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
block.html 48.2 KB
Newer Older
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
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 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 


<!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>Design Doc: Block and Scope &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="../howto/index_en.html">HOW TO</a></li>
<li class="toctree-l1"><a class="reference internal" href="../api/index_en.html">API</a></li>
</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>
<li class="toctree-l3"><a class="reference internal" href="../getstarted/build_and_install/docker_install_en.html">PaddlePaddle in Docker Containers</a></li>
<li class="toctree-l3"><a class="reference internal" href="../getstarted/build_and_install/build_from_source_en.html">Installing from Sources</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../howto/index_en.html">HOW TO</a><ul>
<li class="toctree-l2"><a class="reference internal" href="../howto/usage/cmd_parameter/index_en.html">Set Command-line Parameters</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../howto/usage/cmd_parameter/use_case_en.html">Use Case</a></li>
<li class="toctree-l3"><a class="reference internal" href="../howto/usage/cmd_parameter/arguments_en.html">Argument Outline</a></li>
<li class="toctree-l3"><a class="reference internal" href="../howto/usage/cmd_parameter/detail_introduction_en.html">Detail Description</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../howto/usage/cluster/cluster_train_en.html">Run Distributed Training</a></li>
<li class="toctree-l2"><a class="reference internal" href="../howto/usage/k8s/k8s_en.html">Paddle On Kubernetes</a></li>
<li class="toctree-l2"><a class="reference internal" href="../howto/usage/k8s/k8s_aws_en.html">Distributed PaddlePaddle Training on AWS with Kubernetes</a></li>
<li class="toctree-l2"><a class="reference internal" href="../howto/dev/build_en.html">Build PaddlePaddle from Source Code and Run Unit Test</a></li>
<li class="toctree-l2"><a class="reference internal" href="../howto/dev/new_layer_en.html">Write New Layers</a></li>
<li class="toctree-l2"><a class="reference internal" href="../howto/dev/contribute_to_paddle_en.html">Contribute Code</a></li>
<li class="toctree-l2"><a class="reference internal" href="../howto/deep_model/rnn/index_en.html">RNN Models</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../howto/deep_model/rnn/rnn_config_en.html">RNN Configuration</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../howto/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>
<li class="toctree-l2"><a class="reference internal" href="../api/v2/data.html">Data Reader Interface and DataSets</a></li>
<li class="toctree-l2"><a class="reference internal" href="../api/v2/run_logic.html">Training and Inference</a></li>
</ul>
</li>
</ul>

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

      

 







<div role="navigation" aria-label="breadcrumbs navigation">
  <ul class="wy-breadcrumbs">
      
