Skip to content

P
Paddle

BaiXuePrincess / Paddle
与 Fork 源项目一致

Fork自 PaddlePaddle / Paddle

通知 1
Star 1
Fork 0
P
Paddle
切换分支/标签
查找文件 普通视图历史永久链接Permalink
new_op_en.html 55.6 KB
Newer Older
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 


<!DOCTYPE html>
<!--[if IE 8]><html class="no-js lt-ie9" lang="en" > <![endif]-->
<!--[if gt IE 8]><!--> <html class="no-js" lang="en" > <!--<![endif]-->
<head>
  <meta charset="utf-8">
  
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  
  <title>How to write a new operator &mdash; PaddlePaddle  documentation</title>
  

  
  

  

  
  
    

  

  
  
    <link rel="stylesheet" href="../../_static/css/theme.css" type="text/css" />
  

  
  
        <link rel="index" title="Index"
              href="../../genindex.html"/>
        <link rel="search" title="Search" href="../../search.html"/>
    <link rel="top" title="PaddlePaddle  documentation" href="../../index.html"/> 

  <link rel="stylesheet" href="https://cdn.jsdelivr.net/perfect-scrollbar/0.6.14/css/perfect-scrollbar.min.css" type="text/css" />
  <link rel="stylesheet" href="../../_static/css/override.css" type="text/css" />
  <script>
  var _hmt = _hmt || [];
  (function() {
    var hm = document.createElement("script");
    hm.src = "//hm.baidu.com/hm.js?b9a314ab40d04d805655aab1deee08ba";
    var s = document.getElementsByTagName("script")[0]; 
    s.parentNode.insertBefore(hm, s);
  })();
  </script>

  

  
  <script src="../../_static/js/modernizr.min.js"></script>

</head>

<body class="wy-body-for-nav" role="document">

  
  <header class="site-header">
    <div class="site-logo">
      <a href="/"><img src="../../_static/images/PP_w.png"></a>
    </div>
    <div class="site-nav-links">
      <div class="site-menu">
        <a class="fork-on-github" href="https://github.com/PaddlePaddle/Paddle" target="_blank"><i class="fa fa-github"></i>Fork me on Github</a>
        <div class="language-switcher dropdown">
          <a type="button" data-toggle="dropdown">
            <span>English</span>
            <i class="fa fa-angle-up"></i>
            <i class="fa fa-angle-down"></i>
          </a>
          <ul class="dropdown-menu">
            <li><a href="/doc_cn">中文</a></li>
            <li><a href="/doc">English</a></li>
          </ul>
        </div>
        <ul class="site-page-links">
          <li><a href="/">Home</a></li>
        </ul>
      </div>
      <div class="doc-module">
        
        <ul>
<li class="toctree-l1"><a class="reference internal" href="../../getstarted/index_en.html">GET STARTED</a></li>
<li class="toctree-l1"><a class="reference internal" href="../index_en.html">HOW TO</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../api/index_en.html">API</a></li>
T
Deploy to GitHub Pages: 664691c89af182de3919fc72a7c875311e03893d  
Travis CI 已提交
87 
<li class="toctree-l1"><a class="reference internal" href="../../mobile/index_en.html">MOBILE</a></li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 
</ul>

        
<div role="search">
  <form id="rtd-search-form" class="wy-form" action="../../search.html" method="get">
    <input type="text" name="q" placeholder="Search docs" />
    <input type="hidden" name="check_keywords" value="yes" />
    <input type="hidden" name="area" value="default" />
  </form>
</div>        
      </div>
    </div>
  </header>
  
  <div class="main-content-wrap">

    
    <nav class="doc-menu-vertical" role="navigation">
        
          
          <ul>
<li class="toctree-l1"><a class="reference internal" href="../../getstarted/index_en.html">GET STARTED</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../../getstarted/build_and_install/index_en.html">Install and Build</a><ul>
T
Deploy to GitHub Pages: 0c0ff2828ccedb51db23290d6df9e4c83839d6af  
Travis CI 已提交
111 112 
<li class="toctree-l3"><a class="reference internal" href="../../getstarted/build_and_install/pip_install_en.html">Install Using pip</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../getstarted/build_and_install/docker_install_en.html">Run in Docker Containers</a></li>
T
Deploy to GitHub Pages: 458ffbf4fe7fe6da5e2ea133c027d560815cc3cc  
Travis CI 已提交
113 
<li class="toctree-l3"><a class="reference internal" href="build_en.html">Build using Docker</a></li>
T
Deploy to GitHub Pages: 0c0ff2828ccedb51db23290d6df9e4c83839d6af  
Travis CI 已提交
114 
<li class="toctree-l3"><a class="reference internal" href="../../getstarted/build_and_install/build_from_source_en.html">Build from Sources</a></li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
115 116 117 118 119 120 121 122 123 124 125 
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../index_en.html">HOW TO</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../usage/cmd_parameter/index_en.html">Set Command-line Parameters</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../usage/cmd_parameter/use_case_en.html">Use Case</a></li>
<li class="toctree-l3"><a class="reference internal" href="../usage/cmd_parameter/arguments_en.html">Argument Outline</a></li>
<li class="toctree-l3"><a class="reference internal" href="../usage/cmd_parameter/detail_introduction_en.html">Detail Description</a></li>
</ul>
</li>
T
Deploy to GitHub Pages: 63ffe5250a120ff430469b8d000deb2b031c4881  
Travis CI 已提交
126 
<li class="toctree-l2"><a class="reference internal" href="../usage/cluster/cluster_train_en.html">PaddlePaddle Distributed Training</a></li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
127 128 129 
<li class="toctree-l2"><a class="reference internal" href="../usage/k8s/k8s_en.html">Paddle On Kubernetes</a></li>
<li class="toctree-l2"><a class="reference internal" href="../usage/k8s/k8s_aws_en.html">Distributed PaddlePaddle Training on AWS with Kubernetes</a></li>
<li class="toctree-l2"><a class="reference internal" href="new_layer_en.html">Write New Layers</a></li>
T
Deploy to GitHub Pages: f122a5da2f27038b48f6ed607e296d762050e920  
Travis CI 已提交
130 
<li class="toctree-l2"><a class="reference internal" href="contribute_to_paddle_en.html">Contribute Code</a></li>
T
Deploy to GitHub Pages: 70ee79c2567d5128a9d527b444fcee30f83c02a5  
Travis CI 已提交
131 
<li class="toctree-l2"><a class="reference internal" href="write_docs_en.html">Contribute Documentation</a></li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 
<li class="toctree-l2"><a class="reference internal" href="../deep_model/rnn/index_en.html">RNN Models</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../deep_model/rnn/rnn_config_en.html">RNN Configuration</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../optimization/gpu_profiling_en.html">Tune GPU Performance</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../../api/index_en.html">API</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../../api/v2/model_configs.html">Model Configuration</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/config/activation.html">Activation</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/config/layer.html">Layers</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/config/evaluators.html">Evaluators</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/config/optimizer.html">Optimizer</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/config/pooling.html">Pooling</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/config/networks.html">Networks</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/config/attr.html">Parameter Attribute</a></li>
</ul>
</li>
T
Deploy to GitHub Pages: d4d8f742a3bc4366bf410bc9ff29c0c32666bf60  
Travis CI 已提交
150 151 152 153 154 155 
<li class="toctree-l2"><a class="reference internal" href="../../api/v2/data.html">Data Reader Interface and DataSets</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/data/data_reader.html">Data Reader Interface</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/data/image.html">Image Interface</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/data/dataset.html">Dataset</a></li>
</ul>
</li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
156 
<li class="toctree-l2"><a class="reference internal" href="../../api/v2/run_logic.html">Training and Inference</a></li>
T
Deploy to GitHub Pages: 1fe05c458fa1d7ff1949759c2a06ed6d19ab8048  
Travis CI 已提交
157 158 159 160 161 162 163 164 165 166 167 168 169 
<li class="toctree-l2"><a class="reference internal" href="../../api/v2/fluid.html">Fluid</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/layers.html">Layers</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/data_feeder.html">DataFeeder</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/executor.html">Executor</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/initializer.html">Initializer</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/evaluator.html">Evaluator</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/nets.html">Nets</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/optimizer.html">Optimizer</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/param_attr.html">ParamAttr</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/profiler.html">Profiler</a></li>
<li class="toctree-l3"><a class="reference internal" href="../../api/v2/fluid/regularizer.html">Regularizer</a></li>
</ul>
</li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
170 171 
</ul>
</li>
T
Deploy to GitHub Pages: 664691c89af182de3919fc72a7c875311e03893d  
Travis CI 已提交
172 173 174 175 176 
<li class="toctree-l1"><a class="reference internal" href="../../mobile/index_en.html">MOBILE</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../../mobile/cross_compiling_for_android_en.html">Build PaddlePaddle for Android</a></li>
<li class="toctree-l2"><a class="reference internal" href="../../mobile/cross_compiling_for_raspberry_en.html">Build PaddlePaddle for Raspberry Pi</a></li>
</ul>
</li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 
</ul>

