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develop/doc/api/v2/config/layer.html
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...@@ -208,7 +208,7 @@ ...@@ -208,7 +208,7 @@
<p>The example usage is:</p> <p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">fc</span> <span class="o">=</span> <span class="n">fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">layer</span><span class="p">,</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">fc</span> <span class="o">=</span> <span class="n">fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">layer</span><span class="p">,</span>
<span class="n">size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span>
<span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Linear</span><span class="p">(),</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Linear</span><span class="p">(),</span>
<span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span> <span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
</pre></div> </pre></div>
</div> </div>
...@@ -225,7 +225,7 @@ ...@@ -225,7 +225,7 @@
<li><strong>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer|list|tuple</em>) &#8211; The input layer. Could be a list/tuple of input layer.</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer|list|tuple</em>) &#8211; The input layer. Could be a list/tuple of input layer.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; The layer dimension.</li> <li><strong>size</strong> (<em>int</em>) &#8211; The layer dimension.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type. Default is tanh.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type. Default is tanh.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute|list.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute|list.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -255,7 +255,7 @@ of this layer maybe sparse. It requires an additional input to indicate ...@@ -255,7 +255,7 @@ of this layer maybe sparse. It requires an additional input to indicate
several selected columns for output. If the selected columns is not several selected columns for output. If the selected columns is not
specified, selective_fc acts exactly like fc.</p> specified, selective_fc acts exactly like fc.</p>
<p>The simple usage is:</p> <p>The simple usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">sel_fc</span> <span class="o">=</span> <span class="n">selective_fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="nb">input</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Tanh</span><span class="p">())</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">sel_fc</span> <span class="o">=</span> <span class="n">selective_fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="nb">input</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Tanh</span><span class="p">())</span>
</pre></div> </pre></div>
</div> </div>
<table class="docutils field-list" frame="void" rules="none"> <table class="docutils field-list" frame="void" rules="none">
...@@ -269,7 +269,7 @@ specified, selective_fc acts exactly like fc.</p> ...@@ -269,7 +269,7 @@ specified, selective_fc acts exactly like fc.</p>
sparse binary matrix, and treat as the mask of selective fc. sparse binary matrix, and treat as the mask of selective fc.
If is None, acts exactly like fc.</li> If is None, acts exactly like fc.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; The layer dimension.</li> <li><strong>size</strong> (<em>int</em>) &#8211; The layer dimension.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type. Default is tanh.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type. Default is tanh.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -469,7 +469,7 @@ rest channels will be processed by rest group of filters.</p> ...@@ -469,7 +469,7 @@ rest channels will be processed by rest group of filters.</p>
<span class="n">num_channels</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">num_channels</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span>
<span class="n">num_filters</span><span class="o">=</span><span class="mi">16</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_filters</span><span class="o">=</span><span class="mi">16</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span> <span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span>
<span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">())</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">())</span>
</pre></div> </pre></div>
</div> </div>
<table class="docutils field-list" frame="void" rules="none"> <table class="docutils field-list" frame="void" rules="none">
...@@ -485,7 +485,7 @@ two image dimension.</li> ...@@ -485,7 +485,7 @@ two image dimension.</li>
currently supports rectangular filters, the filter&#8217;s currently supports rectangular filters, the filter&#8217;s
shape will be (filter_size, filter_size_y).</li> shape will be (filter_size, filter_size_y).</li>
<li><strong>num_filters</strong> &#8211; Each filter group&#8217;s number of filter</li> <li><strong>num_filters</strong> &#8211; Each filter group&#8217;s number of filter</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type. Default is tanh</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type. Default is tanh</li>
<li><strong>groups</strong> (<em>int</em>) &#8211; Group size of filters.</li> <li><strong>groups</strong> (<em>int</em>) &#8211; Group size of filters.</li>
<li><strong>stride</strong> (<em>int|tuple|list</em>) &#8211; The x dimension of the stride. Or input a tuple for two image <li><strong>stride</strong> (<em>int|tuple|list</em>) &#8211; The x dimension of the stride. Or input a tuple for two image
dimension.</li> dimension.</li>
...@@ -780,7 +780,7 @@ y_i &amp;\gets \gamma \hat{x_i} + \beta \qquad &amp;//\ scale\ and\ shift\end{sp ...@@ -780,7 +780,7 @@ y_i &amp;\gets \gamma \hat{x_i} + \beta \qquad &amp;//\ scale\ and\ shift\end{sp
<p>The details of batch normalization please refer to this <p>The details of batch normalization please refer to this