    <li>Design Doc: Block and Scope</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="design-doc-block-and-scope">
<span id="design-doc-block-and-scope"></span><h1>Design Doc: Block and Scope<a class="headerlink" href="#design-doc-block-and-scope" title="Permalink to this headline"></a></h1>
<div class="section" id="the-representation-of-computation">
<span id="the-representation-of-computation"></span><h2>The Representation of Computation<a class="headerlink" href="#the-representation-of-computation" title="Permalink to this headline"></a></h2>
<p>Both deep learning systems and programming languages help users describe computation procedures.  These systems use various representations of computation:</p>
<ul class="simple">
<li>Caffe, Torch, and Paddle: sequences of layers.</li>
<li>TensorFlow, Caffe2, Mxnet: graphs of operators.</li>
<li>PaddlePaddle: nested blocks, like C++ and Java programs.</li>
</ul>
</div>
<div class="section" id="block-in-programming-languages-and-deep-learning">
<span id="block-in-programming-languages-and-deep-learning"></span><h2>Block in Programming Languages and Deep Learning<a class="headerlink" href="#block-in-programming-languages-and-deep-learning" title="Permalink to this headline"></a></h2>
<p>In programming languages, a block is a pair of curly braces that includes local variables definitions and a sequence of instructions, or operators.</p>
<p>Blocks work with control flow structures like <code class="docutils literal"><span class="pre">if</span></code>, <code class="docutils literal"><span class="pre">else</span></code>, and <code class="docutils literal"><span class="pre">for</span></code>, which have equivalents in deep learning:</p>
<p>| programming languages | PaddlePaddle          |
|&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;|&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;|
| for, while loop       | RNN, WhileOp          |
| if, if-else, switch   | IfElseOp, SwitchOp    |
| sequential execution  | a sequence of layers  |</p>
<p>A key difference is that a C++ program describes a one pass computation, whereas a deep learning program describes both the forward and backward passes.</p>
</div>
<div class="section" id="stack-frames-and-the-scope-hierarchy">
<span id="stack-frames-and-the-scope-hierarchy"></span><h2>Stack Frames and the Scope Hierarchy<a class="headerlink" href="#stack-frames-and-the-scope-hierarchy" title="Permalink to this headline"></a></h2>
<p>The existence of the backward makes the execution of a block of traditional programs and PaddlePaddle different to each other:</p>
<p>| programming languages | PaddlePaddle                  |
|&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;|&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;-|
| stack                 | scope hierarchy               |
| stack frame           | scope                         |
| push at entering block| push at entering block        |
| pop at leaving block  | destroy at minibatch completes|</p>
<ol class="simple">
<li>In traditional programs:<ul>
<li>When the execution enters the left curly brace of a block, the runtime pushes a frame into the stack, where it realizes local variables.</li>
<li>After the execution leaves the right curly brace, the runtime pops the frame.</li>
<li>The maximum number of frames in the stack is the maximum depth of nested blocks.</li>
</ul>
</li>
<li>In PaddlePaddle<ul>
<li>When the execution enters a block, PaddlePaddle adds a new scope, where it realizes variables.</li>
<li>PaddlePaddle doesn&#8217;t pop a scope after the execution of the block because variables therein are to be used by the backward pass.  So it has a stack forest known as a <em>scope hierarchy</em>.</li>
<li>The height of the highest tree is the maximum depth of nested blocks.</li>
<li>After the process of a minibatch, PaddlePaddle destroys the scope hierarchy.</li>
</ul>
</li>
</ol>
</div>
<div class="section" id="use-blocks-in-c-and-paddlepaddle-programs">
<span id="use-blocks-in-c-and-paddlepaddle-programs"></span><h2>Use Blocks in C++ and PaddlePaddle Programs<a class="headerlink" href="#use-blocks-in-c-and-paddlepaddle-programs" title="Permalink to this headline"></a></h2>
<p>Let us consolidate the discussion by presenting some examples.</p>
<div class="section" id="blocks-with-if-else-and-ifelseop">
<span id="blocks-with-if-else-and-ifelseop"></span><h3>Blocks with <code class="docutils literal"><span class="pre">if-else</span></code> and <code class="docutils literal"><span class="pre">IfElseOp</span></code><a class="headerlink" href="#blocks-with-if-else-and-ifelseop" title="Permalink to this headline"></a></h3>
<p>The following C++ programs shows how blocks are used with the <code class="docutils literal"><span class="pre">if-else</span></code> structure:</p>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
233 234 235 236 237 
<div class="highlight-c++"><div class="highlight"><pre><span></span><span class="k">namespace</span> <span class="n">pd</span> <span class="o">=</span> <span class="n">paddle</span><span class="p">;</span>

<span class="kt">int</span> <span class="n">x</span> <span class="o">=</span> <span class="mi">10</span><span class="p">;</span>
<span class="kt">int</span> <span class="n">y</span> <span class="o">=</span> <span class="mi">1</span><span class="p">;</span>
<span class="kt">int</span> <span class="n">z</span> <span class="o">=</span> <span class="mi">10</span><span class="p">;</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
238 
<span class="kt">bool</span> <span class="n">cond</span> <span class="o">=</span> <span class="nb">false</span><span class="p">;</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
239 
<span class="kt">int</span> <span class="n">o1</span><span class="p">,</span> <span class="n">o2</span><span class="p">;</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
240 241 
<span class="k">if</span> <span class="p">(</span><span class="n">cond</span><span class="p">)</span> <span class="p">{</span>
  <span class="kt">int</span> <span class="n">z</span> <span class="o">=</span> <span class="n">x</span> <span class="o">+</span> <span class="n">y</span><span class="p">;</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
242 243 
  <span class="n">o1</span> <span class="o">=</span> <span class="n">z</span><span class="p">;</span>
  <span class="n">o2</span> <span class="o">=</span> <span class="n">pd</span><span class="o">::</span><span class="n">layer</span><span class="o">::</span><span class="n">softmax</span><span class="p">(</span><span class="n">z</span><span class="p">);</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
244 
<span class="p">}</span> <span class="k">else</span> <span class="p">{</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
245 246 247 
  <span class="kt">int</span> <span class="n">d</span> <span class="o">=</span> <span class="n">pd</span><span class="o">::</span><span class="n">layer</span><span class="o">::</span><span class="n">fc</span><span class="p">(</span><span class="n">z</span><span class="p">);</span>
  <span class="n">o1</span> <span class="o">=</span> <span class="n">d</span><span class="p">;</span>
  <span class="n">o2</span> <span class="o">=</span> <span class="n">d</span><span class="o">+</span><span class="mi">1</span><span class="p">;</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
248 249 250 251 252 253 
<span class="p">}</span>
</pre></div>
</div>
<p>An equivalent PaddlePaddle program from the design doc of the <a class="reference internal" href="if_else_op.html"><span class="doc">IfElseOp operator</span></a> is as follows:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">paddle</span> <span class="kn">as</span> <span class="nn">pd</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
254 255 256 257 258 259 
<span class="n">x</span> <span class="o">=</span> <span class="n">minibatch</span><span class="p">([</span><span class="mi">10</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">30</span><span class="p">])</span> <span class="c1"># shape=[None, 1]</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">var</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="c1"># shape=[1], value=1</span>
<span class="n">z</span> <span class="o">=</span> <span class="n">minibatch</span><span class="p">([</span><span class="mi">10</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">30</span><span class="p">])</span> <span class="c1"># shape=[None, 1]</span>
<span class="n">cond</span> <span class="o">=</span> <span class="n">larger_than</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="mi">15</span><span class="p">)</span> <span class="c1"># [false, true, true]</span>