        
    </nav>
    
    <section class="doc-content-wrap">

      

 







<div role="navigation" aria-label="breadcrumbs navigation">
  <ul class="wy-breadcrumbs">
      
    <li>How to write a new operator</li>
  </ul>
</div>
      
      <div class="wy-nav-content" id="doc-content">
        <div class="rst-content">
          <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
           <div itemprop="articleBody">
            
  <div class="section" id="how-to-write-a-new-operator">
<span id="how-to-write-a-new-operator"></span><h1>How to write a new operator<a class="headerlink" href="#how-to-write-a-new-operator" title="Permalink to this headline"></a></h1>
<ul class="simple">
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
209 210 211 212 213 214 
<li><a class="reference external" href="#background">Background</a></li>
<li><a class="reference external" href="#implementing-c++-types">Implementing C++ Types</a><ul>
<li><a class="reference external" href="#defining-protoMaker">Defining ProtoMaker</a></li>
<li><a class="reference external" href="#defining-operator">Defining Operator</a></li>
<li><a class="reference external" href="#registering-operator">Registering Operator</a></li>
<li><a class="reference external" href="#compilation">Compilation</a></li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
215 216 
</ul>
</li>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
217 218 219 220 221 222 223 224 
<li><a class="reference external" href="#python-binding">Python Binding</a></li>
<li><a class="reference external" href="#unit-tests">Unit Tests</a><ul>
<li><a class="reference external" href="#testing-forward-operators">Testing Forward Operators</a></li>
<li><a class="reference external" href="#testing-backward-operators">Testing Backward Operators</a></li>
<li><a class="reference external" href="#compiling-and-running">Compiling and Running</a></li>
</ul>
</li>
<li><a class="reference external" href="#remarks">Remarks</a></li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 
</ul>
<div class="section" id="background">
<span id="background"></span><h2>Background<a class="headerlink" href="#background" title="Permalink to this headline"></a></h2>
<p>Here are the base types needed. For details, please refer to the design docs.</p>
<ul class="simple">
<li><code class="docutils literal"><span class="pre">framework::OperatorBase</span></code>: Operator (Op)base class.</li>
<li><code class="docutils literal"><span class="pre">framework::OpKernel</span></code>: Base class for Op computation.</li>
<li><code class="docutils literal"><span class="pre">framework::OperatorWithKernel</span></code>: Inherited from OperatorBase, describing an operator with computation.</li>
<li><code class="docutils literal"><span class="pre">class</span> <span class="pre">OpProtoAndCheckerMaker</span></code>: Describes an Operator&#8217;s input, output, attributes and description, mainly used to interface with Python API.</li>
</ul>
<p>An operator can be differentiated by whether in has kernel methods. An operator with kernel inherits from <code class="docutils literal"><span class="pre">OperatorWithKernel</span></code> while the ones without inherit from <code class="docutils literal"><span class="pre">OperatorBase</span></code>. This tutorial focuses on implementing operators with kernels. In short, an operator includes the following information:</p>
<p>Information           | Where is it defined
&#8212;&#8212;&#8212;&#8212;&#8211;  | :&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;-
OpProtoMake definition  | <code class="docutils literal"><span class="pre">.cc</span></code>files, Backward Op does not need an OpProtoMake interface.
Op definition           | <code class="docutils literal"><span class="pre">.cc</span></code> files
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
240 241 
Kernel implementation       | The kernel methods shared between CPU and CUDA are defined in <code class="docutils literal"><span class="pre">.h</span></code> files. CPU-specific kernels live in <code class="docutils literal"><span class="pre">.cc</span></code> files, while CUDA-specific kernels are implemented in <code class="docutils literal"><span class="pre">.cu</span></code>files.
Registering the Op           | Ops are registered in <code class="docutils literal"><span class="pre">.cc</span></code> files; For Kernel registration, <code class="docutils literal"><span class="pre">.cc</span></code> files contain the CPU implementation, while <code class="docutils literal"><span class="pre">.cu</span></code> files contain the CUDA implementation.</p>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 
<p>New Operator implementations are added to the list <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/operators">paddle/operators</a>, with file names in the format <code class="docutils literal"><span class="pre">*_op.h</span></code> (if applicable), <code class="docutils literal"><span class="pre">*_op.cc</span></code>, <code class="docutils literal"><span class="pre">*_op.cu</span></code> (if applicable).** The system will use the naming scheme to automatically build operators and their corresponding Python extensions. **</p>
<p>Let&#8217;s take matrix multiplication operator, <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/mul_op.cc">MulOp</a>, as an example to introduce the writing of an Operator with Kernel.</p>
</div>
<div class="section" id="implementing-c-types">
<span id="implementing-c-types"></span><h2>Implementing C++ Types<a class="headerlink" href="#implementing-c-types" title="Permalink to this headline"></a></h2>
<div class="section" id="defining-class-protomaker">
<span id="defining-class-protomaker"></span><h3>1. Defining Class ProtoMaker<a class="headerlink" href="#defining-class-protomaker" title="Permalink to this headline"></a></h3>
<p>Matrix Multiplication can be written as $Out = X * Y$, meaning that the operation consists of two inputs and pne output.</p>
<p>First, define <code class="docutils literal"><span class="pre">ProtoMaker</span></code> to describe the Operator&#8217;s input, output, and additional comments:</p>
<div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">MulOpMaker</span> <span class="o">:</span> <span class="k">public</span> <span class="n">framework</span><span class="o">::</span><span class="n">OpProtoAndCheckerMaker</span> <span class="p">{</span>
 <span class="k">public</span><span class="o">:</span>
  <span class="n">MulOpMaker</span><span class="p">(</span><span class="n">framework</span><span class="o">::</span><span class="n">OpProto</span> <span class="o">*</span><span class="n">proto</span><span class="p">,</span> <span class="n">framework</span><span class="o">::</span><span class="n">OpAttrChecker</span> <span class="o">*</span><span class="n">op_checker</span><span class="p">)</span>
      <span class="o">:</span> <span class="n">OpProtoAndCheckerMaker</span><span class="p">(</span><span class="n">proto</span><span class="p">,</span> <span class="n">op_checker</span><span class="p">)</span> <span class="p">{</span>
