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  <div class="section" id="module-paddle.trainer_config_helpers.networks">
<span id="networks"></span><h1>Networks<a class="headerlink" href="#module-paddle.trainer_config_helpers.networks" title="Permalink to this headline"></a></h1>
<p>The networks module contains pieces of neural network that combine multiple
layers.</p>
<p>The pieces are:</p>
<ul class="simple">
<li>NLP<ul>
<li>Text Convolution component</li>
</ul>
</li>
<li>Images<ul>
<li>Conv_Pool</li>
<li>Conv_BatchNorm_Pool</li>
</ul>
</li>
<li>Recurrent<ul>
<li>simple_lstm</li>
</ul>
</li>
<li>Miscs<ul>
<li>dropout_layer</li>
</ul>
</li>
</ul>
<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.sequence_conv_pool">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">sequence_conv_pool</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.sequence_conv_pool" title="Permalink to this definition"></a></dt>
<dd><p>Text convolution pooling layers helper.</p>
<p>Text input =&gt; Context Projection =&gt; FC Layer =&gt; Pooling =&gt; Output.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; name of output layer(pooling layer name)</li>
<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; name of input layer</li>
<li><strong>context_len</strong> (<em>int</em>) &#8211; context projection length. See
context_projection&#8217;s document.</li>
<li><strong>hidden_size</strong> (<em>int</em>) &#8211; FC Layer size.</li>
<li><strong>context_start</strong> (<em>int or None</em>) &#8211; context projection length. See
context_projection&#8217;s context_start.</li>
<li><strong>pool_type</strong> (<em>BasePoolingType.</em>) &#8211; pooling layer type. See pooling_layer&#8217;s document.</li>
<li><strong>context_proj_layer_name</strong> (<em>basestring</em>) &#8211; context projection layer name.
None if user don&#8217;t care.</li>
<li><strong>context_proj_param_attr</strong> (<em>ParameterAttribute or None.</em>) &#8211; context projection parameter attribute.
None if user don&#8217;t care.</li>
<li><strong>fc_layer_name</strong> (<em>basestring</em>) &#8211; fc layer name. None if user don&#8217;t care.</li>
<li><strong>fc_param_attr</strong> (<em>ParameterAttribute or None</em>) &#8211; fc layer parameter attribute. None if user don&#8217;t care.</li>
<li><strong>fc_bias_attr</strong> (<em>ParameterAttribute or None</em>) &#8211; fc bias parameter attribute. False if no bias,
None if user don&#8217;t care.</li>
<li><strong>fc_act</strong> (<a class="reference internal" href="activations.html#paddle.trainer_config_helpers.activations.BaseActivation" title="paddle.trainer_config_helpers.activations.BaseActivation"><em>BaseActivation</em></a>) &#8211; fc layer activation type. None means tanh</li>
<li><strong>pool_bias_attr</strong> (<em>ParameterAttribute or None.</em>) &#8211; pooling layer bias attr. None if don&#8217;t care.
False if no bias.</li>
<li><strong>fc_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; fc layer extra attribute.</li>
<li><strong>context_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; context projection layer extra attribute.</li>
<li><strong>pool_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; pooling layer extra attribute.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">output layer name.</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">LayerOutput</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.text_conv_pool">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">text_conv_pool</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.text_conv_pool" title="Permalink to this definition"></a></dt>
<dd><p>Text convolution pooling layers helper.</p>
<p>Text input =&gt; Context Projection =&gt; FC Layer =&gt; Pooling =&gt; Output.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; name of output layer(pooling layer name)</li>
<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; name of input layer</li>
<li><strong>context_len</strong> (<em>int</em>) &#8211; context projection length. See
context_projection&#8217;s document.</li>
<li><strong>hidden_size</strong> (<em>int</em>) &#8211; FC Layer size.</li>
<li><strong>context_start</strong> (<em>int or None</em>) &#8211; context projection length. See
context_projection&#8217;s context_start.</li>
<li><strong>pool_type</strong> (<em>BasePoolingType.</em>) &#8211; pooling layer type. See pooling_layer&#8217;s document.</li>
<li><strong>context_proj_layer_name</strong> (<em>basestring</em>) &#8211; context projection layer name.
None if user don&#8217;t care.</li>
<li><strong>context_proj_param_attr</strong> (<em>ParameterAttribute or None.</em>) &#8211; context projection parameter attribute.