<span class="n">ie</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">ifelse</span><span class="p">()</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
260 
<span class="k">with</span> <span class="n">ie</span><span class="o">.</span><span class="n">true_block</span><span class="p">():</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
261 262 
    <span class="n">d</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">layer</span><span class="o">.</span><span class="n">add_scalar</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
    <span class="n">ie</span><span class="o">.</span><span class="n">output</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">layer</span><span class="o">.</span><span class="n">softmax</span><span class="p">(</span><span class="n">d</span><span class="p">))</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
263 
<span class="k">with</span> <span class="n">ie</span><span class="o">.</span><span class="n">false_block</span><span class="p">():</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
264 265 266 
    <span class="n">d</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">layer</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
    <span class="n">ie</span><span class="o">.</span><span class="n">output</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">d</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span>
<span class="n">o1</span><span class="p">,</span> <span class="n">o2</span> <span class="o">=</span> <span class="n">ie</span><span class="p">(</span><span class="n">cond</span><span class="p">)</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
267 268 
</pre></div>
</div>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
269 
<p>In both examples, the left branch computes <code class="docutils literal"><span class="pre">x+y</span></code> and <code class="docutils literal"><span class="pre">softmax(x+y)</span></code>, the right branch computes <code class="docutils literal"><span class="pre">x+1</span></code> and <code class="docutils literal"><span class="pre">fc(x)</span></code>.</p>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
270 271 272 273 274 
<p>A difference is that variables in the C++ program contain scalar values, whereas those in the PaddlePaddle programs are mini-batches of instances.  The <code class="docutils literal"><span class="pre">ie.input(true,</span> <span class="pre">0)</span></code> invocation returns instances in the 0-th input, <code class="docutils literal"><span class="pre">x</span></code>, that corresponds to true values in <code class="docutils literal"><span class="pre">cond</span></code> as the local variable <code class="docutils literal"><span class="pre">x</span></code>, where <code class="docutils literal"><span class="pre">ie.input(false,</span> <span class="pre">0)</span></code> returns instances corresponding to false values.</p>
</div>
<div class="section" id="blocks-with-for-and-rnnop">
<span id="blocks-with-for-and-rnnop"></span><h3>Blocks with <code class="docutils literal"><span class="pre">for</span></code> and <code class="docutils literal"><span class="pre">RNNOp</span></code><a class="headerlink" href="#blocks-with-for-and-rnnop" title="Permalink to this headline"></a></h3>
<p>The following RNN model from the <a class="reference external" href="design/rnn.md">RNN design doc</a></p>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">x</span> <span class="o">=</span> <span class="n">sequence</span><span class="p">([</span><span class="mi">10</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">30</span><span class="p">])</span> <span class="c1"># shape=[None, 1]</span>
<span class="n">m</span> <span class="o">=</span> <span class="n">var</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># shape=[1]</span>
<span class="n">W</span> <span class="o">=</span> <span class="n">var</span><span class="p">(</span><span class="mf">0.314</span><span class="p">,</span> <span class="n">param</span><span class="o">=</span><span class="n">true</span><span class="p">)</span> <span class="c1"># shape=[1]</span>
<span class="n">U</span> <span class="o">=</span> <span class="n">var</span><span class="p">(</span><span class="mf">0.375</span><span class="p">,</span> <span class="n">param</span><span class="o">=</span><span class="n">true</span><span class="p">)</span> <span class="c1"># shape=[1]</span>

