Skip to content

P
Paddle

PaddlePaddle / Paddle
大约 1 年 前同步成功

通知 2299
Star 20931
Fork 5422
P
Paddle
切换分支/标签
查找文件 普通视图历史永久链接Permalink
networks.html 54.2 KB
Newer Older
Y
Update docs  
Yu Yang 已提交
1 2 3 4 5 6 7 8 
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
  "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">


<html xmlns="http://www.w3.org/1999/xhtml">
  <head>
    <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
Y
Upload docs  
Yu Yang 已提交
9 
    <title>NLP &mdash; PaddlePaddle  documentation</title>
Y
Update docs  
Yu Yang 已提交
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 
    
    <link rel="stylesheet" href="../../../_static/classic.css" type="text/css" />
    <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
    
    <script type="text/javascript">
      var DOCUMENTATION_OPTIONS = {
        URL_ROOT:    '../../../',
        VERSION:     '',
        COLLAPSE_INDEX: false,
        FILE_SUFFIX: '.html',
        HAS_SOURCE:  true
      };
    </script>
    <script type="text/javascript" src="../../../_static/jquery.js"></script>
    <script type="text/javascript" src="../../../_static/underscore.js"></script>
    <script type="text/javascript" src="../../../_static/doctools.js"></script>
    <script type="text/javascript" src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
    <link rel="top" title="PaddlePaddle  documentation" href="../../../index.html" />
Y
Upload docs  
Yu Yang 已提交
28 29 30 
    <link rel="up" title="Networks" href="networks_index.html" />
    <link rel="next" title="Evaluators" href="evaluators_index.html" />
    <link rel="prev" title="Networks" href="networks_index.html" />
Y
Update docs  
Yu Yang 已提交
31 32 33 34 35 36 37 38 39 40 41 42 
  </head>
  <body role="document">
    <div class="related" role="navigation" aria-label="related navigation">
      <h3>Navigation</h3>
      <ul>
        <li class="right" style="margin-right: 10px">
          <a href="../../../genindex.html" title="General Index"
             accesskey="I">index</a></li>
        <li class="right" >
          <a href="../../../py-modindex.html" title="Python Module Index"
             >modules</a> |</li>
        <li class="right" >
Y
Upload docs  
Yu Yang 已提交
43 
          <a href="evaluators_index.html" title="Evaluators"
Y
Update docs  
Yu Yang 已提交
44 45 
             accesskey="N">next</a> |</li>
        <li class="right" >
Y
Upload docs  
Yu Yang 已提交
46 
          <a href="networks_index.html" title="Networks"
Y
Update docs  
Yu Yang 已提交
47 48 49 
             accesskey="P">previous</a> |</li>
        <li class="nav-item nav-item-0"><a href="../../../index.html">PaddlePaddle  documentation</a> &raquo;</li>
          <li class="nav-item nav-item-1"><a href="../../index.html" >User Interface</a> &raquo;</li>
Y
Upload docs  
Yu Yang 已提交
50 51 
          <li class="nav-item nav-item-2"><a href="index.html" >Model Config Interface</a> &raquo;</li>
          <li class="nav-item nav-item-3"><a href="networks_index.html" accesskey="U">Networks</a> &raquo;</li>
Y
Update docs  
Yu Yang 已提交
52 53 54 55 56 57 58 59 
      </ul>
    </div>  

    <div class="document">
      <div class="documentwrapper">
        <div class="bodywrapper">
          <div class="body" role="main">
Y
Upload docs  
Yu Yang 已提交
60 61 62 63 
  <div class="section" id="nlp">
<h1>NLP<a class="headerlink" href="#nlp" title="Permalink to this headline"></a></h1>
<div class="section" id="sequence-conv-pool">
<h2>sequence_conv_pool<a class="headerlink" href="#sequence-conv-pool" title="Permalink to this headline"></a></h2>
Y
Update docs  
Yu Yang 已提交
64 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
65 66 
<dt>
<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></dt>
Y
Update docs  
Yu Yang 已提交
67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 
<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>
Y
Upload docs  
Yu Yang 已提交
90 
<li><strong>fc_act</strong> (<em>BaseActivation</em>) &#8211; fc layer activation type. None means tanh</li>
Y
Update docs  
Yu Yang 已提交
91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 
