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    <li>Design Doc: Python API</li>
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  <div class="section" id="design-doc-python-api">
<span id="design-doc-python-api"></span><h1>Design Doc: Python API<a class="headerlink" href="#design-doc-python-api" title="永久链接至标题"></a></h1>
<p>Due to the refactorization of the PaddlePaddle core, we need Python classes to construct corresponding protobuf messages that describe a DL program.</p>
<p>| Python classes | Protobuf messages |
| &#8212; | &#8212; |
| Program | ProgramDesc |
| Block | BlockDesc |
| Operator | OpDesc |
| Variable | VarDesc |</p>
<p>Please be aware that these Python classes need to maintain some construction-time information, which are not part of the protobuf messages.</p>
<div class="section" id="core-concepts">
<span id="core-concepts"></span><h2>Core Concepts<a class="headerlink" href="#core-concepts" title="永久链接至标题"></a></h2>
<div class="section" id="program">
<span id="program"></span><h3>Program<a class="headerlink" href="#program" title="永久链接至标题"></a></h3>
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<p>A <code class="docutils literal"><span class="pre">ProgramDesc</span></code> describes a <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/program.md">DL program</a>, which is composed of an array of <code class="docutils literal"><span class="pre">BlockDesc</span></code>s.  The <code class="docutils literal"><span class="pre">BlockDesc</span></code>s in a <code class="docutils literal"><span class="pre">ProgramDesc</span></code> can have a tree-like hierarchical structure. However, the <code class="docutils literal"><span class="pre">ProgramDesc</span></code> onlys stores a flattened array of <code class="docutils literal"><span class="pre">BlockDesc</span></code>s. A <code class="docutils literal"><span class="pre">BlockDesc</span></code> refers to its parent block by its index in the array.  For example, operators in the step block of an RNN operator need to be able to access variables in its ancestor blocks.</p>
<p>Whenever we create a block, we need to set its parent block to the current block, hence the Python class <code class="docutils literal"><span class="pre">Program</span></code> needs to maintain a data member <code class="docutils literal"><span class="pre">current_block</span></code>.</p>
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<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">Program</span><span class="p">(</span><span class="n">objects</span><span class="p">):</span>
    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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        <span class="bp">self</span><span class="o">.</span><span class="n">desc</span> <span class="o">=</span> <span class="n">core</span><span class="o">.</span><span class="n">NewProgram</span><span class="p">()</span> <span class="c1"># a C++ ProgramDesc pointer.</span>
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        <span class="bp">self</span><span class="o">.</span><span class="n">blocks</span> <span class="o">=</span> <span class="n">vector</span><span class="o">&lt;</span><span class="n">Block</span><span class="o">&gt;</span><span class="p">()</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">blocks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">Block</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">))</span> <span class="c1"># the global block</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">current_block</span> <span class="o">=</span> <span class="mi">0</span>          <span class="c1"># initialized to the global block</span>

    <span class="k">def</span> <span class="nf">global_block</span><span class="p">():</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">blocks</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>

    <span class="k">def</span> <span class="nf">current_block</span><span class="p">():</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_block</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">current_block</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">rollback</span><span class="p">():</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">current_block</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">current_block</span><span class="p">()</span><span class="o">.</span><span class="n">parent_idx</span>

    <span class="k">def</span> <span class="nf">create_block</span><span class="p">():</span>
        <span class="n">new_block_idx</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">block</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">blocks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">Block</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">current_block</span><span class="p">))</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">current_block</span> <span class="o">=</span> <span class="n">new_block_idx</span>
        <span class="k">return</span> <span class="n">current_block</span><span class="p">()</span>
</pre></div>
</div>
<p><code class="docutils literal"><span class="pre">Program</span></code> is an accessor to the protobuf message <code class="docutils literal"><span class="pre">ProgramDesc</span></code>, which is created in C++ space, because the InferShape function is in C++, which manipulates <code class="docutils literal"><span class="pre">VarDesc</span></code> messages, which are in turn members of <code class="docutils literal"><span class="pre">BlockDesc</span></code>, which is a member of <code class="docutils literal"><span class="pre">ProgramDesc</span></code>.</p>
<p><code class="docutils literal"><span class="pre">Program</span></code> creates the first block as the global block in its constructor.  All parameters and their initializer operators are in the global block.</p>
</div>
<div class="section" id="block">
<span id="block"></span><h3>Block<a class="headerlink" href="#block" title="永久链接至标题"></a></h3>
<p>A <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/block.md">Block</a> includes</p>
<ol class="simple">
<li>a map from variable names to an instance of the Python <code class="docutils literal"><span class="pre">Variable</span></code> class, and</li>
<li>a list of <code class="docutils literal"><span class="pre">Operator</span></code> instances.</li>