<span class="n">rnn</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">rnn</span><span class="p">()</span>
<span class="k">with</span> <span class="n">rnn</span><span class="o">.</span><span class="n">step</span><span class="p">():</span>
  <span class="n">h</span> <span class="o">=</span> <span class="n">rnn</span><span class="o">.</span><span class="n">memory</span><span class="p">(</span><span class="n">init</span> <span class="o">=</span> <span class="n">m</span><span class="p">)</span>
  <span class="n">hh</span> <span class="o">=</span> <span class="n">rnn</span><span class="o">.</span><span class="n">previous_memory</span><span class="p">(</span><span class="n">h</span><span class="p">)</span>
  <span class="n">a</span> <span class="o">=</span> <span class="n">layer</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">W</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span>
  <span class="n">b</span> <span class="o">=</span> <span class="n">layer</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">U</span><span class="p">,</span> <span class="n">hh</span><span class="p">)</span>  
  <span class="n">s</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>
  <span class="n">act</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">sigmoid</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
  <span class="n">rnn</span><span class="o">.</span><span class="n">update_memory</span><span class="p">(</span><span class="n">h</span><span class="p">,</span> <span class="n">act</span><span class="p">)</span>
  <span class="n">rnn</span><span class="o">.</span><span class="n">output</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
290 291 292 293 294 
<span class="n">o1</span><span class="p">,</span> <span class="n">o2</span> <span class="o">=</span> <span class="n">rnn</span><span class="p">()</span>
</pre></div>
</div>
<p>has its equivalent C++ program as follows</p>
<div class="highlight-c++"><div class="highlight"><pre><span></span><span class="kt">int</span><span class="o">*</span> <span class="n">x</span> <span class="o">=</span> <span class="p">{</span><span class="mi">10</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">30</span><span class="p">};</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
295 296 297 
<span class="kt">int</span><span class="o">*</span> <span class="n">m</span> <span class="o">=</span> <span class="p">{</span><span class="mi">0</span><span class="p">};</span>
<span class="kt">int</span><span class="o">*</span> <span class="n">W</span> <span class="o">=</span> <span class="p">{</span><span class="mf">0.314</span><span class="p">};</span>
<span class="kt">int</span><span class="o">*</span> <span class="n">U</span> <span class="o">=</span> <span class="p">{</span><span class="mf">0.375</span><span class="p">};</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
298 299 300 301 302 303 304 