None if user don&#8217;t care.</li>
<li><strong>fc_layer_name</strong> (<em>basestring</em>) &#8211; fc layer name. None if user don&#8217;t care.</li>
<li><strong>fc_param_attr</strong> (<em>ParameterAttribute or None</em>) &#8211; fc layer parameter attribute. None if user don&#8217;t care.</li>
<li><strong>fc_bias_attr</strong> (<em>ParameterAttribute or None</em>) &#8211; fc bias parameter attribute. False if no bias,
None if user don&#8217;t care.</li>
<li><strong>fc_act</strong> (<a class="reference internal" href="activations.html#paddle.trainer_config_helpers.activations.BaseActivation" title="paddle.trainer_config_helpers.activations.BaseActivation"><em>BaseActivation</em></a>) &#8211; fc layer activation type. None means tanh</li>
<li><strong>pool_bias_attr</strong> (<em>ParameterAttribute or None.</em>) &#8211; pooling layer bias attr. None if don&#8217;t care.
False if no bias.</li>
<li><strong>fc_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; fc layer extra attribute.</li>
<li><strong>context_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; context projection layer extra attribute.</li>
<li><strong>pool_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; pooling layer extra attribute.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">output layer name.</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">LayerOutput</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.simple_img_conv_pool">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">simple_img_conv_pool</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.simple_img_conv_pool" title="Permalink to this definition"></a></dt>
<dd><p>Simple image convolution and pooling group.</p>
<p>Input =&gt; conv =&gt; pooling</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; group name</li>
<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; input layer name.</li>
<li><strong>filter_size</strong> (<em>int</em>) &#8211; see img_conv_layer for details</li>
<li><strong>num_filters</strong> (<em>int</em>) &#8211; see img_conv_layer for details</li>
<li><strong>pool_size</strong> (<em>int</em>) &#8211; see img_pool_layer for details</li>
<li><strong>pool_type</strong> (<a class="reference internal" href="poolings.html#paddle.trainer_config_helpers.poolings.BasePoolingType" title="paddle.trainer_config_helpers.poolings.BasePoolingType"><em>BasePoolingType</em></a>) &#8211; see img_pool_layer for details</li>
<li><strong>act</strong> (<a class="reference internal" href="activations.html#paddle.trainer_config_helpers.activations.BaseActivation" title="paddle.trainer_config_helpers.activations.BaseActivation"><em>BaseActivation</em></a>) &#8211; see img_conv_layer for details</li>
<li><strong>groups</strong> (<em>int</em>) &#8211; see img_conv_layer for details</li>
<li><strong>conv_stride</strong> (<em>int</em>) &#8211; see img_conv_layer for details</li>
<li><strong>conv_padding</strong> (<em>int</em>) &#8211; see img_conv_layer for details</li>
<li><strong>bias_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ParameterAttribute" title="paddle.trainer_config_helpers.attrs.ParameterAttribute"><em>ParameterAttribute</em></a>) &#8211; see img_conv_layer for details</li>
<li><strong>num_channel</strong> (<em>int</em>) &#8211; see img_conv_layer for details</li>
<li><strong>param_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ParameterAttribute" title="paddle.trainer_config_helpers.attrs.ParameterAttribute"><em>ParameterAttribute</em></a>) &#8211; see img_conv_layer for details</li>
<li><strong>shared_bias</strong> (<em>bool</em>) &#8211; see img_conv_layer for details</li>
<li><strong>conv_layer_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; see img_conv_layer for details</li>
<li><strong>pool_stride</strong> (<em>int</em>) &#8211; see img_conv_layer for details</li>
<li><strong>pool_start</strong> (<em>int</em>) &#8211; see img_conv_layer for details</li>
<li><strong>pool_padding</strong> (<em>int</em>) &#8211; see img_conv_layer for details</li>
<li><strong>pool_layer_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; see img_conv_layer for details</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">Layer&#8217;s output</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">LayerOutput</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.img_conv_bn_pool">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">img_conv_bn_pool</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.img_conv_bn_pool" title="Permalink to this definition"></a></dt>
<dd><p>Convolution, batch normalization, pooling group.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; group name</li>
<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; layer&#8217;s input</li>
<li><strong>filter_size</strong> (<em>int</em>) &#8211; see img_conv_layer&#8217;s document</li>
<li><strong>num_filters</strong> (<em>int</em>) &#8211; see img_conv_layer&#8217;s document</li>
