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  <div class="section" id="paddlepaddle-fluid-source-code-overview">
<span id="paddlepaddle-fluid-source-code-overview"></span><h1>PaddlePaddle Fluid Source Code Overview<a class="headerlink" href="#paddlepaddle-fluid-source-code-overview" title="永久链接至标题"></a></h1>
<p>Examples: https://github.com/PaddlePaddle/Paddle/tree/develop/python/paddle/v2/fluid/tests/book</p>
<p>Core: https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/framework</p>
<p>Operator: https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/operators</p>
<p>Memory: https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/memory</p>
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<p>Platform: https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/platform</p>
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</div>
<div class="section" id="compile-time">
<span id="compile-time"></span><h1>Compile Time<a class="headerlink" href="#compile-time" title="永久链接至标题"></a></h1>
<p>The following <strong>defines</strong> the NN. The definition goes into this <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/framework.proto">protocol buffer</a>.</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">x</span> <span class="o">=</span> <span class="n">fluid</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">&#39;x&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="mi">13</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">&#39;float32&#39;</span><span class="p">)</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">fluid</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">data</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">&#39;y&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">&#39;float32&#39;</span><span class="p">)</span>

<span class="n">y_predict</span> <span class="o">=</span> <span class="n">fluid</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">act</span><span class="o">=</span><span class="bp">None</span><span class="p">)</span>
<span class="n">cost</span> <span class="o">=</span> <span class="n">fluid</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">square_error_cost</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">y_predict</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">y</span><span class="p">)</span>
<span class="n">avg_cost</span> <span class="o">=</span> <span class="n">fluid</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">cost</span><span class="p">)</span>

<span class="n">sgd_optimizer</span> <span class="o">=</span> <span class="n">fluid</span><span class="o">.</span><span class="n">optimizer</span><span class="o">.</span><span class="n">SGD</span><span class="p">(</span><span class="n">learning_rate</span><span class="o">=</span><span class="mf">0.001</span><span class="p">)</span>
<span class="n">sgd_optimizer</span><span class="o">.</span><span class="n">minimize</span><span class="p">(</span><span class="n">avg_cost</span><span class="p">)</span>
</pre></div>
</div>
<ul class="simple">
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<li>Variables: <code class="docutils literal"><span class="pre">x</span></code>,  <code class="docutils literal"><span class="pre">y</span></code>, <code class="docutils literal"><span class="pre">y_predict</span></code>, <code class="docutils literal"><span class="pre">cost</span></code> and <code class="docutils literal"><span class="pre">avg_cost</span></code>. <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/v2/fluid/framework.py#">Python</a></li>
<li>Layers: <code class="docutils literal"><span class="pre">fluid.layers.data</span></code>, <code class="docutils literal"><span class="pre">fluid.layers.fc</span></code> and <code class="docutils literal"><span class="pre">fluid.layers.mean</span></code> are layers. <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/tree/develop/python/paddle/v2/fluid/layers">Python</a><ul>
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<li>Every Layer has one or more operators and variables/parameters<ul>
<li>All the operators are defined at <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/operators"><code class="docutils literal"><span class="pre">paddle/operators/</span></code></a>. Other worth-looking files:<ul>
<li>Base class: <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/operator.h"><code class="docutils literal"><span class="pre">paddle/framework/operator.h</span></code></a></li>
<li>Operator Registration: <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/op_registry.h"><code class="docutils literal"><span class="pre">paddle/framework/op_registry.h</span></code></a></li>
<li>Operator Lookup: <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/op_info.h"><code class="docutils literal"><span class="pre">paddle/framework/op_info.h</span></code></a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
<li>Optimizer: <code class="docutils literal"><span class="pre">fluid.optimizer.SGD</span></code>. It does the following<ul>
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<li>Add backward operators. [<a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/v2/fluid/backward.py">Python</a>]</li>
<li>Add optimizer operators. [<a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/v2/fluid/optimizer.py">Python</a>]</li>
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</ul>
</li>
</ul>
</div>
<div class="section" id="run-time">
<span id="run-time"></span><h1>Run Time<a class="headerlink" href="#run-time" title="永久链接至标题"></a></h1>
<p>The following <strong>evaluates</strong> the NN. Instantiates all the variables, operators.</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">place</span> <span class="o">=</span> <span class="n">fluid</span><span class="o">.</span><span class="n">CPUPlace</span><span class="p">()</span>
<span class="n">feeder</span> <span class="o">=</span> <span class="n">fluid</span><span class="o">.</span><span class="n">DataFeeder</span><span class="p">(</span><span class="n">place</span><span class="o">=</span><span class="n">place</span><span class="p">,</span> <span class="n">feed_list</span><span class="o">=</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">exe</span> <span class="o">=</span> <span class="n">fluid</span><span class="o">.</span><span class="n">Executor</span><span class="p">(</span><span class="n">place</span><span class="p">)</span>

<span class="c1"># Allocate memory. Initialize Parameter.</span>
<span class="n">exe</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">fluid</span><span class="o">.</span><span class="n">default_startup_program</span><span class="p">())</span>

<span class="c1"># Allocate memory. Do computation.</span>
<span class="n">exe</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">fluid</span><span class="o">.</span><span class="n">default_main_program</span><span class="p">(),</span>
        <span class="n">feed</span><span class="o">=</span><span class="n">feeder</span><span class="o">.</span><span class="n">feed</span><span class="p">(</span><span class="n">data</span><span class="p">),</span>
        <span class="n">fetch_list</span><span class="o">=</span><span class="p">[</span><span class="n">avg_cost</span><span class="p">])</span>
</pre></div>
</div>
<ul class="simple">
<li>Place: <code class="docutils literal"><span class="pre">place</span></code>. one of CPU, GPU or FPGA. <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/platform/place.h">C++</a><ul>
<li>The device handle are at <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/platform/device_context.h">paddle/platform/device_context.h</a></li>
</ul>
</li>
<li>Executor: <code class="docutils literal"><span class="pre">fluid.Executor(place)</span></code>. [<a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/v2/fluid/executor.py">Python</a>, <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/executor.cc">C++</a>]<ul>
<li>Feeds the data: <code class="docutils literal"><span class="pre">feed=feeder.feed(data)</span></code></li>
<li>Evaluates all the operators</li>
<li>Fetches the result: <code class="docutils literal"><span class="pre">fetch_list=[avg_cost]</span></code></li>
</ul>
</li>
<li>Other worth looking files:<ul>
<li>Scope: <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/scope.h">paddle/framework/scope.h</a>. Where all the variables live<ul>
<li>Variable: <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/variable.h">paddle/framework/variable.h</a>. Where all the data (most likely tensors) live<ul>
<li>Tensor: <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/tensor.h">paddle/framework/tensor.h</a>. Where we allocate memory through <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/memory"><code class="docutils literal"><span class="pre">paddle/memory/</span></code></a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
</ul>
</div>


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