<span class="kt">int</span> <span class="n">mem</span><span class="p">[</span><span class="k">sizeof</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">/</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span> <span class="mi">1</span><span class="p">];</span>
<span class="kt">int</span> <span class="n">o1</span><span class="p">[</span><span class="k">sizeof</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">/</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span> <span class="mi">1</span><span class="p">];</span>
<span class="kt">int</span> <span class="n">o2</span><span class="p">[</span><span class="k">sizeof</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">/</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span> <span class="mi">1</span><span class="p">];</span>
<span class="k">for</span> <span class="p">(</span><span class="kt">int</span> <span class="n">i</span> <span class="o">=</span> <span class="mi">1</span><span class="p">;</span> <span class="n">i</span> <span class="o">&lt;=</span> <span class="k">sizeof</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">/</span><span class="k">sizeof</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]);</span> <span class="o">++</span><span class="n">i</span><span class="p">)</span> <span class="p">{</span>
  <span class="kt">int</span> <span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">];</span>
  <span class="k">if</span> <span class="p">(</span><span class="n">i</span> <span class="o">==</span> <span class="mi">1</span><span class="p">)</span> <span class="n">mem</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">m</span><span class="p">;</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
305 306 307 
  <span class="kt">int</span> <span class="n">a</span> <span class="o">=</span> <span class="n">W</span> <span class="o">*</span> <span class="n">x</span><span class="p">;</span>
  <span class="kt">int</span> <span class="n">b</span> <span class="o">=</span> <span class="n">Y</span> <span class="o">*</span> <span class="n">mem</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">];</span>
  <span class="kt">int</span> <span class="n">s</span> <span class="o">=</span> <span class="n">fc_out</span> <span class="o">+</span> <span class="n">hidden_out</span><span class="p">;</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 
  <span class="kt">int</span> <span class="n">act</span> <span class="o">=</span> <span class="n">sigmoid</span><span class="p">(</span><span class="n">sum</span><span class="p">);</span>
  <span class="n">mem</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">act</span><span class="p">;</span>
  <span class="n">o1</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">act</span><span class="p">;</span>
  <span class="n">o2</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">hidden_out</span><span class="p">;</span>
<span class="p">}</span>
</pre></div>
</div>
</div>
</div>
<div class="section" id="compilation-and-execution">
<span id="compilation-and-execution"></span><h2>Compilation and Execution<a class="headerlink" href="#compilation-and-execution" title="Permalink to this headline"></a></h2>
<p>Like TensorFlow programs, a PaddlePaddle program is written in Python.  The first part describes a neural network as a protobuf message, and the rest part executes the message for training or inference.</p>
<p>The generation of this protobuf message is like what a compiler generates a binary executable file.  The execution of the message that the OS executes the binary file.</p>
</div>
<div class="section" id="the-binary-executable-file-format">
<span id="the-binary-executable-file-format"></span><h2>The &#8220;Binary Executable File Format&#8221;<a class="headerlink" href="#the-binary-executable-file-format" title="Permalink to this headline"></a></h2>
<p>The definition of the protobuf message is as follows:</p>
<div class="highlight-protobuf"><div class="highlight"><pre><span></span><span class="kd">message</span> <span class="nc">BlockDesc</span> <span class="p">{</span>
  <span class="k">repeated</span> <span class="n">VarDesc</span> <span class="na">vars</span> <span class="o">=</span> <span class="mi">1</span><span class="p">;</span>
  <span class="k">repeated</span> <span class="n">OpDesc</span> <span class="na">ops</span> <span class="o">=</span> <span class="mi">2</span><span class="p">;</span>
<span class="p">}</span>
</pre></div>
</div>
<p>The step net in above RNN example would look like</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">BlockDesc</span> <span class="p">{</span>
  <span class="nb">vars</span> <span class="o">=</span> <span class="p">{</span>
    <span class="n">VarDesc</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span> <span class="o">//</span> <span class="n">x</span>
    <span class="n">VarDesc</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span> <span class="o">//</span> <span class="n">h</span>
    <span class="n">VarDesc</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span> <span class="o">//</span> <span class="n">fc_out</span>
    <span class="n">VarDesc</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span> <span class="o">//</span> <span class="n">hidden_out</span>
    <span class="n">VarDesc</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span> <span class="o">//</span> <span class="nb">sum</span>
    <span class="n">VarDesc</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span> <span class="o">//</span> <span class="n">act</span>
  <span class="p">}</span>
  <span class="n">ops</span> <span class="o">=</span> <span class="p">{</span>
    <span class="n">OpDesc</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span> <span class="o">//</span> <span class="n">matmul</span>
    <span class="n">OpDesc</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span> <span class="o">//</span> <span class="n">add_two</span>
    <span class="n">OpDesc</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span> <span class="o">//</span> <span class="n">sigmoid</span>
  <span class="p">}</span>
<span class="p">};</span>
</pre></div>
</div>
<p>Also, the RNN operator in above example is serialized into a protobuf message of type <code class="docutils literal"><span class="pre">OpDesc</span></code> and would look like:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">OpDesc</span> <span class="p">{</span>
  <span class="n">inputs</span> <span class="o">=</span> <span class="p">{</span><span class="mi">0</span><span class="p">}</span> <span class="o">//</span> <span class="n">the</span> <span class="n">index</span> <span class="n">of</span> <span class="n">x</span>
  <span class="n">outputs</span> <span class="o">=</span> <span class="p">{</span><span class="mi">5</span><span class="p">,</span> <span class="mi">3</span><span class="p">}</span> <span class="o">//</span> <span class="n">indices</span> <span class="n">of</span> <span class="n">act</span> <span class="ow">and</span> <span class="n">hidden_out</span>
  <span class="n">attrs</span> <span class="p">{</span>
    <span class="s2">&quot;memories&quot;</span> <span class="p">:</span> <span class="p">{</span><span class="mi">1</span><span class="p">}</span> <span class="o">//</span> <span class="n">the</span> <span class="n">index</span> <span class="n">of</span> <span class="n">h</span>
    <span class="s2">&quot;step_net&quot;</span> <span class="p">:</span> <span class="o">&lt;</span><span class="n">above</span> <span class="n">step</span> <span class="n">net</span><span class="o">&gt;</span>
  <span class="p">}</span>
<span class="p">};</span>
</pre></div>
</div>
<p>This <code class="docutils literal"><span class="pre">OpDesc</span></code> value is in the <code class="docutils literal"><span class="pre">ops</span></code> field of the <code class="docutils literal"><span class="pre">BlockDesc</span></code> value representing the global block.</p>
</div>
<div class="section" id="the-compilation-of-blocks">
<span id="the-compilation-of-blocks"></span><h2>The Compilation of Blocks<a class="headerlink" href="#the-compilation-of-blocks" title="Permalink to this headline"></a></h2>
<p>During the generation of the Protobuf message, the Block should store VarDesc (the Protobuf message which describes Variable) and OpDesc (the Protobuf message which describes Operator).</p>
<p>VarDesc in a block should have its name scope to avoid local variables affect parent block&#8217;s name scope.
Child block&#8217;s name scopes should inherit the parent&#8217;s so that OpDesc in child block can reference a VarDesc that stored in parent block. For example</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Varaible</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">])</span>
<span class="n">b</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">params</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;fc.w&quot;</span><span class="p">,</span> <span class="s2">&quot;fc.b&quot;</span><span class="p">])</span>