</ol>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">Block</span><span class="p">(</span><span class="n">objects</span><span class="p">):</span>
    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">program</span><span class="p">,</span> <span class="n">parent_idx</span><span class="p">):</span>
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        <span class="bp">self</span><span class="o">.</span><span class="n">desc</span> <span class="o">=</span> <span class="n">core</span><span class="o">.</span><span class="n">NewBlock</span><span class="p">(</span><span class="n">program</span><span class="o">.</span><span class="n">desc</span><span class="p">)</span>
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246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 
        <span class="bp">self</span><span class="o">.</span><span class="n">program</span> <span class="o">=</span> <span class="n">program</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">vars</span> <span class="o">=</span> <span class="nb">map</span><span class="o">&lt;</span><span class="n">string</span><span class="p">,</span> <span class="n">Variable</span><span class="o">&gt;</span><span class="p">()</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">ops</span> <span class="o">=</span> <span class="n">vector</span><span class="o">&lt;</span><span class="n">Operator</span><span class="o">&gt;</span><span class="p">()</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">parent_idx</span> <span class="o">=</span> <span class="n">parent_idx</span>

    <span class="k">def</span> <span class="nf">create_var</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">...</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">Variable</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">...</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">_create_global_var</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">...</span><span class="p">):</span>
        <span class="n">program</span><span class="o">.</span><span class="n">global_block</span><span class="p">()</span><span class="o">.</span><span class="n">create_var</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">create_parameter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="o">...</span><span class="p">):</span>
        <span class="c1"># Parameter is a subclass of variable. See Parameter section for details.</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">vars</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_create_global_var</span><span class="p">(</span><span class="o">...</span><span class="p">),</span> <span class="o">...</span><span class="p">)</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">vars</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>

    <span class="k">def</span> <span class="nf">append_operator</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">...</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">ops</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">Operator</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">...</span><span class="p">))</span>

    <span class="k">def</span> <span class="nf">prepend_operator</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">...</span><span class="p">):</span> <span class="c1"># Parameter&#39;s ctor prepands initialize operators.</span>
       <span class="bp">self</span><span class="o">.</span><span class="n">ops</span><span class="o">.</span><span class="n">prepend</span><span class="p">(</span><span class="n">Operator</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">...</span><span class="p">))</span>
</pre></div>
</div>
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<p><code class="docutils literal"><span class="pre">create_parameter</span></code> is necessary because parameters are global variables, defined in the global block, but can be created in some sub-blocks. For example, an FC layer in the step block of an RNN operator.</p>
<p><code class="docutils literal"><span class="pre">prepend_operator</span></code> is necessary because the constructor of <code class="docutils literal"><span class="pre">Parameter</span></code> needs to create the initialize (or load) operator of the parameter, and would like to put it in the <em>preamble</em> of the global block.</p>
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</div>
<div class="section" id="operator">
<span id="operator"></span><h3>Operator<a class="headerlink" href="#operator" title="永久链接至标题"></a></h3>
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<p>The <code class="docutils literal"><span class="pre">Operator</span></code> class fills in the <code class="docutils literal"><span class="pre">OpDesc</span></code> message and calls the C++ function <code class="docutils literal"><span class="pre">InferShape</span></code> to infer the output shapes from the input shapes.</p>
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<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">Operator</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
                 <span class="n">block</span><span class="p">,</span>  <span class="c1"># Block</span>
                 <span class="nb">type</span><span class="p">,</span>   <span class="c1"># string</span>
                 <span class="n">inputs</span><span class="p">,</span> <span class="c1"># dict&lt;string, Variable&gt;</span>
                 <span class="n">outputs</span><span class="p">,</span><span class="c1"># dict&lt;stirng, Variable&gt;</span>
                 <span class="n">attrs</span>   <span class="c1"># dict&lt;string, Any&gt;</span>
                 <span class="p">):</span>
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        <span class="bp">self</span><span class="o">.</span><span class="n">desc</span> <span class="o">=</span> <span class="n">core</span><span class="o">.</span><span class="n">NewOpDesc</span><span class="p">(</span><span class="n">block</span><span class="o">.</span><span class="n">desc</span><span class="p">,</span> <span class="nb">type</span><span class="p">,</span> <span class="n">inputs</span><span class="p">,</span> <span class="n">outputs</span><span class="p">,</span> <span class="n">attrs</span><span class="p">)</span>