<a class="reference external" href="http://arxiv.org/abs/1502.03167">paper</a>.</p> <a class="reference external" href="http://arxiv.org/abs/1502.03167">paper</a>.</p>
<p>The example usage is:</p> <p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">norm</span> <span class="o">=</span> <span class="n">batch_norm</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">net</span><span class="p">,</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">())</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">norm</span> <span class="o">=</span> <span class="n">batch_norm</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">net</span><span class="p">,</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">())</span>
</pre></div> </pre></div>
</div> </div>
<table class="docutils field-list" frame="void" rules="none"> <table class="docutils field-list" frame="void" rules="none">
...@@ -800,7 +800,7 @@ automaticly select cudnn_batch_norm for GPU and ...@@ -800,7 +800,7 @@ automaticly select cudnn_batch_norm for GPU and
batch_norm for CPU. Otherwise, select batch norm batch_norm for CPU. Otherwise, select batch norm
type based on the specified type. If you use cudnn_batch_norm, type based on the specified type. If you use cudnn_batch_norm,
we suggested you use latest version, such as v5.1.</li> we suggested you use latest version, such as v5.1.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type. Better be relu. Because batch <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type. Better be relu. Because batch
normalization will normalize input near zero.</li> normalization will normalize input near zero.</li>
<li><strong>num_channels</strong> (<em>int</em>) &#8211; num of image channels or previous layer&#8217;s number of <li><strong>num_channels</strong> (<em>int</em>) &#8211; num of image channels or previous layer&#8217;s number of
filters. None will automatically get from layer&#8217;s filters. None will automatically get from layer&#8217;s
...@@ -923,7 +923,7 @@ out_{i} = act(in_{i} + out_{i+1} * W) \ \ \text{for} \ start &lt;= i &lt; end\en ...@@ -923,7 +923,7 @@ out_{i} = act(in_{i} + out_{i+1} * W) \ \ \text{for} \ start &lt;= i &lt; end\en
<tbody valign="top"> <tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input Layer</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input Layer</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; activation.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; activation.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; bias attribute.</li> <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; bias attribute.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; parameter attribute.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; parameter attribute.</li>
<li><strong>name</strong> (<em>basestring</em>) &#8211; name of the layer</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; name of the layer</li>
...@@ -970,9 +970,9 @@ more details about LSTM.</p> ...@@ -970,9 +970,9 @@ more details about LSTM.</p>
<li><strong>name</strong> (<em>basestring</em>) &#8211; The lstmemory layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; The lstmemory layer name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer name.</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer name.</li>
<li><strong>reverse</strong> (<em>bool</em>) &#8211; is sequence process reversed or not.</li> <li><strong>reverse</strong> (<em>bool</em>) &#8211; is sequence process reversed or not.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; activation type, paddle.v2.Activation.Tanh by default. <span class="math">\(h_t\)</span></li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; activation type, paddle.v2.activation.Tanh by default. <span class="math">\(h_t\)</span></li>
<li><strong>gate_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; gate activation type, paddle.v2.Activation.Sigmoid by default.</li> <li><strong>gate_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; gate activation type, paddle.v2.activation.Sigmoid by default.</li>
<li><strong>state_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; state activation type, paddle.v2.Activation.Tanh by default.</li> <li><strong>state_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; state activation type, paddle.v2.activation.Tanh by default.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Bias attribute. None means default bias. False means no <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Bias attribute. None means default bias. False means no
bias.</li> bias.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Parameter Attribute.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Parameter Attribute.</li>
...@@ -1035,9 +1035,9 @@ Recurrent Neural Networks on Sequence Modeling.</a></p> ...@@ -1035,9 +1035,9 @@ Recurrent Neural Networks on Sequence Modeling.</a></p>
<li><strong>name</strong> (<em>None|basestring</em>) &#8211; The gru layer name.</li> <li><strong>name</strong> (<em>None|basestring</em>) &#8211; The gru layer name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer.</em>) &#8211; input layer.</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer.</em>) &#8211; input layer.</li>
<li><strong>reverse</strong> (<em>bool</em>) &#8211; Whether sequence process is reversed or not.</li> <li><strong>reverse</strong> (<em>bool</em>) &#8211; Whether sequence process is reversed or not.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; activation type, paddle.v2.Activation.Tanh by default. This activation <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; activation type, paddle.v2.activation.Tanh by default. This activation
affects the <span class="math">\({\tilde{h_t}}\)</span>.</li> affects the <span class="math">\({\tilde{h_t}}\)</span>.</li>
<li><strong>gate_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; gate activation type, paddle.v2.Activation.Sigmoid by default. <li><strong>gate_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; gate activation type, paddle.v2.activation.Sigmoid by default.
