Generate Python docs from pytorch/pytorch@bdf5a87

Author: pytorchbot

docs/master/_images/RReLU.png

@@ -899,14 +899,14 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
 <span class="s2">    have forward mode AD gradients.</span>
 <span class="s2">    &quot;&quot;&quot;</span><span class="p">)</span>
 
-    <span class="k">def</span> <span class="nf">is_shared</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+<div class="viewcode-block" id="Tensor.is_shared"><a class="viewcode-back" href="../../generated/torch.Tensor.is_shared.html#torch.Tensor.is_shared">[docs]</a>    <span class="k">def</span> <span class="nf">is_shared</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
         <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Checks if tensor is in shared memory.</span>
 
 <span class="sd">        This is always ``True`` for CUDA tensors.</span>
 <span class="sd">        &quot;&quot;&quot;</span>
         <span class="k">if</span> <span class="n">has_torch_function_unary</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
             <span class="k">return</span> <span class="n">handle_torch_function</span><span class="p">(</span><span class="n">Tensor</span><span class="o">.</span><span class="n">is_shared</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="p">,),</span> <span class="bp">self</span><span class="p">)</span>
-        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">storage</span><span class="p">()</span><span class="o">.</span><span class="n">is_shared</span><span class="p">()</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">storage</span><span class="p">()</span><span class="o">.</span><span class="n">is_shared</span><span class="p">()</span></div>
 
     <span class="k">def</span> <span class="nf">share_memory_</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
         <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Moves the underlying storage to shared memory.</span>
@@ -934,7 +934,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
             <span class="k">return</span> <span class="n">handle_torch_function</span><span class="p">(</span><span class="n">Tensor</span><span class="o">.</span><span class="n">norm</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="p">,),</span> <span class="bp">self</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="n">p</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="n">dim</span><span class="p">,</span> <span class="n">keepdim</span><span class="o">=</span><span class="n">keepdim</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">norm</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">p</span><span class="p">,</span> <span class="n">dim</span><span class="p">,</span> <span class="n">keepdim</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span></div>
 
-<div class="viewcode-block" id="Tensor.lu"><a class="viewcode-back" href="../../generated/torch.Tensor.lu.html#torch.Tensor.lu">[docs]</a>    <span class="k">def</span> <span class="nf">lu</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pivot</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">get_infos</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
+    <span class="k">def</span> <span class="nf">lu</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pivot</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">get_infos</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
         <span class="sa">r</span><span class="sd">&quot;&quot;&quot;See :func:`torch.lu`&quot;&quot;&quot;</span>
         <span class="c1"># If get_infos is True, then we don&#39;t need to check for errors and vice versa</span>
         <span class="k">if</span> <span class="n">has_torch_function_unary</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
@@ -944,7 +944,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
         <span class="k">if</span> <span class="n">get_infos</span><span class="p">:</span>
             <span class="k">return</span> <span class="n">LU</span><span class="p">,</span> <span class="n">pivots</span><span class="p">,</span> <span class="n">infos</span>
         <span class="k">else</span><span class="p">:</span>
-            <span class="k">return</span> <span class="n">LU</span><span class="p">,</span> <span class="n">pivots</span></div>
+            <span class="k">return</span> <span class="n">LU</span><span class="p">,</span> <span class="n">pivots</span>
 
     <span class="k">def</span> <span class="nf">stft</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n_fft</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">hop_length</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
              <span class="n">win_length</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">window</span><span class="p">:</span> <span class="s1">&#39;Optional[Tensor]&#39;</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
@@ -965,7 +965,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">stft</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n_fft</span><span class="p">,</span> <span class="n">hop_length</span><span class="p">,</span> <span class="n">win_length</span><span class="p">,</span> <span class="n">window</span><span class="p">,</span> <span class="n">center</span><span class="p">,</span>
                           <span class="n">pad_mode</span><span class="p">,</span> <span class="n">normalized</span><span class="p">,</span> <span class="n">onesided</span><span class="p">,</span> <span class="n">return_complex</span><span class="o">=</span><span class="n">return_complex</span><span class="p">)</span>
 
-    <span class="k">def</span> <span class="nf">istft</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n_fft</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">hop_length</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+<div class="viewcode-block" id="Tensor.istft"><a class="viewcode-back" href="../../generated/torch.Tensor.istft.html#torch.Tensor.istft">[docs]</a>    <span class="k">def</span> <span class="nf">istft</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n_fft</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">hop_length</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
               <span class="n">win_length</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">window</span><span class="p">:</span> <span class="s1">&#39;Optional[Tensor]&#39;</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
               <span class="n">center</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> <span class="n">normalized</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
               <span class="n">onesided</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">length</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
@@ -978,7 +978,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
                 <span class="n">return_complex</span><span class="o">=</span><span class="n">return_complex</span>
             <span class="p">)</span>
         <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">istft</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n_fft</span><span class="p">,</span> <span class="n">hop_length</span><span class="p">,</span> <span class="n">win_length</span><span class="p">,</span> <span class="n">window</span><span class="p">,</span> <span class="n">center</span><span class="p">,</span>
-                           <span class="n">normalized</span><span class="p">,</span> <span class="n">onesided</span><span class="p">,</span> <span class="n">length</span><span class="p">,</span> <span class="n">return_complex</span><span class="o">=</span><span class="n">return_complex</span><span class="p">)</span>
+                           <span class="n">normalized</span><span class="p">,</span> <span class="n">onesided</span><span class="p">,</span> <span class="n">length</span><span class="p">,</span> <span class="n">return_complex</span><span class="o">=</span><span class="n">return_complex</span><span class="p">)</span></div>
 
     <span class="k">def</span> <span class="nf">resize</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">sizes</span><span class="p">):</span>
         <span class="k">if</span> <span class="n">has_torch_function_unary</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>