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    <li>Design Doc: Block and Scope</li>
  </ul>
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  <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="永久链接至标题"></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="永久链接至标题"></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>
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<li>TensorFlow, Caffe2, Mxnet: graph of operators.</li>
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<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="永久链接至标题"></a></h2>
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<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>
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<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="永久链接至标题"></a></h2>
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<p>The existence of the backward pass makes the execution of a block of PaddlePaddle different from traditional programs:</p>
<p>| programming languages | PaddlePaddle                    |
|&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;|&#8212;&#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 when minibatch completes|</p>
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<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>
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<li>PaddlePaddle doesn&#8217;t pop a scope after the execution of the block because variables therein are used by the backward pass.  So it has a stack forest known as a <em>scope hierarchy</em>.</li>
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<li>The height of the highest tree is the maximum depth of nested blocks.</li>
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<li>After the processing of a minibatch, PaddlePaddle destroys the scope hierarchy.</li>
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</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="永久链接至标题"></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="永久链接至标题"></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>
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<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>
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<span class="kt">bool</span> <span class="n">cond</span> <span class="o">=</span> <span class="nb">false</span><span class="p">;</span>
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<span class="kt">int</span> <span class="n">o1</span><span class="p">,</span> <span class="n">o2</span><span class="p">;</span>
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<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>
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  <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>
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<span class="p">}</span> <span class="k">else</span> <span class="p">{</span>
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  <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>
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<span class="p">}</span>
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<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>
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<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>
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<span class="k">with</span> <span class="n">ie</span><span class="o">.</span><span class="n">true_block</span><span class="p">():</span>
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    <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>
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<span class="k">with</span> <span class="n">ie</span><span class="o">.</span><span class="n">false_block</span><span class="p">():</span>
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    <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>
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</pre></div>
</div>
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<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">fc(x)</span></code> and <code class="docutils literal"><span class="pre">x+1</span></code> .</p>
<p>The difference is that variables in the C++ program contain scalar values, whereas those in the PaddlePaddle programs are mini-batches of instances.</p>
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</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="永久链接至标题"></a></h3>
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<p>The following RNN model in PaddlePaddle from the <a class="reference external" href="design/rnn.md">RNN design doc</a> :</p>
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<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>
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  <span class="n">h_prev</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>
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  <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>
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  <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">h_prev</span><span class="p">)</span>
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  <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>
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<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>
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<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>
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<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>
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<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>
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  <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>
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  <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>
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<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="永久链接至标题"></a></h2>
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<p>Like TensorFlow, a PaddlePaddle program is written in Python. The first part describes a neural network as a protobuf message, and the rest executes the message for training or inference.</p>
<p>The generation of this protobuf message is similar to how a compiler generates a binary executable file. The execution of the message is similar to how the OS executes the binary file.</p>
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</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="永久链接至标题"></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>
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<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>
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<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>
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  <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="ow">in</span> <span class="nb">vars</span> <span class="n">of</span> <span class="n">BlockDesc</span> <span class="n">above</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="ow">in</span> <span class="nb">vars</span> <span class="n">of</span> <span class="n">BlockDesc</span> <span class="n">above</span>
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  <span class="n">attrs</span> <span class="p">{</span>
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    <span class="s2">&quot;states&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>
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    <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>
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<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>
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<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="永久链接至标题"></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.
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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">Variable</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>
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<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>
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<span class="k">with</span> <span class="n">rnn</span><span class="o">.</span><span class="n">stepnet</span><span class="p">():</span>
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    <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>
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    <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>
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    <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>
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403 404 405 406 

<span class="n">out</span> <span class="o">=</span> <span class="n">rnn</span><span class="p">()</span>
</pre></div>
</div>
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<p>The method <code class="docutils literal"><span class="pre">pd.get_variable</span></code> can help retrieve a Variable by the name. The Variable may be stored in a parent block, but might be retrieved in a child block, so block should have a variable scope that supports inheritance.</p>
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<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>
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<p><code class="docutils literal"><span class="pre">SymbolTable</span></code> can do the following:</p>
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<ul class="simple">
<li>store the definitions (some names and attributes) of variables and operators,</li>
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<li>verify if a variable was declared,</li>
<li>make it possible to implement type checking (offer Protobuf message pointers to <code class="docutils literal"><span class="pre">InferShape</span></code> handlers).</li>
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</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>
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  <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 is left default.</span>
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  <span class="n">VarDesc</span><span class="o">*</span> <span class="nf">Var</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>
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  <span class="c1">// find a VarDesc by name, if recursive is true, find parent&#39;s SymbolTable</span>
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  <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">//</span>
  <span class="c1">// NOTE maybe some C++ classes such as VarDescBuilder and OpDescBuilder should</span>
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  <span class="c1">// be proposed and embedded into pybind to enable python operation on C++ pointers.</span>
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  <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>
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<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 provides <code class="docutils literal"><span class="pre">Run</span></code> and <code class="docutils literal"><span class="pre">InferShape</span></code> functions.</p>
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<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>
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  <span class="c1">// some other necessary interfaces of NetOp are listed below</span>
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  <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="永久链接至标题"></a></h2>
<p>Block inherits from OperatorBase, which has a Run method.
Block&#8217;s Run method will run its operators sequentially.</p>
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<p>There is another important interface called <code class="docutils literal"><span class="pre">Eval</span></code>, which takes some arguments called targets and generates a minimal graph which treats 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>
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<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>
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<span class="c1">// NOTE: The return type is not a Block but the block&#39;s description so that this can be distributed</span>
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500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 
<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>
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