提交 61e4932e 编写于 作者: T Travis CI

Deploy to GitHub Pages: 87f9b583

上级 8ae1db2e
......@@ -562,32 +562,8 @@ Duplicable: False Optional: False</li>
<h2>dropout<a class="headerlink" href="#dropout" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">dropout</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>Dropout Operator.</p>
<p>Dropout refers to randomly dropping out units in a nerual network. It is a
regularization technique for reducing overfitting by preventing neuron
co-adaption during training. The dropout operator randomly set (according to
the given dropout probability) the outputs of some units to zero, while others
are set equal to their corresponding inputs.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>x</strong> &#8211; The input of dropout op.
Duplicable: False Optional: False</li>
<li><strong>dropout_prob</strong> (<em>FLOAT</em>) &#8211; Probability of setting units to zero.</li>
<li><strong>is_test</strong> (<em>BOOLEAN</em>) &#8211; True if in test phase.</li>
<li><strong>seed</strong> (<em>INT</em>) &#8211; Dropout random seed.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">The output of dropout op.</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">dropout</code><span class="sig-paren">(</span><em>x</em>, <em>dropout_prob</em>, <em>is_test=False</em>, <em>seed=0</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd></dd></dl>
</div>
<div class="section" id="reshape">
......
因为 它太大了无法显示 source diff 。你可以改为 查看blob
......@@ -575,32 +575,8 @@ Duplicable: False Optional: False</li>
<h2>dropout<a class="headerlink" href="#dropout" 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">dropout</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd><p>Dropout Operator.</p>
<p>Dropout refers to randomly dropping out units in a nerual network. It is a
regularization technique for reducing overfitting by preventing neuron
co-adaption during training. The dropout operator randomly set (according to
the given dropout probability) the outputs of some units to zero, while others
are set equal to their corresponding inputs.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first simple">
<li><strong>x</strong> &#8211; The input of dropout op.
Duplicable: False Optional: False</li>
<li><strong>dropout_prob</strong> (<em>FLOAT</em>) &#8211; Probability of setting units to zero.</li>
<li><strong>is_test</strong> (<em>BOOLEAN</em>) &#8211; True if in test phase.</li>
<li><strong>seed</strong> (<em>INT</em>) &#8211; Dropout random seed.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first last">The output of dropout op.</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<code class="descclassname">paddle.v2.fluid.layers.</code><code class="descname">dropout</code><span class="sig-paren">(</span><em>x</em>, <em>dropout_prob</em>, <em>is_test=False</em>, <em>seed=0</em>, <em>**kwargs</em><span class="sig-paren">)</span></dt>
<dd></dd></dl>
</div>
<div class="section" id="reshape">
......
此差异已折叠。
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册