    <span class="n">AddInput</span><span class="p">(</span><span class="s">&quot;X&quot;</span><span class="p">,</span> <span class="s">&quot;(Tensor), 2D tensor of size (M x K)&quot;</span><span class="p">);</span>
    <span class="n">AddInput</span><span class="p">(</span><span class="s">&quot;Y&quot;</span><span class="p">,</span> <span class="s">&quot;(Tensor), 2D tensor of size (K x N)&quot;</span><span class="p">);</span>
    <span class="n">AddOutput</span><span class="p">(</span><span class="s">&quot;Out&quot;</span><span class="p">,</span> <span class="s">&quot;(Tensor), 2D tensor of size (M x N)&quot;</span><span class="p">);</span>
    <span class="n">AddComment</span><span class="p">(</span><span class="sa">R</span><span class="s">&quot;</span><span class="dl">DOC(</span><span class="s"></span>
<span class="s">Two Element Mul Operator.</span>
<span class="s">The equation is: Out = X * Y</span>
<span class="dl">)DOC</span><span class="s">&quot;</span><span class="p">);</span>
  <span class="p">}</span>
<span class="p">};</span>
</pre></div>
</div>
<p><a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/mul_op.cc#L43"><code class="docutils literal"><span class="pre">MulOpMaker</span></code></a>is inherited from<code class="docutils literal"><span class="pre">framework::OpProtoAndCheckerMaker</span></code>, consisting of 2 variables in the constructor：</p>
<ul class="simple">
<li><code class="docutils literal"><span class="pre">framework::OpProto</span></code> stores Operator input and variable attribute, used for generating Python API interfaces.</li>
<li><code class="docutils literal"><span class="pre">framework::OpAttrChecker</span></code> is used to validate variable attributes.</li>
</ul>
<p>The constructor utilizes <code class="docutils literal"><span class="pre">AddInput</span></code>, <code class="docutils literal"><span class="pre">AddOutput</span></code>, and <code class="docutils literal"><span class="pre">AddComment</span></code>, so that the corresponding information will be added to <code class="docutils literal"><span class="pre">OpProto</span></code>.</p>
<p>The code above adds two inputs <code class="docutils literal"><span class="pre">X</span></code> and <code class="docutils literal"><span class="pre">Y</span></code> to <code class="docutils literal"><span class="pre">MulOp</span></code>, an output <code class="docutils literal"><span class="pre">Out</span></code>, and their corresponding descriptions, in accordance to Paddle&#8217;s <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/name_convention.md">naming convention</a>.</p>
<p>An additional example <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/scale_op.cc#L37"><code class="docutils literal"><span class="pre">ScaleOp</span></code></a> is implemented as follows:</p>
<div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="k">template</span> <span class="o">&lt;</span><span class="k">typename</span> <span class="n">AttrType</span><span class="o">&gt;</span>
<span class="k">class</span> <span class="nc">ScaleOpMaker</span> <span class="o">:</span> <span class="k">public</span> <span class="n">framework</span><span class="o">::</span><span class="n">OpProtoAndCheckerMaker</span> <span class="p">{</span>
 <span class="k">public</span><span class="o">:</span>
  <span class="n">ScaleOpMaker</span><span class="p">(</span><span class="n">framework</span><span class="o">::</span><span class="n">OpProto</span> <span class="o">*</span><span class="n">proto</span><span class="p">,</span> <span class="n">framework</span><span class="o">::</span><span class="n">OpAttrChecker</span> <span class="o">*</span><span class="n">op_checker</span><span class="p">)</span>
      <span class="o">:</span> <span class="n">OpProtoAndCheckerMaker</span><span class="p">(</span><span class="n">proto</span><span class="p">,</span> <span class="n">op_checker</span><span class="p">)</span> <span class="p">{</span>
    <span class="n">AddInput</span><span class="p">(</span><span class="s">&quot;X&quot;</span><span class="p">,</span> <span class="s">&quot;The input tensor of scale operator.&quot;</span><span class="p">).</span><span class="n">NotInGradient</span><span class="p">();</span>
    <span class="n">AddOutput</span><span class="p">(</span><span class="s">&quot;Out&quot;</span><span class="p">,</span> <span class="s">&quot;The output tensor of scale operator.&quot;</span><span class="p">).</span><span class="n">NotInGradient</span><span class="p">();</span>
    <span class="n">AddComment</span><span class="p">(</span><span class="sa">R</span><span class="s">&quot;</span><span class="dl">DOC(</span><span class="s">Scale operator</span>
<span class="s">The equation is: Out = scale*X</span>
<span class="dl">)DOC</span><span class="s">&quot;</span><span class="p">);</span>
    <span class="n">AddAttr</span><span class="o">&lt;</span><span class="n">AttrType</span><span class="o">&gt;</span><span class="p">(</span><span class="s">&quot;scale&quot;</span><span class="p">,</span> <span class="s">&quot;scale of scale operator.&quot;</span><span class="p">).</span><span class="n">SetDefault</span><span class="p">(</span><span class="mf">1.0</span><span class="p">);</span>
  <span class="p">}</span>
<span class="p">};</span>
</pre></div>
</div>
<p>There are two changes in this example:</p>
<ul class="simple">
<li><code class="docutils literal"><span class="pre">AddInput(&quot;X&quot;,&quot;...&quot;).NotInGradient()</span></code> expresses that input <code class="docutils literal"><span class="pre">X</span></code> is not involved in <code class="docutils literal"><span class="pre">ScaleOp</span></code>&#8216;s corresponding computation. If an input to an operator is not participating in back-propagation, please explicitly set <code class="docutils literal"><span class="pre">.NotInGradient()</span></code>.</li>
<li><code class="docutils literal"><span class="pre">AddAttr&lt;AttrType&gt;(&quot;scale&quot;,</span> <span class="pre">&quot;...&quot;).SetDefault(1.0);</span></code>  adds <code class="docutils literal"><span class="pre">scale</span></code>constant as an attribute, and sets the default value to 1.0.</li>
</ul>
</div>
<div class="section" id="defining-operator">
<span id="defining-operator"></span><h3>2. Defining Operator<a class="headerlink" href="#defining-operator" title="Permalink to this headline"></a></h3>
<p>The following code defines the interface for MulOp:</p>
<div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">MulOp</span> <span class="o">:</span> <span class="k">public</span> <span class="n">framework</span><span class="o">::</span><span class="n">OperatorWithKernel</span> <span class="p">{</span>
 <span class="k">public</span><span class="o">:</span>
  <span class="k">using</span> <span class="n">framework</span><span class="o">::</span><span class="n">OperatorWithKernel</span><span class="o">::</span><span class="n">OperatorWithKernel</span><span class="p">;</span>

