Generate Python docs from pytorch/pytorch@f628f2e

Author: pytorchbot

docs/master/_dynamo.html

@@ -237,7 +237,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.14.0a0+gita43e09c ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.14.0a0+gitf628f2e ) &#x25BC</a>
     </div>
 
 
@@ -301,14 +301,14 @@
 </ul>
 <p class="caption" role="heading"><span class="caption-text">torch.compile</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/custom-backends.html">Custom Backends</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/deep-dive.html">TorchDynamo Deeper Dive</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/faq.html">Frequently Asked Questions</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/index.html">TorchDynamo Overview</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/installation.html">Installing TorchDynamo</a></li>
 <li class="toctree-l1"><a class="reference internal" href="dynamo/get-started.html">Getting Started</a></li>
 <li class="toctree-l1"><a class="reference internal" href="dynamo/guards-overview.html">Guards Overview</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/index.html">TorchDynamo Documentation</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/installation.html">Installing TorchDynamo</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/custom-backends.html">Custom Backends</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/deep-dive.html">TorchDynamo Deeper Dive</a></li>
 <li class="toctree-l1"><a class="reference internal" href="dynamo/troubleshooting.html">TorchDynamo Troubleshooting</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/faq.html">Frequently Asked Questions</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Language Bindings</span></p>
 <ul>

docs/master/_images/RReLU.png

@@ -235,7 +235,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.14.0a0+gita43e09c ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.14.0a0+gitf628f2e ) &#x25BC</a>
     </div>
 
 
@@ -299,14 +299,14 @@
 </ul>
 <p class="caption" role="heading"><span class="caption-text">torch.compile</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/custom-backends.html">Custom Backends</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/deep-dive.html">TorchDynamo Deeper Dive</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/faq.html">Frequently Asked Questions</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/index.html">TorchDynamo Overview</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/installation.html">Installing TorchDynamo</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../dynamo/get-started.html">Getting Started</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../dynamo/guards-overview.html">Guards Overview</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/index.html">TorchDynamo Documentation</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/installation.html">Installing TorchDynamo</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/custom-backends.html">Custom Backends</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/deep-dive.html">TorchDynamo Deeper Dive</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../dynamo/troubleshooting.html">TorchDynamo Troubleshooting</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/faq.html">Frequently Asked Questions</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Language Bindings</span></p>
 <ul>

docs/master/_modules/index.html

@@ -235,7 +235,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.14.0a0+gita43e09c ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.14.0a0+gitf628f2e ) &#x25BC</a>
     </div>
 
 
@@ -299,14 +299,14 @@
 </ul>
 <p class="caption" role="heading"><span class="caption-text">torch.compile</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/custom-backends.html">Custom Backends</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/deep-dive.html">TorchDynamo Deeper Dive</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/faq.html">Frequently Asked Questions</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/index.html">TorchDynamo Overview</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/installation.html">Installing TorchDynamo</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../dynamo/get-started.html">Getting Started</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../dynamo/guards-overview.html">Guards Overview</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/index.html">TorchDynamo Documentation</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../dynamo/installation.html">Installing TorchDynamo</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/custom-backends.html">Custom Backends</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/deep-dive.html">TorchDynamo Deeper Dive</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../dynamo/troubleshooting.html">TorchDynamo Troubleshooting</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../dynamo/faq.html">Frequently Asked Questions</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Language Bindings</span></p>
 <ul>
@@ -490,7 +490,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 
 <span class="kn">from</span> <span class="nn">._six</span> <span class="kn">import</span> <span class="n">string_classes</span> <span class="k">as</span> <span class="n">_string_classes</span>
 
-<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Set</span><span class="p">,</span> <span class="n">Type</span><span class="p">,</span> <span class="n">TYPE_CHECKING</span><span class="p">,</span> <span class="n">Union</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">Any</span>
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Set</span><span class="p">,</span> <span class="n">Type</span><span class="p">,</span> <span class="n">TYPE_CHECKING</span><span class="p">,</span> <span class="n">Union</span>
 <span class="kn">import</span> <span class="nn">builtins</span>
 
 <span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span>
@@ -509,6 +509,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
     <span class="s1">&#39;set_deterministic_debug_mode&#39;</span><span class="p">,</span> <span class="s1">&#39;get_deterministic_debug_mode&#39;</span><span class="p">,</span>
     <span class="s1">&#39;set_float32_matmul_precision&#39;</span><span class="p">,</span> <span class="s1">&#39;get_float32_matmul_precision&#39;</span><span class="p">,</span>
     <span class="s1">&#39;set_warn_always&#39;</span><span class="p">,</span> <span class="s1">&#39;is_warn_always_enabled&#39;</span><span class="p">,</span> <span class="s1">&#39;SymInt&#39;</span><span class="p">,</span> <span class="s1">&#39;SymFloat&#39;</span><span class="p">,</span>
+    <span class="s1">&#39;compile&#39;</span><span class="p">,</span>
 <span class="p">]</span>
 
 <span class="c1">################################################################################</span>
@@ -1573,6 +1574,74 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
     <span class="n">lstsq</span><span class="p">,</span>
 <span class="p">)</span>
 