<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>
Y
Upload docs  
Yu Yang 已提交
109 110 111 
</div>
<div class="section" id="text-conv-pool">
<h2>text_conv_pool<a class="headerlink" href="#text-conv-pool" title="Permalink to this headline"></a></h2>
Y
Update docs  
Yu Yang 已提交
112 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
113 114 
<dt>
<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></dt>
Y
Update docs  
Yu Yang 已提交
115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 
<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>
Y
Upload docs  
Yu Yang 已提交
138 
<li><strong>fc_act</strong> (<em>BaseActivation</em>) &#8211; fc layer activation type. None means tanh</li>
Y
Update docs  
Yu Yang 已提交
139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 
<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>
Y
Upload docs  
Yu Yang 已提交
157 158 159 160 161 162 
</div>
</div>
<div class="section" id="images">
<h1>Images<a class="headerlink" href="#images" title="Permalink to this headline"></a></h1>
<div class="section" id="img-conv-bn-pool">
<h2>img_conv_bn_pool<a class="headerlink" href="#img-conv-bn-pool" title="Permalink to this headline"></a></h2>
Y
Update docs  
Yu Yang 已提交
163 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
164 165 
<dt>
<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></dt>
Y
Update docs  
Yu Yang 已提交
166 167 168 169 170 171 172 173 174 175 176 
<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>
Y
Upload docs  
Yu Yang 已提交
177 178 
<li><strong>pool_type</strong> (<em>BasePoolingType</em>) &#8211; see img_pool_layer&#8217;s document.</li>
<li><strong>act</strong> (<em>BaseActivation</em>) &#8211; see batch_norm_layer&#8217;s document.</li>
Y
Update docs  
Yu Yang 已提交
179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 
<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>
Y
Upload docs  
Yu Yang 已提交
207 208 209 
</div>
<div class="section" id="img-conv-group">
<h2>img_conv_group<a class="headerlink" href="#img-conv-group" title="Permalink to this headline"></a></h2>
Y
Update docs  
Yu Yang 已提交
210 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
211 212 
<dt>
<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></dt>
Y
Update docs  
Yu Yang 已提交
213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 
<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>
Y
Upload docs  
Yu Yang 已提交
241 242 243 
</div>
<div class="section" id="simple-img-conv-pool">
<h2>simple_img_conv_pool<a class="headerlink" href="#simple-img-conv-pool" title="Permalink to this headline"></a></h2>
Y
Update docs  
Yu Yang 已提交
244 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 
<dt>
<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></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> (<em>BasePoolingType</em>) &#8211; see img_pool_layer for details</li>
<li><strong>act</strong> (<em>BaseActivation</em>) &#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>

</div>
<div class="section" id="vgg-16-network">
<h2>vgg_16_network<a class="headerlink" href="#vgg-16-network" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt>
<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></dt>
Y
Update docs  
Yu Yang 已提交
292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 
<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>
Y
Upload docs  
Yu Yang 已提交
311 312 313 314 315 316 317 318 
</div>
</div>
<div class="section" id="recurrent">
<h1>Recurrent<a class="headerlink" href="#recurrent" title="Permalink to this headline"></a></h1>
<div class="section" id="lstm">
<h2>LSTM<a class="headerlink" href="#lstm" title="Permalink to this headline"></a></h2>
<div class="section" id="lstmemory-unit">
<h3>lstmemory_unit<a class="headerlink" href="#lstmemory-unit" title="Permalink to this headline"></a></h3>
Y
Update docs  
Yu Yang 已提交
319 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
320 321 
<dt>
<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></dt>
Y
Update doc  
Yu Yang 已提交
322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 
<dd><p>Define calculations that a LSTM unit performs in a single time step.