        <span class="n">core</span><span class="o">.</span><span class="n">infer_shape</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">desc</span><span class="p">,</span> <span class="n">inputs</span><span class="p">,</span> <span class="n">outputs</span><span class="p">)</span>
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    <span class="k">def</span> <span class="nf">type</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">desc</span><span class="o">.</span><span class="n">type</span><span class="p">()</span>
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</pre></div>
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<p><code class="docutils literal"><span class="pre">Operator</span></code> creates the <code class="docutils literal"><span class="pre">OpDesc</span></code> message in C++ space, so that it can call the <code class="docutils literal"><span class="pre">InferShape</span></code> function, which is in C++.</p>
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<div class="section" id="variable">
<span id="variable"></span><h3>Variable<a class="headerlink" href="#variable" title="永久链接至标题"></a></h3>
<p>Operators take Variables as its inputs and outputs.</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">Variable</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
                 <span class="n">block</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>      <span class="c1"># Block</span>
                 <span class="n">name</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>       <span class="c1"># string</span>
                 <span class="n">shape</span><span class="p">,</span>           <span class="c1"># tuple</span>
                 <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float32&quot;</span><span class="p">,</span> <span class="c1"># string</span>
                 <span class="n">lod_level</span><span class="o">=</span><span class="bp">None</span>   <span class="c1"># int</span>
                 <span class="p">):</span>
        <span class="k">if</span> <span class="n">name</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
            <span class="n">name</span> <span class="o">=</span> <span class="n">unique_name_generator</span><span class="p">()</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">name</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">block</span> <span class="o">=</span> <span class="n">block</span>
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        <span class="bp">self</span><span class="o">.</span><span class="n">desc</span> <span class="o">=</span> <span class="n">core</span><span class="o">.</span><span class="n">NewVarDesc</span><span class="p">(</span><span class="n">block</span><span class="o">.</span><span class="n">desc</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span> <span class="n">lod_level</span><span class="p">)</span>
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        <span class="bp">self</span><span class="o">.</span><span class="n">writer</span> <span class="o">=</span> <span class="bp">None</span>
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<p>Please be aware of <code class="docutils literal"><span class="pre">self.writer</span></code>, that tracks operator who creates the variable.  It possible that there are more than one operators who write a variable, but in Python space, each write to a variable is represented by a Variable class.  This is guaranteed by the fact that <strong><code class="docutils literal"><span class="pre">core.NewVarDesc</span></code> must NOT create a new <code class="docutils literal"><span class="pre">VarDesc</span></code> message if its name already exists in the specified block</strong>.</p>
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<div class="section" id="parameter">
<span id="parameter"></span><h3>Parameter<a class="headerlink" href="#parameter" title="永久链接至标题"></a></h3>
<p>A parameter is a global variable with an initializer (or load) operator.</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">Parameter</span><span class="p">(</span><span class="n">Variable</span><span class="p">):</span>
    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
                 <span class="n">block</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>      <span class="c1"># Block</span>
                 <span class="n">name</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>       <span class="c1"># string</span>
                 <span class="n">shape</span><span class="p">,</span>           <span class="c1"># tuple</span>
                 <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float32&quot;</span><span class="p">,</span> <span class="c1"># string</span>
                 <span class="n">lod_level</span><span class="o">=</span><span class="bp">None</span>   <span class="c1"># int</span>
                 <span class="n">trainable</span><span class="p">,</span>       <span class="c1"># bool</span>
                 <span class="n">initialize_op_attrs</span><span class="p">,</span>
                 <span class="n">optimize_op_attrs</span><span class="p">):</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Parameter</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">block</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="p">,</span> <span class="n">lod_level</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">trainable</span> <span class="o">=</span> <span class="n">trainable</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">optimize_op_attrs</span> <span class="o">=</span> <span class="n">optimize_op_attrs</span>
        <span class="n">block</span><span class="o">.</span><span class="n">prepend</span><span class="p">(</span><span class="n">Operator</span><span class="p">(</span><span class="n">block</span><span class="p">,</span>  <span class="c1"># Block</span>
                               <span class="n">initialize_op_attrs</span><span class="p">[</span><span class="s1">&#39;type&#39;</span><span class="p">],</span>   <span class="c1"># string</span>
                               <span class="bp">None</span><span class="p">,</span>   <span class="c1"># no inputs</span>
                               <span class="bp">self</span><span class="p">,</span>   <span class="c1"># output is the parameter</span>
                               <span class="n">initialize_op_attrs</span><span class="p">)</span>