<li><strong>pool_size</strong> (<em>int</em>) &#8211; see img_pool_layer&#8217;s document.</li>
<li><strong>pool_type</strong> (<a class="reference internal" href="poolings.html#paddle.trainer_config_helpers.poolings.BasePoolingType" title="paddle.trainer_config_helpers.poolings.BasePoolingType"><em>BasePoolingType</em></a>) &#8211; see img_pool_layer&#8217;s document.</li>
<li><strong>act</strong> (<a class="reference internal" href="activations.html#paddle.trainer_config_helpers.activations.BaseActivation" title="paddle.trainer_config_helpers.activations.BaseActivation"><em>BaseActivation</em></a>) &#8211; see batch_norm_layer&#8217;s document.</li>
<li><strong>groups</strong> (<em>int</em>) &#8211; see img_conv_layer&#8217;s document</li>
<li><strong>conv_stride</strong> (<em>int</em>) &#8211; see img_conv_layer&#8217;s document.</li>
<li><strong>conv_padding</strong> (<em>int</em>) &#8211; see img_conv_layer&#8217;s document.</li>
<li><strong>conv_bias_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ParameterAttribute" title="paddle.trainer_config_helpers.attrs.ParameterAttribute"><em>ParameterAttribute</em></a>) &#8211; see img_conv_layer&#8217;s document.</li>
<li><strong>num_channel</strong> (<em>int</em>) &#8211; see img_conv_layer&#8217;s document.</li>
<li><strong>conv_param_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ParameterAttribute" title="paddle.trainer_config_helpers.attrs.ParameterAttribute"><em>ParameterAttribute</em></a>) &#8211; see img_conv_layer&#8217;s document.</li>
<li><strong>shared_bias</strong> (<em>bool</em>) &#8211; see img_conv_layer&#8217;s document.</li>
<li><strong>conv_layer_attr</strong> (<em>ExtraLayerOutput</em>) &#8211; see img_conv_layer&#8217;s document.</li>
<li><strong>bn_param_attr</strong> (<em>ParameterAttribute.</em>) &#8211; see batch_norm_layer&#8217;s document.</li>
<li><strong>bn_bias_attr</strong> &#8211; see batch_norm_layer&#8217;s document.</li>
<li><strong>bn_layer_attr</strong> &#8211; ParameterAttribute.</li>
<li><strong>pool_stride</strong> (<em>int</em>) &#8211; see img_pool_layer&#8217;s document.</li>
<li><strong>pool_start</strong> (<em>int</em>) &#8211; see img_pool_layer&#8217;s document.</li>
<li><strong>pool_padding</strong> (<em>int</em>) &#8211; see img_pool_layer&#8217;s document.</li>
<li><strong>pool_layer_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; see img_pool_layer&#8217;s document.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">Layer groups output</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">LayerOutput</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.img_conv_group">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">img_conv_group</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.img_conv_group" title="Permalink to this definition"></a></dt>
<dd><p>Image Convolution Group, Used for vgg net.</p>
<p>TODO(yuyang18): Complete docs</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>conv_batchnorm_drop_rate</strong> &#8211; </li>
<li><strong>input</strong> &#8211; </li>
<li><strong>conv_num_filter</strong> &#8211; </li>
<li><strong>pool_size</strong> &#8211; </li>
<li><strong>num_channels</strong> &#8211; </li>
<li><strong>conv_padding</strong> &#8211; </li>
<li><strong>conv_filter_size</strong> &#8211; </li>
<li><strong>conv_act</strong> &#8211; </li>
<li><strong>conv_with_batchnorm</strong> &#8211; </li>
<li><strong>pool_stride</strong> &#8211; </li>
<li><strong>pool_type</strong> &#8211; </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.vgg_16_network">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">vgg_16_network</code><span class="sig-paren">(</span><em>input_image</em>, <em>num_channels</em>, <em>num_classes=1000</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.vgg_16_network" title="Permalink to this definition"></a></dt>
<dd><p>Same model from <a class="reference external" href="https://gist.github.com/ksimonyan/211839e770f7b538e2d8">https://gist.github.com/ksimonyan/211839e770f7b538e2d8</a></p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>num_classes</strong> &#8211; </li>
<li><strong>input_image</strong> (<em>LayerOutput</em>) &#8211; </li>
<li><strong>num_channels</strong> (<em>int</em>) &#8211; </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.simple_lstm">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">simple_lstm</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.simple_lstm" title="Permalink to this definition"></a></dt>
<dd><p>Simple LSTM Cell.</p>
<p>It just combine a mix_layer with fully_matrix_projection and a lstmemory
layer. The simple lstm cell was implemented as follow equations.</p>
<div class="math">
\[i_t = \sigma(W_{xi}x_{t} + W_{hi}h_{t-1} + W_{ci}c_{t-1} + b_i)\]\[f_t = \sigma(W_{xf}x_{t} + W_{hf}h_{t-1} + W_{cf}c_{t-1} + b_f)\]\[c_t = f_tc_{t-1} + i_t tanh (W_{xc}x_t+W_{hc}h_{t-1} + b_c)\]\[o_t = \sigma(W_{xo}x_{t} + W_{ho}h_{t-1} + W_{co}c_t + b_o)\]\[h_t = o_t tanh(c_t)\]</div>
