,r)}var Am=(Object.defineProperty(Tm.prototype,"minFaceSize",{get:function(){return this._minFaceSize},enumerable:!0,configurable:!0}),Object.defineProperty(Tm.prototype,"scaleFactor",{get:function(){return this._scaleFactor},enumerable:!0,configurable:!0}),Object.defineProperty(Tm.prototype,"maxNumScales",{get:function(){return this._maxNumScales},enumerable:!0,configurable:!0}),Object.defineProperty(Tm.prototype,"scoreThresholds",{get:function(){return this._scoreThresholds},enumerable:!0,configurable:!0}),Object.defineProperty(Tm.prototype,"scaleSteps",{get:function(){return this._scaleSteps},enumerable:!0,configurable:!0}),Tm);function Tm(t){var e=void 0===t?{}:t,n=e.minFaceSize,r=e.scaleFactor,o=e.maxNumScales,i=e.scoreThresholds,a=e.scaleSteps;if(this._name="MtcnnOptions",this._minFaceSize=n||20,this._scaleFactor=r||.709,this._maxNumScales=o||10,this._scoreThresholds=i||[.6,.7,.7],this._scaleSteps=a,"number"!=typeof this._minFaceSize||this._minFaceSize<0)throw new Error(this._name+" - expected minFaceSize to be a number > 0");if("number"!=typeof this._scaleFactor||this._scaleFactor<=0||1<=this._scaleFactor)throw new Error(this._name+" - expected scaleFactor to be a number between 0 and 1");if("number"!=typeof this._maxNumScales||this._maxNumScales<0)throw new Error(this._name+" - expected maxNumScales to be a number > 0");if(!Array.isArray(this._scoreThresholds)||3!==this._scoreThresholds.length||this._scoreThresholds.some(function(t){return"number"!=typeof t}))throw new Error(this._name+" - expected scoreThresholds to be an array of numbers of length 3");if(this._scaleSteps&&(!Array.isArray(this._scaleSteps)||this._scaleSteps.some(function(t){return"number"!=typeof t})))throw new Error(this._name+" - expected scaleSteps to be an array of numbers")}function Fm(s,u){function i(t,e,n,r,o){var i=Rn(s(t*e*n*n),[n,n,t,e]),a=En(s(e));return u.push({paramPath:r+"/filters"},{paramPath:r+"/"+(o?"batch_norm_offset":"bias")}),{filters:i,bias:a}}function r(t,e,n,r){var o=i(t,e,n,r,!0);return{filters:o.filters,batch_norm_offset:o.bias}}function t(t,e,n){return{depthwise_conv:function(t,e){var n=Rn(s(9*t),[3,3,t,1]),r=En(s(t)),o=En(s(t)),i=En(s(t)),a=En(s(t));return u.push({paramPath:e+"/filters"},{paramPath:e+"/batch_norm_scale"},{paramPath:e+"/batch_norm_offset"},{paramPath:e+"/batch_norm_mean"},{paramPath:e+"/batch_norm_variance"}),{filters:n,batch_norm_scale:r,batch_norm_offset:o,batch_norm_mean:i,batch_norm_variance:a}}(t,n+"/depthwise_conv"),pointwise_conv:r(t,e,1,n+"/pointwise_conv")}}return{extractMobilenetV1Params:function(){return{conv_0:r(3,32,3,"mobilenetv1/conv_0"),conv_1:t(32,64,"mobilenetv1/conv_1"),conv_2:t(64,128,"mobilenetv1/conv_2"),conv_3:t(128,128,"mobilenetv1/conv_3"),conv_4:t(128,256,"mobilenetv1/conv_4"),conv_5:t(256,256,"mobilenetv1/conv_5"),conv_6:t(256,512,"mobilenetv1/conv_6"),conv_7:t(512,512,"mobilenetv1/conv_7"),conv_8:t(512,512,"mobilenetv1/conv_8"),conv_9:t(512,512,"mobilenetv1/conv_9"),conv_10:t(512,512,"mobilenetv1/conv_10"),conv_11:t(512,512,"mobilenetv1/conv_11"),conv_12:t(512,1024,"mobilenetv1/conv_12"),conv_13:t(1024,1024,"mobilenetv1/conv_13")}},extractPredictionLayerParams:function(){return{conv_0:r(1024,256,1,"prediction_layer/conv_0"),conv_1:r(256,512,3,"prediction_layer/conv_1"),conv_2:r(512,128,1,"prediction_layer/conv_2"),conv_3:r(128,256,3,"prediction_layer/conv_3"),conv_4:r(256,128,1,"prediction_layer/conv_4"),conv_5:r(128,256,3,"prediction_layer/conv_5"),conv_6:r(256,64,1,"prediction_layer/conv_6"),conv_7:r(64,128,3,"prediction_layer/conv_7"),box_predictor_0:{box_encoding_predictor:i(512,12,1,"prediction_layer/box_predictor_0/box_encoding_predictor"),class_predictor:i(512,9,1,"prediction_layer/box_predictor_0/class_predictor")},box_predictor_1:{box_encoding_predictor:i(1024,24,1,"prediction_layer/box_predictor_1/box_encoding_predictor"),class_predictor:i(1024,18,1,"prediction_layer/box_predictor_1/class_predictor")},box_predictor_2:{box_encoding_predictor:i(512,24,1,"prediction_layer/box_predictor_2/box_encoding_predictor"),class_predictor:i(512,18,1,"prediction_layer/box_predictor_2/class_predictor")},box_predictor_3:{box_encoding_predictor:i(256,24,1,"prediction_layer/box_predictor_3/box_encoding_predictor"),class_predictor:i(256,18,1,"prediction_layer/box_predictor_3/class_predictor")},box_predictor_4:{box_encoding_predictor:i(256,24,1,"prediction_layer/box_predictor_4/box_encoding_predictor"),class_predictor:i(256,18,1,"prediction_layer/box_predictor_4/class_predictor")},box_predictor_5:{box_encoding_predictor:i(128,24,1,"prediction_layer/box_predictor_5/box_encoding_predictor"),class_predictor:i(128,18,1,"prediction_layer/box_predictor_5/class_predictor")}}}}}function Nm(t){var e=[],n=function(t,e){var i=yv(t,e);function a(t,e,n){return{filters:i(t+"/Conv2d_"+e+"_pointwise/weights",4,n+"/filters"),batch_norm_offset:i(t+"/Conv2d_"+e+"_pointwise/convolution_bn_offset",1,n+"/batch_norm_offset")}}function n(t){var e="mobilenetv1/conv_"+t,n="MobilenetV1/Conv2d_"+t+"_depthwise",r=e+"/depthwise_conv",o=e+"/pointwise_conv";return{depthwise_conv:{filters:i(n+"/depthwise_weights",4,r+"/filters"),batch_norm_scale:i(n+"/BatchNorm/gamma",1,r+"/batch_norm_scale"),batch_norm_offset:i(n+"/BatchNorm/beta",1,r+"/batch_norm_offset"),batch_norm_mean:i(n+"/BatchNorm/moving_mean",1,r+"/batch_norm_mean"),batch_norm_variance:i(n+"/BatchNorm/moving_variance",1,r+"/batch_norm_variance")},pointwise_conv:a("MobilenetV1",t,o)}}function r(t,e){return{filters:i(t+"/weights",4,e+"/filters"),bias:i(t+"/biases",1,e+"/bias")}}function o(t){return{box_encoding_predictor:r("Prediction/BoxPredictor_"+t+"/BoxEncodingPredictor","prediction_layer/box_predictor_"+t+"/box_encoding_predictor"),class_predictor:r("Prediction/BoxPredictor_"+t+"/ClassPredictor","prediction_layer/box_predictor_"+t+"/class_predictor")}}return{extractMobilenetV1Params:function(){return{conv_0:a("MobilenetV1",0,"mobilenetv1/conv_0"),conv_1:n(1),conv_2:n(2),conv_3:n(3),conv_4:n(4),conv_5:n(5),conv_6:n(6),conv_7:n(7),conv_8:n(8),conv_9:n(9),conv_10:n(10),conv_11:n(11),conv_12:n(12),conv_13:n(13)}},extractPredictionLayerParams:function(){return{conv_0:a("Prediction",0,"prediction_layer/conv_0"),conv_1:a("Prediction",1,"prediction_layer/conv_1"),conv_2:a("Prediction",2,"prediction_layer/conv_2"),conv_3:a("Prediction",3,"prediction_layer/conv_3"),conv_4:a("Prediction",4,"prediction_layer/conv_4"),conv_5:a("Prediction",5,"prediction_layer/conv_5"),conv_6:a("Prediction",6,"prediction_layer/conv_6"),conv_7:a("Prediction",7,"prediction_layer/conv_7"),box_predictor_0:o(0),box_predictor_1:o(1),box_predictor_2:o(2),box_predictor_3:o(3),box_predictor_4:o(4),box_predictor_5:o(5)}}}}(t,e),r=n.extractMobilenetV1Params,o=n.extractPredictionLayerParams,i=t["Output/extra_dim"];if(e.push({originalPath:"Output/extra_dim",paramPath:"output_layer/extra_dim"}),!_p(i))throw new Error("expected weightMap['Output/extra_dim'] to be a Tensor3D, instead have "+i);var a={mobilenetv1:r(),prediction_layer:o(),output_layer:{extra_dim:i}};return fv(t,e),{params:a,paramMappings:e}}function Mm(e,n,r){return Je(function(){var t=cc(e,n.filters,r,"same");return t=bu(t,n.batch_norm_offset),Ss(t,0,6)})}var Om=.0010000000474974513;function Pm(t,e){return Je(function(){var o=null,i=Mm(t,e.conv_0,[2,2]);if([e.conv_1,e.conv_2,e.conv_3,e.conv_4,e.conv_5,e.conv_6,e.conv_7,e.conv_8,e.conv_9,e.conv_10,e.conv_11,e.conv_12,e.conv_13].forEach(function(t,e){var n=e+1,r=function(e){return[2,4,6,12].some(function(t){return t===e})?[2,2]:[1,1]}(n);i=Mm(i=function(e,n,r){return Je(function(){var t=pc(e,n.filters,r,"same");return t=hu(t,n.batch_norm_mean,n.batch_norm_variance,n.batch_norm_offset,n.batch_norm_scale,Om),Ss(t,0,6)})}(i,t.depthwise_conv,r),t.pointwise_conv,[1,1]),11===n&&(o=i)}),null===o)throw new Error("mobileNetV1 - output of conv layer 11 is null");return{out:i,conv11:o}})}function Bm(t,e,n){var r=t.arraySync(),o=Math.min(r[e][0],r[e][2]),i=Math.min(r[e][1],r[e][3]),a=Math.max(r[e][0],r[e][2]),s=Math.max(r[e][1],r[e][3]),u=Math.min(r[n][0],r[n][2]),c=Math.min(r[n][1],r[n][3]),l=Math.max(r[n][0],r[n][2]),h=Math.max(r[n][1],r[n][3]),f=(a-o)*(s-i),p=(l-u)*(h-c);if(f<=0||p<=0)return 0;var d=Math.max(o,u),v=Math.max(i,c),m=Math.min(a,l),g=Math.min(s,h),y=Math.max(m-d,0)*Math.max(g-v,0);return y/(f+p-y)}function Lm(t,e){var n=function(t){var e=Fr(rl(t,[1,0])),n=[zu(e[2],e[0]),zu(e[3],e[1])];return{sizes:n,centers:[bu(e[0],_u(n[0],Cn(2))),bu(e[1],_u(n[1],Cn(2)))]}}(t),r=n.sizes,o=n.centers,i=Fr(rl(e,[1,0])),a=_u(Mu(Fs(_u(i[2],Cn(5))),r[0]),Cn(2)),s=bu(Mu(_u(i[0],Cn(10)),r[0]),o[0]),u=_u(Mu(Fs(_u(i[3],Cn(5))),r[1]),Cn(2)),c=bu(Mu(_u(i[1],Cn(10)),r[1]),o[1]);return rl(Dr([zu(s,a),zu(c,u),bu(s,a),bu(c,u)]),[1,0])}function Wm(e,n){return Je(function(){var t=e.shape[0];return{boxPredictionEncoding:Rr(hv(e,n.box_encoding_predictor),[t,-1,1,4]),classPrediction:Rr(hv(e,n.class_predictor),[t,-1,3])}})}var zm=(Object.defineProperty(Um.prototype,"minConfidence",{get:function(){return this._minConfidence},enumerable:!0,configurable:!0}),Object.defineProperty(Um.prototype,"maxResults",{get:function(){return this._maxResults},enumerable:!0,configurable:!0}),Um);function Um(t){var e=void 0===t?{}:t,n=e.minConfidence,r=e.maxResults;if(this._name="SsdMobilenetv1Options",this._minConfidence=n||.5,this._maxResults=r||100,"number"!=typeof this._minConfidence||this._minConfidence<=0||1<=this._minConfidence)throw new Error(this._name+" - expected minConfidence to be a number between 0 and 1");if("number"!=typeof this._maxResults)throw new Error(this._name+" - expected maxResults to be a number")}var Vm,Gm=(vp(Hm,Vm=av),Hm.prototype.forwardInput=function(r){var o=this.params;if(!o)throw new Error("SsdMobilenetv1 - load model before inference");return Je(function(){var t=r.toBatchTensor(512,!1).toFloat(),e=Pm(zu(Mu(t,Cn(.007843137718737125)),Cn(1)),o.mobilenetv1),n=function(l,h,f){return Je(function(){var t=Mm(Mm(l,f.conv_0,[1,1]),f.conv_1,[2,2]),e=Mm(Mm(t,f.conv_2,[1,1]),f.conv_3,[2,2]),n=Mm(Mm(e,f.conv_4,[1,1]),f.conv_5,[2,2]),r=Mm(Mm(n,f.conv_6,[1,1]),f.conv_7,[2,2]),o=Wm(h,f.box_predictor_0),i=Wm(l,f.box_predictor_1),a=Wm(t,f.box_predictor_2),s=Wm(e,f.box_predictor_3),u=Wm(n,f.box_predictor_4),c=Wm(r,f.box_predictor_5);return{boxPredictions:Bn([o.boxPredictionEncoding,i.boxPredictionEncoding,a.boxPredictionEncoding,s.boxPredictionEncoding,u.boxPredictionEncoding,c.boxPredictionEncoding],1),classPredictions:Bn([o.classPrediction,i.classPrediction,a.classPrediction,s.classPrediction,u.classPrediction,c.classPrediction],1)}})}(e.out,e.conv11,o.prediction_layer);return function(o,i,a){return Je(function(){var t=o.shape[0],e=Lm(Rr(Ar(a.extra_dim,[t,1,1]),[-1,4]),Rr(o,[-1,4]));e=Rr(e,[t,e.shape[0]/t,4]);var n=Vs(Mc(i,[0,0,1],[-1,-1,-1])),r=Mc(n,[0,0,0],[-1,-1,1]);return r=Rr(r,[t,r.shape[1]]),{boxes:Fr(e),scores:Fr(r)}})}(n.boxPredictions,n.classPredictions,o.output_layer)})},Hm.prototype.forward=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},Hm.prototype.locateFaces=function(w,C){return void 0===C&&(C={}),gp(this,void 0,void 0,function(){var e,n,r,s,o,i,a,u,c,l,h,f,p,d,v,m,g,y,x,b;return yp(this,function(t){switch(t.label){case 0:return e=new zm(C),n=e.maxResults,r=e.minConfidence,[4,Zd(w)];case 1:for(s=t.sent(),o=this.forwardInput(s),i=o.boxes,a=o.scores,u=i[0],c=a[0],l=1;l<i.length;l++)i[l].dispose(),a[l].dispose();return p=(f=Array).from,[4,c.data()];case 2:return h=p.apply(f,[t.sent()]),d=function(o,t,e,i,a){var n=o.shape[0],s=Math.min(e,n),r=t.map(function(t,e){return{score:t,boxIndex:e}}).filter(function(t){return t.score>a}).sort(function(t,e){return e.score-t.score}),u=[];return r.forEach(function(t){if(!(u.length>=s)){for(var e=t.score,n=u.length-1;0<=n;--n){var r=Bm(o,t.boxIndex,u[n]);if(0!==r&&(t.score*=r<=i?1:0,t.score<=a))break}e===t.score&&u.push(t.boxIndex)}}),u}(u,h,n,.5,r),v=s.getReshapedInputDimensions(0),m=s.inputSize,g=m/v.width,y=m/v.height,x=u.arraySync(),b=d.map(function(t){var e=[Math.max(0,x[t][0]),Math.min(1,x[t][2])].map(function(t){return t*y}),n=e[0],r=e[1],o=[Math.max(0,x[t][1]),Math.min(1,x[t][3])].map(function(t){return t*g}),i=o[0],a=o[1];return new jp(h[t],new ed(i,n,a-i,r-n),{height:s.getInputHeight(0),width:s.getInputWidth(0)})}),u.dispose(),c.dispose(),[2,b]}})})},Hm.prototype.getDefaultModelName=function(){return"ssd_mobilenetv1_model"},Hm.prototype.extractParamsFromWeigthMap=function(t){return Nm(t)},Hm.prototype.extractParams=function(t){return function(t){var e=[],n=xv(t),r=n.extractWeights,o=n.getRemainingWeights,i=Fm(r,e),a=i.extractMobilenetV1Params,s=i.extractPredictionLayerParams,u=a(),c=s(),l={extra_dim:In(r(20472),[1,5118,4])};if(e.push({paramPath:"output_layer/extra_dim"}),0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{params:{mobilenetv1:u,prediction_layer:c,output_layer:l},paramMappings:e}}(t)},Hm);function Hm(){return Vm.call(this,"SsdMobilenetv1")||this}function qm(t){var e=new Gm;return e.extractWeights(t),e}var jm,Km=(vp(Xm,jm=Gm),Xm);function Xm(){return null!==jm&&jm.apply(this,arguments)||this}var $m,Ym=[new Pp(.738768,.874946),new Pp(2.42204,2.65704),new Pp(4.30971,7.04493),new Pp(10.246,4.59428),new Pp(12.6868,11.8741)],Jm=[new Pp(1.603231,2.094468),new Pp(6.041143,7.080126),new Pp(2.882459,3.518061),new Pp(4.266906,5.178857),new Pp(9.041765,10.66308)],Qm=[117.001,114.697,97.404],Zm=function(t){return"number"==typeof t};function tg(t){if(!t)throw new Error("invalid config: "+t);if("boolean"!=typeof t.withSeparableConvs)throw new Error("config.withSeparableConvs has to be a boolean, have: "+t.withSeparableConvs);if(!Zm(t.iouThreshold)||t.iouThreshold<0||1<t.iouThreshold)throw new Error("config.iouThreshold has to be a number between [0, 1], have: "+t.iouThreshold);if(!Array.isArray(t.classes)||!t.classes.length||!t.classes.every(function(t){return"string"==typeof t}))throw new Error("config.classes has to be an array class names: string[], have: "+JSON.stringify(t.classes));if(!Array.isArray(t.anchors)||!t.anchors.length||!t.anchors.map(function(t){return t||{}}).every(function(t){return Zm(t.x)&&Zm(t.y)}))throw new Error("config.anchors has to be an array of { x: number, y: number }, have: "+JSON.stringify(t.anchors));if(t.meanRgb&&(!Array.isArray(t.meanRgb)||3!==t.meanRgb.length||!t.meanRgb.every(Zm)))throw new Error("config.meanRgb has to be an array of shape [number, number, number], have: "+JSON.stringify(t.meanRgb))}function eg(e){return Je(function(){var t=Mu(e,Cn(.10000000149011612));return bu(tl(zu(e,t)),t)})}function ng(e,n){return Je(function(){var t=gr(e,[[0,0],[1,1],[1,1],[0,0]]);return t=cc(t,n.conv.filters,[1,1],"valid"),t=zu(t,n.bn.sub),t=Mu(t,n.bn.truediv),eg(t=bu(t,n.conv.bias))})}function rg(e,n){return Je(function(){var t=gr(e,[[0,0],[1,1],[1,1],[0,0]]);return t=mc(t,n.depthwise_filter,n.pointwise_filter,[1,1],"valid"),eg(t=bu(t,n.bias))})}function og(o,i){var r=pv(o,i);var t=mv(o,i);return{extractConvParams:r,extractConvWithBatchNormParams:function(t,e,n){return{conv:r(t,e,3,n+"/conv"),bn:function(t,e){var n=En(o(t)),r=En(o(t));return i.push({paramPath:e+"/sub"},{paramPath:e+"/truediv"}),{sub:n,truediv:r}}(e,n+"/bn")}},extractSeparableConvParams:t}}function ig(t,e){var n=yv(t,e);function r(t){return{filters:n(t+"/filters",4),bias:n(t+"/bias",1)}}return{extractConvParams:r,extractConvWithBatchNormParams:function(t){return{conv:r(t+"/conv"),bn:function(t){return{sub:n(t+"/sub",1),truediv:n(t+"/truediv",1)}}(t+"/bn")}},extractSeparableConvParams:gv(n)}}($m=c.TinyYolov2SizeType||(c.TinyYolov2SizeType={}))[$m.XS=224]="XS",$m[$m.SM=320]="SM",$m[$m.MD=416]="MD",$m[$m.LG=608]="LG";var ag=(Object.defineProperty(sg.prototype,"inputSize",{get:function(){return this._inputSize},enumerable:!0,configurable:!0}),Object.defineProperty(sg.prototype,"scoreThreshold",{get:function(){return this._scoreThreshold},enumerable:!0,configurable:!0}),sg);function sg(t){var e=void 0===t?{}:t,n=e.inputSize,r=e.scoreThreshold;if(this._name="TinyYolov2Options",this._inputSize=n||416,this._scoreThreshold=r||.5,"number"!=typeof this._inputSize||this._inputSize%32!=0)throw new Error(this._name+" - expected inputSize to be a number divisible by 32");if("number"!=typeof this._scoreThreshold||this._scoreThreshold<=0||1<=this._scoreThreshold)throw new Error(this._name+" - expected scoreThreshold to be a number between 0 and 1")}var ug,cg=(vp(lg,ug=av),Object.defineProperty(lg.prototype,"config",{get:function(){return this._config},enumerable:!0,configurable:!0}),Object.defineProperty(lg.prototype,"withClassScores",{get:function(){return this.config.withClassScores||1<this.config.classes.length},enumerable:!0,configurable:!0}),Object.defineProperty(lg.prototype,"boxEncodingSize",{get:function(){return 5+(this.withClassScores?this.config.classes.length:0)},enumerable:!0,configurable:!0}),lg.prototype.runTinyYolov2=function(t,e){var n=ng(t,e.conv0);return n=ng(n=Dc(n,[2,2],[2,2],"same"),e.conv1),n=ng(n=Dc(n,[2,2],[2,2],"same"),e.conv2),n=ng(n=Dc(n,[2,2],[2,2],"same"),e.conv3),n=ng(n=Dc(n,[2,2],[2,2],"same"),e.conv4),n=ng(n=Dc(n,[2,2],[2,2],"same"),e.conv5),hv(n=ng(n=ng(n=Dc(n,[2,2],[1,1],"same"),e.conv6),e.conv7),e.conv8,"valid",!1)},lg.prototype.runMobilenet=function(t,e){var n=this.config.isFirstLayerConv2d?eg(hv(t,e.conv0,"valid",!1)):rg(t,e.conv0);return n=rg(n=Dc(n,[2,2],[2,2],"same"),e.conv1),n=rg(n=Dc(n,[2,2],[2,2],"same"),e.conv2),n=rg(n=Dc(n,[2,2],[2,2],"same"),e.conv3),n=rg(n=Dc(n,[2,2],[2,2],"same"),e.conv4),n=rg(n=Dc(n,[2,2],[2,2],"same"),e.conv5),n=Dc(n,[2,2],[1,1],"same"),n=e.conv6?rg(n,e.conv6):n,hv(n=e.conv7?rg(n,e.conv7):n,e.conv8,"valid",!1)},lg.prototype.forwardInput=function(e,n){var r=this,o=this.params;if(!o)throw new Error("TinyYolov2 - load model before inference");return Je(function(){var t=e.toBatchTensor(n,!1).toFloat();return t=(t=r.config.meanRgb?Jp(t,r.config.meanRgb):t).div(Cn(256)),r.config.withSeparableConvs?r.runMobilenet(t,o):r.runTinyYolov2(t,o)})},lg.prototype.forward=function(n,r){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[4,e.apply(this,[t.sent(),r])];case 2:return[2,t.sent()]}})})},lg.prototype.detect=function(d,v){return void 0===v&&(v={}),gp(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p=this;return yp(this,function(t){switch(t.label){case 0:return e=new ag(v),n=e.inputSize,r=e.scoreThreshold,[4,Zd(d)];case 1:return o=t.sent(),[4,this.forwardInput(o,n)];case 2:return i=t.sent(),a=Je(function(){return Fr(i)[0].expandDims()}),s={width:o.getInputWidth(0),height:o.getInputHeight(0)},[4,this.extractBoxes(a,o.getReshapedInputDimensions(0),r)];case 3:return u=t.sent(),i.dispose(),a.dispose(),c=u.map(function(t){return t.box}),l=u.map(function(t){return t.score}),h=u.map(function(t){return t.classScore}),f=u.map(function(t){return p.config.classes[t.label]}),[2,Yp(c.map(function(t){return t.rescale(n)}),l,this.config.iouThreshold,!0).map(function(t){return new Gp(l[t],h[t],f[t],c[t],s)})]}})})},lg.prototype.getDefaultModelName=function(){return""},lg.prototype.extractParamsFromWeigthMap=function(t){return function(t,e){var n,r=[],o=ig(t,r),i=o.extractConvParams,a=o.extractConvWithBatchNormParams,s=o.extractSeparableConvParams;if(e.withSeparableConvs){var u=e.filterSizes&&e.filterSizes.length||9;n={conv0:e.isFirstLayerConv2d?i("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:7<u?s("conv6"):void 0,conv7:8<u?s("conv7"):void 0,conv8:i("conv8")}}else n={conv0:a("conv0"),conv1:a("conv1"),conv2:a("conv2"),conv3:a("conv3"),conv4:a("conv4"),conv5:a("conv5"),conv6:a("conv6"),conv7:a("conv7"),conv8:i("conv8")};return fv(t,r),{params:n,paramMappings:r}}(t,this.config)},lg.prototype.extractParams=function(t){var e=this.config.filterSizes||lg.DEFAULT_FILTER_SIZES,n=e?e.length:void 0;if(7!==n&&8!==n&&9!==n)throw new Error("TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found "+n+" filterSizes in config");return function(t,e,n,r){var o,i=xv(t),a=i.extractWeights,s=i.getRemainingWeights,u=[],c=og(a,u),l=c.extractConvParams,h=c.extractConvWithBatchNormParams,f=c.extractSeparableConvParams;if(e.withSeparableConvs){var p=r[0],d=r[1],v=r[2],m=r[3],g=r[4],y=r[5],x=r[6],b=r[7],w=r[8];o={conv0:e.isFirstLayerConv2d?l(p,d,3,"conv0"):f(p,d,"conv0"),conv1:f(d,v,"conv1"),conv2:f(v,m,"conv2"),conv3:f(m,g,"conv3"),conv4:f(g,y,"conv4"),conv5:f(y,x,"conv5"),conv6:b?f(x,b,"conv6"):void 0,conv7:w?f(b,w,"conv7"):void 0,conv8:l(w||b||x,5*n,1,"conv8")}}else p=r[0],d=r[1],v=r[2],m=r[3],g=r[4],y=r[5],x=r[6],b=r[7],w=r[8],o={conv0:h(p,d,"conv0"),conv1:h(d,v,"conv1"),conv2:h(v,m,"conv2"),conv3:h(m,g,"conv3"),conv4:h(g,y,"conv4"),conv5:h(y,x,"conv5"),conv6:h(x,b,"conv6"),conv7:h(b,w,"conv7"),conv8:l(w,5*n,1,"conv8")};if(0!==s().length)throw new Error("weights remaing after extract: "+s().length);return{params:o,paramMappings:u}}(t,this.config,this.boxEncodingSize,e)},lg.prototype.extractBoxes=function(T,F,N){return gp(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p,d,v,m,g,y,x,b,w,C,E,_,I,R,k,S,D,A=this;return yp(this,function(t){switch(t.label){case 0:return e=F.width,n=F.height,r=Math.max(e,n),o=r/e,i=r/n,a=T.shape[1],s=this.config.anchors.length,u=Je(function(){var t=T.reshape([a,a,s,A.boxEncodingSize]);return[t.slice([0,0,0,0],[a,a,s,4]),t.slice([0,0,0,4],[a,a,s,1]),A.withClassScores?Qr(t.slice([0,0,0,5],[a,a,s,A.config.classes.length]),3):Cn(0)]}),c=u[0],l=u[1],h=u[2],f=[],[4,l.array()];case 1:return p=t.sent(),[4,c.array()];case 2:d=t.sent(),v=0,t.label=3;case 3:if(!(v<a))return[3,12];m=0,t.label=4;case 4:if(!(m<a))return[3,11];g=0,t.label=5;case 5:return g<s?(y=Zp(p[v][m][g][0]),!N||N<y?(x=(m+Zp(d[v][m][g][0]))/a*o,b=(v+Zp(d[v][m][g][1]))/a*i,w=Math.exp(d[v][m][g][2])*this.config.anchors[g].x/a*o,C=Math.exp(d[v][m][g][3])*this.config.anchors[g].y/a*i,E=x-w/2,_=b-C/2,I={row:v,col:m,anchor:g},this.withClassScores?[4,this.extractPredictedClass(h,I)]:[3,7]):[3,9]):[3,10];case 6:return D=t.sent(),[3,8];case 7:D={classScore:1,label:0},t.label=8;case 8:k=(R=D).classScore,S=R.label,f.push(mp({box:new Up(E,_,E+w,_+C),score:y,classScore:y*k,label:S},I)),t.label=9;case 9:return g++,[3,5];case 10:return m++,[3,4];case 11:return v++,[3,3];case 12:return c.dispose(),l.dispose(),h.dispose(),[2,f]}})})},lg.prototype.extractPredictedClass=function(e,a){return gp(this,void 0,void 0,function(){var n,r,o,i;return yp(this,function(t){switch(t.label){case 0:return n=a.row,r=a.col,o=a.anchor,[4,e.array()];case 1:return i=t.sent(),[2,Array(this.config.classes.length).fill(0).map(function(t,e){return i[n][r][o][e]}).map(function(t,e){return{classScore:t,label:e}}).reduce(function(t,e){return t.classScore>e.classScore?t:e})]}})})},lg.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024],lg);function lg(t){var e=ug.call(this,"TinyYolov2")||this;return tg(t),e._config=t,e}var hg,fg=(vp(pg,hg=cg),Object.defineProperty(pg.prototype,"withSeparableConvs",{get:function(){return this.config.withSeparableConvs},enumerable:!0,configurable:!0}),Object.defineProperty(pg.prototype,"anchors",{get:function(){return this.config.anchors},enumerable:!0,configurable:!0}),pg.prototype.locateFaces=function(e,n){return gp(this,void 0,void 0,function(){return yp(this,function(t){switch(t.label){case 0:return[4,this.detect(e,n)];case 1:return[2,t.sent().map(function(t){return new jp(t.score,t.relativeBox,{width:t.imageWidth,height:t.imageHeight})})]}})})},pg.prototype.getDefaultModelName=function(){return this.withSeparableConvs?"tiny_yolov2_separable_conv_model":"tiny_yolov2_model"},pg.prototype.extractParamsFromWeigthMap=function(t){return hg.prototype.extractParamsFromWeigthMap.call(this,t)},pg);function pg(t){void 0===t&&(t=!0);var e=Object.assign({},{withSeparableConvs:t,iouThreshold:.4,classes:["face"]},t?{anchors:Jm,meanRgb:Qm}:{anchors:Ym,withClassScores:!0});return hg.call(this,e)||this}var dg,vg=(vp(mg,dg=ag),mg);function mg(){var t=null!==dg&&dg.apply(this,arguments)||this;return t._name="TinyFaceDetectorOptions",t}var gg=(yg.prototype.then=function(n){return gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=n,[4,this.run()];case 1:return[2,e.apply(void 0,[t.sent()])]}})})},yg.prototype.run=function(){return gp(this,void 0,void 0,function(){return yp(this,function(t){throw new Error("ComposableTask - run is not implemented")})})},yg);function yg(){}function xg(a,s,u,c,l){return void 0===l&&(l=function(t){return t.alignedRect}),gp(this,void 0,void 0,function(){var e,n,r,o,i;return yp(this,function(t){switch(t.label){case 0:return e=a.map(function(t){return Wv(t)?l(t):t.detection}),(r=c)?[3,5]:s instanceof vt?[4,ev(s,e)]:[3,2];case 1:return o=t.sent(),[3,4];case 2:return[4,tv(s,e)];case 3:o=t.sent(),t.label=4;case 4:r=o,t.label=5;case 5:return[4,u(n=r)];case 6:return i=t.sent(),n.forEach(function(t){return t instanceof vt&&t.dispose()}),[2,i]}})})}function bg(e,r,o,i,a){return gp(this,void 0,void 0,function(){var n=this;return yp(this,function(t){return[2,xg([e],r,function(e){return gp(n,void 0,void 0,function(){return yp(this,function(t){return[2,o(e[0])]})})},i,a)]})})}var wg=2,Cg=12;function Eg(t){var e=xv(t),n=e.extractWeights,r=e.getRemainingWeights,o=[],i=function(r,o){var u=pv(r,o),c=dv(r,o);function l(t,e){var n=En(r(t));return o.push({paramPath:e}),n}function h(t,e,n){return void 0===n&&(n=!1),{conv1:u(t[0],t[1],3,e+"/conv1"),prelu1_alpha:l(t[1],e+"/prelu1_alpha"),conv2:u(t[1],t[2],3,e+"/conv2"),prelu2_alpha:l(t[2],e+"/prelu2_alpha"),conv3:u(t[2],t[3],n?2:3,e+"/conv3"),prelu3_alpha:l(t[3],e+"/prelu3_alpha")}}return{extractPNetParams:function(){var t=h([3,10,16,32],"pnet"),e=u(32,2,1,"pnet/conv4_1"),n=u(32,4,1,"pnet/conv4_2");return mp(mp({},t),{conv4_1:e,conv4_2:n})},extractRNetParams:function(){var t=h([3,28,48,64],"rnet",!0),e=c(576,128,"rnet/fc1"),n=l(128,"rnet/prelu4_alpha"),r=c(128,2,"rnet/fc2_1"),o=c(128,4,"rnet/fc2_2");return mp(mp({},t),{fc1:e,prelu4_alpha:n,fc2_1:r,fc2_2:o})},extractONetParams:function(){var t=h([3,32,64,64],"onet"),e=u(64,128,2,"onet/conv4"),n=l(128,"onet/prelu4_alpha"),r=c(1152,256,"onet/fc1"),o=l(256,"onet/prelu5_alpha"),i=c(256,2,"onet/fc2_1"),a=c(256,4,"onet/fc2_2"),s=c(256,10,"onet/fc2_3");return mp(mp({},t),{conv4:e,prelu4_alpha:n,fc1:r,prelu5_alpha:o,fc2_1:i,fc2_2:a,fc2_3:s})}}}(n,o),a=i.extractPNetParams,s=i.extractRNetParams,u=i.extractONetParams,c=a(),l=s(),h=u();if(0!==r().length)throw new Error("weights remaing after extract: "+r().length);return{params:{pnet:c,rnet:l,onet:h},paramMappings:o}}function _g(t){var e=[],n=function(t,e){var n=yv(t,e);function u(t){return{filters:n(t+"/weights",4,t+"/filters"),bias:n(t+"/bias",1)}}function c(t){return{weights:n(t+"/weights",2),bias:n(t+"/bias",1)}}function l(t){return n(t,1)}function h(t){return{conv1:u(t+"/conv1"),prelu1_alpha:l(t+"/prelu1_alpha"),conv2:u(t+"/conv2"),prelu2_alpha:l(t+"/prelu2_alpha"),conv3:u(t+"/conv3"),prelu3_alpha:l(t+"/prelu3_alpha")}}return{extractPNetParams:function(){var t=h("pnet"),e=u("pnet/conv4_1"),n=u("pnet/conv4_2");return mp(mp({},t),{conv4_1:e,conv4_2:n})},extractRNetParams:function(){var t=h("rnet"),e=c("rnet/fc1"),n=l("rnet/prelu4_alpha"),r=c("rnet/fc2_1"),o=c("rnet/fc2_2");return mp(mp({},t),{fc1:e,prelu4_alpha:n,fc2_1:r,fc2_2:o})},extractONetParams:function(){var t=h("onet"),e=u("onet/conv4"),n=l("onet/prelu4_alpha"),r=c("onet/fc1"),o=l("onet/prelu5_alpha"),i=c("onet/fc2_1"),a=c("onet/fc2_2"),s=c("onet/fc2_3");return mp(mp({},t),{conv4:e,prelu4_alpha:n,fc1:r,prelu5_alpha:o,fc2_1:i,fc2_2:a,fc2_3:s})}}}(t,e),r=n.extractPNetParams,o=n.extractRNetParams,i=n.extractONetParams,a=r(),s=o(),u=i();return fv(t,e),{params:{pnet:a,rnet:s,onet:u},paramMappings:e}}function Ig(t,e){var n=e[0],r=e[1];return{height:Math.floor(n*t),width:Math.floor(r*t)}}var Rg,kg=(vp(Sg,Rg=Lp),Sg);function Sg(t,e,n,r){return Rg.call(this,{left:t,top:e,right:n,bottom:r},!0)||this}function Dg(t){return Je(function(){return Mu(zu(t,Cn(127.5)),Cn(.0078125))})}function Ag(t,e){return Je(function(){return bu(tl(t),Mu(e,Ls(tl(Ls(t)))))})}function Tg(e,n,r){return void 0===r&&(r=!1),Je(function(){var t=hv(e,n.conv1,"valid");return t=Ag(t,n.prelu1_alpha),t=Ag(t=hv(t=Dc(t,r?[2,2]:[3,3],[2,2],"same"),n.conv2,"valid"),n.prelu2_alpha),t=Ag(t=hv(t=r?t:Dc(t,[3,3],[2,2],"valid"),n.conv3,"valid"),n.prelu3_alpha)})}function Fg(s,t,u,c,l){l.stage1=[];var e=t.map(function(a){return Je(function(){var t={scale:a},e=function(o,i){return Je(function(){var t=Ig(i,o.shape.slice(1)),e=t.height,n=t.width,r=Dg(th.resizeBilinear(o,[e,n]));return rl(r,[0,2,1,3])})}(s,a),n=Date.now(),r=function(r,o){return Je(function(){var t=Tg(r,o,!0),e=hv(t,o.conv4_1,"valid"),n=pr(qc(e,3),3);return{prob:Qr(zu(e,n),3),regions:hv(t,o.conv4_2,"valid")}})}(e,c),o=r.prob,i=r.regions;return t.pnet=Date.now()-n,{scoresTensor:Fr(Fr(o,3)[1])[0],regionsTensor:Fr(i)[0],scale:a,statsForScale:t}})}).map(function(t){var e=t.scoresTensor,n=t.regionsTensor,r=t.scale,o=t.statsForScale,i=function(t,o,i,e){for(var n=[],a=t.arraySync(),r=0;r<t.shape[0];r++)for(var s=0;s<t.shape[1];s++)a[r][s]>=e&&n.push(new Pp(s,r));return n.map(function(t){var e=new 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a=t.width,s=t.height;return gp(this,void 0,void 0,function(){var l,e,i,n=this;return yp(this,function(t){switch(t.label){case 0:return l=Od(h),[4,Promise.all(r.map(function(c){return gp(n,void 0,void 0,function(){var e,n,r,o,i,a,s,u;return yp(this,function(t){return e=c.padAtBorders(h.height,h.width),n=e.y,r=e.ey,o=e.x,i=e.ex,a=o-1,s=n-1,u=l.getImageData(a,s,i-a,r-s),[2,Nd.isNodejs()?Kd(u):createImageBitmap(u)]})})}))];case 1:return e=t.sent(),i=[],e.forEach(function(t){var e=Od(jd({width:a,height:s}));e.drawImage(t,0,0,a,s);for(var n=e.getImageData(0,0,a,s).data,r=[],o=0;o<n.length;o+=4)r.push(n[o+2]),r.push(n[o+1]),r.push(n[o]);i.push(r)}),[2,i.map(function(t){return Je(function(){return Dg(rl(Rn(t,[1,a,s,3]),[0,2,1,3]).toFloat())})})]}})})}function Mg(v,m,g,y,x){return gp(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p,d;return yp(this,function(t){switch(t.label){case 0:return e=Date.now(),[4,Ng(v,m,{width:24,height:24})];case 1:return 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o=s.apply(a,[t.sent()]),r.dispose(),u=o.map(function(t,e){return{score:t,idx:e}}).filter(function(t){return t.score>y}).map(function(t){return t.idx}),c=u.map(function(t){var e=i[t].regions.arraySync();return new kg(e[0][0],e[0][1],e[0][2],e[0][3])}),l=u.map(function(t,e){return g[t].calibrate(c[e])}),h=u.map(function(t){return o[t]}),f=[],p=[],d=[],0<l.length&&(e=Date.now(),v=Yp(l,h,.7,!1),b.stage3_nms=Date.now()-e,f=v.map(function(t){return l[t]}),p=v.map(function(t){return h[t]}),d=v.map(function(r,o){return Array(5).fill(0).map(function(t,e){var n=i[r].points.arraySync();return new Pp(n[0][e]*(f[o].width+1)+f[o].left,n[0][e+5]*(f[o].height+1)+f[o].top)})})),i.forEach(function(t){t.regions.dispose(),t.scores.dispose(),t.points.dispose()}),[2,{boxes:f,scores:p,points:d}]}})})}var Pg,Bg=(vp(Lg,Pg=av),Lg.prototype.load=function(e){return gp(this,void 0,void 0,function(){return yp(this,function(t){return console.warn("mtcnn is deprecated and will be removed 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ad(b.points[t].map(function(t){return t.sub(new Pp(e.left,e.top)).div(new Pp(e.width,e.height))}),{width:e.width,height:e.height}))}),[2,a({results:w,stats:r})]}})})},Lg.prototype.forward=function(n,r){return void 0===r&&(r={}),gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[4,e.apply(this,[t.sent(),r])];case 2:return[2,t.sent().results]}})})},Lg.prototype.forwardWithStats=function(n,r){return void 0===r&&(r={}),gp(this,void 0,void 0,function(){var e;return yp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,Zd(n)];case 1:return[2,e.apply(this,[t.sent(),r])]}})})},Lg.prototype.getDefaultModelName=function(){return"mtcnn_model"},Lg.prototype.extractParamsFromWeigthMap=function(t){return _g(t)},Lg.prototype.extractParams=function(t){return Eg(t)},Lg);function Lg(){return Pg.call(this,"Mtcnn")||this}var Wg,zg=[new Pp(1.603231,2.094468),new Pp(6.041143,7.080126),new Pp(2.882459,3.518061),new Pp(4.266906,5.178857),new Pp(9.041765,10.66308)],Ug=[117.001,114.697,97.404],Vg=(vp(Gg,Wg=cg),Object.defineProperty(Gg.prototype,"anchors",{get:function(){return this.config.anchors},enumerable:!0,configurable:!0}),Gg.prototype.locateFaces=function(e,n){return gp(this,void 0,void 0,function(){return yp(this,function(t){switch(t.label){case 0:return[4,this.detect(e,n)];case 1:return[2,t.sent().map(function(t){return new jp(t.score,t.relativeBox,{width:t.imageWidth,height:t.imageHeight})})]}})})},Gg.prototype.getDefaultModelName=function(){return"tiny_face_detector_model"},Gg.prototype.extractParamsFromWeigthMap=function(t){return Wg.prototype.extractParamsFromWeigthMap.call(this,t)},Gg);function Gg(){var t={withSeparableConvs:!0,iouThreshold:.4,classes:["face"],anchors:zg,meanRgb:Ug,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};return Wg.call(this,t)||this}function Hg(t,e){return Xg.ssdMobilenetv1.locateFaces(t,e)}function qg(t){return Xg.faceLandmark68Net.detectLandmarks(t)}function jg(t){return Xg.ssdMobilenetv1.load(t)}var Kg,Xg={ssdMobilenetv1:new Gm,tinyFaceDetector:new Vg,tinyYolov2:new fg,mtcnn:new Bg,faceLandmark68Net:new am,faceLandmark68TinyNet:new fm,faceRecognitionNet:new Im,faceExpressionNet:new Ov,ageGenderNet:new tm},$g=jg,Yg=Hg,Jg=qg,Qg=(vp(Zg,Kg=gg),Zg);function Zg(t,e,n){var r=Kg.call(this)||this;return r.parentTask=t,r.input=e,r.extractedFaces=n,r}var ty,ey=(vp(ny,ty=Qg),ny.prototype.run=function(){return gp(this,void 0,void 0,function(){var e,n,r=this;return yp(this,function(t){switch(t.label){case 0:return[4,this.parentTask];case 1:return[4,xg(e=t.sent(),this.input,function(e){return gp(r,void 0,void 0,function(){return yp(this,function(t){switch(t.label){case 0:return[4,Promise.all(e.map(function(t){return Xg.faceExpressionNet.predictExpressions(t)}))];case 1:return[2,t.sent()]}})})},this.extractedFaces)];case 2:return n=t.sent(),[2,e.map(function(t,e){return Lv(t,n[e])})]}})})},ny.prototype.withAgeAndGender=function(){return new my(this,this.input)},ny);function ny(){return null!==ty&&ty.apply(this,arguments)||this}var ry,oy=(vp(iy,ry=Qg),iy.prototype.run=function(){return gp(this,void 0,void 0,function(){var e,n;return yp(this,function(t){switch(t.label){case 0:return[4,this.parentTask];case 1:return(e=t.sent())?[4,bg(e,this.input,function(t){return Xg.faceExpressionNet.predictExpressions(t)},this.extractedFaces)]:[2];case 2:return n=t.sent(),[2,Lv(e,n)]}})})},iy.prototype.withAgeAndGender=function(){return new xy(this,this.input)},iy);function iy(){return null!==ry&&ry.apply(this,arguments)||this}var ay,sy=(vp(uy,ay=ey),uy.prototype.withAgeAndGender=function(){return new Cy(this,this.input)},uy.prototype.withFaceDescriptors=function(){return new Ty(this,this.input)},uy);function uy(){return null!==ay&&ay.apply(this,arguments)||this}var cy,ly=(vp(hy,cy=oy),hy.prototype.withAgeAndGender=function(){return new Iy(this,this.input)},hy.prototype.withFaceDescriptor=function(){return new My(this,this.input)},hy);function hy(){return null!==cy&&cy.apply(this,arguments)||this}var fy,py=(vp(dy,fy=gg),dy);function dy(t,e,n){var r=fy.call(this)||this;return r.parentTask=t,r.input=e,r.extractedFaces=n,r}var vy,my=(vp(gy,vy=py),gy.prototype.run=function(){return gp(this,void 0,void 0,function(){var e,o,n=this;return yp(this,function(t){switch(t.label){case 0:return[4,this.parentTask];case 1:return[4,xg(e=t.sent(),this.input,function(e){return gp(n,void 0,void 0,function(){return yp(this,function(t){switch(t.label){case 0:return[4,Promise.all(e.map(function(t){return Xg.ageGenderNet.predictAgeAndGender(t)}))];case 1:return[2,t.sent()]}})})},this.extractedFaces)];case 2:return o=t.sent(),[2,e.map(function(t,e){var n=o[e],r=n.age;return Sm(Dm(t,n.gender,n.genderProbability),r)})]}})})},gy.prototype.withFaceExpressions=function(){return new ey(this,this.input)},gy);function gy(){return null!==vy&&vy.apply(this,arguments)||this}var yy,xy=(vp(by,yy=py),by.prototype.run=function(){return gp(this,void 0,void 0,function(){var e,n,r,o,i;return yp(this,function(t){switch(t.label){case 0:return[4,this.parentTask];case 1:return(e=t.sent())?[4,bg(e,this.input,function(t){return Xg.ageGenderNet.predictAgeAndGender(t)},this.extractedFaces)]:[2];case 2:return n=t.sent(),r=n.age,o=n.gender,i=n.genderProbability,[2,Sm(Dm(e,o,i),r)]}})})},by.prototype.withFaceExpressions=function(){return new oy(this,this.input)},by);function by(){return null!==yy&&yy.apply(this,arguments)||this}var wy,Cy=(vp(Ey,wy=my),Ey.prototype.withFaceExpressions=function(){return new sy(this,this.input)},Ey.prototype.withFaceDescriptors=function(){return new Ty(this,this.input)},Ey);function Ey(){return null!==wy&&wy.apply(this,arguments)||this}var _y,Iy=(vp(Ry,_y=xy),Ry.prototype.withFaceExpressions=function(){return new ly(this,this.input)},Ry.prototype.withFaceDescriptor=function(){return new My(this,this.input)},Ry);function Ry(){return null!==_y&&_y.apply(this,arguments)||this}var ky,Sy=(vp(Dy,ky=gg),Dy);function Dy(t,e){var n=ky.call(this)||this;return n.parentTask=t,n.input=e,n}var Ay,Ty=(vp(Fy,Ay=Sy),Fy.prototype.run=function(){return gp(this,void 0,void 0,function(){var n;return yp(this,function(t){switch(t.label){case 0:return[4,this.parentTask];case 1:return[4,xg(n=t.sent(),this.input,function(t){return Promise.all(t.map(function(t){return Xg.faceRecognitionNet.computeFaceDescriptor(t)}))},null,function(t){return t.landmarks.align(null,{useDlibAlignment:!0})})];case 2:return[2,t.sent().map(function(t,e){return km(n[e],t)})]}})})},Fy.prototype.withFaceExpressions=function(){return new sy(this,this.input)},Fy.prototype.withAgeAndGender=function(){return new Cy(this,this.input)},Fy);function Fy(){return null!==Ay&&Ay.apply(this,arguments)||this}var Ny,My=(vp(Oy,Ny=Sy),Oy.prototype.run=function(){return gp(this,void 0,void 0,function(){var e,n;return yp(this,function(t){switch(t.label){case 0:return[4,this.parentTask];case 1:return(e=t.sent())?[4,bg(e,this.input,function(t){return Xg.faceRecognitionNet.computeFaceDescriptor(t)},null,function(t){return t.landmarks.align(null,{useDlibAlignment:!0})})]:[2];case 2:return n=t.sent(),[2,km(e,n)]}})})},Oy.prototype.withFaceExpressions=function(){return new ly(this,this.input)},Oy.prototype.withAgeAndGender=function(){return new Iy(this,this.input)},Oy);function Oy(){return null!==Ny&&Ny.apply(this,arguments)||this}var Py,By=(vp(Ly,Py=gg),Object.defineProperty(Ly.prototype,"landmarkNet",{get:function(){return this.useTinyLandmarkNet?Xg.faceLandmark68TinyNet:Xg.faceLandmark68Net},enumerable:!0,configurable:!0}),Ly);function Ly(t,e,n){var r=Py.call(this)||this;return r.parentTask=t,r.input=e,r.useTinyLandmarkNet=n,r}var Wy,zy=(vp(Uy,Wy=By),Uy.prototype.run=function(){return gp(this,void 0,void 0,function(){var e,n,r,o,i,a=this;return yp(this,function(t){switch(t.label){case 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this.throwIfDisposed(),gt.equalStrict(this,t)},wt.prototype.lessEqual=function(t){return this.throwIfDisposed(),gt.lessEqual(this,t)},wt.prototype.lessEqualStrict=function(t){return this.throwIfDisposed(),gt.lessEqualStrict(this,t)},wt.prototype.greater=function(t){return this.throwIfDisposed(),gt.greater(this,t)},wt.prototype.greaterStrict=function(t){return this.throwIfDisposed(),gt.greaterStrict(this,t)},wt.prototype.greaterEqual=function(t){return this.throwIfDisposed(),gt.greaterEqual(this,t)},wt.prototype.greaterEqualStrict=function(t){return this.throwIfDisposed(),gt.greaterEqualStrict(this,t)},wt.prototype.logicalAnd=function(t){return this.throwIfDisposed(),gt.logicalAnd(this,t)},wt.prototype.logicalOr=function(t){return this.throwIfDisposed(),gt.logicalOr(this,t)},wt.prototype.logicalNot=function(){return this.throwIfDisposed(),gt.logicalNot(this)},wt.prototype.logicalXor=function(t){return this.throwIfDisposed(),gt.logicalXor(this,t)},wt.prototype.where=function(t,e){return this.throwIfDisposed(),gt.where(t,this,e)},wt.prototype.neg=function(){return this.throwIfDisposed(),gt.neg(this)},wt.prototype.ceil=function(){return this.throwIfDisposed(),gt.ceil(this)},wt.prototype.floor=function(){return this.throwIfDisposed(),gt.floor(this)},wt.prototype.sign=function(){return this.throwIfDisposed(),gt.sign(this)},wt.prototype.isNaN=function(){return this.throwIfDisposed(),gt.isNaN(this)},wt.prototype.isInf=function(){return this.throwIfDisposed(),gt.isInf(this)},wt.prototype.isFinite=function(){return this.throwIfDisposed(),gt.isFinite(this)},wt.prototype.exp=function(){return this.throwIfDisposed(),gt.exp(this)},wt.prototype.expm1=function(){return this.throwIfDisposed(),gt.expm1(this)},wt.prototype.log=function(){return this.throwIfDisposed(),gt.log(this)},wt.prototype.log1p=function(){return this.throwIfDisposed(),gt.log1p(this)},wt.prototype.sqrt=function(){return this.throwIfDisposed(),gt.sqrt(this)},wt.prototype.rsqrt=function(){return this.throwIfDisposed(),gt.rsqrt(this)},wt.prototype.square=function(){return this.throwIfDisposed(),gt.square(this)},wt.prototype.reciprocal=function(){return this.throwIfDisposed(),gt.reciprocal(this)},wt.prototype.abs=function(){return this.throwIfDisposed(),gt.abs(this)},wt.prototype.clipByValue=function(t,e){return this.throwIfDisposed(),gt.clipByValue(this,t,e)},wt.prototype.relu=function(){return this.throwIfDisposed(),gt.relu(this)},wt.prototype.relu6=function(){return this.throwIfDisposed(),gt.relu6(this)},wt.prototype.elu=function(){return this.throwIfDisposed(),gt.elu(this)},wt.prototype.selu=function(){return this.throwIfDisposed(),gt.selu(this)},wt.prototype.leakyRelu=function(t){return void 0===t&&(t=.2),this.throwIfDisposed(),gt.leakyRelu(this,t)},wt.prototype.prelu=function(t){return this.throwIfDisposed(),gt.prelu(this,t)},wt.prototype.sigmoid=function(){return this.throwIfDisposed(),gt.sigmoid(this)},wt.prototype.logSigmoid=function(){return this.throwIfDisposed(),gt.logSigmoid(this)},wt.prototype.softplus=function(){return this.throwIfDisposed(),gt.softplus(this)},wt.prototype.zerosLike=function(){return this.throwIfDisposed(),gt.zerosLike(this)},wt.prototype.onesLike=function(){return this.throwIfDisposed(),gt.onesLike(this)},wt.prototype.sin=function(){return this.throwIfDisposed(),gt.sin(this)},wt.prototype.cos=function(){return this.throwIfDisposed(),gt.cos(this)},wt.prototype.tan=function(){return this.throwIfDisposed(),gt.tan(this)},wt.prototype.asin=function(){return this.throwIfDisposed(),gt.asin(this)},wt.prototype.acos=function(){return this.throwIfDisposed(),gt.acos(this)},wt.prototype.atan=function(){return this.throwIfDisposed(),gt.atan(this)},wt.prototype.sinh=function(){return this.throwIfDisposed(),gt.sinh(this)},wt.prototype.cosh=function(){return this.throwIfDisposed(),gt.cosh(this)},wt.prototype.tanh=function(){return this.throwIfDisposed(),gt.tanh(this)},wt.prototype.asinh=function(){return this.throwIfDisposed(),gt.asinh(this)},wt.prototype.acosh=function(){return this.throwIfDisposed(),gt.acosh(this)},wt.prototype.atanh=function(){return this.throwIfDisposed(),gt.atanh(this)},wt.prototype.erf=function(){return this.throwIfDisposed(),gt.erf(this)},wt.prototype.round=function(){return this.throwIfDisposed(),gt.round(this)},wt.prototype.step=function(t){return void 0===t&&(t=0),this.throwIfDisposed(),gt.step(this,t)},wt.prototype.softmax=function(t){return void 0===t&&(t=-1),this.throwIfDisposed(),gt.softmax(this,t)},wt.prototype.logSoftmax=function(t){return void 0===t&&(t=-1),this.throwIfDisposed(),gt.logSoftmax(this,t)},wt.prototype.resizeBilinear=function(t,e){return void 0===e&&(e=!1),this.throwIfDisposed(),gt.image.resizeBilinear(this,t,e)},wt.prototype.resizeNearestNeighbor=function(t,e){return void 0===e&&(e=!1),this.throwIfDisposed(),gt.image.resizeNearestNeighbor(this,t,e)},wt.prototype.conv1d=function(t,e,n,r,o,i){return void 0===r&&(r="NWC"),void 0===o&&(o=1),this.throwIfDisposed(),gt.conv1d(this,t,e,n,r,o,i)},wt.prototype.conv2d=function(t,e,n,r,o,i){return void 0===r&&(r="NHWC"),void 0===o&&(o=[1,1]),this.throwIfDisposed(),gt.conv2d(this,t,e,n,r,o,i)},wt.prototype.conv2dTranspose=function(t,e,n,r,o){return this.throwIfDisposed(),gt.conv2dTranspose(this,t,e,n,r,o)},wt.prototype.depthwiseConv2D=function(t,e,n,r,o,i){return void 0===r&&(r="NHWC"),void 0===o&&(o=[1,1]),this.throwIfDisposed(),gt.depthwiseConv2d(this,t,e,n,r,o,i)},wt.prototype.separableConv2d=function(t,e,n,r,o,i){return void 0===o&&(o=[1,1]),void 0===i&&(i="NHWC"),this.throwIfDisposed(),gt.separableConv2d(this,t,e,n,r,o,i)},wt.prototype.avgPool=function(t,e,n,r){return this.throwIfDisposed(),gt.avgPool(this,t,e,n,r)},wt.prototype.maxPool=function(t,e,n,r){return this.throwIfDisposed(),gt.maxPool(this,t,e,n,r)},wt.prototype.localResponseNormalization=function(t,e,n,r){return void 0===t&&(t=5),void 0===e&&(e=1),void 0===n&&(n=1),void 0===r&&(r=.5),gt.localResponseNormalization(this,t,e,n,r)},wt.prototype.pool=function(t,e,n,r,o){return this.throwIfDisposed(),gt.pool(this,t,e,n,r,o)},wt.prototype.variable=function(t,e,n){return void 0===t&&(t=!0),this.throwIfDisposed(),mt().makeVariable(this,t,e,n)},wt.prototype.unsortedSegmentSum=function(t,e){return this.throwIfDisposed(),gt.unsortedSegmentSum(this,t,e)},wt.prototype.batchToSpaceND=function(t,e){return this.throwIfDisposed(),gt.batchToSpaceND(this,t,e)},wt.prototype.spaceToBatchND=function(t,e){return this.throwIfDisposed(),gt.spaceToBatchND(this,t,e)},wt.prototype.topk=function(t,e){return void 0===t&&(t=1),void 0===e&&(e=!0),this.throwIfDisposed(),gt.topk(this,t,e)},wt.prototype.stridedSlice=function(t,e,n,r,o,i,a,s){return void 0===r&&(r=0),void 0===o&&(o=0),void 0===i&&(i=0),void 0===a&&(a=0),void 0===s&&(s=0),this.throwIfDisposed(),gt.stridedSlice(this,t,e,n,r,o,i,a,s)},wt.prototype.depthToSpace=function(t,e){return this.throwIfDisposed(),gt.depthToSpace(this,t,e)},wt.prototype.fft=function(){return this.throwIfDisposed(),gt.spectral.fft(this)},wt.prototype.ifft=function(){return this.throwIfDisposed(),gt.spectral.ifft(this)},wt.prototype.rfft=function(){return this.throwIfDisposed(),gt.spectral.rfft(this)},wt.prototype.irfft=function(){return this.throwIfDisposed(),gt.spectral.irfft(this)},wt);function wt(t,e,n,r){this.kept=!1,this.isDisposedInternal=!1,this.shape=t.slice(),this.dtype=e||"float32",this.size=L(t),this.strides=Y(t),this.dataId=n,this.id=r,this.rankType=this.rank<5?this.rank.toString():"higher"}Object.defineProperty(bt,Symbol.hasInstance,{value:function(t){return!!t&&null!