This function itself is not a recurrent layer, so that it can not be
directly applied to sequence input. This function is always used in
recurrent_group (see layers.py for more details) to implement attention
mechanism.</p>
<p>Please refer to  <strong>Generating Sequences With Recurrent Neural Networks</strong>
for more details about LSTM. The link goes as follows:
.. _Link: <a class="reference external" href="https://arxiv.org/abs/1308.0850">https://arxiv.org/abs/1308.0850</a></p>
<div class="math">
\[\begin{split}i_t &amp; = \sigma(W_{xi}x_{t} + W_{hi}h_{t-1} + W_{ci}c_{t-1} + b_i)\end{split}\]\[\begin{split}f_t &amp; = \sigma(W_{xf}x_{t} + W_{hf}h_{t-1} + W_{cf}c_{t-1} + b_f)\end{split}\]\[\begin{split}c_t &amp; = f_tc_{t-1} + i_t tanh (W_{xc}x_t+W_{hc}h_{t-1} + b_c)\end{split}\]\[\begin{split}o_t &amp; = \sigma(W_{xo}x_{t} + W_{ho}h_{t-1} + W_{co}c_t + b_o)\end{split}\]\[\begin{split}h_t &amp; = o_t tanh(c_t)\end{split}\]</div>
<p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">lstm_step</span> <span class="o">=</span> <span class="n">lstmemory_unit</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="p">[</span><span class="n">layer1</span><span class="p">],</span>
                           <span class="n">size</span><span class="o">=</span><span class="mi">256</span><span class="p">,</span>
                           <span class="n">act</span><span class="o">=</span><span class="n">TanhActivation</span><span class="p">(),</span>
                           <span class="n">gate_act</span><span class="o">=</span><span class="n">SigmoidActivation</span><span class="p">(),</span>
                           <span class="n">state_act</span><span class="o">=</span><span class="n">TanhActivation</span><span class="p">())</span>
</pre></div>
</div>
Y
Update docs  
Yu Yang 已提交
340 341 342 343 344 345 
<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; input layer name.</li>
Y
Upload docs  
Yu Yang 已提交
346 347 348 
<li><strong>name</strong> (<em>basestring</em>) &#8211; lstmemory unit name.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; lstmemory unit size.</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; Parameter config, None if use default.</li>
Y
Update doc  
Yu Yang 已提交
349 350 351 
<li><strong>act</strong> (<em>BaseActivation</em>) &#8211; lstm final activiation type</li>
<li><strong>gate_act</strong> (<em>BaseActivation</em>) &#8211; lstm gate activiation type</li>
<li><strong>state_act</strong> (<em>BaseActivation</em>) &#8211; lstm state activiation type.</li>
Y
Upload docs  
Yu Yang 已提交
352 353 354 355 
<li><strong>mixed_bias_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; bias parameter attribute of mixed layer.
False means no bias, None means default bias.</li>
<li><strong>lstm_bias_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; bias parameter attribute of lstm layer.
False means no bias, None means default bias.</li>
Y
Update docs  
Yu Yang 已提交
356 
<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>
Y
Upload docs  
Yu Yang 已提交
357 358 
<li><strong>lstm_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; lstm layer&#8217;s extra attribute.</li>
<li><strong>get_output_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; get output layer&#8217;s extra attribute.</li>
Y
Update docs  
Yu Yang 已提交
359 360 361 
</ul>
</td>
</tr>
Y
Upload docs  
Yu Yang 已提交
362 
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">lstmemory unit name.</p>
Y
Update docs  
Yu Yang 已提交
363 364 365 366 367 368 369 370 371 
</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>
Y
Upload docs  
Yu Yang 已提交
372 373 374 
</div>
<div class="section" id="lstmemory-group">
<h3>lstmemory_group<a class="headerlink" href="#lstmemory-group" title="Permalink to this headline"></a></h3>
Y
Update docs  
Yu Yang 已提交
375 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
376 377 
<dt>
<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></dt>
Y
Update doc  
Yu Yang 已提交
378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 
<dd><p>lstm_group is a recurrent layer group version Long Short Term Memory. It
does exactly the same calculation as the lstmemory layer (see lstmemory in
layers.py for the maths) does. A promising benefit is that LSTM memory
cell states, or hidden states in every time step are accessible to for the
user. This is especially useful in attention model. If you do not need to
access to the internal states of the lstm, but merely use its outputs,
it is recommanded to use the lstmemory, which is relatively faster than
lstmemory_group.</p>
<p>NOTE: In PaddlePaddle&#8217;s implementation, the following input-to-hidden
multiplications:
<span class="math">\(W_{xi}x_{t}\)</span> , <span class="math">\(W_{xf}x_{t}\)</span>,
