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  <div class="section" id="module-paddle.v2.layer">
<span id="layers"></span><h1>Layers<a class="headerlink" href="#module-paddle.v2.layer" title="永久链接至标题"></a></h1>
<p><cite>paddle.v2.layer</cite> is a part of model config packages in paddle.v2. In API v2,
we want to make Paddle a plain Python package. The model config package defined
the way how to configure a neural network topology in Paddle Python code.</p>
<p>The primary usage shows below.</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">paddle.v2</span> <span class="kn">as</span> <span class="nn">paddle</span>

<span class="n">img</span> <span class="o">=</span> <span class="n">paddle</span><span class="o">.</span><span class="n">layer</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;img&#39;</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">data_type</span><span class="o">.</span><span class="n">dense_vector</span><span class="p">(</span><span class="mi">784</span><span class="p">))</span>
<span class="n">hidden</span> <span class="o">=</span> <span class="n">paddle</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="nb">input</span><span class="o">=</span><span class="n">img</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">200</span><span class="p">)</span>
<span class="n">prediction</span> <span class="o">=</span> <span class="n">paddle</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="nb">input</span><span class="o">=</span><span class="n">hidden</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span>
                             <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Softmax</span><span class="p">())</span>

<span class="c1"># use prediction instance where needed.</span>
<span class="n">parameters</span> <span class="o">=</span> <span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">parameters</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">cost</span><span class="p">)</span>
</pre></div>
</div>
<dl class="function">
<dt id="paddle.v2.layer.parse_network">
<code class="descclassname">paddle.v2.layer.</code><code class="descname">parse_network</code><span class="sig-paren">(</span><em>*outputs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.layer.parse_network" title="永久链接至目标"></a></dt>
<dd><p>parse all output layers and then generate a model config proto.
:param outputs:
:return:</p>
</dd></dl>

</div>


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