=t.dataId&&null!=t.shape&&null!=t.dtype}});var Ct,Et,_t,It,Rt,kt,St,Dt,At,Tt,Nt,Ft=(t(Mt,kt=bt),Mt.prototype.assign=function(t){if(t.dtype!==this.dtype)throw new Error("dtype of the new value ("+t.dtype+") and previous value ("+this.dtype+") must match");if(!A(t.shape,this.shape))throw new Error("shape of the new value ("+t.shape+") and previous value ("+this.shape+") must match");mt().disposeTensor(this),this.dataId=t.dataId,mt().incRef(this,null)},Mt.prototype.dispose=function(){mt().disposeVariable(this),this.isDisposedInternal=!0},Mt);function Mt(t,e,n,r){var o=kt.call(this,t.shape,t.dtype,t.dataId,r)||this;return o.trainable=e,o.name=n,o}Object.defineProperty(Ft,Symbol.hasInstance,{value:function(t){return t instanceof bt&&null!=t.assign&&t.assign instanceof Function}}),(Nt=Ct=Ct||{}).R0="R0",Nt.R1="R1",Nt.R2="R2",Nt.R3="R3",Nt.R4="R4",Nt.R5="R5",Nt.R6="R6",(Tt=Et=Et||{}).float32="float32",Tt.int32="int32",Tt.bool="int32",Tt.complex64="complex64",(At=_t=_t||{}).float32="float32",At.int32="int32",At.bool="bool",At.complex64="complex64",(Dt=It=It||{}).float32="float32",Dt.int32="float32",Dt.bool="float32",Dt.complex64="complex64",(St=Rt=Rt||{}).float32="complex64",St.int32="complex64",St.bool="complex64",St.complex64="complex64";var Ot={float32:It,int32:Et,bool:_t,complex64:Rt};function Pt(t,e){if("string"!==t&&"string"!==e)return Ot[t][e];if("string"===t&&"string"===e)return"string";throw new Error("Can not upcast "+t+" with "+e)}function Bt(t){return Pt(t,"int32")}function Lt(t,e){if(t.dtype===e.dtype)return[t,e];var n=Pt(t.dtype,e.dtype);return[t.cast(n),e.cast(n)]}function Wt(t,e){P(t.dtype===e.dtype,function(){return"The dtypes of the first("+t.dtype+") and second("+e.dtype+") input must match"})}function zt(t){var e=[];return function t(e,n,r){if(null!=e)if(e instanceof bt)n.push(e);else if(o=e,Array.isArray(o)||"object"==typeof o){var o,i=e;for(var a in i){var s=i[a];r.has(s)||(r.add(s),t(s,n,r))}}}(t,e,new Set),e}var Ut,Vt=Object.freeze({makeTypesMatch:Lt,assertTypesMatch:Wt,isTensorInList:function(e,t){return t.some(function(t){return t.id===e.id})},getTensorsInContainer:zt}),Gt=(jt.prototype.dispose=function(){for(var t in this.registeredVariables)this.registeredVariables[t].dispose()},jt),Ht=(qt.prototype.ready=function(){return y(this,void 0,void 0,function(){var e,n,r;return R(this,function(t){switch(t.label){case 0:if(null!=this.pendingBackendInit)return[2,this.pendingBackendInit.then(function(){})];if(null!=this.backendInstance)return[2];e=this.getSortedBackends(),n=0,t.label=1;case 1:return n<e.length?(r=e[n],[4,this.initializeBackend(r).success]):[3,5];case 2:return t.sent()?[4,this.setBackend(r)]:[3,4];case 3:return t.sent(),[2];case 4:return n++,[3,1];case 5:throw new Error("Could not initialize any backends, all backend initializations failed.")}})})},Object.defineProperty(qt.prototype,"backend",{get:function(){if(null!=this.pendingBackendInit)throw new Error("Backend '"+this.backendName+"' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods");if(null==this.backendInstance){var t=this.initializeBackendsAndReturnBest(),e=t.name;if(t.asyncInit)throw new Error("The highest priority backend '"+e+"' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods");this.setBackend(e)}return this.backendInstance},enumerable:!0,configurable:!0}),qt.prototype.backendNames=function(){return Object.keys(this.registryFactory)},qt.prototype.findBackend=function(t){if(!(t in this.registry)){if(!(t in this.registryFactory))return null;if(this.initializeBackend(t).asyncInit)return null}return this.registry[t]},qt.prototype.findBackendFactory=function(t){return t in this.registryFactory?this.registryFactory[t].factory:null},qt.prototype.registerBackend=function(t,e,n){return void 0===n&&(n=1),t in this.registryFactory?(console.warn(t+" backend was already registered. Reusing existing backend factory."),!1):(this.registryFactory[t]={factory:e,priority:n},!0)},qt.prototype.setBackend=function(o){return y(this,void 0,void 0,function(){var e,n,r;return R(this,function(t){switch(t.label){case 0:if(null==this.registryFactory[o])throw new Error("Backend name '"+o+"' not found in registry");return this.backendName=o,null!=this.registry[o]?[3,4]:(this.backendInstance=null,e=this.initializeBackend(o),n=e.success,e.asyncInit?[4,n]:[3,2]);case 1:return r=t.sent(),[3,3];case 2:r=n,t.label=3;case 3:if(!r)return[2,!1];t.label=4;case 4:return this.backendInstance=this.registry[o],this.setupRegisteredKernels(),this.profiler=new st(this.backendInstance),[2,!0]}})})},qt.prototype.setupRegisteredKernels=function(){var e=this;a(this.backendName).forEach(function(t){null!=t.setupFunc&&t.setupFunc(e.backendInstance)})},qt.prototype.disposeRegisteredKernels=function(e){var n=this;a(e).forEach(function(t){null!=t.disposeFunc&&t.disposeFunc(n.registry[e])})},qt.prototype.initializeBackend=function(e){var n=this,t=this.registryFactory[e];if(null==t)throw new Error("Cannot initialize backend "+e+", no registration found.");try{var r=t.factory();if(Promise.resolve(r)!==r)return this.registry[e]=r,{success:!0,asyncInit:!1};var o=++this.pendingBackendInitId,i=r.then(function(t){return!(o<n.pendingBackendInitId||(n.registry[e]=t,n.pendingBackendInit=null))}).catch(function(t){return!(o<n.pendingBackendInitId||(n.pendingBackendInit=null,console.warn("Initialization of backend "+e+" failed"),console.warn(t.stack||t.message),1))});return{success:this.pendingBackendInit=i,asyncInit:!0}}catch(n){return console.warn("Initialization of backend "+e+" failed"),console.warn(n.stack||n.message),{success:!1,asyncInit:!1}}},qt.prototype.removeBackend=function(t){if(!(t in this.registryFactory))throw new Error(t+" backend not found in registry");this.backendName===t&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)},qt.prototype.getSortedBackends=function(){var n=this;if(0===Object.keys(this.registryFactory).length)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort(function(t,e){return n.registryFactory[e].priority-n.registryFactory[t].priority})},qt.prototype.initializeBackendsAndReturnBest=function(){for(var t=this.getSortedBackends(),e=0;e<t.length;e++){var n=t[e],r=this.initializeBackend(n),o=r.success,i=r.asyncInit;if(i||o)return{name:n,asyncInit:i}}throw new Error("Could not initialize any backends, all backend initializations failed.")},qt.prototype.moveData=function(t,e){var n=this.state.tensorInfo.get(e),r=n.backend,o=this.readSync(e);r.disposeData(e),(n.backend=t).move(e,o,n.shape,n.dtype),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++},qt.prototype.tidy=function(t,e){var n,r=this,o=null;if(null==e){if("function"!=typeof t)throw new Error("Please provide a function to tidy()");e=t}else{if("string"!=typeof t&&!(t instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if("function"!=typeof e)throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");o=t}return this.scopedRun(function(){return r.startScope(o)},function(){return r.endScope(n)},function(){return(n=e())instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n})},qt.prototype.scopedRun=function(t,e,n){t();try{var r=n();return e(),r}catch(t){throw e(),t}},qt.prototype.nextTensorId=function(){return qt.nextTensorId++},qt.prototype.nextVariableId=function(){return qt.nextVariableId++},qt.prototype.clone=function(t){var e=this.makeTensorFromDataId(t.dataId,t.shape,t.dtype),n={x:t};return this.addTapeNode(this.state.activeScope.name,n,[e],function(t){return{x:function(){return t.toFloat()}}},[]),e},qt.prototype.runKernel=function(t,e,n,r,o){return this.runKernelFunc(null,e,null,t,n,r,o)},qt.prototype.shouldCheckForMemLeaks=function(){return this.ENV.getBool("IS_TEST")},qt.prototype.checkKernelForMemLeak=function(t,e,n){var r=this.backend.numDataIds(),o=0;n.forEach(function(t){o+="complex64"===t.dtype?3:1});var i=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],a=r-e-o-i;if(0<a)throw new Error("Backend '"+this.backendName+"' has an internal memory leak ("+a+" data ids) after running '"+t+"'")},qt.prototype.runKernelFunc=function(n,o,t,i,a,s,u){var e,c=this;void 0===s&&(s=[]),void 0===u&&(u=[]);var r=[],l=this.isTapeOn();function h(t){l&&(r=t.map(function(t){return c.keep(c.clone(t))}))}null==i&&(i=null!=this.state.activeScope?this.state.activeScope.name:"");var f,p=this.state.numBytes,d=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);var v,m=g(i,this.backendName);return f=null!=m?function(){var t=c.backend.numDataIds();v=m.kernelFunc({inputs:o,attrs:a,backend:c.backend});var e=Array.isArray(v)?v:[v];c.shouldCheckForMemLeaks()&&c.checkKernelForMemLeak(i,t,e);var n=e.map(function(t){var e=t.dataId,n=t.shape,r=t.dtype;return c.makeTensorFromDataId(e,n,r)}),r=n.filter(function(t,e){return u[e]});return h((s||[]).slice().concat(r)),n}:function(){var t=c.backend.numDataIds();v=c.tidy(function(){return n(c.backend,h)});var e=Array.isArray(v)?v:[v];return c.shouldCheckForMemLeaks()&&c.checkKernelForMemLeak(i,t,e),e},this.scopedRun(function(){return c.state.kernelDepth++},function(){return c.state.kernelDepth--},function(){e=c.ENV.getBool("DEBUG")?c.profiler.profileKernel(i,o,function(){return f()}):f()}),l&&this.addTapeNode(i,o,e,t,r),this.state.profiling&&this.state.activeProfile.kernels.push({name:i,bytesAdded:this.state.numBytes-p,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-d,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(o).map(function(t){return o[t].shape}),outputShapes:e.map(function(t){return t.shape})}),Array.isArray(v)?e:e[0]},qt.prototype.makeTensor=function(t,e,n,r){if(null==t)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;var o=t;"string"===n&&G(t[0])&&(o=t.map(function(t){return nt(t)}));var i=r.write(o,e,n),a=new bt(e,n,i,this.nextTensorId());if(this.incRef(a,r),"string"===n){var s=this.state.tensorInfo.get(i),u=V(o);this.state.numBytes+=u-s.bytes,s.bytes=u}return a},qt.prototype.makeTensorFromDataId=function(t,e,n,r){var o=new bt(e,n=n||"float32",t,this.nextTensorId());return this.incRef(o,r),o},qt.prototype.makeVariable=function(t,e,n,r){void 0===e&&(e=!0),n=n||this.nextVariableId().toString(),null!=r&&r!==t.dtype&&(t=t.asType(r));var o=new Ft(t,e,n,this.nextTensorId());if(null!=this.state.registeredVariables[o.name])throw new Error("Variable with name "+o.name+" was already registered");return this.state.registeredVariables[o.name]=o,this.incRef(o,this.backend),o},qt.prototype.incRef=function(t,e){var n=this.state.tensorInfo.has(t.dataId)?this.state.tensorInfo.get(t.dataId).refCount:0;if(this.state.numTensors++,"string"===t.dtype&&this.state.numStringTensors++,0===n){this.state.numDataBuffers++;var r=0;"complex64"!==t.dtype&&"string"!==t.dtype&&(r=t.size*U(t.dtype)),this.state.tensorInfo.set(t.dataId,{backend:e||this.backend,dtype:t.dtype,shape:t.shape,bytes:r,refCount:0}),this.state.numBytes+=r}this.state.tensorInfo.get(t.dataId).refCount++,t instanceof Ft||this.track(t)},qt.prototype.disposeTensor=function(t){if(this.state.tensorInfo.has(t.dataId)){this.state.numTensors--,"string"===t.dtype&&this.state.numStringTensors--;var e=this.state.tensorInfo.get(t.dataId);e.refCount<=1?("complex64"!==t.dtype&&(this.state.numBytes-=e.bytes),this.state.numDataBuffers--,e.backend.disposeData(t.dataId),this.state.tensorInfo.delete(t.dataId)):this.state.tensorInfo.get(t.dataId).refCount--}},qt.prototype.disposeVariables=function(){for(var t in this.state.registeredVariables){var e=this.state.registeredVariables[t];this.disposeVariable(e)}},qt.prototype.disposeVariable=function(t){this.disposeTensor(t),null!=this.state.registeredVariables[t.name]&&delete this.state.registeredVariables[t.name]},qt.prototype.memory=function(){var t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,0<this.state.numStringTensors&&(t.unreliable=!0,null==t.reasons&&(t.reasons=[]),t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),t},qt.prototype.profile=function(r){return y(this,void 0,void 0,function(){var e,n;return R(this,function(t){return this.state.profiling=!0,e=this.state.numBytes,n=this.state.numTensors,this.state.activeProfile.kernels=[],this.state.activeProfile.result=r(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max.apply(Math,this.state.activeProfile.kernels.map(function(t){return t.totalBytesSnapshot})),this.state.activeProfile.newBytes=this.state.numBytes-e,this.state.activeProfile.newTensors=this.state.numTensors-n,[2,this.state.activeProfile]})})},qt.prototype.isTapeOn=function(){return 0<this.state.gradientDepth&&0===this.state.kernelDepth},qt.prototype.addTapeNode=function(t,e,o,n,r){var i=this,a={id:this.state.nextTapeNodeId++,kernelName:t,inputs:e,outputs:o,saved:r},s=l(t);null!=s&&(n=s.gradFunc),null!=n&&(a.gradient=function(t){return t=t.map(function(t,e){if(null!=t)return t;var n=o[e],r=Z(n.size,n.dtype);return i.makeTensor(r,n.shape,n.dtype)}),n(1<t.length?t:t[0],r)}),this.state.activeTape.push(a)},qt.prototype.keep=function(t){return t.kept=!0,t},qt.prototype.startTape=function(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++},qt.prototype.endTape=function(){this.state.gradientDepth--},qt.prototype.startScope=function(t){var e={track:[],name:"unnamed scope",id:this.state.nextScopeId++};t&&(e.name=t),this.state.scopeStack.push(e),this.state.activeScope=e},qt.prototype.endScope=function(t){for(var e=this,n=zt(t),r=new Set(n.map(function(t){return t.id})),o=0;o<this.state.activeScope.track.length;o++){var i=this.state.activeScope.track[o];i.kept||r.has(i.id)||i.dispose()}var a=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],n.forEach(function(t){t.kept||t.scopeId!==a.id||e.track(t)})},qt.prototype.gradients=function(t,o,i,e){var u=this;if(void 0===e&&(e=!1),P(0<o.length,function(){return"gradients() received an empty list of xs."}),null!=i&&"float32"!==i.dtype)throw new Error("dy must have 'float32' dtype, but has '"+i.dtype+"'");var a=this.scopedRun(function(){return u.startTape()},function(){return u.endTape()},function(){return u.tidy("forward",t)});P(a instanceof bt,function(){return"The result y returned by f() must be a tensor."});var s=function(t,e,n){for(var r={},o={},i=0;i<e.length;i++)r[e[i].id]=!0;for(i=0;i<t.length;i++){var a=(d=t[i]).inputs;for(var s in a){for(var u=a[s],c=!1,l=0;l<e.length;l++)if(r[u.id]){d.outputs.forEach(function(t){return r[t.id]=!0}),c=!0,o[d.id]=!0;break}if(c)break}}var h={};h[n.id]=!0;var 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The gradient of input '"+t+"' has shape '"+e.shape+"', which does not match the shape of the input '"+n.shape+"'");if(null==a[n.id])a[n.id]=e;else{var r=a[n.id];a[n.id]=r.add(e),r.dispose()}}var i=o.gradient(n);for(var r in o.inputs)e(r)},e=s.length-1;0<=e;e--)t(e)}(n,s);var r=o.map(function(t){return n[t.id]});return 0===u.state.gradientDepth&&(u.state.activeTape.forEach(function(t){for(var e=0,n=t.saved;e<n.length;e++)n[e].dispose()}),u.state.activeTape=null),{value:a,grads:r}})},qt.prototype.customGrad=function(r){var e=this;return P(K(r),function(){return"The f passed in customGrad(f) must be a function."}),function(){for(var i,a=[],t=0;t<arguments.length;t++)a[t]=arguments[t];P(a.every(function(t){return t instanceof bt}),function(){return"The args passed in customGrad(f)(x1, x2,...) must all be tensors"});var n={};return a.forEach(function(t,e){n[e]=t}),e.runKernelFunc(function(t,e){return P((i=r.apply(void 0,a.concat([e]))).value instanceof bt,function(){return"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"}),P(K(i.gradFunc),function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."}),i.value},n,function(t,e){var n=i.gradFunc(t,e),r=Array.isArray(n)?n:[n];P(r.length===a.length,function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."}),P(r.every(function(t){return t instanceof bt}),function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors."});var o={};return r.forEach(function(t,e){o[e]=function(){return t}}),o})}},qt.prototype.readSync=function(t){return this.state.tensorInfo.get(t).backend.readSync(t)},qt.prototype.read=function(t){return this.state.tensorInfo.get(t).backend.read(t)},qt.prototype.time=function(r){return y(this,void 0,void 0,function(){var e,n;return R(this,function(t){switch(t.label){case 0:return e=tt(),[4,this.backend.time(r)];case 1:return(n=t.sent()).wallMs=tt()-e,[2,n]}})})},qt.prototype.track=function(t){return null!=this.state.activeScope&&(t.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(t)),t},Object.defineProperty(qt.prototype,"registeredVariables",{get:function(){return this.state.registeredVariables},enumerable:!0,configurable:!0}),qt.prototype.reset=function(){for(var t in this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new Gt,this.registry)this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null},qt.nextTensorId=0,qt.nextVariableId=0,qt);function qt(t){this.ENV=t,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Gt}function jt(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null}}var Kt=function(){var t,e=function(){if(null==Ut){var t=void 0;if("undefined"!=typeof window)t=window;else if("undefined"!=typeof global)t=global;else if("undefined"!=typeof process)t=process;else{if("undefined"==typeof self)throw new Error("Could not find a global object");t=self}Ut=t}return Ut}();if(null==e._tfengine){var n=new o(e);e._tfengine=new Ht(n)}return t=e._tfengine.ENV,i=t,mt=function(){return e._tfengine},e._tfengine}();function Xt(){return"undefined"!=typeof window&&null!=window.document||"undefined"!=typeof WorkerGlobalScope}var Yt=_();Yt.registerFlag("DEBUG",function(){return!1},function(t){t&&console.warn("Debugging mode is ON. 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sampleTexture("+e+", uv);\n    }\n  "}(t);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t.shapeInfo.texShape;if(null!=o&&A(e,o)){var i=o[0],a=o[1];return"\n    float "+r+"(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2("+a+".0, "+i+".0);\n      return sampleTexture("+n+", uv);\n    }\n  "}var s=T(e),u=s.newShape,c=s.keptDims,l=u;if(l.length<e.length){var h=ii(t,l);return"\n      "+y(h)+"\n      float "+r+"(int row, int col) {\n        return "+r+"("+ai(["row","col"],c)+");\n      }\n    "}if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col) {\n        int index = round(dot(vec2(row, col), vec2("+e[1]+", 1)));\n        "+ri(t)+"\n      }\n    ";var f=o[0],p=o[1],d=ni(n);return 1===p?"\n    float "+r+"(int row, int col) {\n      float index = dot(vec3(row, col, "+d+"), vec3("+e[1]+", 1, 1));\n      vec2 uv = vec2(0.5, (index + 0.5) / "+f+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ":1===f?"\n    float "+r+"(int row, int col) {\n      float index = dot(vec3(row, col, "+d+"), vec3("+e[1]+", 1, 1));\n      vec2 uv = vec2((index + 0.5) / "+p+".0, 0.5);\n      return sampleTexture("+n+", uv);\n    }\n  ":"\n  float "+r+"(int row, int col) {\n    // Explicitly use integer operations as dot() only works on floats.\n    int index = row * "+e[1]+" + col + "+d+";\n    vec2 uv = uvFromFlat("+f+", "+p+", index);\n    return sampleTexture("+n+", uv);\n  }\n"}(t);case 3:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[1]*e[2],i=e[2],a=T(e),s=a.newShape,u=a.keptDims,c=s;if(c.length<e.length){var l=ii(t,c);return"\n        "+y(l)+"\n        float "+r+"(int row, int col, int depth) {\n          return "+r+"("+ai(["row","col","depth"],u)+");\n        }\n      "}if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col, int depth) {\n        int index = round(dot(vec3(row, col, depth),\n                          vec3("+o+", "+i+", 1)));\n        "+ri(t)+"\n      }\n    ";var h=t.shapeInfo.texShape,f=h[0],p=h[1],d=t.shapeInfo.flatOffset;if(p===o&&null==d)return"\n        float "+r+"(int row, int col, int depth) {\n          float texR = float(row);\n          float texC = dot(vec2(col, depth), vec2("+i+", 1));\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2("+p+".0, "+f+".0);\n          return sampleTexture("+n+", uv);\n        }\n      ";if(p===i&&null==d)return"\n    float "+r+"(int row, int col, int depth) {\n      float texR = dot(vec2(row, col), vec2("+e[1]+", 1));\n      float texC = float(depth);\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+p+".0, "+f+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ";var v=ni(n);return"\n      float "+r+"(int row, int col, int depth) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * "+o+" + col * "+i+" + depth + "+v+";\n        vec2 uv = uvFromFlat("+f+", "+p+", index);\n        return sampleTexture("+n+", uv);\n      }\n  "}(t);case 4:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[3],i=e[2]*o,a=e[1]*i,s=T(e),u=s.newShape,c=s.keptDims;if(u.length<e.length){var l=ii(t,u);return"\n      "+y(l)+"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        return "+r+"("+ai(["row","col","depth","depth2"],c)+");\n      }\n    "}if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        int index = round(dot(vec4(row, col, depth, depth2),\n                          vec4("+a+", "+i+", "+o+", 1)));\n        "+ri(t)+"\n      }\n    ";var h=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,p=f[0],d=f[1];if(d===a&&null==h)return"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3("+i+", "+o+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+d+".0, "+p+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(d===o&&null==h)return"\n      float "+r+"(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3("+e[1]*e[2]+", "+e[2]+", 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+d+".0, "+p+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var v=ni(n);return"\n    float "+r+"(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+a+" + col * "+i+" +\n          depth * "+o+" + depth2;\n      vec2 uv = uvFromFlat("+p+", "+d+", index + "+v+");\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);case 5:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=e[4],i=e[3]*o,a=e[2]*i,s=e[1]*a,u=T(e),c=u.newShape,l=u.keptDims;if(c.length<e.length){var h=ii(t,c);return"\n      "+y(h)+"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        return "+r+"("+ai(["row","col","depth","depth2","depth3"],l)+");\n      }\n    "}if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        float index = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+s+", "+a+", "+i+", "+o+")) +\n          depth3;\n        "+ri(t)+"\n      }\n    ";var f=t.shapeInfo.flatOffset,p=t.shapeInfo.texShape,d=p[0],v=p[1];if(v===s&&null==f)return"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n                         vec4("+a+", "+i+", "+o+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+v+".0, "+d+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(v===o&&null==f)return"\n      float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n        float texR = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+e[1]*e[2]*e[3]+",\n               "+e[2]*e[3]+", "+e[3]+", 1));\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+v+".0, "+d+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var m=ni(n);return"\n    float "+r+"(int row, int col, int depth, int depth2, int depth3) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+s+" + col * "+a+" + depth * "+i+" +\n          depth2 * "+o+" + depth3 + "+m+";\n      vec2 uv = uvFromFlat("+d+", "+v+", index);\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);case 6:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),o=T(e),i=o.newShape,a=o.keptDims;if(i.length<e.length){var s=ii(t,i);return"\n      "+y(s)+"\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        return "+r+"("+ai(["row","col","depth","depth2","depth3","depth4"],a)+");\n      }\n    "}var u=e[5],c=e[4]*u,l=e[3]*c,h=e[2]*l,f=e[1]*h;if(t.shapeInfo.isUniform)return"\n      float "+r+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n        int index = round(dot(\n          vec4(row, col, depth, depth2),\n          vec4("+f+", "+h+", "+l+", "+c+")) +\n          dot(\n            vec2(depth3, depth4),\n            vec2("+u+", 1)));\n        "+ri(t)+"\n      }\n    ";var p=t.shapeInfo.flatOffset,d=t.shapeInfo.texShape,v=d[0],m=d[1];if(m===f&&null==p)return"\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n          vec4("+h+", "+l+", "+c+", "+u+")) +\n               float(depth4);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+m+".0, "+v+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";if(m===u&&null==p)return"\n      float "+r+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        float texR = dot(vec4(row, col, depth, depth2),\n          vec4("+e[1]*e[2]*e[3]*e[4]+",\n               "+e[2]*e[3]*e[4]+",\n               "+e[3]*e[4]+",\n               "+e[4]+")) + float(depth3);\n        int texC = depth4;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+m+".0, "+v+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ";var g=ni(n);return"\n    float "+r+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+f+" + col * "+h+" + depth * "+l+" +\n          depth2 * "+c+" + depth3 * "+u+" + depth4 + "+g+";\n      vec2 uv = uvFromFlat("+v+", "+m+", index);\n      return sampleTexture("+n+", uv);\n    }\n  "}(t);default:throw new Error(e.length+"-D input sampling is not yet supported")}}(t);var o=t.shapeInfo.logicalShape,i=e.logicalShape;return o.length<=i.length&&(r+=n?function(t,e){var n,r=t.name,o=r.charAt(0).toUpperCase()+r.slice(1),i="get"+o+"AtOutCoords",a=t.shapeInfo.logicalShape.length,s=e.logicalShape.length,u=vo(t.shapeInfo.logicalShape,e.logicalShape),c=oi(s),l=s-a,h=["x","y","z","w","u","v"];n=0===a?"":s<2&&1<=u.length?"coords = 0;":u.map(function(t){return"coords."+h[t+l]+" = 0;"}).join("\n");var f;f=s<2&&0<a?"coords":t.shapeInfo.logicalShape.map(function(t,e){return"coords."+h[e+l]}).join(", ");var p="return outputValue;",d=1===L(t.shapeInfo.logicalShape),v=1===L(e.logicalShape);if(1!==a||d||v){if(d&&!v)p=1===s?"\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\n      ":"\n        return vec4(outputValue.x);\n      ";else if(u.length){var m=a-2,g=a-1;-1<u.indexOf(m)&&-1<u.indexOf(g)?p="return vec4(outputValue.x);":-1<u.indexOf(m)?p="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":-1<u.indexOf(g)&&(p="return vec4(outputValue.xx, outputValue.zz);")}}else p="\n      return vec4(outputValue.xy, outputValue.xy);\n    ";return"\n    vec4 "+i+"() {\n      "+c+" coords = getOutputCoords();\n      "+n+"\n      vec4 outputValue = get"+o+"("+f+");\n      "+p+"\n    }\n  "}(t,e):function(t,e){var n=t.name,r=n.charAt(0).toUpperCase()+n.slice(1),o="get"+r+"AtOutCoords",i=e.texShape,a=t.shapeInfo.texShape,s=t.shapeInfo.logicalShape.length,u=e.logicalShape.length;if(!t.shapeInfo.isUniform&&s===u&&null==t.shapeInfo.flatOffset&&A(a,i))return"\n      float "+o+"() {\n        return sampleTexture("+n+", resultUV);\n      }\n    ";var c=oi(u),l=vo(t.shapeInfo.logicalShape,e.logicalShape),h=u-s,f=["x","y","z","w","u","v"];return"\n    float "+o+"() {\n      "+c+" coords = getOutputCoords();\n      "+(0===s?"":u<2&&1<=l.length?"coords = 0;":l.map(function(t){return"coords."+f[t+h]+" = 0;"}).join("\n"))+"\n      return get"+r+"("+(u<2&&0<s?"coords":t.shapeInfo.logicalShape.map(function(t,e){return"coords."+f[e+h]}).join(", "))+");\n    }\n  "}(t,e)),r}(t,e,r)}).join("\n"),l=e.texShape,h=Jo(),f="\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return "+h.texture2D+"(textureSampler, uv).r;\n    }\n  ",p=(s=h).version+"\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    "+s.varyingFs+" vec2 resultUV;\n    "+s.defineOutput+"\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    uniform float NAN;\n    "+s.defineSpecialNaN+"\n    "+s.defineSpecialInf+"\n    "+s.defineRound+"\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    int idiv(int a, int b, float sign) {\n      int res = a / b;\n      int mod = imod(a, b);\n      if (sign < 0. && mod != 0) {\n        res -= 1;\n      }\n      return res;\n    }\n\n    //Based on the work of Dave Hoskins\n    //https://www.shadertoy.com/view/4djSRW\n    #define HASHSCALE1 443.8975\n    float random(float seed){\n      vec2 p = resultUV * seed;\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n      p3 += dot(p3, p3.yzx + 19.19);\n      return fract((p3.x + p3.y) * p3.z);\n    }\n\n    \nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n    \nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n    \nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n  ";return a=e.isPacked?(i=function(t,e){switch(t.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return n=e,1===(r=[Math.ceil(n[0]/2),Math.ceil(n[1]/2)])[0]?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * "+r[1]+".0);\n      }\n    ":1===r[1]?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * "+r[0]+".0);\n      }\n    ":"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+r[0]+", "+r[1]+"));\n      return 2 * (resTexRC.x * "+r[1]+" + resTexRC.y);\n    }\n  ";case 2:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(A(t,e))return"\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2("+n[0]+", "+n[1]+"));\n      }\n    ";var r=Math.ceil(t[1]/2);return"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec2(r, c);\n    }\n  "}(t,e);case 3:return o=t,i=e,a=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],u=(s=Math.ceil(o[2]/2))*Math.ceil(o[1]/2),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+a[0]+", "+a[1]+"));\n      int index = resTexRC.x * "+a[1]+" + resTexRC.y;\n\n      int b = index / "+u+";\n      index -= b * "+u+";\n\n      int r = 2 * (index / "+s+");\n      int c = imod(index, "+s+") * 2;\n\n      return ivec3(b, r, c);\n    }\n  ";default:return function(t,e){for(var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],r=Math.ceil(t[t.length-1]/2),o=r*Math.ceil(t[t.length-2]/2),i=o,a="",s="b, r, c",u=2;u<t.length-1;u++)a="\n      int b"+u+" = index / "+(i*=t[t.length-u-1])+";\n      index -= b"+u+" * "+i+";\n    "+a,s="b"+u+", "+s;return"\n    ivec"+t.length+" getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n\n      "+a+"\n\n      int b = index / "+o+";\n      index -= b * "+o+";\n\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec"+t.length+"("+s+");\n    }\n  "}(t,e)}var n,r,o,i,a,s,u}(e.logicalShape,l),"\n    void setOutput(vec4 val) {\n      "+h.output+" = val;\n    }\n  "):(i=function(t,e){switch(t.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return 1===(l=e)[0]?"\n      int getOutputCoords() {\n        return int(resultUV.x * "+l[1]+".0);\n      }\n    ":1===l[1]?"\n      int getOutputCoords() {\n        return int(resultUV.y * "+l[0]+".0);\n      }\n    ":"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+l[0]+", "+l[1]+"));\n      return resTexRC.x * "+l[1]+" + resTexRC.y;\n    }\n  ";case 2:return A(u=t,c=e)?"\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2("+c[0]+", "+c[1]+"));\n      }\n    ":1===u[1]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+c[0]+", "+c[1]+"));\n        int index = resTexRC.x * "+c[1]+" + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ":1===u[0]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+c[0]+", "+c[1]+"));\n        int index = resTexRC.x * "+c[1]+" + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ":"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+c[0]+", "+c[1]+"));\n      int index = resTexRC.x * "+c[1]+" + resTexRC.y;\n      int r = index / "+u[1]+";\n      int c = index - r * "+u[1]+";\n      return ivec2(r, c);\n    }\n  ";case 3:return h=e,f=Qo(["r","c","d"],t),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+h[0]+", "+h[1]+"));\n      int index = resTexRC.x * "+h[1]+" + resTexRC.y;\n      "+f+"\n      return ivec3(r, c, d);\n    }\n  ";case 4:return a=e,s=Qo(["r","c","d","d2"],t),"\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+a[0]+", "+a[1]+"));\n      int index = resTexRC.x * "+a[1]+" + resTexRC.y;\n      "+s+"\n      return ivec4(r, c, d, d2);\n    }\n  ";case 5:return o=e,i=Qo(["r","c","d","d2","d3"],t),"\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2("+o[0]+",\n                             "+o[1]+"));\n\n      int index = resTexRC.x * "+o[1]+" + resTexRC.y;\n\n      "+i+"\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  ";case 6:return n=e,r=Qo(["r","c","d","d2","d3","d4"],t),"\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n\n      "+r+"\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  ";default:throw new Error(t.length+"-D output sampling is not yet supported")}var n,r,o,i,a,s,u,c,l,h,f}(e.logicalShape,l),"\n    void setOutput(float val) {\n      "+h.output+" = vec4(val, 0, 0, 0);\n    }\n  "),r&&(p+="\n  float getChannel(vec4 frag, vec2 innerDims) {\n    vec2 modCoord = mod(innerDims, 2.);\n    return modCoord.x == 0. ?\n      (modCoord.y == 0. ? frag.r : frag.g) :\n      (modCoord.y == 0. ? frag.b : frag.a);\n  }\n  float getChannel(vec4 frag, int dim) {\n    float modCoord = mod(float(dim), 2.);\n    return modCoord == 0. ? frag.r : frag.g;\n  }\n"),[p,f,a,u,i,c,n].join("\n")}function ni(t){return"offset"+t}function ri(t){var e=t.name,n=L(t.shapeInfo.logicalShape);return n<2?"return "+e+";":"\n    for (int i = 0; i < "+n+"; i++) {\n      if (i == index) {\n        return "+e+"[i];\n      }\n    }\n  "}function oi(t){if(t<=1)return"int";if(2===t)return"ivec2";if(3===t)return"ivec3";if(4===t)return"ivec4";if(5===t)return"ivec5";if(6===t)return"ivec6";throw Error("GPU for rank "+t+" is not yet supported")}function ii(t,e){var n=JSON.parse(JSON.stringify(t));return n.shapeInfo.logicalShape=e,n}function ai(e,t){return t.map(function(t){return e[t]}).join(", ")}function si(t,e,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,P(2<t.length,function(){return"Packed arg"+(n.charAt(0).toUpperCase()+n.slice(1))+" supports only inputs with rank above 2."});var o=t[t.length-1],i=Math.ceil(o/e);this.outputShape=t.slice(0,-1),1<i&&this.outputShape.push(i),r||this.variableNames.push("bestIndicesA");var a,s,u=this.outputShape,c=u.length,l=oi(c),h=$o("coords",c);if(1===i){var f=oi(s=c+1);a="\n        "+f+" sourceLocR = "+f+"("+h.join()+", 0);\n        ++"+h[c-1]+";\n        "+f+" sourceLocG = "+f+"("+h.join()+", 0);\n        ++"+h[c-2]+";\n        "+f+" sourceLocA = "+f+"("+h.join()+", 0);\n        --"+h[c-1]+";\n        "+f+" sourceLocB = "+f+"("+h.join()+", 0);\n        --"+h[c-2]+";"}else a="\n        "+l+" sourceLocR = coords;\n        ++"+h[(s=c)-1]+";\n        "+l+" sourceLocG = coords;\n        ++"+h[c-2]+";\n        "+l+" sourceLocA = coords;\n        --"+h[c-1]+";\n        "+l+" sourceLocB = coords;\n        --"+h[c-2]+";";var p=["x","y","z","w","u","v"].slice(0,s),d="."+p[s-1],v=p.map(function(t){return"int "+t}),m=$o("sourceLocR",s-1).concat("inIdx.r"),g=$o("sourceLocG",s-1).concat("inIdx.g"),y=$o("sourceLocB",s-1).concat("inIdx.b"),x=$o("sourceLocA",s-1).concat("inIdx.a"),b="max"===n?"greaterThan":"lessThan",w=r?"":"\n          inIdx = round(vec4(getBestIndicesAChannel("+m.join()+"),\n                             getBestIndicesAChannel("+g.join()+"),\n                             getBestIndicesAChannel("+y.join()+"),\n                             getBestIndicesAChannel("+x.join()+")));",C="vec4(\n            getAChannel("+m.join()+"),\n            hasNextCol ? getAChannel("+g.join()+") : 0.,\n            hasNextRow ? getAChannel("+y.join()+") : 0.,\n            hasNextRow && hasNextCol ? getAChannel("+x.join()+") : 0.)",E=r?"":"\n      float getBestIndicesAChannel("+v.join()+") {\n        return getChannel(getBestIndicesA("+p.join()+"),\n                                          vec2("+p.slice(-2).join()+"));\n      }";this.userCode="\n      float getAChannel("+v.join()+") {\n        return getChannel(getA("+p.join()+"),\n                               vec2("+p.slice(-2).join()+"));\n      }\n      "+E+"\n      void main() {\n        "+l+" coords = getOutputCoords();\n        bool hasNextCol = "+h[c-1]+" < "+(u[c-1]-1)+";\n        bool hasNextRow = "+h[c-2]+" < "+(u[c-2]-1)+";\n        "+a+"\n        ivec4 srcIdx = ivec4(sourceLocR"+d+", sourceLocG"+d+",\n          sourceLocB"+d+", sourceLocA"+d+") * "+e+";\n        ivec4 inIdx = srcIdx;\n        vec4 bestIndex = vec4(inIdx);\n        vec4 bestValue = "+C+";\n\n        for (int i = 0; i < "+e+"; i++) {\n          inIdx = srcIdx;\n          "+w+"\n          vec4 candidate = "+C+";\n          bvec4 nan = isnan(candidate);\n          bvec4 replace = bvec4(\n            vec4("+b+"(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\n                           replace.y  ? candidate.y : bestValue.y,\n                           replace.z  ? candidate.z : bestValue.z,\n                           replace.w  ? candidate.w : bestValue.w);\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n          srcIdx++;\n        }\n        setOutput(bestIndex);\n      }\n    "}function ui(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,i=t.dilationHeight,a=t.dilationWidth,s=t.effectiveFilterHeight,u=t.effectiveFilterWidth,c=s-1-t.padInfo.top,l=u-1-t.padInfo.left,h=1/(e*n);this.userCode="\n      const ivec2 pads = ivec2("+c+", "+l+");\n      const float avgMultiplier = float("+h+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+s+";\n            wR += "+i+") {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+u+";\n            wC+= "+a+") {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function ci(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,i=t.strideHeight,a=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,p=l-1-t.padInfo.front,d=h-1-t.padInfo.top,v=f-1-t.padInfo.left,m=1/(e*n*r);this.userCode="\n      const ivec3 pads = ivec3("+p+", "+d+", "+v+");\n      const float avgMultiplier = float("+m+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+l+";\n            wD += "+s+") {\n          float dyD = float(dyDCorner + wD) / "+o+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+h+";\n              wR += "+u+") {\n            float dyR = float(dyRCorner + wR) / "+i+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+f+";\n                wC += "+c+") {\n              float dyC = float(dyCCorner + wC) / "+a+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function li(t,e,n,r,o,i){this.outputShape=[],this.variableNames=["x","mean","variance"],go(t,e),go(t,n);var a="0.0";null!=r&&(go(t,r),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");var s="1.0";null!=o&&(go(t,o),this.variableNames.push("scale"),s="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = "+a+";\n        float scale = "+s+";\n        float inv = scale * inversesqrt(variance + float("+i+"));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    "}function hi(t,e,n,r,o,i){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],go(t,e),go(t,n);var a="vec4(0.0)";null!=r&&(go(t,r),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");var s="vec4(1.0)";null!=o&&(go(t,o),this.variableNames.push("scale"),s="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        vec4 offset = "+a+";\n        vec4 scale = "+s+";\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4("+i+"));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    "}function fi(t,e,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=go(e,n),this.userCode="\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        "+t+"\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    "}function pi(t,e,n){this.variableNames=["A","B"],this.outputShape=go(e,n),this.userCode="\n      float binaryOperation(float a, float b) {\n        "+t+"\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    "}function di(t,e,n,r){void 0===r&&(r=!1),this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=go(e,n);var o=this.outputShape.length,i="";if(r)if(0===o||1===L(this.outputShape))i="\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        ";else if(i="\n          "+oi(o)+" coords = getOutputCoords();\n        ",1===o)i+="\n            result.y = (coords + 1) >= "+this.outputShape[0]+" ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          ";else{var a=$o("coords",o);i+="\n            bool nextRowOutOfBounds =\n              ("+a[o-2]+" + 1) >= "+this.outputShape[o-2]+";\n            bool nextColOutOfBounds =\n              ("+a[o-1]+" + 1) >= "+this.outputShape[o-1]+";\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          "}this.userCode="\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        "+t+"\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        "+i+"\n\n        setOutput(result);\n      }\n    "}function vi(t){this.variableNames=["real","imag"],this.outputShape=t,this.userCode="\n      void main() {\n        float re = abs(getRealAtOutCoords());\n        float im = abs(getImagAtOutCoords());\n        float mx = max(re, im);\n\n        // sadly the length function in glsl is not underflow-safe\n        // (at least not on Intel GPUs). So the safe solution is\n        // to ensure underflow-safety in all cases.