<span class="math">\(W_{xc}x_t\)</span>, <span class="math">\(W_{xo}x_{t}\)</span> are not done in lstmemory_unit to
speed up the calculations. Consequently, an additional mixed_layer with
full_matrix_projection must be included before lstmemory_unit is called.</p>
<p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">lstm_step</span> <span class="o">=</span> <span class="n">lstmemory_group</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="p">[</span><span class="n">layer1</span><span class="p">],</span>
                            <span class="n">size</span><span class="o">=</span><span class="mi">256</span><span class="p">,</span>
                            <span class="n">act</span><span class="o">=</span><span class="n">TanhActivation</span><span class="p">(),</span>
                            <span class="n">gate_act</span><span class="o">=</span><span class="n">SigmoidActivation</span><span class="p">(),</span>
                            <span class="n">state_act</span><span class="o">=</span><span class="n">TanhActivation</span><span class="p">())</span>
</pre></div>
</div>
Y
Upload docs  
Yu Yang 已提交
400 401 402 403 404 405 406 407 408 409 
<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; input layer name.</li>
<li><strong>name</strong> (<em>basestring</em>) &#8211; lstmemory group name.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; lstmemory group size.</li>
<li><strong>reverse</strong> (<em>bool</em>) &#8211; is lstm reversed</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; Parameter config, None if use default.</li>
Y
Update doc  
Yu Yang 已提交
410 411 412 
<li><strong>act</strong> (<em>BaseActivation</em>) &#8211; lstm final activiation type</li>
<li><strong>gate_act</strong> (<em>BaseActivation</em>) &#8211; lstm gate activiation type</li>
<li><strong>state_act</strong> (<em>BaseActivation</em>) &#8211; lstm state activiation type.</li>
Y
Upload docs  
Yu Yang 已提交
413 414 415 416 417 418 419 420 421 422 
<li><strong>mixed_bias_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; bias parameter attribute of mixed layer.
False means no bias, None means default bias.</li>
<li><strong>lstm_bias_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; bias parameter attribute of lstm layer.
False means no bias, None means default bias.</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_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; lstm layer&#8217;s extra attribute.</li>
<li><strong>get_output_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; get output layer&#8217;s extra attribute.</li>
</ul>
</td>
</tr>
Y
Update doc  
Yu Yang 已提交
423 
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">the lstmemory group.</p>
Y
Upload docs  
Yu Yang 已提交
424 425 426 427 428 429 430 
</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>
Y
Update docs  
Yu Yang 已提交
431 432 
</dd></dl>
Y
Upload docs  
Yu Yang 已提交
433 434 435 
</div>
<div class="section" id="simple-lstm">
<h3>simple_lstm<a class="headerlink" href="#simple-lstm" title="Permalink to this headline"></a></h3>
Y
Update docs  
Yu Yang 已提交
436 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
437 438 439 440 441 442 443 444 445 446 
<dt>
<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></dt>
<dd><p>Simple LSTM Cell.</p>
<p>It just combine a mixed layer with fully_matrix_projection and a lstmemory
layer. The simple lstm cell was implemented as follow equations.</p>
<div class="math">
\[\begin{split}i_t &amp; = \sigma(W_{xi}x_{t} + W_{hi}h_{t-1} + W_{ci}c_{t-1} + b_i)\end{split}\]\[\begin{split}f_t &amp; = \sigma(W_{xf}x_{t} + W_{hf}h_{t-1} + W_{cf}c_{t-1} + b_f)\end{split}\]\[\begin{split}c_t &amp; = f_tc_{t-1} + i_t tanh (W_{xc}x_t+W_{hc}h_{t-1} + b_c)\end{split}\]\[\begin{split}o_t &amp; = \sigma(W_{xo}x_{t} + W_{ho}h_{t-1} + W_{co}c_t + b_o)\end{split}\]\[\begin{split}h_t &amp; = o_t tanh(c_t)\end{split}\]</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">
Y
Update docs  
Yu Yang 已提交
447 448 449 450 
<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">
Y
Upload docs  
Yu Yang 已提交
451 452 453 
<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>
Y
Update doc  
Yu Yang 已提交
454 
<li><strong>reverse</strong> (<em>bool</em>) &#8211; whether to process the input data in a reverse order</li>
Y
Upload docs  
Yu Yang 已提交
455 456 457 458 
<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>
Y
Update doc  
Yu Yang 已提交
459 460 461 
<li><strong>act</strong> (<em>BaseActivation</em>) &#8211; lstm final activiation type</li>
<li><strong>gate_act</strong> (<em>BaseActivation</em>) &#8211; lstm gate activiation type</li>
<li><strong>state_act</strong> (<em>BaseActivation</em>) &#8211; lstm state activiation type.</li>
Y
Upload docs  
Yu Yang 已提交
462 463 
<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>
Y
Update docs  
