auto-generating sphinx docs

Author: pytorchbot

docs/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 70ea54c860b1ca3e07a20e4470914a97
+config: 5c9c098f2b2b63c7722a5b518429df6c
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/_modules/index.html

@@ -347,6 +347,7 @@
 </li>
 <li class="toctree-l2"><a class="reference internal" href="../nn.html#vision-functions">Vision functions</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="../nn.html#pixel-shuffle"><span class="hidden-section">pixel_shuffle</span></a></li>
+<li class="toctree-l3"><a class="reference internal" href="../nn.html#pad"><span class="hidden-section">pad</span></a></li>
 </ul>
 </li>
 </ul>

docs/_modules/torch.html

@@ -348,6 +348,7 @@
 </li>
 <li class="toctree-l2"><a class="reference internal" href="../../nn.html#vision-functions">Vision functions</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="../../nn.html#pixel-shuffle"><span class="hidden-section">pixel_shuffle</span></a></li>
+<li class="toctree-l3"><a class="reference internal" href="../../nn.html#pad"><span class="hidden-section">pad</span></a></li>
 </ul>
 </li>
 </ul>
@@ -504,7 +505,7 @@ <h1>Source code for torch._utils</h1><div class="highlight"><pre>
 <span class="sd">                      Otherwise, the argument has no effect.</span>
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="k">if</span> <span class="n">new_type</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__module__</span> <span class="o">+</span> <span class="s1">&#39;.&#39;</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">__module__</span> <span class="o">+</span> <span class="s1">&#39;.&#39;</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span>
 
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">new_type</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
         <span class="n">new_type</span> <span class="o">=</span> <span class="n">_import_dotted_name</span><span class="p">(</span><span class="n">new_type</span><span class="p">)</span>
@@ -513,7 +514,7 @@ <h1>Source code for torch._utils</h1><div class="highlight"><pre>
     <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_sparse</span><span class="p">:</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="n">new_type</span><span class="o">.</span><span class="n">is_sparse</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Cannot cast sparse tensor to dense tensor&quot;</span><span class="p">)</span>
-        <span class="n">new_type_name</span> <span class="o">=</span> <span class="n">new_type</span><span class="o">.</span><span class="vm">__module__</span> <span class="o">+</span> <span class="s1">&#39;.&#39;</span> <span class="o">+</span> <span class="n">new_type</span><span class="o">.</span><span class="vm">__name__</span>
+        <span class="n">new_type_name</span> <span class="o">=</span> <span class="n">new_type</span><span class="o">.</span><span class="n">__module__</span> <span class="o">+</span> <span class="s1">&#39;.&#39;</span> <span class="o">+</span> <span class="n">new_type</span><span class="o">.</span><span class="n">__name__</span>
         <span class="n">new_values_type_name</span> <span class="o">=</span> <span class="n">new_type_name</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;.sparse&#39;</span><span class="p">,</span> <span class="s1">&#39;&#39;</span><span class="p">)</span>
         <span class="n">new_values</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">values</span><span class="p">()</span><span class="o">.</span><span class="n">type</span><span class="p">(</span><span class="n">new_values_type_name</span><span class="p">,</span> <span class="k">async</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">new_type</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">indices</span><span class="p">(),</span> <span class="n">new_values</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">())</span>
@@ -544,12 +545,12 @@ <h1>Source code for torch._utils</h1><div class="highlight"><pre>
             <span class="n">device</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span>
     <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="n">device</span><span class="p">):</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_sparse</span><span class="p">:</span>
-            <span class="n">new_type</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">sparse</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span>
+            <span class="n">new_type</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">sparse</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span><span class="p">)</span>
             <span class="n">indices</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indices</span><span class="p">()</span><span class="o">.</span><span class="n">cuda</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="k">async</span><span class="p">)</span>
             <span class="n">values</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">values</span><span class="p">()</span><span class="o">.</span><span class="n">cuda</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="k">async</span><span class="p">)</span>
             <span class="k">return</span> <span class="n">new_type</span><span class="p">(</span><span class="n">indices</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">())</span>
         <span class="k">else</span><span class="p">:</span>
-            <span class="n">new_type</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span>
+            <span class="n">new_type</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span><span class="p">)</span>
             <span class="k">return</span> <span class="n">new_type</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">())</span><span class="o">.</span><span class="n">copy_</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="k">async</span><span class="p">)</span>
 
 

docs/_modules/torch/_tensor_str.html

@@ -348,6 +348,7 @@
 </li>
 <li class="toctree-l2"><a class="reference internal" href="../../nn.html#vision-functions">Vision functions</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="../../nn.html#pixel-shuffle"><span class="hidden-section">pixel_shuffle</span></a></li>
+<li class="toctree-l3"><a class="reference internal" href="../../nn.html#pad"><span class="hidden-section">pad</span></a></li>
 </ul>
 </li>
 </ul>

docs/_modules/torch/_utils.html

@@ -348,6 +348,7 @@
 </li>
 <li class="toctree-l2"><a class="reference internal" href="../../../nn.html#vision-functions">Vision functions</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="../../../nn.html#pixel-shuffle"><span class="hidden-section">pixel_shuffle</span></a></li>
+<li class="toctree-l3"><a class="reference internal" href="../../../nn.html#pad"><span class="hidden-section">pad</span></a></li>
 </ul>
 </li>
 </ul>
@@ -532,7 +533,7 @@ <h1>Source code for torch.autograd.function</h1><div class="highlight"><pre>
 <span class="sd">            :class:`Function` that created corresponding input, and an index</span>
 <span class="sd">            of the previous function output that&#39;s been used.</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="fm">__call__</span> <span class="o">=</span> <span class="n">_C</span><span class="o">.</span><span class="n">_FunctionBase</span><span class="o">.</span><span class="n">_do_forward</span>
+    <span class="n">__call__</span> <span class="o">=</span> <span class="n">_C</span><span class="o">.</span><span class="n">_FunctionBase</span><span class="o">.</span><span class="n">_do_forward</span>
 
 <div class="viewcode-block" id="Function.save_for_backward"><a class="viewcode-back" href="../../../autograd.html#torch.autograd.Function.save_for_backward">[docs]</a>    <span class="k">def</span> <span class="nf">save_for_backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">tensors</span><span class="p">):</span>
         <span class="sd">&quot;&quot;&quot;Saves given tensors for a future call to :func:`~Function.backward`.</span>
@@ -631,7 +632,7 @@ <h1>Source code for torch.autograd.function</h1><div class="highlight"><pre>
 <span class="k">class</span> <span class="nc">InplaceFunction</span><span class="p">(</span><span class="n">Function</span><span class="p">):</span>
 
     <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
-        <span class="nb">super</span><span class="p">(</span><span class="n">InplaceFunction</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">InplaceFunction</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">inplace</span> <span class="o">=</span> <span class="n">inplace</span>
 
 
@@ -708,7 +709,7 @@ <h1>Source code for torch.autograd.function</h1><div class="highlight"><pre>
         <span class="n">result</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">backward_extended</span><span class="p">(</span><span class="o">*</span><span class="n">nested_gradients</span><span class="p">)</span>
         <span class="k">return</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">_iter_None_tensors</span><span class="p">(</span><span class="n">result</span><span class="p">))</span>
 
-    <span class="fm">__call__</span> <span class="o">=</span> <span class="n">_do_forward</span>
+    <span class="n">__call__</span> <span class="o">=</span> <span class="n">_do_forward</span>
 
     <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
         <span class="n">nested_tensors</span> <span class="o">=</span> <span class="n">_map_variable_tensor</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_nested_input</span><span class="p">)</span>