\n        setOutput(\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\n        );\n      }\n    "}function mi(t){this.outputShape=[],this.outputShape=bn(t,1),this.variableNames=t.map(function(t,e){return"T"+e});var e=new Array(t.length-1);e[0]=t[0][1];for(var n=1;n<e.length;n++)e[n]=e[n-1]+t[n][1];var r=["if (yC < "+e[0]+") setOutput(getT0(yR, yC));"];for(n=1;n<e.length;n++){var o=e[n-1];r.push("else if (yC < "+e[n]+") setOutput(getT"+n+"(yR, yC-"+o+"));")}var i=e.length,a=e[e.length-1];r.push("else setOutput(getT"+i+"(yR, yC-"+a+"));"),this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        "+r.join("\n        ")+"\n      }\n    "}function gi(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=bn(t,e);var n=this.outputShape,r=n.length,o=oi(r),i=$o("coords",r),a=["x","y","z","w","u","v"].slice(0,r);this.variableNames=t.map(function(t,e){return"T"+e});var s=new Array(t.length-1);s[0]=t[0][e];for(var u=1;u<s.length;u++)s[u]=s[u-1]+t[u][e];var c=a[e],l=a.slice(-2),h=a.join(),f="if ("+c+" < "+s[0]+") {\n        return getChannel(\n            getT0("+h+"), vec2("+l.join()+"));\n        }";for(u=1;u<s.length;u++){var p=s[u-1];f+="\n        if ("+c+" < "+s[u]+"  && "+c+" >= "+s[u-1]+") {\n          return getChannel(\n            getT"+u+"("+ki(a,c,p)+"),\n            vec2("+ki(l,c,p)+"));\n        }"}var d=s.length,v=s[s.length-1];f+="\n        return getChannel(\n          getT"+d+"("+ki(a,c,v)+"),\n          vec2("+ki(l,c,v)+"));",this.userCode="\n      float getValue("+a.map(function(t){return"int "+t})+") {\n        "+f+"\n      }\n\n      void main() {\n        "+o+" coords = getOutputCoords();\n        vec4 result = vec4(getValue("+i+"), 0., 0., 0.);\n\n        "+i[r-1]+" = "+i[r-1]+" + 1;\n        if ("+i[r-1]+" < "+n[r-1]+") {\n          result.g = getValue("+i+");\n        }\n\n        "+i[r-2]+" = "+i[r-2]+" + 1;\n        if ("+i[r-2]+" < "+n[r-2]+") {\n          result.a = getValue("+i+");\n        }\n\n        "+i[r-1]+" = "+i[r-1]+" - 1;\n        if ("+i[r-2]+" < "+n[r-2]+" &&\n            "+i[r-1]+" < "+n[r-1]+") {\n          result.b = getValue("+i+");\n        }\n        setOutput(result);\n      }\n    "}var yi="return a + b;",xi="return a - b;",bi="return a * b;",wi="return (a < 0.) ? b * a : a;",Ci="\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n",Ei=(Ri.prototype.getCustomSetupFunc=function(n,r){var o=this;return function(t,e){null==o.minLoc&&(o.minLoc=t.getUniformLocationNoThrow(e,"minVal"),o.maxLoc=t.getUniformLocationNoThrow(e,"maxVal")),t.gl.uniform1f(o.minLoc,n),t.gl.uniform1f(o.maxLoc,r)}},Ri),_i=(Ii.prototype.getCustomSetupFunc=function(n,r){var o=this;return function(t,e){null==o.minLoc&&(o.minLoc=t.getUniformLocationNoThrow(e,"minVal"),o.maxLoc=t.getUniformLocationNoThrow(e,"maxVal")),t.gl.uniform1f(o.minLoc,n),t.gl.uniform1f(o.maxLoc,r)}},Ii);function Ii(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        vec4 value = getAAtOutCoords();\n\n        if (any(isnan(value))) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\n      }\n    "}function Ri(t){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    "}function ki(t,e,n){var r=t.indexOf(e);return t.map(function(t,e){return e===r?t+" - "+n:t}).join()}function Si(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,i="channelsLast"===t.dataFormat;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+o+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              if ("+i+") {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function Di(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,i="channelsLast"===t.dataFormat,a=e-1-t.padInfo.top,s=n-1-t.padInfo.left,u=i?1:2,c=i?2:3,l=i?3:1;this.userCode="\n      const ivec2 pads = ivec2("+a+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords["+l+"];\n\n        ivec2 dyCorner = ivec2(coords["+u+"], coords["+c+"]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n\n              if ("+i+") {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function Ai(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.padInfo.front,i=t.padInfo.top,a=t.padInfo.left;this.userCode="\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yF = 0; yF < "+t.outDepth+"; yF++) {\n            int xF = wF + yF * "+e+" - "+o+";\n\n            if (xF < 0 || xF >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n              int xR = wR + yR * "+n+" - "+i+";\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n                int xC = wC + yC * "+r+" - "+a+";\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function Ti(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,o=t.strideDepth,i=t.strideHeight,a=t.strideWidth,s=e-1-t.padInfo.front,u=n-1-t.padInfo.top,c=r-1-t.padInfo.left;this.userCode="\n      const ivec3 pads = ivec3("+s+", "+u+", "+c+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+e+"; wF++) {\n          float dyF = float(dyFCorner + wF) / "+o+".0;\n\n          if (dyF < 0.0 || dyF >= "+t.outDepth+".0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = "+e+" - 1 - wF;\n\n          for (int wR = 0; wR < "+n+"; wR++) {\n            float dyR = float(dyRCorner + wR) / "+i+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = "+n+" - 1 - wR;\n\n            for (int wC = 0; wC < "+r+"; wC++) {\n              float dyC = float(dyCCorner + wC) / "+a+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = "+r+" - 1 - wC;\n\n              for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function Ni(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,o=t.padInfo.left,i=t.outChannels/t.inChannels;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * "+i+" + dm;\n\n        float dotProd = 0.0;\n\n        // TO DO: Vec4 over the batch size\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+o+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function Fi(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,o=t.strideWidth,i=e-1-t.padInfo.top,a=n-1-t.padInfo.left,s=t.outChannels/t.inChannels;this.userCode="\n      const ivec2 pads = ivec2("+i+", "+a+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+o+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < "+s+"; dm++) {\n              int d2 = d1 * "+s+" + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function Mi(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.outputShape=t.outShape;var o=t.padInfo.top,i=t.padInfo.left,a=t.strideHeight,s=t.strideWidth,u=t.dilationHeight,c=t.dilationWidth,l=t.filterHeight,h=t.filterWidth,f=4*Math.floor(t.inChannels/4),p=t.inChannels%4,d="channelsLast"===t.dataFormat,v=d?1:2,m=d?2:3,g=d?3:1,y="",x="";n&&(y=r?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"\n          float activation(float x) {\n            "+n+"\n          }\n        ",x="result = activation(result);");var b=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+y+"\n\n      const ivec2 strides = ivec2("+a+", "+s+");\n      const ivec2 pads = ivec2("+o+", "+i+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords["+g+"];\n\n        ivec2 xRCCorner =\n            ivec2(coords["+v+"], coords["+m+"]) * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+l+"; wR++) {\n          int xR = xRCorner + wR * "+u+";\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+h+"; wC++) {\n            int xC = xCCorner + wC * "+c+";\n\n            if (xC < 0 || xC >= "+t.inWidth+") {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < "+f+"; d1 += 4) {\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              if ("+d+") {\n                vec4 xValues = vec4(\n                  getX(batch, xR, xC, d1),\n                  getX(batch, xR, xC, d1 + 1),\n                  getX(batch, xR, xC, d1 + 2),\n                  getX(batch, xR, xC, d1 + 3)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec4 xValues = vec4(\n                  getX(batch, d1, xR, xC),\n                  getX(batch, d1 + 1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if ("+(1==p)+") {\n\n              if ("+d+") {\n                dotProd +=\n                    getX(batch, xR, xC, "+f+") *\n                    getW(wR, wC, "+f+", d2);\n              } else {\n                dotProd +=\n                    getX(batch, "+f+", xR, xC) *\n                    getW(wR, wC, "+f+", d2);\n              }\n\n            } else if ("+(2==p)+") {\n              vec2 wValues = vec2(\n                getW(wR, wC, "+f+", d2),\n                getW(wR, wC, "+f+" + 1, d2)\n              );\n\n              if ("+d+") {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, "+f+"),\n                  getX(batch, xR, xC, "+f+" + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, "+f+", xR, xC),\n                  getX(batch, "+f+" + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if ("+(3==p)+") {\n              vec3 wValues = vec3(\n                getW(wR, wC, "+f+", d2),\n                getW(wR, wC, "+f+" + 1, d2),\n                getW(wR, wC, "+f+" + 2, d2)\n              );\n\n              if ("+d+") {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, "+f+"),\n                  getX(batch, xR, xC, "+f+" + 1),\n                  getX(batch, xR, xC, "+f+" + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, "+f+", xR, xC),\n                  getX(batch, "+f+" + 1, xR, xC),\n                  getX(batch, "+f+" + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        "+b+"\n        "+x+"\n        setOutput(result);\n      }\n    "}function Oi(t){this.variableNames=["x","W"],this.outputShape=t.outShape;var e=t.padInfo.front,n=t.padInfo.top,r=t.padInfo.left,o=t.strideDepth,i=t.strideHeight,a=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.filterDepth,h=t.filterHeight,f=t.filterWidth,p=4*Math.floor(t.inChannels/4),d=t.inChannels%4;this.userCode="\n      const ivec3 strides = ivec3("+o+", "+i+", "+a+");\n      const ivec3 pads = ivec3("+e+", "+n+", "+r+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+l+"; wF++) {\n          int xF = xFCorner + wF * "+s+";\n\n          if (xF < 0 || xF >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+h+"; wR++) {\n            int xR = xRCorner + wR * "+u+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+f+"; wC++) {\n              int xC = xCCorner + wC * "+c+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < "+p+"; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if ("+(1==d)+") {\n                dotProd +=\n                  getX(batch, xF, xR, xC, "+p+") *\n                  getW(wF, wR, wC, "+p+", d2);\n              } else if ("+(2==d)+") {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, "+p+"),\n                  getX(batch, xF, xR, xC, "+p+" + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, "+p+", d2),\n                  getW(wF, wR, wC, "+p+" + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if ("+(3==d)+") {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, "+p+"),\n                  getX(batch, xF, xR, xC, "+p+" + 1),\n                  getX(batch, xF, xR, xC, "+p+" + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, "+p+", d2),\n                  getW(wF, wR, wC, "+p+" + 1, d2),\n                  getW(wF, wR, wC, "+p+" + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function Pi(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.outputShape=t.outShape;var o=t.inHeight,i=t.inWidth,a=t.padInfo.top,s=t.padInfo.left,u=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,p=t.filterWidth,d=t.outChannels/t.inChannels,v="",m="";n&&(v=r?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"\n          float activation(float x) {\n            "+n+"\n          }\n        ",m="result = activation(result);");var g=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+v+"\n\n      const ivec2 strides = ivec2("+u+", "+c+");\n      const ivec2 pads = ivec2("+a+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / "+d+";\n        int q = d2 - d1 * "+d+";\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < "+f+"; wR++) {\n          int xR = xRCorner + wR * "+l+";\n\n          if (xR < 0 || xR >= "+o+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+p+"; wC++) {\n            int xC = xCCorner + wC * "+h+";\n\n            if (xC < 0 || xC >= "+i+") {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n\n        float result = dotProd;\n        "+g+"\n        "+m+"\n        setOutput(result);\n      }\n    "}function Bi(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.outShape;for(var o=t.inHeight,i=t.inWidth,a=t.padInfo.top,s=t.padInfo.left,u=t.strideHeight,c=t.strideWidth,l=t.dilationHeight,h=t.dilationWidth,f=t.filterHeight,p=t.filterWidth,d=p,v="int xR; int xC; int xCOffset;",m=0;m<f;m++)for(var g=0;g<p;g++)v+="\n          vec4 xTexelR"+m+"C"+2*g+" = vec4(0.);\n          vec4 wR"+m+"C"+g+" = vec4(0.);\n          vec4 xR"+m+"C"+g+" = vec4(0.);";for(m=0;m<f;m++)for(var y=0;y<d;y++){if(v+="\n          xR = xRCorner + "+m*l+";\n          xC = xCCorner + "+(g=2*y)*h+";\n        ",1===c){if(g<p&&(v+=s%2==1?"\n                xCOffset = xC + 1;\n                if(xR >= 0 && xR < "+o+" && xCOffset >= 0 && xCOffset < "+i+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if(xCOffset + 1 >= "+i+") {\n                    xTexelR"+m+"C"+g+".zw = vec2(0.);\n                  }\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                xCOffset = xC + 1 - 2;\n                if(xR >= 0 && xR < "+o+" && xCOffset >= 0 && xCOffset < "+i+") {\n                  vec4 previous = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if(xCOffset + 1 >= "+i+") {\n                    previous.zw = vec2(0.);\n                  }\n\n                  xR"+m+"C"+g+" = vec4(previous.zw, xTexelR"+m+"C"+g+".xy);\n                } else {\n                  xR"+m+"C"+g+" = vec4(0, 0, xTexelR"+m+"C"+g+".xy);\n                }\n              ":"\n                if(xR >= 0 && xR < "+o+" && xC >= 0 && xC < "+i+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                xR"+m+"C"+g+" = xTexelR"+m+"C"+g+";\n              ",g+1<p)){var x=s%2==0?E(h):h;h%2==0&&s%2==1||h%2!=0&&s%2!=1?(v+="\n                  xCOffset = xC + "+s%2+" + "+x+";\n\n                  if(xR >= 0 && xR < "+o+" &&\n                    xCOffset >= 0 && xCOffset < "+i+") {\n                    xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n                ",1<h&&(v+="\n                    xCOffset -= 2;\n                    if(xR >= 0 && xR < "+o+" &&\n                      xCOffset >= 0 && xCOffset < "+i+") {\n                      xTexelR"+m+"C"+g+" = getX(batch, xR, xCOffset, d1);\n                    } else {\n                      xTexelR"+m+"C"+g+" = vec4(0.);\n                    }\n                  "),v+="\n                  xR"+m+"C"+(g+1)+" = vec4(\n                    xTexelR"+m+"C"+g+".zw, xTexelR"+m+"C"+(g+2)+".xy);\n                "):v+="\n                  xCOffset = xC + "+x+";\n\n                  if(xR >= 0 && xR < "+o+" &&\n                    xCOffset >= 0 && xCOffset < "+i+") {\n                    xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n\n                  xR"+m+"C"+(g+1)+" = xTexelR"+m+"C"+(g+2)+";\n                "}}else g<p&&(v+="\n              if(xR >= 0 && xR < "+o+") {\n            ",s%2==1?(v+="\n                xCOffset = xC + 1 - "+c+";\n                if(xCOffset >= 0 && xCOffset < "+i+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < "+i+") {\n                  xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xC + 1, d1);\n                } else {\n                  xTexelR"+m+"C"+(g+2)+" = vec4(0.);\n                }\n\n                xR"+m+"C"+g+" = vec4(\n                  xTexelR"+m+"C"+g+".zw, xTexelR"+m+"C"+(g+2)+".zw);\n              ",g+1<p&&(v+="\n                  vec4 final = vec4(0.);\n                  xCOffset = xC + 1 + "+c+";\n                  if(xCOffset >= 0 && xCOffset < "+i+") {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xR"+m+"C"+(g+1)+" = vec4(xTexelR"+m+"C"+(g+2)+".xy, final.xy);\n                ")):(v+="\n                if(xC >= 0 && xC < "+i+") {\n                  xTexelR"+m+"C"+g+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+m+"C"+g+" = vec4(0.);\n                }\n\n                xCOffset = xC + "+c+";\n                if(xCOffset >= 0 && xCOffset < "+i+") {\n                  xTexelR"+m+"C"+(g+2)+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+m+"C"+(g+2)+" = vec4(0.);\n                }\n\n                xR"+m+"C"+g+" = vec4(\n                  xTexelR"+m+"C"+g+".xy, xTexelR"+m+"C"+(g+2)+".xy);\n              ",g+1<p&&(v+="\n                  xR"+m+"C"+(g+1)+" = vec4(\n                    xTexelR"+m+"C"+g+".zw, xTexelR"+m+"C"+(g+2)+".zw);\n                ")),v+="}");g<p&&(v+="\n            vec4 wTexelR"+m+"C"+g+" = getW("+m+", "+g+", d1, q);\n            wR"+m+"C"+g+" = vec4(wTexelR"+m+"C"+g+".xz, wTexelR"+m+"C"+g+".xz);\n          ",g+1<p&&(v+="\n              vec4 wTexelR"+m+"C"+(g+1)+" = getW("+m+", "+(g+1)+", d1, q);\n              wR"+m+"C"+(g+1)+" =\n                vec4(wTexelR"+m+"C"+(g+1)+".xz, wTexelR"+m+"C"+(g+1)+".xz);"))}for(m=0;m<f;m++)for(g=0;g<p;g++)v+="dotProd += xR"+m+"C"+g+" * wR"+m+"C"+g+";";var b="",w="";n&&(b=r?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"vec4 activation(vec4 x) {\n          "+n+"\n        }",w="result = activation(result);");var C=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+b+"\n\n      const ivec2 strides = ivec2("+u+", "+c+");\n      const ivec2 pads = ivec2("+a+", "+s+");\n\n      void main() {\n\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2;\n        int q = 0;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        vec4 dotProd = vec4(0.);\n\n        "+v+"\n\n        vec4 result = dotProd;\n        "+C+"\n        "+w+"\n        setOutput(result);\n      }\n    "}function Li(t,e,n,r,o){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];var i=t[0],a=t[1],s=t[2],u=t[3],c=e[0],l=n[0],h=n[1];this.outputShape=[c,l,h,u];var f="bilinear"===r?1:0,p=[a-1+".0",s-1+".0"],d=p[0],v=p[1],m=1<l?[""+(a-1)/(l-1),"(y2-y1) * height_ratio","y1*"+d+" + float(y)*(height_scale)"]:["0.0","0.0","0.5 * (y1+y2) * "+d],g=m[0],y=m[1],x=m[2],b=1<h?[""+(s-1)/(h-1),"(x2-x1) * width_ratio","x1*"+v+" + float(x)*(width_scale)"]:["0.0","0.0","0.5 * (x1+x2) * "+v],w=b[0],C=b[1],E=b[2];this.userCode="\n      const float height_ratio = float("+g+");\n      const float width_ratio = float("+w+");\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n        float x2 = getBoxes(b,3);\n\n        // get image in batch index\n        int bInd = round(getBoxInd(b));\n        if(bInd < 0 || bInd >= "+i+") {\n          return;\n        }\n\n        float height_scale = "+y+";\n        float width_scale = "+C+";\n\n        float in_y = "+x+";\n        if( in_y < 0.0 || in_y > "+d+" ) {\n          setOutput(float("+o+"));\n          return;\n        }\n        float in_x = "+E+";\n        if( in_x < 0.0 || in_x > "+v+" ) {\n          setOutput(float("+o+"));\n          return;\n        }\n\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\n        if("+f+" == 1) {\n          // Compute the four integer indices.\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    "}function Wi(t,e,n){this.variableNames=["x"];var r=(this.outputShape=t).length,o=t[t.length-1],i=n?"<":">";this.userCode="\n      int getIndex(int i) {\n        "+(n?"return "+o+" -i - 1;":"return i;")+"\n      }\n\n      void main() {\n        "+oi(r)+" coords = getOutputCoords();\n        int end = "+zi(r,"coords")+";\n        float val = 0.0;\n        for (int i = "+o+" - 1; i >= 0; i -= 1) {\n          int idx = getIndex(i);\n          if (idx "+i+" end) {\n            continue;\n          }\n          if (idx == end && "+e+") {\n            continue;\n          }\n          "+zi(r,"coords")+" = idx;\n          val += getX("+function(t,e){if(1===r)return e;if(2===r)return e+".x, "+e+".y";if(3===r)return"coords.x, coords.y, coords.z";if(4===r)return"coords.x, coords.y, coords.z, coords.w";throw Error("Cumulative sum for rank "+r+" is not yet supported")}(0,"coords")+");\n        }\n        setOutput(val);\n      }\n    "}function zi(t,e){if(1===t)return""+e;if(2===t)return e+".y";if(3===t)return e+".z";if(4===t)return e+".w";throw Error("Cumulative sum for rank "+t+" is not yet supported")}function Ui(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=$t.DENSE;var e=se(t),n=Jo();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+Qo(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getA(rc.x, rc.y, rc.z);\n        }\n\n        "+n.output+" = result;\n      }\n    "}function Vi(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=$t.DENSE;var e=se(t),n=Jo();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+Qo(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\n        }\n\n        "+n.output+" = result;\n      }\n    "}function Gi(t){this.variableNames=["X"],this.outputShape=[t,t],this.userCode="\n      void main() {\n          ivec2 coords = getOutputCoords();\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\n          setOutput(val);\n      }\n    "}function Hi(t){this.variableNames=["A"],this.outTexUsage=Jt.DOWNLOAD;var e=Jo();this.outputShape=t,this.userCode="\n      "+ti+"\n\n      void main() {\n        float x = getAAtOutCoords();\n        "+e.output+" = encode_float(x);\n      }\n    "}function qi(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Jt.DOWNLOAD;var e=Jo();this.outputShape=t,this.userCode="\n      "+ti+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n        "+e.output+" = encode_float(x);\n      }\n    "}function ji(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"];var r=Jo(),o=e[0],i=e[1];this.outputShape=t;var a="result";n&&(a="floor(result * 255. + 0.5)"),this.userCode="\n      "+Zo(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        int flatIndex = getFlatIndex(coords);\n        int offset = imod(flatIndex, 4);\n\n        flatIndex = idiv(flatIndex, 4, 1.);\n        \n        int r = flatIndex / "+i+";\n        int c = imod(flatIndex, "+i+");\n        vec2 uv = (vec2(c, r) + halfCR) / vec2("+i+".0, "+o+".0);\n        vec4 values = "+r.texture2D+"(A, uv);\n\n        float result;\n\n        if(offset == 0) {\n          result = values[0];\n        } else if(offset == 1) {\n          result = values[1];\n        } else if(offset == 2) {\n          result = values[2];\n        } else {\n          result = values[3];\n        }\n\n        "+r.output+" = vec4("+a+", 0., 0., 0.);\n      }\n    "}function Ki(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var r=Jo(),o=e[0],i=e[1];this.outputShape=t;var a="",s="result";n&&(s="floor(result * 255. + 0.5)");for(var u=0;u<=1;u++)for(var c=0;c<=1;c++){var l=2*u+c;a+="\n          localCoords = coords;\n          if(localCoords[2] + "+c+" < "+t[2]+") {\n            localCoords[2] += "+c+";\n            if(localCoords[1] + "+u+" < "+t[1]+") {\n              localCoords[1] += "+u+";\n\n              flatIndex = getFlatIndex(localCoords);\n              offset = imod(flatIndex, 4);\n\n              flatIndex = idiv(flatIndex, 4, 1.);\n\n              r = flatIndex / "+i+";\n              c = imod(flatIndex, "+i+");\n              uv = (vec2(c, r) + halfCR) / vec2("+i+".0, "+o+".0);\n              values = "+r.texture2D+"(A, uv);\n\n              if(offset == 0) {\n                result["+l+"] = values[0];\n              } else if(offset == 1) {\n                result["+l+"] = values[1];\n              } else if(offset == 2) {\n                result["+l+"] = values[2];\n              } else {\n                result["+l+"] = values[3];\n              }\n            }\n          }\n        "}this.userCode="\n      "+Zo(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        vec4 result = vec4(0.);\n        int flatIndex, r, c, offset;\n        ivec3 localCoords;\n        vec2 uv;\n        vec4 values;\n\n        "+a+"\n\n        "+r.output+" = "+s+";\n      }\n    "}function Xi(t,e,n){this.variableNames=["real","imag"];var r=e[1];this.outputShape=e;var o=n?"2.0 * "+Math.PI:"-2.0 * "+Math.PI,i=n?r+".0":"1.0";this.userCode="\n      const float exponentMultiplier = "+o+";\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        "+t+"\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float("+r+");\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < "+r+"; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / "+i+";\n        }\n\n        return result;\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        setOutput(mulMatDFT(coords[0], coords[1]));\n      }\n    "}function Yi(t,e,n){this.variableNames=["A","indices"];var r=t.slice();r[n]=e,this.outputShape=r,this.rank=r.length;var o=oi(this.rank),i=function(t,e){var n=t.length;if(4<n)throw Error("Gather for rank "+n+" is not yet supported");if(1===n)return"int(getIndices(resRC))";for(var r=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],i=0;i<t.length;i++)i===e?o.push("int(getIndices("+r[i]+"))"):o.push(""+r[i]);return o.join()}(t,n);this.userCode="\n      void main() {\n        "+o+" resRC = getOutputCoords();\n        setOutput(getA("+i+"));\n      }\n    "}var $i=(Zi.prototype.getHeightCoordString=function(){return"NHWC"===this.dataFormat?"coords[1]":"coords[2]"},Zi.prototype.getWidthCoordString=function(){return"NHWC"===this.dataFormat?"coords[2]":"coords[3]"},Zi.prototype.getDepthCoordString=function(){return"NHWC"===this.dataFormat?"coords[3]":"coords[1]"},Zi.prototype.getOutputDepthSize=function(){return"NHWC"===this.dataFormat?this.outputShape[3]:this.outputShape[1]},Zi.prototype.getInputSamplingString=function(){return"NHWC"===this.dataFormat?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"},Zi),Ji=(Qi.prototype.getCustomSetupFunc=function(n){var r=this;return function(t,e){null==r.valueLoc&&(r.valueLoc=t.getUniformLocationNoThrow(e,"value")),t.gl.uniform1f(r.valueLoc,n)}},Qi);function Qi(t,e){this.outputShape=[],this.variableNames=["x"],this.outputShape=t,this.userCode="\n      uniform float value;\n      void main() {\n        // Input can be obtained from uniform value.\n        setOutput(value);\n      }\n    "}function Zi(t,e,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=t,this.blockSize=e,this.dataFormat=n,this.userCode="\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = "+this.getHeightCoordString()+";\n      int w = "+this.getWidthCoordString()+";\n      int d = "+this.getDepthCoordString()+";\n\n      int in_h = h / "+e+";\n      int offset_h = imod(h, "+e+");\n      int in_w = w / "+e+";\n      int offset_w = imod(w, "+e+");\n      int offset_d = (offset_h * "+e+" + offset_w) *\n        "+this.getOutputDepthSize()+";\n      int in_d = d + offset_d;\n\n      float result = "+this.getInputSamplingString()+";\n      setOutput(result);\n    }\n  "}function ta(t,e,n){this.sliceDim=t,this.strides=e,this.variableNames=["x","indices"],this.outputShape=n;var r=oi(e.length),o=oi(n.length),i=1<this.sliceDim?"strides[j]":"strides";this.userCode="\n        "+r+" strides = "+r+"("+this.strides+");\n         void main() {\n          "+o+" coords = getOutputCoords();\n          int flattenIndex = 0;\n          for (int j = 0; j < "+this.sliceDim+"; j++) {\n            int index = round(getIndices(coords[0], j));\n            flattenIndex += index * "+i+";\n          }\n          setOutput(getX(flattenIndex, coords[1]));\n        }\n      "}function ea(t,e){var n=Jo();return de(t,e,n.version+"\n    precision highp float;\n    "+n.attribute+" vec3 clipSpacePos;\n    "+n.attribute+" vec2 uv;\n    "+n.varyingVs+" vec2 resultUV;\n\n    void main() {\n      gl_Position = vec4(clipSpacePos, 1);\n      resultUV = uv;\n    }")}function na(t,e){return Ce(t,e,new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]))}function ra(t,e){return Ee(t,e,new Uint16Array([0,1,2,2,1,3]))}function oa(t,e,n,r,o,i,a){Ie(n,r);var s=_e(t,e),u=t.TEXTURE_2D;return le(t,e,function(){return t.bindTexture(u,s)}),le(t,e,function(){return t.texParameteri(u,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE)}),le(t,e,function(){return t.texParameteri(u,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE)}),le(t,e,function(){return t.texParameteri(u,t.TEXTURE_MIN_FILTER,t.NEAREST)}),le(t,e,function(){return t.texParameteri(u,t.TEXTURE_MAG_FILTER,t.NEAREST)}),le(t,e,function(){return t.texImage2D(u,0,o,n,r,0,i,a,null)}),le(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)}),s}function ia(t,e,n,r,o){var i=ae(n,r);return oa(t,e,i[0],i[1],o.internalFormatFloat,o.textureFormatFloat,t.FLOAT)}function aa(t,e,n,r,o){var i=ae(n,r);return oa(t,e,i[0],i[1],o.internalFormatHalfFloat,o.textureFormatFloat,o.textureTypeHalfFloat)}function sa(t,e,n,r,o){var i=ae(n,r);return oa(t,e,i[0],i[1],t.RGBA,t.RGBA,t.UNSIGNED_BYTE)}function ua(t,e,n,r,o){var i=ue(n,r);return oa(t,e,i[0],i[1],o.internalFormatPackedFloat,t.RGBA,t.FLOAT)}function ca(t,e,n,r,o){var i=ue(n,r);return oa(t,e,i[0],i[1],o.internalFormatPackedHalfFloat,t.RGBA,o.textureTypeHalfFloat)}function la(t,e,n,r){return le(t,e,function(){return t.bindBuffer(t.ARRAY_BUFFER,r)}),ke(t,e,n,"clipSpacePos",r,3,20,0)&&ke(t,e,n,"uv",r,2,20,12)}function ha(t,e,n,r,o,i,a){var s,u,c;le(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),c=i instanceof Uint8Array?(s=new Uint8Array(r*o*4),u=t.UNSIGNED_BYTE,t.RGBA):(s=new Float32Array(r*o*4),u=t.FLOAT,a.internalFormatPackedFloat),s.set(i),le(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,c,r,o,0,t.RGBA,u,s)}),le(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)})}function fa(t,e,n,r){le(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),r.data instanceof Uint8Array?le(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,r.width,r.height,0,t.RGBA,t.UNSIGNED_BYTE,r.data)}):le(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,r)}),le(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)})}function pa(t,e,n,r,o){var i=t.createBuffer();le(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,i)});var a=16*n*r;return le(t,e,function(){return t.bufferData(t.PIXEL_PACK_BUFFER,a,t.STREAM_READ)}),le(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,0)}),le(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,null)}),i}function da(t,e,n){var r=t,o=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,e),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,o),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),o}function va(t,e,n,r,o){var i=ae(n,r),a=i[0],s=i[1],u=new Uint8Array(n*r*4);return le(t,e,function(){return t.readPixels(0,0,a,s,o.downloadTextureFormat,t.UNSIGNED_BYTE,u)}),new Float32Array(u.buffer)}function ma(t,e,n,r,o,i,a,s){var u,c=t,l=new Float32Array((u=ue(i,a))[0]*u[1]*4);return c.bindBuffer(c.PIXEL_PACK_BUFFER,e),c.getBufferSubData(c.PIXEL_PACK_BUFFER,0,l),c.bindBuffer(c.PIXEL_PACK_BUFFER,null),l}function ga(t,e,n,r){var o=new Float32Array(n*r*4);return le(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,o)}),o}var ya=Object.freeze({createVertexShader:ea,createVertexBuffer:na,createIndexBuffer:ra,createFloat32MatrixTexture:ia,createFloat16MatrixTexture:aa,createUnsignedBytesMatrixTexture:sa,createPackedMatrixTexture:ua,createFloat16PackedMatrixTexture:ca,bindVertexProgramAttributeStreams:la,uploadDenseMatrixToTexture:ha,uploadPixelDataToTexture:fa,createBufferFromOutputTexture:pa,downloadFloat32MatrixFromBuffer:da,downloadByteEncodedFloatMatrixFromOutputTexture:va,downloadPackedMatrixFromBuffer:ma,downloadMatrixFromPackedOutputTexture:ga}),xa=(Object.defineProperty(ba.prototype,"debug",{get:function(){return _().getBool("DEBUG")},enumerable:!0,configurable:!0}),ba.prototype.dispose=function(){var t=this;if(!this.disposed){null!=this.program&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),null!=this.outputTexture&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");var e=this.gl;le(e,this.debug,function(){return e.finish()}),le(e,this.debug,function(){return e.bindFramebuffer(e.FRAMEBUFFER,null)}),le(e,this.debug,function(){return e.deleteFramebuffer(t.framebuffer)}),le(e,this.debug,function(){return e.bindBuffer(e.ARRAY_BUFFER,null)}),le(e,this.debug,function(){return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)}),le(e,this.debug,function(){return e.deleteBuffer(t.indexBuffer)}),this.disposed=!0}},ba.prototype.createFloat32MatrixTexture=function(t,e){return this.throwIfDisposed(),ia(this.gl,this.debug,t,e,this.textureConfig)},ba.prototype.createFloat16MatrixTexture=function(t,e){return this.throwIfDisposed(),aa(this.gl,this.debug,t,e,this.textureConfig)},ba.prototype.createUnsignedBytesMatrixTexture=function(t,e){return this.throwIfDisposed(),sa(this.gl,this.debug,t,e,this.textureConfig)},ba.prototype.uploadPixelDataToTexture=function(t,e){this.throwIfDisposed(),fa(this.gl,this.debug,t,e)},ba.prototype.uploadDenseMatrixToTexture=function(t,e,n,r){this.throwIfDisposed(),ha(this.gl,this.debug,t,e,n,r,this.textureConfig)},ba.prototype.createFloat16PackedMatrixTexture=function(t,e){return this.throwIfDisposed(),ca(this.gl,this.debug,t,e,this.textureConfig)},ba.prototype.createPackedMatrixTexture=function(t,e){return this.throwIfDisposed(),ua(this.gl,this.debug,t,e,this.textureConfig)},ba.prototype.deleteMatrixTexture=function(t){var e=this;this.throwIfDisposed(),this.outputTexture===t&&(Fe(this.gl,this.debug,this.framebuffer),this.outputTexture=null),le(this.gl,this.debug,function(){return e.gl.deleteTexture(t)})},ba.prototype.downloadByteEncodedFloatMatrixFromOutputTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return va(r.gl,r.debug,e,n,r.textureConfig)})},ba.prototype.downloadPackedMatrixFromBuffer=function(t,e,n,r,o,i){return ma(this.gl,t,0,0,0,o,i,this.textureConfig)},ba.prototype.downloadFloat32MatrixFromBuffer=function(t,e){return da(this.gl,t,e)},ba.prototype.createBufferFromTexture=function(t,e,n){this.bindTextureToFrameBuffer(t);var r=pa(this.gl,this.debug,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r},ba.prototype.createAndWaitForFence=function(){var t=this.createFence(this.gl);return this.pollFence(t)},ba.prototype.createFence=function(t){var e,n,r=this;if(_().getBool("WEBGL_FENCE_API_ENABLED")){var o=t,i=o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE,0);t.flush(),n=function(){var t=o.clientWaitSync(i,0,0);return t===o.ALREADY_SIGNALED||t===o.CONDITION_SATISFIED},e=i}else n=0<_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?(e=this.beginQuery(),this.endQuery(),function(){return r.isQueryAvailable(e,_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}):function(){return!0};return{query:e,isFencePassed:n}},ba.prototype.downloadMatrixFromPackedTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return ga(r.gl,r.debug,e,n)})},ba.prototype.createProgram=function(t){this.throwIfDisposed();var e=this.gl,n=ve(e,this.debug,t),r=ea(e,this.debug),o=xe(e,this.debug);return le(e,this.debug,function(){return e.attachShader(o,r)}),le(e,this.debug,function(){return e.attachShader(o,n)}),be(e,this.debug,o),this.debug&&we(e,this.debug,o),this.vertexAttrsAreBound||(this.setProgram(o),this.vertexAttrsAreBound=la(e,this.debug,this.program,this.vertexBuffer)),o},ba.prototype.deleteProgram=function(t){var e=this;this.throwIfDisposed(),t===this.program&&(this.program=null),null!=t&&le(this.gl,this.debug,function(){return e.gl.deleteProgram(t)})},ba.prototype.setProgram=function(t){var e=this;this.throwIfDisposed(),this.program=t,null!=this.program&&this.debug&&we(this.gl,this.debug,this.program),le(this.gl,this.debug,function(){return e.gl.useProgram(t)})},ba.prototype.getUniformLocation=function(t,e,n){return void 0===n&&(n=!0),this.throwIfDisposed(),n?De(this.gl,this.debug,t,e):Ae(this.gl,t,e)},ba.prototype.getAttributeLocation=function(t,e){var n=this;return this.throwIfDisposed(),le(this.gl,this.debug,function(){return n.gl.getAttribLocation(t,e)})},ba.prototype.getUniformLocationNoThrow=function(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)},ba.prototype.setInputMatrixTexture=function(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),Te(this.gl,this.debug,this.program,t,e,n)},ba.prototype.setOutputMatrixTexture=function(t,e,n){this.setOutputMatrixTextureDriver(t,n,e)},ba.prototype.setOutputPackedMatrixTexture=function(t,e,n){this.throwIfDisposed();var r=ue(e,n),o=r[0],i=r[1];this.setOutputMatrixTextureDriver(t,o,i)},ba.prototype.setOutputMatrixWriteRegion=function(t,e,n,r){this.setOutputMatrixWriteRegionDriver(n,t,r,e)},ba.prototype.setOutputPackedMatrixWriteRegion=function(t,e,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")},ba.prototype.debugValidate=function(){null!=this.program&&we(this.gl,this.debug,this.program),Me(this.gl)},ba.prototype.executeProgram=function(){this.throwIfDisposed(),this.throwIfNoProgram();var t=this.gl;this.debug&&this.debugValidate(),le(t,this.debug,function(){return t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0)})},ba.prototype.blockUntilAllProgramsCompleted=function(){var t=this;this.throwIfDisposed(),le(this.gl,this.debug,function(){return t.gl.finish()})},ba.prototype.getQueryTimerExtension=function(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=pe(this.gl,this.debug,2===_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension},ba.prototype.getQueryTimerExtensionWebGL2=function(){return this.getQueryTimerExtension()},ba.prototype.getQueryTimerExtensionWebGL1=function(){return this.getQueryTimerExtension()},ba.prototype.beginQuery=function(){if(2===_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var t=this.gl,e=this.getQueryTimerExtensionWebGL2(),n=t.createQuery();return t.beginQuery(e.TIME_ELAPSED_EXT,n),n}var r=this.getQueryTimerExtensionWebGL1(),o=r.createQueryEXT();return r.beginQueryEXT(r.TIME_ELAPSED_EXT,o),o},ba.prototype.endQuery=function(){if(2!==_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var t=this.getQueryTimerExtensionWebGL1();t.endQueryEXT(t.TIME_ELAPSED_EXT)}else{var e=this.gl,n=this.getQueryTimerExtensionWebGL2();e.endQuery(n.TIME_ELAPSED_EXT)}},ba.prototype.waitForQueryAndGetTime=function(n){return y(this,void 0,void 0,function(){var e=this;return R(this,function(t){switch(t.label){case 0:return[4,k(function(){return e.disposed||e.isQueryAvailable(n,_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))})];case 1:return t.sent(),[2,this.getQueryTime(n,_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))]}})})},ba.prototype.getQueryTime=function(t,e){if(0===e)return null;if(2===e){var n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}var r=this.getQueryTimerExtensionWebGL1();return r.getQueryObjectEXT(t,r.QUERY_RESULT_EXT)/1e6},ba.prototype.isQueryAvailable=function(t,e){if(0===e)return!0;if(2!==e)return o=(r=this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(t,r.QUERY_RESULT_AVAILABLE_EXT),null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint;var n=this.gl,r=this.getQueryTimerExtensionWebGL2(),o=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),o&&!this.disjoint},ba.prototype.pollFence=function(e){var n=this;return new Promise(function(t){n.addItemToPoll(function(){return e.isFencePassed()},function(){return t()})})},ba.prototype.pollItems=function(){for(var t=function(t){for(var e=0;e<t.length&&t[e]();++e);return e-1}(this.itemsToPoll.map(function(t){return t.isDoneFn})),e=0;e<=t;++e)(0,this.itemsToPoll[e].resolveFn)();this.itemsToPoll=this.itemsToPoll.slice(t+1)},ba.prototype.addItemToPoll=function(t,e){var n=this;this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),1<this.itemsToPoll.length||k(function(){return n.pollItems(),0===n.itemsToPoll.length})},ba.prototype.bindTextureToFrameBuffer=function(t){this.throwIfDisposed(),Ne(this.gl,this.debug,t,this.framebuffer),this.debug&&Me(this.gl)},ba.prototype.unbindTextureToFrameBuffer=function(){null!=this.outputTexture?(Ne(this.gl,this.debug,this.outputTexture,this.framebuffer),this.debug&&Me(this.gl)):Fe(this.gl,this.debug,this.framebuffer)},ba.prototype.downloadMatrixDriver=function(t,e){this.bindTextureToFrameBuffer(t);var n=e();return this.unbindTextureToFrameBuffer(),n},ba.prototype.setOutputMatrixTextureDriver=function(t,e,n){this.throwIfDisposed();var r=this.gl;Ne(r,this.debug,t,this.framebuffer),this.debug&&Me(r),this.outputTexture=t,le(r,this.debug,function(){return r.viewport(0,0,e,n)}),le(r,this.debug,function(){return r.scissor(0,0,e,n)})},ba.prototype.setOutputMatrixWriteRegionDriver=function(t,e,n,r){var o=this;this.throwIfDisposed(),le(this.gl,this.debug,function(){return o.gl.scissor(t,e,n,r)})},ba.prototype.throwIfDisposed=function(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")},ba.prototype.throwIfNoProgram=function(){if(null==this.program)throw new Error("No GPU program is currently set.")},ba);function ba(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];var e=_().getNumber("WEBGL_VERSION");null!=t?oe(e,this.gl=t):this.gl=ie(e);var n="WEBGL_color_buffer_float";if(1===_().getNumber("WEBGL_VERSION")){if(this.textureFloatExtension=pe(this.gl,this.debug,"OES_texture_float"),Ke(this.gl,"OES_texture_half_float"))this.textureHalfFloatExtension=pe(this.gl,this.debug,"OES_texture_half_float");else if(_().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Ke(this.gl,"EXT_color_buffer_half_float"))this.colorBufferHalfFloatExtension=pe(this.gl,this.debug,"EXT_color_buffer_half_float");else if(_().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Ke(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else{if(!Ke(this.gl,"EXT_color_buffer_half_float"))throw new Error("GL context does not support color renderable floats");this.colorBufferHalfFloatExtension=this.gl.getExtension("EXT_color_buffer_half_float")}this.vertexBuffer=na(this.gl,this.debug),this.indexBuffer=ra(this.gl,this.debug),this.framebuffer=Re(this.gl,this.debug),this.textureConfig=ce(this.gl,this.textureHalfFloatExtension)}function wa(t,s){if(t.length!==s.length)throw Error("Binary was compiled with "+t.length+" inputs, but was executed with "+s.length+" inputs");t.forEach(function(t,e){var n=t.logicalShape,r=s[e],o=r.shape;if(!A(n,o))throw Error("Binary was compiled with different shapes than the current args. Shapes "+n+" and "+o+" must match");if(!t.isUniform||!r.isUniform){var i=t.texShape,a=r.isUniform?null:r.texData.texShape;if(!A(i,a))throw Error("Binary was compiled with different texture shapes than the current args. Shape "+i+" and "+a+" must match")}})}function Ca(t,e,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var r=n.filterWidth,o=n.inChannels,i=n.strideWidth,a=n.strideHeight,s=n.padInfo,u=n.outWidth,c=n.dilationWidth,l=n.dilationHeight,h=n.dataFormat,f=s.left,p=s.top,d=o*r,v=Jo(),m="channelsLast"===h,g=m?0:1,y=m?1:2,x="",b=0;b<=1;b++)for(var w=0;w<=1;w++)x+="\n          blockIndex = rc.y + "+w+";\n          pos = rc.x + "+b+";\n\n          if(blockIndex < "+t[1]+" && pos < "+t[0]+") {\n            offsetY = int(blockIndex / ("+u+")) * "+a+" - "+p+";\n            d0 = offsetY + "+l+" * (pos / "+d+");\n\n            if(d0 < "+e[g]+" && d0 >= 0) {\n\n              offsetX = int(mod(float(blockIndex), "+u+".) * "+i+". - "+f+".);\n              d1 = offsetX + "+c+" * (int(mod(float(pos), "+d+".) / "+o+".));\n\n              if(d1 < "+e[y]+" && d1 >= 0) {\n\n                ch = int(mod(float(pos), "+o+".));\n\n                if ("+m+") {\n                  innerDims = vec2(d1, ch);\n                  result["+(2*b+w)+"] = getChannel(\n                    getA(d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result["+(2*b+w)+"] = getChannel(\n                    getA(ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        ";this.userCode="\n      void main() {\n        ivec2 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        "+x+"\n\n        "+v.output+" = result;\n      }\n    "}function Ea(t,e,n,r,o){this.variableNames=["x"],this.outputShape=[];var i,a=e,s=t[3]-1;this.outputShape=t;var u="float("+n+") + float("+r+") * sum";i=.5===o?"inversesqrt("+u+")":1===o?"1.0/("+u+")":"exp(log("+u+") * float(-"+o+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -"+a+"; j <= "+a+"; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  "+s+") {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * "+i+";\n        setOutput(val);\n      }\n    "}function _a(t,e,n,r,o){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=r,this.beta=o,this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < "+this.depth+"; ++d) {\n          int depthBegin = int(max(0.0, float(d - "+e+")));\n          int depthEnd = int(min(float("+this.depth+"),\n              float(d + "+e+" + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = "+this.depth+";\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float("+r+") * norm + float("+n+");\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float("+r+")\n                * float("+o+")\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * "+o+");\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    "}function Ia(t,e,n,r,o){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;var i,a=e,s=t[3]-1;this.outputShape=t;var u="float("+n+") + float("+r+") * sum";i=.5===o?"inversesqrt("+u+")":1===o?"1.0/("+u+")":"exp(log("+u+") * float(-"+o+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < "+this.outputShape[3]+";\n        bool hasNextRow = c < "+this.outputShape[2]+";\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - "+a+";\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - "+a+"; j <= "+a+"; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2("+s+"));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * "+i+";\n        setOutput(result);\n      }\n    "}function Ra(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideHeight,n=t.strideWidth,r=t.dilationHeight,o=t.effectiveFilterHeight,i=t.effectiveFilterWidth,a=o-1-t.padInfo.top,s=i-1-t.padInfo.left,u=o*i-1;this.userCode="\n      const ivec2 pads = ivec2("+a+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+o+";\n          wR += "+r+") {\n          float dyR = float(dyRCorner + wR) / "+e+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+i+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+n+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = "+u+" - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * "+i+" + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function ka(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,o=t.dilationDepth,i=t.dilationHeight,a=t.dilationWidth,s=t.effectiveFilterDepth,u=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=s-1-t.padInfo.front,h=u-1-t.padInfo.top,f=c-1-t.padInfo.left,p=s*u*c-1;this.userCode="\n      const ivec3 pads = ivec3("+l+", "+h+", "+f+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+s+";\n           wD += "+o+") {\n          float dyD = float(dyDCorner + wD) / "+e+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+u+";\n              wR += "+i+") {\n            float dyR = float(dyRCorner + wR) / "+n+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+c+";\n                wC += "+a+") {\n              float dyC = float(dyCCorner + wC) / "+r+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = "+p+" -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * "+u+" * "+c+" +\n                  wR * "+c+" + wC;\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n              dotProd += dyValue * mask;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}function Sa(t,e,n,r,o,i,a){void 0===n&&(n=!1),void 0===r&&(r=!1),void 0===o&&(o=!1),void 0===i&&(i=null),void 0===a&&(a=!1),this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;var s=n?t[1]:t[2],u=Math.ceil(s/2),c=n?"i * 2, rc.y":"rc.y, i * 2",l=r?"rc.z, i * 2":"i * 2, rc.z",h=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],p="",d="";i&&(p=a?