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'>1.6.0a0+77dd00c &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.6.0a0+4fef376 &#x25BC</a>
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@@ -234,7 +234,7 @@
 <li class="toctree-l1"><a class="reference internal" href="onnx.html">torch.onnx</a></li>
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 <li class="toctree-l1"><a class="reference internal" href="quantization.html">Quantization</a></li>
-<li class="toctree-l1"><a class="reference internal" href="rpc/index.html">Distributed RPC Framework</a></li>
+<li class="toctree-l1"><a class="reference internal" href="rpc.html">Distributed RPC Framework</a></li>
 <li class="toctree-l1"><a class="reference internal" href="random.html">torch.random</a></li>
 <li class="toctree-l1"><a class="reference internal" href="sparse.html">torch.sparse</a></li>
 <li class="toctree-l1"><a class="reference internal" href="storage.html">torch.Storage</a></li>

docs/master/_images/ReLU61.png

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.6.0a0+77dd00c &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.6.0a0+4fef376 &#x25BC</a>
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@@ -233,7 +233,7 @@
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 <li class="toctree-l1"><a class="reference internal" href="../optim.html">torch.optim</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../quantization.html">Quantization</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../rpc/index.html">Distributed RPC Framework</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../rpc.html">Distributed RPC Framework</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../random.html">torch.random</a></li>
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docs/master/_modules/index.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.6.0a0+77dd00c &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.6.0a0+4fef376 &#x25BC</a>
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@@ -233,7 +233,7 @@
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 <li class="toctree-l1"><a class="reference internal" href="../quantization.html">Quantization</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../rpc/index.html">Distributed RPC Framework</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../rpc.html">Distributed RPC Framework</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../random.html">torch.random</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../sparse.html">torch.sparse</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../storage.html">torch.Storage</a></li>
@@ -504,7 +504,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">module</span> <span class="o">+</span> <span class="n">class_name</span>
 
 
-<div class="viewcode-block" id="is_tensor"><a class="viewcode-back" href="../torch.html#torch.is_tensor">[docs]</a><span class="k">def</span> <span class="nf">is_tensor</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
+<div class="viewcode-block" id="is_tensor"><a class="viewcode-back" href="../generated/torch.is_tensor.html#torch.is_tensor">[docs]</a><span class="k">def</span> <span class="nf">is_tensor</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns True if `obj` is a PyTorch tensor.</span>
 
 <span class="sd">    Args:</span>
@@ -513,7 +513,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span></div>
 
 
-<div class="viewcode-block" id="is_storage"><a class="viewcode-back" href="../torch.html#torch.is_storage">[docs]</a><span class="k">def</span> <span class="nf">is_storage</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
+<div class="viewcode-block" id="is_storage"><a class="viewcode-back" href="../generated/torch.is_storage.html#torch.is_storage">[docs]</a><span class="k">def</span> <span class="nf">is_storage</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns True if `obj` is a PyTorch storage object.</span>
 
 <span class="sd">    Args:</span>
@@ -522,7 +522,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="nb">type</span><span class="p">(</span><span class="n">obj</span><span class="p">)</span> <span class="ow">in</span> <span class="n">_storage_classes</span></div>
 