Yu Yang 已提交
464 465 466 
</ul>
</td>
</tr>
Y
Upload docs  
Yu Yang 已提交
467 468 469 470 
<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>
Y
Update docs  
Yu Yang 已提交
471 472 473 474 475 476 
</td>
</tr>
</tbody>
</table>
</dd></dl>
Y
Upload docs  
Yu Yang 已提交
477 478 479 
</div>
<div class="section" id="bidirectional-lstm">
<h3>bidirectional_lstm<a class="headerlink" href="#bidirectional-lstm" title="Permalink to this headline"></a></h3>
Y
Update docs  
Yu Yang 已提交
480 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
481 482 
<dt>
<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></dt>
Y
Update doc  
Yu Yang 已提交
483 484 485 486 487 488 489 490 491 492 493 494 495 
<dd><p>A bidirectional_lstm is a recurrent unit that iterates over the input
sequence both in forward and bardward orders, and then concatenate two
outputs form a final output. However, concatenation of two outputs
is not the only way to form the final output, you can also, for example,
just add them together.</p>
<p>Please refer to  <strong>Neural Machine Translation by Jointly Learning to Align
and Translate</strong> for more details about the bidirectional lstm.
The link goes as follows:
.. _Link: <a class="reference external" href="https://arxiv.org/pdf/1409.0473v3.pdf">https://arxiv.org/pdf/1409.0473v3.pdf</a></p>
<p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">lstm_step</span> <span class="o">=</span> <span class="n">bidirectional_lstm</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="p">[</span><span class="n">input1</span><span class="p">],</span> <span class="n">size</span><span class="o">=</span><span class="mi">512</span><span class="p">)</span>
</pre></div>
</div>
Y
Update docs  
Yu Yang 已提交
496 497 498 499 500 501 502 503 
<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>
Y
Update doc  
Yu Yang 已提交
504 505 506 507 508 
<li><strong>return_seq</strong> (<em>bool</em>) &#8211; If set False, outputs of the last time step are
concatenated and returned.
If set True, the entire output sequences that are
processed in forward and backward directions are
concatenated and returned.</li>
Y
Update docs  
Yu Yang 已提交
509 510 511 512 513 514 515 516 517 518 519 520 521 
</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>
Y
Upload docs  
Yu Yang 已提交
522 523 524 525 526 527 
</div>
</div>
<div class="section" id="gru">
<h2>GRU<a class="headerlink" href="#gru" title="Permalink to this headline"></a></h2>
<div class="section" id="gru-unit">
<h3>gru_unit<a class="headerlink" href="#gru-unit" title="Permalink to this headline"></a></h3>
Y
Update docs  
Yu Yang 已提交
528 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
529 530 
<dt>
<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></dt>
Y
Update doc  
Yu Yang 已提交
531 532 533 534 535 536 537 
<dd><p>Define calculations that a gated recurrent unit performs in a single time
step. This function itself is not a recurrent layer, so that it can not be
directly applied to sequence input. This function is almost always used in
the recurrent_group (see layers.py for more details) to implement attention
mechanism.</p>
<p>Please see grumemory in layers.py for the details about the maths.</p>
<table class="docutils field-list" frame="void" rules="none">
Y
Upload docs  
Yu Yang 已提交
538 539 540 541 
<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">
Y
Update doc  
Yu Yang 已提交
542 543 544 545 546 547 
<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; input layer name.</li>
<li><strong>name</strong> (<em>basestring</em>) &#8211; name of the gru group.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; hidden size of the gru.</li>
<li><strong>act</strong> (<em>BaseActivation</em>) &#8211; type of the activation</li>
<li><strong>gate_act</strong> (<em>BaseActivation</em>) &#8211; type of the gate activation</li>
<li><strong>gru_layer_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; Extra parameter attribute of the gru layer.</li>
Y
Upload docs  
Yu Yang 已提交
548 549 550 
</ul>
</td>
</tr>
Y
Update doc  
Yu Yang 已提交
551 552 553 554 
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">the gru output layer.</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>
Y
Upload docs  
Yu Yang 已提交
555 556 557 558 559 560 561 562 563 
</td>
</tr>
</tbody>
</table>
</dd></dl>

</div>
<div class="section" id="gru-group">
<h3>gru_group<a class="headerlink" href="#gru-group" title="Permalink to this headline"></a></h3>
Y
Update doc  
Yu Yang 已提交
564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 
<dl class="function">
<dt>
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">gru_group</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>gru_group is a recurrent layer group version Gated Recurrent Unit. It
does exactly the same calculation as the grumemory layer does. A promising