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          "+i+"\n        }":"vec4 activation(vec4 x) {\n          "+i+"\n        }",d="result = activation(result);");var v=o?"result += getBiasAtOutCoords();":"";o&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+p+"\n\n      const float sharedDimension = "+u+".0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < "+u+"; i++) {\n          vec4 a = getMatrixA(rc.x, "+c+");\n          vec4 b = getMatrixB(rc.x, "+l+");\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += ("+h[0]+" * "+f[0]+");\n          result += ("+h[1]+" * "+f[1]+");\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        "+v+"\n\n        "+d+"\n\n        setOutput(result);\n      }\n    "}function Da(t,e,n,r){this.variableNames=["indices"],this.outputShape=[t,e],this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float("+r+"), float("+n+"),\n                      float(index == coords.y)));\n      }\n    "}function Aa(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var e,n,r,o,i=(this.outputShape=t).length;if(0===i)this.userCode="\n        void main() {\n          setOutput(vec4(getA(), 0., 0., 0.));\n        }\n      ";else{var a=$o("rc",i),s=oi(i),u=function(t,e,n){if(1===t)return"rc > "+e[0];for(var r="",o=t-2;o<t;o++)r+=n[o]+" >= "+e[o],o<t-1&&(r+="||");return r}(i,t,a),c=function(t,e,n){if(1===t)return"";var r=a.slice(-2);return"\n    int r = "+r[0]+";\n    int c = "+r[1]+";\n    int rp1 = r + 1;\n    int cp1 = c + 1;\n\n    bool cEdge = cp1 >= "+e+";\n    bool rEdge = rp1 >= "+n+";\n  "}(i,t[t.length-1],t[t.length-2]),l=(n=a,r=(e=t).length,o=function(t,e){for(var n=[],r=0;r<=1;r++)for(var o=0;o<=1;o++){for(var i=(0===r?"r":"rp1")+", "+(0===o?"c":"cp1"),a=2;a<t;a++)i=e[e.length-1-a]+","+i;n.push(i)}return n}(r,n),1===r?"getA(rc),\n            rc + 1 >= "+e[0]+" ? 0. : getA(rc + 1),\n            0, 0":"getA("+o[0]+"),\n          cEdge ? 0. : getA("+o[1]+"),\n          rEdge ? 0. : getA("+o[2]+"),\n          rEdge || cEdge ? 0. : getA("+o[3]+")");this.userCode="\n        void main() {\n          "+s+" rc = getOutputCoords();\n\n          if("+u+") {\n            setOutput(vec4(0));\n          } else {\n            "+c+"\n\n            setOutput(vec4("+l+"));\n          }\n        }\n      "}}var Ta=(Na.prototype.getCustomSetupFunc=function(n){var r=this;return function(t,e){null==r.seedLoc&&(r.seedLoc=t.getUniformLocation(e,"seed")),t.gl.uniform1f(r.seedLoc,n)}},Na);function Na(t,e,n){this.variableNames=["probs"],this.outputShape=[t,n],this.userCode="\n      uniform float seed;\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < "+(e-1)+"; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float("+(e-1)+"));\n      }\n    "}function Fa(n,t,e){this.variableNames=["x"],this.outputShape=t.map(function(t,e){return t[0]+n[e]+t[1]});var r=n.length,o=oi(r),i=t.map(function(t){return t[0]}).join(","),a=t.map(function(t,e){return t[0]+n[e]}).join(","),s=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);this.userCode=1!==r?"\n      "+o+" start = "+o+"("+i+");\n      "+o+" end = "+o+"("+a+");\n\n      void main() {\n        "+o+" outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(float("+e+"));\n        } else {\n          "+o+" coords = outC - start;\n          setOutput(getX("+s+"));\n        }\n      }\n    ":"\n        int start = "+i+";\n        int end = "+a+";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(float("+e+"));\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      "}function Ma(n,t,e){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map(function(t,e){return t[0]+n[e]+t[1]});for(var r=n.length,o=oi(r),i=t.map(function(t){return t[0]}).join(","),a=t.map(function(t,e){return t[0]+n[e]}).join(","),s=$o("rc",r),u=$o("source",r),c=s[r-1]+" < "+this.outputShape[r-1],l=1===r?"source":"vec2("+u.slice(-2).join()+")",h=[o+" rc = outputLoc;",s[r-1]+" += 1;\n       if("+c+") {\n      ",1===r?"":"}\n       rc = outputLoc;\n       "+s[r-2]+" += 1;\n       if("+s[r-2]+" < "+this.outputShape[r-2]+") {",1===r?"":"  "+s[r-1]+" += 1;\n         if("+c+") {"],f=1===r?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="",d=0,v=1===r?2:4;d<v;d++)p+="\n        "+h[d]+"\n        if ("+f+") {\n          result["+d+"] = float("+e+");\n        } else {\n          "+o+" source = rc - start;\n          result["+d+"] = getChannel(getX("+u.join()+"), "+l+");\n        }\n      ";p+=1===r?"} ":"}}",this.userCode="\n      const "+o+" start = "+o+"("+i+");\n      const "+o+" end = "+o+"("+a+");\n\n      void main() {\n        "+o+" outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        "+p+"\n        setOutput(result);\n      }\n    "}function Oa(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,o=t.strideHeight,i=t.strideWidth,a=t.dilationHeight,s=t.dilationWidth,u=t.effectiveFilterHeight,c=t.effectiveFilterWidth,l=t.padInfo.top,h=t.padInfo.left;this.outputShape=t.outShape;var f="avg"===e,p="0.0";if(f||(p="-1.0 / 1e-20"),n)this.userCode="\n        const ivec2 strides = ivec2("+o+", "+i+");\n        const ivec2 pads = ivec2("+l+", "+h+");\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < "+u+";\n              wR += "+a+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+c+";\n                wC += "+s+") {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value >= currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = wR * "+c+" + wC;\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else{var d=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(d="avgValue / count");var v=4*Math.floor(r/4),m=r%4,g="\n      if ("+f+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec2 strides = ivec2("+o+", "+i+");\n      const ivec2 pads = ivec2("+l+", "+h+");\n      const float initializationValue = "+p+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+p+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < "+u+";\n            wR += "+a+") {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+v+"; wC += 4) {\n            int xC = xCCorner + wC * "+s+";\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              getValue(batch, xR, xC + 2 * "+s+", d),\n              getValue(batch, xR, xC + 3 * "+s+", d)\n            );\n\n            "+g+"\n          }\n\n          int xC = xCCorner + "+v+";\n          if ("+(1==m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            "+g+"\n          } else if ("+(2==m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              initializationValue,\n              initializationValue\n            );\n\n            "+g+"\n          } else if ("+(3==m)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              getValue(batch, xR, xC + 2 * "+s+", d),\n              initializationValue\n            );\n\n            "+g+"\n          }\n        }\n        setOutput("+d+");\n      }\n    "}}function Pa(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,o=t.strideDepth,i=t.strideHeight,a=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,c=t.dilationWidth,l=t.effectiveFilterDepth,h=t.effectiveFilterHeight,f=t.effectiveFilterWidth,p=t.padInfo.front,d=t.padInfo.top,v=t.padInfo.left;this.outputShape=t.outShape;var m="avg"===e,g="0.0";if(m||(g="-1.0 / 1e-20"),n)this.userCode="\n        const ivec3 strides =\n            ivec3("+o+", "+i+", "+a+");\n        const ivec3 pads = ivec3("+p+", "+d+", "+v+");\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < "+l+";\n              wD += "+s+") {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int wR = 0; wR < "+h+";\n                wR += "+u+") {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int wC = 0; wC < "+f+";\n                  wC += "+c+") {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value >= currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;\n                  minMaxPosition =\n                      wD * "+h+" * "+f+" +\n                      wR * "+f+" + wC;;\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else{var y=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(y="avgValue / count");var x=4*Math.floor(r/4),b=r%4,w="\n      if ("+m+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec3 strides =\n        ivec3("+o+", "+i+", "+a+");\n      const ivec3 pads = ivec3("+p+", "+d+", "+v+");\n      const float initializationValue = "+g+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+g+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < "+l+";\n            wD += "+s+") {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+h+";\n            wR += "+u+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+x+"; wC += 4) {\n              int xC = xCCorner + wC * "+c+";\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+c+", ch),\n                getValue(batch, xD, xR, xC + 3 * "+c+", ch)\n              );\n\n              "+w+"\n            }\n\n            int xC = xCCorner + "+x+";\n            if ("+(1==b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(2==b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(3==b)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+c+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+c+", ch),\n                initializationValue\n              );\n\n              "+w+"\n            }\n          }\n          setOutput("+y+");\n        }\n      }\n    "}}function Ba(t,e){this.variableNames=["x"];var n=t.windowSize,r=t.batchSize,o=t.inSize,i=Math.ceil(o/n);this.outputShape=[r,i];var a="0.0",s="";"prod"===e?a="1.0":"min"===e?(a="1.0 / 1e-20",s="min"):"max"===e&&(a="-1.0 / 1e-20",s="max");var u=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"sum"===e?u="sumValue":"prod"===e?u="prodValue":"all"===e?u="allValue":"any"===e&&(u="anyValue");var c=4*Math.floor(n/4),l=n%4,h="\n      if ("+("sum"===e)+") {\n        sumValue += dot(values, ones);\n      } else if ("+("prod"===e)+") {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = "+s+"(values, minMaxValue);\n      }\n    ",f="vec4";"all"===e?(a="1.0",h="\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      ",f="bvec4"):"any"===e&&(a="0.0",h="\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      ",f="bvec4");var p="";0<o%n&&(p="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return initializationValue;\n        }\n      "),this.userCode="\n      const float initializationValue = "+a+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        "+p+"\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * "+n+";\n\n        vec4 minMaxValue = vec4("+a+");\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < "+c+"; i += 4) {\n          int inIdx = inOffset + i;\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          "+h+"\n        }\n\n        int inIdx = inOffset + "+c+";\n        if ("+(1==l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          "+h+"\n        } else if ("+(2==l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          "+h+"\n        } else if ("+(3==l)+") {\n          "+f+" values = "+f+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          "+h+"\n        }\n        setOutput("+u+");\n      }\n    "}function La(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t;for(var n="",r=0;r<4;r++){var o="thisRC = rc;";r%2==1&&(o+="thisRC.z += 1;"),1<r&&(o+="thisRC.y += 1;"),n+="\n        "+o+"\n        "+(0<r?"if(thisRC.y < rows && thisRC.z < cols){":"")+"\n          int flatIndex = getFlatIndex(thisRC);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result["+r+"] =\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n        "+(0<r?"}":"")+"\n      "}this.userCode="\n      \n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      "+Qo(["r","c","d"],e)+"\n      return ivec3(r, c, d);\n    }\n  \n      "+Zo(t)+"\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.);\n\n        ivec3 thisRC;\n        int rows = "+t[1]+";\n        int cols = "+t[2]+";\n\n        "+n+"\n\n        setOutput(result);\n      }\n    "}function Wa(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],i=r[2],a=t.shape,s=a[1],u=a[2],c=[n&&1<s?o-1:o,n&&1<u?i-1:i],l=[n&&1<s?s-1:s,n&&1<u?u-1:u],h=c[0]/l[0],f=c[1]/l[1],p=1/h,d=1/f,v=2*Math.ceil(p)+2,m=2*Math.ceil(d)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+h+");\n        const float widthScale = float("+f+");\n\n        const float invHeightScale = float("+p+");\n        const float invWidthScale = float("+d+");\n\n        const int winHeight = int("+v+");\n        const int winWidth = int("+m+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+s+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+u+") {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), "+(o-1)+".0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), "+(i-1)+".0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    "}function za(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var o=t[0],i=t[1],a=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&1<e?i-1:i,r&&1<n?a-1:a],c=[r&&1<e?e-1:e,r&&1<n?n-1:n];this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/c[0]+",\n          "+u[1]/c[1]+");\n      const vec2 inputShapeRC = vec2("+i+".0, "+a+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    "}function Ua(t,e,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];var o=t[0],i=t[1],a=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&1<e?i-1:i,r&&1<n?a-1:a],c=[r&&1<e?e-1:e,r&&1<n?n-1:n];this.userCode="\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          "+u[0]/c[0]+",\n          "+u[1]/c[1]+",\n          "+u[1]/c[1]+");\n      const vec3 inputShapeRC = vec3("+i+".0, "+a+".0,\n                                     "+a+".0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < "+(s-1)+";\n        bool hasNextRow = coords.z < "+(n-1)+";\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    "}function Va(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,o=r[1],i=r[2],a=t.shape,s=a[1],u=a[2],c=[n&&1<s?o-1:o,n&&1<u?i-1:i],l=[n&&1<s?s-1:s,n&&1<u?u-1:u],h=c[0]/l[0],f=c[1]/l[1],p=1/h,d=1/f,v=2*Math.ceil(p)+2,m=2*Math.ceil(d)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+h+");\n        const float widthScale = float("+f+");\n\n        const float invHeightScale = float("+p+");\n        const float invWidthScale = float("+d+");\n\n        const int winHeight = int("+v+");\n        const int winWidth = int("+m+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+s+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+u+") {\n              continue;\n            }\n\n            float sourceFracRow =\n              float("+c[0]+") *\n                (float(dyR) / float("+l[0]+"));\n\n            float sourceFracCol =\n                float("+c[1]+") *\n                  (float(dyC) / float("+l[1]+"));\n\n            int sourceNearestRow = int(min(\n                float(int("+o+") - 1),\n                "+n+" ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int("+i+") - 1),\n                "+n+" ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    "}function Ga(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var o=t[0],i=t[1],a=t[2],s=t[3];this.outputShape=[o,e,n,s];var u=[r&&1<e?i-1:i,r&&1<n?a-1:a],c=[r&&1<e?e-1:e,r&&1<n?n-1:n],l=r?"0.5":"0.0";this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/c[0]+",\n          "+u[1]/c[1]+");\n      const vec2 inputShapeRC = vec2("+i+".0, "+a+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + "+l+")));\n\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    "}function Ha(r,o){this.variableNames=["x"];var t=r.length;if(4<t)throw new Error("WebGL backend: Reverse of rank-"+t+" tensor is not yet supported");if(this.outputShape=r,1!==t){var e=r.map(function(t,e){return n=e,-1!==o.indexOf(n)&&1!==r[n]?r[n]+" - coords["+n+"] - 1":"coords["+n+"]";var n}).join(","),n=oi(t);this.userCode="\n      void main() {\n        "+n+" coords = getOutputCoords();\n        setOutput(getX("+e+"));\n      }\n    "}else this.userCode="\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX("+r[0]+" - coord - 1));\n        }\n      "}function qa(i,a){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;var t=i.length;if(4<t)throw new Error("WebGL backend: Reverse of rank-"+t+" tensor is not yet supported");this.outputShape=i;var e,n,r,o=$o("rc",t),s=o[t-1]+" + 1 < "+this.outputShape[t-1],u=o[t-2]+" + 1 < "+this.outputShape[t-2],c=oi(t);function l(o){var t=i.map(function(t,e){return n=e,r=o,-1!==a.indexOf(n)&&1!==i[n]?i[n]+" - "+r[n]+" - 1":""+r[n];var n,r});return"getChannel(getX("+t.join(",")+"), vec2("+t.slice(-2).join(",")+"))"}this.userCode=1===t?"\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX("+i[0]+" - rc - 1),\n            "+i[0]+" - rc - 1);\n          if("+s+"){\n              result.g = getChannel(getX("+i[0]+" - (rc  + 1) - 1),\n                "+i[0]+" - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      ":"\n        void main() {\n          "+c+" rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = "+l(o.slice())+";\n          if("+s+"){\n            result.g = "+((r=o.slice())[t-1]="("+r[t-1]+" + 1)",l(r))+";\n          }\n          if("+u+") {\n            result.b = "+((n=o.slice())[t-2]="("+n[t-2]+" + 1)",l(n))+";\n            if("+s+") {\n              result.a = "+((e=o.slice())[t-1]="("+e[t-1]+" + 1)",e[t-2]="("+e[t-2]+" + 1)",l(e))+";\n            }\n          }\n          setOutput(result);\n        }\n    "}function ja(t,e,n,r,o,i,a){this.variableNames=["updates","indices","defaultValue"],this.outputShape=i;var s=oi(o.length),u=oi(i.length),c="";1===n?c="i":2===n&&(c="i, j");var l="getIndices("+c+")",h="";1===r?h="i":2===r&&(h="i, coords[1]");var f="getUpdates("+h+")",p=1<e?"strides[j]":"strides";this.userCode="\n        "+s+" strides = "+s+"("+o+");\n\n        void main() {\n          "+u+" coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < "+t+"; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < "+e+"; j++) {\n              int index = round("+l+");\n              flattenedIndex += index * "+p+";\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += "+f+";\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      "}function Ka(t,e){this.variableNames=["x","segmentIds"];var n=t.windowSize,r=t.batchSize,o=t.inSize,i=t.numSegments,a=i*Math.ceil(o/n);this.outputShape=[r,a];var s=4*Math.floor(n/4),u=n%4,c="\n        sumValue += dot(values, segFilter);\n    ",l="";0<o%n&&(l="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return initializationValue;\n        }\n      ");var h="";0<o%n&&(h="\n        if (inIdx < 0 || inIdx >= "+o+") {\n          return -1.0;\n        }\n      "),this.userCode="\n      const float initializationValue = 0.0;\n\n      float getValue(int batch, int inIdx) {\n        "+l+"\n        return getX(batch, inIdx);\n      }\n\n      float getSegmentIdAtIndex(int inIdx) {\n        "+h+"\n        return getSegmentIds(inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = int(floor(float(outIdx) / float(\n          "+i+")) * float("+n+"));\n        int currentSeg = int(mod(float(outIdx), float("+i+")));\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < "+s+"; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n          );\n\n          "+c+"\n        }\n\n        int inIdx = inOffset + "+s+";\n        if ("+(1==u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            0,\n            0,\n            0\n          );\n\n          "+c+"\n        } else if ("+(2==u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n              0,\n              0\n          );\n\n          "+c+"\n        } else if ("+(3==u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            0\n          );\n\n          "+c+"\n        }\n        setOutput(sumValue);\n      }\n    "}function Xa(t,e,n){var r,o;if(this.variableNames=["c","a","b"],this.outputShape=e,4<n)throw Error("Where for rank "+n+" is not yet supported");if(1===n)r=o="resRC";else{for(var i=["resRC.x","resRC.y","resRC.z","resRC.w"],a=[],s=[],u=0;u<e.length;u++)s.push(""+i[u]),u<t&&a.push(""+i[u]);r=a.join(),o=s.join()}var c=oi(n);this.userCode="\n      void main() {\n        "+c+" resRC = getOutputCoords();\n        float cVal = getC("+r+");\n        if (cVal >= 1.0) {\n          setOutput(getA("+o+"));\n        } else {\n          setOutput(getB("+o+"));\n        }\n      }\n    "}var Ya=(Ja.prototype.getCustomSetupFunc=function(n){var r=this;if(n.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+n.length+")");return function(t,e){null==r.startLoc&&(r.startLoc=t.getUniformLocationNoThrow(e,"start"),null==r.startLoc)||t.gl.uniform1iv(r.startLoc,n)}},Ja),$a=["x","y","z","w","u","v"];function Ja(t){this.variableNames=["source"],this.outputShape=t,this.rank=t.length;var e,n=oi(this.rank),r="uniform int start["+this.rank+"];",o=function(t){if(1===t)return"sourceLoc";if(t<=6)return $a.slice(0,t).map(function(t){return"sourceLoc."+t}).join(",");throw Error("Slicing for rank "+t+" is not yet supported")}(this.rank);e="\n        "+n+" sourceLoc;\n        "+n+" coords = getOutputCoords();\n        "+t.map(function(t,e){return"sourceLoc."+$a[e]+" = start["+e+"] + coords."+$a[e]+";"}).join("\n")+"\n      ",this.userCode="\n      "+r+"\n      void main() {\n        "+e+"\n        setOutput(getSource("+o+"));\n      }\n    "}function Qa(t,e,n){this.variableNames=["x"];var r=(this.outputShape=n).length,o=oi(n.length),i=oi(n.length),a="";if(1===r)a="coords * strides + begin";else{var s=0;a=n.map(function(t,e){return s++,1===n.length?"coords * strides["+e+"] + begin["+e+"]":"coords["+(s-1)+"] * strides["+e+"] + begin["+e+"]"}).join(",")}this.userCode="\n      "+o+" begin = "+o+"("+t+");\n      "+o+" strides = "+o+"("+e+");\n\n      void main() {\n        "+i+" coords = getOutputCoords();\n        setOutput(getX("+a+"));\n      }\n    "}var Za=(ns.prototype.getCustomSetupFunc=function(n){var r=this;if(n.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+n.length+")");return function(t,e){null==r.startLoc&&(r.startLoc=t.getUniformLocationNoThrow(e,"start"),null==r.startLoc)||t.gl.uniform1iv(r.startLoc,n)}},ns),ts=(es.prototype.acquireTexture=function(t,e,n){var r,o=rs(e,n),i=os(t,o,n);if(i in this.freeTextures||(this.freeTextures[i]=[]),i in this.usedTextures||(this.usedTextures[i]=[]),0<this.freeTextures[i].length){this.numFreeTextures--,this.numUsedTextures++,this.log();var a=this.freeTextures[i].shift();return this.usedTextures[i].push(a),a}return this.numUsedTextures++,this.log(),o===Qt.PACKED_2X2_FLOAT32?r=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Qt.PACKED_2X2_FLOAT16?r=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Qt.UNPACKED_FLOAT32?r=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Qt.UNPACKED_FLOAT16?r=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Qt.PACKED_4X1_UNSIGNED_BYTE&&(r=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[i].push(r),r},es.prototype.releaseTexture=function(t,e,n,r){if(null!=this.freeTextures){var o=os(e,rs(n,r),r);o in this.freeTextures||(this.freeTextures[o]=[]),this.freeTextures[o].push(t),this.numFreeTextures++,this.numUsedTextures--;var i=this.usedTextures[o],a=i.indexOf(t);if(a<0)throw new Error("Cannot release a texture that was never provided by this texture manager");i.splice(a,1),this.log()}},es.prototype.log=function(){if(this.logEnabled){var t=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",this.numFreeTextures+" / "+this.numUsedTextures,"("+t+")")}},es.prototype.getNumUsedTextures=function(){return this.numUsedTextures},es.prototype.getNumFreeTextures=function(){return this.numFreeTextures},es.prototype.dispose=function(){var e=this;if(null!=this.freeTextures){for(var t in this.freeTextures)this.freeTextures[t].forEach(function(t){e.gpgpu.deleteMatrixTexture(t)});for(var t in this.usedTextures)this.usedTextures[t].forEach(function(t){e.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0}},es);function es(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}function ns(t){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length;var e=oi(this.rank),n=$o("coords",this.rank),r=$o("sourceLoc",this.rank),o=1===this.rank?"sourceLoc":"vec2("+r.slice(-2).join()+")",i="getChannel(getSource("+r.join()+"), "+o+")",a="\n      result.x = "+i+";\n      if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n        ++"+r[this.rank-1]+";\n        result.y = "+i+";\n        --"+r[this.rank-1]+";\n      }\n    ",s=1===this.rank?"":"\n      --"+n[this.rank-1]+";\n      if (++"+n[this.rank-2]+" < "+t[this.rank-2]+") {\n        ++"+r[this.rank-2]+";\n        result.z = "+i+";\n        if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n          ++"+r[this.rank-1]+";\n          result.w = "+i+";\n        }\n      }\n    ",u=this.rank<=4?"sourceLoc = coords +\n            "+e+"("+t.map(function(t,e){return"start["+e+"]"}).join()+");":t.map(function(t,e){return r[e]+" = "+n[e]+" + start["+e+"];"}).join("\n");this.userCode="\n      uniform int start["+this.rank+"];\n      void main() {\n        "+e+" coords = getOutputCoords();\n        "+e+" sourceLoc;\n        "+u+"\n        vec4 result = vec4(0.);\n        "+a+"\n        "+s+"\n        setOutput(result);\n      }\n    "}function rs(t,e){if(t===Jt.UPLOAD)return Qt.PACKED_2X2_FLOAT32;if(t===Jt.RENDER||null==t)return n=e,_().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?n?Qt.PACKED_2X2_FLOAT32:Qt.UNPACKED_FLOAT32:n?Qt.PACKED_2X2_FLOAT16:Qt.UNPACKED_FLOAT16;var n;if(t===Jt.DOWNLOAD||t===Jt.PIXELS)return Qt.PACKED_4X1_UNSIGNED_BYTE;throw new Error("Unknown logical texture type "+t)}function os(t,e,n){return t[0]+"_"+t[1]+"_"+e+"_"+n}function is(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[r]*e[r];this.outputShape=n,this.rank=n.length;var o=oi(this.rank),i=function(t){var e=t.length;if(5<e)throw Error("Tile for rank "+e+" is not yet supported");if(1===e)return"imod(resRC, "+t[0]+")";for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[],o=0;o<t.length;o++)r.push("imod("+n[o]+", "+t[o]+")");return r.join()}(t);this.userCode="\n      void main() {\n        "+o+" resRC = getOutputCoords();\n        setOutput(getA("+i+"));\n      }\n    "}function as(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];this.outputShape=n,this.rank=n.length;var o=oi(this.rank),i=function(t){var e=t.length;if(6<e)throw Error("Transpose for rank "+e+" is not yet supported");for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(e),o=0;o<t.length;o++)r[t[o]]=n[o];return r.join()}(e);this.userCode="\n    void main() {\n      "+o+" resRC = getOutputCoords();\n      setOutput(getA("+i+"));\n    }\n    "}function ss(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];if(this.outputShape=n,this.rank=n.length,6<this.rank)throw Error("Packed transpose for rank "+this.rank+" is not yet supported.");var o=oi(this.rank),i=Yo("rc",this.rank),a=new Array(this.rank);for(r=0;r<e.length;r++)a[e[r]]=i[r];var s="vec2("+a.slice(-2).join()+")",u="++"+i[this.rank-1]+" < "+n[this.rank-1],c="getChannel(getA("+a.join()+"), "+s+")";this.userCode="\n    void main() {\n      "+o+" rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = "+c+";\n      if("+u+") {\n        result[1] = "+c+";\n      }\n      --"+i[this.rank-1]+";\n      if(++"+i[this.rank-2]+" < "+n[this.rank-2]+") {\n        result[2] = "+c+";\n        if("+u+") {\n          result[3] = "+c+";\n        }\n      }\n      setOutput(result);\n    }\n    "}function us(t,e){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      float unaryOperation(float x) {\n        "+e+"\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    "}function cs(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.userCode="\n      vec4 unaryOperation(vec4 x) {\n        "+e+"\n      }\n\n      void main() {\n        vec4 x = getAAtOutCoords();\n        vec4 y = unaryOperation(x);\n\n        setOutput(y);\n  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Ds,As=(t(Ts,Ds=lo),Ts.prototype.numDataIds=function(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes},Ts.prototype.write=function(t,e,n){if(_().getBool("DEBUG")&&this.checkNumericalProblems(t),"complex64"===n&&null!=t)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");var r={};return this.texData.set(r,{shape:e,dtype:n,values:t,usage:Jt.UPLOAD}),r},Ts.prototype.move=function(t,e,n,r){if(_().getBool("DEBUG")&&this.checkNumericalProblems(e),"complex64"===r)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:r,values:e,usage:Jt.UPLOAD})},Ts.prototype.readSync=function(t){var e=this.texData.get(t),n=e.values,r=e.dtype,o=e.complexTensors,i=e.slice,a=e.shape,s=e.isPacked;if(null!=i){var u;u=s?new cs(a,Es):new us(a,Es);var c=this.runWebGLProgram(u,[{dataId:t,shape:a,dtype:r}],r),l=this.readSync(c.dataId);return this.disposeData(c.dataId),l}if(null!=n)return this.convertAndCacheOnCPU(t);if("string"===r)return n;var h,f,p=null!=this.activeTimers;return p&&(h=tt()),f="complex64"===r?Mo(o.real.dataSync(),o.imag.dataSync()):this.getValuesFromTexture(t),p&&(this.downloadWaitMs+=tt()-h),this.convertAndCacheOnCPU(t,f)},Ts.prototype.read=function(E){return y(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p,d,v,m,g,y,x,b,w,C;return R(this,function(t){switch(t.label){case 0:if(this.pendingRead.has(E))return e=this.pendingRead.get(E),[2,new Promise(function(t){return e.push(t)})];if(n=this.texData.get(E),r=n.values,o=n.shape,i=n.slice,a=n.dtype,s=n.complexTensors,u=n.isPacked,null!=i)return c=u?new cs(o,Es):new us(o,Es),l=this.runWebGLProgram(c,[{dataId:E,shape:o,dtype:a}],a),h=this.read(l.dataId),this.disposeData(l.dataId),[2,h];if(null!=r)return[2,this.convertAndCacheOnCPU(E)];if(!_().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&2===_().getNumber("WEBGL_VERSION"))throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");return f=null,"complex64"!==a&&_().get("WEBGL_BUFFER_SUPPORTED")&&(p=this.decode(E),d=this.texData.get(p.dataId),f=(C=this.gpgpu).createBufferFromTexture.apply(C,[d.texture].concat(se(o)))),this.pendingRead.set(E,[]),"complex64"===a?[3,2]:[4,this.gpgpu.createAndWaitForFence()];case 1:t.sent(),t.label=2;case 2:return"complex64"!==a?[3,4]:[4,Promise.all([s.real.data(),s.imag.data()])];case 3:return m=t.sent(),g=m[0],y=m[1],v=Mo(g,y),[3,5];case 4:v=null==f?this.getValuesFromTexture(E):(x=L(o),this.gpgpu.downloadFloat32MatrixFromBuffer(f,x)),t.label=5;case 5:return null!=p&&this.disposeData(p.dataId),b=this.convertAndCacheOnCPU(E,v),w=this.pendingRead.get(E),this.pendingRead.delete(E),w.forEach(function(t){return t(b)}),this.pendingDisposal.has(E)&&(this.pendingDisposal.delete(E),this.disposeData(E),this.pendingDeletes--),[2,b]}})})},Ts.prototype.checkNumericalProblems=function(t){if(null!=t)for(var e=0;e<t.length;e++){var n=t[e];if(!he(n)){if(_().getBool("WEBGL_RENDER_FLOAT32_CAPABLE"))throw Error("The value "+n+" cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'");throw Error("The value "+n+" cannot be represented on this device.")}}},Ts.prototype.getValuesFromTexture=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,i=n.isPacked,a=L(r);if(_().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){var s=this.decode(t),u=this.texData.get(s.dataId),c=(e=this.gpgpu).downloadMatrixFromPackedTexture.apply(e,[u.texture].concat(se(r))).subarray(0,a);return this.disposeData(s.dataId),c}var l=_().getBool("WEBGL_PACK")&&!0===i,h=l?ze(r):r,f=l?new qi(h):new Hi(h),p=this.runWebGLProgram(f,[{shape:h,dtype:o,dataId:t}],"float32"),d=this.texData.get(p.dataId),v=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(d.texture,d.texShape[0],d.texShape[1]).subarray(0,a);return this.disposeData(p.dataId),v},Ts.prototype.time=function(u){return y(this,void 0,void 0,function(){var e,n,r,o,i,a,s;return R(this,function(t){switch(t.label){case 0:return e=this.activeTimers,r=!(n=[]),null==this.programTimersStack?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,u(),o=b(this.activeTimers.map(function(t){return t.query})).filter(function(t){return null!=t}),i=b(this.activeTimers.map(function(t){return t.name})).filter(function(t){return null!=t}),this.activeTimers=e,r&&(this.programTimersStack=null),a={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},0<_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")?[4,Promise.all(o)]:[3,2];case 1:return s=t.sent(),a.kernelMs=v(s),a.getExtraProfileInfo=function(){return s.map(function(t,e){return{name:i[e],ms:t}}).map(function(t){return t.name+": "+t.ms}).join(", ")},[3,3];case 2:a.kernelMs={error:"WebGL query timers are not supported in this environment."},t.label=3;case 3:return this.uploadWaitMs=0,this.downloadWaitMs=0,[2,a]}})})},Ts.prototype.memory=function(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU}},Ts.prototype.startTimer=function(){return 0<_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")?this.gpgpu.beginQuery():{startMs:tt(),endMs:null}},Ts.prototype.endTimer=function(t){return 0<_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")?this.gpgpu.endQuery():t.endMs=tt(),t},Ts.prototype.getQueryTime=function(n){return y(this,void 0,void 0,function(){var e;return R(this,function(t){return 0<_().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")?[2,this.gpgpu.waitForQueryAndGetTime(n)]:[2,(e=n).endMs-e.startMs]})})},Ts.prototype.disposeData=function(t){if(!this.pendingDisposal.has(t)){if(this.pendingRead.has(t))return this.pendingDisposal.add(t),void this.pendingDeletes++;if(this.texData.has(t)){this.releaseGPUData(t);var e=this.texData.get(t).complexTensors;null!=e&&(e.real.dispose(),e.imag.dispose()),this.texData.delete(t)}}},Ts.prototype.releaseGPUData=function(t){var e=this.texData.get(t),n=e.texture,r=e.dtype,o=e.texShape,i=e.usage,a=e.isPacked,s=e.slice,u=s&&s.origDataId||t,c=this.dataRefCount.get(u);1<c?this.dataRefCount.set(u,c-1):(this.dataRefCount.delete(u),null!=n&&(this.numBytesInGPU-=this.computeBytes(o,r),this.textureManager.releaseTexture(n,o,i,a)));var l=this.texData.get(t);l.texture=null,l.texShape=null,l.isPacked=!1,l.slice=null},Ts.prototype.getTexture=function(t){return this.uploadToGPU(t),this.texData.get(t).texture},Ts.prototype.getDataInfo=function(t){return this.texData.get(t)},Ts.prototype.getCPUBackend=function(){return _().getBool("WEBGL_CPU_FORWARD")?(null==this.cpuBackend&&(this.cpuBackend=Kt.findBackend("cpu")),this.cpuBackend):null},Ts.prototype.shouldExecuteOnCPU=function(t,e){var n=this;return void 0===e&&(e=128),null!=this.getCPUBackend()&&t.every(function(t){return null==n.texData.get(t.dataId).texture&&t.size<e})},Ts.prototype.getGPGPUContext=function(){return this.gpgpu},Ts.prototype.complex=function(t,e){var n=this.makeOutput(t.shape,"complex64");return this.texData.get(n.dataId).complexTensors={real:Kt.keep(t.clone()),imag:Kt.keep(e.clone())},n},Ts.prototype.real=function(t){return this.texData.get(t.dataId).complexTensors.real.clone()},Ts.prototype.imag=function(t){return this.texData.get(t.dataId).complexTensors.imag.clone()},Ts.prototype.slice=function(t,e,n){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.slice(t,e,n);if(0===L(n))return In([],n,t.dtype);var r=this.texData.get(t.dataId).isPacked,o=eo(t.shape,e,n);if(!r&&o)return this.uploadToGPU(t.dataId),this.shallowSlice(t,e,n);var i=_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Za(n):new Ya(n),a=i.getCustomSetupFunc(e);return this.compileAndRun(i,[t],null,a)},Ts.prototype.shallowSlice=function(t,e,n){var r=this.texData.get(t.dataId),o=this.makeOutput(n,t.dtype),i=this.texData.get(o.dataId);Object.assign(i,r),i.shape=n,i.dtype=t.dtype;var a=no(e,t.strides);r.slice&&(a+=r.slice.flatOffset),i.slice={flatOffset:a,origDataId:r.slice&&r.slice.origDataId||t.dataId};var s=this.dataRefCount.get(i.slice.origDataId)||1;return this.dataRefCount.set(i.slice.origDataId,s+1),o},Ts.prototype.stridedSlice=function(t,e,n,r){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.stridedSlice(t,e,n,r);var o=Qr(e,n,r);if(o.some(function(t){return 0===t}))return In([],o);var i=new Qa(e,r,o);return this.compileAndRun(i,[t])},Ts.prototype.reverse=function(t,e){var n=_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new qa(t.shape,e):new Ha(t.shape,e);return this.compileAndRun(n,[t])},Ts.prototype.concat=function(t,e){if("complex64"===t[0].dtype){var n=t.map(function(t){return En(t)}),r=t.map(function(t){return _n(t)});return Cn(this.concat(n,e),this.concat(r,e))}if(this.shouldExecuteOnCPU(t))return this.cpuBackend.concat(t,e);if(1===t.length)return t[0];if(t.length>_().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){var o=Math.floor(t.length/2),i=this.concat(t.slice(0,o),e),a=this.concat(t.slice(o),e);return this.concat([i,a],e)}if(_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&1<t[0].rank){var s=new gi(t.map(function(t){return t.shape}),e);return this.compileAndRun(s,t)}var u=bn(t.map(function(t){return t.shape}),e),c=t.map(function(t){return t.as2D(-1,L(t.shape.slice(e)))}),l=new mi(c.map(function(t){return t.shape}));return this.compileAndRun(l,c).reshape(u)},Ts.prototype.neg=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.neg(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,ys,t.dtype);var e=new us(t.shape,ys);return this.compileAndRun(e,[t])},Ts.prototype.batchMatMul=function(t,e,n,r){var o=n?t.shape[2]:t.shape[1],i=r?e.shape[1]:e.shape[2],a=n?t.shape[1]:t.shape[2],s=t.shape[0];if((1===o||1===i)&&1e3<a){n&&(t=t.transpose([0,2,1])),r&&(e=e.transpose([0,2,1]));var u=1===i?t:t.as3D(s,a,1),c=1===i?2:1,l=1===i?e.as3D(s,1,a):e;return this.multiply(u,l).sum(c,!0)}var h=Pt(t.dtype,e.dtype),f=new Sa(t.shape,[s,o,i],n,r);return this.compileAndRun(f,[t,e],h)},Ts.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,i=t.bias,a=t.activation,s=t.preluActivationWeights,u=r?e.shape[2]:e.shape[1],c=o?n.shape[1]:n.shape[2],l=e.shape[0],h=Pt(e.dtype,n.dtype),f=null!=i,p=null!=s,d=a?Ss(a,!0):null,v=new Sa(e.shape,[l,u,c],r,o,f,d,p),m=[e,n];return i&&m.push(i),s&&m.push(s),this.compileAndRun(v,m,h)},Ts.prototype.multiply=function(t,e){if("complex64"===t.dtype){var n=this.texData.get(t.dataId),r=this.texData.get(e.dataId),o=new fi("return areal * breal - aimag * bimag;",t.shape,e.shape),i=new fi("return areal * bimag + aimag * breal;",t.shape,e.shape),a=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag),this.makeComplexComponentTensorInfo(e,r.complexTensors.real),this.makeComplexComponentTensorInfo(e,r.complexTensors.imag)],s=this.compileAndRun(o,a),u=this.compileAndRun(i,a),c=this.complex(s,u);return s.dispose(),u.dispose(),c}if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.multiply(t,e);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,bi,t.dtype);var l=new pi(bi,t.shape,e.shape);return this.compileAndRun(l,[t,e],t.dtype)},Ts.prototype.batchNormalization=function(t,e,n,r,o,i){var a=[t,e,n],s=null;null!=i&&(s=i.shape,a.push(i));var u=null;if(null!=o&&(u=o.shape,a.push(o)),_().getBool("WEBGL_PACK_NORMALIZATION")){var c=new hi(t.shape,e.shape,n.shape,s,u,r);return this.compileAndRun(c,a)}var l=new li(t.shape,e.shape,n.shape,s,u,r);return this.compileAndRun(l,a)},Ts.prototype.localResponseNormalization4D=function(t,e,n,r,o){var i=_().getBool("WEBGL_PACK_NORMALIZATION")?new Ia(t.shape,e,n,r,o):new Ea(t.shape,e,n,r,o);return this.compileAndRun(i,[t])},Ts.prototype.LRNGrad=function(t,e,n,r,o,i,a){var s=new _a(e.shape,r,o,i,a);return this.compileAndRun(s,[e,n,t])},Ts.prototype.tile=function(t,e){if("string"===t.dtype){var n=this.readSync(t.dataId).map(function(t){return rt(t)});return Go(cr(t.shape,t.dtype,n),e)}var r=new is(t.shape,e);return this.compileAndRun(r,[t])},Ts.prototype.pad=function(t,e,n){var r=_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Ma(t.shape,e,n):new Fa(t.shape,e,n);return this.compileAndRun(r,[t])},Ts.prototype.transpose=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.transpose(t,e);var n=_().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new ss(t.shape,e):new as(t.shape,e);return this.compileAndRun(n,[t])},Ts.prototype.gather=function(t,e,n){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.gather(t,e,n);var r=new Yi(t.shape,e.size,n);return this.compileAndRun(r,[t,e])},Ts.prototype.batchToSpaceND=function(t,e,n){P(t.rank<=4,function(){return"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet"});var r=e.reduce(function(t,e){return t*e}),o=Lr(t.shape,e,r),i=Wr(o.length,e.length),a=zr(t.shape,e,r),s=Ur(n,e.length),u=Vr(a,n,e.length);return t.reshape(o).transpose(i).reshape(a).slice(s,u)},Ts.prototype.spaceToBatchND=function(t,e,n){P(t.rank<=4,function(){return"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet"});var r=e.reduce(function(t,e){return t*e}),o=[[0,0]];o.push.apply(o,n);for(var i=1+e.length;i<t.shape.length;++i)o.push([0,0]);var a=t.pad(o),s=Lr(a.shape,e,r,!1),u=Wr(s.length,e.length,!1),c=zr(a.shape,e,r,!1);return a.reshape(s).transpose(u).reshape(c)},Ts.prototype.reduce=function(t,e,n){var r=t.shape[0],o=t.shape[1],i=qr(o),a=new Ba({windowSize:i,inSize:o,batchSize:r},e),s=this.compileAndRun(a,[t],n);return 1===s.shape[1]?s:this.reduce(s,e,n)},Ts.prototype.argReduce=function(t,e,n){void 0===n&&(n=null);var r=t.shape[0],o=t.shape[1];null!=n&&(r=n.shape[0],o=n.shape[1]);var i=qr(o),a=new Xo({windowSize:i,inSize:o,batchSize:r},e,null==n),s=[t];null!=n&&s.push(n);var u=this.compileAndRun(a,s,"int32");return 1===u.shape[1]?u:this.argReduce(t,e,u)},Ts.prototype.argReducePacked=function(t,e,n){void 0===n&&(n=null);var r=null!=n?n.shape:t.shape,o=qr(r[r.length-1]),i=new si(r,o,e,null==n),a=null==n?[t]:[t,n],s=this.compileAndRun(i,a,"int32");return s.rank===t.rank?this.argReducePacked(t,e,s):s},Ts.prototype.sum=function(t,e){vn("sum",e,t.rank);var n=pn(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o),a=Bt(t.dtype);return this.reduce(i,"sum",a).reshape(r)},Ts.prototype.prod=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.prod(t,e);var n=pn(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o),a=Bt(t.dtype);return this.reduce(i,"prod",a).reshape(r)},Ts.prototype.unsortedSegmentSum=function(t,e,n){var r=0,o=mn([r],t.rank),i=t;null!=o&&(i=t.transpose(o),r=yn(1,t.rank)[0]);var a=function(t,e,n){for(var r=[],o=t.length,i=0;i<o;i++)i!==e?r.push(t[i]):r.push(n);return r}(i.shape,r,n),s=L([i.shape[r]]),u=i.as2D(-1,s),c=Bt(t.dtype),l=this.segOpCompute(u,"unsortedSegmentSum",e,c,n).reshape(a);return null!=o&&(l=l.transpose(gn(o))),l},Ts.prototype.segOpCompute=function(t,e,n,r,o){var i=t.shape[0],a=t.shape[1],s=function(t,e){var n,r=!1;for(t<=30?(n=t,r=!0):n=X(t,Math.floor(Math.sqrt(t)));!r;)e<n||n===t?r=!0:n=X(t,n+1);return n}(a,o),u=new Ka({windowSize:s,inSize:a,batchSize:i,numSegments:o},e),c=this.compileAndRun(u,[t,n],r);return c.shape[1]===o?c:(n=Wn(0,o).tile([a/s]),this.segOpCompute(c,e,n,r,o))},Ts.prototype.argMinMaxReduce=function(t,e,n){var r=[e];if(vn("arg"+n.charAt(0).toUpperCase()+n.slice(1),r,t.rank),!_().getBool("WEBGL_PACK_REDUCE")||t.rank<=2){var o=pn(t.shape,r),i=o[0],a=L(o[1]),s=t.as2D(-1,a);return this.argReduce(s,n).reshape(i)}return this.argReducePacked(t,n)},Ts.prototype.argMin=function(t,e){return this.argMinMaxReduce(t,e,"min")},Ts.prototype.argMax=function(t,e){return this.argMinMaxReduce(t,e,"max")},Ts.prototype.cumsum=function(t,e,n,r){if(e!==t.rank-1)throw new Error("WebGL cumsum shader expects an inner-most axis="+(t.rank-1)+" but got axis="+e);var o=new Wi(t.shape,n,r);return this.compileAndRun(o,[t])},Ts.prototype.equal=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(equal(a, b));\n","bool");var n=new pi("return float(a == b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},Ts.prototype.notEqual=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(notEqual(a, b));\n","bool");var n=new pi("return float(a != b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},Ts.prototype.less=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.less(t,e);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(lessThan(a, b));\n","bool");var n=new pi("return float(a < b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},Ts.prototype.lessEqual=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(lessThanEqual(a, b));\n","bool");var n=new pi("return float(a <= b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},Ts.prototype.greater=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.greater(t,e);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(greaterThan(a, b));\n","bool");var n=new pi("return float(a > b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},Ts.prototype.greaterEqual=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(greaterThanEqual(a, b));\n","bool");var n=new pi("return float(a >= b);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},Ts.prototype.logicalNot=function(t){var e=new us(t.shape,"return float(!