auto-generating sphinx docs

Author: pytorchbot

docs/master/__config__.html

@@ -159,7 +159,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/index.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/__config__.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/_jit_internal.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 
@@ -1053,6 +1053,29 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
 <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">7</span><span class="p">):</span>
     <span class="nb">globals</span><span class="p">()[</span><span class="s2">&quot;BroadcastingList</span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">BroadcastingList1</span>
 
+
+<div class="viewcode-block" id="is_scripting"><a class="viewcode-back" href="../../jit_language_reference.html#torch.jit.is_scripting">[docs]</a><span class="k">def</span> <span class="nf">is_scripting</span><span class="p">():</span>
+    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Function that returns True when in compilation and False otherwise. This</span>
+<span class="sd">    is useful especially with the @unused decorator to leave code in your</span>
+<span class="sd">    model that is not yet TorchScript compatible.</span>
+<span class="sd">    .. testcode::</span>
+
+<span class="sd">        import torch</span>
+
+<span class="sd">        @torch.jit.unused</span>
+<span class="sd">        def unsupported_linear_op(x):</span>
+<span class="sd">            return x</span>
+
+<span class="sd">        def linear(x):</span>
+<span class="sd">           if not torch.jit.is_scripting():</span>
+<span class="sd">              return torch.linear(x)</span>
+<span class="sd">           else:</span>
+<span class="sd">              return unsupported_linear_op(x)</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="k">return</span> <span class="kc">False</span></div>
+
+
 <span class="c1"># Retrieves a fully-qualified name (module hierarchy + classname) for a given obj.</span>
 <span class="k">def</span> <span class="nf">_qualified_name</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
     <span class="c1"># This special case allows us to override the qualified name on a type.</span>

docs/master/_modules/torch/_lobpcg.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/_lowrank.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 
@@ -426,7 +426,7 @@ <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">q</span><span class="o">=</span><span class="mi">6</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="kc">None</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">q</span><span class="o">=</span><span class="mi">6</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">2</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="c1"># type: (Tensor, Optional[int], Optional[int], Optional[Tensor]) -&gt; Tuple[Tensor, Tensor, Tensor]</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>
@@ -471,7 +471,7 @@ <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">q</span><span class="o">=</span><span class="mi">6</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">M</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
@@ -511,7 +511,7 @@ <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">q</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">2</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">q</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">center</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">niter</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span>
     <span class="c1"># type: (Tensor, Optional[int], bool, int) -&gt; Tuple[Tensor, Tensor, Tensor]</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>
@@ -612,7 +612,7 @@ <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/_tensor_str.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/_utils.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/autograd.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/autograd/anomaly_mode.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/autograd/function.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/autograd/functional.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+d38ed4d &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.7.0a0+e68ee78 &#x25BC</a>
                 </div>