This activation affects the <span class="math">\(z_t\)</span> and <span class="math">\(r_t\)</span>. It is the This activation affects the <span class="math">\(z_t\)</span> and <span class="math">\(r_t\)</span>. It is the
<span class="math">\(\sigma\)</span> in the above formula.</li> <span class="math">\(\sigma\)</span> in the above formula.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Bias attribute. None means default bias. False means no <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Bias attribute. None means default bias. False means no
...@@ -1100,7 +1100,7 @@ It is ignored when name is provided.</li> ...@@ -1100,7 +1100,7 @@ It is ignored when name is provided.</li>
<li><strong>is_seq</strong> (<em>bool</em>) &#8211; is sequence for boot</li> <li><strong>is_seq</strong> (<em>bool</em>) &#8211; is sequence for boot</li>
<li><strong>boot</strong> (<em>paddle.v2.config_base.Layer|None</em>) &#8211; boot layer of memory.</li> <li><strong>boot</strong> (<em>paddle.v2.config_base.Layer|None</em>) &#8211; boot layer of memory.</li>
<li><strong>boot_bias</strong> (<em>paddle.v2.attr.ParameterAttribute|None</em>) &#8211; boot layer&#8217;s bias</li> <li><strong>boot_bias</strong> (<em>paddle.v2.attr.ParameterAttribute|None</em>) &#8211; boot layer&#8217;s bias</li>
<li><strong>boot_bias_active_type</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; boot layer&#8217;s active type.</li> <li><strong>boot_bias_active_type</strong> (<em>paddle.v2.activation.Base</em>) &#8211; boot layer&#8217;s active type.</li>
<li><strong>boot_with_const_id</strong> (<em>int</em>) &#8211; boot layer&#8217;s id.</li> <li><strong>boot_with_const_id</strong> (<em>int</em>) &#8211; boot layer&#8217;s id.</li>
</ul> </ul>
</td> </td>
...@@ -1130,7 +1130,7 @@ Neural Turning Machine like models.</p> ...@@ -1130,7 +1130,7 @@ Neural Turning Machine like models.</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">step</span><span class="p">(</span><span class="nb">input</span><span class="p">):</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">step</span><span class="p">(</span><span class="nb">input</span><span class="p">):</span>
<span class="n">output</span> <span class="o">=</span> <span class="n">fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">layer</span><span class="p">,</span> <span class="n">output</span> <span class="o">=</span> <span class="n">fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">layer</span><span class="p">,</span>
<span class="n">size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span>
<span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Linear</span><span class="p">(),</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Linear</span><span class="p">(),</span>
<span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span> <span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="k">return</span> <span class="n">output</span> <span class="k">return</span> <span class="n">output</span>
...@@ -1223,10 +1223,10 @@ output is <span class="math">\(o_t\)</span>, which name is &#8216;state&#8217; a ...@@ -1223,10 +1223,10 @@ output is <span class="math">\(o_t\)</span>, which name is &#8216;state&#8217; a
<code class="code docutils literal"><span class="pre">state.size</span></code>.</li> <code class="code docutils literal"><span class="pre">state.size</span></code>.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer. <span class="math">\(Wx_t + Wh_{t-1}\)</span></li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer. <span class="math">\(Wx_t + Wh_{t-1}\)</span></li>
<li><strong>state</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; State Layer. <span class="math">\(c_{t-1}\)</span></li> <li><strong>state</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; State Layer. <span class="math">\(c_{t-1}\)</span></li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type. Default is tanh</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type. Default is tanh</li>
<li><strong>gate_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Gate Activation Type. Default is sigmoid, and should <li><strong>gate_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Gate Activation Type. Default is sigmoid, and should
be sigmoid only.</li> be sigmoid only.</li>
<li><strong>state_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; State Activation Type. Default is sigmoid, and should <li><strong>state_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; State Activation Type. Default is sigmoid, and should
be sigmoid only.</li> be sigmoid only.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; Bias Attribute.</li> <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; Bias Attribute.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; layer&#8217;s extra attribute.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; layer&#8217;s extra attribute.</li>
...@@ -1428,7 +1428,7 @@ Each inputs is a projection or operator.</p> ...@@ -1428,7 +1428,7 @@ Each inputs is a projection or operator.</p>
<li><strong>size</strong> (<em>int</em>) &#8211; layer size.</li> <li><strong>size</strong> (<em>int</em>) &#8211; layer size.</li>
<li><strong>input</strong> &#8211; inputs layer. It is an optional parameter. If set, <li><strong>input</strong> &#8211; inputs layer. It is an optional parameter. If set,
then this function will just return layer&#8217;s name.</li> then this function will just return layer&#8217;s name.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
default Bias.</li> default Bias.</li>
...@@ -1925,7 +1925,7 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.</p> ...@@ -1925,7 +1925,7 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.</p>
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> <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; Layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li>