(x >= 1.0));");return this.compileAndRun(e,[t])},Ts.prototype.logicalAnd=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n","bool");var n=new pi("return float(a >= 1.0 && b >= 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},Ts.prototype.logicalOr=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n","bool");var n=new pi("return float(a >= 1.0 || b >= 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e],"bool")},Ts.prototype.select=function(t,e,n){var r=new Xa(t.rank,e.shape,e.rank);return this.compileAndRun(r,[t,e,n],Pt(e.dtype,n.dtype))},Ts.prototype.where=function(t){an("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");var e=t.dataSync();return qo(t.shape,e)},Ts.prototype.topk=function(t,e,n){return Ho(t.dataSync(),t.shape,t.dtype,e)},Ts.prototype.min=function(t,e){vn("min",e,t.rank);var n=pn(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o);return this.reduce(i,"min",i.dtype).reshape(r)},Ts.prototype.minimum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.minimum(t,e);var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new di("\n  vec4 result = vec4(min(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new pi("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return min(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},Ts.prototype.mod=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new di("\n  vec4 result = mod(a, b);\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new pi("if (b == 0.0) return NAN;\n  return mod(a, b);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},Ts.prototype.max=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.max(t,e);vn("max",e,t.rank);var n=pn(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o);return this.reduce(i,"max",i.dtype).reshape(r)},Ts.prototype.maximum=function(t,e){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.maximum(t,e);var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new di("\n  vec4 result = vec4(max(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new pi("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return max(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},Ts.prototype.all=function(t,e){vn("all",e,t.rank);var n=pn(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o);return this.reduce(i,"all",i.dtype).reshape(r)},Ts.prototype.any=function(t,e){vn("any",e,t.rank);var n=pn(t.shape,e),r=n[0],o=L(n[1]),i=t.as2D(-1,o);return this.reduce(i,"any",i.dtype).reshape(r)},Ts.prototype.realDivide=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n","float32",!0);var n=new pi("\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;",t.shape,e.shape);return this.compileAndRun(n,[t,e],"float32")},Ts.prototype.floorDiv=function(t,e){if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,"\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    result[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    result[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    result[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    result[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4(result);\n","int32");var n=new pi("\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n",t.shape,e.shape);return this.compileAndRun(n,[t,e],"int32")},Ts.prototype.add=function(t,e){if("complex64"===t.dtype&&"complex64"===e.dtype)return this.complexSeparableBinaryOp(t,e,yi);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.add(t,e);var n=Pt(t.dtype,e.dtype);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,yi,n);var r=new pi(yi,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},Ts.prototype.packedUnaryOp=function(t,e,n){var r=new cs(t.shape,e);return this.compileAndRun(r,[t],n)},Ts.prototype.packedBinaryOp=function(t,e,n,r,o){void 0===o&&(o=!1);var i=new di(n,t.shape,e.shape,o);return this.compileAndRun(i,[t,e],r)},Ts.prototype.complexSeparableBinaryOp=function(a,s,u){var c=this,t=this.texData.get(a.dataId),e=this.texData.get(s.dataId),n=[[t.complexTensors.real,e.complexTensors.real],[t.complexTensors.imag,e.complexTensors.imag]].map(function(t){var e=t[0],n=t[1],r=c.makeComplexComponentTensorInfo(a,e),o=c.makeComplexComponentTensorInfo(s,n),i=new pi(u,a.shape,s.shape);return c.compileAndRun(i,[r,o],Pt(e.dtype,n.dtype))}),r=n[0],o=n[1],i=this.complex(r,o);return r.dispose(),o.dispose(),i},Ts.prototype.makeComplexComponentTensorInfo=function(t,e){return{dataId:e.dataId,dtype:e.dtype,shape:t.shape}},Ts.prototype.addN=function(t){if(1===t.length)return t[0];if(t.length>_().get("WEBGL_MAX_TEXTURES_IN_SHADER")){var e=Math.floor(t.length/2),n=this.addN(t.slice(0,e)),r=this.addN(t.slice(e));return this.addN([n,r])}var o=t.map(function(t){return t.dtype}).reduce(function(t,e){return Pt(t,e)}),i=t.map(function(t){return t.shape}),a=_().getBool("WEBGL_PACK")?new Ko(t[0].shape,i):new jo(t[0].shape,i);return this.compileAndRun(a,t,o)},Ts.prototype.subtract=function(t,e){if("complex64"===t.dtype&&"complex64"===e.dtype)return this.complexSeparableBinaryOp(t,e,xi);if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.subtract(t,e);var n=Pt(t.dtype,e.dtype);if(_().getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(t,e,xi,t.dtype);var r=new pi(xi,t.shape,e.shape);return this.compileAndRun(r,[t,e],n)},Ts.prototype.pow=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new di("\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new pi("\nif(a < 0.0 && floor(b) < b){\n  return NAN;\n}\nif (b == 0.0) {\n  return 1.0;\n}\nreturn (round(mod(b, 2.0)) != 1) ?\n    pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",t.shape,e.shape),r=Pt(t.dtype,e.dtype);return this.compileAndRun(n,[t,e],r)},Ts.prototype.ceil=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.ceil(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,xs,t.dtype);var e=new us(t.shape,xs);return this.compileAndRun(e,[t])},Ts.prototype.floor=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.floor(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,bs,t.dtype);var e=new us(t.shape,bs);return this.compileAndRun(e,[t])},Ts.prototype.sign=function(t){var e=new us(t.shape,"\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n");return this.compileAndRun(e,[t])},Ts.prototype.isNaN=function(t){var e=new us(t.shape,"return float(isnan(x));");return this.compileAndRun(e,[t],"bool")},Ts.prototype.isInf=function(t){var e=new us(t.shape,"return float(isinf(x));");return this.compileAndRun(e,[t],"bool")},Ts.prototype.isFinite=function(t){var e=new us(t.shape,"return float(!isnan(x) && !isinf(x));");return this.compileAndRun(e,[t],"bool")},Ts.prototype.round=function(t){var e=new us(t.shape,"\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n");return this.compileAndRun(e,[t])},Ts.prototype.exp=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.exp(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,ws,t.dtype);var e=new us(t.shape,ws);return this.compileAndRun(e,[t])},Ts.prototype.expm1=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.expm1(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Cs,t.dtype);var e=new us(t.shape,Cs);return this.compileAndRun(e,[t])},Ts.prototype.softmax=function(t,e){var n=D([e],t.shape),r=this.max(t,n),o=dn(r.shape,n),i=this.subtract(t,r.reshape(o)),a=this.exp(i),s=this.sum(a,n).reshape(o);return this.realDivide(a,s)},Ts.prototype.log=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.log(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,"\n  vec4 result = log(x);\n  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\n\n  return result;\n",t.dtype);var e=new us(t.shape,"if (x < 0.0) return NAN;\n  return log(x);");return this.compileAndRun(e,[t])},Ts.prototype.log1p=function(t){var e=new us(t.shape,"return log(1.0 + x);");return this.compileAndRun(e,[t])},Ts.prototype.sqrt=function(t){var e=new us(t.shape,"return sqrt(x);");return this.compileAndRun(e,[t])},Ts.prototype.rsqrt=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.rsqrt(t);var e=new us(t.shape,"return inversesqrt(x);");return this.compileAndRun(e,[t])},Ts.prototype.reciprocal=function(t){var e=new us(t.shape,"return 1.0 / x;");return this.compileAndRun(e,[t])},Ts.prototype.relu=function(t){var e;return e=_().getBool("WEBGL_PACK")?new cs(t.shape,_s):new us(t.shape,vs),this.compileAndRun(e,[t])},Ts.prototype.relu6=function(t){var e;return e=_().getBool("WEBGL_PACK")?new cs(t.shape,Is):new us(t.shape,ms),this.compileAndRun(e,[t])},Ts.prototype.prelu=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new di(Ci,t.shape,e.shape):new pi(wi,t.shape,e.shape);return this.compileAndRun(n,[t,e])},Ts.prototype.elu=function(t){if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Rs,t.dtype);var e=new us(t.shape,gs);return this.compileAndRun(e,[t])},Ts.prototype.eluDer=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new di("\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\n",t.shape,e.shape):new pi("return (b >= 1.0) ? a : a * (b + 1.0);",t.shape,e.shape);return this.compileAndRun(n,[t,e])},Ts.prototype.selu=function(t){var e=new us(t.shape,"\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = 1.7580993408473768;\n  float scale = 1.0507009873554805;\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n");return this.compileAndRun(e,[t])},Ts.prototype.int=function(t){var e=new us(t.shape,"return float(int(x));");return this.compileAndRun(e,[t],"int32")},Ts.prototype.clip=function(t,e,n){var r,o=(r=_().getBool("WEBGL_PACK_CLIP")?new _i(t.shape):new Ei(t.shape)).getCustomSetupFunc(e,n);return this.compileAndRun(r,[t],null,o)},Ts.prototype.abs=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.abs(t);if(_().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,ds,t.dtype);var e=new us(t.shape,ds);return this.compileAndRun(e,[t])},Ts.prototype.complexAbs=function(t){var e=this.texData.get(t.dataId),n=new vi(t.shape),r=[this.makeComplexComponentTensorInfo(t,e.complexTensors.real),this.makeComplexComponentTensorInfo(t,e.complexTensors.imag)];return this.compileAndRun(n,r)},Ts.prototype.sigmoid=function(t){var e=new us(t.shape,"return 1.0 / (1.0 + exp(-1.0 * x));");return this.compileAndRun(e,[t])},Ts.prototype.softplus=function(t){var e=new us(t.shape,"\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n");return this.compileAndRun(e,[t])},Ts.prototype.sin=function(t){var e=new us(t.shape,"if (isnan(x)) return x;\n  return sin(x);\n");return this.compileAndRun(e,[t])},Ts.prototype.cos=function(t){var e=new us(t.shape,"if (isnan(x)) return x;\n  return cos(x);\n");return this.compileAndRun(e,[t])},Ts.prototype.tan=function(t){var e=new us(t.shape,"return tan(x);");return this.compileAndRun(e,[t])},Ts.prototype.asin=function(t){var e=new us(t.shape,"if (isnan(x)) return x;\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return asin(x);\n");return this.compileAndRun(e,[t])},Ts.prototype.acos=function(t){var e=new us(t.shape,"if (isnan(x)) return x;\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return acos(x);\n");return this.compileAndRun(e,[t])},Ts.prototype.atan=function(t){var e=new us(t.shape,"if (isnan(x)) return x;\n  return atan(x);\n");return this.compileAndRun(e,[t])},Ts.prototype.atan2=function(t,e){var n=_().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new di("\n  vec4 result = atan(a, b);\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",t.shape,e.shape):new pi("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return atan(a, b);\n",t.shape,e.shape);return this.compileAndRun(n,[t,e])},Ts.prototype.sinh=function(t){var e=new us(t.shape,"\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},Ts.prototype.cosh=function(t){var e=new us(t.shape,"\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},Ts.prototype.tanh=function(t){var e=new us(t.shape,"\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n");return this.compileAndRun(e,[t])},Ts.prototype.asinh=function(t){var e=new us(t.shape,"if (isnan(x)) return x;return log(x + sqrt(x * x + 1.0));");return this.compileAndRun(e,[t])},Ts.prototype.acosh=function(t){var e=new us(t.shape,"if (isnan(x)) return x;\n  if (x < 1.0) return NAN;\n  return log(x + sqrt(x * x - 1.0));");return this.compileAndRun(e,[t])},Ts.prototype.atanh=function(t){var e=new us(t.shape,"if (isnan(x)) return x;\n  if ((x < -1.0) || (x > 1.0)) return NAN;\n  return (log(1.0 + x) - log(1.0 - x)) / 2.0;");return this.compileAndRun(e,[t])},Ts.prototype.erf=function(t){var e=new us(t.shape,'\n  // Error function is calculated approximately with elementary function.\n  // See "Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables", Abramowitz and Stegun.\n  float p = 0.3275911;\n  float a1 = 0.254829592;\n  float a2 = -0.284496736;\n  float a3 = 1.421413741;\n  float a4 = -1.453152027;\n  float a5 = 1.061405429;\n\n  float sign = sign(x);\n  x = abs(x);\n  float t = 1.0 / (1.0 + p * x);\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\n');return this.compileAndRun(e,[t])},Ts.prototype.step=function(t,e){var n,r=new us(t.shape,(void 0===(n=e)&&(n=0),ps+"\n    return x > 0.0 ? 1.0 : float("+n+");\n  "));return this.compileAndRun(r,[t])},Ts.prototype.conv2dByMatMul=function(t,e,n,r,o,i){var a=t.shape,s=this.texData.get(t.dataId),u=n.inChannels,c=a[0]*a[1]*a[2],l=n.outChannels,h="channelsLast"===n.dataFormat,f=(1==c||1===l)&&1e3<u,p=a[2]%2!=0&&!!s.isPacked;if(f||!_().getBool("WEBGL_LAZILY_UNPACK")||!_().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!p){var d=h?a[0]*a[1]*a[2]:a[0]*a[2]*a[3],v=this.reshape(t,[1,d,n.inChannels]),m=this.reshape(e,[1,n.inChannels,n.outChannels]);return this.reshape(this.fusedBatchMatMul({a:v,b:m,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:i}),n.outShape)}var g=h?a[0]*a[1]*(a[2]+1):a[0]*a[2]*(a[3]+1),y={dataId:t.dataId,shape:[1,g,n.inChannels],dtype:t.dtype},x=s.shape;s.shape=s.shape.slice(),s.shape[s.shape.length-2]++,P(Ge(s.shape,y.shape),function(){return"packed reshape "+s.shape+" to "+y.shape+" isn't free"});var b=this.reshape(e,[1,n.inChannels,n.outChannels]),w=this.fusedBatchMatMul({a:y,b:b,transposeA:!1,transposeB:!1,bias:r,activation:o,preluActivationWeights:i}),C=this.texData.get(w.dataId);return P(C.isPacked,function(){return"batchMatMul result is expected to be packed"}),s.shape=x,C.shape=n.outShape,Kt.makeTensorFromDataId(w.dataId,n.outShape,w.dtype)},Ts.prototype.conv2dWithIm2Row=function(t,e,n,r,o,i){var a=n.filterWidth,s=n.filterHeight,u=n.inChannels,c=n.outWidth,l=n.outHeight,h="channelsLast"===n.dataFormat,f=a*s*u,p=l*c,d=[f,p],v=t.squeeze([0]),m=e.reshape([1,f,-1]),g=new Ca(d,v.shape,n),y=this.compileAndRun(g,[v]).reshape([1,d[0],d[1]]),x=null!=r,b=null!=i,w=o?Ss(o,!0):null,C=new Sa(y.shape,[1,p,n.outChannels],!0,!1,x,w,b),E=[y,m];r&&E.push(r),b&&E.push(i);var _=this.compileAndRun(C,E);return h?_.reshape([1,l,c,n.outChannels]):_.reshape([1,n.outChannels,l,c])},Ts.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,i=t.activation,a=t.preluActivationWeights;if(1===r.filterHeight&&1===r.filterWidth&&1===r.dilationHeight&&1===r.dilationWidth&&1===r.strideHeight&&1===r.strideWidth&&("SAME"===r.padInfo.type||"VALID"===r.padInfo.type))return this.conv2dByMatMul(e,n,r,o,i,a);if(_().getBool("WEBGL_CONV_IM2COL")&&1===e.shape[0])return this.conv2dWithIm2Row(e,n,r,o,i,a);var s=null!=o,u=null!=a,c=i?Ss(i,!1):null,l=new Mi(r,s,c,u),h=[e,n];return o&&h.push(o),a&&h.push(a),this.compileAndRun(l,h)},Ts.prototype.conv2d=function(t,e,n){if(1===n.filterHeight&&1===n.filterWidth&&1===n.dilationHeight&&1===n.dilationWidth&&1===n.strideHeight&&1===n.strideWidth&&("SAME"===n.padInfo.type||"VALID"===n.padInfo.type))return this.conv2dByMatMul(t,e,n);if(_().getBool("WEBGL_CONV_IM2COL")&&1===t.shape[0])return this.conv2dWithIm2Row(t,e,n);var r=new Mi(n);return this.compileAndRun(r,[t,e])},Ts.prototype.conv2dDerInput=function(t,e,n){var r=new Di(n);return this.compileAndRun(r,[t,e])},Ts.prototype.conv2dDerFilter=function(t,e,n){var r=new Si(n);return this.compileAndRun(r,[t,e])},Ts.prototype.fusedDepthwiseConv2D=function(t){var e,n=t.input,r=t.filter,o=t.convInfo,i=t.bias,a=t.activation,s=t.preluActivationWeights,u=_().getBool("WEBGL_PACK_DEPTHWISECONV")&&o.strideWidth<=2&&o.outChannels/o.inChannels==1,c=a?Ss(a,u):null,l=[n,r],h=null!=i,f=null!=s;return h&&l.push(i),f&&l.push(s),e=u?new Bi(o,h,c,f):new Pi(o,h,c,f),this.compileAndRun(e,l)},Ts.prototype.depthwiseConv2D=function(t,e,n){var r;return r=_().getBool("WEBGL_PACK_DEPTHWISECONV")&&n.strideWidth<=2&&n.outChannels/n.inChannels==1?new Bi(n):new Pi(n),this.compileAndRun(r,[t,e])},Ts.prototype.depthwiseConv2DDerInput=function(t,e,n){var r=new Fi(n);return this.compileAndRun(r,[t,e])},Ts.prototype.depthwiseConv2DDerFilter=function(t,e,n){var r=new Ni(n);return this.compileAndRun(r,[t,e])},Ts.prototype.conv3d=function(t,e,n){var r=new Oi(n);return this.compileAndRun(r,[t,e])},Ts.prototype.conv3dDerInput=function(t,e,n){var r=new Ti(n);return this.compileAndRun(r,[t,e])},Ts.prototype.conv3dDerFilter=function(t,e,n){var r=new Ai(n);return this.compileAndRun(r,[t,e])},Ts.prototype.maxPool=function(t,e){var n=new Oa(e,"max",!1);return this.compileAndRun(n,[t])},Ts.prototype.avgPool=function(t,e){var n=new Oa(e,"avg",!1);return this.compileAndRun(n,[t],"float32")},Ts.prototype.maxPoolBackprop=function(t,e,n,r){var o=new Oa(r,"max",!0),i=this.compileAndRun(o,[e]),a=new Ra(r),s=this.compileAndRun(a,[t,i],e.dtype);return i.dispose(),s},Ts.prototype.avgPoolBackprop=function(t,e,n){var r=new ui(n);return this.compileAndRun(r,[t],e.dtype)},Ts.prototype.cast=function(t,e){return Ao(t,e,this)},Ts.prototype.unstack=function(t,e){for(var n=t.shape[e],r=new Array(t.rank-1),o=0,i=0;i<t.rank;i++)i!==e&&(r[o++]=t.shape[i]);var a=new Array(t.rank).fill(0),s=t.shape.slice();s[e]=1;var u=new Array(n);for(i=0;i<u.length;i++)u[a[e]=i]=this.slice(t,a,s).reshape(r);return u},Ts.prototype.avgPool3d=function(t,e){var n=new Pa(e,"avg",!1);return this.compileAndRun(n,[t],"float32")},Ts.prototype.avgPool3dBackprop=function(t,e,n){var r=new ci(n);return this.compileAndRun(r,[t],e.dtype)},Ts.prototype.maxPool3d=function(t,e){var n=new Pa(e,"max",!1);return this.compileAndRun(n,[t],"float32")},Ts.prototype.maxPool3dBackprop=function(t,e,n,r){var o=new Pa(r,"max",!0),i=this.compileAndRun(o,[e]),a=new ka(r),s=this.compileAndRun(a,[t,i],e.dtype);return i.dispose(),s},Ts.prototype.reshape=function(t,e){var n=this.texData.get(t.dataId);if(!n.isPacked||Ge(t.shape,e)||null!==n.texture&&Ge(n.shape,e))return To(t,e);var r=this.packedReshape(t,e);return Kt.makeTensorFromDataId(r.dataId,r.shape,r.dtype)},Ts.prototype.resizeBilinear=function(t,e,n,r){var o=_().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Ua(t.shape,e,n,r):new za(t.shape,e,n,r);return this.compileAndRun(o,[t],"float32")},Ts.prototype.resizeBilinearBackprop=function(t,e,n){var r=new Wa(t,e,n);return this.compileAndRun(r,[t])},Ts.prototype.resizeNearestNeighbor=function(t,e,n,r){var o=new Ga(t.shape,e,n,r);return this.compileAndRun(o,[t])},Ts.prototype.resizeNearestNeighborBackprop=function(t,e,n){var r=new Va(t,e,n);return this.compileAndRun(r,[t])},Ts.prototype.multinomial=function(t,e,n,r){var o=e?t:so(t),i=o.shape[0],a=o.shape[1],s=new Ta(i,a,n),u=s.getCustomSetupFunc(r);return this.compileAndRun(s,[o],"int32",u)},Ts.prototype.oneHot=function(t,e,n,r){var o=new Da(t.size,e,n,r);return this.compileAndRun(o,[t])},Ts.prototype.diag=function(t){var e=new Gi(t.size);return this.compileAndRun(e,[t])},Ts.prototype.nonMaxSuppression=function(t,e,n,r,o){return an("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead"),Bo(t.dataSync(),e.dataSync(),n,r,o)},Ts.prototype.cropAndResize=function(t,e,n,r,o,i){var a=new Li(t.shape,e.shape,r,o,i);return this.compileAndRun(a,[t,e,n],"float32")},Ts.prototype.depthToSpace=function(t,e,n){P(1<e,function(){return"blockSize should be > 1 for depthToSpace, but was: "+e});var r=t.shape[0],o="NHWC"===n?t.shape[1]:t.shape[2],i="NHWC"===n?t.shape[2]:t.shape[3],a="NHWC"===n?t.shape[3]:t.shape[1],s=o*e,u=i*e,c=a/(e*e),l=new $i("NHWC"===n?[r,s,u,c]:[r,c,s,u],e,n);return this.compileAndRun(l,[t])},Ts.prototype.split=function(t,e,n){return Vo(t,e,n)},Ts.prototype.scatterND=function(t,e,n){var r=Xr(0,t,n),o=r.sliceRank,i=r.numUpdates,a=r.sliceSize,s=r.strides,u=r.outputSize,c=[u/a,a],l=t.reshape([i,o]),h=e.reshape([i,a]);if(0===u)return To(In([]),n);var f=kn(0),p=new ja(i,o,l.rank,h.rank,s,c);return this.compileAndRun(p,[h,l,f]).reshape(n)},Ts.prototype.sparseToDense=function(t,e,n,r){var o=Xr(0,t,n),i=o.sliceRank,a=o.numUpdates,s=o.strides,u=o.outputSize,c=new ja(a,i,t.rank,e.rank,s,[u,1],!1);return this.compileAndRun(c,[e,t,r]).reshape(n)},Ts.prototype.fft=function(t){return this.fftImpl(t,!1)},Ts.prototype.ifft=function(t){return this.fftImpl(t,!0)},Ts.prototype.fftImpl=function(t,e){var n=this.texData.get(t.dataId),r=new Xi("return real * expR - imag * expI;",t.shape,e),o=new Xi("return real * expI + imag * expR;",t.shape,e),i=[this.makeComplexComponentTensorInfo(t,n.complexTensors.real),this.makeComplexComponentTensorInfo(t,n.complexTensors.imag)],a=this.compileAndRun(r,i),s=this.compileAndRun(o,i),u=this.complex(a,s).as2D(t.shape[0],t.shape[1]);return a.dispose(),s.dispose(),u},Ts.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=Gr(t,e),i=o[0],a=o[1],s=o[2],u=o[3],c=e.reshape([a,r]),l=t.reshape([t.size/s,s]),h=new ta(r,u,[a,s]);return this.compileAndRun(h,[l,c]).reshape(i)},Ts.prototype.fill=function(t,e,n){if("string"===(n=n||j(e))){var r=F(n,L(t));return r.fill(e),Kt.makeTensor(r,t,n,this)}var o=new Ji(t,e),i=o.getCustomSetupFunc(e);return this.compileAndRun(o,[],n,i)},Ts.prototype.onesLike=function(t){if("string"===t.dtype)throw new Error("onesLike is not supported under string dtype");return this.fill(t.shape,1,t.dtype)},Ts.prototype.zerosLike=function(t){return this.fill(t.shape,"string"===t.dtype?"":0,t.dtype)},Ts.prototype.linspace=function(t,e,n){return No(t,e,n)},Ts.prototype.makeTensorInfo=function(t,e){var n=this.write(null,t,e);return this.texData.get(n).usage=null,{dataId:n,shape:t,dtype:e}},Ts.prototype.makeOutput=function(t,e){var n=this.makeTensorInfo(t,e).dataId;return Kt.makeTensorFromDataId(n,t,e,this)},Ts.prototype.unpackTensor=function(t){var e=new ls(t.shape);return this.runWebGLProgram(e,[t],t.dtype)},Ts.prototype.packTensor=function(t){var e=new Aa(t.shape);return this.runWebGLProgram(e,[t],t.dtype,null,!0)},Ts.prototype.packedReshape=function(t,e){var n=[Le(t.shape)].concat(We(t.shape)),r={dtype:t.dtype,shape:n,dataId:t.dataId},o=[Le(e)].concat(We(e)),i=new La(o,n),a=this.runWebGLProgram(i,[r],t.dtype,null,!0);return{dataId:a.dataId,shape:e,dtype:a.dtype}},Ts.prototype.decode=function(t){var e,n=this.texData.get(t),r=n.isPacked,o=n.shape,i=n.dtype,a=ze(o);return e=r?new Vi(a):new Ui(a),{dtype:i,shape:o,dataId:this.runWebGLProgram(e,[{shape:a,dtype:i,dataId:t}],i,null,!0).dataId}},Ts.prototype.runWebGLProgram=function(o,t,e,n,r){var i=this;void 0===r&&(r=!1);var a=this.makeTensorInfo(o.outputShape,e),s=this.texData.get(a.dataId);if(o.packedOutput&&(s.isPacked=!0),o.outPackingScheme===$t.DENSE){var u=se(o.outputShape);s.texShape=u.map(function(t){return 2*t})}if(null!=o.outTexUsage&&(s.usage=o.outTexUsage),0===L(a.shape))return s.values=N(a.dtype,0),a;var c=[],l=t.map(function(t){if("complex64"===t.dtype)throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");var e=i.texData.get(t.dataId);if(null==e.texture){if(!o.packedInputs&&L(t.shape)<=_().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:t.shape,texData:null,isUniform:!0,uniformValues:e.values};o.packedInputs&&(e.isPacked=!0,e.shape=t.shape)}else if(!!e.isPacked!=!!o.packedInputs)t=e.isPacked?i.unpackTensor(t):i.packTensor(t),c.push(t),e=i.texData.get(t.dataId);else if(e.isPacked&&!Ge(e.shape,t.shape)){var n=t,r=t.shape;t.shape=e.shape,t=i.packedReshape(t,r),c.push(t),e=i.texData.get(t.dataId),n.shape=r}return i.uploadToGPU(t.dataId),{shape:t.shape,texData:e,isUniform:!1}});this.uploadToGPU(a.dataId);var h,f={shape:a.shape,texData:s,isUniform:!1},p=function(t,e,n){var r="";l.concat(n).forEach(function(t){var e=null!=t.texData&&null!=t.texData.slice&&0<t.texData.slice.flatOffset,n=t.isUniform?"uniform":t.texData.texShape;r+=t.shape+"_"+n+"_"+e});var o=t.userCode;return t.constructor.name+"_"+r+"_"+o}(o,0,f),d=this.getAndSaveBinary(p,function(){return function(t,r,e,n){var o=r.userCode,i=e.map(function(t,e){var n={logicalShape:t.shape,texShape:t.isUniform?null:t.texData.texShape,isUniform:t.isUniform,isPacked:!t.isUniform&&t.texData.isPacked,flatOffset:null};return null!=t.texData&&null!=t.texData.slice&&0<t.texData.slice.flatOffset&&(n.flatOffset=t.texData.slice.flatOffset),{name:r.variableNames[e],shapeInfo:n}}),a=i.map(function(t){return t.shapeInfo}),s={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},u=ei(i,s,o,r.packedInputs),c=t.createProgram(u),l=null,h=t.getUniformLocation(c,"NAN",!1);1===_().getNumber("WEBGL_VERSION")&&(l=t.getUniformLocation(c,"INFINITY",!1));for(var f={},p=0;p<r.variableNames.length;p++){var d=r.variableNames[p];f[d]=t.getUniformLocation(c,d,!1),f["offset"+d]=t.getUniformLocation(c,"offset"+d,!1)}return{program:r,source:u,webGLProgram:c,uniformLocations:f,inShapeInfos:a,outShapeInfo:s,infLoc:l,nanLoc:h}}(i.gpgpu,o,l,f)}),v=null!=this.activeTimers;if(v&&(h=this.startTimer()),function(a,s,t,e,n){wa(s.inShapeInfos,t),wa([s.outShapeInfo],[e]);var r=e.texData.texture,o=e.texData.texShape;e.texData.isPacked?a.setOutputPackedMatrixTexture(r,o[0],o[1]):a.setOutputMatrixTexture(r,o[0],o[1]),a.setProgram(s.webGLProgram),1===_().getNumber("WEBGL_VERSION")&&null!==s.infLoc&&a.gl.uniform1f(s.infLoc,1/0),null!==s.nanLoc&&a.gl.uniform1f(s.nanLoc,NaN),t.forEach(function(t,e){var n=s.program.variableNames[e],r=s.uniformLocations[n],o=s.uniformLocations["offset"+n];if(null!=r)if(t.isUniform)if(L(t.shape)<2)a.gl.uniform1f(r,t.uniformValues[0]);else{var i=t.uniformValues;i instanceof Float32Array||(i=new Float32Array(i)),a.gl.uniform1fv(r,i)}else null!=t.texData.slice&&null!=o&&a.gl.uniform1i(o,t.texData.slice.flatOffset),a.setInputMatrixTexture(t.texData.texture,r,e)}),null!=n&&n(a,s.webGLProgram),a.executeProgram()}(this.gpgpu,d,l,f,n),c.forEach(function(t){return i.disposeData(t.dataId)}),v&&(h=this.endTimer(h),this.activeTimers.push({name:o.constructor.name,query:this.getQueryTime(h)})),_().getBool("WEBGL_LAZILY_UNPACK")||!s.isPacked||!1!==r)return a;var m=this.unpackTensor(a);return this.disposeData(a.dataId),m},Ts.prototype.compileAndRun=function(t,e,n,r,o){void 0===o&&(o=!1),n=n||e[0].dtype;var i=this.runWebGLProgram(t,e,n,r,o);return Kt.makeTensorFromDataId(i.dataId,i.shape,i.dtype)},Ts.prototype.getAndSaveBinary=function(t,e){return t in this.binaryCache||(this.binaryCache[t]=e()),this.binaryCache[t]},Ts.prototype.getTextureManager=function(){return this.textureManager},Ts.prototype.dispose=function(){var e=this;this.disposed||(_().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(function(t){e.gpgpu.deleteProgram(e.binaryCache[t].webGLProgram),delete e.binaryCache[t]}),this.textureManager.dispose(),null!=this.canvas&&"undefined"!=typeof HTMLCanvasElement&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)},Ts.prototype.floatPrecision=function(){var n=this;return null==this.floatPrecisionValue&&(this.floatPrecisionValue=nn(function(){if(!_().get("WEBGL_RENDER_FLOAT32_ENABLED")){var t=_().getBool("DEBUG");_().set("DEBUG",!1);var e=n.abs(kn(1e-8)).dataSync()[0];if(_().set("DEBUG",t),0<e)return 32}return 16})),this.floatPrecisionValue},Ts.prototype.epsilon=function(){return 32===this.floatPrecision()?1e-7:1e-4},Ts.prototype.uploadToGPU=function(t){var e,n=this.texData.get(t),r=n.shape,o=n.dtype,i=n.values,a=n.texture,s=n.usage,u=n.isPacked;if(null==a){var c,l=null!=this.activeTimers;l&&(c=tt());var h=n.texShape;if(null==h&&(h=Ue(r,u),n.texShape=h),null!=i){var f=ze(r),p=void 0,d=h[1],v=h[0],m=i instanceof Uint8Array;p=u?(d=(e=ue(h[0],h[1]))[0],v=e[1],new Ki(f,[v,d],m)):new ji(f,[v,d],m);var g=this.makeTensorInfo([v,d],o);this.texData.get(g.dataId).usage=m?Jt.PIXELS:Jt.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(g.dataId),d,v,i);var y=this.runWebGLProgram(p,[g],o,null,!0),x=this.texData.get(y.dataId);n.texture=x.texture,n.texShape=x.texShape,n.isPacked=x.isPacked,n.usage=x.usage,this.disposeData(g.dataId),this.texData.delete(y.dataId),n.values=null,l&&(this.uploadWaitMs+=tt()-c)}else{var b=this.acquireTexture(h,s,o,u);n.texture=b}}},Ts.prototype.convertAndCacheOnCPU=function(t,e){var n=this.texData.get(t),r=n.dtype;return this.releaseGPUData(t),null!=e&&(n.values=function(t,e){if("float32"===e||"complex64"===e)return t;if("int32"!==e&&"bool"!==e)throw new Error("Unknown dtype "+e);for(var n="int32"===e?new Int32Array(t.length):new Uint8Array(t.length),r=0;r<n.length;++r)n[r]=Math.round(t[r]);return n}(e,r)),n.values},Ts.prototype.acquireTexture=function(t,e,n,r){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>1024*this.numMBBeforeWarning*1024){var o=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn("High memory usage in GPU: "+o+" MB, most likely due to a memory leak")}return this.textureManager.acquireTexture(t,e,r)},Ts.prototype.computeBytes=function(t,e){return t[0]*t[1]*U(e)},Ts);function Ts(t){var e,n=Ds.call(this)||this;if(n.pendingRead=new WeakMap,n.pendingDisposal=new WeakSet,n.dataRefCount=new WeakMap,n.numBytesInGPU=0,n.uploadWaitMs=0,n.downloadWaitMs=0,n.warnedAboutMemory=!1,n.pendingDeletes=0,n.disposed=!1,!_().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(null==t){var r=ie(_().getNumber("WEBGL_VERSION"));n.binaryCache=((e=_().getNumber("WEBGL_VERSION"))in 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1===o.rank&&(e=e.sum(u)),e.reshape(o.shape)},offset:function(){var t=n;return 1===o.rank&&(t=t.sum(u)),t.reshape(o.shape)}}},"BatchNormalization",{varianceEpsilon:v},l).reshape(s.shape)}function xu(t){return null==t?null:0===t.rank?t.as1D():1===t.rank?t:2===t.rank?t.as4D(1,1,t.shape[0],t.shape[1]):3===t.rank?t.as4D(1,t.shape[0],t.shape[1],t.shape[2]):t}function bu(){en("tf.batchNormalization() is going away. 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Got dilations '"+a+"'"});var n=e[0],r=e[1];return{x:function(){return wc(n.shape,t,r,o,i)},$filter:function(){return function(t,e,n,r,o){var i=t;4===t.rank&&(i=t.as5D(1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]));var a=e;4===a.rank&&(a=e.as5D(1,e.shape[0],e.shape[1],e.shape[2],e.shape[3])),P(5===i.rank,function(){return"Error in conv3dDerFilter: input must be rank 5, but got shape "+i.shape+"."}),P(5===a.rank,function(){return"Error in conv3dDerFilter: dy must be rank 5, but got shape "+a.shape+"."}),P(5===n.length,function(){return"Error in conv3dDerFilter: filterShape must be length 5, but got "+n+"."}),P(i.shape[4]===n[3],function(){return"Error in conv3dDerFilter: depth of input "+i.shape[4]+") must match input depth in filter ("+n[3]+"."}),P(a.shape[4]===n[4],function(){return"Error in conv3dDerFilter: depth of dy ("+a.shape[4]+") must match output depth for filter ("+n[4]+")."});var s=wo(i.shape,n,r,1,o);return Kt.runKernelFunc(function(t){return t.conv3dDerFilter(i,a,s)},{x5D:i,dy5D:a})}(n,t,r.shape,o,i)}}});return l?f.as4D(f.shape[1],f.shape[2],f.shape[3],f.shape[4]):f}}),Ic=wn({conv2dDerFilter_:function(t,e,n,r,o,i,a){void 0===i&&(i="NHWC");var s=t;3===t.rank&&(s=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var u=e;3===u.rank&&(u=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),P(4===s.rank,function(){return"Error in conv2dDerFilter: input must be rank 4, but got shape "+s.shape+"."}),P(4===u.rank,function(){return"Error in conv2dDerFilter: dy must be rank 4, but got shape "+u.shape+"."}),P(4===n.length,function(){return"Error in conv2dDerFilter: filterShape must be length 4, but got "+n+"."});var c="NHWC"===i?s.shape[3]:s.shape[1],l="NHWC"===i?u.shape[3]:u.shape[1];P(c===n[2],function(){return"Error in conv2dDerFilter: depth of input "+c+") must match input depth in filter ("+n[2]+"."}),P(l===n[3],function(){return"Error in conv2dDerFilter: depth of dy ("+l+") must match output depth for filter ("+n[3]+")."}),null!=a&&P(B(o),function(){return"Error in conv2dDerFilter: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+o+"."});var h=Do(i),f=bo(s.shape,n,r,1,o,a,!1,h);return Kt.runKernelFunc(function(t){return t.conv2dDerFilter(s,u,f)},{x4D:s,dy4D:u})}}),Rc=wn({conv2dDerInput_:xc}),kc=wn({depthwiseConv2d_:function(t,e,n,r,o,i,a){void 0===i&&(i=[1,1]);var s=cn(t,"x","depthwiseConv2d"),u=cn(e,"filter","depthwiseConv2d"),c=s,l=!1;3===s.rank&&(l=!0,c=s.as4D(1,s.shape[0],s.shape[1],s.shape[2])),P(4===c.rank,function(){return"Error in depthwiseConv2d: input must be rank 4, but got rank "+c.rank+"."}),P(4===u.rank,function(){return"Error in depthwiseConv2d: filter must be rank 4, but got rank "+u.rank+"."}),P(c.shape[3]===u.shape[2],function(){return"Error in depthwiseConv2d: number of input channels ("+c.shape[3]+") must match the inChannels dimension in filter "+u.shape[2]+"."}),null==i&&(i=[1,1]),P(So(n,i),function(){return"Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+i+"'"}),null!=a&&P(B(r),function(){return"Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+r+"."});var h=bo(c.shape,u.shape,n,i,r,a,!0),f=[c,u],p=Kt.runKernelFunc(function(t,e){var n=t.depthwiseConv2D(c,u,h);return e([c,u]),n},{x:c,filter:u},function(t,e){P(ko(i),function(){return"Error in gradient of depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '"+i+"'"});var n=e[0],r=e[1];return{x:function(){return Sc(n.shape,t,r,h)},filter:function(){return Dc(n,t,r.shape,h)}}},"DepthwiseConv2dNative",h,f);return l?p.as3D(p.shape[1],p.shape[2],p.shape[3]):p}}),Sc=wn({depthwiseConv2dDerInput_:function(t,e,n,r){var o=e,i=!1;3===e.rank&&(i=!0,o=e.as4D(1,e.shape[0],e.shape[1],e.shape[2]));var a=Kt.runKernelFunc(function(t){return t.depthwiseConv2DDerInput(o,n,r)},{dy4D:o});return i?a.as3D(a.shape[1],a.shape[2],a.shape[3]):a}}),Dc=wn({depthwiseConv2dDerFilter_:function(t,e,n,r){var o=t;3===t.rank&&(o=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var i=e;return 3===i.rank&&(i=e.as4D(1,e.shape[0],e.shape[1],e.shape[2])),Kt.runKernelFunc(function(t){return t.depthwiseConv2DDerFilter(o,i,r)},{x4D:o,dy4D:i})}}),Ac=wn({separableConv2d_:function(t,e,n,r,o,i,a){void 0===i&&(i=[1,1]),void 0===a&&(a="NHWC");var s=cn(t,"x","separableConv2d"),u=cn(e,"depthwiseFilter","separableConv2d"),c=cn(n,"pointwiseFilter","separableConv2d"),l=s,h=!1;if(3===s.rank&&(h=!0,l=s.as4D(1,s.shape[0],s.shape[1],s.shape[2])),"NCHW"===a)throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");P(4===l.rank,function(){return"Error in separableConv2d: input must be rank 4, but got rank "+l.rank+"."}),P(4===u.rank,function(){return"Error in separableConv2d: depthwise filter must be rank 4, but got rank "+u.rank+"."}),P(4===c.rank,function(){return"Error in separableConv2d: pointwise filter must be rank 4, but got rank "+u.rank+"."}),P(1===c.shape[0],function(){return"Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got "+c.shape[0]+"."}),P(1===c.shape[1],function(){return"Error in separableConv2d: the second dimension of pointwise filter must be 1, but got "+c.shape[1]+"."});var f=u.shape[2],p=u.shape[3];P(c.shape[2]===f*p,function(){return"Error in separableConv2d: the third dimension of pointwise filter must be "+f*p+", but got "+c.shape[2]+"."});var d=kc(l,u,r,o,a,i),v=Ec(d,c,1,"valid",a);return h?v.as3D(v.shape[1],v.shape[2],v.shape[3]):v}}),Tc=wn({conv2dTranspose_:function(t,e,n,r,o,i){return xc(n,cn(t,"x","conv2dTranspose"),cn(e,"filter","conv2dTranspose"),r,o,"NHWC",i)}}),Nc=wn({conv3dTranspose_:function(t,e,n,r,o){return wc(n,cn(t,"x","conv3dTranspose"),cn(e,"filter","conv3dTranspose"),r,o)}}),Fc=wn({matMul_:function(t,e,i,a){var n;void 0===i&&(i=!1),void 0===a&&(a=!1);var r=cn(t,"a","matMul"),o=cn(e,"b","matMul");n=Lt(r,o),r=n[0],o=n[1];var s=i?r.shape[r.rank-2]:r.shape[r.rank-1],u=a?o.shape[o.rank-1]:o.shape[o.rank-2],c=i?r.shape[r.rank-1]:r.shape[r.rank-2],l=a?o.shape[o.rank-2]:o.shape[o.rank-1],h=r.shape.slice(0,-2),f=o.shape.slice(0,-2),p=L(h),d=L(f);P(2<=r.rank&&2<=o.rank&&r.rank===o.rank,function(){return"Error in matMul: inputs must have the same rank of at least 2, got ranks "+r.rank+" and "+o.rank+"."}),P(A(h,f),function(){return"Error in matMul: outer dimensions ("+h+") and ("+f+") of Tensors with shapes "+r.shape+" and "+o.shape+" must match."}),P(s===u,function(){return"Error in matMul: inner shapes ("+s+") and ("+u+") of Tensors with shapes "+r.shape+" and "+o.shape+" and transposeA="+i+" and transposeB="+a+" must match."});var v=r.shape.slice(0,-2).concat([c,l]),m=i?r.as3D(p,s,c):r.as3D(p,c,s),g=a?o.as3D(d,l,u):o.as3D(d,u,l),y={transposeA:i,transposeB:a};return Kt.runKernelFunc(function(t,e){var n=t.batchMatMul(m,g,i,a);return e([m,g]),n},{a:m,b:g},function(t,e){var n=e,r=n[0],o=n[1];return i||a?!i&&a?{a:function(){return t.matMul(o,!1,!1)},b:function(){return t.matMul(r,!0,!1)}}:i&&!a?{a:function(){return o.matMul(t,!1,!0)},b:function(){return r.matMul(t,!1,!1)}}:{a:function(){return o.matMul(t,!0,!0)},b:function(){return t.matMul(r,!0,!0)}}:{a:function(){return t.matMul(o,!1,!0)},b:function(){return r.matMul(t,!0,!1)}}},"BatchMatMul",y).reshape(v)}}),Mc=wn({dot_:function(t,e){var n=cn(t,"t1","dot"),r=cn(e,"t2","dot");P(!(1!==n.rank&&2!==n.rank||1!==r.rank&&2!==r.rank),function(){return"Error in dot: inputs must all be rank 1 or 2, but got ranks "+n.rank+" and "+r.rank+"."});var o=1===n.rank?n.size:n.shape[1],i=1===r.rank?r.size:r.shape[0];return P(o===i,function(){return"Error in dot: inner dimensions of inputs must match, but got "+o+" and "+i+"."}),1===n.rank&&1===r.rank?n.as2D(1,-1).matMul(r.as2D(-1,1)).asScalar():1===n.rank&&2===r.rank?n.as2D(1,-1).matMul(r.as2D(r.shape[0],r.shape[1])).as1D():2===n.rank&&1===r.rank?n.matMul(r.as2D(-1,1)).as1D():n.matMul(r.as2D(r.shape[0],r.shape[1]))}}),Oc=wn({outerProduct_:function(t,e){var n=cn(t,"v1","outerProduct"),r=cn(e,"v2","outerProduct");return P(1===n.rank&&1===r.rank,function(){return"Error in outerProduct: inputs must be rank 1, but got ranks "+n.rank+" and "+r.rank+"."}),n.as2D(-1,1).matMul(r.as2D(1,-1))}}),Pc=wn({reverse_:function(t,e){var n=cn(t,"x","reverse");if(0===n.rank)return n.clone();var r=D(e,n.shape);return Kt.runKernelFunc(function(t){return t.reverse(n,r)},{$x:n},function(t){return{$x:function(){return t.reverse(r)}}}).reshapeAs(n)}}),Bc=wn({reverse1d_:function(t){var e=cn(t,"x","reverse");return P(1===e.rank,function(){return"Error in reverse1D: x must be rank 1 but got rank "+e.rank+"."}),Pc(e,0)}}),Lc=wn({reverse2d_:function(t,e){var n=cn(t,"x","reverse");return P(2===n.rank,function(){return"Error in reverse2D: x must be rank 2 but got rank "+n.rank+"."}),Pc(n,e)}}),Wc=wn({reverse3d_:function(t,e){var n=cn(t,"x","reverse");return P(3===n.rank,function(){return"Error in reverse3D: x must be rank 3 but got rank "+n.rank+"."}),Pc(n,e)}}),zc=wn({reverse4d_:function(t,e){var n=cn(t,"x","reverse");return P(4===n.rank,function(){return"Error in reverse4D: x must be rank 4 but got rank "+n.rank+"."}),Pc(n,e)}});function Uc(t,r,o,i,a,e){var n=cn(t,"x","maxPool"),s=n,u=!1;3===n.rank&&(u=!0,s=n.as4D(1,n.shape[0],n.shape[1],n.shape[2])),null==i&&(i=[1,1]),P(4===s.rank,function(){return"Error in maxPool: input must be rank 4 but got rank "+s.rank+"."}),P(So(o,i),function(){return"Error in maxPool: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+i+"'"}),null!=e&&P(B(a),function(){return"Error in maxPool: pad must be an integer when using, dimRoundingMode "+e+" but got pad "+a+"."});var c=yo(s.shape,r,o,i,a,e);if(1===c.filterWidth&&1===c.filterHeight&&A(c.inShape,c.outShape))return n.clone();var l=[s],h=Kt.runKernelFunc(function(t,e){var n=t.maxPool(s,c);return e([s,n]),n},{x:s},function(h,t){var e=t[0],n=t[1];return{x:function(){return function(t,e,n,r,o,i,a){var s=cn(h,"dy","maxPoolBackprop"),u=cn(e,"input","maxPoolBackprop"),c=cn(n,"output","maxPoolBackprop");P(u.rank===s.rank,function(){return"Rank of input ("+u.rank+") does not match rank of dy ("+s.rank+")"}),null==i&&(i=[1,1]),P(So(o,i),function(){return"Error in maxPoolBackProp: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+i+"'"}),P(4===s.rank,function(){return"Error in maxPoolBackprop: dy must be rank 4 but got rank "+s.rank+"."}),P(4===u.rank,function(){return"Error in maxPoolBackprop: input must be rank 4 but got rank "+u.rank+"."});var l=yo(u.shape,r,o,i,a,void 0);return Kt.runKernelFunc(function(t){return t.maxPoolBackprop(s,u,c,l)},{$dy:s,$input:u})}(0,e,n,r,o,i,a)}}},"MaxPool",c,l);return u?h.as3D(h.shape[1],h.shape[2],h.shape[3]):h}function Vc(t,e,n,r,o,i){var a=cn(t,"x","avgPool","float32");null==r&&(r=[1,1]),P(So(n,r),function(){return"Error in avgPool: Either strides or dilations must be 1. Got strides "+n+" and dilations '"+r+"'"});var s=a,u=!1;3===a.rank&&(u=!0,s=a.as4D(1,a.shape[0],a.shape[1],a.shape[2])),P(4===s.rank,function(){return"Error in avgPool: x must be rank 4 but got rank "+s.rank+"."}),null!=i&&P(B(o),function(){return"Error in avgPool: pad must be an integer when using, dimRoundingMode "+i+" but got pad "+o+"."});var c=yo(s.shape,e,n,r,o,i);if(1===c.filterWidth&&1===c.filterHeight&&A(c.inShape,c.outShape))return a.clone();var l=Kt.runKernelFunc(function(t){return t.avgPool(s,c)},{x:s},function(p){return{x:function(){return function(t,e,n,r,o,i){var a=cn(p,"dy","avgPoolBackprop"),s=cn(e,"input","avgPoolBackprop");P(s.rank===a.rank,function(){return"Rank of input ("+s.rank+") does not match rank of dy ("+a.rank+")"}),null==o&&(o=[1,1]),P(So(r,o),function(){return"Error in avgPoolBackprop: Either strides or dilations must be 1. Got strides "+r+" and dilations '"+o+"'"});var u=s,c=a,l=!1;3===s.rank&&(l=!0,u=s.as4D(1,s.shape[0],s.shape[1],s.shape[2]),c=a.as4D(1,a.shape[0],a.shape[1],a.shape[2])),P(4===c.rank,function(){return"Error in avgPoolBackprop: dy must be rank 4 but got rank "+c.rank+"."}),P(4===u.rank,function(){return"Error in avgPoolBackprop: input must be rank 4 but got rank "+u.rank+"."});var h=yo(u.shape,n,r,o,i),f=Kt.runKernelFunc(function(t){return t.avgPoolBackprop(c,u,h)},{dy4D:c,input4D:u});return l?f.as3D(f.shape[1],f.shape[2],f.shape[3]):f}(0,s,e,n,r,o)}}},"AvgPool",c);return l=l.cast(a.dtype),u?l.as3D(l.shape[1],l.shape[2],l.shape[3]):l}var Gc=wn({maxPool_:function(t,e,n,r,o){return Uc(t,e,n,1,r,o)}}),Hc=wn({avgPool_:function(t,e,n,r,o){return Vc(t,e,n,1,r,o)}}),qc=wn({pool_:function(t,e,n,r,o,i){null==o&&(o=[1,1]),null==i&&(i=1),0===r&&(r="valid");var a=cn(t,"x","maxPool"),s=a,u=!1;3===a.rank&&(u=!0,s=a.as4D(1,a.shape[0],a.shape[1],a.shape[2])),P(So(i,o),function(){return"Error in pool: Either strides or dilations must be 1. Got strides "+i+" and dilations '"+o+"'"});var c,l,h,f,p,d,v=yo(s.shape,e,i,o,r),m=[v.dilationHeight,v.dilationWidth];c="same"===r?(l=[v.filterHeight,v.filterWidth],h=m,f=l.map(function(t,e){return t+(t-1)*(h[e]-1)}).map(function(t){return t-1}),p=f.map(function(t){return Math.floor(t/2)}),d=f.map(function(t,e){return t-p[e]}),f.map(function(t,e){return[p[e],d[e]]})):[[0,0],[0,0]];var g,y,x,b,w,C,E,_,I=1===m[0]&&1===m[1],R=(g=[v.inHeight,v.inWidth],y=m,b=(x=c).map(function(t){return t[0]}),w=x.map(function(t){return t[1]}),C=g.concat(b,w),E=y.map(function(t,e){return(t-C[e]%t)%t}),_=w.map(function(t,e){return t+E[e]}),[y.map(function(t,e){return[b[e],_[e]]}),y.map(function(t,e){return[0,E[e]]})]),k=R[1],S=I?r:"valid",D=I?s:Nr(s,m,R[0]),A=("avg"===n?function(){return Vc(D,e,i,1,S)}:function(){return Uc(D,e,i,1,S)})(),T=I?A:fr(A,m,k);return u?T.as3D(T.shape[1],T.shape[2],T.shape[3]):T}}),jc=wn({maxPool3d_:function(t,r,o,i,a,e,s){void 0===e&&(e="NDHWC");var n=cn(t,"x","maxPool3d"),u=n,c=!1;4===n.rank&&(c=!0,u=n.as5D(1,n.shape[0],n.shape[1],n.shape[2],n.shape[3])),null==s&&(s=[1,1,1]),P(5===u.rank,function(){return"Error in maxPool3d: x must be rank 5 but got rank "+u.rank+"."}),P("NDHWC"===e,function(){return"Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of "+e}),P(So(o,s),function(){return"Error in maxPool3d: Either strides or dilations must be 1. Got strides "+o+" and dilations '"+s+"'"}),null!=a&&P(B(i),function(){return"Error in maxPool3d: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+i+"."});var l=xo(u.shape,r,o,s,i,a,e),h=Kt.runKernelFunc(function(t,e){var n=t.maxPool3d(u,l);return e([u,n]),n},{x:u},function(g,t){var e=t[0],n=t[1];return{x:function(){return function(t,e,n,r,o,i,a,s){var u=cn(g,"dy","maxPool3dBackprop"),c=cn(e,"input","maxPool3dBackprop"),l=cn(n,"output","maxPool3dBackprop"),h=u,f=c,p=l,d=!1;4===c.rank&&(d=!0,h=u.as5D(1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]),f=c.as5D(1,c.shape[0],c.shape[1],c.shape[2],c.shape[3]),p=l.as5D(1,l.shape[0],l.shape[1],l.shape[2],l.shape[3])),P(5===h.rank,function(){return"Error in maxPool3dBackprop: dy must be rank 5 but got rank "+h.rank+"."}),P(5===f.rank,function(){return"Error in maxPool3dBackprop: input must be rank 5 but got rank "+f.rank+"."}),P(5===p.rank,function(){return"Error in maxPool3dBackprop: output must be rank 5 but got rank "+p.rank+"."}),null==i&&(i=[1,1,1]),P(So(o,i),function(){return"Error in maxPool3dBackprop: Either strides or dilations must be 1. 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o=t.sent(),i=o[0],a=o[1],s=Bo(i,a,l,h,f),e!==u&&e.dispose(),n!==c&&n.dispose(),[2,s]}})})},nonMaxSuppressionWithScore:ph,nonMaxSuppressionWithScoreAsync:function(u,c,l,h,f,p){return void 0===h&&(h=.5),void 0===f&&(f=Number.NEGATIVE_INFINITY),void 0===p&&(p=0),y(this,void 0,void 0,function(){var e,n,r,o,i,a,s;return R(this,function(t){switch(t.label){case 0:return e=cn(u,"boxes","nonMaxSuppressionAsync"),n=cn(c,"scores","nonMaxSuppressionAsync"),r=ih(e,n,l,h,f,p),l=r.maxOutputSize,h=r.iouThreshold,f=r.scoreThreshold,p=r.softNmsSigma,[4,Promise.all([e.data(),n.data()])];case 1:return o=t.sent(),i=o[0],a=o[1],s=Lo(i,a,l,h,f,p),e!==u&&e.dispose(),n!==c&&n.dispose(),[2,s]}})})},cropAndResize:dh}),mh=wn({fusedMatMul_:function(t){var e,n=t.a,r=t.b,o=t.transposeA,s=void 0!==o&&o,i=t.transposeB,u=void 0!==i&&i,c=t.bias,a=t.activation,l=void 0===a?"linear":a,h=t.preluActivationWeights;if(!1===ah(Kt.state.gradientDepth,l)){var f=Fc(n,r,s,u);return null!