<span class="n">rnn</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">create_rnn</span><span class="p">()</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
371 372 
<span class="k">with</span> <span class="n">rnn</span><span class="o">.</span><span class="n">stepnet</span><span class="p">()</span>
    <span class="n">x</span> <span class="o">=</span> <span class="n">a</span><span class="o">.</span><span class="n">as_step_input</span><span class="p">()</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
373 374 
    <span class="c1"># reuse fc&#39;s parameter</span>
    <span class="n">fc_without_b</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">get_variable</span><span class="p">(</span><span class="s2">&quot;fc.w&quot;</span><span class="p">)</span>
T
Deploy to GitHub Pages: bfe6dcb5d345b3a734c2d496a97bffa184dfbbd4  
Travis CI 已提交
375 
    <span class="n">rnn</span><span class="o">.</span><span class="n">output</span><span class="p">(</span><span class="n">fc_without_b</span><span class="p">)</span>
T
Deploy to GitHub Pages: 59c48f9831e4a189ea042cd1ebb9be39e98b6d03  
Travis CI 已提交
376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 

<span class="n">out</span> <span class="o">=</span> <span class="n">rnn</span><span class="p">()</span>
</pre></div>
</div>
<p>the method <code class="docutils literal"><span class="pre">pd.get_variable</span></code> can help retrieve a Variable by a name, a Variable may store in a parent block, but might be retrieved in a child block, so block should have a variable scope that supports inheritance.</p>
<p>In compiler design, the symbol table is a data structure created and maintained by compilers to store information about the occurrence of various entities such as variable names, function names, classes, etc.</p>
<p>To store the definition of variables and operators, we define a C++ class <code class="docutils literal"><span class="pre">SymbolTable</span></code>, like the one used in compilers.</p>
<p><code class="docutils literal"><span class="pre">SymbolTable</span></code> can do the following stuff:</p>
<ul class="simple">
<li>store the definitions (some names and attributes) of variables and operators,</li>
<li>to verify if a variable was declared,</li>
<li>to make it possible to implement type checking (offer Protobuf message pointers to <code class="docutils literal"><span class="pre">InferShape</span></code> handlers).</li>
</ul>
<div class="highlight-c++"><div class="highlight"><pre><span></span><span class="c1">// Information in SymbolTable is enough to trace the dependency graph. So maybe</span>
<span class="c1">// the Eval() interface takes a SymbolTable is enough.</span>
<span class="k">class</span> <span class="nc">SymbolTable</span> <span class="p">{</span>
 <span class="k">public</span><span class="o">:</span>
  <span class="n">SymbolTable</span><span class="p">(</span><span class="n">SymbolTable</span><span class="o">*</span> <span class="n">parent</span><span class="p">)</span> <span class="o">:</span> <span class="n">parent_</span><span class="p">(</span><span class="n">parent</span><span class="p">)</span> <span class="p">{}</span>

  <span class="n">OpDesc</span><span class="o">*</span> <span class="n">NewOp</span><span class="p">(</span><span class="k">const</span> <span class="n">string</span><span class="o">&amp;</span> <span class="n">name</span><span class="o">=</span><span class="s">&quot;&quot;</span><span class="p">);</span>

  <span class="c1">// TODO determine whether name is generated by python or C++</span>
  <span class="c1">// currently assume that a unique name will be generated by C++ if the</span>
  <span class="c1">// argument name left default.</span>
  <span class="n">VarDesc</span><span class="o">*</span> <span class="nf">NewVar</span><span class="p">(</span><span class="k">const</span> <span class="n">string</span><span class="o">&amp;</span> <span class="n">name</span><span class="o">=</span><span class="s">&quot;&quot;</span><span class="p">);</span>

