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  <div class="section" id="background">
<span id="background"></span><h1>Background<a class="headerlink" href="#background" title="永久链接至标题">¶</a></h1>
<p>PaddlePaddle divides the description of neural network computation graph into two stages: compile time and runtime.</p>
<p>PaddlePaddle use proto message to describe compile time graph because</p>
<ol class="simple">
<li>Computation graph should be able to be saved to a file.</li>
<li>In distributed training, the graph will be serialized and send to multiple workers.</li>
</ol>
<p>The computation graph is constructed by Data Node and Operation Node. The concept to represent them is in the table below.</p>
<p>| |compile time|runtime|
|&#8212;|&#8212;|&#8212;|
|Data|VarDesc(proto)|Variable(cpp)|
|Operation|OpDesc(proto)|Operator(cpp)|</p>
</div>
<div class="section" id="definition-of-vardesc">
<span id="definition-of-vardesc"></span><h1>Definition of VarDesc<a class="headerlink" href="#definition-of-vardesc" title="永久链接至标题">¶</a></h1>
<p>A VarDesc should have a name, and value. The are two kinds of variable type in compile time, they are <code class="docutils literal"><span class="pre">LoDTensor</span></code> and <code class="docutils literal"><span class="pre">SelectedRows</span></code>.</p>
<div class="highlight-proto"><div class="highlight"><pre><span></span><span class="kd">message</span> <span class="nc">VarDesc</span> <span class="p">{</span>
  <span class="k">required</span> <span class="kt">string</span> <span class="na">name</span> <span class="o">=</span> <span class="mi">1</span><span class="p">;</span>
  <span class="kd">enum</span> <span class="n">VarType</span> <span class="p">{</span>
    <span class="na">LOD_TENSOR</span> <span class="o">=</span> <span class="mi">0</span><span class="p">;</span>
    <span class="na">SELECTED_ROWS</span> <span class="o">=</span> <span class="mi">1</span><span class="p">;</span>
  <span class="p">}</span>
  <span class="k">required</span> <span class="n">VarType</span> <span class="na">type</span> <span class="o">=</span> <span class="mi">2</span><span class="p">;</span>
  <span class="k">optional</span> <span class="n">LoDTensorDesc</span> <span class="na">lod_desc</span> <span class="o">=</span> <span class="mi">3</span><span class="p">;</span>
  <span class="k">optional</span> <span class="n">TensorDesc</span> <span class="na">selected_rows_desc</span> <span class="o">=</span> <span class="mi">4</span><span class="p">;</span>
  <span class="k">optional</span> <span class="kt">bool</span> <span class="na">persistable</span> <span class="o">=</span> <span class="mi">5</span> <span class="p">[</span> <span class="k">default</span> <span class="o">=</span> <span class="kc">false</span> <span class="p">];</span>
<span class="p">}</span>
</pre></div>
</div>
</div>
<div class="section" id="definition-of-tensordesc">
<span id="definition-of-tensordesc"></span><h1>Definition of TensorDesc<a class="headerlink" href="#definition-of-tensordesc" title="永久链接至标题">¶</a></h1>
<div class="highlight-proto"><div class="highlight"><pre><span></span><span class="kd">enum</span> <span class="n">DataType</span> <span class="p">{</span>
  <span class="na">BOOL</span> <span class="o">=</span> <span class="mi">0</span><span class="p">;</span>
  <span class="na">INT16</span> <span class="o">=</span> <span class="mi">1</span><span class="p">;</span>
  <span class="na">INT32</span> <span class="o">=</span> <span class="mi">2</span><span class="p">;</span>
  <span class="na">INT64</span> <span class="o">=</span> <span class="mi">3</span><span class="p">;</span>
  <span class="na">FP16</span> <span class="o">=</span> <span class="mi">4</span><span class="p">;</span>
  <span class="na">FP32</span> <span class="o">=</span> <span class="mi">5</span><span class="p">;</span>
  <span class="na">FP64</span> <span class="o">=</span> <span class="mi">6</span><span class="p">;</span>
<span class="p">}</span>

<span class="kd">message</span> <span class="nc">TensorDesc</span> <span class="p">{</span>
  <span class="k">required</span> <span class="n">DataType</span> <span class="na">data_type</span> <span class="o">=</span> <span class="mi">1</span><span class="p">;</span>
  <span class="k">repeated</span> <span class="kt">int64</span> <span class="na">dims</span> <span class="o">=</span> <span class="mi">2</span><span class="p">;</span> <span class="c1">// [UNK, 640, 480] is saved as [-1, 640, 480]</span>
<span class="p">}</span>
</pre></div>
</div>
<p>A TensorDesc describes <code class="docutils literal"><span class="pre">SelectedRows</span></code> and <code class="docutils literal"><span class="pre">LoDTensor</span></code>. For details of <code class="docutils literal"><span class="pre">SelectedRows</span></code>, please reference <a class="reference external" href="./selected_rows.md"><code class="docutils literal"><span class="pre">SelectedRows</span></code></a>.</p>
</div>
<div class="section" id="definition-of-lodtensordesc">
<span id="definition-of-lodtensordesc"></span><h1>Definition of LodTensorDesc<a class="headerlink" href="#definition-of-lodtensordesc" title="永久链接至标题">¶</a></h1>
<div class="highlight-proto"><div class="highlight"><pre><span></span><span class="kd">message</span> <span class="nc">LoDTensorDesc</span> <span class="p">{</span>
  <span class="k">required</span> <span class="n">TensorDesc</span> <span class="na">tensor</span> <span class="o">=</span> <span class="mi">1</span><span class="p">;</span>
  <span class="k">optional</span> <span class="n">int</span> <span class="na">lod_level</span> <span class="o">=</span> <span class="mi">2</span><span class="p">;</span>
<span class="p">}</span>
</pre></div>
</div>
<p>A LoDTensorDesc contains a tensor and a lod_level.</p>
</div>
<div class="section" id="definition-of-variable-in-python">
<span id="definition-of-variable-in-python"></span><h1>Definition of Variable in Python<a class="headerlink" href="#definition-of-variable-in-python" title="永久链接至标题">¶</a></h1>
<p>For Variable in Python, please reference <a class="reference external" href="./python_api.md"><code class="docutils literal"><span class="pre">Python</span> <span class="pre">API</span></code></a>.</p>
</div>


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