 <span class="k">protected</span><span class="o">:</span>
  <span class="kt">void</span> <span class="n">InferShape</span><span class="p">(</span><span class="k">const</span> <span class="n">framework</span><span class="o">::</span><span class="n">InferShapeContext</span> <span class="o">&amp;</span><span class="n">ctx</span><span class="p">)</span> <span class="k">const</span> <span class="k">override</span> <span class="p">{</span>
    <span class="k">auto</span> <span class="n">dim0</span> <span class="o">=</span> <span class="n">ctx</span><span class="p">.</span><span class="n">Input</span><span class="o">&lt;</span><span class="n">Tensor</span><span class="o">&gt;</span><span class="p">(</span><span class="s">&quot;X&quot;</span><span class="p">)</span><span class="o">-&gt;</span><span class="n">dims</span><span class="p">();</span>
    <span class="k">auto</span> <span class="n">dim1</span> <span class="o">=</span> <span class="n">ctx</span><span class="p">.</span><span class="n">Input</span><span class="o">&lt;</span><span class="n">Tensor</span><span class="o">&gt;</span><span class="p">(</span><span class="s">&quot;Y&quot;</span><span class="p">)</span><span class="o">-&gt;</span><span class="n">dims</span><span class="p">();</span>
    <span class="n">PADDLE_ENFORCE_EQ</span><span class="p">(</span><span class="n">dim0</span><span class="p">.</span><span class="n">size</span><span class="p">(),</span> <span class="mi">2</span><span class="p">,</span>
                      <span class="s">&quot;input X(%s) should be a tensor with 2 dims, a matrix&quot;</span><span class="p">,</span>
                      <span class="n">ctx</span><span class="p">.</span><span class="n">op_</span><span class="p">.</span><span class="n">Input</span><span class="p">(</span><span class="s">&quot;X&quot;</span><span class="p">));</span>
    <span class="n">PADDLE_ENFORCE_EQ</span><span class="p">(</span><span class="n">dim1</span><span class="p">.</span><span class="n">size</span><span class="p">(),</span> <span class="mi">2</span><span class="p">,</span>
                      <span class="s">&quot;input Y(%s) should be a tensor with 2 dims, a matrix&quot;</span><span class="p">,</span>
                      <span class="n">ctx</span><span class="p">.</span><span class="n">op_</span><span class="p">.</span><span class="n">Input</span><span class="p">(</span><span class="s">&quot;Y&quot;</span><span class="p">));</span>
    <span class="n">PADDLE_ENFORCE_EQ</span><span class="p">(</span>
        <span class="n">dim0</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">dim1</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span>
        <span class="s">&quot;First matrix&#39;s width must be equal with second matrix&#39;s height.&quot;</span><span class="p">);</span>
    <span class="n">ctx</span><span class="p">.</span><span class="n">Output</span><span class="o">&lt;</span><span class="n">Tensor</span><span class="o">&gt;</span><span class="p">(</span><span class="s">&quot;Out&quot;</span><span class="p">)</span><span class="o">-&gt;</span><span class="n">Resize</span><span class="p">({</span><span class="n">dim0</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">dim1</span><span class="p">[</span><span class="mi">1</span><span class="p">]});</span>
  <span class="p">}</span>
<span class="p">};</span>
</pre></div>
</div>
<p><a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/mul_op.cc#L22"><code class="docutils literal"><span class="pre">MulOp</span></code></a> is inherited from <code class="docutils literal"><span class="pre">OperatorWithKernel</span></code>. Its <code class="docutils literal"><span class="pre">public</span></code> member</p>
<div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="k">using</span> <span class="n">framework</span><span class="o">::</span><span class="n">OperatorWithKernel</span><span class="o">::</span><span class="n">OperatorWithKernel</span><span class="p">;</span>
</pre></div>
</div>
<p>expresses an operator constructor using base class <code class="docutils literal"><span class="pre">OperatorWithKernel</span></code>, alternatively written as</p>
<div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="n">MulOp</span><span class="p">(</span><span class="k">const</span> <span class="n">std</span><span class="o">::</span><span class="n">string</span> <span class="o">&amp;</span><span class="n">type</span><span class="p">,</span> <span class="k">const</span> <span class="n">framework</span><span class="o">::</span><span class="n">VariableNameMap</span> <span class="o">&amp;</span><span class="n">inputs</span><span class="p">,</span>
      <span class="k">const</span> <span class="n">framework</span><span class="o">::</span><span class="n">VariableNameMap</span> <span class="o">&amp;</span><span class="n">outputs</span><span class="p">,</span>
      <span class="k">const</span> <span class="n">framework</span><span class="o">::</span><span class="n">AttributeMap</span> <span class="o">&amp;</span><span class="n">attrs</span><span class="p">)</span>
  <span class="o">:</span> <span class="n">OperatorWithKernel</span><span class="p">(</span><span class="n">type</span><span class="p">,</span> <span class="n">inputs</span><span class="p">,</span> <span class="n">outputs</span><span class="p">,</span> <span class="n">attrs</span><span class="p">)</span> <span class="p">{}</span>
</pre></div>
</div>
<p><code class="docutils literal"><span class="pre">InferShape</span></code> interface needs to be re-written.<code class="docutils literal"><span class="pre">InferShape</span></code> is a constant method and cannot modify Op&#8217;s member variables, its constant member <code class="docutils literal"><span class="pre">const</span> <span class="pre">framework::InferShapeContext</span> <span class="pre">&amp;ctx</span></code> can be used to extract input, output, and attributes. It functions to</p>
<ul class="simple">
<li>1). validate and error out early: it checks input data dimensions and types.</li>
<li>2). configures the tensor shape in the output.</li>
</ul>
<p>Usually <code class="docutils literal"><span class="pre">OpProtoMaker</span></code> and <code class="docutils literal"><span class="pre">Op</span></code>&#8216;s type definitions are written in <code class="docutils literal"><span class="pre">.cc</span></code> files, which also include the registration methods introduced later.</p>
</div>
<div class="section" id="defining-opkernel">
<span id="defining-opkernel"></span><h3>3. Defining OpKernel<a class="headerlink" href="#defining-opkernel" title="Permalink to this headline"></a></h3>
<p><code class="docutils literal"><span class="pre">MulKernel</span></code> inherits <code class="docutils literal"><span class="pre">framework::OpKernel</span></code>, which includes the following templates:</p>
<ul class="simple">
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
342 
<li><code class="docutils literal"><span class="pre">typename</span> <span class="pre">DeviceContext</span></code> denotes device context type. When different devices, namely the CPUDeviceContext and the CUDADeviceContext, share the same kernel, this template needs to be added. If they don&#8217;t share kernels, this must not be added. An example of a non-sharing kernel is <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/cross_entropy_op.h#L43"><code class="docutils literal"><span class="pre">OnehotCrossEntropyOpKernel</span></code></a>.</li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
343 344 345 346 347 348 349 350 351 
<li><code class="docutils literal"><span class="pre">typename</span> <span class="pre">T</span></code> denotes data type, such as <code class="docutils literal"><span class="pre">float</span></code> or <code class="docutils literal"><span class="pre">double</span></code>.</li>
</ul>
<p><code class="docutils literal"><span class="pre">MulKernel</span></code> types need to rewrite the interface for <code class="docutils literal"><span class="pre">Compute</span></code>.</p>
<ul class="simple">
<li><code class="docutils literal"><span class="pre">Compute</span></code> takes one input variable <code class="docutils literal"><span class="pre">const</span> <span class="pre">framework::ExecutionContext&amp;</span> <span class="pre">context</span></code>.</li>
<li>Compared with <code class="docutils literal"><span class="pre">InferShapeContext</span></code>, <code class="docutils literal"><span class="pre">ExecutionContext</span></code> includes device types, and can similarly extract input, output, and attribute variables.</li>
<li><code class="docutils literal"><span class="pre">Compute</span></code> implements the computation logics of an <code class="docutils literal"><span class="pre">OpKernel</span></code>.</li>
</ul>
<p><code class="docutils literal"><span class="pre">MulKernel</span></code>&#8216;s implementation of <code class="docutils literal"><span class="pre">Compute</span></code> is as follows:</p>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
352 
<div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="k">template</span> <span class="o">&lt;</span><span class="k">typename</span> <span class="n">DeviceContext</span><span class="p">,</span> <span class="k">typename</span> <span class="n">T</span><span class="o">&gt;</span>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
353 354 355 356 357 358 359 
<span class="k">class</span> <span class="nc">MulKernel</span> <span class="o">:</span> <span class="k">public</span> <span class="n">framework</span><span class="o">::</span><span class="n">OpKernel</span> <span class="p">{</span>
<span class="k">public</span><span class="o">:</span>
