提交 ebd3633e 编写于 作者: T Travis CI

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上级 0eda3b88
......@@ -1177,7 +1177,7 @@ in the input parameters to the function.</p>
<h2>conv2d<a class="headerlink" href="#conv2d" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">conv2d</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>filter_size</em>, <em>stride=None</em>, <em>padding=None</em>, <em>groups=None</em>, <em>param_attr=None</em>, <em>bias_attr=None</em>, <em>act=None</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">conv2d</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>filter_size</em>, <em>stride=None</em>, <em>padding=None</em>, <em>groups=None</em>, <em>param_attr=None</em>, <em>bias_attr=None</em>, <em>use_cudnn=True</em>, <em>act=None</em><span class="sig-paren">)</span></dt>
<dd><p><strong>Convlution2D Layer</strong></p>
<p>The convolution2D layer calculates the output based on the input, filter
and strides, paddings, dilations, groups parameters. Input(Input) and Output(Output)
......@@ -1237,6 +1237,8 @@ of the input channels, while the second half of the filters is only
connected to the second half of the input channels. Default: groups=1</li>
<li><strong>param_attr</strong> (<em>ParamAttr</em>) &#8211; The parameters to the Conv2d Layer. Default: None</li>
<li><strong>bias_attr</strong> (<em>ParamAttr</em>) &#8211; Bias parameter for the Conv2d layer. Default: None</li>
<li><strong>use_cudnn</strong> (<em>bool</em>) &#8211; Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True</li>
<li><strong>act</strong> (<em>str</em>) &#8211; Activation type. Default: None</li>
</ul>
</td>
......@@ -1396,7 +1398,7 @@ then output is a Tensor:
<h2>pool2d<a class="headerlink" href="#pool2d" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">pool2d</code><span class="sig-paren">(</span><em>input</em>, <em>pool_size</em>, <em>pool_type</em>, <em>pool_stride=None</em>, <em>pool_padding=None</em>, <em>global_pooling=False</em>, <em>name=None</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">pool2d</code><span class="sig-paren">(</span><em>input</em>, <em>pool_size</em>, <em>pool_type</em>, <em>pool_stride=None</em>, <em>pool_padding=None</em>, <em>global_pooling=False</em>, <em>use_cudnn=True</em>, <em>name=None</em><span class="sig-paren">)</span></dt>
<dd><p>This function adds the operator for pooling in 2 dimensions, using the
pooling configurations mentioned in input parameters.</p>
</dd></dl>
......@@ -1984,7 +1986,7 @@ to compute the length.</td>
<h2>conv2d_transpose<a class="headerlink" href="#conv2d-transpose" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">conv2d_transpose</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>output_size=None</em>, <em>filter_size=None</em>, <em>padding=None</em>, <em>stride=None</em>, <em>dilation=None</em>, <em>param_attr=None</em>, <em>name=None</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">conv2d_transpose</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>output_size=None</em>, <em>filter_size=None</em>, <em>padding=None</em>, <em>stride=None</em>, <em>dilation=None</em>, <em>param_attr=None</em>, <em>use_cudnn=True</em>, <em>name=None</em><span class="sig-paren">)</span></dt>
<dd><p>The transpose of conv2d layer.</p>
<p>This layer is also known as deconvolution layer.</p>
<table class="docutils field-list" frame="void" rules="none">
......@@ -2012,6 +2014,8 @@ stride_H = stride_W = stride.</li>
contain two integers, (dilation_H, dilation_W). Otherwise, the
dilation_H = dilation_W = dilation.</li>
<li><strong>param_attr</strong> &#8211; Parameter Attribute.</li>
<li><strong>use_cudnn</strong> (<em>bool</em>) &#8211; Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True</li>
<li><strong>name</strong> (<em>str|None</em>) &#8211; A name for this layer(optional). If set None, the layer
will be named automatically.</li>
</ul>
......