 
-<div class="viewcode-block" id="set_default_tensor_type"><a class="viewcode-back" href="../torch.html#torch.set_default_tensor_type">[docs]</a><span class="k">def</span> <span class="nf">set_default_tensor_type</span><span class="p">(</span><span class="n">t</span><span class="p">):</span>
+<div class="viewcode-block" id="set_default_tensor_type"><a class="viewcode-back" href="../generated/torch.set_default_tensor_type.html#torch.set_default_tensor_type">[docs]</a><span class="k">def</span> <span class="nf">set_default_tensor_type</span><span class="p">(</span><span class="n">t</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Sets the default ``torch.Tensor`` type to floating point tensor type</span>
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@@ -546,7 +546,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
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-<div class="viewcode-block" id="set_default_dtype"><a class="viewcode-back" href="../torch.html#torch.set_default_dtype">[docs]</a><span class="k">def</span> <span class="nf">set_default_dtype</span><span class="p">(</span><span class="n">d</span><span class="p">):</span>
+<div class="viewcode-block" id="set_default_dtype"><a class="viewcode-back" href="../generated/torch.set_default_dtype.html#torch.set_default_dtype">[docs]</a><span class="k">def</span> <span class="nf">set_default_dtype</span><span class="p">(</span><span class="n">d</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Sets the default floating point dtype to :attr:`d`. This type will be</span>
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@@ -667,6 +667,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
     <span class="k">if</span> <span class="n">name</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s1">&#39;__&#39;</span><span class="p">):</span>
         <span class="k">continue</span>
     <span class="nb">globals</span><span class="p">()[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">_VariableFunctions</span><span class="p">,</span> <span class="n">name</span><span class="p">)</span>
+    <span class="n">__all__</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
 
 <span class="c1">################################################################################</span>
 <span class="c1"># Import interface functions defined in Python</span>
@@ -730,7 +731,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="k">del</span> <span class="n">_torch_docs</span><span class="p">,</span> <span class="n">_tensor_docs</span><span class="p">,</span> <span class="n">_storage_docs</span>
 
 
-<div class="viewcode-block" id="compiled_with_cxx11_abi"><a class="viewcode-back" href="../torch.html#torch.compiled_with_cxx11_abi">[docs]</a><span class="k">def</span> <span class="nf">compiled_with_cxx11_abi</span><span class="p">():</span>
+<div class="viewcode-block" id="compiled_with_cxx11_abi"><a class="viewcode-back" href="../generated/torch.compiled_with_cxx11_abi.html#torch.compiled_with_cxx11_abi">[docs]</a><span class="k">def</span> <span class="nf">compiled_with_cxx11_abi</span><span class="p">():</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns whether PyTorch was built with _GLIBCXX_USE_CXX11_ABI=1&quot;&quot;&quot;</span>
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docs/master/_modules/torch.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.6.0a0+77dd00c &#x25BC</a>
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@@ -233,7 +233,7 @@
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-<li class="toctree-l1"><a class="reference internal" href="../../rpc/index.html">Distributed RPC Framework</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../rpc.html">Distributed RPC Framework</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../random.html">torch.random</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../sparse.html">torch.sparse</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../storage.html">torch.Storage</a></li>

docs/master/_modules/torch/__config__.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.6.0a0+77dd00c &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.6.0a0+4fef376 &#x25BC</a>
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@@ -233,7 +233,7 @@
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 <li class="toctree-l1"><a class="reference internal" href="../../quantization.html">Quantization</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../rpc/index.html">Distributed RPC Framework</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../rpc.html">Distributed RPC Framework</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../random.html">torch.random</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../sparse.html">torch.sparse</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../storage.html">torch.Storage</a></li>
@@ -634,7 +634,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">fn</span></div>
 
 
-<div class="viewcode-block" id="unused"><a class="viewcode-back" href="../../jit.html#torch.jit.unused">[docs]</a><span class="k">def</span> <span class="nf">unused</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
+<div class="viewcode-block" id="unused"><a class="viewcode-back" href="../../generated/torch.jit.unused.html#torch.jit.unused">[docs]</a><span class="k">def</span> <span class="nf">unused</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    This decorator indicates to the compiler that a function or method should</span>
 <span class="sd">    be ignored and replaced with the raising of an exception. This allows you</span>
@@ -674,7 +674,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
     <span class="n">fn</span><span class="o">.</span><span class="n">_torchscript_modifier</span> <span class="o">=</span> <span class="n">FunctionModifiers</span><span class="o">.</span><span class="n">UNUSED</span>
     <span class="k">return</span> <span class="n">fn</span></div>
 