<span class="kt">void</span> <span class="n">Compute</span><span class="p">(</span><span class="k">const</span> <span class="n">framework</span><span class="o">::</span><span class="n">ExecutionContext</span><span class="o">&amp;</span> <span class="n">context</span><span class="p">)</span> <span class="k">const</span> <span class="k">override</span> <span class="p">{</span>
  <span class="k">auto</span><span class="o">*</span> <span class="n">X</span> <span class="o">=</span> <span class="n">context</span><span class="p">.</span><span class="n">Input</span><span class="o">&lt;</span><span class="n">Tensor</span><span class="o">&gt;</span><span class="p">(</span><span class="s">&quot;X&quot;</span><span class="p">);</span>
  <span class="k">auto</span><span class="o">*</span> <span class="n">Y</span> <span class="o">=</span> <span class="n">context</span><span class="p">.</span><span class="n">Input</span><span class="o">&lt;</span><span class="n">Tensor</span><span class="o">&gt;</span><span class="p">(</span><span class="s">&quot;Y&quot;</span><span class="p">);</span>
  <span class="k">auto</span><span class="o">*</span> <span class="n">Z</span> <span class="o">=</span> <span class="n">context</span><span class="p">.</span><span class="n">Output</span><span class="o">&lt;</span><span class="n">Tensor</span><span class="o">&gt;</span><span class="p">(</span><span class="s">&quot;Out&quot;</span><span class="p">);</span>
  <span class="n">Z</span><span class="o">-&gt;</span><span class="n">mutable_data</span><span class="o">&lt;</span><span class="n">T</span><span class="o">&gt;</span><span class="p">(</span><span class="n">context</span><span class="p">.</span><span class="n">GetPlace</span><span class="p">());</span>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
360 361 
  <span class="k">auto</span><span class="o">&amp;</span> <span class="n">device_context</span> <span class="o">=</span> <span class="n">context</span><span class="p">.</span><span class="k">template</span> <span class="n">device_context</span><span class="o">&lt;</span><span class="n">DeviceContext</span><span class="o">&gt;</span><span class="p">();</span>
  <span class="n">math</span><span class="o">::</span><span class="n">matmul</span><span class="o">&lt;</span><span class="n">DeviceContext</span><span class="p">,</span> <span class="n">T</span><span class="o">&gt;</span><span class="p">(</span><span class="o">*</span><span class="n">X</span><span class="p">,</span> <span class="nb">false</span><span class="p">,</span> <span class="o">*</span><span class="n">Y</span><span class="p">,</span> <span class="nb">false</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">Z</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="n">device_context</span><span class="p">);</span>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
362 363 364 365 
<span class="p">}</span>
<span class="p">};</span>
</pre></div>
</div>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
366 367 
<p>Note that <strong>different devices (CPU, CUDA)share an Op definition; whether or not they share the same <code class="docutils literal"><span class="pre">OpKernel</span></code> depends on whether <code class="docutils literal"><span class="pre">Compute</span></code> calls functions that support both devices.</strong></p>
<p><code class="docutils literal"><span class="pre">MulOp</span></code>&#8216;s CPU and CUDA share the same <code class="docutils literal"><span class="pre">Kernel</span></code>. A non-sharing  <code class="docutils literal"><span class="pre">OpKernel</span></code> example can be seen in <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/cross_entropy_op.h#L43"><code class="docutils literal"><span class="pre">OnehotCrossEntropyOpKernel</span></code></a>.</p>
T
Deploy to GitHub Pages: e93e997176bdb71400c85efd1b39e5b868ba806a  
Travis CI 已提交
368 
<p>To ease the writing of <code class="docutils literal"><span class="pre">OpKernel</span></code> compute, and for reusing code cross-device, <a class="reference external" href="https://bitbucket.org/eigen/eigen/src/default/unsupported/Eigen/CXX11/src/Tensor/README.md?fileviewer=file-view-default"><code class="docutils literal"><span class="pre">Eigen-unsupported</span> <span class="pre">Tensor</span></code></a> module is used to implement <code class="docutils literal"><span class="pre">Compute</span></code> interface. To learn about how the Eigen library is used in PaddlePaddle, please see <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/doc/howto/dev/use_eigen_cn.md">usage document</a>.</p>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
369 370 371 372 373 374 375 376 377 
<p>This concludes the forward implementation of an operator. Next its operation and kernel need to be registered in a <code class="docutils literal"><span class="pre">.cc</span></code> file.</p>
<p>The definition of its corresponding backward operator, if applicable, is similar to that of an forward operator. <strong>Note that a backward operator does not include a <code class="docutils literal"><span class="pre">ProtoMaker</span></code></strong>.</p>
</div>
<div class="section" id="registering-operator">
<span id="registering-operator"></span><h3>4. Registering Operator<a class="headerlink" href="#registering-operator" title="Permalink to this headline"></a></h3>
<ul>
<li><p class="first">In <code class="docutils literal"><span class="pre">.cc</span></code> files, register forward and backward operator classes and the CPU kernel.</p>
<div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="k">namespace</span> <span class="n">ops</span> <span class="o">=</span> <span class="n">paddle</span><span class="o">::</span><span class="n">operators</span><span class="p">;</span>
<span class="n">REGISTER_OP</span><span class="p">(</span><span class="n">mul</span><span class="p">,</span> <span class="n">ops</span><span class="o">::</span><span class="n">MulOp</span><span class="p">,</span> <span class="n">ops</span><span class="o">::</span><span class="n">MulOpMaker</span><span class="p">,</span> <span class="n">mul_grad</span><span class="p">,</span> <span class="n">ops</span><span class="o">::</span><span class="n">MulOpGrad</span><span class="p">);</span>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
378 
<span class="n">REGISTER_OP_CPU_KERNEL</span><span class="p">(</span><span class="n">mul</span><span class="p">,</span> <span class="n">ops</span><span class="o">::</span><span class="n">MulKernel</span><span class="o">&lt;</span><span class="n">paddle</span><span class="o">::</span><span class="n">platform</span><span class="o">::</span><span class="n">CPUDeviceContext</span><span class="p">,</span> <span class="kt">float</span><span class="o">&gt;</span><span class="p">);</span>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
379 
<span class="n">REGISTER_OP_CPU_KERNEL</span><span class="p">(</span><span class="n">mul_grad</span><span class="p">,</span>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
380 
              <span class="n">ops</span><span class="o">::</span><span class="n">MulGradKernel</span><span class="o">&lt;</span><span class="n">paddle</span><span class="o">::</span><span class="n">platform</span><span class="o">::</span><span class="n">CPUDeviceContext</span><span class="p">,</span> <span class="kt">float</span><span class="o">&gt;</span><span class="p">);</span>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
381 382 383 384 385 386 
</pre></div>
</div>
<p>In that code block,</p>
<ul class="simple">
<li><code class="docutils literal"><span class="pre">REGISTER_OP</span></code> registers the <code class="docutils literal"><span class="pre">ops::MulOp</span></code> class, type named <code class="docutils literal"><span class="pre">mul</span></code>, its type <code class="docutils literal"><span class="pre">ProtoMaker</span></code> is <code class="docutils literal"><span class="pre">ops::MulOpMaker</span></code>, registering <code class="docutils literal"><span class="pre">ops::MulOpGrad</span></code> as <code class="docutils literal"><span class="pre">mul_grad</span></code>.</li>
<li><code class="docutils literal"><span class="pre">REGISTER_OP_WITHOUT_GRADIENT</span></code> registers an operator without gradient.</li>
T
Deploy to GitHub Pages: a80e0100e5b90da2046579e3e4cedcf567b78fb0  
Travis CI 已提交
387 
<li><code class="docutils literal"><span class="pre">REGISTER_OP_CPU_KERNEL</span></code> registers <code class="docutils literal"><span class="pre">ops::MulKernel</span></code> class and specialized template types <code class="docutils literal"><span class="pre">paddle::platform::CPUPlace</span></code> and <code class="docutils literal"><span class="pre">float</span></code>, which also registers <code class="docutils literal"><span class="pre">ops::MulGradKernel</span></code>.</li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
388 389 390 391 
</ul>
</li>
</ul>
<ul>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
392 
<li><p class="first">Registering CUDA Kernel in <code class="docutils literal"><span class="pre">.cu</span></code> files</p>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
393 
<ul class="simple">
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
394 
<li>Note that if CUDA Kernel is implemented using the <code class="docutils literal"><span class="pre">Eigen</span> <span class="pre">unsupported</span></code> module, then on top of <code class="docutils literal"><span class="pre">.cu</span></code>, a macro definition <code class="docutils literal"><span class="pre">#define</span> <span class="pre">EIGEN_USE_GPU</span></code> is needed, such as</li>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
395 396 397 398 399 
</ul>
<div class="highlight-cpp"><div class="highlight"><pre><span></span><span class="c1">// if use Eigen unsupported module before include head files</span>
<span class="cp">#define EIGEN_USE_GPU</span>