<li><strong>input</strong> (<em>list|tuple|collections.Sequence</em>) &#8211; input layers or projections</li> <li><strong>input</strong> (<em>list|tuple|collections.Sequence</em>) &#8211; input layers or projections</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li>
</ul> </ul>
</td> </td>
...@@ -1969,7 +1969,7 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.</p> ...@@ -1969,7 +1969,7 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.</p>
<li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li>
<li><strong>a</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input sequence layer</li> <li><strong>a</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input sequence layer</li>
<li><strong>b</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input sequence layer</li> <li><strong>b</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input sequence layer</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -2202,7 +2202,7 @@ output sequence has T*M/N instances, the dimension of each instance is N.</p> ...@@ -2202,7 +2202,7 @@ output sequence has T*M/N instances, the dimension of each instance is N.</p>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input layer.</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input layer.</li>
<li><strong>reshape_size</strong> (<em>int</em>) &#8211; the size of reshaped sequence.</li> <li><strong>reshape_size</strong> (<em>int</em>) &#8211; the size of reshaped sequence.</li>
<li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; extra layer attributes.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; extra layer attributes.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -2236,7 +2236,7 @@ default Bias.</li> ...@@ -2236,7 +2236,7 @@ default Bias.</li>
and <span class="math">\(f\)</span> is activation function.</p> and <span class="math">\(f\)</span> is activation function.</p>
<p>The example usage is:</p> <p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">addto</span> <span class="o">=</span> <span class="n">addto</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">layer2</span><span class="p">],</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">addto</span> <span class="o">=</span> <span class="n">addto</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">layer2</span><span class="p">],</span>
<span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">(),</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">(),</span>
<span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span> <span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
</pre></div> </pre></div>
</div> </div>
...@@ -2258,7 +2258,7 @@ Please refer to dropout for details.</p> ...@@ -2258,7 +2258,7 @@ Please refer to dropout for details.</p>
<li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer|list|tuple</em>) &#8211; Input layers. It could be a paddle.v2.config_base.Layer or list/tuple of <li><strong>input</strong> (<em>paddle.v2.config_base.Layer|list|tuple</em>) &#8211; Input layers. It could be a paddle.v2.config_base.Layer or list/tuple of
paddle.v2.config_base.Layer.</li> paddle.v2.config_base.Layer.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type, default is tanh.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type, default is tanh.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|bool</em>) &#8211; Bias attribute. If False, means no bias. None is default <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|bool</em>) &#8211; Bias attribute. If False, means no bias. None is default
bias.</li> bias.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer attribute.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer attribute.</li>
...@@ -2560,7 +2560,7 @@ For example, each sample:</p> ...@@ -2560,7 +2560,7 @@ For example, each sample:</p>
<li><strong>a</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input layer a.</li> <li><strong>a</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input layer a.</li>
<li><strong>b</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer b.</li> <li><strong>b</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer b.</li>
<li><strong>size</strong> (<em>int.</em>) &#8211; the layer dimension.</li> <li><strong>size</strong> (<em>int.</em>) &#8211; the layer dimension.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type. Default is tanh.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type. Default is tanh.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -3342,7 +3342,7 @@ A fast and simple algorithm for training neural probabilistic language models.</ ...@@ -3342,7 +3342,7 @@ A fast and simple algorithm for training neural probabilistic language models.</
<li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; label layer</li> <li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; label layer</li>
<li><strong>weight</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; weight layer, can be None(default)</li> <li><strong>weight</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; weight layer, can be None(default)</li>
<li><strong>num_classes</strong> (<em>int</em>) &#8211; number of classes.</li> <li><strong>num_classes</strong> (<em>int</em>) &#8211; number of classes.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation, default is Sigmoid.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation, default is Sigmoid.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute|list.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute|list.</li>
<li><strong>num_neg_samples</strong> (<em>int</em>) &#8211; number of negative samples. Default is 10.</li> <li><strong>num_neg_samples</strong> (<em>int</em>) &#8211; number of negative samples. Default is 10.</li>
<li><strong>neg_distribution</strong> (<em>list|tuple|collections.Sequence|None</em>) &#8211; The distribution for generating the random negative labels. <li><strong>neg_distribution</strong> (<em>list|tuple|collections.Sequence|None</em>) &#8211; The distribution for generating the random negative labels.