<p>Please refer <strong>Generating Sequences With Recurrent Neural Networks</strong> if you
want to know what lstm is. <a class="reference external" href="http://arxiv.org/abs/1308.0850">Link</a> is here.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; lstm layer name.</li>
<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; input layer name.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; lstm layer size.</li>
<li><strong>reverse</strong> (<em>bool</em>) &#8211; is lstm reversed</li>
<li><strong>mat_param_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ParameterAttribute" title="paddle.trainer_config_helpers.attrs.ParameterAttribute"><em>ParameterAttribute</em></a>) &#8211; mixed layer&#8217;s matrix projection parameter attribute.</li>
<li><strong>bias_param_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; bias parameter attribute. False means no bias, None
means default bias.</li>
<li><strong>inner_param_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ParameterAttribute" title="paddle.trainer_config_helpers.attrs.ParameterAttribute"><em>ParameterAttribute</em></a>) &#8211; lstm cell parameter attribute.</li>
<li><strong>act</strong> (<a class="reference internal" href="activations.html#paddle.trainer_config_helpers.activations.BaseActivation" title="paddle.trainer_config_helpers.activations.BaseActivation"><em>BaseActivation</em></a>) &#8211; lstm final activate type</li>
<li><strong>gate_act</strong> (<a class="reference internal" href="activations.html#paddle.trainer_config_helpers.activations.BaseActivation" title="paddle.trainer_config_helpers.activations.BaseActivation"><em>BaseActivation</em></a>) &#8211; lstm gate activate type</li>
<li><strong>state_act</strong> (<a class="reference internal" href="activations.html#paddle.trainer_config_helpers.activations.BaseActivation" title="paddle.trainer_config_helpers.activations.BaseActivation"><em>BaseActivation</em></a>) &#8211; lstm state activate type.</li>
<li><strong>mixed_layer_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; mixed layer&#8217;s extra attribute.</li>
<li><strong>lstm_cell_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ExtraLayerAttribute" title="paddle.trainer_config_helpers.attrs.ExtraLayerAttribute"><em>ExtraLayerAttribute</em></a>) &#8211; lstm layer&#8217;s extra attribute.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">lstm layer name.</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">LayerOutput</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.lstmemory_unit">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">lstmemory_unit</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.lstmemory_unit" title="Permalink to this definition"></a></dt>
<dd><p>TODO(yuyang18): complete docs</p>
<p>&#64;param input:
&#64;param name:
&#64;param size:
&#64;param mixed_bias_attr:
&#64;param mixed_layer_attr:
&#64;param param_attr:
&#64;param lstm_bias_attr:
&#64;param act:
&#64;param gate_act:
&#64;param state_act:
&#64;param lstm_layer_attr:
&#64;param get_output_layer_attr:
&#64;return:</p>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.lstmemory_group">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">lstmemory_group</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.lstmemory_group" title="Permalink to this definition"></a></dt>
<dd><p>TODO(yuyang18): complete docs</p>
<p>&#64;param input:
&#64;param size:
&#64;param name:
&#64;param reverse:
&#64;param param_attr:
&#64;param mix_bias_attr:
&#64;param lstm_bias_attr:
&#64;param act:
&#64;param gate_act:
&#64;param state_act:
&#64;param mixed_layer_attr:
&#64;param lstm_layer_attr:
&#64;param get_output_layer_attr:
&#64;return:</p>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.gru_unit">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">gru_unit</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.gru_unit" title="Permalink to this definition"></a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; </li>
<li><strong>name</strong> &#8211; </li>
<li><strong>size</strong> &#8211; </li>
<li><strong>gru_bias_attr</strong> &#8211; </li>
<li><strong>act</strong> &#8211; </li>
<li><strong>gate_act</strong> &#8211; </li>
<li><strong>gru_layer_attr</strong> &#8211; </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.bidirectional_lstm">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">bidirectional_lstm</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.bidirectional_lstm" title="Permalink to this definition"></a></dt>
<dd><p>TODO(yuyang18): Complete docs</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; bidirectional lstm layer name.</li>
<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; input layer.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; lstm layer size.</li>
<li><strong>return_seq</strong> (<em>bool</em>) &#8211; If False, concat word in last time step and return.