benefit is that gru hidden sates are accessible to for the user. This is
especially useful in attention model. If you do not need to access to
any internal state, but merely use the outputs of a GRU, it is recommanded
to use the grumemory, which is relatively faster.</p>
<p>Please see grumemory in layers.py for more detail about the maths.</p>
<p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">gru</span> <span class="o">=</span> <span class="n">gur_group</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="p">[</span><span class="n">layer1</span><span class="p">],</span>
                <span class="n">size</span><span class="o">=</span><span class="mi">256</span><span class="p">,</span>
                <span class="n">act</span><span class="o">=</span><span class="n">TanhActivation</span><span class="p">(),</span>
                <span class="n">gate_act</span><span class="o">=</span><span class="n">SigmoidActivation</span><span class="p">())</span>
</pre></div>
</div>
<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; input layer name.</li>
<li><strong>name</strong> (<em>basestring</em>) &#8211; name of the gru group.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; hidden size of the gru.</li>
<li><strong>reverse</strong> (<em>bool</em>) &#8211; whether to process the input data in a reverse order</li>
<li><strong>act</strong> (<em>BaseActivation</em>) &#8211; type of the activiation</li>
<li><strong>gate_act</strong> (<em>BaseActivation</em>) &#8211; type of the gate activiation</li>
<li><strong>gru_bias_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; bias. False means no bias, None means default bias.</li>
<li><strong>gru_layer_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; Extra parameter attribute of the gru layer.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">the gru group.</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>
Y
Upload docs  
Yu Yang 已提交
607 608 609 
</div>
<div class="section" id="simple-gru">
<h3>simple_gru<a class="headerlink" href="#simple-gru" title="Permalink to this headline"></a></h3>
Y
Update doc  
Yu Yang 已提交
610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 
<dl class="function">
<dt>
<code class="descclassname">paddle.trainer_config_helpers.networks.</code><code class="descname">simple_gru</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>simple_gru is also a recurrent layer group version Gated Recurrent Unit as
gru_group. The difference only lies in implemention details.
The computational speed is that, grumemory is relatively better than
gru_group, and gru_group is relatively better than simple_gru.</p>
<p>simple_gru does exactly the same calculation as the grumemory layer does.
Please see grumemory in layers.py for more detail about the maths.</p>
<p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">gru</span> <span class="o">=</span> <span class="n">gur_group</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="p">[</span><span class="n">layer1</span><span class="p">],</span>
                <span class="n">size</span><span class="o">=</span><span class="mi">256</span><span class="p">,</span>
                <span class="n">act</span><span class="o">=</span><span class="n">TanhActivation</span><span class="p">(),</span>
                <span class="n">gate_act</span><span class="o">=</span><span class="n">SigmoidActivation</span><span class="p">())</span>
</pre></div>
</div>
<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; input layer name.</li>
<li><strong>name</strong> (<em>basestring</em>) &#8211; name of the gru group.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; hidden size of the gru.</li>
<li><strong>reverse</strong> (<em>bool</em>) &#8211; whether to process the input data in a reverse order</li>
<li><strong>act</strong> (<em>BaseActivation</em>) &#8211; type of the activiation</li>
<li><strong>gate_act</strong> (<em>BaseActivation</em>) &#8211; type of the gate activiation</li>
<li><strong>gru_bias_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; bias. False means no bias, None means default bias.</li>
<li><strong>gru_layer_attr</strong> (<em>ParameterAttribute|False</em>) &#8211; Extra parameter attribute of the gru layer.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">the gru group.</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>
Y
Upload docs  
Yu Yang 已提交
652 653 654 655 656 657 658 
</div>
</div>
<div class="section" id="simple-attention">
<h2>simple_attention<a class="headerlink" href="#simple-attention" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt>
<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></dt>
Y
Update docs  
Yu Yang 已提交
659 
<dd><p>Calculate and then return a context vector by attention machanism.