=c&&(f=Ou(f,c)),ch(f,l,h)}var p=cn(n,"a","fused matMul"),d=cn(r,"b","fused matMul");e=Lt(p,d),p=e[0],d=e[1];var v=s?p.shape[p.rank-2]:p.shape[p.rank-1],m=u?d.shape[d.rank-1]:d.shape[d.rank-2],g=s?p.shape[p.rank-1]:p.shape[p.rank-2],y=u?d.shape[d.rank-2]:d.shape[d.rank-1],x=p.shape.slice(0,-2),b=d.shape.slice(0,-2),w=L(x),C=L(b);P(2<=p.rank&&2<=d.rank&&p.rank===d.rank,function(){return"Error in fused matMul: inputs must have the same rank of at least 2, got ranks "+p.rank+" and "+d.rank+"."}),P(A(x,b),function(){return"Error in fused matMul: outer dimensions ("+x+") and ("+b+") of Tensors with shapes "+p.shape+" and "+d.shape+" must match."}),P(v===m,function(){return"Error in fused matMul: inner shapes ("+v+") and ("+m+") of Tensors with shapes "+p.shape+" and "+d.shape+" and transposeA="+s+" and transposeB="+u+" must match."});var E,_,I=p.shape.slice(0,-2).concat([g,y]),R=s?p.as3D(w,v,g):p.as3D(w,g,v),k=u?d.as3D(C,y,m):d.as3D(C,m,y);null!=c&&go(I,(E=Lt(E=cn(c,"bias","fused 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e=t.x,n=t.filter,u=t.strides,c=t.pad,r=t.dataFormat,o=void 0===r?"NHWC":r,i=t.dilations,l=void 0===i?[1,1]:i,a=t.dimRoundingMode,h=t.bias,s=t.activation,f=void 0===s?"linear":s,p=t.preluActivationWeights;if(f=f||"linear",!1===ah(Kt.state.gradientDepth,f)){var d=Ec(e,n,u,c,o,l,a);return null!=h&&(d=Ou(d,h)),ch(d,f,p)}var v=cn(e,"x","conv2d"),m=cn(n,"filter","conv2d"),g=v,y=!1;3===v.rank&&(y=!0,g=v.as4D(1,v.shape[0],v.shape[1],v.shape[2])),P(4===g.rank,function(){return"Error in fused conv2d: input must be rank 4, but got rank "+g.rank+"."}),P(4===m.rank,function(){return"Error in fused conv2d: filter must be rank 4, but got rank "+m.rank+"."}),null!=a&&P(B(c),function(){return"Error in fused conv2d: pad must be an integer when using, dimRoundingMode "+a+" but got pad "+c+"."}),P(g.shape[3]===m.shape[2],function(){return"Error in conv2d: depth of input ("+g.shape[3]+") must match input depth for filter "+m.shape[2]+"."}),P(So(u,l),function(){return"Error in conv2D: Either strides or 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Got strides "+u+" and dilations '"+l+"'"}),P("NHWC"===o,function(){return"Error in conv2d: got dataFormat of "+o+" but only NHWC is currently supported."});var x,b,w=bo(g.shape,m.shape,u,l,c,a);null!=h&&(x=Lt(x=cn(h,"bias","fused conv2d"),v)[0],go(w.outShape,x.shape)),null!=p&&(b=cn(p,"prelu weights","fused conv2d"));var C={x:g,filter:m};null!=h&&(C.bias=x),null!=p&&(C.preluActivationWeights=b);var E=[m,g],_=Kt.runKernelFunc(function(t,e){var n=t.fusedConv2d({input:g,filter:m,convInfo:w,bias:x,activation:f,preluActivationWeights:b});return e([m,g,n]),n},C,function(t,e){var n=e,r=n[0],o=n[1],i=n[2],a=sh(t,i,f);P(ko(l),function(){return"Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. 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Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. 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o=n?t.shape[1]:t.shape[2],i=n?t.shape[2]:t.shape[1],a=r?e.shape[1]:e.shape[2],s=t.shape[0],u=this.readSync(t.dataId),c=this.readSync(e.dataId),l=n?[t.strides[0],1,t.strides[1]]:[t.strides[0],t.strides[1],1],h=l[0],f=l[1],p=l[2],d=r?[1,e.strides[1],e.strides[0]]:[e.strides[1],1,e.strides[0]],v=d[0],m=d[1],g=d[2],y=i*a,x=cr([s,i,a],t.dtype),b=x.values,w=this.blockSize,C=0;C<s;C++)for(var E=0;E<i;E+=w)for(var _=0;_<a;_+=w)for(var I=0;I<o;I+=w)for(var R=Math.min(E+w,i),k=Math.min(_+w,a),S=Math.min(I+w,o),D=E;D<R;D++)for(var A=_;A<k;A++){for(var T=0,N=I;N<S;N++)T+=u[C*h+D*f+N*p]*c[N*v+A*m+C*g];b[C*y+(D*a+A)]+=T}return x.toTensor()},Ih.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,o=t.transposeB,i=t.bias,a=t.activation,s=t.preluActivationWeights,u=this.batchMatMul(e,n,r,o);return 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n=pn(t.shape,e),r=n[0],o=n[1],i=Pn(r,Pt(t.dtype,"int32")),a=L(o),s=this.readSync(i.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*a,h=1,f=0;f<a;++f)h*=u[l+f];s[c]=h}return i},Ih.prototype.unsortedSegmentSum=function(t,e,n){wh(t,"unsortedSegmentSum");for(var r=[],o=t.rank-e.rank,i=0;i<o;++i)e=e.expandDims(i+1);for(i=0;i<n;++i){var a=kn(i,"int32"),s=nc(a,e).asType("float32").mul(t).sum(0);r.push(s)}return Mr(r)},Ih.prototype.argMin=function(t,e){wh(t,"argMin");var n=[e];vn("argMin",n,t.rank);for(var r=pn(t.shape,n),o=r[0],i=r[1],a=Pn(o,"int32"),s=L(i),u=this.readSync(a.dataId),c=this.readSync(t.dataId),l=0;l<u.length;++l){for(var h=l*s,f=c[h],p=0,d=0;d<s;++d){var v=c[h+d];v<f&&(f=v,p=d)}u[l]=p}return a},Ih.prototype.argMax=function(t,e){wh(t,"argMax");var n=[e];vn("argMax",n,t.rank);for(var r=pn(t.shape,n),o=r[0],i=r[1],a=Pn(o,"int32"),s=L(i),u=this.readSync(a.dataId),c=this.readSync(t.dataId),l=0;l<u.length;++l){for(var h=l*s,f=c[h],p=0,d=0;d<s;++d){var 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wh([t,e],"lessEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t<=e?1:0})},Ih.prototype.greater=function(t,e){return wh([t,e],"greater"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return e<t?1:0})},Ih.prototype.greaterEqual=function(t,e){return wh([t,e],"greaterEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return e<=t?1:0})},Ih.prototype.logicalNot=function(t){wh(t,"logicalNot");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)n[r]=e[r]?0:1;return this.makeOutput(n,t.shape,"bool")},Ih.prototype.logicalAnd=function(t,e){return wh([t,e],"logicalAnd"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t&&e})},Ih.prototype.logicalOr=function(t,e){return wh([t,e],"logicalOr"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t||e})},Ih.prototype.select=function(t,e,n){wh([t,e,n],"select");for(var r=this.readSync(t.dataId),o=this.readSync(e.dataId),i=this.readSync(n.dataId),a=Pn(e.shape,Pt(e.dtype,n.dtype)),s=this.readSync(a.dataId),u=0,c=0===t.rank||1<t.rank||1===e.rank?1:L(e.shape.slice(1)),l=0;l<r.length;l++)for(var h=0;h<c;h++)1===r[l]?s[u++]=o[l]:s[u++]=i[l];return a},Ih.prototype.where=function(t){wh([t],"where");var e=this.readSync(t.dataId);return qo(t.shape,e)},Ih.prototype.topk=function(t,e,n){return wh(t,"topk"),Ho(this.readSync(t.dataId),t.shape,t.dtype,e)},Ih.prototype.min=function(t,e){wh(t,"min"),vn("min",e,t.rank);for(var n=pn(t.shape,e),r=n[0],o=n[1],i=Pn(r,t.dtype),a=L(o),s=this.readSync(i.dataId),u=this.readSync(t.dataId),c=0;c<s.length;++c){for(var l=c*a,h=u[l],f=0;f<a;++f){var p=u[l+f];p<h&&(h=p)}s[c]=h}return i},Ih.prototype.minimum=function(t,e){return wh([t,e],"minimum"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.min(t,e)})},Ih.prototype.mod=function(t,e){return wh([t,e],"mod"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var 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i},Ih.prototype.squaredDifference=function(t,e){return wh([t,e],"squaredDifference"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var n=t-e;return n*n})},Ih.prototype.ceil=function(t){wh(t,"ceil");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.ceil(e[r]);return this.makeOutput(n,t.shape,"float32")},Ih.prototype.floor=function(t){wh(t,"floor");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.floor(e[r]);return this.makeOutput(n,t.shape,"float32")},Ih.prototype.sign=function(t){wh(t,"x");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)e[r]<0?n[r]=-1:0<e[r]?n[r]=1:n[r]=0;return this.makeOutput(n,t.shape,"float32")},Ih.prototype.isNaN=function(t){wh(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isNaN(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},Ih.prototype.isInf=function(t){wh(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Math.abs(e[r])===1/0&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},Ih.prototype.isFinite=function(t){wh(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isFinite(e[r])&&(n[r]=1);return this.makeOutput(n,t.shape,"bool")},Ih.prototype.round=function(t){wh(t,"round");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var o=Math.floor(e[r]);e[r]-o<.5?n[r]=Math.floor(e[r]):.5<e[r]-o?n[r]=Math.ceil(e[r]):n[r]=o%2==0?o:o+1}return this.makeOutput(n,t.shape,"float32")},Ih.prototype.exp=function(t){wh(t,"exp");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.exp(e[r]);return this.makeOutput(n,t.shape,"float32")},Ih.prototype.expm1=function(t){wh(t,"expm1");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.expm1(e[r]);return 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this.makeOutput(n,e.shape,"float32")},Ih.prototype.selu=function(t){wh(t,"selu");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=n[r];e[r]=0<=o?1.0507009873554805*o:1.7580993408473768*(Math.exp(o)-1)}return this.makeOutput(e,t.shape,"float32")},Ih.prototype.clip=function(t,e,n){wh(t,"clip");for(var r=new Float32Array(t.size),o=this.readSync(t.dataId),i=0;i<o.length;++i){var a=o[i];r[i]=n<a?n:a<e?e:a}return this.makeOutput(r,t.shape,"float32")},Ih.prototype.abs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.abs(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.complexAbs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<t.size;++r){var o=n[2*r],i=n[2*r+1];e[r]=Math.hypot(o,i)}return this.makeOutput(e,t.shape,"float32")},Ih.prototype.int=function(t){wh(t,"int");for(var e=new 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this.makeOutput(e,t.shape,"float32")},Ih.prototype.tan=function(t){wh(t,"tan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.tan(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.asin=function(t){wh(t,"asin");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asin(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.acos=function(t){wh(t,"acos");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acos(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.atan=function(t){wh(t,"atan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atan(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.atan2=function(t,e){return wh([t,e],"atan2"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.atan2(t,e)})},Ih.prototype.sinh=function(t){wh(t,"sinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sinh(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.cosh=function(t){wh(t,"cosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cosh(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.tanh=function(t){wh(t,"tanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=w(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.asinh=function(t){wh(t,"asinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asinh(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.acosh=function(t){wh(t,"acosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acosh(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.atanh=function(t){wh(t,"atanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atanh(n[r]);return this.makeOutput(e,t.shape,"float32")},Ih.prototype.erf=function(t){wh(t,"erf");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var o=Math.sign(n[r]),i=Math.abs(n[r]),a=1/(1+.3275911*i);e[r]=o*(1-((((1.061405429*a-1.453152027)*a+1.421413741)*a-.284496736)*a+.254829592)*a*Math.exp(-i*i))}return this.makeOutput(e,t.shape,"float32")},Ih.prototype.step=function(t,e){void 0===e&&(e=0),wh(t,"step");for(var n=new Float32Array(t.size),r=this.readSync(t.dataId),o=0;o<r.length;++o){var i=r[o];isNaN(i)?n[o]=NaN:n[o]=0<i?1:e}return this.makeOutput(n,t.shape,"float32")},Ih.prototype.fusedConv2d=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,i=t.activation,a=t.preluActivationWeights,s=this.conv2d(e,n,r);return o&&(s=this.add(s,o)),i&&(s=Ch(this,s,i,a)),s},Ih.prototype.conv2d=function(t,e,n){wh([t,e],"conv2d");for(var r=n.filterHeight,o=n.filterWidth,i=n.dilationHeight,a=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,c="channelsLast"===n.dataFormat,l=cr(n.outShape,t.dtype),h=t.strides[0],f=c?t.strides[1]:t.strides[2],p=c?t.strides[2]:1,d=c?1:t.strides[1],v=l.strides[0],m=c?l.strides[1]:l.strides[2],g=c?l.strides[2]:1,y=c?1:l.strides[1],x=this.readSync(t.dataId),b=this.readSync(e.dataId),w=l.values,C=0;C<n.batchSize;++C)for(var E=C*h,_=C*v,I=0;I<n.outHeight;++I)for(var R=_+I*m,k=I*n.strideHeight-u,S=0;S<r;S++){var D=k+S*i;if(!(D<0||D>=n.inHeight))for(var A=S*e.strides[0],T=E+D*f,N=0;N<n.outWidth;++N)for(var F=R+N*g,M=N*n.strideWidth-s,O=0;O<o;O++){var P=M+O*a;if(!(P<0||P>=n.inWidth))for(var B=T+P*p,L=A+O*e.strides[1],W=0;W<n.inChannels;++W){for(var z=x[B+W*d],U=0;U<n.outChannels;++U)w[F+U*y]+=z*b[L+U];L+=n.outChannels}}}return l.toTensor()},Ih.prototype.conv3d=function(t,e,n){for(var r=n.filterDepth,o=n.filterHeight,i=n.filterWidth,a=n.dilationDepth,s=n.dilationHeight,u=n.dilationWidth,c=n.padInfo.front,l=n.padInfo.left,h=n.padInfo.top,f=cr(n.outShape,t.dtype),p=this.readSync(t.dataId),d=this.readSync(e.dataId),v=f.values,m=0;m<n.batchSize;++m)for(var g=m*t.strides[0],y=m*f.strides[0],x=0;x<n.outDepth;++x)for(var b=y+x*f.strides[1],w=x*n.strideDepth-c,C=0;C<r;C++){var E=w+C*a;if(!(E<0||E>=n.inDepth))for(var _=C*e.strides[0],I=g+E*t.strides[1],R=0;R<n.outHeight;++R)for(var k=b+R*f.strides[2],S=R*n.strideHeight-h,D=0;D<o;D++){var A=S+D*s;if(!(A<0||A>=n.inHeight))for(var T=_+D*e.strides[1],N=I+A*t.strides[2],F=0;F<n.outWidth;++F)for(var M=k+F*n.outChannels,O=F*n.strideWidth-l,P=0;P<i;P++){var B=O+P*u;if(!(B<0||B>=n.inWidth))for(var L=T+P*e.strides[2],W=N+B*n.inChannels,z=L,U=0;U<n.inChannels;++U){for(var V=p[W+U],G=0;G<n.outChannels;++G)v[M+G]+=V*d[z+G];z+=n.outChannels}}}}return f.toTensor()},Ih.prototype.conv2dDerInput=function(t,e,n){wh([t,e],"conv2dDerInput");for(var r=cr(n.inShape,"float32"),o=r.values,i=this.readSync(t.dataId),a=this.readSync(e.dataId),s=e.strides,u=s[0],c=s[1],l=s[2],h=n.batchSize,f=n.filterHeight,p=n.filterWidth,d=n.inChannels,v=n.inHeight,m=n.inWidth,g=n.outChannels,y=n.outHeight,x=n.outWidth,b=n.strideHeight,w=n.strideWidth,C=n.dataFormat,E=f-1-n.padInfo.top,_=p-1-n.padInfo.left,I="channelsLast"===C,R=r.strides[0],k=I?r.strides[1]:r.strides[2],S=I?r.strides[2]:1,D=I?1:r.strides[1],A=t.strides[0],T=I?t.strides[1]:t.strides[2],N=I?t.strides[2]:1,F=I?1:t.strides[1],M=0;M<h;++M)for(var O=0;O<d;++O)for(var P=0;P<v;++P)for(var B=P-E,L=Math.max(0,Math.ceil(B/b)),W=Math.min(y,(f+B)/b),z=0;z<m;++z){for(var U=z-_,V=Math.max(0,Math.ceil(U/w)),G=Math.min(x,(p+U)/w),H=0,q=L;q<W;++q)for(var j=q*b-B,K=V;K<G;++K)for(var X=A*M+T*q+N*K,Y=u*(f-1-j)+c*(p-1-(K*w-U))+l*O,$=0;$<g;++$)H+=i[X+F*$]*a[Y+$];o[R*M+k*P+S*z+D*O]=H}return r.toTensor()},Ih.prototype.conv3dDerInput=function(t,e,n){for(var r=cr(n.inShape,"float32"),o=r.values,i=r.strides,a=i[0],s=i[1],u=i[2],c=i[3],l=this.readSync(t.dataId),h=t.strides,f=h[0],p=h[1],d=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=n.batchSize,E=n.filterDepth,_=n.filterHeight,I=n.filterWidth,R=n.inChannels,k=n.inDepth,S=n.inHeight,D=n.inWidth,A=n.outChannels,T=n.outDepth,N=n.outHeight,F=n.outWidth,M=n.strideDepth,O=n.strideHeight,P=n.strideWidth,B=E-1-n.padInfo.front,L=_-1-n.padInfo.top,W=I-1-n.padInfo.left,z=0;z<C;++z)for(var U=0;U<R;++U)for(var V=0;V<k;++V)for(var G=V-B,H=Math.max(0,Math.ceil(G/M)),q=Math.min(T,(E+G)/M),j=0;j<S;++j)for(var K=j-L,X=Math.max(0,Math.ceil(K/O)),Y=Math.min(N,(_+K)/O),$=0;$<D;++$){for(var J=$-W,Q=Math.max(0,Math.ceil(J/P)),Z=Math.min(F,(I+J)/P),tt=0,et=H;et<q;++et)for(var nt=et*M-G,rt=X;rt<Y;++rt)for(var ot=rt*O-K,it=Q;it<Z;++it)for(var at=f*z+p*et+d*rt+v*it,st=y*(E-1-nt)+x*(_-1-ot)+b*(I-1-(it*P-J))+w*U,ut=0;ut<A;++ut)tt+=l[at+ut]*m[st+ut];o[a*z+s*V+u*j+c*$+U]=tt}return r.toTensor()},Ih.prototype.conv2dDerFilter=function(t,e,n){wh([t,e],"conv2dDerFilter");for(var r=n.strideHeight,o=n.strideWidth,i=n.filterHeight,a=n.filterWidth,s="channelsLast"===n.dataFormat,u=cr(n.filterShape,"float32"),c=n.padInfo.left,l=n.padInfo.top,h=this.bufferSync(t),f=this.bufferSync(e),p=0;p<i;++p)for(var d=Math.max(0,Math.ceil((l-p)/r)),v=Math.min(n.outHeight,(n.inHeight+l-p)/r),m=0;m<a;++m)for(var g=Math.max(0,Math.ceil((c-m)/o)),y=Math.min(n.outWidth,(n.inWidth+c-m)/o),x=0;x<n.inChannels;++x)for(var b=0;b<n.outChannels;++b){for(var w=0,C=0;C<n.batchSize;++C)for(var E=d;E<v;++E)for(var _=p+E*r-l,I=g;I<y;++I){var R=m+I*o-c;w+=s?h.get(C,_,R,x)*f.get(C,E,I,b):h.get(C,x,_,R)*f.get(C,b,E,I)}u.set(w,p,m,x,b)}return u.toTensor()},Ih.prototype.conv3dDerFilter=function(t,e,n){for(var r=n.strideDepth,o=n.strideHeight,i=n.strideWidth,a=n.filterDepth,s=n.filterHeight,u=n.filterWidth,c=cr(n.filterShape,"float32"),l=c.values,h=c.strides,f=h[0],p=h[1],d=h[2],v=h[3],m=this.readSync(e.dataId),g=e.strides,y=g[0],x=g[1],b=g[2],w=g[3],C=this.readSync(t.dataId),E=t.strides,_=E[0],I=E[1],R=E[2],k=E[3],S=n.padInfo.front,D=n.padInfo.left,A=n.padInfo.top,T=0;T<a;++T)for(var N=Math.max(0,Math.ceil((S-T)/r)),F=Math.min(n.outDepth,(n.inDepth+S-T)/r),M=T*f,O=0;O<s;++O)for(var P=Math.max(0,Math.ceil((A-O)/o)),B=Math.min(n.outHeight,(n.inHeight+A-O)/o),L=O*p+M,W=0;W<u;++W)for(var z=Math.max(0,Math.ceil((D-W)/i)),U=Math.min(n.outWidth,(n.inWidth+D-W)/i),V=W*d+L,G=0;G<n.inChannels;++G)for(var H=G*v+V,q=0;q<n.outChannels;++q){for(var j=0,K=0;K<n.batchSize;++K)for(var X=K*_,Y=K*y,$=N;$<F;++$)for(var J=(T+$*r-S)*I+X,Q=$*x+Y,Z=P;Z<B;++Z)for(var tt=(O+Z*o-A)*R+J,et=Z*b+Q,nt=z;nt<U;++nt){var rt=nt*w+et;j+=C[(W+nt*i-D)*k+tt+G]*m[rt+q]}l[H+q]=j}return c.toTensor()},Ih.prototype.fusedDepthwiseConv2D=function(t){var e=t.input,n=t.filter,r=t.convInfo,o=t.bias,i=t.activation,a=t.preluActivationWeights,s=this.depthwiseConv2D(e,n,r);return o&&(s=this.add(s,o)),i&&(s=Ch(this,s,i,a)),s},Ih.prototype.depthwiseConv2D=function(t,e,n){wh([t,e],"depthwiseConv2D");for(var r=n.filterHeight,o=n.filterWidth,i=n.dilationHeight,a=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,c=n.outChannels/n.inChannels,l=cr(n.outShape,t.dtype),h=this.readSync(t.dataId),f=this.readSync(e.dataId),p=l.values,d=0;d<n.batchSize;++d)for(var v=d*t.strides[0],m=d*l.strides[0],g=0;g<n.outHeight;++g)for(var y=m+g*l.strides[1],x=g*n.strideHeight-s,b=0;b<r;++b){var w=x+b*i;if(!(w<0||w>=n.inHeight))for(var C=b*e.strides[0],E=v+w*t.strides[1],_=0;_<n.outWidth;++_)for(var I=y+_*l.strides[2],R=_*n.strideWidth-u,k=0;k<o;++k){var S=R+k*a;if(!(S<0||S>=n.inWidth))for(var D=C+k*e.strides[1],A=E+S*n.inChannels,T=I,N=D,F=0;F<n.inChannels;++F){for(var M=h[A+F],O=0;O<c;++O)p[T+O]+=M*f[N+O];T+=c,N+=c}}}return l.toTensor()},Ih.prototype.depthwiseConv2DDerInput=function(t,e,n){wh([t,e],"depthwiseConv2DDerInput");for(var r=cr(n.inShape,"float32"),o=r.values,i=r.strides,a=i[0],s=i[1],u=i[2],c=this.readSync(t.dataId),l=t.strides,h=l[0],f=l[1],p=l[2],d=this.readSync(e.dataId),v=e.strides,m=v[0],g=v[1],y=v[2],x=n.batchSize,b=n.filterHeight,w=n.filterWidth,C=n.inChannels,E=n.inHeight,_=n.inWidth,I=n.outChannels,R=n.outHeight,k=n.outWidth,S=n.strideHeight,D=n.strideWidth,A=b-1-n.padInfo.top,T=w-1-n.padInfo.left,N=I/C,F=0;F<x;++F)for(var M=0;M<C;++M)for(var O=0;O<E;++O)for(var P=O-A,B=Math.max(0,Math.ceil(P/S)),L=Math.min(R,(b+P)/S),W=0;W<_;++W){for(var z=W-T,U=Math.max(0,Math.ceil(z/D)),V=Math.min(k,(w+z)/D),G=0,H=B;H<L;++H)for(var q=H*S-P,j=U;j<V;++j)for(var K=h*F+f*H+p*j,X=m*(b-1-q)+g*(w-1-(j*D-z))+y*M,Y=0;Y<N;++Y)G+=c[K+(M*N+Y)]*d[X+Y];o[a*F+s*O+u*W+M]=G}return r.toTensor()},Ih.prototype.depthwiseConv2DDerFilter=function(t,e,n){wh([t,e],"depthwiseConv2DDerFilter");for(var r=n.strideHeight,o=n.strideWidth,i=n.filterHeight,a=n.filterWidth,s=cr(n.filterShape,"float32"),u=n.padInfo.left,c=n.padInfo.top,l=n.outChannels/n.inChannels,h=this.bufferSync(t),f=this.bufferSync(e),p=0;p<i;++p)for(var d=Math.max(0,Math.ceil((c-p)/r)),v=Math.min(n.outHeight,(n.inHeight+c-p)/r),m=0;m<a;++m)for(var g=Math.max(0,Math.ceil((u-m)/o)),y=Math.min(n.outWidth,(n.inWidth+u-m)/o),x=0;x<n.outChannels;++x){for(var b=Math.trunc(x/l),w=x%l,C=0,E=0;E<n.batchSize;++E)for(var _=d;_<v;++_)for(var I=p+_*r-c,R=g;R<y;++R){var k=m+R*o-u;C+=h.get(E,I,k,b)*f.get(E,_,R,x)}s.set(C,p,m,b,w)}return s.toTensor()},Ih.prototype.tile=function(t,e){return wh(t,"tile"),Go(this.bufferSync(t),e)},Ih.prototype.pad=function(n,t,e){wh(n,"pad");var r=t.map(function(t,e){return t[0]+n.shape[e]+t[1]}),o=t.map(function(t){return t[0]}),i=this.bufferSync(n),a=cr(r,n.dtype);0!==e&&a.values.fill(e);for(var s=0;s<n.size;s++){var u=i.indexToLoc(s),c=u.map(function(t,e){return t+o[e]});a.set.apply(a,[i.get.apply(i,u)].concat(c))}return a.toTensor()},Ih.prototype.transpose=function(t,e){wh(t,"transpose");for(var n=new Array(t.rank),r=0;r<n.length;r++)n[r]=t.shape[e[r]];var o=this.readSync(t.dataId),i=cr(n,t.dtype),a=this.bufferSync(t);for(r=0;r<t.size;++r){for(var s=a.indexToLoc(r),u=new Array(s.length),c=0;c<u.length;c++)u[c]=s[e[c]];var l=i.locToIndex(u);i.values[l]=o[r]}return i.toTensor()},Ih.prototype.gather=function(t,e,n){wh([t,e],"gather");var r=t.shape.slice(),o=this.readSync(e.dataId);r[n]=o.length;for(var i=cr(r,t.dtype),a=this.bufferSync(t),s=0;s<i.size;++s){var u=i.indexToLoc(s),c=u.slice();c[n]=o[u[n]];var l=a.locToIndex(c);i.values[s]=a.values[l]}return i.toTensor()},Ih.prototype.batchToSpaceND=function(t,e,n){wh([t],"batchToSpaceND");var r=e.reduce(function(t,e){return t*e}),o=Lr(t.shape,e,r),i=Wr(o.length,e.length),a=zr(t.shape,e,r),s=Ur(n,e.length),u=Vr(a,n,e.length);return t.reshape(o).transpose(i).reshape(a).slice(s,u)},Ih.prototype.spaceToBatchND=function(t,e,n){wh([t],"spaceToBatchND");var r=e.reduce(function(t,e){return t*e}),o=[[0,0]];o.push.apply(o,n);for(var i=1+e.length;i<t.shape.length;++i)o.push([0,0]);var a=t.pad(o),s=Lr(a.shape,e,r,!1),u=Wr(s.length,e.length,!1),c=zr(a.shape,e,r,!1);return a.reshape(s).transpose(u).reshape(c)},Ih.prototype.pool=function(t,e,n){wh(t,"pool");for(var r=e.strideHeight,o=e.strideWidth,i=e.dilationHeight,a=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=this.readSync(t.dataId),p=cr(e.outShape,t.dtype),d=p.values,v=e.outShape[1]*e.outShape[2]*e.outShape[3],m=e.outShape[2]*e.outShape[3],g=e.outShape[3],y=0;y<e.batchSize;++y)for(var x=y*v,b=y*t.strides[0],w=0;w<e.inChannels;++w)for(var C=0;C<e.outHeight;++C)for(var E=C*r-c,_=Math.max(0,E),I=Math.min(e.inHeight,s+E),R=x+C*m,k=0;k<e.outWidth;++k){for(var S=k*o-l,D=Math.max(0,S),A=Math.min(e.inWidth,u+S),T=h,N=0,F=0,M=_;M<I;M+=i){for(var O=b+M*t.strides[1],P=D;P<A;P+=a){var B=f[O+P*t.strides[2]+w];"max"===n&&T<B?T=B:"avg"===n&&(N+=B,F++)}if(isNaN(T))break}d[R+k*g+w]="avg"===n?N/F:T}return p.toTensor()},Ih.prototype.maxPool=function(t,e){return this.pool(t,e,"max")},Ih.prototype.maxPoolPositions=function(t,e){for(var n=cr(e.outShape,"int32"),r=e.strideHeight,o=e.strideWidth,i=e.dilationHeight,a=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=e.padInfo.top,l=e.padInfo.left,h=this.bufferSync(t),f=0;f<e.batchSize;++f)for(var p=0;p<e.inChannels;++p)for(var d=0;d<e.outHeight;++d){for(var v=d*r-c,m=v;m<0;)m+=i;for(var g=Math.min(e.inHeight,s+v),y=0;y<e.outWidth;++y){for(var x=y*o-l,b=x;b<0;)b+=a;for(var w=Math.min(e.inWidth,u+x),C=Number.NEGATIVE_INFINITY,E=-1,_=m;_<g;_+=i)for(var I=_-v,R=b;R<w;R+=a){var k=R-x,S=h.get(f,_,R,p);C<S&&(C=S,E=I*u+k)}n.set(E,f,d,y,p)}}return n.toTensor()},Ih.prototype.maxPoolBackprop=function(t,e,n,r){wh([e,n],"maxPoolBackprop");for(var o=this.maxPoolPositions(e,r),i=r.strideHeight,a=r.strideWidth,s=r.dilationHeight,u=r.dilationWidth,c=r.effectiveFilterHeight,l=r.effectiveFilterWidth,h=l-1-r.padInfo.left,f=c-1-r.padInfo.top,p=cr(e.shape,"float32"),d=this.bufferSync(o),v=this.bufferSync(t),m=0;m<r.batchSize;++m)for(var g=0;g<r.inChannels;++g)for(var y=0;y<r.inHeight;++y)for(var x=0;x<r.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=s){var _=(b+E)/i;if(!(_<0||_>=r.outHeight||Math.floor(_)!==_))for(var I=0;I<l;I+=u){var R=(w+I)/a;if(!(R<0||R>=r.outWidth||Math.floor(R)!==R)){var k=c*l-1-d.get(m,_,R,g)===E*l+I?1:0;0!=k&&(C+=v.get(m,_,R,g)*k)}}}p.set(C,m,y,x,g)}return p.toTensor()},Ih.prototype.avgPoolBackprop=function(t,e,n){wh([t,e],"avgPoolBackprop");for(var r=n.strideHeight,o=n.strideWidth,i=n.filterHeight,a=n.filterWidth,s=n.dilationHeight,u=n.dilationWidth,c=n.effectiveFilterHeight,l=n.effectiveFilterWidth,h=l-1-n.padInfo.left,f=c-1-n.padInfo.top,p=cr(e.shape,"float32"),d=1/(i*a),v=this.bufferSync(t),m=0;m<n.batchSize;++m)for(var g=0;g<n.inChannels;++g)for(var y=0;y<n.inHeight;++y)for(var x=0;x<n.inWidth;++x){for(var b=y-f,w=x-h,C=0,E=0;E<c;E+=s){var _=(b+E)/r;if(!(_<0||_>=n.outHeight||Math.floor(_)!==_))for(var I=0;I<l;I+=u){var R=(w+I)/o;R<0||R>=n.outWidth||Math.floor(R)!==R||(C+=v.get(m,_,R,g))}}p.set(C*d,m,y,x,g)}return p.toTensor()},Ih.prototype.pool3d=function(t,e,n){wh(t,"pool3d");for(var r=e.strideDepth,o=e.strideHeight,i=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,p=e.padInfo.top,d=e.padInfo.left,v="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=this.readSync(t.dataId),g=cr(e.outShape,t.dtype),y=g.values,x=e.outShape[1]*e.outShape[2]*e.outShape[3]*e.outShape[4],b=e.outShape[2]*e.outShape[3]*e.outShape[4],w=e.outShape[3]*e.outShape[4],C=e.outShape[4],E=0;E<e.batchSize;++E)for(var _=E*x,I=E*t.strides[0],R=0;R<e.inChannels;++R)for(var k=0;k<e.outDepth;++k){for(var S=k*r-f,D=S;D<0;)D+=a;for(var A=Math.min(e.inDepth,c+S),T=_+k*b,N=0;N<e.outHeight;++N){for(var F=N*o-p,M=F;M<0;)M+=s;for(var O=Math.min(e.inHeight,l+F),P=T+N*w,B=0;B<e.outWidth;++B){for(var L=B*i-d,W=L;W<0;)W+=u;for(var z=Math.min(e.inWidth,h+L),U=P+B*C,V=v,G=0,H=0,q=D;q<A;q+=a){for(var j=I+q*t.strides[1],K=M;K<O;K+=s){for(var X=j+K*t.strides[2],Y=W;Y<z;Y+=u){var $=m[X+Y*t.strides[3]+R];if("max"===n&&V<$?V=$:"avg"===n&&(G+=$,H++),isNaN(V))break}if(isNaN(V))break}if(isNaN(V))break}y[U+R]="avg"===n?G/H:V}}}return g.toTensor()},Ih.prototype.avgPool3d=function(t,e){return wh(t,"avgPool3d"),this.pool3d(t,e,"avg").toFloat()},Ih.prototype.avgPool3dBackprop=function(t,e,n){wh([t,e],"avgPool3dBackprop");for(var r=n.strideDepth,o=n.strideHeight,i=n.strideWidth,a=n.filterDepth,s=n.filterHeight,u=n.filterWidth,c=n.dilationDepth,l=n.dilationHeight,h=n.dilationWidth,f=n.effectiveFilterDepth,p=n.effectiveFilterHeight,d=n.effectiveFilterWidth,v=f-1-n.padInfo.front,m=d-1-n.padInfo.left,g=p-1-n.padInfo.top,y=cr(e.shape,"float32"),x=1/(a*s*u),b=this.bufferSync(t),w=0;w<n.batchSize;++w)for(var C=0;C<n.inChannels;++C)for(var E=0;E<n.inDepth;++E)for(var _=0;_<n.inHeight;++_)for(var I=0;I<n.inWidth;++I){for(var R=E-v,k=_-g,S=I-m,D=0,A=0;A<f;A+=c){var T=(R+A)/r;if(!(T<0||T>=n.outDepth||Math.floor(T)!==T))for(var N=0;N<p;N+=l){var F=(k+N)/o;if(!(F<0||F>=n.outHeight||Math.floor(F)!==F))for(var M=0;M<d;M+=h){var O=(S+M)/i;O<0||O>=n.outWidth||Math.floor(O)!==O||(D+=b.get(w,T,F,O,C))}}}y.set(D*x,w,E,_,I,C)}return y.toTensor()},Ih.prototype.maxPool3d=function(t,e){return wh(t,"maxPool3d"),this.pool3d(t,e,"max").toFloat()},Ih.prototype.maxPool3dPositions=function(t,e){for(var n=cr(e.outShape,"int32"),r=e.strideDepth,o=e.strideHeight,i=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,l=e.effectiveFilterHeight,h=e.effectiveFilterWidth,f=e.padInfo.front,p=e.padInfo.top,d=e.padInfo.left,v=this.bufferSync(t),m=0;m<e.batchSize;++m)for(var g=0;g<e.inChannels;++g)for(var y=0;y<e.outDepth;++y){for(var x=y*r-f,b=x;b<0;)b+=a;for(var w=Math.min(e.inDepth,c+x),C=0;C<e.outHeight;++C){for(var E=C*o-p,_=E;_<0;)_+=s;for(var I=Math.min(e.inHeight,l+E),R=0;R<e.outWidth;++R){for(var k=R*i-d,S=k;S<0;)S+=u;for(var D=Math.min(e.inWidth,h+k),A=Number.NEGATIVE_INFINITY,T=-1,N=b;N<w;N+=a)for(var F=N-x,M=_;M<I;M+=s)for(var O=M-E,P=S;P<D;P+=u){var B=P-k,L=v.get(m,N,M,P,g);A<=L&&(A=L,T=F*l*h+O*l+B)}n.set(T,m,y,C,R,g)}}}return n.toTensor()},Ih.prototype.maxPool3dBackprop=function(t,e,n,r){wh([e,n],"maxPool3dBackprop");for(var o=this.maxPool3dPositions(e,r),i=r.strideDepth,a=r.strideHeight,s=r.strideWidth,u=r.dilationDepth,c=r.dilationHeight,l=r.dilationWidth,h=r.effectiveFilterDepth,f=r.effectiveFilterHeight,p=r.effectiveFilterWidth,d=h-1-r.padInfo.front,v=p-1-r.padInfo.left,m=f-1-r.padInfo.top,g=cr(e.shape,"float32"),y=this.bufferSync(o),x=this.bufferSync(t),b=0;b<r.batchSize;++b)for(var w=0;w<r.inChannels;++w)for(var C=0;C<r.inDepth;++C)for(var E=0;E<r.inHeight;++E)for(var _=0;_<r.inWidth;++_){for(var I=C-d,R=E-m,k=_-v,S=0,D=0;D<h;D+=u){var A=(I+D)/i;if(!(A<0||A>=r.outDepth||Math.floor(A)!==A))for(var T=0;T<f;T+=c){var N=(R+T)/a;if(!(N<0||N>=r.outHeight||Math.floor(N)!==N))for(var F=0;F<p;F+=l){var M=(k+F)/s;if(!(M<0||M>=r.outWidth||Math.floor(M)!==M)){var O=h*f*p-1-y.get(b,A,N,M,w)===D*f*p+T*p+F?1:0;0!=O&&(S+=x.get(b,A,N,M,w)*O)}}}}g.set(S,b,C,E,_,w)}return g.toTensor()},Ih.prototype.cast=function(t,e){return Ao(t,e,this)},Ih.prototype.reshape=function(t,e){return To(t,e)},Ih.prototype.avgPool=function(t,e){return wh(t,"avgPool"),this.pool(t,e,"avg").toFloat()},Ih.prototype.resizeBilinear=function(t,e,n,r){wh(t,"resizeBilinear");for(var o=t.shape,i=o[0],a=o[1],s=o[2],u=o[3],c=this.readSync(t.dataId),l=new Float32Array(L([i,e,n,u])),h=[r&&1<e?a-1:a,r&&1<n?s-1:s],f=[r&&1<e?e-1:e,r&&1<n?n-1:n],p=0,d=h[0]/f[0],v=h[1]/f[1],m=0;m<i;m++)for(var g=0;g<e;g++)for(var y=d*g,x=Math.floor(y),b=y-x,w=Math.min(a-1,Math.ceil(y)),C=m*t.strides[0]+x*t.strides[1],E=m*t.strides[0]+w*t.strides[1],_=0;_<n;_++)for(var I=v*_,R=Math.floor(I),k=I-R,S=Math.min(s-1,Math.ceil(I)),D=C+R*t.strides[2],A=E+R*t.strides[2],T=C+S*t.strides[2],N=E+S*t.strides[2],F=0;F<u;F++){var M=c[D+F],O=c[A+F],P=M+(c[T+F]-M)*k,B=P+(O+(c[N+F]-O)*k-P)*b;l[p++]=B}return In(l,[i,e,n,u])},Ih.prototype.resizeBilinearBackprop=function(t,e,n){wh([t,e],"resizeBilinearBackprop");for(var r=e.shape,o=r[0],i=r[1],a=r[2],s=r[3],u=t.shape,c=u[1],l=u[2],h=new Float32Array(o*i*a*s),f=[n&&1<c?i-1:i,n&&1<l?a-1:a],p=[n&&1<c?c-1:c,n&&1<l?l-1:l],d=f[0]/p[0],v=f[1]/p[1],m=this.readSync(t.dataId),g=0,y=0;y<o;y++)for(var x=y*e.strides[0],b=0;b<c;b++)for(var w=b*d,C=Math.floor(w),E=Math.min(Math.ceil(w),i-1),_=x+C*e.strides[1],I=x+E*e.strides[1],R=w-C,k=1-R,S=0;S<l;S++)for(var D=S*v,A=Math.floor(D),T=Math.min(Math.ceil(D),a-1),N=D-A,F=1-N,M=_+A*e.strides[2],O=_+T*e.strides[2],P=I+A*e.strides[2],B=I+T*e.strides[2],L=k*F,W=k*N,z=R*F,U=R*N,V=0;V<s;V++){var G=m[g++];h[M+V]+=G*L,h[O+V]+=G*W,h[P+V]+=G*z,h[B+V]+=G*U}return Tn(h,[o,a,i,s],e.dtype)},Ih.prototype.resizeNearestNeighbor=function(t,e,n,r){wh(t,"resizeNearestNeighbor");for(var o=t.shape,i=o[0],a=o[1],s=o[2],u=o[3],c=this.readSync(t.dataId),l=new Float32Array(i*e*n*u),h=[r&&1<e?a-1:a,r&&1<n?s-1:s],f=[r&&1<e?e-1:e,r&&1<n?n-1:n],p=h[0]/f[0],d=h[1]/f[1],v=0,m=0;m<i;m++)for(var g=m*t.strides[0],y=0;y<e;y++)for(var x=p*y,b=g+Math.min(a-1,r?Math.round(x):Math.floor(x))*t.strides[1],w=0;w<n;w++)for(var C=d*w,E=b+Math.min(s-1,r?Math.round(C):Math.floor(C))*t.strides[2],_=0;_<u;_++){var I=c[E+_];l[v++]=I}return In(l,[i,e,n,u],t.dtype)},Ih.prototype.resizeNearestNeighborBackprop=function(t,e,n){wh([t,e],"resizeNearestNeighborBackprop");for(var r=e.shape,o=r[0],i=r[1],a=r[2],s=r[3],u=t.shape,c=u[1],l=u[2],h=new Float32Array(o*i*a*s),f=this.readSync(t.dataId),p=[n&&1<c?i-1:i,n&&1<l?a-1:a],d=[n&&1<c?c-1:c,n&&1<l?l-1:l],v=p[0]/d[0],m=p[1]/d[1],g=1/v,y=1/m,x=2*Math.ceil(g)+2,b=2*Math.ceil(y)+2,w=0;w<o;w++)for(var C=w*e.strides[0],E=0;E<i;E++)for(var _=C+E*e.strides[1],I=Math.floor(E*g),R=Math.floor(I-x/2),k=0;k<a;k++)for(var S=_+k*e.strides[2],D=Math.floor(k*y),A=Math.floor(D-b/2),T=0;T<s;T++){for(var N=0,F=0;F<x;F++){var M=F+R;if(!(M<0||c<=M)){var O=C+M*t.strides[1],P=M*v;if(E===Math.min(i-1,n?Math.round(P):Math.floor(P)))for(var B=0;B<b;B++){var L=B+A;if(!(L<0||l<=L)){var W=O+L*t.strides[2],z=L*m;k===Math.min(a-1,n?Math.round(z):Math.floor(z))&&(N+=f[W+T])}}}}h[S+T]=N}return Tn(h,e.shape,e.dtype)},Ih.prototype.batchNormalization=function(t,e,n,r,o,i){wh([t,e,n,o,i],"batchNorm");for(var a=this.readSync(t.dataId),s=this.readSync(e.dataId),u=this.readSync(n.dataId),c=o?this.readSync(o.dataId):new Float32Array([1]),l=i?this.readSync(i.dataId):new Float32Array([0]),h=new Float32Array(a.length),f=l.length,p=c.length,d=u.length,v=s.length,m=0,g=0,y=0,x=0,b=0;b<a.length;++b)h[b]=l[m++]+(a[b]-s[g++])*c[y++]/Math.sqrt(u[x++]+r),f<=m&&(m=0),v<=g&&(g=0),p<=y&&(y=0),d<=x&&(x=0);return Tn(h,t.shape)},Ih.prototype.localResponseNormalization4D=function(t,a,e,n,r){wh(t,"localResponseNormalization4D");var s=t.shape[3],u=s-1,c=this.readSync(t.dataId),o=t.size,i=new Float32Array(o);function l(t){for(var e=t%s,n=t-e+Math.max(0,e-a),r=t-e+Math.min(e+a,u),o=0;n<=r;n++){var i=c[n];o+=i*i}return o}for(var h=0;h<o;h++){var f=l(h),p=c[h]*Math.pow(e+n*f,-r);i[h]=p}return Tn(i,t.shape)},Ih.prototype.LRNGrad=function(t,e,n,r,o,i,a){wh(t,"LRNGrad");for(var s=t.shape[3],u=this.readSync(t.dataId),c=this.readSync(e.dataId),l=this.readSync(n.dataId),h=new Float32Array(t.size),f=t.size,p=0;p<f;p++){for(var d=p%s,v=p-d+Math.max(0,d-r),m=p-d+Math.min(s,d+r+1),g=0,y=v;y<m;y++)g+=Math.pow(c[y],2);for(g=i*g+o,y=v;y<m;y++){var x=-2*i*a*c[y]*l[p]/g;p===y&&(x+=Math.pow(g,-a)),x*=u[p],h[y]+=x}}return Tn(h,t.shape)},Ih.prototype.multinomial=function(t,e,n,r){wh(t,"multinomial");for(var o=e?t:so(t),i=o.shape[0],a=o.shape[1],s=Pn([i,n],"int32"),u=this.readSync(s.dataId),c=this.readSync(o.dataId),l=0;l<i;++l){var h=l*a,f=new Float32Array(a-1);f[0]=c[h];for(var p=1;p<f.length;++p)f[p]=f[p-1]+c[h+p];for(var d=nr(r.toString()),v=l*n,m=0;m<n;++m){var g=d();u[v+m]=f.length;for(var y=0;y<f.length;y++)if(g<f[y]){u[v+m]=y;break}}}return s},Ih.prototype.oneHot=function(t,e,n,r){wh(t,"oneHot");var o=new Float32Array(t.size*e);o.fill(r);for(var i=this.readSync(t.dataId),a=0;a<t.size;++a)0<=i[a]&&i[a]<e&&(o[a*e+i[a]]=n);return Dn(o,[t.size,e],"int32")},Ih.prototype.nonMaxSuppression=function(t,e,n,r,o){return wh(t,"nonMaxSuppression"),Bo(this.readSync(t.dataId),this.readSync(e.dataId),n,r,o)},Ih.prototype.fft=function(t){return this.fftBatch(t,!1)},Ih.prototype.ifft=function(t){return this.fftBatch(t,!0)},Ih.prototype.fftBatch=function(t,e){for(var n=t.shape[0],r=t.shape[1],o=cr(t.shape,"float32"),i=cr(t.shape,"float32"),a=En(t).as2D(n,r),s=_n(t).as2D(n,r),u=0;u<n;u++)for(var c=a.slice([u,0],[1,r]),l=s.slice([u,0],[1,r]),h=Cn(c,l),f=this.readSync(this.fftImpl(h,e).dataId),p=0;p<r;p++){var d=Oo(f,p);o.values[u*r+p]=d.real,i.values[u*r+p]=d.imag}return Cn(o.toTensor(),i.toTensor()).as2D(n,r)},Ih.prototype.fftImpl=function(t,e){var n=t.as1D(),r=n.size;if(this.isExponentOf2(r)){var o=this.fftRadix2(n,r,e).as2D(t.shape[0],t.shape[1]);return e&&(o=Cn(En(o).div(kn(r)),_n(o).div(kn(r)))),o}var i=this.readSync(t.dataId),a=function(t){for(var e=new Float32Array(t.length/2),n=new Float32Array(t.length/2),r=0;r<t.length;r+=2)e[r/2]=t[r],n[r/2]=t[r+1];return{real:e,imag:n}}(this.fourierTransformByMatmul(i,r,e));return Cn(a.real,a.imag).as2D(t.shape[0],t.shape[1])},Ih.prototype.isExponentOf2=function(t){return 0==(t&t-1)},Ih.prototype.fftRadix2=function(t,e,n){if(1===e)return t;var r=this.readSync(t.dataId),o=e/2,i=function(t){for(var e=Math.ceil(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=0;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return{real:n,imag:r}}(r),a=Cn(i.real,i.imag).as1D(),s=function(t){for(var e=Math.floor(t.length/4),n=new Float32Array(e),r=new Float32Array(e),o=2;o<t.length;o+=4)n[Math.floor(o/4)]=t[o],r[Math.floor(o/4)]=t[o+1];return{real:n,imag:r}}(r),u=Cn(s.real,s.imag).as1D();a=this.fftRadix2(a,o,n),u=this.fftRadix2(u,o,n);var c=function(t,e){for(var n=new Float32Array(t/2),r=new Float32Array(t/2),o=0;o<Math.ceil(t/2);o++){var i=(e?2:-2)*Math.PI*(o/t);n[o]=Math.cos(i),r[o]=Math.sin(i)}return{real:n,imag:r}}(e,n),l=Cn(c.real,c.imag).mul(u),h=a.add(l),f=a.sub(l),p=En(h).concat(En(f)),d=_n(h).concat(_n(f));return Cn(p,d).as1D()},Ih.prototype.fourierTransformByMatmul=function(t,e,n){for(var r=new Float32Array(2*e),o=0;o<e;o++){for(var i=0,a=0,s=0;s<e;s++){var u=(d=o*s,v=e,m=(n?2:-2)*Math.PI*(d/v),{real:Math.cos(m),imag:Math.sin(m)}),c=Oo(t,s);i+=c.real*u.real-c.imag*u.imag,a+=c.real*u.imag+c.imag*u.real}n&&(i/=e,a/=e),h=i,f=a,(l=r)[2*(p=o)]=h,l[2*p+1]=f}var l,h,f,p,d,v,m;return r},Ih.prototype.depthToSpace=function(t,e,n){P("NHWC"===n,function(){return"Only NHWC dataFormat supported on CPU for depthToSpace. Got "+n}),P(1<e,function(){return"blockSize should be > 1 for depthToSpace, but was: "+e});for(var r=t.shape[0],o=t.shape[1],i=t.shape[2],a=t.shape[3],s=o*e,u=i*e,c=a/(e*e),l=this.readSync(t.dataId),h=new Float32Array(r*s*u*c),f=0,p=0;p<r;++p)for(var d=0;d<s;++d)for(var v=Math.floor(d/e),m=d%e,g=0;g<u;++g)for(var y=Math.floor(g/e),x=(m*e+g%e)*c,b=0;b<c;++b){var w=b+x+a*(y+i*(v+o*p));h[f++]=l[w]}return Tn(h,[r,s,u,c])},Ih.prototype.broadcastedBinaryOp=function(a,s,t,u){var e=go(a.shape,s.shape),c=cr(e,t),l=this.readSync(a.dataId),h=this.readSync(s.dataId),f=vo(a.shape,e),p=vo(s.shape,e),d=c.values;if(f.length+p.length===0)for(var n=0;n<d.length;++n)d[n]=u(l[n%l.length],h[n%h.length]);else{var v=this.bufferSync(a),m=this.bufferSync(s),r=function(t){var e=c.indexToLoc(t),n=e.slice(-a.rank);f.forEach(function(t){return n[t]=0});var r=v.locToIndex(n),o=e.slice(-s.rank);p.forEach(function(t){return o[t]=0});var i=m.locToIndex(o);d[t]=u(l[r],h[i])};for(n=0;n<d.length;++n)r(n)}return c.toTensor()},Ih.prototype.broadcastedBinaryComplexOp=function(s,u,c){var t=go(s.shape,u.shape),l=cr(t,"float32"),e=cr(t,"float32"),h=this.readSync(s.dataId),f=this.readSync(u.dataId),p=vo(s.shape,t),d=vo(u.shape,t),v=l.values,m=e.values;if(p.length+d.length===0)for(var n=0;n<v.length;n++){var r=n%h.length,o=n%f.length,i=c(h[2*r],h[2*r+1],f[2*o],f[2*o+1]);v[n]=i.real,m[n]=i.imag}else{var g=this.bufferSync(this.data.get(s.dataId).complexTensors.real),y=this.bufferSync(this.data.get(u.dataId).complexTensors.real),a=function(t){var e=l.indexToLoc(t),n=e.slice(-s.rank);p.forEach(function(t){return n[t]=0});var r=g.locToIndex(n),o=e.slice(-u.rank);d.forEach(function(t){return o[t]=0});var i=y.locToIndex(o),a=c(h[2*r],h[2*r+1],f[2*i],f[2*i+1]);v[t]=a.real,m[t]=a.imag};for(n=0;n<v.length;n++)a(n)}return this.complex(l.toTensor(),e.toTensor())},Ih.prototype.split=function(t,e,n){return Vo(t,e,n)},Ih.prototype.dispose=function(){},Ih.prototype.floatPrecision=function(){return 32},Ih.prototype.epsilon=function(){return 1e-7},Ih.prototype.cropAndResize=function(t,e,n,r,o,i){for(var a=t.shape,s=a[0],u=a[1],c=a[2],l=a[3],h=e.shape[0],f=r[0],p=r[1],d=cr([h,f,p,l],"float32"),v=this.readSync(e.dataId),m=this.readSync(n.dataId),g=this.readSync(t.dataId),y=t.strides,x=d.strides,b=0;b<h;b++){var w=4*b,C=v[w],E=v[1+w],_=v[2+w],I=v[3+w],R=m[b];if(!(s<=R))for(var k=1<f?(_-C)*(u-1)/(f-1):0,S=1<p?(I-E)*(c-1)/(p-1):0,D=0;D<f;D++){var A=1<f?C*(u-1)+D*k:.5*(C+_)*(u-1);if(A<0||u-1<A)for(var T=0;T<p;T++)for(var N=0;N<l;N++){var F=N+T*x[2]+D*x[1]+b*x[0];d.values[F]=i}else if("bilinear"===o){var M=Math.floor(A),O=Math.ceil(A),P=A-M;for(T=0;T<p;T++)if((q=1<p?E*(c-1)+T*S:.5*(E+I)*(c-1))<0||c-1<q)for(N=0;N<l;N++)F=N+T*x[2]+D*x[1]+b*x[0],d.values[F]=i;else{var B=Math.floor(q),L=Math.ceil(q),W=q-B;for(N=0;N<l;N++){var z=g[F=N+B*y[2]+M*y[1]+R*y[0]],U=g[F=N+L*y[2]+M*y[1]+R*y[0]],V=g[F=N+B*y[2]+O*y[1]+R*y[0]],G=z+(U-z)*W,H=V+(g[F=N+L*y[2]+O*y[1]+R*y[0]]-V)*W;F=N+T*x[2]+D*x[1]+b*x[0],d.values[F]=G+(H-G)*P}}}else for(T=0;T<p;++T){var q;if((q=1<p?E*(c-1)+T*S:.5*(E+I)*(c-1))<0||c-1<q)for(N=0;N<l;N++)F=N+T*x[2]+D*x[1]+b*x[0],d.values[F]=i;else{var j=Math.round(q),K=Math.round(A);for(N=0;N<l;N++){var X=N+j*y[2]+K*y[1]+R*y[0],Y=N+T*x[2]+D*x[1]+b*x[0];d.values[Y]=g[X]}}}}}return d.toTensor()},Ih.prototype.sparseToDense=function(t,e,n,r){var o=Xr(0,t,n),i=o.sliceRank,a=o.numUpdates,s=o.sliceSize,u=o.strides,c=o.outputSize;return this.scatter(t,e,n,c,s,a,i,u,r,!1)},Ih.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],o=Gr(t,e),i=o[0],a=o[1],s=o[2],u=o[3];if(0===a)return In([],i,t.dtype);for(var c=new vt([a,s],t.dtype),l=this.readSync(e.dataId),h=this.readSync(t.dataId),f=0;f<a;f++){for(var p=[],d=0,v=0;v<r;v++){var m=l[f*r+v];d+=m*u[v],p.push(m)}if(d<0||d>=t.size/s)throw new Error("Invalid indices: "+p+" does not index into "+t.shape);for(var g=0;g<s;g++)c.values[f*s+g]=h[d*s+g]}return c.toTensor().reshape(i)},Ih.prototype.scatterND=function(t,e,n){var r=Xr(0,t,n),o=r.sliceRank,i=r.numUpdates,a=r.sliceSize,s=r.strides,u=r.outputSize,c=kn(0);return this.scatter(t,e,n,u,a,i,o,s,c,!0)},Ih.prototype.fill=function(t,e,n){var r=F(n=n||j(e),L(t));return r.fill(e),Kt.makeTensor(r,t,n,this)},Ih.prototype.onesLike=function(t){if("string"===t.dtype)throw new Error("onesLike is not supported for string tensors");return this.fill(t.shape,1,t.dtype)},Ih.prototype.zerosLike=function(t){var e=F(t.dtype,L(t.shape));return this.makeOutput(e,t.shape,t.dtype)},Ih.prototype.linspace=function(t,e,n){return No(t,e,n)},Ih.prototype.scatter=function(t,e,n,r,o,i,a,s,u,c){var l=[r/o,o],h=this.readSync(t.dataId),f=this.readSync(e.dataId);if(0===r)return In([],n,e.dtype);var p=new vt(l,e.dtype);p.values.fill(this.readSync(u.dataId)[0]);for(var d=0;d<i;d++){for(var v=[],m=0,g=0;g<a;g++){var y=h[d*a+g];v.push(y),m+=y*s[g]}if(m<0||r/o<=m)throw new Error("Invalid indices: "+v+" does not index into "+n);for(var x=0;x<o;x++)c?p.values[m*o+x]+=f[d*o+x]:p.values[m*o+x]=0===e.rank?f[0]:f[d*o+x]}return p.toTensor().reshape(n)},Ih);function Ih(){var t=Eh.call(this)||this;return t.blockSize=48,t.firstUse=!0,t.data=new co(t,Kt),t}Kt.registerBackend("cpu",function(){return new _h},1);for(var Rh=0,kh=[{kernelName:"NonMaxSuppressionV5",backendName:"cpu",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=t.attrs,o=e,i=o.boxes,a=o.scores,s=r,u=s.maxOutputSize,c=s.iouThreshold,l=s.scoreThreshold,h=s.softNmsSigma,f=n;wh(i,"NonMaxSuppressionWithScore");var p=Lo(f.data.get(i.dataId).values,f.data.get(a.dataId).values,u,c,l,h);return[p.selectedIndices,p.selectedScores]}},{kernelName:"Square",backendName:"cpu",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e.x,o=n;wh(r,"square");for(var i=o.data.get(r.dataId).values,a=new Float32Array(i.length),s=0;s<i.length;++s){var u=i[s];a[s]=u*u}return{dataId:o.write(a,r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},{kernelName:Fs,backendName:"cpu",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=e,o=r.a,i=r.b,a=n;wh([o,i],Fs);var s=a.data.get(o.dataId).values,u=a.data.get(i.dataId).values,c=function(t,e,a,s,n,u){var r=go(t,e),c=r.length,l=Y(r),h=N(n,L(r)),f=t.length,p=e.length,d=Y(t),v=Y(e),m=vo(t,r),g=vo(e,r);if(m.length+g.length===0)for(var o=0;o<h.length;++o)h[o]=u(a[o%a.length],s[o%s.length]);else{var i=function(t){var e=it(t,c,l),n=e.slice(-f);m.forEach(function(t){return n[t]=0});var r=ot(n,f,d),o=e.slice(-p);g.forEach(function(t){return o[t]=0});var i=ot(o,p,v);h[t]=u(a[r],s[i])};for(o=0;o<h.length;++o)i(o)}return[h,r]}(o.shape,i.shape,s,u,o.dtype,function(t,e){var n=t-e;return n*n}),l=c[0],h=c[1];return{dataId:a.write(l,h,o.dtype),shape:h,dtype:o.dtype}}}];Rh<kh.length;Rh++)s(kh[Rh]);for(var Sh,Dh=function(t){this.variableNames=["A"];var e=Jo(),n=t[0],r=t[1];this.outputShape=t,this.userCode="\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+r+".0, "+n+".0);\n\n        vec4 values = "+e.texture2D+"(A, uv);\n        float value;\n        if (depth == 0) {\n          value = values.r;\n        } else if (depth == 1) {\n          value = values.g;\n        } else if (depth == 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    "},Ah=function(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;var e=Jo(),n=t[0],r=t[1];this.outputShape=t,this.userCode="\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n\n        vec4 result = vec4(0.);\n\n        for(int row=0; row<=1; row++) {\n          for(int col=0; col<=1; col++) {\n            texC = coords[1] + row;\n            depth = coords[2] + col;\n\n            vec2 uv = (vec2(texC, texR) + halfCR) /\n                       vec2("+r+".0, "+n+".0);\n            vec4 values = "+e.texture2D+"(A, uv);\n            float value;\n            if (depth == 0) {\n              value = values.r;\n            } else if (depth == 1) {\n              value = values.g;\n            } else if (depth == 2) {\n              value = values.b;\n            } else if (depth == 3) {\n              value = values.a;\n            }\n\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\n          }\n        }\n\n        "+e.output+" = result;\n      }\n    "},Th=0,Nh=[{kernelName:"FromPixels",backendName:"webgl",kernelFunc:function(t){var e=t.inputs,n=t.backend,r=t.attrs,o=e.pixels,i=r.numChannels,a="undefined"!=typeof HTMLVideoElement&&o instanceof HTMLVideoElement,s="undefined"!