+<div class="viewcode-block" id="compile"><a class="viewcode-back" href="../generated/torch.compile.html#torch.compile">[docs]</a><span class="k">def</span> <span class="nf">compile</span><span class="p">(</span><span class="n">model</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span>
+            <span class="n">fullgraph</span><span class="p">:</span> <span class="n">builtins</span><span class="o">.</span><span class="n">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+            <span class="n">dynamic</span><span class="p">:</span> <span class="n">builtins</span><span class="o">.</span><span class="n">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+            <span class="n">backend</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Callable</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;inductor&quot;</span><span class="p">,</span>
+            <span class="n">mode</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="kc">None</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+            <span class="n">passes</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">builtins</span><span class="o">.</span><span class="n">int</span><span class="p">,</span> <span class="n">builtins</span><span class="o">.</span><span class="n">bool</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+            <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Callable</span><span class="p">:</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Optimizes given model/function using Dynamo and specified backend</span>
+
+<span class="sd">    Args:</span>
+<span class="sd">       model (Callable): Module/function to optimize</span>
+<span class="sd">       fullgraph (bool): Whether it is ok to break model into several subgraphs</span>
+<span class="sd">       dynamic (bool): Use dynamic shape tracing</span>
+<span class="sd">       backend (str or Callable): backend to be used</span>
+<span class="sd">       mode (str): Can be either &quot;default&quot;, &quot;reduce-overhead&quot; or &quot;max-autotune&quot;</span>
+<span class="sd">       passes (dict): A dictionary of passes to the backend. Passes currently recognized by inductor backend:</span>
+<span class="sd">                       - static-memory</span>
+<span class="sd">                       - matmul-tune</span>
+<span class="sd">                       - matmul-padding</span>
+<span class="sd">                       - triton-autotune</span>
+<span class="sd">                       - triton-bmm</span>
+<span class="sd">                       - triton-mm</span>
+<span class="sd">                       - triton-convolution</span>
+<span class="sd">                       - rematerialize-threshold</span>
+<span class="sd">                       - rematerialize-acc-threshold</span>
+
+<span class="sd">    Example::</span>
+
+<span class="sd">        @torch.compile(passes={&quot;matmul-padding&quot;: True}, fullgraph=True)</span>
+<span class="sd">        def foo(x):</span>
+<span class="sd">            return torch.sin(x) + torch.cos(x)</span>
+
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="c1"># Decorator mode</span>
+    <span class="k">if</span> <span class="n">model</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="k">def</span> <span class="nf">fn</span><span class="p">(</span><span class="n">model</span><span class="p">:</span> <span class="n">Callable</span><span class="p">):</span>
+            <span class="k">if</span> <span class="n">model</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+                <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Model can&#39;t be None&quot;</span><span class="p">)</span>
+            <span class="k">return</span> <span class="nb">compile</span><span class="p">(</span><span class="n">model</span><span class="p">,</span>
+                           <span class="n">fullgraph</span><span class="o">=</span><span class="n">fullgraph</span><span class="p">,</span>
+                           <span class="n">dynamic</span><span class="o">=</span><span class="n">dynamic</span><span class="p">,</span>
+                           <span class="n">backend</span><span class="o">=</span><span class="n">backend</span><span class="p">,</span>
+                           <span class="n">mode</span><span class="o">=</span><span class="n">mode</span><span class="p">,</span>
+                           <span class="n">passes</span><span class="o">=</span><span class="n">passes</span><span class="p">,</span>
+                           <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">fn</span>
+
+    <span class="kn">import</span> <span class="nn">torch._dynamo</span>
+    <span class="kn">from</span> <span class="nn">torch._dynamo.eval_frame</span> <span class="kn">import</span> <span class="n">lookup_backend</span>
+    <span class="kn">from</span> <span class="nn">torch._inductor.config</span> <span class="kn">import</span> <span class="n">InductorConfigContext</span>
+    <span class="k">if</span> <span class="n">mode</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">passes</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Either mode or passes can be specified, but both can&#39;t be specified at the same time.&quot;</span><span class="p">)</span>
+    <span class="k">if</span> <span class="n">mode</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">passes</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="n">mode</span> <span class="o">=</span> <span class="s2">&quot;default&quot;</span>
+    <span class="k">if</span> <span class="n">backend</span> <span class="o">==</span> <span class="s2">&quot;inductor&quot;</span><span class="p">:</span>
+        <span class="n">compile_fn</span> <span class="o">=</span> <span class="n">lookup_backend</span><span class="p">(</span><span class="n">backend</span><span class="p">)</span>
+        <span class="n">cm</span> <span class="o">=</span> <span class="n">InductorConfigContext</span><span class="p">(</span><span class="n">mode</span> <span class="k">if</span> <span class="n">mode</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">passes</span><span class="p">)</span>
+
+        <span class="k">def</span> <span class="nf">_compile_fn</span><span class="p">(</span><span class="n">model_</span><span class="p">,</span> <span class="n">inputs_</span><span class="p">):</span>
+            <span class="k">with</span> <span class="n">cm</span><span class="p">:</span>
+                <span class="k">return</span> <span class="n">compile_fn</span><span class="p">(</span><span class="n">model_</span><span class="p">,</span> <span class="n">inputs_</span><span class="p">)</span>
+
+        <span class="n">_compile_fn</span><span class="o">.</span><span class="n">_torchdynamo_orig_callable</span> <span class="o">=</span> <span class="n">compile_fn</span>  <span class="c1"># type: ignore[attr-defined]</span>
+        <span class="n">backend</span> <span class="o">=</span> <span class="n">_compile_fn</span>
+    <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">_dynamo</span><span class="o">.</span><span class="n">optimize</span><span class="p">(</span><span class="n">backend</span><span class="o">=</span><span class="n">backend</span><span class="p">,</span> <span class="n">nopython</span><span class="o">=</span><span class="n">fullgraph</span><span class="p">,</span> <span class="n">dynamic</span><span class="o">=</span><span class="n">dynamic</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)(</span><span class="n">model</span><span class="p">)</span></div>
+
+
 <span class="k">def</span> <span class="nf">_register_device_module</span><span class="p">(</span><span class="n">device_type</span><span class="p">,</span> <span class="n">module</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Register an external runtime module of the specific :attr:`device_type`</span>
 <span class="sd">    supported by torch.</span>