<span class="k">namespace</span> <span class="n">ops</span> <span class="o">=</span> <span class="n">paddle</span><span class="o">::</span><span class="n">operators</span><span class="p">;</span>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
400 401 402 
<span class="n">REGISTER_OP_CUDA_KERNEL</span><span class="p">(</span><span class="n">mul</span><span class="p">,</span> <span class="n">ops</span><span class="o">::</span><span class="n">MulKernel</span><span class="o">&lt;</span><span class="n">paddle</span><span class="o">::</span><span class="n">platform</span><span class="o">::</span><span class="n">CUDADeviceContext</span><span class="p">,</span> <span class="kt">float</span><span class="o">&gt;</span><span class="p">);</span>
<span class="n">REGISTER_OP_CUDA_KERNEL</span><span class="p">(</span><span class="n">mul_grad</span><span class="p">,</span>
                       <span class="n">ops</span><span class="o">::</span><span class="n">MulGradKernel</span><span class="o">&lt;</span><span class="n">paddle</span><span class="o">::</span><span class="n">platform</span><span class="o">::</span><span class="n">CUDADeviceContext</span><span class="p">,</span> <span class="kt">float</span><span class="o">&gt;</span><span class="p">);</span>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 
</pre></div>
</div>
</li>
</ul>
</div>
<div class="section" id="compilation">
<span id="compilation"></span><h3>5. Compilation<a class="headerlink" href="#compilation" title="Permalink to this headline"></a></h3>
<p>Run the following commands to compile.</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">make</span> <span class="n">mul_op</span>
</pre></div>
</div>
</div>
</div>
<div class="section" id="python-binding">
<span id="python-binding"></span><h2>Python Binding<a class="headerlink" href="#python-binding" title="Permalink to this headline"></a></h2>
<p>The system will automatically bind to Python and link it to a generated library.</p>
</div>
<div class="section" id="unit-tests">
<span id="unit-tests"></span><h2>Unit Tests<a class="headerlink" href="#unit-tests" title="Permalink to this headline"></a></h2>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
422 423 424 425 426 427 428 429 430 431 432 433 434 
<p>Unit tests for an operator include</p>
<ol class="simple">
<li>comparing a forward operator&#8217;s implementations on different devices,</li>
<li>comparing a backward operator&#8217;s implementation on different devices, and</li>
<li>a scaling test for the backward operator.</li>
</ol>
<p>Here, we introduce the <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/v2/framework/tests/test_mul_op.py">unit tests for <code class="docutils literal"><span class="pre">MulOp</span></code></a>.</p>
<div class="section" id="testing-forward-operators">
<span id="testing-forward-operators"></span><h3>Testing Forward Operators<a class="headerlink" href="#testing-forward-operators" title="Permalink to this headline"></a></h3>
<p>A forward operator unit test inherits <code class="docutils literal"><span class="pre">unittest.TestCase</span></code> and defines metaclass <code class="docutils literal"><span class="pre">__metaclass__</span> <span class="pre">=</span> <span class="pre">OpTestMeta</span></code>. More concrete tests are performed in <code class="docutils literal"><span class="pre">OpTestMeta</span></code>. Testing a forward operator requires the following:</p>
<ol class="simple">
<li>Defining input, output and relevant attributes in <code class="docutils literal"><span class="pre">setUp</span></code> method.</li>
<li>Generating random input data.</li>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
435 436 
<li>Implementing the same computation logic in a Python script.</li>
<li>Call check gradient function to check the backward operator.</li>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
437 438 439 
</ol>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">unittest</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
440 
<span class="kn">from</span> <span class="nn">op_test</span> <span class="kn">import</span> <span class="n">OpTest</span>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
441 442
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
443 
<span class="k">class</span> <span class="nc">TestMulOp</span><span class="p">(</span><span class="n">OpTest</span><span class="p">):</span>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
444 
    <span class="k">def</span> <span class="nf">setUp</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
445 
        <span class="bp">self</span><span class="o">.</span><span class="n">op_type</span> <span class="o">=</span> <span class="s2">&quot;mul&quot;</span>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
446 447 448 449 450 451 
        <span class="bp">self</span><span class="o">.</span><span class="n">inputs</span> <span class="o">=</span> <span class="p">{</span>
            <span class="s1">&#39;X&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">random</span><span class="p">((</span><span class="mi">32</span><span class="p">,</span> <span class="mi">84</span><span class="p">))</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s2">&quot;float32&quot;</span><span class="p">),</span>
            <span class="s1">&#39;Y&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">random</span><span class="p">((</span><span class="mi">84</span><span class="p">,</span> <span class="mi">100</span><span class="p">))</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s2">&quot;float32&quot;</span><span class="p">)</span>
        <span class="p">}</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">outputs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;Out&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">inputs</span><span class="p">[</span><span class="s1">&#39;X&#39;</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">inputs</span><span class="p">[</span><span class="s1">&#39;Y&#39;</span><span class="p">])}</span>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
452 453 454 
    <span class="k">def</span> <span class="nf">test_check_output</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_output</span><span class="p">()</span>
T
Deploy to GitHub Pages: e82fda25213872caa49021f4fa4d67031e581cff  
Travis CI 已提交
455 456 
    <span class="k">def</span> <span class="nf">test_check_grad_normal</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_grad</span><span class="p">([</span><span class="s1">&#39;X&#39;</span><span class="p">,</span> <span class="s1">&#39;Y&#39;</span><span class="p">],</span> <span class="s1">&#39;Out&#39;</span><span class="p">,</span> <span class="n">max_relative_error</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
457
T
Deploy to GitHub Pages: e82fda25213872caa49021f4fa4d67031e581cff  
Travis CI 已提交
458 
    <span class="k">def</span> <span class="nf">test_check_grad_ingore_x</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
459 
        <span class="bp">self</span><span class="o">.</span><span class="n">check_grad</span><span class="p">(</span>