=typeof HTMLImageElement&&o instanceof 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i=Rp.call(this)||this;if(i.learningRate=t,i.decay=e,i.momentum=n,i.epsilon=r,i.accumulatedMeanSquares=[],i.accumulatedMoments=[],i.accumulatedMeanGrads=[],i.centered=o,null==r&&(i.epsilon=Kt.backend.epsilon()),null==t)throw new Error("learningRate for RMSPropOptimizer must be defined.");return i}Qf(kp);var Dp=(Np.sgd=function(t){return new wp(t)},Np.momentum=function(t,e,n){return void 0===n&&(n=!1),new _p(t,e,n)},Np.rmsprop=function(t,e,n,r,o){return void 0===e&&(e=.9),void 0===n&&(n=0),void 0===r&&(r=null),void 0===o&&(o=!1),new kp(t,e,n,r,o)},Np.adam=function(t,e,n,r){return void 0===t&&(t=.001),void 0===e&&(e=.9),void 0===n&&(n=.999),void 0===r&&(r=null),new vp(t,e,n,r)},Np.adadelta=function(t,e,n){return void 0===t&&(t=.001),void 0===e&&(e=.95),void 0===n&&(n=null),new cp(t,e,n)},Np.adamax=function(t,e,n,r,o){return void 0===t&&(t=.002),void 0===e&&(e=.9),void 0===n&&(n=.999),void 0===r&&(r=null),void 0===o&&(o=0),new yp(t,e,n,r,o)},Np.adagrad=function(t,e){return void 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i?t:dv(t),f=Math.abs(u-c)/2,p=n&&u<c?f:0,d=n&&c<u?f:0;return nv(l).drawImage(h,p,d,u,c),l}var yv=(Object.defineProperty(xv.prototype,"imageTensors",{get:function(){return this._imageTensors},enumerable:!0,configurable:!0}),Object.defineProperty(xv.prototype,"canvases",{get:function(){return this._canvases},enumerable:!0,configurable:!0}),Object.defineProperty(xv.prototype,"isBatchInput",{get:function(){return 1<this.batchSize||this._treatAsBatchInput},enumerable:!0,configurable:!0}),Object.defineProperty(xv.prototype,"batchSize",{get:function(){return this._batchSize},enumerable:!0,configurable:!0}),Object.defineProperty(xv.prototype,"inputDimensions",{get:function(){return this._inputDimensions},enumerable:!0,configurable:!0}),Object.defineProperty(xv.prototype,"inputSize",{get:function(){return this._inputSize},enumerable:!0,configurable:!0}),Object.defineProperty(xv.prototype,"reshapedInputDimensions",{get:function(){var n=this;return Zp(this.batchSize,0,1).map(function(t,e){return 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tv.getEnv().Canvas)return Kf.fromPixels(gv(e,r,o));throw new Error("toBatchTensor - at batchIdx "+t+", expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have "+e)});return Mr(t.map(function(t){return t.toFloat()})).as4D(i.batchSize,r,r,3)})},xv);function xv(t,e){var o=this;if(void 0===e&&(e=!1),this._imageTensors=[],this._canvases=[],this._treatAsBatchInput=!1,this._inputDimensions=[],!Array.isArray(t))throw new Error("NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have "+t);this._treatAsBatchInput=e,this._batchSize=t.length,t.forEach(function(t,e){if(qp(t))return o._imageTensors[e]=t,void(o._inputDimensions[e]=t.shape);if(jp(t)){var n=t.shape[0];if(1!==n)throw new Error("NetInput - tf.Tensor4D with batchSize "+n+" passed, but not supported in input array");return o._imageTensors[e]=t,void(o._inputDimensions[e]=t.shape.slice(1))}var r=t instanceof tv.getEnv().Canvas?t:dv(t);o._canvases[e]=r,o._inputDimensions[e]=[r.height,r.width,3]})}function bv(n){return Lp(this,void 0,void 0,function(){var r,o,e;return Wp(this,function(t){switch(t.label){case 0:if(n instanceof yv)return[2,n];if(!(r=Array.isArray(n)?n:[n]).length)throw new Error("toNetInput - empty array passed as input");return o=function(t){return Array.isArray(n)?" at input index "+t+":":""},(e=r.map(ev)).forEach(function(t,e){if(!mv(t)&&!qp(t)&&!jp(t)){if("string"==typeof r[e])throw new Error("toNetInput -"+o(e)+" string passed, but could not resolve HTMLElement for element id "+r[e]);throw new Error("toNetInput -"+o(e)+" expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id")}if(jp(t)){var n=t.shape[0];if(1!==n)throw new Error("toNetInput -"+o(e)+" tf.Tensor4D with batchSize "+n+" passed, but not supported in input array")}}),[4,Promise.all(e.map(function(t){return mv(t)&&lv(t)}))];case 1:return t.sent(),[2,new yv(e,Array.isArray(n))]}})})}function wv(s,u){return Lp(this,void 0,void 0,function(){var e,n,r,o,i,a;return Wp(this,function(t){switch(t.label){case 0:return e=tv.getEnv().Canvas,(n=s)instanceof e?[3,5]:[4,bv(s)];case 1:if(1<(r=t.sent()).batchSize)throw new Error("extractFaces - batchSize > 1 not supported");return(o=r.getInput(0))instanceof e?(i=o,[3,4]):[3,2];case 2:return[4,vv(o)];case 3:i=t.sent(),t.label=4;case 4:n=i,t.label=5;case 5:return a=nv(n),[2,u.map(function(t){return t instanceof pd?t.forSize(n.width,n.height).box.floor():t}).map(function(t){return t.clipAtImageBorders(n.width,n.height)}).map(function(t){var e=t.x,n=t.y,r=t.width,o=t.height,i=pv({width:r,height:o});return nv(i).putImageData(a.getImageData(e,n,r,o),0,0),i})]}})})}function Cv(u,e){return Lp(this,void 0,void 0,function(){return Wp(this,function(t){if(!qp(u)&&!jp(u))throw new Error("extractFaceTensors - expected image tensor to be 3D or 4D");if(jp(u)&&1<u.shape[0])throw new Error("extractFaceTensors - batchSize > 1 not supported");return[2,nn(function(){var t=u.shape.slice(jp(u)?1:0),i=t[0],a=t[1],s=t[2];return e.map(function(t){return t instanceof pd?t.forSize(a,i).box:t}).map(function(t){return t.clipAtImageBorders(a,i)}).map(function(t){var e=t.x,n=t.y,r=t.width,o=t.height;return Jc(u.as3D(i,a,s),[n,e,0],[o,r,s])})})]})})}function Ev(n,r){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return[4,(0,tv.getEnv().fetch)(n,r)];case 1:if(!((e=t.sent()).status<400))throw new Error("failed to fetch: ("+e.status+") "+e.statusText+", from url: "+e.url);return[2,e]}})})}function _v(e){return Lp(this,void 0,void 0,function(){return Wp(this,function(t){switch(t.label){case 0:return[4,Ev(e)];case 1:return[2,t.sent().json()]}})})}function Iv(t,e){var n=e+"-weights_manifest.json";if(!t)return{modelBaseUri:"",manifestUri:n};if("/"===t)return{modelBaseUri:"/",manifestUri:"/"+n};var r=t.startsWith("http://")?"http://":t.startsWith("https://")?"https://":"",o=(t=t.replace(r,"")).split("/").filter(function(t){return t}),i=t.endsWith(".json")?o[o.length-1]:n,a=r+(t.endsWith(".json")?o.slice(0,o.length-1):o).join("/");return{modelBaseUri:a=t.startsWith("/")?"/"+a:a,manifestUri:"/"===a?"/"+i:a+"/"+i}}function Rv(i,a){return Lp(this,void 0,void 0,function(){var e,n,r,o;return Wp(this,function(t){switch(t.label){case 0:return e=Iv(i,a),n=e.manifestUri,r=e.modelBaseUri,[4,_v(n)];case 1:return o=t.sent(),[2,Gf.loadWeights(o,r)]}})})}var kv=(Object.defineProperty(Sv.prototype,"params",{get:function(){return this._params},enumerable:!0,configurable:!0}),Object.defineProperty(Sv.prototype,"paramMappings",{get:function(){return this._paramMappings},enumerable:!0,configurable:!0}),Object.defineProperty(Sv.prototype,"isLoaded",{get:function(){return!!this.params},enumerable:!0,configurable:!0}),Sv.prototype.getParamFromPath=function(t){var e=this.traversePropertyPath(t);return e.obj[e.objProp]},Sv.prototype.reassignParamFromPath=function(t,e){var n=this.traversePropertyPath(t),r=n.obj,o=n.objProp;r[o].dispose(),r[o]=e},Sv.prototype.getParamList=function(){var n=this;return this._paramMappings.map(function(t){var e=t.paramPath;return{path:e,tensor:n.getParamFromPath(e)}})},Sv.prototype.getTrainableParams=function(){return this.getParamList().filter(function(t){return t.tensor instanceof Ft})},Sv.prototype.getFrozenParams=function(){return this.getParamList().filter(function(t){return!(t.tensor instanceof Ft)})},Sv.prototype.variable=function(){var r=this;this.getFrozenParams().forEach(function(t){var e=t.path,n=t.tensor;r.reassignParamFromPath(e,n.variable())})},Sv.prototype.freeze=function(){var o=this;this.getTrainableParams().forEach(function(t){var e=t.path,n=t.tensor,r=In(n.dataSync());n.dispose(),o.reassignParamFromPath(e,r)})},Sv.prototype.dispose=function(e){void 0===e&&(e=!0),this.getParamList().forEach(function(t){if(e&&t.tensor.isDisposed)throw new Error("param tensor has already been disposed for path "+t.path);t.tensor.dispose()}),this._params=void 0},Sv.prototype.serializeParams=function(){return new Float32Array(this.getParamList().map(function(t){var e=t.tensor;return Array.from(e.dataSync())}).reduce(function(t,e){return t.concat(e)}))},Sv.prototype.load=function(e){return Lp(this,void 0,void 0,function(){return Wp(this,function(t){switch(t.label){case 0:return e instanceof Float32Array?(this.extractWeights(e),[2]):[4,this.loadFromUri(e)];case 1:return t.sent(),[2]}})})},Sv.prototype.loadFromUri=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:if(n&&"string"!=typeof n)throw new Error(this._name+".loadFromUri - expected model uri");return[4,Rv(n,this.getDefaultModelName())];case 1:return e=t.sent(),this.loadFromWeightMap(e),[2]}})})},Sv.prototype.loadFromDisk=function(h){return Lp(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l;return Wp(this,function(t){switch(t.label){case 0:if(h&&"string"!=typeof h)throw new Error(this._name+".loadFromDisk - expected model file path");return e=tv.getEnv().readFile,n=Iv(h,this.getDefaultModelName()),r=n.manifestUri,o=n.modelBaseUri,i=function(t){return Promise.all(t.map(function(t){return e(t).then(function(t){return t.buffer})}))},a=Gf.weightsLoaderFactory(i),c=(u=JSON).parse,[4,e(r)];case 1:return s=c.apply(u,[t.sent().toString()]),[4,a(s,o)];case 2:return l=t.sent(),this.loadFromWeightMap(l),[2]}})})},Sv.prototype.loadFromWeightMap=function(t){var e=this.extractParamsFromWeigthMap(t),n=e.paramMappings,r=e.params;this._paramMappings=n,this._params=r},Sv.prototype.extractWeights=function(t){var e=this.extractParams(t),n=e.paramMappings,r=e.params;this._paramMappings=n,this._params=r},Sv.prototype.traversePropertyPath=function(n){if(!this.params)throw new Error("traversePropertyPath - model has no loaded params");var t=n.split("/").reduce(function(t,e){if(!t.nextObj.hasOwnProperty(e))throw new Error("traversePropertyPath - object does not have property "+e+", for path "+n);return{obj:t.nextObj,objProp:e,nextObj:t.nextObj[e]}},{nextObj:this.params}),e=t.obj,r=t.objProp;if(!(e&&r&&e[r]instanceof bt))throw new Error("traversePropertyPath - parameter is not a tensor, for path "+n);return{obj:e,objProp:r}},Sv);function Sv(t){this._name=t,this._params=void 0,this._paramMappings=[]}function Dv(e,n,r){return nn(function(){var t=Ac(e,n.depthwise_filter,n.pointwise_filter,r,"same");return t=Ou(t,n.bias)})}function Av(r,o,i){return void 0===i&&(i=!1),nn(function(){var t=dl(i?Ou(Ec(r,o.conv0.filters,[2,2],"same"),o.conv0.bias):Dv(r,o.conv0,[2,2])),e=Dv(t,o.conv1,[1,1]),n=Dv(dl(Ou(t,e)),o.conv2,[1,1]);return dl(Ou(t,Ou(e,n)))})}function Tv(o,i,a,s){return void 0===a&&(a=!1),void 0===s&&(s=!0),nn(function(){var t=dl(a?Ou(Ec(o,i.conv0.filters,s?[2,2]:[1,1],"same"),i.conv0.bias):Dv(o,i.conv0,s?[2,2]:[1,1])),e=Dv(t,i.conv1,[1,1]),n=Dv(dl(Ou(t,e)),i.conv2,[1,1]),r=Dv(dl(Ou(t,Ou(e,n))),i.conv3,[1,1]);return dl(Ou(t,Ou(e,Ou(n,r))))})}function Nv(e,n,r,o){return void 0===r&&(r="same"),void 0===o&&(o=!1),nn(function(){var t=Ou(Ec(e,n.filters,[1,1],r),n.bias);return o?dl(t):t})}function Fv(t,n){Object.keys(t).forEach(function(e){n.some(function(t){return t.originalPath===e})||t[e].dispose()})}function Mv(a,s){return function(t,e,n,r){var o=Tn(a(t*e*n*n),[n,n,t,e]),i=Sn(a(e));return s.push({paramPath:r+"/filters"},{paramPath:r+"/bias"}),{filters:o,bias:i}}}function Ov(i,a){return function(t,e,n){var r=Dn(i(t*e),[t,e]),o=Sn(i(e));return a.push({paramPath:n+"/weights"},{paramPath:n+"/bias"}),{weights:r,bias:o}}}var Pv=function(t,e,n){this.depthwise_filter=t,this.pointwise_filter=e,this.bias=n};function Bv(a,s){return function(t,e,n){var r=Tn(a(9*t),[3,3,t,1]),o=Tn(a(t*e),[1,1,t,e]),i=Sn(a(e));return s.push({paramPath:n+"/depthwise_filter"},{paramPath:n+"/pointwise_filter"},{paramPath:n+"/bias"}),new Pv(r,o,i)}}function Lv(o){return function(t){var e=o(t+"/depthwise_filter",4),n=o(t+"/pointwise_filter",4),r=o(t+"/bias",1);return new Pv(e,n,r)}}function Wv(o,i){return function(t,e,n){var r=o[t];if(!Gp(r,e))throw new Error("expected weightMap["+t+"] to be a Tensor"+e+"D, instead have "+r);return i.push({originalPath:t,paramPath:n||t}),r}}function zv(t){var n=t;return{extractWeights:function(t){var e=n.slice(0,t);return n=n.slice(t),e},getRemainingWeights:function(){return n}}}function Uv(t,e){var o=Mv(t,e),i=Bv(t,e);function a(t,e,n,r){return void 0===r&&(r=!1),{conv0:r?o(t,e,3,n+"/conv0"):i(t,e,n+"/conv0"),conv1:i(e,e,n+"/conv1"),conv2:i(e,e,n+"/conv2")}}return{extractDenseBlock3Params:a,extractDenseBlock4Params:function(t,e,n,r){void 0===r&&(r=!1);var o=a(t,e,n,r);return{conv0:o.conv0,conv1:o.conv1,conv2:o.conv2,conv3:i(e,e,n+"/conv3")}}}}function Vv(e){return function(t){return{filters:e(t+"/filters",4),bias:e(t+"/bias",1)}}}function Gv(t,e){var n=Wv(t,e),r=Vv(n),o=Lv(n);return{extractDenseBlock3Params:function(t,e){return void 0===e&&(e=!1),{conv0:e?r(t+"/conv0"):o(t+"/conv0"),conv1:o(t+"/conv1"),conv2:o(t+"/conv2")}},extractDenseBlock4Params:function(t,e){return void 0===e&&(e=!1),{conv0:e?r(t+"/conv0"):o(t+"/conv0"),conv1:o(t+"/conv1"),conv2:o(t+"/conv2"),conv3:o(t+"/conv3")}}}}var Hv,qv=(Pp(jv,Hv=kv),jv.prototype.forwardInput=function(e){var n=this.params;if(!n)throw new Error("FaceFeatureExtractor - load model before inference");return nn(function(){var t=Tv(yd(e.toBatchTensor(112,!0),[122.782,117.001,104.298]).div(kn(255)),n.dense0,!0);return t=Tv(t=Tv(t=Tv(t,n.dense1),n.dense2),n.dense3),t=Hc(t,[7,7],[2,2],"valid")})},jv.prototype.forward=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,bv(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},jv.prototype.getDefaultModelName=function(){return"face_feature_extractor_model"},jv.prototype.extractParamsFromWeigthMap=function(t){return function(t){var e=[],n=Gv(t,e).extractDenseBlock4Params,r={dense0:n("dense0",!0),dense1:n("dense1"),dense2:n("dense2"),dense3:n("dense3")};return Fv(t,e),{params:r,paramMappings:e}}(t)},jv.prototype.extractParams=function(t){return function(t){var e=[],n=zv(t),r=n.extractWeights,o=n.getRemainingWeights,i=Uv(r,e).extractDenseBlock4Params,a=i(3,32,"dense0",!0),s=i(32,64,"dense1"),u=i(64,128,"dense2"),c=i(128,256,"dense3");if(0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{paramMappings:e,params:{dense0:a,dense1:s,dense2:u,dense3:c}}}(t)},jv);function jv(){return Hv.call(this,"FaceFeatureExtractor")||this}function Kv(t,e){return nn(function(){return Ou(Fc(t,e.weights),e.bias)})}function Xv(e){var n={},r={};return Object.keys(e).forEach(function(t){(t.startsWith("fc")?r:n)[t]=e[t]}),{featureExtractorMap:n,classifierMap:r}}var Yv,$v=(Pp(Jv,Yv=kv),Object.defineProperty(Jv.prototype,"faceFeatureExtractor",{get:function(){return this._faceFeatureExtractor},enumerable:!0,configurable:!0}),Jv.prototype.runNet=function(e){var n=this,r=this.params;if(!r)throw new Error(this._name+" - load model before inference");return nn(function(){var t=e instanceof yv?n.faceFeatureExtractor.forwardInput(e):e;return Kv(t.as2D(t.shape[0],-1),r.fc)})},Jv.prototype.dispose=function(t){void 0===t&&(t=!0),this.faceFeatureExtractor.dispose(t),Yv.prototype.dispose.call(this,t)},Jv.prototype.loadClassifierParams=function(t){var e=this.extractClassifierParams(t),n=e.params,r=e.paramMappings;this._params=n,this._paramMappings=r},Jv.prototype.extractClassifierParams=function(t){return function(t,e,n){var r=[],o=zv(t),i=o.extractWeights,a=o.getRemainingWeights,s=Ov(i,r)(e,n,"fc");if(0!==a().length)throw new Error("weights remaing after extract: "+a().length);return{paramMappings:r,params:{fc:s}}}(t,this.getClassifierChannelsIn(),this.getClassifierChannelsOut())},Jv.prototype.extractParamsFromWeigthMap=function(t){var e=Xv(t),n=e.featureExtractorMap,r=e.classifierMap;return this.faceFeatureExtractor.loadFromWeightMap(n),function(t){var e,n=[],r=Wv(t,n),o={fc:(e="fc",{weights:r(e+"/weights",2),bias:r(e+"/bias",1)})};return Fv(t,n),{params:o,paramMappings:n}}(r)},Jv.prototype.extractParams=function(t){var e=this.getClassifierChannelsIn(),n=this.getClassifierChannelsOut(),r=n*e+n,o=t.slice(0,t.length-r),i=t.slice(t.length-r);return this.faceFeatureExtractor.extractWeights(o),this.extractClassifierParams(i)},Jv);function Jv(t,e){var n=Yv.call(this,t)||this;return n._faceFeatureExtractor=e,n}var Qv=["neutral","happy","sad","angry","fearful","disgusted","surprised"],Zv=(tm.prototype.asSortedArray=function(){var e=this;return Qv.map(function(t){return{expression:t,probability:e[t]}}).sort(function(t,e){return e.probability-t.probability})},tm);function tm(n){var r=this;if(7!==n.length)throw new Error("FaceExpressions.constructor - expected probabilities.length to be 7, have: "+n.length);Qv.forEach(function(t,e){r[t]=n[e]})}var em,nm=(Pp(rm,em=$v),rm.prototype.forwardInput=function(t){var e=this;return nn(function(){return so(e.runNet(t))})},rm.prototype.forward=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,bv(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},rm.prototype.predictExpressions=function(a){return Lp(this,void 0,void 0,function(){var e,n,r,o,i=this;return Wp(this,function(t){switch(t.label){case 0:return[4,bv(a)];case 1:return e=t.sent(),[4,this.forwardInput(e)];case 2:return n=t.sent(),[4,Promise.all(Br(n).map(function(n){return Lp(i,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return[4,n.data()];case 1:return e=t.sent(),n.dispose(),[2,e]}})})}))];case 3:return r=t.sent(),n.dispose(),o=r.map(function(t){return new Zv(t)}),[2,e.isBatchInput?o:o[0]]}})})},rm.prototype.getDefaultModelName=function(){return"face_expression_model"},rm.prototype.getClassifierChannelsIn=function(){return 256},rm.prototype.getClassifierChannelsOut=function(){return 7},rm);function rm(t){return void 0===t&&(t=new qv),em.call(this,"FaceExpressionNet",t)||this}function om(t){return t.expressions instanceof Zv}function im(t,e){var n={expressions:e};return Object.assign({},t,n)}function am(t){return Gd(t)&&t.landmarks instanceof _d&&t.unshiftedLandmarks instanceof _d&&t.alignedRect instanceof pd}function sm(t,e){var n=t.detection.box,r=e.shiftBy(n.x,n.y),o=r.align(),i=t.detection.imageDims,a={landmarks:r,unshiftedLandmarks:e,alignedRect:new pd(t.detection.score,o.rescale(i.reverse()),i)};return Object.assign({},t,a)}var um=function(t){void 0===t&&(t={});var e=t.drawLines,n=void 0===e||e,r=t.drawPoints,o=void 0===r||r,i=t.lineWidth,a=t.lineColor,s=t.pointSize,u=t.pointColor;this.drawLines=n,this.drawPoints=o,this.lineWidth=i||1,this.pointSize=s||2,this.lineColor=a||"rgba(0, 255, 255, 1)",this.pointColor=u||"rgba(255, 0, 255, 1)"},cm=(lm.prototype.draw=function(t){var e=nv(t),n=this.options,r=n.drawLines,o=n.drawPoints,i=n.lineWidth,a=n.lineColor,s=n.pointSize,u=n.pointColor;r&&this.faceLandmarks instanceof Ad&&(e.strokeStyle=a,e.lineWidth=i,Mp(e,this.faceLandmarks.getJawOutline()),Mp(e,this.faceLandmarks.getLeftEyeBrow()),Mp(e,this.faceLandmarks.getRightEyeBrow()),Mp(e,this.faceLandmarks.getNose()),Mp(e,this.faceLandmarks.getLeftEye(),!0),Mp(e,this.faceLandmarks.getRightEye(),!0),Mp(e,this.faceLandmarks.getMouth(),!0)),o&&(e.strokeStyle=u,e.fillStyle=u,this.faceLandmarks.positions.forEach(function(t){e.beginPath(),e.arc(t.x,t.y,s,0,2*Math.PI),e.fill()}))},lm);function lm(t,e){void 0===e&&(e={}),this.faceLandmarks=t,this.options=new um(e)}var hm=Object.freeze({__proto__:null,drawContour:Mp,drawDetections:function(o,t){(Array.isArray(t)?t:[t]).forEach(function(t){var e=t instanceof pd?t.score:Gd(t)?t.detection.score:void 0,n=t instanceof pd?t.box:Gd(t)?t.detection.box:new id(t),r=e?""+Yp(e):void 0;new sv(n,{label:r}).draw(o)})},drawFaceExpressions:function(o,t,i,a){void 0===i&&(i=.1),(Array.isArray(t)?t:[t]).forEach(function(t){var e=t instanceof Zv?t:om(t)?t.expressions:void 0;if(!e)throw new Error("drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof");var n=e.asSortedArray().filter(function(t){return t.probability>i}),r=Gd(t)?t.detection.box.bottomLeft:a||new rd(0,0);new ov(n.map(function(t){return t.expression+" ("+Yp(t.probability)+")"}),r).draw(o)})},DrawBoxOptions:av,DrawBox:sv,DrawFaceLandmarksOptions:um,DrawFaceLandmarks:cm,drawFaceLandmarks:function(n,t){(Array.isArray(t)?t:[t]).forEach(function(t){var e=t instanceof _d?t:am(t)?t.landmarks:void 0;if(!e)throw new Error("drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof");new cm(e).draw(n)})},get AnchorPosition(){return Qd},DrawTextFieldOptions:rv,DrawTextField:ov});function fm(t,e){var n=[],r=zv(t),o=r.extractWeights,i=r.getRemainingWeights,a=function(t,e){var r=Mv(t,e),o=Bv(t,e);return{extractConvParams:r,extractSeparableConvParams:o,extractReductionBlockParams:function(t,e,n){return{separable_conv0:o(t,e,n+"/separable_conv0"),separable_conv1:o(e,e,n+"/separable_conv1"),expansion_conv:r(t,e,1,n+"/expansion_conv")}},extractMainBlockParams:function(t,e){return{separable_conv0:o(t,t,e+"/separable_conv0"),separable_conv1:o(t,t,e+"/separable_conv1"),separable_conv2:o(t,t,e+"/separable_conv2")}}}}(o,n),s=a.extractConvParams,u=a.extractSeparableConvParams,c=a.extractReductionBlockParams,l=a.extractMainBlockParams,h={conv_in:s(3,32,3,"entry_flow/conv_in"),reduction_block_0:c(32,64,"entry_flow/reduction_block_0"),reduction_block_1:c(64,128,"entry_flow/reduction_block_1")},f={};Zp(e,0,1).forEach(function(t){f["main_block_"+t]=l(128,"middle_flow/main_block_"+t)});var p={reduction_block:c(128,256,"exit_flow/reduction_block"),separable_conv:u(256,512,"exit_flow/separable_conv")};if(0!==i().length)throw new Error("weights remaing after extract: "+i().length);return{paramMappings:n,params:{entry_flow:h,middle_flow:f,exit_flow:p}}}function pm(t,e){var n=[],r=function(t,e){var n=Wv(t,e),r=Vv(n),o=Lv(n);return{extractConvParams:r,extractSeparableConvParams:o,extractReductionBlockParams:function(t){return{separable_conv0:o(t+"/separable_conv0"),separable_conv1:o(t+"/separable_conv1"),expansion_conv:r(t+"/expansion_conv")}},extractMainBlockParams:function(t){return{separable_conv0:o(t+"/separable_conv0"),separable_conv1:o(t+"/separable_conv1"),separable_conv2:o(t+"/separable_conv2")}}}}(t,n),o=r.extractConvParams,i=r.extractSeparableConvParams,a=r.extractReductionBlockParams,s=r.extractMainBlockParams,u={conv_in:o("entry_flow/conv_in"),reduction_block_0:a("entry_flow/reduction_block_0"),reduction_block_1:a("entry_flow/reduction_block_1")},c={};Zp(e,0,1).forEach(function(t){c["main_block_"+t]=s("middle_flow/main_block_"+t)});var l={reduction_block:a("exit_flow/reduction_block"),separable_conv:i("exit_flow/separable_conv")};return Fv(t,n),{params:{entry_flow:u,middle_flow:c,exit_flow:l},paramMappings:n}}function dm(t,e,n){return Ou(Ec(t,e.filters,n,"same"),e.bias)}function vm(t,e,n){void 0===n&&(n=!0);var r=n?dl(t):t;return r=Dv(r,e.separable_conv0,[1,1]),r=Dv(dl(r),e.separable_conv1,[1,1]),r=Gc(r,[3,3],[2,2],"same"),r=Ou(r,dm(t,e.expansion_conv,[2,2]))}var mm,gm,ym=(Pp(xm,mm=kv),xm.prototype.forwardInput=function(n){var r=this,o=this.params;if(!o)throw new Error("TinyXception - load model before inference");return nn(function(){var t=yd(n.toBatchTensor(112,!0),[122.782,117.001,104.298]).div(kn(256)),e=dl(dm(t,o.entry_flow.conv_in,[2,2]));return e=vm(e=vm(e,o.entry_flow.reduction_block_0,!1),o.entry_flow.reduction_block_1),Zp(r._numMainBlocks,0,1).forEach(function(t){e=function(t,e){var n=Dv(dl(t),e.separable_conv0,[1,1]);return n=Dv(dl(n),e.separable_conv1,[1,1]),n=Dv(dl(n),e.separable_conv2,[1,1]),n=Ou(n,t)}(e,o.middle_flow["main_block_"+t])}),e=vm(e,o.exit_flow.reduction_block),e=dl(Dv(e,o.exit_flow.separable_conv,[1,1]))})},xm.prototype.forward=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,bv(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},xm.prototype.getDefaultModelName=function(){return"tiny_xception_model"},xm.prototype.extractParamsFromWeigthMap=function(t){return pm(t,this._numMainBlocks)},xm.prototype.extractParams=function(t){return fm(t,this._numMainBlocks)},xm);function xm(t){var e=mm.call(this,"TinyXception")||this;return e._numMainBlocks=t,e}(gm=c.Gender||(c.Gender={})).FEMALE="female",gm.MALE="male";var bm,wm=(Pp(Cm,bm=kv),Object.defineProperty(Cm.prototype,"faceFeatureExtractor",{get:function(){return this._faceFeatureExtractor},enumerable:!0,configurable:!0}),Cm.prototype.runNet=function(n){var r=this,o=this.params;if(!o)throw new Error(this._name+" - load model before inference");return nn(function(){var t=n instanceof yv?r.faceFeatureExtractor.forwardInput(n):n,e=Hc(t,[7,7],[2,2],"valid").as2D(t.shape[0],-1);return{age:Kv(e,o.fc.age).as1D(),gender:Kv(e,o.fc.gender)}})},Cm.prototype.forwardInput=function(r){var o=this;return nn(function(){var t=o.runNet(r),e=t.age,n=t.gender;return{age:e,gender:so(n)}})},Cm.prototype.forward=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,bv(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},Cm.prototype.predictAgeAndGender=function(s){return Lp(this,void 0,void 0,function(){var e,n,r,o,i,a,u=this;return Wp(this,function(t){switch(t.label){case 0:return[4,bv(s)];case 1:return e=t.sent(),[4,this.forwardInput(e)];case 2:return n=t.sent(),r=Br(n.age),o=Br(n.gender),i=r.map(function(t,e){return{ageTensor:t,genderTensor:o[e]}}),[4,Promise.all(i.map(function(t){var a=t.ageTensor,s=t.genderTensor;return Lp(u,void 0,void 0,function(){var e,n,r,o,i;return Wp(this,function(t){switch(t.label){case 0:return[4,a.data()];case 1:return e=t.sent()[0],[4,s.data()];case 2:return n=t.sent()[0],o=(r=.5<n)?c.Gender.MALE:c.Gender.FEMALE,i=r?n:1-n,a.dispose(),s.dispose(),[2,{age:e,gender:o,genderProbability:i}]}})})}))];case 3:return a=t.sent(),n.age.dispose(),n.gender.dispose(),[2,e.isBatchInput?a:a[0]]}})})},Cm.prototype.getDefaultModelName=function(){return"age_gender_model"},Cm.prototype.dispose=function(t){void 0===t&&(t=!0),this.faceFeatureExtractor.dispose(t),bm.prototype.dispose.call(this,t)},Cm.prototype.loadClassifierParams=function(t){var e=this.extractClassifierParams(t),n=e.params,r=e.paramMappings;this._params=n,this._paramMappings=r},Cm.prototype.extractClassifierParams=function(t){return function(t){var e=[],n=zv(t),r=n.extractWeights,o=n.getRemainingWeights,i=Ov(r,e),a=i(512,1,"fc/age"),s=i(512,2,"fc/gender");if(0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{paramMappings:e,params:{fc:{age:a,gender:s}}}}(t)},Cm.prototype.extractParamsFromWeigthMap=function(t){var e=Xv(t),n=e.featureExtractorMap,r=e.classifierMap;return this.faceFeatureExtractor.loadFromWeightMap(n),function(t){var e=[],n=Wv(t,e);function r(t){return{weights:n(t+"/weights",2),bias:n(t+"/bias",1)}}var o={fc:{age:r("fc/age"),gender:r("fc/gender")}};return Fv(t,e),{params:o,paramMappings:e}}(r)},Cm.prototype.extractParams=function(t){var e=t.slice(0,t.length-1539),n=t.slice(t.length-1539);return this.faceFeatureExtractor.extractWeights(e),this.extractClassifierParams(n)},Cm);function Cm(t){void 0===t&&(t=new ym(2));var e=bm.call(this,"AgeGenderNet")||this;return e._faceFeatureExtractor=t,e}var Em,_m=(Pp(Im,Em=$v),Im.prototype.postProcess=function(t,o,e){var i=e.map(function(t){var e=t.width,n=t.height,r=o/Math.max(n,e);return{width:e*r,height:n*r}}),a=i.length;return nn(function(){function n(t,e){return Mr([Bn([68],t),Bn([68],e)],1).as2D(1,136).as1D()}function r(t,e){var n=i[t],r=n.width,o=n.height;return e(r,o)?Math.abs(r-o)/2:0}return t.mul(Bn([a,136],o)).sub(Mr(Array.from(Array(a),function(t,e){return n(function(t){return r(t,function(t,e){return t<e})}(e),function(t){return r(t,function(t,e){return e<t})}(e))}))).div(Mr(Array.from(Array(a),function(t,e){return n(i[e].width,i[e].height)})))})},Im.prototype.forwardInput=function(e){var n=this;return nn(function(){var t=n.runNet(e);return n.postProcess(t,e.inputSize,e.inputDimensions.map(function(t){return{height:t[0],width:t[1]}}))})},Im.prototype.forward=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,bv(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},Im.prototype.detectLandmarks=function(o){return Lp(this,void 0,void 0,function(){var u,e,n,r=this;return Wp(this,function(t){switch(t.label){case 0:return[4,bv(o)];case 1:return u=t.sent(),e=nn(function(){return Br(r.forwardInput(u))}),[4,Promise.all(e.map(function(a,s){return Lp(r,void 0,void 0,function(){var e,n,r,o,i;return Wp(this,function(t){switch(t.label){case 0:return r=(n=Array).from,[4,a.data()];case 1:return e=r.apply(n,[t.sent()]),o=e.filter(function(t,e){return Xp(e)}),i=e.filter(function(t,e){return!Xp(e)}),[2,new Ad(Array(68).fill(0).map(function(t,e){return new rd(o[e],i[e])}),{height:u.getInputHeight(s),width:u.getInputWidth(s)})]}})})}))];case 2:return n=t.sent(),e.forEach(function(t){return t.dispose()}),[2,u.isBatchInput?n:n[0]]}})})},Im.prototype.getClassifierChannelsOut=function(){return 136},Im);function Im(){return null!==Em&&Em.apply(this,arguments)||this}var Rm,km=(Pp(Sm,Rm=_m),Sm.prototype.getDefaultModelName=function(){return"face_landmark_68_model"},Sm.prototype.getClassifierChannelsIn=function(){return 256},Sm);function Sm(t){return void 0===t&&(t=new qv),Rm.call(this,"FaceLandmark68Net",t)||this}var Dm,Am=(Pp(Tm,Dm=kv),Tm.prototype.forwardInput=function(e){var n=this.params;if(!n)throw new Error("TinyFaceFeatureExtractor - load model before inference");return nn(function(){var t=Av(yd(e.toBatchTensor(112,!0),[122.782,117.001,104.298]).div(kn(255)),n.dense0,!0);return t=Av(t=Av(t,n.dense1),n.dense2),t=Hc(t,[14,14],[2,2],"valid")})},Tm.prototype.forward=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,bv(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},Tm.prototype.getDefaultModelName=function(){return"face_feature_extractor_tiny_model"},Tm.prototype.extractParamsFromWeigthMap=function(t){return function(t){var e=[],n=Gv(t,e).extractDenseBlock3Params,r={dense0:n("dense0",!0),dense1:n("dense1"),dense2:n("dense2")};return Fv(t,e),{params:r,paramMappings:e}}(t)},Tm.prototype.extractParams=function(t){return function(t){var e=[],n=zv(t),r=n.extractWeights,o=n.getRemainingWeights,i=Uv(r,e).extractDenseBlock3Params,a=i(3,32,"dense0",!0),s=i(32,64,"dense1"),u=i(64,128,"dense2");if(0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{paramMappings:e,params:{dense0:a,dense1:s,dense2:u}}}(t)},Tm);function Tm(){return Dm.call(this,"TinyFaceFeatureExtractor")||this}var Nm,Fm=(Pp(Mm,Nm=_m),Mm.prototype.getDefaultModelName=function(){return"face_landmark_68_tiny_model"},Mm.prototype.getClassifierChannelsIn=function(){return 128},Mm);function Mm(t){return void 0===t&&(t=new Am),Nm.call(this,"FaceLandmark68TinyNet",t)||this}var Om,Pm=(Pp(Bm,Om=km),Bm);function Bm(){return null!==Om&&Om.apply(this,arguments)||this}function Lm(t,e,n,r,o){void 0===o&&(o="same");var i=e.conv,a=i.filters,s=i.bias,u=Ec(t,a,n,o);return u=function(t,e){return Ou(Yu(t,e.weights),e.biases)}(u=Ou(u,s),e.scale),r?dl(u):u}function Wm(t,e){return Lm(t,e,[1,1],!1)}function zm(t,e){return Lm(t,e,[2,2],!0,"valid")}function Um(a,s){function o(t,e,n,r){var o=function(t,e,n){var r=a(t),o=r.length/(e*n*n);if(Kp(o))throw new Error("depth has to be an integer: "+o+", weights.length: "+r.length+", numFilters: "+e+", filterSize: "+n);return nn(function(){return gl(Tn(r,[e,o,n,n]),[2,3,1,0])})}(t,e,n),i=Sn(a(e));return s.push({paramPath:r+"/filters"},{paramPath:r+"/bias"}),{filters:o,bias:i}}function i(t,e,n,r){return{conv:o(t,e,n,r+"/conv"),scale:function(t,e){var n=Sn(a(t)),r=Sn(a(t));return s.push({paramPath:e+"/weights"},{paramPath:e+"/biases"}),{weights:n,biases:r}}(e,r+"/scale")}}return{extractConvLayerParams:i,extractResidualLayerParams:function(t,e,n,r,o){return void 0===o&&(o=!1),{conv1:i((o?.5:1)*t,e,n,r+"/conv1"),conv2:i(t,e,n,r+"/conv2")}}}}function Vm(t,e){var n=Wv(t,e);function r(t){return{conv:{filters:n(t+"/conv/filters",4),bias:n(t+"/conv/bias",1)},scale:function(t){return{weights:n(t+"/scale/weights",1),biases:n(t+"/scale/biases",1)}}(t)}}return{extractConvLayerParams:r,extractResidualLayerParams:function(t){return{conv1:r(t+"/conv1"),conv2:r(t+"/conv2")}}}}function Gm(t,e){var n=function(t,e){return Lm(t,e,[1,1],!0)}(t,e.conv1);return n=Wm(n,e.conv2),n=Ou(n,t),n=dl(n)}function Hm(t,e){var n=zm(t,e.conv1);n=Wm(n,e.conv2);var r=Hc(t,2,2,"valid"),o=Pn(r.shape),i=r.shape[3]!==n.shape[3];if(r.shape[1]!==n.shape[1]||r.shape[2]!==n.shape[2]){var a=zp(n.shape);a[1]=1;var s=Pn(a),u=zp((n=Vn([n,s],1)).shape);u[2]=1;var c=Pn(u);n=Vn([n,c],2)}return r=i?Vn([r,o],3):r,n=Ou(r,n),n=dl(n)}var qm,jm=(Pp(Km,qm=kv),Km.prototype.forwardInput=function(n){var r=this.params;if(!r)throw new Error("FaceRecognitionNet - load model before inference");return nn(function(){var t=zm(yd(n.toBatchTensor(150,!0).toFloat(),[122.782,117.001,104.298]).div(kn(256)),r.conv32_down),e=(t=Hm(t=Gm(t=Gm(t=Hm(t=Gm(t=Gm(t=Hm(t=Gm(t=Gm(t=Gm(t=Hm(t=Gm(t=Gm(t=Gm(t=Gc(t,3,2,"valid"),r.conv32_1),r.conv32_2),r.conv32_3),r.conv64_down),r.conv64_1),r.conv64_2),r.conv64_3),r.conv128_down),r.conv128_1),r.conv128_2),r.conv256_down),r.conv256_1),r.conv256_2),r.conv256_down_out)).mean([1,2]);return Fc(e,r.fc)})},Km.prototype.forward=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,bv(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},Km.prototype.computeFaceDescriptor=function(i){return Lp(this,void 0,void 0,function(){var e,n,r,o=this;return Wp(this,function(t){switch(t.label){case 0:return[4,bv(i)];case 1:return e=t.sent(),n=nn(function(){return Br(o.forwardInput(e))}),[4,Promise.all(n.map(function(t){return t.data()}))];case 2:return r=t.sent(),n.forEach(function(t){return t.dispose()}),[2,e.isBatchInput?r:r[0]]}})})},Km.prototype.getDefaultModelName=function(){return"face_recognition_model"},Km.prototype.extractParamsFromWeigthMap=function(t){return function(t){var e=[],n=Vm(t,e),r=n.extractConvLayerParams,o=n.extractResidualLayerParams,i=r("conv32_down"),a=o("conv32_1"),s=o("conv32_2"),u=o("conv32_3"),c=o("conv64_down"),l=o("conv64_1"),h=o("conv64_2"),f=o("conv64_3"),p=o("conv128_down"),d=o("conv128_1"),v=o("conv128_2"),m=o("conv256_down"),g=o("conv256_1"),y=o("conv256_2"),x=o("conv256_down_out"),b=t.fc;if(e.push({originalPath:"fc",paramPath:"fc"}),!Hp(b))throw new Error("expected weightMap[fc] to be a Tensor2D, instead have "+b);var w={conv32_down:i,conv32_1:a,conv32_2:s,conv32_3:u,conv64_down:c,conv64_1:l,conv64_2:h,conv64_3:f,conv128_down:p,conv128_1:d,conv128_2:v,conv256_down:m,conv256_1:g,conv256_2:y,conv256_down_out:x,fc:b};return Fv(t,e),{params:w,paramMappings:e}}(t)},Km.prototype.extractParams=function(t){return function(t){var e=zv(t),n=e.extractWeights,r=e.getRemainingWeights,o=[],i=Um(n,o),a=i.extractConvLayerParams,s=i.extractResidualLayerParams,u=a(4704,32,7,"conv32_down"),c=s(9216,32,3,"conv32_1"),l=s(9216,32,3,"conv32_2"),h=s(9216,32,3,"conv32_3"),f=s(36864,64,3,"conv64_down",!0),p=s(36864,64,3,"conv64_1"),d=s(36864,64,3,"conv64_2"),v=s(36864,64,3,"conv64_3"),m=s(147456,128,3,"conv128_down",!0),g=s(147456,128,3,"conv128_1"),y=s(147456,128,3,"conv128_2"),x=s(589824,256,3,"conv256_down",!0),b=s(589824,256,3,"conv256_1"),w=s(589824,256,3,"conv256_2"),C=s(589824,256,3,"conv256_down_out"),E=nn(function(){return gl(Dn(n(32768),[128,256]),[1,0])});if(o.push({paramPath:"fc"}),0!==r().length)throw new Error("weights remaing after extract: "+r().length);return{params:{conv32_down:u,conv32_1:c,conv32_2:l,conv32_3:h,conv64_down:f,conv64_1:p,conv64_2:d,conv64_3:v,conv128_down:m,conv128_1:g,conv128_2:y,conv256_down:x,conv256_1:b,conv256_2:w,conv256_down_out:C,fc:E},paramMappings:o}}(t)},Km);function Km(){return qm.call(this,"FaceRecognitionNet")||this}function Xm(t,e){var n={descriptor:e};return Object.assign({},t,n)}function Ym(t,e){var n={age:e};return Object.assign({},t,n)}function $m(t,e,n){var r={gender:e,genderProbability:n};return Object.assign({},t,r)}var Jm=(Object.defineProperty(Qm.prototype,"minFaceSize",{get:function(){return this._minFaceSize},enumerable:!0,configurable:!0}),Object.defineProperty(Qm.prototype,"scaleFactor",{get:function(){return this._scaleFactor},enumerable:!0,configurable:!0}),Object.defineProperty(Qm.prototype,"maxNumScales",{get:function(){return this._maxNumScales},enumerable:!0,configurable:!0}),Object.defineProperty(Qm.prototype,"scoreThresholds",{get:function(){return this._scoreThresholds},enumerable:!0,configurable:!0}),Object.defineProperty(Qm.prototype,"scaleSteps",{get:function(){return this._scaleSteps},enumerable:!0,configurable:!0}),Qm);function Qm(t){var e=void 0===t?{}:t,n=e.minFaceSize,r=e.scaleFactor,o=e.maxNumScales,i=e.scoreThresholds,a=e.scaleSteps;if(this._name="MtcnnOptions",this._minFaceSize=n||20,this._scaleFactor=r||.709,this._maxNumScales=o||10,this._scoreThresholds=i||[.6,.7,.7],this._scaleSteps=a,"number"!=typeof this._minFaceSize||this._minFaceSize<0)throw new Error(this._name+" - expected minFaceSize to be a number > 0");if("number"!=typeof this._scaleFactor||this._scaleFactor<=0||1<=this._scaleFactor)throw new Error(this._name+" - expected scaleFactor to be a number between 0 and 1");if("number"!=typeof this._maxNumScales||this._maxNumScales<0)throw new Error(this._name+" - expected maxNumScales to be a number > 0");if(!Array.isArray(this._scoreThresholds)||3!==this._scoreThresholds.length||this._scoreThresholds.some(function(t){return"number"!=typeof t}))throw new Error(this._name+" - expected scoreThresholds to be an array of numbers of length 3");if(this._scaleSteps&&(!Array.isArray(this._scaleSteps)||this._scaleSteps.some(function(t){return"number"!=typeof t})))throw new Error(this._name+" - expected scaleSteps to be an array of numbers")}function Zm(s,u){function i(t,e,n,r,o){var i=Tn(s(t*e*n*n),[n,n,t,e]),a=Sn(s(e));return u.push({paramPath:r+"/filters"},{paramPath:r+"/"+(o?"batch_norm_offset":"bias")}),{filters:i,bias:a}}function r(t,e,n,r){var o=i(t,e,n,r,!0);return{filters:o.filters,batch_norm_offset:o.bias}}function t(t,e,n){return{depthwise_conv:function(t,e){var n=Tn(s(9*t),[3,3,t,1]),r=Sn(s(t)),o=Sn(s(t)),i=Sn(s(t)),a=Sn(s(t));return u.push({paramPath:e+"/filters"},{paramPath:e+"/batch_norm_scale"},{paramPath:e+"/batch_norm_offset"},{paramPath:e+"/batch_norm_mean"},{paramPath:e+"/batch_norm_variance"}),{filters:n,batch_norm_scale:r,batch_norm_offset:o,batch_norm_mean:i,batch_norm_variance:a}}(t,n+"/depthwise_conv"),pointwise_conv:r(t,e,1,n+"/pointwise_conv")}}return{extractMobilenetV1Params:function(){return{conv_0:r(3,32,3,"mobilenetv1/conv_0"),conv_1:t(32,64,"mobilenetv1/conv_1"),conv_2:t(64,128,"mobilenetv1/conv_2"),conv_3:t(128,128,"mobilenetv1/conv_3"),conv_4:t(128,256,"mobilenetv1/conv_4"),conv_5:t(256,256,"mobilenetv1/conv_5"),conv_6:t(256,512,"mobilenetv1/conv_6"),conv_7:t(512,512,"mobilenetv1/conv_7"),conv_8:t(512,512,"mobilenetv1/conv_8"),conv_9:t(512,512,"mobilenetv1/conv_9"),conv_10:t(512,512,"mobilenetv1/conv_10"),conv_11:t(512,512,"mobilenetv1/conv_11"),conv_12:t(512,1024,"mobilenetv1/conv_12"),conv_13:t(1024,1024,"mobilenetv1/conv_13")}},extractPredictionLayerParams:function(){return{conv_0:r(1024,256,1,"prediction_layer/conv_0"),conv_1:r(256,512,3,"prediction_layer/conv_1"),conv_2:r(512,128,1,"prediction_layer/conv_2"),conv_3:r(128,256,3,"prediction_layer/conv_3"),conv_4:r(256,128,1,"prediction_layer/conv_4"),conv_5:r(128,256,3,"prediction_layer/conv_5"),conv_6:r(256,64,1,"prediction_layer/conv_6"),conv_7:r(64,128,3,"prediction_layer/conv_7"),box_predictor_0:{box_encoding_predictor:i(512,12,1,"prediction_layer/box_predictor_0/box_encoding_predictor"),class_predictor:i(512,9,1,"prediction_layer/box_predictor_0/class_predictor")},box_predictor_1:{box_encoding_predictor:i(1024,24,1,"prediction_layer/box_predictor_1/box_encoding_predictor"),class_predictor:i(1024,18,1,"prediction_layer/box_predictor_1/class_predictor")},box_predictor_2:{box_encoding_predictor:i(512,24,1,"prediction_layer/box_predictor_2/box_encoding_predictor"),class_predictor:i(512,18,1,"prediction_layer/box_predictor_2/class_predictor")},box_predictor_3:{box_encoding_predictor:i(256,24,1,"prediction_layer/box_predictor_3/box_encoding_predictor"),class_predictor:i(256,18,1,"prediction_layer/box_predictor_3/class_predictor")},box_predictor_4:{box_encoding_predictor:i(256,24,1,"prediction_layer/box_predictor_4/box_encoding_predictor"),class_predictor:i(256,18,1,"prediction_layer/box_predictor_4/class_predictor")},box_predictor_5:{box_encoding_predictor:i(128,24,1,"prediction_layer/box_predictor_5/box_encoding_predictor"),class_predictor:i(128,18,1,"prediction_layer/box_predictor_5/class_predictor")}}}}}function tg(t){var e=[],n=function(t,e){var i=Wv(t,e);function a(t,e,n){return{filters:i(t+"/Conv2d_"+e+"_pointwise/weights",4,n+"/filters"),batch_norm_offset:i(t+"/Conv2d_"+e+"_pointwise/convolution_bn_offset",1,n+"/batch_norm_offset")}}function n(t){var e="mobilenetv1/conv_"+t,n="MobilenetV1/Conv2d_"+t+"_depthwise",r=e+"/depthwise_conv",o=e+"/pointwise_conv";return{depthwise_conv:{filters:i(n+"/depthwise_weights",4,r+"/filters"),batch_norm_scale:i(n+"/BatchNorm/gamma",1,r+"/batch_norm_scale"),batch_norm_offset:i(n+"/BatchNorm/beta",1,r+"/batch_norm_offset"),batch_norm_mean:i(n+"/BatchNorm/moving_mean",1,r+"/batch_norm_mean"),batch_norm_variance:i(n+"/BatchNorm/moving_variance",1,r+"/batch_norm_variance")},pointwise_conv:a("MobilenetV1",t,o)}}function r(t,e){return{filters:i(t+"/weights",4,e+"/filters"),bias:i(t+"/biases",1,e+"/bias")}}function o(t){return{box_encoding_predictor:r("Prediction/BoxPredictor_"+t+"/BoxEncodingPredictor","prediction_layer/box_predictor_"+t+"/box_encoding_predictor"),class_predictor:r("Prediction/BoxPredictor_"+t+"/ClassPredictor","prediction_layer/box_predictor_"+t+"/class_predictor")}}return{extractMobilenetV1Params:function(){return{conv_0:a("MobilenetV1",0,"mobilenetv1/conv_0"),conv_1:n(1),conv_2:n(2),conv_3:n(3),conv_4:n(4),conv_5:n(5),conv_6:n(6),conv_7:n(7),conv_8:n(8),conv_9:n(9),conv_10:n(10),conv_11:n(11),conv_12:n(12),conv_13:n(13)}},extractPredictionLayerParams:function(){return{conv_0:a("Prediction",0,"prediction_layer/conv_0"),conv_1:a("Prediction",1,"prediction_layer/conv_1"),conv_2:a("Prediction",2,"prediction_layer/conv_2"),conv_3:a("Prediction",3,"prediction_layer/conv_3"),conv_4:a("Prediction",4,"prediction_layer/conv_4"),conv_5:a("Prediction",5,"prediction_layer/conv_5"),conv_6:a("Prediction",6,"prediction_layer/conv_6"),conv_7:a("Prediction",7,"prediction_layer/conv_7"),box_predictor_0:o(0),box_predictor_1:o(1),box_predictor_2:o(2),box_predictor_3:o(3),box_predictor_4:o(4),box_predictor_5:o(5)}}}}(t,e),r=n.extractMobilenetV1Params,o=n.extractPredictionLayerParams,i=t["Output/extra_dim"];if(e.push({originalPath:"Output/extra_dim",paramPath:"output_layer/extra_dim"}),!qp(i))throw new Error("expected weightMap['Output/extra_dim'] to be a Tensor3D, instead have "+i);var a={mobilenetv1:r(),prediction_layer:o(),output_layer:{extra_dim:i}};return Fv(t,e),{params:a,paramMappings:e}}function eg(e,n,r){return nn(function(){var t=Ec(e,n.filters,r,"same");return t=Ou(t,n.batch_norm_offset),Gs(t,0,6)})}var ng=.0010000000474974513;function rg(t,e){return nn(function(){var o=null,i=eg(t,e.conv_0,[2,2]);if([e.conv_1,e.conv_2,e.conv_3,e.conv_4,e.conv_5,e.conv_6,e.conv_7,e.conv_8,e.conv_9,e.conv_10,e.conv_11,e.conv_12,e.conv_13].forEach(function(t,e){var n=e+1,r=function(e){return[2,4,6,12].some(function(t){return t===e})?[2,2]:[1,1]}(n);i=eg(i=function(e,n,r){return nn(function(){var t=kc(e,n.filters,r,"same");return t=Ru(t,n.batch_norm_mean,n.batch_norm_variance,n.batch_norm_offset,n.batch_norm_scale,ng),Gs(t,0,6)})}(i,t.depthwise_conv,r),t.pointwise_conv,[1,1]),11===n&&(o=i)}),null===o)throw new Error("mobileNetV1 - output of conv layer 11 is null");return{out:i,conv11:o}})}function og(t,e,n){var r=t.arraySync(),o=Math.min(r[e][0],r[e][2]),i=Math.min(r[e][1],r[e][3]),a=Math.max(r[e][0],r[e][2]),s=Math.max(r[e][1],r[e][3]),u=Math.min(r[n][0],r[n][2]),c=Math.min(r[n][1],r[n][3]),l=Math.max(r[n][0],r[n][2]),h=Math.max(r[n][1],r[n][3]),f=(a-o)*(s-i),p=(l-u)*(h-c);if(f<=0||p<=0)return 0;var d=Math.max(o,u),v=Math.max(i,c),m=Math.min(a,l),g=Math.min(s,h),y=Math.max(m-d,0)*Math.max(g-v,0);return y/(f+p-y)}function ig(t,e){var n=function(t){var e=Br(gl(t,[1,0])),n=[tc(e[2],e[0]),tc(e[3],e[1])];return{sizes:n,centers:[Ou(e[0],Wu(n[0],kn(2))),Ou(e[1],Wu(n[1],kn(2)))]}}(t),r=n.sizes,o=n.centers,i=Br(gl(e,[1,0])),a=Wu(Yu(Ks(Wu(i[2],kn(5))),r[0]),kn(2)),s=Ou(Yu(Wu(i[0],kn(10)),r[0]),o[0]),u=Wu(Yu(Ks(Wu(i[3],kn(5))),r[1]),kn(2)),c=Ou(Yu(Wu(i[1],kn(10)),r[1]),o[1]);return gl(Mr([tc(s,a),tc(c,u),Ou(s,a),Ou(c,u)]),[1,0])}function ag(e,n){return nn(function(){var t=e.shape[0];return{boxPredictionEncoding:Tr(Nv(e,n.box_encoding_predictor),[t,-1,1,4]),classPrediction:Tr(Nv(e,n.class_predictor),[t,-1,3])}})}var sg=(Object.defineProperty(ug.prototype,"minConfidence",{get:function(){return this._minConfidence},enumerable:!0,configurable:!0}),Object.defineProperty(ug.prototype,"maxResults",{get:function(){return this._maxResults},enumerable:!0,configurable:!0}),ug);function ug(t){var e=void 0===t?{}:t,n=e.minConfidence,r=e.maxResults;if(this._name="SsdMobilenetv1Options",this._minConfidence=n||.5,this._maxResults=r||100,"number"!=typeof this._minConfidence||this._minConfidence<=0||1<=this._minConfidence)throw new Error(this._name+" - expected minConfidence to be a number between 0 and 1");if("number"!=typeof this._maxResults)throw new Error(this._name+" - expected maxResults to be a number")}var cg,lg=(Pp(hg,cg=kv),hg.prototype.forwardInput=function(r){var o=this.params;if(!o)throw new Error("SsdMobilenetv1 - load model before inference");return nn(function(){var t=r.toBatchTensor(512,!1).toFloat(),e=rg(tc(Yu(t,kn(.007843137718737125)),kn(1)),o.mobilenetv1),n=function(l,h,f){return nn(function(){var t=eg(eg(l,f.conv_0,[1,1]),f.conv_1,[2,2]),e=eg(eg(t,f.conv_2,[1,1]),f.conv_3,[2,2]),n=eg(eg(e,f.conv_4,[1,1]),f.conv_5,[2,2]),r=eg(eg(n,f.conv_6,[1,1]),f.conv_7,[2,2]),o=ag(h,f.box_predictor_0),i=ag(l,f.box_predictor_1),a=ag(t,f.box_predictor_2),s=ag(e,f.box_predictor_3),u=ag(n,f.box_predictor_4),c=ag(r,f.box_predictor_5);return{boxPredictions:Vn([o.boxPredictionEncoding,i.boxPredictionEncoding,a.boxPredictionEncoding,s.boxPredictionEncoding,u.boxPredictionEncoding,c.boxPredictionEncoding],1),classPredictions:Vn([o.classPrediction,i.classPrediction,a.classPrediction,s.classPrediction,u.classPrediction,c.classPrediction],1)}})}(e.out,e.conv11,o.prediction_layer);return function(o,i,a){return nn(function(){var t=o.shape[0],e=ig(Tr(Or(a.extra_dim,[t,1,1]),[-1,4]),Tr(o,[-1,4]));e=Tr(e,[t,e.shape[0]/t,4]);var n=ru(Xc(i,[0,0,1],[-1,-1,-1])),r=Xc(n,[0,0,0],[-1,-1,1]);return r=Tr(r,[t,r.shape[1]]),{boxes:Br(e),scores:Br(r)}})}(n.boxPredictions,n.classPredictions,o.output_layer)})},hg.prototype.forward=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,bv(n)];case 1:return[2,e.apply(this,[t.sent()])]}})})},hg.prototype.locateFaces=function(w,C){return void 0===C&&(C={}),Lp(this,void 0,void 0,function(){var e,n,r,s,o,i,a,u,c,l,h,f,p,d,v,m,g,y,x,b;return Wp(this,function(t){switch(t.label){case 0:return e=new sg(C),n=e.maxResults,r=e.minConfidence,[4,bv(w)];case 1:for(s=t.sent(),o=this.forwardInput(s),i=o.boxes,a=o.scores,u=i[0],c=a[0],l=1;l<i.length;l++)i[l].dispose(),a[l].dispose();return p=(f=Array).from,[4,c.data()];case 2:return h=p.apply(f,[t.sent()]),d=function(o,t,e,i,a){var n=o.shape[0],s=Math.min(e,n),r=t.map(function(t,e){return{score:t,boxIndex:e}}).filter(function(t){return t.score>a}).sort(function(t,e){return e.score-t.score}),u=[];return r.forEach(function(t){if(!