......
develop/doc_cn/api/v2/config/layer.html
浏览文件 @ 35e6dbc4
...@@ -215,7 +215,7 @@ ...@@ -215,7 +215,7 @@
<p>The example usage is:</p> <p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">fc</span> <span class="o">=</span> <span class="n">fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">layer</span><span class="p">,</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">fc</span> <span class="o">=</span> <span class="n">fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">layer</span><span class="p">,</span>
<span class="n">size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span>
<span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Linear</span><span class="p">(),</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Linear</span><span class="p">(),</span>
<span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span> <span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
</pre></div> </pre></div>
</div> </div>
...@@ -232,7 +232,7 @@ ...@@ -232,7 +232,7 @@
<li><strong>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer|list|tuple</em>) &#8211; The input layer. Could be a list/tuple of input layer.</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer|list|tuple</em>) &#8211; The input layer. Could be a list/tuple of input layer.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; The layer dimension.</li> <li><strong>size</strong> (<em>int</em>) &#8211; The layer dimension.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type. Default is tanh.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type. Default is tanh.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute|list.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute|list.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -262,7 +262,7 @@ of this layer maybe sparse. It requires an additional input to indicate ...@@ -262,7 +262,7 @@ of this layer maybe sparse. It requires an additional input to indicate
several selected columns for output. If the selected columns is not several selected columns for output. If the selected columns is not
specified, selective_fc acts exactly like fc.</p> specified, selective_fc acts exactly like fc.</p>
<p>The simple usage is:</p> <p>The simple usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">sel_fc</span> <span class="o">=</span> <span class="n">selective_fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="nb">input</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Tanh</span><span class="p">())</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">sel_fc</span> <span class="o">=</span> <span class="n">selective_fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="nb">input</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Tanh</span><span class="p">())</span>
</pre></div> </pre></div>
</div> </div>
<table class="docutils field-list" frame="void" rules="none"> <table class="docutils field-list" frame="void" rules="none">
...@@ -276,7 +276,7 @@ specified, selective_fc acts exactly like fc.</p> ...@@ -276,7 +276,7 @@ specified, selective_fc acts exactly like fc.</p>
sparse binary matrix, and treat as the mask of selective fc. sparse binary matrix, and treat as the mask of selective fc.
If is None, acts exactly like fc.</li> If is None, acts exactly like fc.</li>
<li><strong>size</strong> (<em>int</em>) &#8211; The layer dimension.</li> <li><strong>size</strong> (<em>int</em>) &#8211; The layer dimension.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type. Default is tanh.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type. Default is tanh.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -476,7 +476,7 @@ rest channels will be processed by rest group of filters.</p> ...@@ -476,7 +476,7 @@ rest channels will be processed by rest group of filters.</p>
<span class="n">num_channels</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">num_channels</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span>
<span class="n">num_filters</span><span class="o">=</span><span class="mi">16</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_filters</span><span class="o">=</span><span class="mi">16</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span> <span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span>
<span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">())</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">())</span>
</pre></div> </pre></div>
</div> </div>
<table class="docutils field-list" frame="void" rules="none"> <table class="docutils field-list" frame="void" rules="none">
...@@ -492,7 +492,7 @@ two image dimension.</li> ...@@ -492,7 +492,7 @@ two image dimension.</li>
currently supports rectangular filters, the filter&#8217;s currently supports rectangular filters, the filter&#8217;s
shape will be (filter_size, filter_size_y).</li> shape will be (filter_size, filter_size_y).</li>
<li><strong>num_filters</strong> &#8211; Each filter group&#8217;s number of filter</li> <li><strong>num_filters</strong> &#8211; Each filter group&#8217;s number of filter</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type. Default is tanh</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type. Default is tanh</li>
<li><strong>groups</strong> (<em>int</em>) &#8211; Group size of filters.</li> <li><strong>groups</strong> (<em>int</em>) &#8211; Group size of filters.</li>
<li><strong>stride</strong> (<em>int|tuple|list</em>) &#8211; The x dimension of the stride. Or input a tuple for two image <li><strong>stride</strong> (<em>int|tuple|list</em>) &#8211; The x dimension of the stride. Or input a tuple for two image
dimension.</li> dimension.</li>
...@@ -787,7 +787,7 @@ y_i &amp;\gets \gamma \hat{x_i} + \beta \qquad &amp;//\ scale\ and\ shift\end{sp ...@@ -787,7 +787,7 @@ y_i &amp;\gets \gamma \hat{x_i} + \beta \qquad &amp;//\ scale\ and\ shift\end{sp
<p>The details of batch normalization please refer to this <p>The details of batch normalization please refer to this
<a class="reference external" href="http://arxiv.org/abs/1502.03167">paper</a>.</p> <a class="reference external" href="http://arxiv.org/abs/1502.03167">paper</a>.</p>
