提交 07658199 编写于 作者: T Travis CI

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Trainer API Trainer API
########### ###########
========== ==========
Parameters Parameters
========== ==========
...@@ -24,3 +25,10 @@ Event ...@@ -24,3 +25,10 @@ Event
.. automodule:: paddle.v2.event .. automodule:: paddle.v2.event
:members: :members:
=========
Inference
=========
.. autofunction:: paddle.v2.infer
\ No newline at end of file
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<li><a class="reference internal" href="#module-paddle.v2.parameters">Parameters</a></li> <li><a class="reference internal" href="#module-paddle.v2.parameters">Parameters</a></li>
<li><a class="reference internal" href="#module-paddle.v2.trainer">Trainer</a></li> <li><a class="reference internal" href="#module-paddle.v2.trainer">Trainer</a></li>
<li><a class="reference internal" href="#module-paddle.v2.event">Event</a></li> <li><a class="reference internal" href="#module-paddle.v2.event">Event</a></li>
<li><a class="reference internal" href="#inference">Inference</a></li>
</ul> </ul>
</li> </li>
</ul> </ul>
...@@ -496,6 +497,51 @@ index that reader returns.</li> ...@@ -496,6 +497,51 @@ index that reader returns.</li>
<dd><p>Event On One Batch Training Complete.</p> <dd><p>Event On One Batch Training Complete.</p>
</dd></dl> </dd></dl>
</div>
<div class="section" id="inference">
<h2>Inference<a class="headerlink" href="#inference" title="Permalink to this headline"></a></h2>
<dl class="function">
<dt id="paddle.v2.infer">
<code class="descclassname">paddle.v2.</code><code class="descname">infer</code><span class="sig-paren">(</span><em>output</em>, <em>parameters</em>, <em>input=None</em>, <em>batch_size=None</em>, <em>reader=None</em>, <em>feeding=None</em>, <em>field='value'</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.infer" title="Permalink to this definition"></a></dt>
<dd><p>Infer a neural network by given neural network output and parameters. The
user should pass either a batch of input data or reader method.</p>
<p>Example usages:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">result</span> <span class="o">=</span> <span class="n">paddle</span><span class="o">.</span><span class="n">infer</span><span class="p">(</span><span class="n">prediction</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="nb">input</span><span class="o">=</span><span class="n">SomeData</span><span class="p">,</span>
<span class="n">batch_size</span><span class="o">=</span><span class="mi">32</span><span class="p">)</span>
<span class="k">print</span> <span class="n">result</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>output</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; output of the neural network that would be inferred</li>
<li><strong>parameters</strong> (<a class="reference internal" href="#paddle.v2.parameters.Parameters" title="paddle.v2.parameters.Parameters"><em>paddle.v2.parameters.Parameters</em></a>) &#8211; parameters of the neural network.</li>
<li><strong>input</strong> (<em>collections.Iterable</em>) &#8211; input data batch. Should be a python iterable object, and each
element is the data batch.</li>
<li><strong>batch_size</strong> (<em>int</em>) &#8211; the batch size when perform inference. Default is the
length of input.</li>
<li><strong>reader</strong> (<em>callable</em>) &#8211; input data reader creator in batch. If this field is set, the
<cite>input</cite> and <cite>batch_size</cite> will be ignored.</li>
<li><strong>feeding</strong> &#8211; Reader dictionary. Default could generate from input
value.</li>
<li><strong>field</strong> (<em>str</em>) &#8211; The prediction field. It should in [<cite>value</cite>, <cite>ids</cite>]. <cite>value</cite>
means return the prediction probabilities, <cite>ids</cite> means return
the prediction labels. Default is <cite>value</cite></li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">a numpy array</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">numpy.ndarray</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</div> </div>
</div> </div>
......
...@@ -437,11 +437,13 @@ ...@@ -437,11 +437,13 @@
</li> </li>
<li><a href="api/v2/model_configs.html#paddle.v2.networks.img_conv_bn_pool">img_conv_bn_pool (class in paddle.v2.networks)</a> <li><a href="api/v2/model_configs.html#paddle.v2.networks.img_conv_bn_pool">img_conv_bn_pool (class in paddle.v2.networks)</a>
</li> </li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="api/v2/model_configs.html#paddle.v2.networks.img_conv_group">img_conv_group (class in paddle.v2.networks)</a> <li><a href="api/v2/model_configs.html#paddle.v2.networks.img_conv_group">img_conv_group (class in paddle.v2.networks)</a>
</li> </li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="api/v2/model_configs.html#paddle.v2.layer.img_pool">img_pool (class in paddle.v2.layer)</a> <li><a href="api/v2/model_configs.html#paddle.v2.layer.img_pool">img_pool (class in paddle.v2.layer)</a>
</li>
<li><a href="api/v2/run_logic.html#paddle.v2.infer">infer() (in module paddle.v2)</a>
</li> </li>
<li><a href="api/v2/data.html#paddle.v2.data_type.InputType">InputType (class in paddle.v2.data_type)</a> <li><a href="api/v2/data.html#paddle.v2.data_type.InputType">InputType (class in paddle.v2.data_type)</a>
</li> </li>
......
