提交 d87339de 编写于 作者: T Travis CI

Deploy to GitHub Pages: b7a6cc9c

上级 57e1f878
......@@ -362,6 +362,11 @@ trans
.. autoclass:: paddle.v2.layer.trans
:noindex:
scale_shift
-----------
.. autoclass:: paddle.v2.layer.scale_shift
:noindex:
Sampling Layers
===============
......
......@@ -2941,6 +2941,44 @@ processed in one batch.</p>
</table>
</dd></dl>
</div>
<div class="section" id="scale-shift">
<h3>scale_shift<a class="headerlink" href="#scale-shift" title="Permalink to this headline"></a></h3>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.layer.</code><code class="descname">scale_shift</code></dt>
<dd><p>A layer applies a linear transformation to each element in each row of
the input matrix. For each element, the layer first re-scale it and then
adds a bias to it.</p>
<p>This layer is very like the SlopeInterceptLayer, except the scale and
bias are trainable.</p>
<div class="math">
\[y = w * x + b\]</div>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">scale_shift</span> <span class="o">=</span> <span class="n">scale_shift</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">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
</pre></div>
</div>
<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>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer.</em>) &#8211; The input layer.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The parameter attribute of scaling.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The parameter attribute of shifting.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">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>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
</div>
<div class="section" id="sampling-layers">
......
因为 它太大了无法显示 source diff 。你可以改为 查看blob
......@@ -362,6 +362,11 @@ trans
.. autoclass:: paddle.v2.layer.trans
:noindex:
scale_shift
-----------
.. autoclass:: paddle.v2.layer.scale_shift
:noindex:
Sampling Layers
===============
......
......@@ -2946,6 +2946,44 @@ processed in one batch.</p>
</table>
</dd></dl>
</div>
<div class="section" id="scale-shift">
<h3>scale_shift<a class="headerlink" href="#scale-shift" title="永久链接至标题"></a></h3>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.layer.</code><code class="descname">scale_shift</code></dt>
<dd><p>A layer applies a linear transformation to each element in each row of
the input matrix. For each element, the layer first re-scale it and then
adds a bias to it.</p>
<p>This layer is very like the SlopeInterceptLayer, except the scale and
bias are trainable.</p>
<div class="math">
\[y = w * x + b\]</div>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">scale_shift</span> <span class="o">=</span> <span class="n">scale_shift</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">bias_attr</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
</pre></div>
</div>
<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>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li>
<li><strong>input</strong> (<em>paddle.v2.config_base.Layer.</em>) &#8211; The input layer.</li>
<li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The parameter attribute of scaling.</li>
<li><strong>bias_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The parameter attribute of shifting.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first">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>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
</div>
<div class="section" id="sampling-layers">
......
因为 它太大了无法显示 source diff 。你可以改为 查看blob
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