<p>The example usage is:</p> <p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">norm</span> <span class="o">=</span> <span class="n">batch_norm</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">net</span><span class="p">,</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">())</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">norm</span> <span class="o">=</span> <span class="n">batch_norm</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">net</span><span class="p">,</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">())</span>
</pre></div> </pre></div>
</div> </div>
<table class="docutils field-list" frame="void" rules="none"> <table class="docutils field-list" frame="void" rules="none">
...@@ -807,7 +807,7 @@ automaticly select cudnn_batch_norm for GPU and ...@@ -807,7 +807,7 @@ automaticly select cudnn_batch_norm for GPU and
batch_norm for CPU. Otherwise, select batch norm batch_norm for CPU. Otherwise, select batch norm
type based on the specified type. If you use cudnn_batch_norm, type based on the specified type. If you use cudnn_batch_norm,
we suggested you use latest version, such as v5.1.</li> we suggested you use latest version, such as v5.1.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type. Better be relu. Because batch <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type. Better be relu. Because batch
normalization will normalize input near zero.</li> normalization will normalize input near zero.</li>
<li><strong>num_channels</strong> (<em>int</em>) &#8211; num of image channels or previous layer&#8217;s number of <li><strong>num_channels</strong> (<em>int</em>) &#8211; num of image channels or previous layer&#8217;s number of
filters. None will automatically get from layer&#8217;s filters. None will automatically get from layer&#8217;s
...@@ -930,7 +930,7 @@ out_{i} = act(in_{i} + out_{i+1} * W) \ \ \text{for} \ start &lt;= i &lt; end\en ...@@ -930,7 +930,7 @@ out_{i} = act(in_{i} + out_{i+1} * W) \ \ \text{for} \ start &lt;= i &lt; end\en
<tbody valign="top"> <tbody valign="top">
<tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first simple"> <tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first simple">
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input Layer</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input Layer</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; activation.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; activation.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; bias attribute.</li> <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; bias attribute.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; parameter attribute.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; parameter attribute.</li>
<li><strong>name</strong> (<em>basestring</em>) &#8211; name of the layer</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; name of the layer</li>
...@@ -977,9 +977,9 @@ more details about LSTM.</p> ...@@ -977,9 +977,9 @@ more details about LSTM.</p>
<li><strong>name</strong> (<em>basestring</em>) &#8211; The lstmemory layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; The lstmemory layer name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer name.</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer name.</li>
<li><strong>reverse</strong> (<em>bool</em>) &#8211; is sequence process reversed or not.</li> <li><strong>reverse</strong> (<em>bool</em>) &#8211; is sequence process reversed or not.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; activation type, paddle.v2.Activation.Tanh by default. <span class="math">\(h_t\)</span></li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; activation type, paddle.v2.activation.Tanh by default. <span class="math">\(h_t\)</span></li>
<li><strong>gate_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; gate activation type, paddle.v2.Activation.Sigmoid by default.</li> <li><strong>gate_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; gate activation type, paddle.v2.activation.Sigmoid by default.</li>
<li><strong>state_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; state activation type, paddle.v2.Activation.Tanh by default.</li> <li><strong>state_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; state activation type, paddle.v2.activation.Tanh by default.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Bias attribute. None means default bias. False means no <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Bias attribute. None means default bias. False means no
bias.</li> bias.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Parameter Attribute.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Parameter Attribute.</li>
...@@ -1042,9 +1042,9 @@ Recurrent Neural Networks on Sequence Modeling.</a></p> ...@@ -1042,9 +1042,9 @@ Recurrent Neural Networks on Sequence Modeling.</a></p>
<li><strong>name</strong> (<em>None|basestring</em>) &#8211; The gru layer name.</li> <li><strong>name</strong> (<em>None|basestring</em>) &#8211; The gru layer name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer.</em>) &#8211; input layer.</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer.</em>) &#8211; input layer.</li>
<li><strong>reverse</strong> (<em>bool</em>) &#8211; Whether sequence process is reversed or not.</li> <li><strong>reverse</strong> (<em>bool</em>) &#8211; Whether sequence process is reversed or not.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; activation type, paddle.v2.Activation.Tanh by default. This activation <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; activation type, paddle.v2.activation.Tanh by default. This activation
affects the <span class="math">\({\tilde{h_t}}\)</span>.</li> affects the <span class="math">\({\tilde{h_t}}\)</span>.</li>
<li><strong>gate_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; gate activation type, paddle.v2.Activation.Sigmoid by default. <li><strong>gate_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; gate activation type, paddle.v2.activation.Sigmoid by default.