  <span class="c1">// find a VarDesc by name, if recursive true, find parent&#39;s SymbolTable</span>
  <span class="c1">// recursively.</span>
  <span class="c1">// this interface is introduced to support InferShape, find protobuf messages</span>
  <span class="c1">// of variables and operators, pass pointers into InferShape.</span>
  <span class="c1">// operator</span>
  <span class="c1">//</span>
  <span class="c1">// NOTE maybe some C++ classes such as VarDescBuilder and OpDescBuilder should</span>
  <span class="c1">// be proposed and embedded into pybind to enable python operate on C++ pointers.</span>
  <span class="n">VarDesc</span><span class="o">*</span> <span class="nf">FindVar</span><span class="p">(</span><span class="k">const</span> <span class="n">string</span><span class="o">&amp;</span> <span class="n">name</span><span class="p">,</span> <span class="kt">bool</span> <span class="n">recursive</span><span class="o">=</span><span class="nb">true</span><span class="p">);</span>

  <span class="n">OpDesc</span><span class="o">*</span> <span class="nf">FindOp</span><span class="p">(</span><span class="k">const</span> <span class="n">string</span><span class="o">&amp;</span> <span class="n">name</span><span class="p">);</span>

  <span class="n">BlockDesc</span> <span class="nf">Compile</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>

 <span class="k">private</span><span class="o">:</span>
  <span class="n">SymbolTable</span><span class="o">*</span> <span class="n">parent_</span><span class="p">;</span>

  <span class="n">map</span><span class="o">&lt;</span><span class="n">string</span><span class="p">,</span> <span class="n">OpDesc</span><span class="o">&gt;</span> <span class="n">ops_</span><span class="p">;</span>
  <span class="n">map</span><span class="o">&lt;</span><span class="n">string</span><span class="p">,</span> <span class="n">VarDesc</span><span class="o">&gt;</span> <span class="n">vars_</span><span class="p">;</span>
<span class="p">};</span>
</pre></div>
</div>
<p>After all the description of variables and operators is added into SymbolTable,
the block has enough information to run.</p>
<p>The <code class="docutils literal"><span class="pre">Block</span></code> class takes a <code class="docutils literal"><span class="pre">BlockDesc</span></code> as input, and provide <code class="docutils literal"><span class="pre">Run</span></code> and <code class="docutils literal"><span class="pre">InferShape</span></code> functions.</p>
<div class="highlight-c++"><div class="highlight"><pre><span></span><span class="k">namespace</span> <span class="p">{</span>

<span class="k">class</span> <span class="nc">Block</span> <span class="o">:</span> <span class="n">OperatorBase</span> <span class="p">{</span>
<span class="k">public</span><span class="o">:</span>
  <span class="n">Block</span><span class="p">(</span><span class="k">const</span> <span class="n">BlockDesc</span><span class="o">&amp;</span> <span class="n">desc</span><span class="p">)</span> <span class="n">desc_</span><span class="p">(</span><span class="n">desc</span><span class="p">)</span> <span class="p">{}</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">Scope</span><span class="o">&amp;</span> <span class="n">scope</span><span class="p">)</span> <span class="k">const</span> <span class="k">override</span> <span class="p">{</span>
    <span class="k">if</span> <span class="p">(</span><span class="o">!</span><span class="n">symbols_ready_</span><span class="p">)</span> <span class="p">{</span>
      <span class="n">CreateVariables</span><span class="p">(</span><span class="n">scope</span><span class="p">);</span>
      <span class="n">CreateOperators</span><span class="p">();</span>
    <span class="p">}</span>
    <span class="c1">// should run InferShape first.</span>
    <span class="k">for</span> <span class="p">(</span><span class="k">auto</span><span class="o">&amp;</span> <span class="nl">op</span> <span class="p">:</span> <span class="n">runtime_table_</span><span class="p">.</span><span class="n">ops</span><span class="p">())</span> <span class="p">{</span>
      <span class="n">op</span><span class="o">-&gt;</span><span class="n">InferShape</span><span class="p">(</span><span class="n">scope</span><span class="p">);</span>
    <span class="p">}</span>
  <span class="p">}</span>