......@@ -222,7 +222,7 @@
<h2>simple_img_conv_pool<a class="headerlink" href="#simple-img-conv-pool" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.nets.</code><code class="descname">simple_img_conv_pool</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>filter_size</em>, <em>pool_size</em>, <em>pool_stride</em>, <em>act</em>, <em>param_attr=None</em>, <em>pool_type='max'</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.nets.</code><code class="descname">simple_img_conv_pool</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>filter_size</em>, <em>pool_size</em>, <em>pool_stride</em>, <em>act</em>, <em>param_attr=None</em>, <em>pool_type='max'</em>, <em>use_cudnn=True</em><span class="sig-paren">)</span></dt>
<dd></dd></dl>
</div>
......@@ -230,7 +230,7 @@
<h2>img_conv_group<a class="headerlink" href="#img-conv-group" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.nets.</code><code class="descname">img_conv_group</code><span class="sig-paren">(</span><em>input</em>, <em>conv_num_filter</em>, <em>pool_size</em>, <em>conv_padding=1</em>, <em>conv_filter_size=3</em>, <em>conv_act=None</em>, <em>param_attr=None</em>, <em>conv_with_batchnorm=False</em>, <em>conv_batchnorm_drop_rate=None</em>, <em>pool_stride=1</em>, <em>pool_type=None</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.nets.</code><code class="descname">img_conv_group</code><span class="sig-paren">(</span><em>input</em>, <em>conv_num_filter</em>, <em>pool_size</em>, <em>conv_padding=1</em>, <em>conv_filter_size=3</em>, <em>conv_act=None</em>, <em>param_attr=None</em>, <em>conv_with_batchnorm=False</em>, <em>conv_batchnorm_drop_rate=None</em>, <em>pool_stride=1</em>, <em>pool_type=None</em>, <em>use_cudnn=True</em><span class="sig-paren">)</span></dt>
<dd><p>Image Convolution Group, Used for vgg net.</p>
</dd></dl>
......
因为 它太大了无法显示 source diff 。你可以改为 查看blob
......@@ -1196,7 +1196,7 @@ in the input parameters to the function.</p>
<h2>conv2d<a class="headerlink" href="#conv2d" title="永久链接至标题"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">conv2d</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>filter_size</em>, <em>stride=None</em>, <em>padding=None</em>, <em>groups=None</em>, <em>param_attr=None</em>, <em>bias_attr=None</em>, <em>act=None</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">conv2d</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>filter_size</em>, <em>stride=None</em>, <em>padding=None</em>, <em>groups=None</em>, <em>param_attr=None</em>, <em>bias_attr=None</em>, <em>use_cudnn=True</em>, <em>act=None</em><span class="sig-paren">)</span></dt>
<dd><p><strong>Convlution2D Layer</strong></p>
<p>The convolution2D layer calculates the output based on the input, filter
and strides, paddings, dilations, groups parameters. Input(Input) and Output(Output)
......@@ -1256,6 +1256,8 @@ of the input channels, while the second half of the filters is only
connected to the second half of the input channels. Default: groups=1</li>
<li><strong>param_attr</strong> (<em>ParamAttr</em>) &#8211; The parameters to the Conv2d Layer. Default: None</li>
<li><strong>bias_attr</strong> (<em>ParamAttr</em>) &#8211; Bias parameter for the Conv2d layer. Default: None</li>
<li><strong>use_cudnn</strong> (<em>bool</em>) &#8211; Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True</li>
<li><strong>act</strong> (<em>str</em>) &#8211; Activation type. Default: None</li>
</ul>
</td>
......@@ -1415,7 +1417,7 @@ then output is a Tensor:
<h2>pool2d<a class="headerlink" href="#pool2d" title="永久链接至标题"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">pool2d</code><span class="sig-paren">(</span><em>input</em>, <em>pool_size</em>, <em>pool_type</em>, <em>pool_stride=None</em>, <em>pool_padding=None</em>, <em>global_pooling=False</em>, <em>name=None</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">pool2d</code><span class="sig-paren">(</span><em>input</em>, <em>pool_size</em>, <em>pool_type</em>, <em>pool_stride=None</em>, <em>pool_padding=None</em>, <em>global_pooling=False</em>, <em>use_cudnn=True</em>, <em>name=None</em><span class="sig-paren">)</span></dt>
