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

@@ -3847,9 +3847,13 @@ should be consistent as that used in your labels.</li>
 <dl class="class">
 <dt>
 <em class="property">class </em><code class="descclassname">paddle.v2.layer.</code><code class="descname">nce</code></dt>
-<dd><p>Noise-contrastive estimation.
-Implements the method in the following paper:
-A fast and simple algorithm for training neural probabilistic language models.</p>
+<dd><p>Noise-contrastive estimation. This layer implements the method in the
+following paper:</p>
+<dl class="docutils">
+<dt>Reference:</dt>
+<dd>A fast and simple algorithm for training neural probabilistic language
+models. <a class="reference external" href="https://www.cs.toronto.edu/~amnih/papers/ncelm.pdf">https://www.cs.toronto.edu/~amnih/papers/ncelm.pdf</a></dd>
+</dl>
 <p>The example usage is:</p>
 <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">cost</span> <span class="o">=</span> <span class="n">nce</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">label</span><span class="o">=</span><span class="n">layer2</span><span class="p">,</span>
                  <span class="n">param_attr</span><span class="o">=</span><span class="p">[</span><span class="n">attr1</span><span class="p">,</span> <span class="n">attr2</span><span class="p">],</span> <span class="n">weight</span><span class="o">=</span><span class="n">layer3</span><span class="p">,</span>
@@ -3862,24 +3866,31 @@ A fast and simple algorithm for training neural probabilistic language models.</
 <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; The name of this layer. It is optional.</li>
-<li><strong>input</strong> (<em>paddle.v2.config_base.Layer | list | tuple | collections.Sequence</em>) &#8211; The input layers. It could be a paddle.v2.config_base.Layer of list/tuple of paddle.v2.config_base.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>num_classes</strong> (<em>int</em>) &#8211; number of classes.</li>
-<li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type. paddle.v2.activation.Sigmoid is the default.</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>neg_distribution</strong> (<em>list | tuple | collections.Sequence | None</em>) &#8211; The distribution for generating the random negative labels.
-A uniform distribution will be used if not provided.
-If not None, its length must be equal to num_classes.</li>
-<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute | None | bool | Any</em>) &#8211; The bias attribute. If the parameter is set to False or an object
-whose type is not paddle.v2.attr.ParameterAttribute, no bias is defined. If the
-parameter is set to True, the bias is initialized to zero.</li>
+<li><strong>input</strong> (<em>paddle.v2.config_base.Layer | list | tuple | collections.Sequence</em>) &#8211; The input layers. It should be a paddle.v2.config_base.Layer or a list/tuple
+of paddle.v2.config_base.Layer.</li>
+<li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The ground truth.</li>
+<li><strong>weight</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The weight layer defines a weight for each sample in the
+mini-batch. The default value is None.</li>
+<li><strong>num_classes</strong> (<em>int</em>) &#8211; The class number.</li>
+<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|list</em>) &#8211; The parameter attributes.</li>
+<li><strong>num_neg_samples</strong> (<em>int</em>) &#8211; The number of sampled negative labels. The default
+value is 10.</li>
+<li><strong>neg_distribution</strong> (<em>list | tuple | collections.Sequence | None</em>) &#8211; The discrete noisy distribution over the output
+space from which num_neg_samples negative labels
+are sampled. If this parameter is not set, a
+uniform distribution will be used. A user defined
+distribution is a list whose length must be equal
+to the num_classes. Each member of the list defines
+the probability of a class given input x.</li>
+<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute | None | bool | Any</em>) &#8211; The attribute for bias. If this parameter is set False or
+any object whose type is not paddle.v2.attr.ParameterAttribute, no bias
+is added. If this parameter is set True, the bias is
+initialized to zero.</li>
 <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li>
 </ul>
 </td>
 </tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">layer name.</p>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The paddle.v2.config_base.Layer object.</p>
 </td>
 </tr>
 <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">paddle.v2.config_base.Layer</p>

