Deploy to GitHub Pages: 0d26a158

develop/doc/api/v2/config/networks.html

@@ -342,27 +342,33 @@ False if no bias.</li>
 <dt>
 <code class="descclassname">paddle.v2.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>
 <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>
+<li><strong>conv_batchnorm_drop_rate</strong> (<em>list</em>) &#8211; if conv_with_batchnorm[i] is true,
+conv_batchnorm_drop_rate[i] represents the drop rate of each batch norm.</li>
+<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; layer&#8217;s input.</li>
+<li><strong>conv_num_filter</strong> (<em>int</em>) &#8211; output channels num.</li>
+<li><strong>pool_size</strong> (<em>int</em>) &#8211; pooling filter size.</li>
+<li><strong>num_channels</strong> (<em>int</em>) &#8211; input channels num.</li>
+<li><strong>conv_padding</strong> (<em>int</em>) &#8211; convolution padding size.</li>
+<li><strong>conv_filter_size</strong> (<em>int</em>) &#8211; convolution filter size.</li>
+<li><strong>conv_act</strong> (<em>BaseActivation</em>) &#8211; activation funciton after convolution.</li>
+<li><strong>conv_with_batchnorm</strong> (<em>list</em>) &#8211; conv_with_batchnorm[i] represents
+if there is a batch normalization after each convolution.</li>
+<li><strong>pool_stride</strong> (<em>int</em>) &#8211; pooling stride size.</li>
+<li><strong>pool_type</strong> (<em>BasePoolingType</em>) &#8211; pooling type.</li>
+<li><strong>param_attr</strong> (<em>ParameterAttribute</em>) &#8211; Convolution param attribute.
+None means default attribute.</li>
 </ul>
 </td>
 </tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
+<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">Type:</th><td class="field-body"><p class="first last">LayerOutput</p>
 </td>
 </tr>
 </tbody>

develop/doc_cn/api/v2/config/networks.html

@@ -347,27 +347,33 @@ False if no bias.</li>
 <dt>
 <code class="descclassname">paddle.v2.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>
 <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">参数:</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>
+<li><strong>conv_batchnorm_drop_rate</strong> (<em>list</em>) &#8211; if conv_with_batchnorm[i] is true,
+conv_batchnorm_drop_rate[i] represents the drop rate of each batch norm.</li>
+<li><strong>input</strong> (<em>LayerOutput</em>) &#8211; layer&#8217;s input.</li>
+<li><strong>conv_num_filter</strong> (<em>int</em>) &#8211; output channels num.</li>
+<li><strong>pool_size</strong> (<em>int</em>) &#8211; pooling filter size.</li>
+<li><strong>num_channels</strong> (<em>int</em>) &#8211; input channels num.</li>
+<li><strong>conv_padding</strong> (<em>int</em>) &#8211; convolution padding size.</li>
+<li><strong>conv_filter_size</strong> (<em>int</em>) &#8211; convolution filter size.</li>
+<li><strong>conv_act</strong> (<em>BaseActivation</em>) &#8211; activation funciton after convolution.</li>
+<li><strong>conv_with_batchnorm</strong> (<em>list</em>) &#8211; conv_with_batchnorm[i] represents
+if there is a batch normalization after each convolution.</li>
+<li><strong>pool_stride</strong> (<em>int</em>) &#8211; pooling stride size.</li>
+<li><strong>pool_type</strong> (<em>BasePoolingType</em>) &#8211; pooling type.</li>
+<li><strong>param_attr</strong> (<em>ParameterAttribute</em>) &#8211; Convolution param attribute.
+None means default attribute.</li>
 </ul>
 </td>
 </tr>
-<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first last"></p>
+<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first">Layer&#8217;s output</p>
+</td>
+</tr>
+<tr class="field-odd field"><th class="field-name">Type:</th><td class="field-body"><p class="first last">LayerOutput</p>
 </td>
 </tr>
 </tbody>