Generate Python docs from pytorch/pytorch@2a7f9f0

Author: pytorchbot

docs/master/__config__.html

@@ -208,7 +208,7 @@
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-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
     </div>
 
 

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+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch.html

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           <div class="pytorch-left-menu-search">
 
     <div class="version">
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+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/__config__.html

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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
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docs/master/_modules/torch/_jit_internal.html

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           <div class="pytorch-left-menu-search">
 
     <div class="version">
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+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
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docs/master/_modules/torch/_lobpcg.html

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           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
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docs/master/_modules/torch/_lowrank.html

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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
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@@ -714,7 +714,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
         <span class="c1"># All strings are unicode in Python 3.</span>
         <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">_tensor_str</span><span class="o">.</span><span class="n">_str</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
 
-<div class="viewcode-block" id="Tensor.backward"><a class="viewcode-back" href="../../generated/torch.Tensor.backward.html#torch.Tensor.backward">[docs]</a>    <span class="k">def</span> <span class="nf">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">retain_graph</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_graph</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">inputs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
+    <span class="k">def</span> <span class="nf">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">retain_graph</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">create_graph</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">inputs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
         <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Computes the gradient of current tensor w.r.t. graph leaves.</span>
 
 <span class="sd">        The graph is differentiated using the chain rule. If the tensor is</span>
@@ -770,7 +770,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
                 <span class="n">retain_graph</span><span class="o">=</span><span class="n">retain_graph</span><span class="p">,</span>
                 <span class="n">create_graph</span><span class="o">=</span><span class="n">create_graph</span><span class="p">,</span>
                 <span class="n">inputs</span><span class="o">=</span><span class="n">inputs</span><span class="p">)</span>
-        <span class="n">torch</span><span class="o">.</span><span class="n">autograd</span><span class="o">.</span><span class="n">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="p">,</span> <span class="n">retain_graph</span><span class="p">,</span> <span class="n">create_graph</span><span class="p">,</span> <span class="n">inputs</span><span class="o">=</span><span class="n">inputs</span><span class="p">)</span></div>
+        <span class="n">torch</span><span class="o">.</span><span class="n">autograd</span><span class="o">.</span><span class="n">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="p">,</span> <span class="n">retain_graph</span><span class="p">,</span> <span class="n">create_graph</span><span class="p">,</span> <span class="n">inputs</span><span class="o">=</span><span class="n">inputs</span><span class="p">)</span>
 
     <span class="k">def</span> <span class="nf">register_hook</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">hook</span><span class="p">):</span>
         <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Registers a backward hook.</span>
@@ -872,14 +872,14 @@ <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>
@@ -938,7 +938,7 @@ <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>
@@ -951,7 +951,7 @@ <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>

docs/master/_modules/torch/_tensor.html

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     <div class="version">
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docs/master/_modules/torch/_tensor_str.html

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     <div class="version">
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docs/master/_modules/torch/_vmap_internals.html

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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
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docs/master/_modules/torch/ao/ns/_numeric_suite.html

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           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
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docs/master/_modules/torch/ao/ns/_numeric_suite_fx.html

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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
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docs/master/_modules/torch/ao/ns/fx/utils.html

@@ -207,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/ao/quantization/fake_quantize.html

@@ -207,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/ao/quantization/fuse_modules.html

@@ -207,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
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docs/master/_modules/torch/ao/quantization/observer.html

@@ -207,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git0d66748 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git2a7f9f0 ) &#x25BC</a>
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