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...@@ -2,6 +2,7 @@ ...@@ -2,6 +2,7 @@
Trainer API Trainer API
########### ###########
========== ==========
Parameters Parameters
========== ==========
...@@ -24,3 +25,10 @@ Event ...@@ -24,3 +25,10 @@ Event
.. automodule:: paddle.v2.event .. automodule:: paddle.v2.event
:members: :members:
=========
Inference
=========
.. autofunction:: paddle.v2.infer
\ No newline at end of file
...@@ -178,6 +178,7 @@ ...@@ -178,6 +178,7 @@
<li><a class="reference internal" href="#module-paddle.v2.parameters">Parameters</a></li> <li><a class="reference internal" href="#module-paddle.v2.parameters">Parameters</a></li>
<li><a class="reference internal" href="#module-paddle.v2.trainer">Trainer</a></li> <li><a class="reference internal" href="#module-paddle.v2.trainer">Trainer</a></li>
<li><a class="reference internal" href="#module-paddle.v2.event">Event</a></li> <li><a class="reference internal" href="#module-paddle.v2.event">Event</a></li>
<li><a class="reference internal" href="#inference">Inference</a></li>
</ul> </ul>
</li> </li>
</ul> </ul>
...@@ -503,6 +504,51 @@ index that reader returns.</li> ...@@ -503,6 +504,51 @@ index that reader returns.</li>
<dd><p>Event On One Batch Training Complete.</p> <dd><p>Event On One Batch Training Complete.</p>
</dd></dl> </dd></dl>
</div>
<div class="section" id="inference">
<h2>Inference<a class="headerlink" href="#inference" title="永久链接至标题"></a></h2>
<dl class="function">
<dt id="paddle.v2.infer">
<code class="descclassname">paddle.v2.</code><code class="descname">infer</code><span class="sig-paren">(</span><em>output</em>, <em>parameters</em>, <em>input=None</em>, <em>batch_size=None</em>, <em>reader=None</em>, <em>feeding=None</em>, <em>field='value'</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.infer" title="永久链接至目标"></a></dt>
<dd><p>Infer a neural network by given neural network output and parameters. The
user should pass either a batch of input data or reader method.</p>
<p>Example usages:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">result</span> <span class="o">=</span> <span class="n">paddle</span><span class="o">.</span><span class="n">infer</span><span class="p">(</span><span class="n">prediction</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="nb">input</span><span class="o">=</span><span class="n">SomeData</span><span class="p">,</span>
<span class="n">batch_size</span><span class="o">=</span><span class="mi">32</span><span class="p">)</span>
<span class="k">print</span> <span class="n">result</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>output</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; output of the neural network that would be inferred</li>
<li><strong>parameters</strong> (<a class="reference internal" href="#paddle.v2.parameters.Parameters" title="paddle.v2.parameters.Parameters"><em>paddle.v2.parameters.Parameters</em></a>) &#8211; parameters of the neural network.</li>
<li><strong>input</strong> (<em>collections.Iterable</em>) &#8211; input data batch. Should be a python iterable object, and each
element is the data batch.</li>
<li><strong>batch_size</strong> (<em>int</em>) &#8211; the batch size when perform inference. Default is the
length of input.</li>
<li><strong>reader</strong> (<em>callable</em>) &#8211; input data reader creator in batch. If this field is set, the
<cite>input</cite> and <cite>batch_size</cite> will be ignored.</li>
<li><strong>feeding</strong> &#8211; Reader dictionary. Default could generate from input
value.</li>
<li><strong>field</strong> (<em>str</em>) &#8211; The prediction field. It should in [<cite>value</cite>, <cite>ids</cite>]. <cite>value</cite>
means return the prediction probabilities, <cite>ids</cite> means return
the prediction labels. Default is <cite>value</cite></li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first">a numpy array</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">numpy.ndarray</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</div> </div>
</div> </div>
......
...@@ -444,11 +444,13 @@ ...@@ -444,11 +444,13 @@
</li> </li>
<li><a href="api/v2/model_configs.html#paddle.v2.networks.img_conv_bn_pool">img_conv_bn_pool (paddle.v2.networks 中的类)</a> <li><a href="api/v2/model_configs.html#paddle.v2.networks.img_conv_bn_pool">img_conv_bn_pool (paddle.v2.networks 中的类)</a>
</li> </li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="api/v2/model_configs.html#paddle.v2.networks.img_conv_group">img_conv_group (paddle.v2.networks 中的类)</a> <li><a href="api/v2/model_configs.html#paddle.v2.networks.img_conv_group">img_conv_group (paddle.v2.networks 中的类)</a>
</li> </li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="api/v2/model_configs.html#paddle.v2.layer.img_pool">img_pool (paddle.v2.layer 中的类)</a> <li><a href="api/v2/model_configs.html#paddle.v2.layer.img_pool">img_pool (paddle.v2.layer 中的类)</a>
</li>
<li><a href="api/v2/run_logic.html#paddle.v2.infer">infer() (在 paddle.v2 模块中)</a>
</li> </li>
<li><a href="api/v2/data.html#paddle.v2.data_type.InputType">InputType (paddle.v2.data_type 中的类)</a> <li><a href="api/v2/data.html#paddle.v2.data_type.InputType">InputType (paddle.v2.data_type 中的类)</a>
</li> </li>
......
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