T
Deploy to GitHub Pages: e82fda25213872caa49021f4fa4d67031e581cff  
Travis CI 已提交
460 
            <span class="p">[</span><span class="s1">&#39;Y&#39;</span><span class="p">],</span> <span class="s1">&#39;Out&#39;</span><span class="p">,</span> <span class="n">max_relative_error</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">no_grad_set</span><span class="o">=</span><span class="nb">set</span><span class="p">(</span><span class="s2">&quot;X&quot;</span><span class="p">))</span>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
461
T
Deploy to GitHub Pages: e82fda25213872caa49021f4fa4d67031e581cff  
Travis CI 已提交
462 
    <span class="k">def</span> <span class="nf">test_check_grad_ingore_y</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
463 
        <span class="bp">self</span><span class="o">.</span><span class="n">check_grad</span><span class="p">(</span>
T
Deploy to GitHub Pages: e82fda25213872caa49021f4fa4d67031e581cff  
Travis CI 已提交
464 
            <span class="p">[</span><span class="s1">&#39;X&#39;</span><span class="p">],</span> <span class="s1">&#39;Out&#39;</span><span class="p">,</span> <span class="n">max_relative_error</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">no_grad_set</span><span class="o">=</span><span class="nb">set</span><span class="p">(</span><span class="s1">&#39;Y&#39;</span><span class="p">))</span>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
465
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
466 467 
</pre></div>
</div>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
468 469 470 471 472 473 474 475 
<p>Get its output, and compare it with the forward operator&#8217;s own output.</p>
<p>The code above first loads required packages. In addition, we have</p>
<ul class="simple">
<li><code class="docutils literal"><span class="pre">self.op_type</span> <span class="pre">=</span> <span class="pre">&quot;mul&quot;</span></code> defines the type that is identical to what the operator&#8217;s registered type.</li>
<li><code class="docutils literal"><span class="pre">self.inputs</span></code> defines input, with type <code class="docutils literal"><span class="pre">numpy.array</span></code> and initializes it.</li>
<li><code class="docutils literal"><span class="pre">self.outputs</span></code> defines output and completes the same operator computation in the Python script, and returns its result from the Python script.</li>
</ul>
<p>Some key points in checking gradient above include:</p>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
476 477 
<ul class="simple">
<li><code class="docutils literal"><span class="pre">test_normal</span></code> calls <code class="docutils literal"><span class="pre">check_grad</span></code> to validate scaling tests&#8217; correctness and stability through numeric methods.<ul>
T
Deploy to GitHub Pages: e82fda25213872caa49021f4fa4d67031e581cff  
Travis CI 已提交
478 479 480 
<li>The first variable <code class="docutils literal"><span class="pre">[&quot;X&quot;,</span> <span class="pre">&quot;Y&quot;]</span></code> appoints <code class="docutils literal"><span class="pre">X</span></code> and <code class="docutils literal"><span class="pre">Y</span></code> to be scale tested.</li>
<li>The second variable <code class="docutils literal"><span class="pre">&quot;Out&quot;</span></code> points to the network&#8217;s final output target <code class="docutils literal"><span class="pre">Out</span></code>.</li>
<li>The third variable <code class="docutils literal"><span class="pre">max_relative_error</span></code> points to the maximum relative tolerance error during scaling tests.</li>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
481 482 
</ul>
</li>
T
Deploy to GitHub Pages: e82fda25213872caa49021f4fa4d67031e581cff  
Travis CI 已提交
483 
<li><code class="docutils literal"><span class="pre">test_check_grad_ingore_x</span></code> and <code class="docutils literal"><span class="pre">test_check_grad_ingore_y</span></code>branches test the cases where there is only one scaling input.</li>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 
</ul>
</div>
<div class="section" id="compiling-and-running">
<span id="compiling-and-running"></span><h3>Compiling and Running<a class="headerlink" href="#compiling-and-running" title="Permalink to this headline"></a></h3>
<p>Any new unit testing file of the format <code class="docutils literal"><span class="pre">test_*.py</span></code>  added to the director <code class="docutils literal"><span class="pre">python/paddle/v2/framework/tests</span></code> is automatically added to the project to compile.</p>
<p>Note that <strong>unlike the compile test for Ops, running unit tests requires compiling the entire project</strong> and requires compiling with flag <code class="docutils literal"><span class="pre">WITH_TESTING</span></code> on i.e. <code class="docutils literal"><span class="pre">cmake</span> <span class="pre">paddle_dir</span> <span class="pre">-DWITH_TESTING=ON</span></code>.</p>
<p>After successfully compiling the project, run the following command to run unit tests:</p>
<div class="highlight-bash"><div class="highlight"><pre><span></span>make <span class="nb">test</span> <span class="nv">ARGS</span><span class="o">=</span><span class="s2">&quot;-R test_mul_op -V&quot;</span>
</pre></div>
</div>
<p>Or,</p>
<div class="highlight-bash"><div class="highlight"><pre><span></span>ctest -R test_mul_op
</pre></div>
</div>
</div>
</div>
<div class="section" id="remarks">
<span id="remarks"></span><h2>Remarks<a class="headerlink" href="#remarks" title="Permalink to this headline"></a></h2>
<ul class="simple">
<li>Every <code class="docutils literal"><span class="pre">*_op.h</span></code> (if applicable), <code class="docutils literal"><span class="pre">*_op.cc</span></code>, and <code class="docutils literal"><span class="pre">*_op.cu</span></code> (if applicable) must be created for a unique Op. Compiling will fail if multiple operators are included per file.</li>
<li>The type with which an operator is registered needs to be identical to the Op&#8217;s name. Registering <code class="docutils literal"><span class="pre">REGISTER_OP(B,</span> <span class="pre">...)</span></code> in <code class="docutils literal"><span class="pre">A_op.cc</span></code> will cause unit testing failures.</li>
T
Deploy to GitHub Pages: de8c4627776b2b9a60dbcc64c48e858c80a2715f  
Travis CI 已提交
505 
<li>If the operator does not implement a CUDA kernel, please refrain from creating an empty <code class="docutils literal"><span class="pre">*_op.cu</span></code> file, or else unit tests will fail.</li>
T
Deploy to GitHub Pages: 369947560b21fa2b5e9c3248f967b2fbc4218c6c  
Travis CI 已提交
506 507 
<li>If multiple operators rely on some shared methods, a file NOT named <code class="docutils literal"><span class="pre">*_op.*</span></code> can be created to store them, such as <code class="docutils literal"><span class="pre">gather.h</span></code>.</li>
</ul>
T
Deploy to GitHub Pages: 17827d7e6124102b447bf90f7274356dd91fa9fc  
Travis CI 已提交
508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 
</div>
</div>


