Deploy to GitHub Pages: ca62c104

develop/doc/api/v2/data.html

@@ -474,7 +474,7 @@ nested sequence.</li>
 <span id="datafeeder"></span><h2>DataFeeder<a class="headerlink" href="#module-paddle.v2.data_feeder" title="Permalink to this headline">¶</a></h2>
 <dl class="class">
 <dt id="paddle.v2.data_feeder.DataFeeder">
-<em class="property">class </em><code class="descclassname">paddle.v2.data_feeder.</code><code class="descname">DataFeeder</code><span class="sig-paren">(</span><em>data_types</em>, <em>reader_dict</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.data_feeder.DataFeeder" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><code class="descclassname">paddle.v2.data_feeder.</code><code class="descname">DataFeeder</code><span class="sig-paren">(</span><em>data_types</em>, <em>feeding=None</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.data_feeder.DataFeeder" title="Permalink to this definition">¶</a></dt>
 <dd><p>DataFeeder converts the data returned by paddle.reader into a data structure
 of Arguments which is defined in the API. The paddle.reader usually returns
 a list of mini-batch data entries. Each data entry in the list is one sample.
@@ -509,7 +509,7 @@ interface.</p>
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
 <li><strong>data_types</strong> (<em>list</em>) &#8211; A list to specify data name and type. Each item is
 a tuple of (data_name, data_type).</li>
-<li><strong>reader_dict</strong> (<em>dict</em>) &#8211; A dictionary to specify the position of each data
+<li><strong>reader_dict</strong> &#8211; A dictionary to specify the position of each data
 in the input data.</li>
 </ul>
 </td>

develop/doc/api/v2/run_logic.html

@@ -429,7 +429,7 @@ TODO(yuyang18): Complete comments</p>
 </table>
 <dl class="method">
 <dt id="paddle.v2.trainer.SGD.train">
-<code class="descname">train</code><span class="sig-paren">(</span><em>reader</em>, <em>num_passes=1</em>, <em>event_handler=None</em>, <em>reader_dict=None</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.trainer.SGD.train" title="Permalink to this definition">¶</a></dt>
+<code class="descname">train</code><span class="sig-paren">(</span><em>reader</em>, <em>num_passes=1</em>, <em>event_handler=None</em>, <em>feeding=None</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.trainer.SGD.train" title="Permalink to this definition">¶</a></dt>
 <dd><p>Training method. Will train num_passes of input data.</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
@@ -440,6 +440,8 @@ TODO(yuyang18): Complete comments</p>
 <li><strong>num_passes</strong> &#8211; The total train passes.</li>
 <li><strong>event_handler</strong> (<em></em><em>(</em><em>BaseEvent</em><em>) </em><em>=&gt; None</em>) &#8211; Event handler. A method will be invoked when event
 occurred.</li>
+<li><strong>feeding</strong> (<em>dict</em>) &#8211; Feeding is a map of neural network input name and array
+index that reader returns.</li>
 </ul>
 </td>
 </tr>

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Prediction","Activations","Parameter Attributes","DataSources","Evaluators","Layers","Networks","Optimizers","Poolings","Data Related API","Configuration Related API","Trainer API","PaddlePaddle Design Doc","Python Data Reader Design Doc","Simple Linear Regression","Installing from Sources","PaddlePaddle in Docker Containers","Install and Build","Debian Package installation guide","GET STARTED","RNN Models","RNN Configuration","Contribute Code","Write New Layers","HOW TO","Tune GPU Performance","Run Distributed Training","Argument Outline","Detail Description","Set Command-line Parameters","Use Case","Distributed PaddlePaddle Training on AWS with Kubernetes","Paddle On Kubernetes","<no title>","<no title>","PaddlePaddle Documentation","Chinese Word Embedding Model Tutorial","Generative Adversarial Networks (GAN)","Image Classification Tutorial","Model Zoo - ImageNet","TUTORIALS","Quick Start","MovieLens Dataset","Regression MovieLens Ratting","Semantic Role labeling Tutorial","Sentiment Analysis Tutorial","Text generation 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\ No newline at end of file

develop/doc_cn/api/v2/data.html

@@ -481,7 +481,7 @@ nested sequence.</li>
 <span id="datafeeder"></span><h2>DataFeeder<a class="headerlink" href="#module-paddle.v2.data_feeder" title="永久链接至标题">¶</a></h2>
 <dl class="class">
 <dt id="paddle.v2.data_feeder.DataFeeder">
-<em class="property">class </em><code class="descclassname">paddle.v2.data_feeder.</code><code class="descname">DataFeeder</code><span class="sig-paren">(</span><em>data_types</em>, <em>reader_dict</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.data_feeder.DataFeeder" title="永久链接至目标">¶</a></dt>
+<em class="property">class </em><code class="descclassname">paddle.v2.data_feeder.</code><code class="descname">DataFeeder</code><span class="sig-paren">(</span><em>data_types</em>, <em>feeding=None</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.data_feeder.DataFeeder" title="永久链接至目标">¶</a></dt>
 <dd><p>DataFeeder converts the data returned by paddle.reader into a data structure
 of Arguments which is defined in the API. The paddle.reader usually returns
 a list of mini-batch data entries. Each data entry in the list is one sample.
@@ -516,7 +516,7 @@ interface.</p>
 <tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first last simple">
 <li><strong>data_types</strong> (<em>list</em>) &#8211; A list to specify data name and type. Each item is
 a tuple of (data_name, data_type).</li>
-<li><strong>reader_dict</strong> (<em>dict</em>) &#8211; A dictionary to specify the position of each data
+<li><strong>reader_dict</strong> &#8211; A dictionary to specify the position of each data
 in the input data.</li>
 </ul>
 </td>

develop/doc_cn/api/v2/run_logic.html

@@ -436,7 +436,7 @@ TODO(yuyang18): Complete comments</p>
 </table>
 <dl class="method">
 <dt id="paddle.v2.trainer.SGD.train">
-<code class="descname">train</code><span class="sig-paren">(</span><em>reader</em>, <em>num_passes=1</em>, <em>event_handler=None</em>, <em>reader_dict=None</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.trainer.SGD.train" title="永久链接至目标">¶</a></dt>
+<code class="descname">train</code><span class="sig-paren">(</span><em>reader</em>, <em>num_passes=1</em>, <em>event_handler=None</em>, <em>feeding=None</em><span class="sig-paren">)</span><a class="headerlink" href="#paddle.v2.trainer.SGD.train" title="永久链接至目标">¶</a></dt>
 <dd><p>Training method. Will train num_passes of input data.</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
@@ -447,6 +447,8 @@ TODO(yuyang18): Complete comments</p>
 <li><strong>num_passes</strong> &#8211; The total train passes.</li>
 <li><strong>event_handler</strong> (<em></em><em>(</em><em>BaseEvent</em><em>) </em><em>=&gt; None</em>) &#8211; Event handler. A method will be invoked when event
 occurred.</li>
+<li><strong>feeding</strong> (<em>dict</em>) &#8211; Feeding is a map of neural network input name and array
+index that reader returns.</li>
 </ul>
 </td>
 </tr>