Generate Python docs from pytorch/pytorch@3a21f38

Author: pytorchbot

docs/master/__config__.html

@@ -46,6 +46,20 @@
 <meta name="robots" content="noindex">
 
 
+  <!-- Google Analytics -->
+  
+    <script async src="https://www.googletagmanager.com/gtag/js?id=UA-117752657-2"></script>
+    <script>
+      window.dataLayer = window.dataLayer || [];
+      function gtag(){dataLayer.push(arguments);}
+      gtag('js', new Date());
+
+      gtag('config', 'UA-117752657-2');
+    </script>
+  
+  <!-- End Google Analytics -->
+  
+
 
 
   <script src="_static/js/modernizr.min.js"></script>
@@ -194,7 +208,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gitf8f96d4 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git3a21f38 ) &#x25BC</a>
     </div>
 
 

docs/master/_images/RReLU.png

@@ -45,6 +45,20 @@
 <meta name="robots" content="noindex">
 
 
+  <!-- Google Analytics -->
+  
+    <script async src="https://www.googletagmanager.com/gtag/js?id=UA-117752657-2"></script>
+    <script>
+      window.dataLayer = window.dataLayer || [];
+      function gtag(){dataLayer.push(arguments);}
+      gtag('js', new Date());
+
+      gtag('config', 'UA-117752657-2');
+    </script>
+  
+  <!-- End Google Analytics -->
+  
+
 
 
   <script src="../_static/js/modernizr.min.js"></script>
@@ -193,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gitf8f96d4 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git3a21f38 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/index.html

@@ -45,6 +45,20 @@
 <meta name="robots" content="noindex">
 
 
+  <!-- Google Analytics -->
+  
+    <script async src="https://www.googletagmanager.com/gtag/js?id=UA-117752657-2"></script>
+    <script>
+      window.dataLayer = window.dataLayer || [];
+      function gtag(){dataLayer.push(arguments);}
+      gtag('js', new Date());
+
+      gtag('config', 'UA-117752657-2');
+    </script>
+  
+  <!-- End Google Analytics -->
+  
+
 
 
   <script src="../_static/js/modernizr.min.js"></script>
@@ -193,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gitf8f96d4 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git3a21f38 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch.html

@@ -45,6 +45,20 @@
 <meta name="robots" content="noindex">
 
 
+  <!-- Google Analytics -->
+  
+    <script async src="https://www.googletagmanager.com/gtag/js?id=UA-117752657-2"></script>
+    <script>
+      window.dataLayer = window.dataLayer || [];
+      function gtag(){dataLayer.push(arguments);}
+      gtag('js', new Date());
+
+      gtag('config', 'UA-117752657-2');
+    </script>
+  
+  <!-- End Google Analytics -->
+  
+
 
 
   <script src="../../_static/js/modernizr.min.js"></script>
@@ -193,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gitf8f96d4 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git3a21f38 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/__config__.html

@@ -45,6 +45,20 @@
 <meta name="robots" content="noindex">
 
 
+  <!-- Google Analytics -->
+  
+    <script async src="https://www.googletagmanager.com/gtag/js?id=UA-117752657-2"></script>
+    <script>
+      window.dataLayer = window.dataLayer || [];
+      function gtag(){dataLayer.push(arguments);}
+      gtag('js', new Date());
+
+      gtag('config', 'UA-117752657-2');
+    </script>
+  
+  <!-- End Google Analytics -->
+  
+
 
 
   <script src="../../_static/js/modernizr.min.js"></script>
@@ -193,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gitf8f96d4 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git3a21f38 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_jit_internal.html

@@ -45,6 +45,20 @@
 <meta name="robots" content="noindex">
 
 
+  <!-- Google Analytics -->
+  
+    <script async src="https://www.googletagmanager.com/gtag/js?id=UA-117752657-2"></script>
+    <script>
+      window.dataLayer = window.dataLayer || [];
+      function gtag(){dataLayer.push(arguments);}
+      gtag('js', new Date());
+
+      gtag('config', 'UA-117752657-2');
+    </script>
+  
+  <!-- End Google Analytics -->
+  
+
 
 
   <script src="../../_static/js/modernizr.min.js"></script>
@@ -193,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gitf8f96d4 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git3a21f38 ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_lobpcg.html

@@ -45,6 +45,20 @@
 <meta name="robots" content="noindex">
 
 
+  <!-- Google Analytics -->
+  
+    <script async src="https://www.googletagmanager.com/gtag/js?id=UA-117752657-2"></script>
+    <script>
+      window.dataLayer = window.dataLayer || [];
+      function gtag(){dataLayer.push(arguments);}
+      gtag('js', new Date());
+
+      gtag('config', 'UA-117752657-2');
+    </script>
+  
+  <!-- End Google Analytics -->
+  
+
 
 
   <script src="../../_static/js/modernizr.min.js"></script>
@@ -193,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gitf8f96d4 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git3a21f38 ) &#x25BC</a>
     </div>
 