If True, concat sequnce in all time step and return.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">lstm layer name.</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">LayerOutput</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.simple_attention">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">simple_attention</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.simple_attention" title="Permalink to this definition"></a></dt>
<dd><p>Calculate and then return a context vector by attention machanism.
Size of the context vector equals to size of encoded_sequence.</p>
<div class="math">
\[a(s_{i-1},h_{j}) = v_{a}f(W_{a}s_{t-1} + U_{a}h_{j})\]</div>
<div class="math">
\[e_{i,j} = a(s_{i-1}, h_{j})\]</div>
<div class="math">
\[a_{i,j} = \frac{exp(e_{i,i})}{\sum_{k=1}^{T_{x}{exp(e_{i,k})}}}\]</div>
<div class="math">
\[c_{i} = \sum_{j=1}^{T_{x}}a_{i,j}h_{j}\]</div>
<p>where <span class="math">\(h_{j}\)</span> is the jth element of encoded_sequence,
<span class="math">\(U_{a}h_{j}\)</span> is the jth element of encoded_proj
<span class="math">\(s_{i-1}\)</span> is decoder_state
<span class="math">\(f\)</span> is weight_act, and is set to tanh by default.</p>
<p>Please refer to <strong>Neural Machine Translation by Jointly Learning to
Align and Translate</strong> for more details. The link is as follows:
<a class="reference external" href="https://arxiv.org/abs/1409.0473">https://arxiv.org/abs/1409.0473</a>.</p>
<p>The example usage is:
..  code-block:: python</p>
<blockquote>
<div><dl class="docutils">
<dt>context = simple_attention(encoded_sequence=enc_seq,</dt>
<dd>encoded_proj=enc_proj,
decoder_state=decoder_prev,)</dd>
</dl>
</div></blockquote>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; name of the attention model.</li>
<li><strong>softmax_param_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ParameterAttribute" title="paddle.trainer_config_helpers.attrs.ParameterAttribute"><em>ParameterAttribute</em></a>) &#8211; parameter attribute of sequence softmax
that is used to produce attention weight</li>
<li><strong>weight_act</strong> (<em>Activation</em>) &#8211; activation of the attention model</li>
<li><strong>encoded_sequence</strong> (<em>LayerOutput</em>) &#8211; output of the encoder</li>
<li><strong>encoded_proj</strong> (<em>LayerOutput</em>) &#8211; attention weight is computed by a feed forward neural
network which has two inputs : decoder&#8217;s hidden state
of previous time step and encoder&#8217;s output.
encoded_proj is output of the feed-forward network for
encoder&#8217;s output. Here we pre-compute it outside
simple_attention for speed consideration.</li>
<li><strong>decoder_state</strong> (<em>LayerOutput</em>) &#8211; hidden state of decoder in previous time step</li>
<li><strong>transform_param_attr</strong> (<a class="reference internal" href="attrs.html#paddle.trainer_config_helpers.attrs.ParameterAttribute" title="paddle.trainer_config_helpers.attrs.ParameterAttribute"><em>ParameterAttribute</em></a>) &#8211; parameter attribute of the feed-forward
network that takes decoder_state as inputs to
compute attention weight.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a context vector</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.dropout_layer">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">dropout_layer</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.dropout_layer" title="Permalink to this definition"></a></dt>
<dd><p>&#64;TODO(yuyang18): Add comments.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> &#8211; </li>
<li><strong>input</strong> &#8211; </li>
<li><strong>dropout_rate</strong> &#8211; </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
</td>
</tr>
</tbody>
</table>
</dd></dl>

<dl class="function">
<dt id="paddle.trainer_config_helpers.networks.outputs">
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">outputs</code><span class="sig-paren">(</span><em>layers</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.trainer_config_helpers.networks.outputs" title="Permalink to this definition"></a></dt>
<dd><p>Declare the end of network. Currently it will only calculate the
input/output order of network. It will calculate the predict network or
train network&#8217;s output automatically.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>layers</strong> (<em>list|tuple|LayerOutput</em>) &#8211; </td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>

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