This activation affects the <span class="math">\(z_t\)</span> and <span class="math">\(r_t\)</span>. It is the This activation affects the <span class="math">\(z_t\)</span> and <span class="math">\(r_t\)</span>. It is the
<span class="math">\(\sigma\)</span> in the above formula.</li> <span class="math">\(\sigma\)</span> in the above formula.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Bias attribute. None means default bias. False means no <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|False</em>) &#8211; Bias attribute. None means default bias. False means no
...@@ -1107,7 +1107,7 @@ It is ignored when name is provided.</li> ...@@ -1107,7 +1107,7 @@ It is ignored when name is provided.</li>
<li><strong>is_seq</strong> (<em>bool</em>) &#8211; is sequence for boot</li> <li><strong>is_seq</strong> (<em>bool</em>) &#8211; is sequence for boot</li>
<li><strong>boot</strong> (<em>paddle.v2.config_base.Layer|None</em>) &#8211; boot layer of memory.</li> <li><strong>boot</strong> (<em>paddle.v2.config_base.Layer|None</em>) &#8211; boot layer of memory.</li>
<li><strong>boot_bias</strong> (<em>paddle.v2.attr.ParameterAttribute|None</em>) &#8211; boot layer&#8217;s bias</li> <li><strong>boot_bias</strong> (<em>paddle.v2.attr.ParameterAttribute|None</em>) &#8211; boot layer&#8217;s bias</li>
<li><strong>boot_bias_active_type</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; boot layer&#8217;s active type.</li> <li><strong>boot_bias_active_type</strong> (<em>paddle.v2.activation.Base</em>) &#8211; boot layer&#8217;s active type.</li>
<li><strong>boot_with_const_id</strong> (<em>int</em>) &#8211; boot layer&#8217;s id.</li> <li><strong>boot_with_const_id</strong> (<em>int</em>) &#8211; boot layer&#8217;s id.</li>
</ul> </ul>
</td> </td>
...@@ -1137,7 +1137,7 @@ Neural Turning Machine like models.</p> ...@@ -1137,7 +1137,7 @@ Neural Turning Machine like models.</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">step</span><span class="p">(</span><span class="nb">input</span><span class="p">):</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">step</span><span class="p">(</span><span class="nb">input</span><span class="p">):</span>
<span class="n">output</span> <span class="o">=</span> <span class="n">fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">layer</span><span class="p">,</span> <span class="n">output</span> <span class="o">=</span> <span class="n">fc</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">layer</span><span class="p">,</span>
<span class="n">size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span>
<span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Linear</span><span class="p">(),</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Linear</span><span class="p">(),</span>
<span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span> <span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="k">return</span> <span class="n">output</span> <span class="k">return</span> <span class="n">output</span>
...@@ -1230,10 +1230,10 @@ output is <span class="math">\(o_t\)</span>, which name is &#8216;state&#8217; a ...@@ -1230,10 +1230,10 @@ output is <span class="math">\(o_t\)</span>, which name is &#8216;state&#8217; a
<code class="code docutils literal"><span class="pre">state.size</span></code>.</li> <code class="code docutils literal"><span class="pre">state.size</span></code>.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer. <span class="math">\(Wx_t + Wh_{t-1}\)</span></li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer. <span class="math">\(Wx_t + Wh_{t-1}\)</span></li>
<li><strong>state</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; State Layer. <span class="math">\(c_{t-1}\)</span></li> <li><strong>state</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; State Layer. <span class="math">\(c_{t-1}\)</span></li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type. Default is tanh</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type. Default is tanh</li>
<li><strong>gate_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Gate Activation Type. Default is sigmoid, and should <li><strong>gate_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Gate Activation Type. Default is sigmoid, and should
be sigmoid only.</li> be sigmoid only.</li>
<li><strong>state_act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; State Activation Type. Default is sigmoid, and should <li><strong>state_act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; State Activation Type. Default is sigmoid, and should
be sigmoid only.</li> be sigmoid only.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; Bias Attribute.</li> <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; Bias Attribute.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; layer&#8217;s extra attribute.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; layer&#8217;s extra attribute.</li>
...@@ -1435,7 +1435,7 @@ Each inputs is a projection or operator.</p> ...@@ -1435,7 +1435,7 @@ Each inputs is a projection or operator.</p>
<li><strong>size</strong> (<em>int</em>) &#8211; layer size.</li> <li><strong>size</strong> (<em>int</em>) &#8211; layer size.</li>
<li><strong>input</strong> &#8211; inputs layer. It is an optional parameter. If set, <li><strong>input</strong> &#8211; inputs layer. It is an optional parameter. If set,
then this function will just return layer&#8217;s name.</li> then this function will just return layer&#8217;s name.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
default Bias.</li> default Bias.</li>
...@@ -1932,7 +1932,7 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.</p> ...@@ -1932,7 +1932,7 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.</p>
<tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first simple"> <tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li>
<li><strong>input</strong> (<em>list|tuple|collections.Sequence</em>) &#8211; input layers or projections</li> <li><strong>input</strong> (<em>list|tuple|collections.Sequence</em>) &#8211; input layers or projections</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li>
</ul> </ul>
</td> </td>
...@@ -1976,7 +1976,7 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.</p> ...@@ -1976,7 +1976,7 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.</p>
<li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li>
