chunk-d49d412a.35d45afc.js

(window["webpackJsonp"]=window["webpackJsonp"]||[]).push([["chunk-d49d412a"],{"3db7":function(t,e,a){"use strict";a("9350")},"867f":function(t,e,a){"use strict";a.r(e);var r=function(){var t=this,e=t._self._c;return e("div",{staticClass:"container"},[t._m(0),e("div",{staticClass:"content"},[e("p",{staticClass:"title"},[t._v("从源文件快速上手")]),e("a-divider",{staticStyle:{margin:"10px 0","background-image":"linear-gradient(to right,  rgb(103, 179, 241),  rgb(103, 179, 241), #f6f6f6, #f6f6f6)"}}),e("p",{staticStyle:{"text-indent":"2em"}},[t._v("如果你从GitHub下载了LibCity的源码，你可以使用提供的脚本进行简单的使用：")]),t._m(1),e("p",{staticStyle:{"text-indent":"2em"}},[t._v("这个例子将会在Foursquare-TKY这个数据集上使用DeepMove模型执行轨迹位置预测任务。并且，该脚本还支持通过命令行来设置参数。下面将给出几个例子作为参考。")]),e("p",{staticStyle:{"text-indent":"2em"}},[t._v("如果您想在METR_LA这个数据集上使用DCRNN模型执行交通状态预测任务，只需通过设定相关参数运行脚本：")]),t._m(2),e("p",{staticStyle:{"text-indent":"2em"}},[t._v("您会得到一些类似下面的输出：")]),t._m(3),e("p",{staticStyle:{"text-indent":"2em"}},[t._v("正如您所见，原始数据集METR_LA的原子文件会被加载并被分成训练集、验证集和测试集三个部分。我们在训练集上进行参数更新，选择在验证集上效果最佳的模型参数，最后报告其在测试集上的结果。")]),e("p",{staticStyle:{"text-indent":"2em"}},[t._v("开始训练：")]),t._m(4),e("br"),t._m(5),t._m(6),t._m(7),e("br")],1)])},i=[function(){var t=this,e=t._self._c;return e("div",{staticClass:"header"},[e("div",{staticStyle:{"padding-top":"20px",color:"white"}},[e("p",{staticStyle:{margin:"20px 0 30px 130px","font-size":"60px"}},[t._v("快速上手")]),e("p",{staticStyle:{margin:"0px 0 20px 130px","font-size":"30px"}},[t._v(" 该页面会帮助你快速了解LibCity的基本使用. ")])])])},function(){var t=this,e=t._self._c;return e("div",{staticClass:"code"},[e("code",{attrs:{"data-lang":"bash"}},[t._v("python run_model.py")])])},function(){var t=this,e=t._self._c;return e("div",{staticClass:"code"},[e("code",{attrs:{"data-lang":"bash"}},[t._v("python run_model.py --task traffic_state_pred --model DCRNN --dataset METR_LA")])])},function(){var t=this,e=t._self._c;return e("div",{staticClass:"code",staticStyle:{"font-size":"16px"}},[e("code",{attrs:{"data-lang":"bash"}},[t._v(" - INFO - Log directory: ./libcity/log"),e("br"),t._v(" - INFO - Begin pipeline, task=traffic_state_pred, model_name=DCRNN, dataset_name=METR_LA"),e("br"),t._v(" - INFO - Loaded file METR_LA.geo, num_nodes=207"),e("br"),t._v(" - INFO - Loaded file METR_LA.rel, shape=(207, 207)"),e("br"),t._v(" - INFO - Start Calculate the weight by Gauss kernel!"),e("br"),t._v(" - INFO - Loading ./libcity/cache/dataset_cache/point_based_METR_LA_12_12_0.7_0.1_standard_64_True_False_True.npz"),e("br"),t._v(" - INFO - train x: (23974, 12, 207, 2)y: (23974, 12, 207, 2)"),e("br"),t._v(" - INFO - eval x: (3425, 12, 207, 2)y: (3425, 12, 207, 2)"),e("br"),t._v(" - INFO - test x: (6850, 12, 207, 2)y: (6850, 12, 207, 2)"),e("br"),t._v(" - INFO - StandardScaler mean: 54.40592829587626, std: 19.493739270573098"),e("br")])])},function(){var t=this,e=t._self._c;return e("div",{staticClass:"code",staticStyle:{"font-size":"16px"}},[e("code",{attrs:{"data-lang":"bash"}},[t._v(" - INFO - Start training ..."),e("br"),t._v(" - INFO - num_batches:375"),e("br"),t._v(" - INFO - Total trainable parameters 372353"),e("br"),t._v(" - INFO - epoch complete!"),e("br"),t._v(" - INFO - evaluating now!"),e("br"),t._v(" - INFO - Epoch [0/100] (375) train_mae: 3.3774, val_mae: 4.3733, lr: 0.010000, 403.5s"),e("br"),t._v(" - INFO - Saved model at 0"),e("br"),t._v(" - INFO - Val loss decrease from inf to 4.3733, saving to ./libcity/cache/model_cache/DCRNN_METR_LA_epoch0.tar"),e("br"),t._v(" ..."),e("br"),t._v(" - INFO - epoch complete!"),e("br"),t._v(" - INFO - evaluating now!"),e("br"),t._v(" - INFO - Epoch [99/100] (37500) train_mae: 2.8075, val_mae: 2.8501, lr: 0.000001, 401.7s"),e("br"),t._v(" - INFO - Loaded model at 66"),e("br"),t._v(" - INFO - Saved model at ./libcity/cache/model_cache/DCRNN_METR_LA.m"),e("br"),t._v(" - INFO - Start evaluating ..."),e("br"),t._v(" - INFO - Evaluate result is ..."),e("br")])])},function(){var t=this,e=t._self._c;return e("p",[t._v("如果您想修改参数，例如"),e("code",{staticStyle:{color:"#e83e8c","font-size":"90%"}},[t._v("learning_rate")]),t._v("，只需根据您的需求增加额外的参数，例如：")])},function(){var t=this,e=t._self._c;return e("div",{staticClass:"code"},[e("code",{attrs:{"data-lang":"bash"}},[t._v("python run_model.py --learning_rate 0.001")])])},function(){var t=this,e=t._self._c;return e("p",[t._v("所有支持的参数和更多的细节可见"),e("a",{attrs:{target:"_blank",href:"https://bigscity-libcity-docs.readthedocs.io/en/latest/get_started/quick_start.html"}},[t._v("文档")]),t._v("。")])}],s={data(){return{}},components:{}},_=s,n=(a("3db7"),a("1805")),c=Object(n["a"])(_,r,i,!1,null,"6fc8f4d0",null);e["default"]=c.exports},9350:function(t,e,a){}}]);
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