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

@@ -3861,9 +3861,13 @@ should be consistent as that used in your labels.</li>
 <dl class="class">
 <dt>
 <em class="property">class </em><code class="descclassname">paddle.v2.layer.</code><code class="descname">nce</code></dt>
-<dd><p>Noise-contrastive estimation.
-Implements the method in the following paper:
-A fast and simple algorithm for training neural probabilistic language models.</p>
+<dd><p>Noise-contrastive estimation. This layer implements the method in the
+following paper:</p>
+<dl class="docutils">
+<dt>Reference:</dt>
+<dd>A fast and simple algorithm for training neural probabilistic language
+models. <a class="reference external" href="https://www.cs.toronto.edu/~amnih/papers/ncelm.pdf">https://www.cs.toronto.edu/~amnih/papers/ncelm.pdf</a></dd>
+</dl>
 <p>The example usage is:</p>
 <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">cost</span> <span class="o">=</span> <span class="n">nce</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">label</span><span class="o">=</span><span class="n">layer2</span><span class="p">,</span>
                  <span class="n">param_attr</span><span class="o">=</span><span class="p">[</span><span class="n">attr1</span><span class="p">,</span> <span class="n">attr2</span><span class="p">],</span> <span class="n">weight</span><span class="o">=</span><span class="n">layer3</span><span class="p">,</span>
@@ -3876,24 +3880,31 @@ A fast and simple algorithm for training neural probabilistic language models.</
 <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>name</strong> (<em>basestring</em>) &#8211; The name of this layer. It is optional.</li>
-<li><strong>input</strong> (<em>paddle.v2.config_base.Layer | list | tuple | collections.Sequence</em>) &#8211; The input layers. It could be a paddle.v2.config_base.Layer of list/tuple of paddle.v2.config_base.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>num_classes</strong> (<em>int</em>) &#8211; number of classes.</li>
-<li><strong>act</strong> (<em>paddle.v2.activation.Base</em>) &#8211; Activation type. paddle.v2.activation.Sigmoid is the default.</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>neg_distribution</strong> (<em>list | tuple | collections.Sequence | None</em>) &#8211; The distribution for generating the random negative labels.
-A uniform distribution will be used if not provided.
-If not None, its length must be equal to num_classes.</li>
-<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute | None | bool | Any</em>) &#8211; The bias attribute. If the parameter is set to False or an object
-whose type is not paddle.v2.attr.ParameterAttribute, no bias is defined. If the
-parameter is set to True, the bias is initialized to zero.</li>
+<li><strong>input</strong> (<em>paddle.v2.config_base.Layer | list | tuple | collections.Sequence</em>) &#8211; The input layers. It should be a paddle.v2.config_base.Layer or a list/tuple
+of paddle.v2.config_base.Layer.</li>
+<li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The ground truth.</li>
+<li><strong>weight</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The weight layer defines a weight for each sample in the
+mini-batch. The default value is None.</li>
+<li><strong>num_classes</strong> (<em>int</em>) &#8211; The class number.</li>
+<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute|list</em>) &#8211; The parameter attributes.</li>
+<li><strong>num_neg_samples</strong> (<em>int</em>) &#8211; The number of sampled negative labels. The default
+value is 10.</li>
+<li><strong>neg_distribution</strong> (<em>list | tuple | collections.Sequence | None</em>) &#8211; The discrete noisy distribution over the output
+space from which num_neg_samples negative labels
+are sampled. If this parameter is not set, a
+uniform distribution will be used. A user defined
+distribution is a list whose length must be equal
+to the num_classes. Each member of the list defines
+the probability of a class given input x.</li>
+<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute | None | bool | Any</em>) &#8211; The attribute for bias. If this parameter is set False or
+any object whose type is not paddle.v2.attr.ParameterAttribute, no bias
+is added. If this parameter is set True, the bias is
+initialized to zero.</li>
 <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute</em>) &#8211; Extra Layer Attribute.</li>
 </ul>
 </td>
 </tr>
-<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first">layer name.</p>
+<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first">The paddle.v2.config_base.Layer object.</p>
 </td>
 </tr>
 <tr class="field-odd field"><th class="field-name">返回类型:</th><td class="field-body"><p class="first last">paddle.v2.config_base.Layer</p>