<li><strong>a</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input sequence layer</li> <li><strong>a</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input sequence layer</li>
<li><strong>b</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input sequence layer</li> <li><strong>b</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input sequence layer</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -2209,7 +2209,7 @@ output sequence has T*M/N instances, the dimension of each instance is N.</p> ...@@ -2209,7 +2209,7 @@ output sequence has T*M/N instances, the dimension of each instance is N.</p>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input layer.</li> <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input layer.</li>
<li><strong>reshape_size</strong> (<em>int</em>) &#8211; the size of reshaped sequence.</li> <li><strong>reshape_size</strong> (<em>int</em>) &#8211; the size of reshaped sequence.</li>
<li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation type.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; extra layer attributes.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; extra layer attributes.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em><em> or </em><em>None</em><em> or </em><em>bool</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -2243,7 +2243,7 @@ default Bias.</li> ...@@ -2243,7 +2243,7 @@ default Bias.</li>
and <span class="math">\(f\)</span> is activation function.</p> and <span class="math">\(f\)</span> is activation function.</p>
<p>The example usage is:</p> <p>The example usage is:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">addto</span> <span class="o">=</span> <span class="n">addto</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">layer2</span><span class="p">],</span> <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">addto</span> <span class="o">=</span> <span class="n">addto</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">layer2</span><span class="p">],</span>
<span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">Activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">(),</span> <span class="n">act</span><span class="o">=</span><span class="n">paddle</span><span class="o">.</span><span class="n">v2</span><span class="o">.</span><span class="n">activation</span><span class="o">.</span><span class="n">Relu</span><span class="p">(),</span>
<span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span> <span class="n">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
</pre></div> </pre></div>
</div> </div>
...@@ -2265,7 +2265,7 @@ Please refer to dropout for details.</p> ...@@ -2265,7 +2265,7 @@ Please refer to dropout for details.</p>
<li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li> <li><strong>name</strong> (<em>basestring</em>) &#8211; Layer name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer|list|tuple</em>) &#8211; Input layers. It could be a paddle.v2.config_base.Layer or list/tuple of <li><strong>input</strong> (<em>paddle.v2.config_base.Layer|list|tuple</em>) &#8211; Input layers. It could be a paddle.v2.config_base.Layer or list/tuple of
paddle.v2.config_base.Layer.</li> paddle.v2.config_base.Layer.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type, default is tanh.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type, default is tanh.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|bool</em>) &#8211; Bias attribute. If False, means no bias. None is default <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|bool</em>) &#8211; Bias attribute. If False, means no bias. None is default
bias.</li> bias.</li>
<li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer attribute.</li> <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer attribute.</li>
...@@ -2567,7 +2567,7 @@ For example, each sample:</p> ...@@ -2567,7 +2567,7 @@ For example, each sample:</p>
<li><strong>a</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input layer a.</li> <li><strong>a</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input layer a.</li>
<li><strong>b</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer b.</li> <li><strong>b</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; input layer b.</li>
<li><strong>size</strong> (<em>int.</em>) &#8211; the layer dimension.</li> <li><strong>size</strong> (<em>int.</em>) &#8211; the layer dimension.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation Type. Default is tanh.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation Type. Default is tanh.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or <li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|None|Any</em>) &#8211; The Bias Attribute. If no bias, then pass False or
something not type of paddle.v2.attr.ParameterAttribute. None will get a something not type of paddle.v2.attr.ParameterAttribute. None will get a
...@@ -3349,7 +3349,7 @@ A fast and simple algorithm for training neural probabilistic language models.</ ...@@ -3349,7 +3349,7 @@ A fast and simple algorithm for training neural probabilistic language models.</
<li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; label layer</li> <li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; label layer</li>
<li><strong>weight</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; weight layer, can be None(default)</li> <li><strong>weight</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; weight layer, can be None(default)</li>
<li><strong>num_classes</strong> (<em>int</em>) &#8211; number of classes.</li> <li><strong>num_classes</strong> (<em>int</em>) &#8211; number of classes.</li>
<li><strong>act</strong> (<em>paddle.v2.Activation.Base</em>) &#8211; Activation, default is Sigmoid.</li> <li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation, default is Sigmoid.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute|list.</li> <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The Parameter Attribute|list.</li>
<li><strong>num_neg_samples</strong> (<em>int</em>) &#8211; number of negative samples. Default is 10.</li> <li><strong>num_neg_samples</strong> (<em>int</em>) &#8211; number of negative samples. Default is 10.</li>
<li><strong>neg_distribution</strong> (<em>list|tuple|collections.Sequence|None</em>) &#8211; The distribution for generating the random negative labels. <li><strong>neg_distribution</strong> (<em>list|tuple|collections.Sequence|None</em>) &#8211; The distribution for generating the random negative labels.
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