<dd><p>This function adds the operator for pooling in 2 dimensions, using the
pooling configurations mentioned in input parameters.</p>
</dd></dl>
......@@ -2003,7 +2005,7 @@ to compute the length.</td>
<h2>conv2d_transpose<a class="headerlink" href="#conv2d-transpose" title="永久链接至标题"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">conv2d_transpose</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>output_size=None</em>, <em>filter_size=None</em>, <em>padding=None</em>, <em>stride=None</em>, <em>dilation=None</em>, <em>param_attr=None</em>, <em>name=None</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">conv2d_transpose</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>output_size=None</em>, <em>filter_size=None</em>, <em>padding=None</em>, <em>stride=None</em>, <em>dilation=None</em>, <em>param_attr=None</em>, <em>use_cudnn=True</em>, <em>name=None</em><span class="sig-paren">)</span></dt>
<dd><p>The transpose of conv2d layer.</p>
<p>This layer is also known as deconvolution layer.</p>
<table class="docutils field-list" frame="void" rules="none">
......@@ -2031,6 +2033,8 @@ stride_H = stride_W = stride.</li>
contain two integers, (dilation_H, dilation_W). Otherwise, the
dilation_H = dilation_W = dilation.</li>
<li><strong>param_attr</strong> &#8211; Parameter Attribute.</li>
<li><strong>use_cudnn</strong> (<em>bool</em>) &#8211; Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True</li>
<li><strong>name</strong> (<em>str|None</em>) &#8211; A name for this layer(optional). If set None, the layer
will be named automatically.</li>
</ul>
......
......@@ -241,7 +241,7 @@
<h2>simple_img_conv_pool<a class="headerlink" href="#simple-img-conv-pool" title="永久链接至标题"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.nets.</code><code class="descname">simple_img_conv_pool</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>filter_size</em>, <em>pool_size</em>, <em>pool_stride</em>, <em>act</em>, <em>param_attr=None</em>, <em>pool_type='max'</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.nets.</code><code class="descname">simple_img_conv_pool</code><span class="sig-paren">(</span><em>input</em>, <em>num_filters</em>, <em>filter_size</em>, <em>pool_size</em>, <em>pool_stride</em>, <em>act</em>, <em>param_attr=None</em>, <em>pool_type='max'</em>, <em>use_cudnn=True</em><span class="sig-paren">)</span></dt>
<dd></dd></dl>
</div>
......@@ -249,7 +249,7 @@
<h2>img_conv_group<a class="headerlink" href="#img-conv-group" title="永久链接至标题"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.nets.</code><code class="descname">img_conv_group</code><span class="sig-paren">(</span><em>input</em>, <em>conv_num_filter</em>, <em>pool_size</em>, <em>conv_padding=1</em>, <em>conv_filter_size=3</em>, <em>conv_act=None</em>, <em>param_attr=None</em>, <em>conv_with_batchnorm=False</em>, <em>conv_batchnorm_drop_rate=None</em>, <em>pool_stride=1</em>, <em>pool_type=None</em><span class="sig-paren">)</span></dt>
<code class="descclassname">paddle.v2.fluid.nets.</code><code class="descname">img_conv_group</code><span class="sig-paren">(</span><em>input</em>, <em>conv_num_filter</em>, <em>pool_size</em>, <em>conv_padding=1</em>, <em>conv_filter_size=3</em>, <em>conv_act=None</em>, <em>param_attr=None</em>, <em>conv_with_batchnorm=False</em>, <em>conv_batchnorm_drop_rate=None</em>, <em>pool_stride=1</em>, <em>pool_type=None</em>, <em>use_cudnn=True</em><span class="sig-paren">)</span></dt>
<dd><p>Image Convolution Group, Used for vgg net.</p>
</dd></dl>
......
因为 它太大了无法显示 source diff 。你可以改为 查看blob
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