Deploy to GitHub Pages: 95de6f51

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

@@ -426,7 +426,7 @@ F1-score of this label.</li>
 <dd><p>Positive-negative pair rate Evaluator which adapts to rank task like
 learning to rank. This evaluator must contain at least three layers.</p>
 <p>The simple usage:</p>
-<div class="highlight-python"><div class="highlight"><pre><span></span><span class="nb">eval</span> <span class="o">=</span> <span class="n">evaluator</span><span class="o">.</span><span class="n">pnpair</span><span class="p">(</span><span class="nb">input</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="n">info</span><span class="p">)</span>
+<div class="highlight-python"><div class="highlight"><pre><span></span><span class="nb">eval</span> <span class="o">=</span> <span class="n">evaluator</span><span class="o">.</span><span class="n">pnpair</span><span class="p">(</span><span class="nb">input</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="n">query_id</span><span class="p">)</span>
 </pre></div>
 </div>
 <table class="docutils field-list" frame="void" rules="none">
@@ -436,9 +436,13 @@ learning to rank. This evaluator must contain at least three layers.</p>
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
 <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input Layer name. The output prediction of network.</li>
 <li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Label layer name.</li>
-<li><strong>info</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Info layer name. (TODO, explaination)</li>
+<li><strong>query_id</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Query_id layer name. Query_id indicates that which query
+each sample belongs to. Its shape should be
+the same as output of Label layer.</li>
 <li><strong>weight</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Weight Layer name. It should be a matrix with size
-[sample_num, 1]. (TODO, explaination)</li>
+[sample_num, 1] which indicates the weight of each sample.
+The default weight of sample is 1 if the weight layer is None.
+And the pair weight is the mean of the two samples&#8217; weight.</li>
 <li><strong>name</strong> (<em>None|basestring</em>) &#8211; Evaluator name.</li>
 </ul>
 </td>

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

@@ -4378,6 +4378,10 @@ a_i * z_i  &amp;\quad \mathrm{otherwise}\end{split}\]</div>
 <li>partial_sum = number of outputs, indicates all elements share the same weight.</li>
 </ul>
 </li>
+<li><strong>channel_shared</strong> (<em>bool</em>) &#8211; whether or not the parameter are shared across channels.
+- channel_shared = True, we set the partial_sum to the number of outputs.
+- channel_shared = False, we set the partial_sum to the number of elements in one channel.</li>
+<li><strong>num_channels</strong> (<em>int</em>) &#8211; number of input channel.</li>
 <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The parameter attribute. See paddle.v2.attr.ParameterAttribute for details.</li>
 <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute | None</em>) &#8211; The extra layer attribute. See paddle.v2.attr.ExtraAttribute for
 details.</li>

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

@@ -440,7 +440,7 @@ F1-score of this label.</li>
 <dd><p>Positive-negative pair rate Evaluator which adapts to rank task like
 learning to rank. This evaluator must contain at least three layers.</p>
 <p>The simple usage:</p>
-<div class="highlight-python"><div class="highlight"><pre><span></span><span class="nb">eval</span> <span class="o">=</span> <span class="n">evaluator</span><span class="o">.</span><span class="n">pnpair</span><span class="p">(</span><span class="nb">input</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="n">info</span><span class="p">)</span>
+<div class="highlight-python"><div class="highlight"><pre><span></span><span class="nb">eval</span> <span class="o">=</span> <span class="n">evaluator</span><span class="o">.</span><span class="n">pnpair</span><span class="p">(</span><span class="nb">input</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="n">query_id</span><span class="p">)</span>
 </pre></div>
 </div>
 <table class="docutils field-list" frame="void" rules="none">
@@ -450,9 +450,13 @@ learning to rank. This evaluator must contain at least three layers.</p>
 <tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first last simple">
 <li><strong>input</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Input Layer name. The output prediction of network.</li>
 <li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Label layer name.</li>
-<li><strong>info</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Info layer name. (TODO, explaination)</li>
+<li><strong>query_id</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Query_id layer name. Query_id indicates that which query
+each sample belongs to. Its shape should be
+the same as output of Label layer.</li>
 <li><strong>weight</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; Weight Layer name. It should be a matrix with size
-[sample_num, 1]. (TODO, explaination)</li>
+[sample_num, 1] which indicates the weight of each sample.
+The default weight of sample is 1 if the weight layer is None.
+And the pair weight is the mean of the two samples&#8217; weight.</li>
 <li><strong>name</strong> (<em>None|basestring</em>) &#8211; Evaluator name.</li>
 </ul>
 </td>

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

@@ -4392,6 +4392,10 @@ a_i * z_i  &amp;\quad \mathrm{otherwise}\end{split}\]</div>
 <li>partial_sum = number of outputs, indicates all elements share the same weight.</li>
 </ul>
 </li>
+<li><strong>channel_shared</strong> (<em>bool</em>) &#8211; whether or not the parameter are shared across channels.
+- channel_shared = True, we set the partial_sum to the number of outputs.
+- channel_shared = False, we set the partial_sum to the number of elements in one channel.</li>
+<li><strong>num_channels</strong> (<em>int</em>) &#8211; number of input channel.</li>
 <li><strong>param_attr</strong> (<em>paddle.v2.attr.ParameterAttribute</em>) &#8211; The parameter attribute. See paddle.v2.attr.ParameterAttribute for details.</li>
 <li><strong>layer_attr</strong> (<em>paddle.v2.attr.ExtraAttribute | None</em>) &#8211; The extra layer attribute. See paddle.v2.attr.ExtraAttribute for
 details.</li>