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<p>When users create a parameter, they can call</p>
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<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">program</span><span class="o">.</span><span class="n">create_parameter</span><span class="p">(</span>
  <span class="o">...</span><span class="p">,</span>
  <span class="n">init_attr</span><span class="o">=</span><span class="p">{</span>
    <span class="nb">type</span><span class="p">:</span> <span class="s2">&quot;uniform_random&quot;</span><span class="p">,</span>
    <span class="nb">min</span><span class="p">:</span> <span class="o">-</span><span class="mf">1.0</span><span class="p">,</span>
    <span class="nb">max</span><span class="p">:</span> <span class="mf">1.0</span><span class="p">,</span>
  <span class="p">})</span>
<span class="p">)</span>
</pre></div>
</div>
<p>In above example, <code class="docutils literal"><span class="pre">init_attr.type</span></code> names an initialize operator.  It can also name the load operator</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">init_attr</span><span class="o">=</span><span class="p">{</span>
 <span class="nb">type</span><span class="p">:</span> <span class="s2">&quot;load&quot;</span><span class="p">,</span>
 <span class="n">filename</span><span class="p">:</span> <span class="s2">&quot;something.numpy&quot;</span><span class="p">,</span>
<span class="p">}</span>
</pre></div>
</div>
<p><code class="docutils literal"><span class="pre">optimize_op_attrs</span></code> is not in the <code class="docutils literal"><span class="pre">VarDesc</span></code> message, but kept in the Python instance, as it will be used in the Python space when creating the optimize operator&#8217;s <code class="docutils literal"><span class="pre">OpDesc</span></code>, and will be in the <code class="docutils literal"><span class="pre">OpDesc</span></code> message.</p>
</div>
</div>
<div class="section" id="layer-functions">
<span id="layer-functions"></span><h2>Layer Functions<a class="headerlink" href="#layer-functions" title="永久链接至标题"></a></h2>
<p>A layer is a Python function that creates some operators and variables.  Layers simplify the work of application programmers.</p>
<div class="section" id="data-layer">
<span id="data-layer"></span><h3>Data Layer<a class="headerlink" href="#data-layer" title="永久链接至标题"></a></h3>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">data_layer</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="nb">type</span><span class="p">,</span> <span class="n">column_name</span><span class="p">):</span>
    <span class="n">block</span> <span class="o">=</span> <span class="n">the_current_program</span><span class="o">.</span><span class="n">glolal_block</span><span class="p">()</span>
    <span class="n">var</span> <span class="o">=</span> <span class="n">block</span><span class="o">.</span><span class="n">create_global_var</span><span class="p">(</span>
            <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span>
            <span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="bp">None</span><span class="p">]</span> <span class="o">+</span> <span class="nb">type</span><span class="o">.</span><span class="n">dims</span><span class="p">(),</span>
            <span class="n">dtype</span><span class="o">=</span><span class="nb">type</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
    <span class="n">block</span><span class="o">.</span><span class="n">prepend_operator</span><span class="p">(</span><span class="n">block</span><span class="p">,</span>
                           <span class="nb">type</span><span class="o">=</span><span class="s2">&quot;Feed&quot;</span><span class="p">,</span>
                           <span class="n">inputs</span> <span class="o">=</span> <span class="bp">None</span><span class="p">,</span>
                           <span class="n">outputs</span> <span class="o">=</span> <span class="p">[</span><span class="n">var</span><span class="p">],</span>
                           <span class="p">{</span><span class="n">column_name</span><span class="p">:</span> <span class="n">column_name</span><span class="p">})</span>
    <span class="k">return</span> <span class="n">var</span>
</pre></div>
</div>
<p>The input to the feed operator is a special variable in the global scope, which is the output of <a class="reference external" href="https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/reader/README.md">Python readers</a>.</p>
</div>
<div class="section" id="fc-layer">
<span id="fc-layer"></span><h3>FC Layer<a class="headerlink" href="#fc-layer" title="永久链接至标题"></a></h3>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">fc_layer</span><span class="p">(</span><span class="nb">input</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="o">...</span><span class="p">):</span>
    <span class="n">block</span> <span class="o">=</span> <span class="n">program</span><span class="o">.</span><span class="n">current_block</span><span class="p">()</span>
    <span class="n">w</span> <span class="o">=</span> <span class="n">block</span><span class="o">.</span><span class="n">create_parameter</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
    <span class="n">b</span> <span class="o">=</span> <span class="n">block</span><span class="o">.</span><span class="n">create_parameter</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
    <span class="n">out</span> <span class="o">=</span> <span class="n">block</span><span class="o">.</span><span class="n">create_var</span><span class="p">()</span>
    <span class="n">op</span> <span class="o">=</span> <span class="n">block</span><span class="o">.</span><span class="n">append_operator</span><span class="p">(</span><span class="s2">&quot;FC&quot;</span><span class="p">,</span> <span class="n">X</span><span class="o">=</span><span class="nb">input</span><span class="p">,</span> <span class="n">W</span><span class="o">=</span><span class="n">w</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="n">b</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="n">out</span><span class="p">)</span>
    <span class="n">out</span><span class="o">.</span><span class="n">writer</span> <span class="o">=</span> <span class="n">op</span>
    <span class="k">return</span> <span class="n">out</span>
</pre></div>
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