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doc/ui/api/trainer_config_helpers/layers.html

@@ -257,13 +257,14 @@ default Bias.</li>
 <h2>conv_operator<a class="headerlink" href="#conv-operator" title="Permalink to this headline">¶</a></h2>
 <dl class="function">
 <dt>
-<code class="descclassname">paddle.trainer_config_helpers.layers.</code><code class="descname">conv_operator</code><span class="sig-paren">(</span><em>input</em>, <em>filter_size</em>, <em>num_filters</em>, <em>num_channel=None</em>, <em>stride=1</em>, <em>padding=0</em>, <em>groups=1</em>, <em>filter_size_y=None</em>, <em>stride_y=None</em>, <em>padding_y=None</em><span class="sig-paren">)</span></dt>
+<code class="descclassname">paddle.trainer_config_helpers.layers.</code><code class="descname">conv_operator</code><span class="sig-paren">(</span><em>img</em>, <em>filter</em>, <em>filter_size</em>, <em>num_filters</em>, <em>num_channel=None</em>, <em>stride=1</em>, <em>padding=0</em>, <em>groups=1</em>, <em>filter_size_y=None</em>, <em>stride_y=None</em>, <em>padding_y=None</em><span class="sig-paren">)</span></dt>
 <dd><p>Different from img_conv_layer, conv_op is an Operator, which can be used
 in mixed_layer. And conv_op takes two inputs to perform convolution.
 The first input is the image and the second is filter kernel. It only
 support GPU mode.</p>
 <p>The example usage is:</p>
-<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">op</span> <span class="o">=</span> <span class="n">conv_operator</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="p">[</span><span class="n">layer1</span><span class="p">,</span> <span class="n">layer2</span><span class="p">],</span>
+<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">op</span> <span class="o">=</span> <span class="n">conv_operator</span><span class="p">(</span><span class="n">img</span><span class="o">=</span><span class="n">input1</span><span class="p">,</span>
+                   <span class="nb">filter</span><span class="o">=</span><span class="n">input2</span><span class="p">,</span>
                    <span class="n">filter_size</span><span class="o">=</span><span class="mf">3.0</span><span class="p">,</span>
                    <span class="n">num_filters</span><span class="o">=</span><span class="mi">64</span><span class="p">,</span>
                    <span class="n">num_channels</span><span class="o">=</span><span class="mi">64</span><span class="p">)</span>
@@ -274,7 +275,8 @@ support GPU mode.</p>
 <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>input</strong> (<em>LayerOutput|list|tuple</em>) &#8211; Input layer.</li>
+<li><strong>img</strong> (<em>LayerOutput</em>) &#8211; input image</li>
+<li><strong>filter</strong> (<em>LayerOutput</em>) &#8211; input filter</li>
 <li><strong>filter_size</strong> (<em>int</em>) &#8211; The x dimension of a filter kernel.</li>
 <li><strong>filter_size_y</strong> (<em>int</em>) &#8211; The y dimension of a filter kernel. Since
 PaddlePaddle now supports rectangular filters,