Y
Upload docs  
Yu Yang 已提交
660 
Size of the context vector equals to size of the encoded_sequence.</p>
Y
Update docs  
Yu Yang 已提交
661 
<div class="math">
Y
Upload docs  
Yu Yang 已提交
662 
\[\begin{split}a(s_{i-1},h_{j}) &amp; = v_{a}f(W_{a}s_{t-1} + U_{a}h_{j})\end{split}\]\[\begin{split}e_{i,j} &amp; = a(s_{i-1}, h_{j})\end{split}\]\[\begin{split}a_{i,j} &amp; = \frac{exp(e_{i,j})}{\sum_{k=1}^{T_x}{exp(e_{i,k})}}\end{split}\]\[\begin{split}c_{i} &amp; = \sum_{j=1}^{T_{x}}a_{i,j}h_{j}\end{split}\]</div>
Y
Update docs  
Yu Yang 已提交
663 664 665 666 667 668 669 
<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>
Y
Upload docs  
Yu Yang 已提交
670 671 672 673 674 675 
<p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">context</span> <span class="o">=</span> <span class="n">simple_attention</span><span class="p">(</span><span class="n">encoded_sequence</span><span class="o">=</span><span class="n">enc_seq</span><span class="p">,</span>
                           <span class="n">encoded_proj</span><span class="o">=</span><span class="n">enc_proj</span><span class="p">,</span>
                           <span class="n">decoder_state</span><span class="o">=</span><span class="n">decoder_prev</span><span class="p">,)</span>
</pre></div>
</div>
Y
Update docs  
Yu Yang 已提交
676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 
<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>
Y
Upload docs  
Yu Yang 已提交
706 707 708 709 710 711 
</div>
</div>
<div class="section" id="miscs">
<h1>Miscs<a class="headerlink" href="#miscs" title="Permalink to this headline"></a></h1>
<div class="section" id="dropout-layer">
<h2>dropout_layer<a class="headerlink" href="#dropout-layer" title="Permalink to this headline"></a></h2>
Y
Update docs  
Yu Yang 已提交
712 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
713 714 
<dt>
<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></dt>
Y
Update docs  
Yu Yang 已提交
715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 
<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>
Y
Upload docs  
Yu Yang 已提交
734 735 736 
</div>
<div class="section" id="outputs">
<h2>outputs<a class="headerlink" href="#outputs" title="Permalink to this headline"></a></h2>
Y
Update docs  
Yu Yang 已提交
737 
<dl class="function">
Y
Upload docs  
Yu Yang 已提交
738 739 
<dt>
<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></dt>
Y
Update docs  
Yu Yang 已提交
740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 
<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>
Y
Upload docs  
Yu Yang 已提交
755 
</div>
Y
Update docs  
Yu Yang 已提交
756 757 758 759 760 761 762 763 
</div>


          </div>
        </div>
      </div>
      <div class="sphinxsidebar" role="navigation" aria-label="main navigation">
        <div class="sphinxsidebarwrapper">
Y
Upload docs  
Yu Yang 已提交
764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 
  <h3><a href="../../../index.html">Table Of Contents</a></h3>
  <ul>
<li><a class="reference internal" href="#">NLP</a><ul>
<li><a class="reference internal" href="#sequence-conv-pool">sequence_conv_pool</a></li>
<li><a class="reference internal" href="#text-conv-pool">text_conv_pool</a></li>
</ul>
</li>
<li><a class="reference internal" href="#images">Images</a><ul>
<li><a class="reference internal" href="#img-conv-bn-pool">img_conv_bn_pool</a></li>
<li><a class="reference internal" href="#img-conv-group">img_conv_group</a></li>
<li><a class="reference internal" href="#simple-img-conv-pool">simple_img_conv_pool</a></li>
<li><a class="reference internal" href="#vgg-16-network">vgg_16_network</a></li>
</ul>
</li>
<li><a class="reference internal" href="#recurrent">Recurrent</a><ul>
<li><a class="reference internal" href="#lstm">LSTM</a><ul>
<li><a class="reference internal" href="#lstmemory-unit">lstmemory_unit</a></li>