(u.length>=s)){for(var e=t.score,n=u.length-1;0<=n;--n){var r=og(o,t.boxIndex,u[n]);if(0!==r&&(t.score*=r<=i?1:0,t.score<=a))break}e===t.score&&u.push(t.boxIndex)}}),u}(u,h,n,.5,r),v=s.getReshapedInputDimensions(0),m=s.inputSize,g=m/v.width,y=m/v.height,x=u.arraySync(),b=d.map(function(t){var e=[Math.max(0,x[t][0]),Math.min(1,x[t][2])].map(function(t){return t*y}),n=e[0],r=e[1],o=[Math.max(0,x[t][1]),Math.min(1,x[t][3])].map(function(t){return t*g}),i=o[0],a=o[1];return new pd(h[t],new Cd(i,n,a-i,r-n),{height:s.getInputHeight(0),width:s.getInputWidth(0)})}),u.dispose(),c.dispose(),[2,b]}})})},hg.prototype.getDefaultModelName=function(){return"ssd_mobilenetv1_model"},hg.prototype.extractParamsFromWeigthMap=function(t){return tg(t)},hg.prototype.extractParams=function(t){return function(t){var e=[],n=zv(t),r=n.extractWeights,o=n.getRemainingWeights,i=Zm(r,e),a=i.extractMobilenetV1Params,s=i.extractPredictionLayerParams,u=a(),c=s(),l={extra_dim:An(r(20472),[1,5118,4])};if(e.push({paramPath:"output_layer/extra_dim"}),0!==o().length)throw new Error("weights remaing after extract: "+o().length);return{params:{mobilenetv1:u,prediction_layer:c,output_layer:l},paramMappings:e}}(t)},hg);function hg(){return cg.call(this,"SsdMobilenetv1")||this}function fg(t){var e=new lg;return e.extractWeights(t),e}var pg,dg=(Pp(vg,pg=lg),vg);function vg(){return null!==pg&&pg.apply(this,arguments)||this}var mg,gg=[new rd(.738768,.874946),new rd(2.42204,2.65704),new rd(4.30971,7.04493),new rd(10.246,4.59428),new rd(12.6868,11.8741)],yg=[new rd(1.603231,2.094468),new rd(6.041143,7.080126),new rd(2.882459,3.518061),new rd(4.266906,5.178857),new rd(9.041765,10.66308)],xg=[117.001,114.697,97.404],bg=function(t){return"number"==typeof t};function wg(t){if(!t)throw new Error("invalid config: "+t);if("boolean"!=typeof t.withSeparableConvs)throw new Error("config.withSeparableConvs has to be a boolean, have: "+t.withSeparableConvs);if(!bg(t.iouThreshold)||t.iouThreshold<0||1<t.iouThreshold)throw new Error("config.iouThreshold has to be a number between [0, 1], have: "+t.iouThreshold);if(!Array.isArray(t.classes)||!t.classes.length||!t.classes.every(function(t){return"string"==typeof t}))throw new Error("config.classes has to be an array class names: string[], have: "+JSON.stringify(t.classes));if(!Array.isArray(t.anchors)||!t.anchors.length||!t.anchors.map(function(t){return t||{}}).every(function(t){return bg(t.x)&&bg(t.y)}))throw new Error("config.anchors has to be an array of { x: number, y: number }, have: "+JSON.stringify(t.anchors));if(t.meanRgb&&(!Array.isArray(t.meanRgb)||3!==t.meanRgb.length||!t.meanRgb.every(bg)))throw new Error("config.meanRgb has to be an array of shape [number, number, number], have: "+JSON.stringify(t.meanRgb))}function Cg(e){return nn(function(){var t=Yu(e,kn(.10000000149011612));return Ou(dl(tc(e,t)),t)})}function Eg(e,n){return nn(function(){var t=Cr(e,[[0,0],[1,1],[1,1],[0,0]]);return t=Ec(t,n.conv.filters,[1,1],"valid"),t=tc(t,n.bn.sub),t=Yu(t,n.bn.truediv),Cg(t=Ou(t,n.conv.bias))})}function _g(e,n){return nn(function(){var t=Cr(e,[[0,0],[1,1],[1,1],[0,0]]);return t=Ac(t,n.depthwise_filter,n.pointwise_filter,[1,1],"valid"),Cg(t=Ou(t,n.bias))})}function Ig(o,i){var r=Mv(o,i);var t=Bv(o,i);return{extractConvParams:r,extractConvWithBatchNormParams:function(t,e,n){return{conv:r(t,e,3,n+"/conv"),bn:function(t,e){var n=Sn(o(t)),r=Sn(o(t));return i.push({paramPath:e+"/sub"},{paramPath:e+"/truediv"}),{sub:n,truediv:r}}(e,n+"/bn")}},extractSeparableConvParams:t}}function Rg(t,e){var n=Wv(t,e);function r(t){return{filters:n(t+"/filters",4),bias:n(t+"/bias",1)}}return{extractConvParams:r,extractConvWithBatchNormParams:function(t){return{conv:r(t+"/conv"),bn:function(t){return{sub:n(t+"/sub",1),truediv:n(t+"/truediv",1)}}(t+"/bn")}},extractSeparableConvParams:Lv(n)}}(mg=c.TinyYolov2SizeType||(c.TinyYolov2SizeType={}))[mg.XS=224]="XS",mg[mg.SM=320]="SM",mg[mg.MD=416]="MD",mg[mg.LG=608]="LG";var kg=(Object.defineProperty(Sg.prototype,"inputSize",{get:function(){return this._inputSize},enumerable:!0,configurable:!0}),Object.defineProperty(Sg.prototype,"scoreThreshold",{get:function(){return this._scoreThreshold},enumerable:!0,configurable:!0}),Sg);function Sg(t){var e=void 0===t?{}:t,n=e.inputSize,r=e.scoreThreshold;if(this._name="TinyYolov2Options",this._inputSize=n||416,this._scoreThreshold=r||.5,"number"!=typeof this._inputSize||this._inputSize%32!=0)throw new Error(this._name+" - expected inputSize to be a number divisible by 32");if("number"!=typeof this._scoreThreshold||this._scoreThreshold<=0||1<=this._scoreThreshold)throw new Error(this._name+" - expected scoreThreshold to be a number between 0 and 1")}var Dg,Ag=(Pp(Tg,Dg=kv),Object.defineProperty(Tg.prototype,"config",{get:function(){return this._config},enumerable:!0,configurable:!0}),Object.defineProperty(Tg.prototype,"withClassScores",{get:function(){return this.config.withClassScores||1<this.config.classes.length},enumerable:!0,configurable:!0}),Object.defineProperty(Tg.prototype,"boxEncodingSize",{get:function(){return 5+(this.withClassScores?this.config.classes.length:0)},enumerable:!0,configurable:!0}),Tg.prototype.runTinyYolov2=function(t,e){var n=Eg(t,e.conv0);return n=Eg(n=Gc(n,[2,2],[2,2],"same"),e.conv1),n=Eg(n=Gc(n,[2,2],[2,2],"same"),e.conv2),n=Eg(n=Gc(n,[2,2],[2,2],"same"),e.conv3),n=Eg(n=Gc(n,[2,2],[2,2],"same"),e.conv4),n=Eg(n=Gc(n,[2,2],[2,2],"same"),e.conv5),Nv(n=Eg(n=Eg(n=Gc(n,[2,2],[1,1],"same"),e.conv6),e.conv7),e.conv8,"valid",!1)},Tg.prototype.runMobilenet=function(t,e){var n=this.config.isFirstLayerConv2d?Cg(Nv(t,e.conv0,"valid",!1)):_g(t,e.conv0);return n=_g(n=Gc(n,[2,2],[2,2],"same"),e.conv1),n=_g(n=Gc(n,[2,2],[2,2],"same"),e.conv2),n=_g(n=Gc(n,[2,2],[2,2],"same"),e.conv3),n=_g(n=Gc(n,[2,2],[2,2],"same"),e.conv4),n=_g(n=Gc(n,[2,2],[2,2],"same"),e.conv5),n=Gc(n,[2,2],[1,1],"same"),n=e.conv6?_g(n,e.conv6):n,Nv(n=e.conv7?_g(n,e.conv7):n,e.conv8,"valid",!1)},Tg.prototype.forwardInput=function(e,n){var r=this,o=this.params;if(!o)throw new Error("TinyYolov2 - load model before inference");return nn(function(){var t=e.toBatchTensor(n,!1).toFloat();return t=(t=r.config.meanRgb?yd(t,r.config.meanRgb):t).div(kn(256)),r.config.withSeparableConvs?r.runMobilenet(t,o):r.runTinyYolov2(t,o)})},Tg.prototype.forward=function(n,r){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=this.forwardInput,[4,bv(n)];case 1:return[4,e.apply(this,[t.sent(),r])];case 2:return[2,t.sent()]}})})},Tg.prototype.detect=function(d,v){return void 0===v&&(v={}),Lp(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p=this;return Wp(this,function(t){switch(t.label){case 0:return e=new kg(v),n=e.inputSize,r=e.scoreThreshold,[4,bv(d)];case 1:return o=t.sent(),[4,this.forwardInput(o,n)];case 2:return i=t.sent(),a=nn(function(){return Br(i)[0].expandDims()}),s={width:o.getInputWidth(0),height:o.getInputHeight(0)},[4,this.extractBoxes(a,o.getReshapedInputDimensions(0),r)];case 3:return u=t.sent(),i.dispose(),a.dispose(),c=u.map(function(t){return t.box}),l=u.map(function(t){return t.score}),h=u.map(function(t){return t.classScore}),f=u.map(function(t){return p.config.classes[t.label]}),[2,gd(c.map(function(t){return t.rescale(n)}),l,this.config.iouThreshold,!0).map(function(t){return new ld(l[t],h[t],f[t],c[t],s)})]}})})},Tg.prototype.getDefaultModelName=function(){return""},Tg.prototype.extractParamsFromWeigthMap=function(t){return function(t,e){var n,r=[],o=Rg(t,r),i=o.extractConvParams,a=o.extractConvWithBatchNormParams,s=o.extractSeparableConvParams;if(e.withSeparableConvs){var u=e.filterSizes&&e.filterSizes.length||9;n={conv0:e.isFirstLayerConv2d?i("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:7<u?s("conv6"):void 0,conv7:8<u?s("conv7"):void 0,conv8:i("conv8")}}else n={conv0:a("conv0"),conv1:a("conv1"),conv2:a("conv2"),conv3:a("conv3"),conv4:a("conv4"),conv5:a("conv5"),conv6:a("conv6"),conv7:a("conv7"),conv8:i("conv8")};return Fv(t,r),{params:n,paramMappings:r}}(t,this.config)},Tg.prototype.extractParams=function(t){var e=this.config.filterSizes||Tg.DEFAULT_FILTER_SIZES,n=e?e.length:void 0;if(7!==n&&8!==n&&9!==n)throw new Error("TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found "+n+" filterSizes in config");return function(t,e,n,r){var o,i=zv(t),a=i.extractWeights,s=i.getRemainingWeights,u=[],c=Ig(a,u),l=c.extractConvParams,h=c.extractConvWithBatchNormParams,f=c.extractSeparableConvParams;if(e.withSeparableConvs){var p=r[0],d=r[1],v=r[2],m=r[3],g=r[4],y=r[5],x=r[6],b=r[7],w=r[8];o={conv0:e.isFirstLayerConv2d?l(p,d,3,"conv0"):f(p,d,"conv0"),conv1:f(d,v,"conv1"),conv2:f(v,m,"conv2"),conv3:f(m,g,"conv3"),conv4:f(g,y,"conv4"),conv5:f(y,x,"conv5"),conv6:b?f(x,b,"conv6"):void 0,conv7:w?f(b,w,"conv7"):void 0,conv8:l(w||b||x,5*n,1,"conv8")}}else p=r[0],d=r[1],v=r[2],m=r[3],g=r[4],y=r[5],x=r[6],b=r[7],w=r[8],o={conv0:h(p,d,"conv0"),conv1:h(d,v,"conv1"),conv2:h(v,m,"conv2"),conv3:h(m,g,"conv3"),conv4:h(g,y,"conv4"),conv5:h(y,x,"conv5"),conv6:h(x,b,"conv6"),conv7:h(b,w,"conv7"),conv8:l(w,5*n,1,"conv8")};if(0!==s().length)throw new Error("weights remaing after extract: "+s().length);return{params:o,paramMappings:u}}(t,this.config,this.boxEncodingSize,e)},Tg.prototype.extractBoxes=function(T,N,F){return Lp(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p,d,v,m,g,y,x,b,w,C,E,_,I,R,k,S,D,A=this;return Wp(this,function(t){switch(t.label){case 0:return e=N.width,n=N.height,r=Math.max(e,n),o=r/e,i=r/n,a=T.shape[1],s=this.config.anchors.length,u=nn(function(){var t=T.reshape([a,a,s,A.boxEncodingSize]);return[t.slice([0,0,0,0],[a,a,s,4]),t.slice([0,0,0,4],[a,a,s,1]),A.withClassScores?so(t.slice([0,0,0,5],[a,a,s,A.config.classes.length]),3):kn(0)]}),c=u[0],l=u[1],h=u[2],f=[],[4,l.array()];case 1:return p=t.sent(),[4,c.array()];case 2:d=t.sent(),v=0,t.label=3;case 3:if(!(v<a))return[3,12];m=0,t.label=4;case 4:if(!(m<a))return[3,11];g=0,t.label=5;case 5:return g<s?(y=bd(p[v][m][g][0]),!F||F<y?(x=(m+bd(d[v][m][g][0]))/a*o,b=(v+bd(d[v][m][g][1]))/a*i,w=Math.exp(d[v][m][g][2])*this.config.anchors[g].x/a*o,C=Math.exp(d[v][m][g][3])*this.config.anchors[g].y/a*i,E=x-w/2,_=b-C/2,I={row:v,col:m,anchor:g},this.withClassScores?[4,this.extractPredictedClass(h,I)]:[3,7]):[3,9]):[3,10];case 6:return D=t.sent(),[3,8];case 7:D={classScore:1,label:0},t.label=8;case 8:k=(R=D).classScore,S=R.label,f.push(Bp({box:new ud(E,_,E+w,_+C),score:y,classScore:y*k,label:S},I)),t.label=9;case 9:return g++,[3,5];case 10:return m++,[3,4];case 11:return v++,[3,3];case 12:return c.dispose(),l.dispose(),h.dispose(),[2,f]}})})},Tg.prototype.extractPredictedClass=function(e,a){return Lp(this,void 0,void 0,function(){var n,r,o,i;return Wp(this,function(t){switch(t.label){case 0:return n=a.row,r=a.col,o=a.anchor,[4,e.array()];case 1:return i=t.sent(),[2,Array(this.config.classes.length).fill(0).map(function(t,e){return i[n][r][o][e]}).map(function(t,e){return{classScore:t,label:e}}).reduce(function(t,e){return t.classScore>e.classScore?t:e})]}})})},Tg.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024],Tg);function Tg(t){var e=Dg.call(this,"TinyYolov2")||this;return wg(t),e._config=t,e}var Ng,Fg=(Pp(Mg,Ng=Ag),Object.defineProperty(Mg.prototype,"withSeparableConvs",{get:function(){return this.config.withSeparableConvs},enumerable:!0,configurable:!0}),Object.defineProperty(Mg.prototype,"anchors",{get:function(){return this.config.anchors},enumerable:!0,configurable:!0}),Mg.prototype.locateFaces=function(e,n){return Lp(this,void 0,void 0,function(){return Wp(this,function(t){switch(t.label){case 0:return[4,this.detect(e,n)];case 1:return[2,t.sent().map(function(t){return new pd(t.score,t.relativeBox,{width:t.imageWidth,height:t.imageHeight})})]}})})},Mg.prototype.getDefaultModelName=function(){return this.withSeparableConvs?"tiny_yolov2_separable_conv_model":"tiny_yolov2_model"},Mg.prototype.extractParamsFromWeigthMap=function(t){return Ng.prototype.extractParamsFromWeigthMap.call(this,t)},Mg);function Mg(t){void 0===t&&(t=!0);var e=Object.assign({},{withSeparableConvs:t,iouThreshold:.4,classes:["face"]},t?{anchors:yg,meanRgb:xg}:{anchors:gg,withClassScores:!0});return Ng.call(this,e)||this}var Og,Pg=(Pp(Bg,Og=kg),Bg);function Bg(){var t=null!==Og&&Og.apply(this,arguments)||this;return t._name="TinyFaceDetectorOptions",t}var Lg=(Wg.prototype.then=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=n,[4,this.run()];case 1:return[2,e.apply(void 0,[t.sent()])]}})})},Wg.prototype.run=function(){return Lp(this,void 0,void 0,function(){return Wp(this,function(t){throw new Error("ComposableTask - run is not implemented")})})},Wg);function Wg(){}function zg(a,s,u,c,l){return void 0===l&&(l=function(t){return t.alignedRect}),Lp(this,void 0,void 0,function(){var e,n,r,o,i;return Wp(this,function(t){switch(t.label){case 0:return e=a.map(function(t){return am(t)?l(t):t.detection}),(r=c)?[3,5]:s instanceof bt?[4,Cv(s,e)]:[3,2];case 1:return o=t.sent(),[3,4];case 2:return[4,wv(s,e)];case 3:o=t.sent(),t.label=4;case 4:r=o,t.label=5;case 5:return[4,u(n=r)];case 6:return i=t.sent(),n.forEach(function(t){return t instanceof bt&&t.dispose()}),[2,i]}})})}function Ug(e,r,o,i,a){return Lp(this,void 0,void 0,function(){var n=this;return Wp(this,function(t){return[2,zg([e],r,function(e){return Lp(n,void 0,void 0,function(){return Wp(this,function(t){return[2,o(e[0])]})})},i,a)]})})}var Vg=2,Gg=12;function Hg(t){var e=zv(t),n=e.extractWeights,r=e.getRemainingWeights,o=[],i=function(r,o){var u=Mv(r,o),c=Ov(r,o);function l(t,e){var n=Sn(r(t));return o.push({paramPath:e}),n}function h(t,e,n){return void 0===n&&(n=!1),{conv1:u(t[0],t[1],3,e+"/conv1"),prelu1_alpha:l(t[1],e+"/prelu1_alpha"),conv2:u(t[1],t[2],3,e+"/conv2"),prelu2_alpha:l(t[2],e+"/prelu2_alpha"),conv3:u(t[2],t[3],n?2:3,e+"/conv3"),prelu3_alpha:l(t[3],e+"/prelu3_alpha")}}return{extractPNetParams:function(){var t=h([3,10,16,32],"pnet"),e=u(32,2,1,"pnet/conv4_1"),n=u(32,4,1,"pnet/conv4_2");return Bp(Bp({},t),{conv4_1:e,conv4_2:n})},extractRNetParams:function(){var t=h([3,28,48,64],"rnet",!0),e=c(576,128,"rnet/fc1"),n=l(128,"rnet/prelu4_alpha"),r=c(128,2,"rnet/fc2_1"),o=c(128,4,"rnet/fc2_2");return Bp(Bp({},t),{fc1:e,prelu4_alpha:n,fc2_1:r,fc2_2:o})},extractONetParams:function(){var t=h([3,32,64,64],"onet"),e=u(64,128,2,"onet/conv4"),n=l(128,"onet/prelu4_alpha"),r=c(1152,256,"onet/fc1"),o=l(256,"onet/prelu5_alpha"),i=c(256,2,"onet/fc2_1"),a=c(256,4,"onet/fc2_2"),s=c(256,10,"onet/fc2_3");return Bp(Bp({},t),{conv4:e,prelu4_alpha:n,fc1:r,prelu5_alpha:o,fc2_1:i,fc2_2:a,fc2_3:s})}}}(n,o),a=i.extractPNetParams,s=i.extractRNetParams,u=i.extractONetParams,c=a(),l=s(),h=u();if(0!==r().length)throw new Error("weights remaing after extract: "+r().length);return{params:{pnet:c,rnet:l,onet:h},paramMappings:o}}function qg(t){var e=[],n=function(t,e){var n=Wv(t,e);function u(t){return{filters:n(t+"/weights",4,t+"/filters"),bias:n(t+"/bias",1)}}function c(t){return{weights:n(t+"/weights",2),bias:n(t+"/bias",1)}}function l(t){return n(t,1)}function h(t){return{conv1:u(t+"/conv1"),prelu1_alpha:l(t+"/prelu1_alpha"),conv2:u(t+"/conv2"),prelu2_alpha:l(t+"/prelu2_alpha"),conv3:u(t+"/conv3"),prelu3_alpha:l(t+"/prelu3_alpha")}}return{extractPNetParams:function(){var t=h("pnet"),e=u("pnet/conv4_1"),n=u("pnet/conv4_2");return Bp(Bp({},t),{conv4_1:e,conv4_2:n})},extractRNetParams:function(){var t=h("rnet"),e=c("rnet/fc1"),n=l("rnet/prelu4_alpha"),r=c("rnet/fc2_1"),o=c("rnet/fc2_2");return Bp(Bp({},t),{fc1:e,prelu4_alpha:n,fc2_1:r,fc2_2:o})},extractONetParams:function(){var t=h("onet"),e=u("onet/conv4"),n=l("onet/prelu4_alpha"),r=c("onet/fc1"),o=l("onet/prelu5_alpha"),i=c("onet/fc2_1"),a=c("onet/fc2_2"),s=c("onet/fc2_3");return Bp(Bp({},t),{conv4:e,prelu4_alpha:n,fc1:r,prelu5_alpha:o,fc2_1:i,fc2_2:a,fc2_3:s})}}}(t,e),r=n.extractPNetParams,o=n.extractRNetParams,i=n.extractONetParams,a=r(),s=o(),u=i();return Fv(t,e),{params:{pnet:a,rnet:s,onet:u},paramMappings:e}}function jg(t,e){var n=e[0],r=e[1];return{height:Math.floor(n*t),width:Math.floor(r*t)}}var Kg,Xg=(Pp(Yg,Kg=id),Yg);function Yg(t,e,n,r){return Kg.call(this,{left:t,top:e,right:n,bottom:r},!0)||this}function $g(t){return nn(function(){return Yu(tc(t,kn(127.5)),kn(.0078125))})}function Jg(t,e){return nn(function(){return Ou(dl(t),Yu(e,Zs(dl(Zs(t)))))})}function Qg(e,n,r){return void 0===r&&(r=!1),nn(function(){var t=Nv(e,n.conv1,"valid");return t=Jg(t,n.prelu1_alpha),t=Jg(t=Nv(t=Gc(t,r?[2,2]:[3,3],[2,2],"same"),n.conv2,"valid"),n.prelu2_alpha),t=Jg(t=Nv(t=r?t:Gc(t,[3,3],[2,2],"valid"),n.conv3,"valid"),n.prelu3_alpha)})}function Zg(s,t,u,c,l){l.stage1=[];var e=t.map(function(a){return nn(function(){var t={scale:a},e=function(o,i){return nn(function(){var t=jg(i,o.shape.slice(1)),e=t.height,n=t.width,r=$g(vh.resizeBilinear(o,[e,n]));return gl(r,[0,2,1,3])})}(s,a),n=Date.now(),r=function(r,o){return nn(function(){var t=Qg(r,o,!0),e=Nv(t,o.conv4_1,"valid"),n=yr(il(e,3),3);return{prob:so(tc(e,n),3),regions:Nv(t,o.conv4_2,"valid")}})}(e,c),o=r.prob,i=r.regions;return t.pnet=Date.now()-n,{scoresTensor:Br(Br(o,3)[1])[0],regionsTensor:Br(i)[0],scale:a,statsForScale:t}})}).map(function(t){var e=t.scoresTensor,n=t.regionsTensor,r=t.scale,o=t.statsForScale,i=function(t,o,i,e){for(var n=[],a=t.arraySync(),r=0;r<t.shape[0];r++)for(var s=0;s<t.shape[1];s++)a[r][s]>=e&&n.push(new rd(s,r));return n.map(function(t){var e=new ud(Math.round((t.y*Vg+1)/i),Math.round((t.x*Vg+1)/i),Math.round((t.y*Vg+Gg)/i),Math.round((t.x*Vg+Gg)/i)),n=a[t.y][t.x],r=o.arraySync();return{cell:e,score:n,region:new Xg(r[t.y][t.x][0],r[t.y][t.x][1],r[t.y][t.x][2],r[t.y][t.x][3])}})}(e,n,r,u);if(e.dispose(),n.dispose(),!i.length)return l.stage1.push(o),[];var a=Date.now(),s=gd(i.map(function(t){return t.cell}),i.map(function(t){return t.score}),.5);return o.nms=Date.now()-a,o.numBoxes=s.length,l.stage1.push(o),s.map(function(t){return i[t]})}).reduce(function(t,e){return t.concat(e)},[]),n=[],r=[];if(0<e.length){var o=Date.now(),i=gd(e.map(function(t){return t.cell}),e.map(function(t){return t.score}),.7);l.stage1_nms=Date.now()-o,r=i.map(function(t){return e[t].score}),n=i.map(function(t){return e[t]}).map(function(t){var e=t.cell,n=t.region;return new ud(e.left+n.left*e.width,e.top+n.top*e.height,e.right+n.right*e.width,e.bottom+n.bottom*e.height).toSquare().round()})}return{boxes:n,scores:r}}function ty(h,r,t){var a=t.width,s=t.height;return Lp(this,void 0,void 0,function(){var l,e,i,n=this;return Wp(this,function(t){switch(t.label){case 0:return l=nv(h),[4,Promise.all(r.map(function(c){return Lp(n,void 0,void 0,function(){var e,n,r,o,i,a,s,u;return Wp(this,function(t){return e=c.padAtBorders(h.height,h.width),n=e.y,r=e.ey,o=e.x,i=e.ex,a=o-1,s=n-1,u=l.getImageData(a,s,i-a,r-s),[2,tv.isNodejs()?dv(u):createImageBitmap(u)]})})}))];case 1:return e=t.sent(),i=[],e.forEach(function(t){var e=nv(pv({width:a,height:s}));e.drawImage(t,0,0,a,s);for(var n=e.getImageData(0,0,a,s).data,r=[],o=0;o<n.length;o+=4)r.push(n[o+2]),r.push(n[o+1]),r.push(n[o]);i.push(r)}),[2,i.map(function(t){return nn(function(){return $g(gl(Tn(t,[1,a,s,3]),[0,2,1,3]).toFloat())})})]}})})}function ey(v,m,g,y,x){return Lp(this,void 0,void 0,function(){var e,n,r,o,i,a,s,u,c,l,h,f,p,d;return Wp(this,function(t){switch(t.label){case 0:return e=Date.now(),[4,ty(v,m,{width:24,height:24})];case 1:return n=t.sent(),x.stage2_extractImagePatches=Date.now()-e,e=Date.now(),r=n.map(function(t){var e=function(a,s){return nn(function(){var t=Qg(a,s),e=Jg(Kv(Tr(t,[t.shape[0],s.fc1.weights.shape[0]]),s.fc1),s.prelu4_alpha),n=Kv(e,s.fc2_1),r=yr(il(n,1),1),o=so(tc(n,r),1),i=Kv(e,s.fc2_2);return{scores:Br(o,1)[1],regions:i}})}(t,y);return t.dispose(),e}),x.stage2_rnet=Date.now()-e,o=1<r.length?Vn(r.map(function(t){return t.scores})):r[0].scores,s=(a=Array).from,[4,o.data()];case 2:return i=s.apply(a,[t.sent()]),o.dispose(),u=i.map(function(t,e){return{score:t,idx:e}}).filter(function(t){return t.score>g}).map(function(t){return t.idx}),c=u.map(function(t){return m[t]}),l=u.map(function(t){return i[t]}),h=[],f=[],0<c.length&&(e=Date.now(),p=gd(c,l,.7),x.stage2_nms=Date.now()-e,d=p.map(function(t){var e=r[u[t]].regions.arraySync();return new Xg(e[0][0],e[0][1],e[0][2],e[0][3])}),f=p.map(function(t){return l[t]}),h=p.map(function(t,e){return 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o=s.apply(a,[t.sent()]),r.dispose(),u=o.map(function(t,e){return{score:t,idx:e}}).filter(function(t){return t.score>y}).map(function(t){return t.idx}),c=u.map(function(t){var e=i[t].regions.arraySync();return new Xg(e[0][0],e[0][1],e[0][2],e[0][3])}),l=u.map(function(t,e){return g[t].calibrate(c[e])}),h=u.map(function(t){return o[t]}),f=[],p=[],d=[],0<l.length&&(e=Date.now(),v=gd(l,h,.7,!1),b.stage3_nms=Date.now()-e,f=v.map(function(t){return l[t]}),p=v.map(function(t){return h[t]}),d=v.map(function(r,o){return Array(5).fill(0).map(function(t,e){var n=i[r].points.arraySync();return new rd(n[0][e]*(f[o].width+1)+f[o].left,n[0][e+5]*(f[o].height+1)+f[o].top)})})),i.forEach(function(t){t.regions.dispose(),t.scores.dispose(),t.points.dispose()}),[2,{boxes:f,scores:p,points:d}]}})})}var ry,oy=(Pp(iy,ry=kv),iy.prototype.load=function(e){return Lp(this,void 0,void 0,function(){return Wp(this,function(t){return console.warn("mtcnn is deprecated and will be removed 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void 0===n&&(n={}),Lp(this,void 0,void 0,function(){return Wp(this,function(t){switch(t.label){case 0:return console.warn("allFacesMtcnn is deprecated and will be removed soon, use the high level api instead"),[4,wx(e,new Jm(n)).withFaceLandmarks().withFaceDescriptors()];case 1:return[2,t.sent()]}})})},c.allFacesSsdMobilenetv1=Cx,c.allFacesTinyYolov2=function(e,n){return void 0===n&&(n={}),Lp(this,void 0,void 0,function(){return Wp(this,function(t){switch(t.label){case 0:return console.warn("allFacesTinyYolov2 is deprecated and will be removed soon, use the high level api instead"),[4,wx(e,new kg(n)).withFaceLandmarks().withFaceDescriptors()];case 1:return[2,t.sent()]}})})},c.awaitMediaLoaded=lv,c.bufferToImage=hv,c.computeFaceDescriptor=function(t){return vy.faceRecognitionNet.computeFaceDescriptor(t)},c.createCanvas=pv,c.createCanvasFromMedia=dv,c.createFaceDetectionNet=function(t){return fg(t)},c.createFaceRecognitionNet=function(t){var e=new jm;return e.extractWeights(t),e},c.createMtcnn=function(t){var e=new oy;return e.extractWeights(t),e},c.createSsdMobilenetv1=fg,c.createTinyFaceDetector=function(t){var e=new cy;return e.extractWeights(t),e},c.createTinyYolov2=function(t,e){void 0===e&&(e=!0);var n=new Fg(e);return n.extractWeights(t),n},c.detectAllFaces=wx,c.detectFaceLandmarks=fy,c.detectFaceLandmarksTiny=function(t){return vy.faceLandmark68TinyNet.detectLandmarks(t)},c.detectLandmarks=yy,c.detectSingleFace=function(t,e){return void 0===e&&(e=new sg),new xx(t,e)},c.draw=hm,c.env=tv,c.euclideanDistance=_x,c.extendWithAge=Ym,c.extendWithFaceDescriptor=Xm,c.extendWithFaceDetection=Hd,c.extendWithFaceExpressions=im,c.extendWithFaceLandmarks=sm,c.extendWithGender=$m,c.extractFaceTensors=Cv,c.extractFaces=wv,c.fetchImage=function(r){return Lp(this,void 0,void 0,function(){var e,n;return Wp(this,function(t){switch(t.label){case 0:return[4,Ev(r)];case 1:return[4,(e=t.sent()).blob()];case 2:if(!(n=t.sent()).type.startsWith("image/"))throw new Error("fetchImage - expected blob type to be of type image/*, instead have: "+n.type+", for url: "+e.url);return[2,hv(n)]}})})},c.fetchJson=_v,c.fetchNetWeights=function(n){return Lp(this,void 0,void 0,function(){var e;return Wp(this,function(t){switch(t.label){case 0:return e=Float32Array.bind,[4,Ev(n)];case 1:return[4,t.sent().arrayBuffer()];case 2:return[2,new(e.apply(Float32Array,[void 0,t.sent()]))]}})})},c.fetchOrThrow=Ev,c.getContext2dOrThrow=nv,c.getMediaDimensions=fv,c.imageTensorToCanvas=vv,c.imageToSquare=gv,c.inverseSigmoid=function(t){return Math.log(t/(1-t))},c.iou=vd,c.isMediaElement=mv,c.isMediaLoaded=cv,c.isWithAge=function(t){return"number"==typeof t.age},c.isWithFaceDetection=Gd,c.isWithFaceExpressions=om,c.isWithFaceLandmarks=am,c.isWithGender=function(t){return(t.gender===c.Gender.MALE||t.gender===c.Gender.FEMALE)&&ed(t.genderProbability)},c.loadAgeGenderModel=function(t){return vy.ageGenderNet.load(t)},c.loadFaceDetectionModel=my,c.loadFaceExpressionModel=function(t){return vy.faceExpressionNet.load(t)},c.loadFaceLandmarkModel=function(t){return vy.faceLandmark68Net.load(t)},c.loadFaceLandmarkTinyModel=function(t){return vy.faceLandmark68TinyNet.load(t)},c.loadFaceRecognitionModel=function(t){return vy.faceRecognitionNet.load(t)},c.loadMtcnnModel=function(t){return vy.mtcnn.load(t)},c.loadSsdMobilenetv1Model=py,c.loadTinyFaceDetectorModel=function(t){return vy.tinyFaceDetector.load(t)},c.loadTinyYolov2Model=function(t){return vy.tinyYolov2.load(t)},c.loadWeightMap=Rv,c.locateFaces=gy,c.matchDimensions=function(t,e,n){void 0===n&&(n=!1);var r=n?fv(e):e,o=r.width,i=r.height;return{width:t.width=o,height:t.height=i}},c.minBbox=md,c.mtcnn=function(t,e){return vy.mtcnn.forward(t,e)},c.nets=vy,c.nonMaxSuppression=gd,c.normalize=yd,c.padToSquare=xd,c.predictAgeAndGender=function(t){return vy.ageGenderNet.predictAgeAndGender(t)},c.recognizeFaceExpressions=function(t){return vy.faceExpressionNet.predictExpressions(t)},c.resizeResults=function e(t,n){var r=new Up(n.width,n.height),o=r.width,i=r.height;if(o<=0||i<=0)throw new Error("resizeResults - invalid dimensions: "+JSON.stringify({width:o,height:i}));if(Array.isArray(t))return t.map(function(t){return e(t,{width:o,height:i})});if(am(t)){var a=t.detection.forSize(o,i),s=t.unshiftedLandmarks.forSize(a.box.width,a.box.height);return sm(Hd(t,a),s)}return Gd(t)?Hd(t,t.detection.forSize(o,i)):t instanceof _d||t instanceof pd?t.forSize(o,i):t},c.resolveInput=ev,c.shuffleArray=function(t){for(var e=t.slice(),n=e.length-1;0<n;n--){var r=Math.floor(Math.random()*(n+1)),o=e[n];e[n]=e[r],e[r]=o}return e},c.sigmoid=bd,c.ssdMobilenetv1=hy,c.tf=Fp,c.tinyFaceDetector=function(t,e){return vy.tinyFaceDetector.locateFaces(t,e)},c.tinyYolov2=function(t,e){return vy.tinyYolov2.locateFaces(t,e)},c.toNetInput=bv,c.utils=nd,c.validateConfig=wg,Object.defineProperty(c,"__esModule",{value:!0})});
diff --git a/examples/examples-browser/package.json b/examples/examples-browser/package.json
index 975b0fe0..896c7532 100644
--- a/examples/examples-browser/package.json
+++ b/examples/examples-browser/package.json
@@ -5,7 +5,7 @@
   "author": "justadudewhohacks",
   "license": "MIT",
   "dependencies": {
-    "express": "^4.16.4",
-    "request": "^2.88.0"
+    "express": "^4.17.1",
+    "request": "^2.88.2"
   }
 }
diff --git a/examples/examples-browser/public/js/imageSelectionControls.js b/examples/examples-browser/public/js/imageSelectionControls.js
index aa67b890..5777fda5 100644
--- a/examples/examples-browser/public/js/imageSelectionControls.js
+++ b/examples/examples-browser/public/js/imageSelectionControls.js
@@ -10,6 +10,13 @@ async function loadImageFromUrl(url) {
   updateResults()
 }
 
+async function loadImageFromUpload() {
+    const imgFile = $('#queryImgUploadInput').get(0).files[0]
+    const img = await faceapi.bufferToImage(imgFile)
+    $('#inputImg').get(0).src = img.src
+    updateResults()
+}
+
 function renderImageSelectList(selectListId, onChange, initialValue, withFaceExpressionImages) {
   let images = [1, 2, 3, 4, 5].map(idx => `bbt${idx}.jpg`)
 
diff --git a/examples/examples-browser/public/styles.css b/examples/examples-browser/public/styles.css
index d69d3fd4..669837d1 100644
--- a/examples/examples-browser/public/styles.css
+++ b/examples/examples-browser/public/styles.css
@@ -73,4 +73,12 @@
 
 #facesContainer canvas {
   margin: 10px;
+}
+
+input[type="file"]::-webkit-file-upload-button {
+    background: #26a69a;
+    border: 1px solid gray;
+    cursor: pointer;
+    color: #fff;
+    border-radius: .2em;
 }
\ No newline at end of file
diff --git a/examples/examples-browser/views/ageAndGenderRecognition.html b/examples/examples-browser/views/ageAndGenderRecognition.html
index da9f9c42..1747bed5 100644
--- a/examples/examples-browser/views/ageAndGenderRecognition.html
+++ b/examples/examples-browser/views/ageAndGenderRecognition.html
@@ -35,6 +35,7 @@
       >
         Ok
       </button>
+      <input id="queryImgUploadInput" type="file" class="waves-effect btn bold" onchange="loadImageFromUpload()" accept=".jpg, .jpeg, .png">
       <!-- image_selection_control -->
     </div>
 
diff --git a/examples/examples-browser/views/bbtFaceRecognition.html b/examples/examples-browser/views/bbtFaceRecognition.html
index 5797a4a8..8eba5f8f 100644
--- a/examples/examples-browser/views/bbtFaceRecognition.html
+++ b/examples/examples-browser/views/bbtFaceRecognition.html
@@ -48,6 +48,7 @@
         >
           Ok
         </button>
+        <input id="queryImgUploadInput" type="file" class="waves-effect btn bold" onchange="loadImageFromUpload()" accept=".jpg, .jpeg, .png">
       <div id="image_selection_control"></div>
       <!-- image_selection_control -->
 
diff --git a/examples/examples-browser/views/faceDetection.html b/examples/examples-browser/views/faceDetection.html
index 265a2ef1..2eafbd14 100644
--- a/examples/examples-browser/views/faceDetection.html
+++ b/examples/examples-browser/views/faceDetection.html
@@ -35,6 +35,7 @@
       >
         Ok
       </button>
+      <input id="queryImgUploadInput" type="file" class="waves-effect btn bold" onchange="loadImageFromUpload()" accept=".jpg, .jpeg, .png">
       <!-- image_selection_control -->
     </div>
 
diff --git a/examples/examples-browser/views/faceExpressionRecognition.html b/examples/examples-browser/views/faceExpressionRecognition.html
index cdca827f..98f4cf78 100644
--- a/examples/examples-browser/views/faceExpressionRecognition.html
+++ b/examples/examples-browser/views/faceExpressionRecognition.html
@@ -35,6 +35,7 @@
       >
         Ok
       </button>
+      <input id="queryImgUploadInput" type="file" class="waves-effect btn bold" onchange="loadImageFromUpload()" accept=".jpg, .jpeg, .png">
       <!-- image_selection_control -->
     </div>
 
diff --git a/examples/examples-browser/views/faceExtraction.html b/examples/examples-browser/views/faceExtraction.html
index a632a823..a3a3a436 100644
--- a/examples/examples-browser/views/faceExtraction.html
+++ b/examples/examples-browser/views/faceExtraction.html
@@ -45,6 +45,7 @@
       >
         Ok
       </button>
+      <input id="queryImgUploadInput" type="file" class="waves-effect btn bold" onchange="loadImageFromUpload()" accept=".jpg, .jpeg, .png">
       <!-- image_selection_control -->
     </div>
 
diff --git a/examples/examples-browser/views/faceLandmarkDetection.html b/examples/examples-browser/views/faceLandmarkDetection.html
index e5383fa7..955f31ca 100644
--- a/examples/examples-browser/views/faceLandmarkDetection.html
+++ b/examples/examples-browser/views/faceLandmarkDetection.html
@@ -35,6 +35,7 @@
       >
         Ok
       </button>
+      <input id="queryImgUploadInput" type="file" class="waves-effect btn bold" onchange="loadImageFromUpload()" accept=".jpg, .jpeg, .png">
       <!-- image_selection_control -->
     </div>
 
diff --git a/examples/examples-nodejs/package.json b/examples/examples-nodejs/package.json
index ac7fa73c..5acbeef9 100644
--- a/examples/examples-nodejs/package.json
+++ b/examples/examples-nodejs/package.json
@@ -2,8 +2,6 @@
   "author": "justadudewhohacks",
   "license": "MIT",
   "dependencies": {
-    "@tensorflow/tfjs-node": "1.4.0",
-    "canvas": "^2.6.0",
     "face-api.js": "../../"
   }
 }
diff --git a/package-lock.json b/package-lock.json
index 690bd427..b597c79f 100644
--- a/package-lock.json
+++ b/package-lock.json
@@ -1,6 +1,6 @@
 {
   "name": "face-api.js",
-  "version": "0.22.0",
+  "version": "0.22.2",
   "lockfileVersion": 1,
   "requires": true,
   "dependencies": {
@@ -13,6 +13,206 @@
         "@babel/highlight": "^7.0.0"
       }
     },
+    "@babel/core": {
+      "version": "7.9.0",
+      "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.9.0.tgz",
+      "integrity": "sha512-kWc7L0fw1xwvI0zi8OKVBuxRVefwGOrKSQMvrQ3dW+bIIavBY3/NpXmpjMy7bQnLgwgzWQZ8TlM57YHpHNHz4w==",
+      "dev": true,
+      "requires": {
+        "@babel/code-frame": "^7.8.3",
+        "@babel/generator": "^7.9.0",
+        "@babel/helper-module-transforms": "^7.9.0",
+        "@babel/helpers": "^7.9.0",
+        "@babel/parser": "^7.9.0",
+        "@babel/template": "^7.8.6",
+        "@babel/traverse": "^7.9.0",
+        "@babel/types": "^7.9.0",
+        "convert-source-map": "^1.7.0",
+        "debug": "^4.1.0",
+        "gensync": "^1.0.0-beta.1",
+        "json5": "^2.1.2",
+        "lodash": "^4.17.13",
+        "resolve": "^1.3.2",
+        "semver": "^5.4.1",
+        "source-map": "^0.5.0"
+      },
+      "dependencies": {
+        "@babel/code-frame": {
+          "version": "7.8.3",
+          "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.8.3.tgz",
+          "integrity": "sha512-a9gxpmdXtZEInkCSHUJDLHZVBgb1QS0jhss4cPP93EW7s+uC5bikET2twEF3KV+7rDblJcmNvTR7VJejqd2C2g==",
+          "dev": true,
+          "requires": {
+            "@babel/highlight": "^7.8.3"
+          }
+        },
+        "@babel/highlight": {
+          "version": "7.9.0",
+          "resolved": "https://registry.npmjs.org/@babel/highlight/-/highlight-7.9.0.tgz",
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+          "requires": {
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+            "chalk": "^2.0.0",
+            "js-tokens": "^4.0.0"
+          }
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+        "debug": {
+          "version": "4.1.1",
+          "resolved": "https://registry.npmjs.org/debug/-/debug-4.1.1.tgz",
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+          "dev": true,
+          "requires": {
+            "ms": "^2.1.1"
+          }
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+        "resolve": {
+          "version": "1.15.1",
+          "resolved": "https://registry.npmjs.org/resolve/-/resolve-1.15.1.tgz",
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+          "requires": {
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+          }
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+          "version": "0.5.7",
+          "resolved": "https://registry.npmjs.org/source-map/-/source-map-0.5.7.tgz",
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@@ -3742,26 +3515,6 @@
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-      "integrity": "sha512-FJ6b7EgdKxxbDxc79cOlok6Afd++TTs5szo+zJTUyow3ycrRfJVE2pq3vcN53XexvKZu/DJMDfeI/qMiZTrjTw==",
-      "dev": true,
-      "requires": {
-        "define-properties": "^1.1.3",
-        "function-bind": "^1.1.1"
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-    "string.prototype.trimright": {
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-      "resolved": "https://registry.npmjs.org/string.prototype.trimright/-/string.prototype.trimright-2.1.0.tgz",
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-      "dev": true,
-      "requires": {
-        "define-properties": "^1.1.3",
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       "resolved": "https://registry.npmjs.org/string_decoder/-/string_decoder-1.1.1.tgz",
@@ -3780,24 +3533,6 @@
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-    "strip-bom": {
-      "version": "2.0.0",
-      "resolved": "https://registry.npmjs.org/strip-bom/-/strip-bom-2.0.0.tgz",
-      "integrity": "sha1-YhmoVhZSBJHzV4i9vxRHqZx+aw4=",
-      "dev": true,
-      "requires": {
-        "is-utf8": "^0.2.0"
-      }
-    },
-    "strip-indent": {
-      "version": "1.0.1",
-      "resolved": "https://registry.npmjs.org/strip-indent/-/strip-indent-1.0.1.tgz",
-      "integrity": "sha1-DHlipq3vp7vUrDZkYKY4VSrhoKI=",
-      "dev": true,
-      "requires": {
-        "get-stdin": "^4.0.1"
-      }
-    },
     "strip-json-comments": {
       "version": "2.0.1",
       "resolved": "https://registry.npmjs.org/strip-json-comments/-/strip-json-comments-2.0.1.tgz",
@@ -3805,12 +3540,12 @@
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-      "version": "3.2.3",
-      "resolved": "https://registry.npmjs.org/supports-color/-/supports-color-3.2.3.tgz",
-      "integrity": "sha1-ZawFBLOVQXHYpklGsq48u4pfVPY=",
+      "version": "7.1.0",
+      "resolved": "https://registry.npmjs.org/supports-color/-/supports-color-7.1.0.tgz",
+      "integrity": "sha512-oRSIpR8pxT1Wr2FquTNnGet79b3BWljqOuoW/h4oBhxJ/HUbX5nX6JSruTkvXDCFMwDPvsaTTbvMLKZWSy0R5g==",
       "dev": true,
       "requires": {
-        "has-flag": "^1.0.0"
+        "has-flag": "^4.0.0"
       }
     },
     "tar": {
@@ -3828,16 +3563,6 @@
         "yallist": "^3.0.3"
       }
     },
-    "through2": {
-      "version": "3.0.0",
-      "resolved": "https://registry.npmjs.org/through2/-/through2-3.0.0.tgz",
-      "integrity": "sha512-8B+sevlqP4OiCjonI1Zw03Sf8PuV1eRsYQgLad5eonILOdyeRsY27A/2Ze8IlvlMvq31OH+3fz/styI7Ya62yQ==",
-      "dev": true,
-      "requires": {
-        "readable-stream": "2 || 3",
-        "xtend": "~4.0.1"
-      }
-    },
     "timers-browserify": {
       "version": "2.0.11",
       "resolved": "https://registry.npmjs.org/timers-browserify/-/timers-browserify-2.0.11.tgz",
@@ -3862,6 +3587,12 @@
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       "dev": true
     },
+    "to-fast-properties": {
+      "version": "2.0.0",
+      "resolved": "https://registry.npmjs.org/to-fast-properties/-/to-fast-properties-2.0.0.tgz",
+      "integrity": "sha1-3F5pjL0HkmW8c+A3doGk5Og/YW4=",
+      "dev": true
+    },
     "to-regex-range": {
       "version": "5.0.1",
       "resolved": "https://registry.npmjs.org/to-regex-range/-/to-regex-range-5.0.1.tgz",
@@ -3877,29 +3608,23 @@
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       "dev": true
     },
-    "trim-newlines": {
-      "version": "1.0.0",
-      "resolved": "https://registry.npmjs.org/trim-newlines/-/trim-newlines-1.0.0.tgz",
-      "integrity": "sha1-WIeWa7WCpFA6QetST301ARgVphM=",
-      "dev": true
-    },
     "ts-node": {
-      "version": "8.5.4",
-      "resolved": "https://registry.npmjs.org/ts-node/-/ts-node-8.5.4.tgz",
-      "integrity": "sha512-izbVCRV68EasEPQ8MSIGBNK9dc/4sYJJKYA+IarMQct1RtEot6Xp0bXuClsbUSnKpg50ho+aOAx8en5c+y4OFw==",
+      "version": "8.7.0",
+      "resolved": "https://registry.npmjs.org/ts-node/-/ts-node-8.7.0.tgz",
+      "integrity": "sha512-s659CsHrsxaRVDEleuOkGvbsA0rWHtszUNEt1r0CgAFN5ZZTQtDzpsluS7W5pOGJIa1xZE8R/zK4dEs+ldFezg==",
       "dev": true,
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         "arg": "^4.1.0",
         "diff": "^4.0.1",
         "make-error": "^1.1.1",
         "source-map-support": "^0.5.6",
-        "yn": "^3.0.0"
+        "yn": "3.1.1"
       }
     },
     "tslib": {
-      "version": "1.10.0",
-      "resolved": "https://registry.npmjs.org/tslib/-/tslib-1.10.0.tgz",
-      "integrity": "sha512-qOebF53frne81cf0S9B41ByenJ3/IuH8yJKngAX35CmiZySA0khhkovshKK+jGCaMnVomla7gVlIcc3EvKPbTQ=="
+      "version": "1.11.1",
+      "resolved": "https://registry.npmjs.org/tslib/-/tslib-1.11.1.tgz",
+      "integrity": "sha512-aZW88SY8kQbU7gpV19lN24LtXh/yD4ZZg6qieAJDDg+YBsJcSmLGK9QpnUjAKVG/xefmvJGd1WUmfpT/g6AJGA=="
     },
     "tty-browserify": {
       "version": "0.0.1",
@@ -3907,15 +3632,6 @@
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       "dev": true
     },
-    "type-check": {
-      "version": "0.3.2",
-      "resolved": "https://registry.npmjs.org/type-check/-/type-check-0.3.2.tgz",
-      "integrity": "sha1-WITKtRLPHTVeP7eE8wgEsrUg23I=",
-      "dev": true,
-      "requires": {
-        "prelude-ls": "~1.1.2"
-      }
-    },
     "type-is": {
       "version": "1.6.18",
       "resolved": "https://registry.npmjs.org/type-is/-/type-is-1.6.18.tgz",
@@ -3927,9 +3643,9 @@
       }
     },
     "typescript": {
-      "version": "3.7.3",
-      "resolved": "https://registry.npmjs.org/typescript/-/typescript-3.7.3.tgz",
-      "integrity": "sha512-Mcr/Qk7hXqFBXMN7p7Lusj1ktCBydylfQM/FZCk5glCNQJrCUKPkMHdo9R0MTFWsC/4kPFvDS0fDPvukfCkFsw==",
+      "version": "3.8.3",
+      "resolved": "https://registry.npmjs.org/typescript/-/typescript-3.8.3.tgz",
+      "integrity": "sha512-MYlEfn5VrLNsgudQTVJeNaQFUAI7DkhnOjdpAp4T+ku1TfQClewlbSuTVHiA+8skNBgaf02TL/kLOvig4y3G8w==",
       "dev": true
     },
     "uglify-js": {
@@ -3989,15 +3705,14 @@
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     },
     "util": {
-      "version": "0.12.1",
-      "resolved": "https://registry.npmjs.org/util/-/util-0.12.1.tgz",
-      "integrity": "sha512-MREAtYOp+GTt9/+kwf00IYoHZyjM8VU4aVrkzUlejyqaIjd2GztVl5V9hGXKlvBKE3gENn/FMfHE5v6hElXGcQ==",
+      "version": "0.12.2",
+      "resolved": "https://registry.npmjs.org/util/-/util-0.12.2.tgz",
+      "integrity": "sha512-XE+MkWQvglYa+IOfBt5UFG93EmncEMP23UqpgDvVZVFBPxwmkK10QRp6pgU4xICPnWRf/t0zPv4noYSUq9gqUQ==",
       "dev": true,
       "requires": {
         "inherits": "^2.0.3",
         "is-arguments": "^1.0.4",
         "is-generator-function": "^1.0.7",
-        "object.entries": "^1.1.0",
         "safe-buffer": "^5.1.2"
       }
     },
@@ -4013,20 +3728,10 @@
       "integrity": "sha1-n5VxD1CiZ5R7LMwSR0HBAoQn5xM=",
       "dev": true
     },
-    "validate-npm-package-license": {
-      "version": "3.0.4",
-      "resolved": "https://registry.npmjs.org/validate-npm-package-license/-/validate-npm-package-license-3.0.4.tgz",
-      "integrity": "sha512-DpKm2Ui/xN7/HQKCtpZxoRWBhZ9Z0kqtygG8XCgNQ8ZlDnxuQmWhj566j8fN4Cu3/JmbhsDo7fcAJq4s9h27Ew==",
-      "dev": true,
-      "requires": {
-        "spdx-correct": "^3.0.0",
-        "spdx-expression-parse": "^3.0.0"
-      }
-    },
     "vm-browserify": {
-      "version": "1.1.0",
-      "resolved": "https://registry.npmjs.org/vm-browserify/-/vm-browserify-1.1.0.tgz",
-      "integrity": "sha512-iq+S7vZJE60yejDYM0ek6zg308+UZsdtPExWP9VZoCFCz1zkJoXFnAX7aZfd/ZwrkidzdUZL0C/ryW+JwAiIGw==",
+      "version": "1.1.2",
+      "resolved": "https://registry.npmjs.org/vm-browserify/-/vm-browserify-1.1.2.tgz",
+      "integrity": "sha512-2ham8XPWTONajOR0ohOKOHXkm3+gaBmGut3SRuu75xLd/RRaY6vqgh8NBYYk7+RW3u5AtzPQZG8F10LHkl0lAQ==",
       "dev": true
     },
     "void-elements": {
diff --git a/package.json b/package.json
index 8eaf4269..af7c1675 100644
--- a/package.json
+++ b/package.json
@@ -1,6 +1,6 @@
 {
   "name": "face-api.js",
-  "version": "0.22.0",
+  "version": "0.22.2",
   "description": "JavaScript API for face detection and face recognition in the browser with tensorflow.js",
   "module": "./build/es6/index.js",
   "main": "./build/commonjs/index.js",
@@ -33,26 +33,26 @@
   "author": "justadudewhohacks",
   "license": "MIT",
   "dependencies": {
-    "@tensorflow/tfjs-core": "1.4.0",
-    "tslib": "^1.10.0"
+    "@tensorflow/tfjs-core": "1.7.0",
+    "tslib": "^1.11.1"
   },
   "devDependencies": {
-    "@tensorflow/tfjs-node": "1.4.0",
-    "@types/jasmine": "^3.5.0",
-    "@types/node": "^12.12.17",
-    "canvas": "2.6.0",
+    "@tensorflow/tfjs-node": "1.7.0",
+    "@types/jasmine": "^3.5.9",
+    "@types/node": "^13.9.2",
+    "canvas": "2.6.1",
     "jasmine": "^3.5.0",
     "jasmine-core": "^3.5.0",
     "karma": "^4.4.1",
     "karma-chrome-launcher": "^3.1.0",
-    "karma-jasmine": "^2.0.1",
-    "karma-typescript": "^4.1.1",
-    "rollup": "^1.27.13",
+    "karma-jasmine": "^3.1.1",
+    "karma-typescript": "^5.0.1",
+    "rollup": "^2.1.0",
     "rollup-plugin-commonjs": "^10.1.0",
     "rollup-plugin-node-resolve": "^5.2.0",
-    "rollup-plugin-typescript2": "^0.25.3",
+    "rollup-plugin-typescript2": "^0.26.0",
     "rollup-plugin-uglify": "^6.0.4",
-    "ts-node": "^8.5.4",
-    "typescript": "^3.7.3"
+    "ts-node": "^8.7.0",
+    "typescript": "^3.8.3"
   }
 }
diff --git a/src/env/index.ts b/src/env/index.ts
index dcb4e894..832f97cf 100644
--- a/src/env/index.ts
+++ b/src/env/index.ts
@@ -22,10 +22,10 @@ function initialize() {
   // check for isBrowser() first to prevent electron renderer process
   // to be initialized with wrong environment due to isNodejs() returning true
   if (isBrowser()) {
-    setEnv(createBrowserEnv())
+    return setEnv(createBrowserEnv())
   }
   if (isNodejs()) {
-    setEnv(createNodejsEnv())
+    return setEnv(createNodejsEnv())
   }
 }