Generate Python docs from pytorch/pytorch@4ae71c8

Author: pytorchbot

docs/master/__config__.html

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docs/master/_modules/torch/__config__.html

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     <div class="version">
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     <div class="version">
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+      <a href='https://pytorch.org/docs/versions.html'>master (1.11.0a0+git4ae71c8 ) &#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">
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@@ -476,7 +476,7 @@ <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 +521,7 @@ <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 +571,7 @@ <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 +672,7 @@ <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>

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