<li><a class="reference internal" href="#lstmemory-group">lstmemory_group</a></li>
<li><a class="reference internal" href="#simple-lstm">simple_lstm</a></li>
<li><a class="reference internal" href="#bidirectional-lstm">bidirectional_lstm</a></li>
</ul>
</li>
<li><a class="reference internal" href="#gru">GRU</a><ul>
<li><a class="reference internal" href="#gru-unit">gru_unit</a></li>
<li><a class="reference internal" href="#gru-group">gru_group</a></li>
<li><a class="reference internal" href="#simple-gru">simple_gru</a></li>
</ul>
</li>
<li><a class="reference internal" href="#simple-attention">simple_attention</a></li>
</ul>
</li>
<li><a class="reference internal" href="#miscs">Miscs</a><ul>
<li><a class="reference internal" href="#dropout-layer">dropout_layer</a></li>
<li><a class="reference internal" href="#outputs">outputs</a></li>
</ul>
</li>
</ul>
Y
Update docs  
Yu Yang 已提交
802 
  <h4>Previous topic</h4>
Y
Upload docs  
Yu Yang 已提交
803 804 
  <p class="topless"><a href="networks_index.html"
                        title="previous chapter">Networks</a></p>
Y
Update docs  
Yu Yang 已提交
805 
  <h4>Next topic</h4>
Y
Upload docs  
Yu Yang 已提交
806 
  <p class="topless"><a href="evaluators_index.html"
Y
Update docs  
Yu Yang 已提交
807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 
                        title="next chapter">Evaluators</a></p>
  <div role="note" aria-label="source link">
    <h3>This Page</h3>
    <ul class="this-page-menu">
      <li><a href="../../../_sources/ui/api/trainer_config_helpers/networks.txt"
            rel="nofollow">Show Source</a></li>
    </ul>
   </div>
<div id="searchbox" style="display: none" role="search">
  <h3>Quick search</h3>
    <form class="search" action="../../../search.html" method="get">
      <input type="text" name="q" />
      <input type="submit" value="Go" />
      <input type="hidden" name="check_keywords" value="yes" />
      <input type="hidden" name="area" value="default" />
    </form>
    <p class="searchtip" style="font-size: 90%">
    Enter search terms or a module, class or function name.
    </p>
</div>
<script type="text/javascript">$('#searchbox').show(0);</script>
        </div>
      </div>
      <div class="clearer"></div>
    </div>
    <div class="related" role="navigation" aria-label="related navigation">
      <h3>Navigation</h3>
      <ul>
        <li class="right" style="margin-right: 10px">
          <a href="../../../genindex.html" title="General Index"
             >index</a></li>
        <li class="right" >
          <a href="../../../py-modindex.html" title="Python Module Index"
             >modules</a> |</li>
        <li class="right" >
Y
Upload docs  
Yu Yang 已提交
842 
          <a href="evaluators_index.html" title="Evaluators"
Y
Update docs  
Yu Yang 已提交
843 844 
             >next</a> |</li>
        <li class="right" >
Y
Upload docs  
Yu Yang 已提交
845 
          <a href="networks_index.html" title="Networks"
Y
Update docs  
Yu Yang 已提交
846 847 848 
             >previous</a> |</li>
        <li class="nav-item nav-item-0"><a href="../../../index.html">PaddlePaddle  documentation</a> &raquo;</li>
          <li class="nav-item nav-item-1"><a href="../../index.html" >User Interface</a> &raquo;</li>
Y
Upload docs  
Yu Yang 已提交
849 850 
          <li class="nav-item nav-item-2"><a href="index.html" >Model Config Interface</a> &raquo;</li>
          <li class="nav-item nav-item-3"><a href="networks_index.html" >Networks</a> &raquo;</li>
Y
Update docs  
Yu Yang 已提交
851 852 853 854 855 856 857 858 
      </ul>
    </div>
    <div class="footer" role="contentinfo">
        &copy; Copyright 2016, PaddlePaddle developers.
      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.3.5.
    </div>
  </body>
</html>