  <span class="kt">void</span> <span class="n">Run</span><span class="p">(</span><span class="k">const</span> <span class="n">framework</span><span class="o">::</span><span class="n">Scope</span><span class="o">&amp;</span> <span class="n">scope</span><span class="p">,</span>
           <span class="k">const</span> <span class="n">platform</span><span class="o">::</span><span class="n">DeviceContext</span><span class="o">&amp;</span> <span class="n">dev_ctx</span><span class="p">)</span> <span class="k">const</span> <span class="k">override</span> <span class="p">{</span>
    <span class="n">PADDLE_ENFORCE</span><span class="p">(</span><span class="n">symbols_ready_</span><span class="p">,</span> <span class="s">&quot;operators and variables should be created first.&quot;</span><span class="p">);</span>
    <span class="k">for</span> <span class="p">(</span><span class="k">auto</span><span class="o">&amp;</span> <span class="nl">op</span> <span class="p">:</span> <span class="n">runtime_table_</span><span class="p">.</span><span class="n">ops</span><span class="p">())</span> <span class="p">{</span>
      <span class="n">op</span><span class="o">-&gt;</span><span class="n">Run</span><span class="p">(</span><span class="n">scope</span><span class="p">,</span> <span class="n">dev_ctx</span><span class="p">);</span>
    <span class="p">}</span>
  <span class="p">}</span>

  <span class="kt">void</span> <span class="n">CreateVariables</span><span class="p">(</span><span class="k">const</span> <span class="n">framework</span><span class="o">::</span><span class="n">Scope</span><span class="o">&amp;</span> <span class="n">scope</span><span class="p">);</span>
  <span class="kt">void</span> <span class="nf">CreateOperators</span><span class="p">();</span>

  <span class="c1">// some other necessary interfaces of NetOp are list below</span>
  <span class="c1">// ...</span>

<span class="k">private</span><span class="o">:</span>
  <span class="n">BlockDesc</span> <span class="n">desc_</span><span class="p">;</span>
  <span class="kt">bool</span> <span class="n">symbols_ready_</span><span class="p">{</span><span class="nb">false</span><span class="p">};</span>
<span class="p">};</span>
</pre></div>
</div>
</div>
<div class="section" id="the-execution-of-blocks">
<span id="the-execution-of-blocks"></span><h2>The Execution of Blocks<a class="headerlink" href="#the-execution-of-blocks" title="Permalink to this headline"></a></h2>
<p>Block inherits from OperatorBase, which has a Run method.
Block&#8217;s Run method will run its operators sequentially.</p>
<p>There is another important interface called <code class="docutils literal"><span class="pre">Eval</span></code>, which take some arguments called targets, and generate a minimal graph which takes targets as the end points and creates a new Block,
after <code class="docutils literal"><span class="pre">Run</span></code>, <code class="docutils literal"><span class="pre">Eval</span></code> will get the latest value and return the targets.</p>
<p>The definition of Eval is as follows:</p>
<div class="highlight-c++"><div class="highlight"><pre><span></span><span class="c1">// clean a block description by targets using the corresponding dependency graph.</span>
<span class="c1">// return a new BlockDesc with minimal number of operators.</span>
<span class="c1">// NOTE not return a Block but the block&#39;s description so that this can be distributed</span>
<span class="c1">// to a cluster.</span>
<span class="n">BlockDesc</span> <span class="nf">Prune</span><span class="p">(</span><span class="k">const</span> <span class="n">BlockDesc</span><span class="o">&amp;</span> <span class="n">desc</span><span class="p">,</span> <span class="n">vector</span><span class="o">&lt;</span><span class="n">string</span><span class="o">&gt;</span> <span class="n">targets</span><span class="p">);</span>

<span class="kt">void</span> <span class="n">Block</span><span class="o">::</span><span class="n">Eval</span><span class="p">(</span><span class="k">const</span> <span class="n">vector</span><span class="o">&lt;</span><span class="n">string</span><span class="o">&gt;&amp;</span> <span class="n">targets</span><span class="p">,</span>
                 <span class="k">const</span> <span class="n">framework</span><span class="o">::</span><span class="n">Scope</span><span class="o">&amp;</span> <span class="n">scope</span><span class="p">,</span>
                 <span class="k">const</span> <span class="n">platform</span><span class="o">::</span><span class="n">DeviceContext</span><span class="o">&amp;</span> <span class="n">dev_ctx</span><span class="p">)</span> <span class="p">{</span>
  <span class="n">BlockDesc</span> <span class="n">min_desc</span> <span class="o">=</span> <span class="n">Prune</span><span class="p">(</span><span class="n">desc_</span><span class="p">,</span> <span class="n">targets</span><span class="p">);</span>
  <span class="n">Block</span> <span class="nf">min_block</span><span class="p">(</span><span class="n">min_desc</span><span class="p">);</span>
  <span class="n">min_block</span><span class="p">.</span><span class="n">Run</span><span class="p">(</span><span class="n">scope</span><span class="p">,</span> <span class="n">dev_ctx</span><span class="p">);</span>
<span class="p">}</span>
</pre></div>
</div>
</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>