 
@@ -476,7 +490,7 @@ <h1>Source code for torch._lowrank</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">Q</span>
 
 
-<span class="k">def</span> <span class="nf">svd_lowrank</span><span class="p">(</span><span class="n">A</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">q</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="mi">6</span><span class="p">,</span> <span class="n">niter</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="mi">2</span><span class="p">,</span>
+<div class="viewcode-block" id="svd_lowrank"><a class="viewcode-back" href="../../generated/torch.svd_lowrank.html#torch.svd_lowrank">[docs]</a><span class="k">def</span> <span class="nf">svd_lowrank</span><span class="p">(</span><span class="n">A</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">q</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="mi">6</span><span class="p">,</span> <span class="n">niter</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="mi">2</span><span class="p">,</span>
                 <span class="n">M</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Tensor</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">]:</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Return the singular value decomposition ``(U, S, V)`` of a matrix,</span>
 <span class="sd">    batches of matrices, or a sparse matrix :math:`A` such that</span>
@@ -521,7 +535,7 @@ <h1>Source code for torch._lowrank</h1><div class="highlight"><pre>
         <span class="n">tensor_ops</span> <span class="o">=</span> <span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="n">M</span><span class="p">)</span>
         <span class="k">if</span> <span class="p">(</span><span class="ow">not</span> <span class="nb">set</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">type</span><span class="p">,</span> <span class="n">tensor_ops</span><span class="p">))</span><span class="o">.</span><span class="n">issubset</span><span class="p">((</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="nb">type</span><span class="p">(</span><span class="kc">None</span><span class="p">)))</span> <span class="ow">and</span> <span class="n">has_torch_function</span><span class="p">(</span><span class="n">tensor_ops</span><span class="p">)):</span>
             <span class="k">return</span> <span class="n">handle_torch_function</span><span class="p">(</span><span class="n">svd_lowrank</span><span class="p">,</span> <span class="n">tensor_ops</span><span class="p">,</span> <span class="n">A</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="n">q</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="n">niter</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="n">M</span><span class="p">)</span>
-    <span class="k">return</span> <span class="n">_svd_lowrank</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="n">q</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="n">niter</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="n">M</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">_svd_lowrank</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="n">q</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="n">niter</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="n">M</span><span class="p">)</span></div>
 
 
 <span class="k">def</span> <span class="nf">_svd_lowrank</span><span class="p">(</span><span class="n">A</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">q</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="mi">6</span><span class="p">,</span> <span class="n">niter</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="mi">2</span><span class="p">,</span>
@@ -571,7 +585,7 @@ <h1>Source code for torch._lowrank</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">U</span><span class="p">,</span> <span class="n">S</span><span class="p">,</span> <span class="n">V</span>
 
 
-<div class="viewcode-block" id="pca_lowrank"><a class="viewcode-back" href="../../generated/torch.pca_lowrank.html#torch.pca_lowrank">[docs]</a><span class="k">def</span> <span class="nf">pca_lowrank</span><span class="p">(</span><span class="n">A</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">q</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">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="k">def</span> <span class="nf">pca_lowrank</span><span class="p">(</span><span class="n">A</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">q</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">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">niter</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">]:</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Performs linear Principal Component Analysis (PCA) on a low-rank</span>
 <span class="sd">    matrix, batches of such matrices, or sparse matrix.</span>
@@ -672,7 +686,7 @@ <h1>Source code for torch._lowrank</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">_svd_lowrank</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="n">q</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="n">niter</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="n">M</span><span class="p">)</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="n">C</span> <span class="o">=</span> <span class="n">A</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">2</span><span class="p">,),</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-        <span class="k">return</span> <span class="n">_svd_lowrank</span><span class="p">(</span><span class="n">A</span> <span class="o">-</span> <span class="n">C</span><span class="p">,</span> <span class="n">q</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="n">niter</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="n">_svd_lowrank</span><span class="p">(</span><span class="n">A</span> <span class="o">-</span> <span class="n">C</span><span class="p">,</span> <span class="n">q</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="n">niter</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>
 </pre></div>
 
              </article>

docs/master/_modules/torch/_lowrank.html

@@ -45,6 +45,20 @@
 <meta name="robots" content="noindex">
 
 
+  <!-- Google Analytics -->
+  
+    <script async src="https://www.googletagmanager.com/gtag/js?id=UA-117752657-2"></script>
+    <script>
+      window.dataLayer = window.dataLayer || [];
+      function gtag(){dataLayer.push(arguments);}
+      gtag('js', new Date());
+
+      gtag('config', 'UA-117752657-2');
+    </script>
+  
+  <!-- End Google Analytics -->
+  
+
 
 
   <script src="../../_static/js/modernizr.min.js"></script>
@@ -193,7 +207,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+gitf8f96d4 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git3a21f38 ) &#x25BC</a>
     </div>
 
 
@@ -687,7 +701,7 @@ <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>
@@ -743,7 +757,7 @@ <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>