Generate Python docs from pytorch/pytorch@849984a

Author: pytorchbot

docs/master/_images/RReLU.png

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/index.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 
@@ -1339,6 +1339,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 
 <span class="c1"># expose return_types</span>
 <span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">return_types</span>
+<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">library</span>
 </pre></div>
 
              </article>

docs/master/_modules/torch.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/__config__.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_jit_internal.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_lobpcg.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 
@@ -505,7 +505,7 @@ <h1>Source code for torch._lowrank</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">Q</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="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>
@@ -550,7 +550,7 @@ <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></div>
+    <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">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>
@@ -600,7 +600,7 @@ <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>
 
 
-<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>
+<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="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>
@@ -701,7 +701,7 @@ <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>
+        <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>
 </pre></div>
 
              </article>

docs/master/_modules/torch/_lowrank.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 
@@ -763,7 +763,7 @@ <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> <span class="n">tensor_contents</span><span class="o">=</span><span class="n">tensor_contents</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>
+<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="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>
@@ -819,7 +819,7 @@ <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>
+        <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="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>
@@ -921,14 +921,14 @@ <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>
 
-<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="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></div>
+        <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">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>

docs/master/_modules/torch/_tensor.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_tensor_str.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/_vmap_internals.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/amp/autocast_mode.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>
 
 

docs/master/_modules/torch/ao/ns/_numeric_suite.html

@@ -217,7 +217,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git3a6da16 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (1.12.0a0+git849984a ) &#x25BC</a>
     </div>