           </div>
          </div>
          <footer>
  

  <hr/>

  <div role="contentinfo">
    <p>
        &copy; Copyright 2016, PaddlePaddle developers.

    </p>
  </div>
  Built with <a href="http://sphinx-doc.org/">Sphinx</a> using a <a href="https://github.com/snide/sphinx_rtd_theme">theme</a> provided by <a href="https://readthedocs.org">Read the Docs</a>. 

</footer>

        </div>
      </div>

    </section>

  </div>
  


  

    <script type="text/javascript">
        var DOCUMENTATION_OPTIONS = {
            URL_ROOT:'../../',
            VERSION:'',
            COLLAPSE_INDEX:false,
            FILE_SUFFIX:'.html',
            HAS_SOURCE:  true,
            SOURCELINK_SUFFIX: ".txt",
        };
    </script>
      <script type="text/javascript" src="../../_static/jquery.js"></script>
      <script type="text/javascript" src="../../_static/underscore.js"></script>
      <script type="text/javascript" src="../../_static/doctools.js"></script>
      <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
       
  

  
  
    <script type="text/javascript" src="../../_static/js/theme.js"></script>
  
  
  <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha384-Tc5IQib027qvyjSMfHjOMaLkfuWVxZxUPnCJA7l2mCWNIpG9mGCD8wGNIcPD7Txa" crossorigin="anonymous"></script>
  <script src="https://cdn.jsdelivr.net/perfect-scrollbar/0.6.14/js/perfect-scrollbar.jquery.min.js"></script>
  <script src="../../_static/js/paddle_doc_init.js"></script> 

</body>
</html>