-<div class="viewcode-block" id="ignore"><a class="viewcode-back" href="../../jit.html#torch.jit.ignore">[docs]</a><span class="k">def</span> <span class="nf">ignore</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+<div class="viewcode-block" id="ignore"><a class="viewcode-back" href="../../generated/torch.jit.ignore.html#torch.jit.ignore">[docs]</a><span class="k">def</span> <span class="nf">ignore</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    This decorator indicates to the compiler that a function or method should</span>
 <span class="sd">    be ignored and left as a Python function. This allows you to leave code in</span>

docs/master/_modules/torch/_jit_internal.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.6.0a0+77dd00c &#x25BC</a>
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@@ -233,7 +233,7 @@
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-<li class="toctree-l1"><a class="reference internal" href="../../rpc/index.html">Distributed RPC Framework</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../rpc.html">Distributed RPC Framework</a></li>
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 <li class="toctree-l1"><a class="reference internal" href="../../storage.html">torch.Storage</a></li>
@@ -352,7 +352,7 @@ <h1>Source code for torch._lobpcg</h1><div class="highlight"><pre>
 <span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;lobpcg&#39;</span><span class="p">]</span>
 
 
-<div class="viewcode-block" id="lobpcg"><a class="viewcode-back" href="../../torch.html#torch.lobpcg">[docs]</a><span class="k">def</span> <span class="nf">lobpcg</span><span class="p">(</span><span class="n">A</span><span class="p">,</span>                   <span class="c1"># type: Tensor</span>
+<div class="viewcode-block" id="lobpcg"><a class="viewcode-back" href="../../generated/torch.lobpcg.html#torch.lobpcg">[docs]</a><span class="k">def</span> <span class="nf">lobpcg</span><span class="p">(</span><span class="n">A</span><span class="p">,</span>                   <span class="c1"># type: Tensor</span>
            <span class="n">k</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>              <span class="c1"># type: Optional[int]</span>
            <span class="n">B</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>              <span class="c1"># type: Optional[Tensor]</span>
            <span class="n">X</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>              <span class="c1"># type: Optional[Tensor]</span>
@@ -487,18 +487,18 @@ <h1>Source code for torch._lobpcg</h1><div class="highlight"><pre>
 <span class="sd">      Preconditioned Eigensolver: Locally Optimal Block Preconditioned</span>
 <span class="sd">      Conjugate Gradient Method. SIAM J. Sci. Comput., 23(2),</span>
 <span class="sd">      517-541. (25 pages)</span>
-<span class="sd">      `https://epubs.siam.org/doi/abs/10.1137/S1064827500366124`_</span>
+<span class="sd">      https://epubs.siam.org/doi/abs/10.1137/S1064827500366124</span>
 
 <span class="sd">      [StathopoulosEtal2002] Andreas Stathopoulos and Kesheng</span>
 <span class="sd">      Wu. (2002) A Block Orthogonalization Procedure with Constant</span>
 <span class="sd">      Synchronization Requirements. SIAM J. Sci. Comput., 23(6),</span>
 <span class="sd">      2165-2182. (18 pages)</span>
-<span class="sd">      `https://epubs.siam.org/doi/10.1137/S1064827500370883`_</span>
+<span class="sd">      https://epubs.siam.org/doi/10.1137/S1064827500370883</span>
 
 <span class="sd">      [DuerschEtal2018] Jed A. Duersch, Meiyue Shao, Chao Yang, Ming</span>
 <span class="sd">      Gu. (2018) A Robust and Efficient Implementation of LOBPCG.</span>
 <span class="sd">      SIAM J. Sci. Comput., 40(5), C655-C676. (22 pages)</span>
-<span class="sd">      `https://epubs.siam.org/doi/abs/10.1137/17M1129830`_</span>
+<span class="sd">      https://epubs.siam.org/doi/abs/10.1137/17M1129830</span>
 
 <span class="sd">    &quot;&quot;&quot;</span>