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'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>
 
 

docs/master/_modules/index.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>
 
 
@@ -614,7 +614,7 @@ <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="../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="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>
 <span class="sd">    ``t``. This type will also be used as default floating point type for</span>
 <span class="sd">    type inference in :func:`torch.tensor`.</span>
@@ -635,10 +635,10 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">_string_classes</span><span class="p">):</span>
         <span class="n">t</span> <span class="o">=</span> <span class="n">_import_dotted_name</span><span class="p">(</span><span class="n">t</span><span class="p">)</span>
-    <span class="n">_C</span><span class="o">.</span><span class="n">_set_default_tensor_type</span><span class="p">(</span><span class="n">t</span><span class="p">)</span></div>
+    <span class="n">_C</span><span class="o">.</span><span class="n">_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_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="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`.</span>
 <span class="sd">    This dtype is:</span>
 
@@ -666,9 +666,9 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="sd">        torch.complex128</span>
 
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">_C</span><span class="o">.</span><span class="n">_set_default_dtype</span><span class="p">(</span><span class="n">d</span><span class="p">)</span></div>
+    <span class="n">_C</span><span class="o">.</span><span class="n">_set_default_dtype</span><span class="p">(</span><span class="n">d</span><span class="p">)</span>
 
-<div class="viewcode-block" id="set_deterministic"><a class="viewcode-back" href="../generated/torch.set_deterministic.html#torch.set_deterministic">[docs]</a><span class="k">def</span> <span class="nf">set_deterministic</span><span class="p">(</span><span class="n">d</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">set_deterministic</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 whether PyTorch operations must use &quot;deterministic&quot;</span>
 <span class="sd">    algorithms. That is, algorithms which, given the same input, and when</span>
 <span class="sd">    run on the same software and hardware, always produce the same output.</span>
@@ -740,7 +740,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="sd">        d (:class:`bool`): If True, force operations to be deterministic.</span>
 <span class="sd">                           If False, allow non-deterministic operations.</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">_C</span><span class="o">.</span><span class="n">_set_deterministic</span><span class="p">(</span><span class="n">d</span><span class="p">)</span></div>
+    <span class="n">_C</span><span class="o">.</span><span class="n">_set_deterministic</span><span class="p">(</span><span class="n">d</span><span class="p">)</span>
 
 <div class="viewcode-block" id="is_deterministic"><a class="viewcode-back" href="../generated/torch.is_deterministic.html#torch.is_deterministic">[docs]</a><span class="k">def</span> <span class="nf">is_deterministic</span><span class="p">():</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns True if the global deterministic flag is turned on. Refer to</span>
@@ -760,8 +760,8 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
     <span class="k">pass</span>
 
 
-<span class="k">class</span> <span class="nc">FloatStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">FloatStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
-    <span class="k">pass</span>
+<div class="viewcode-block" id="FloatStorage"><a class="viewcode-back" href="../storage.html#torch.FloatStorage">[docs]</a><span class="k">class</span> <span class="nc">FloatStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">FloatStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
+    <span class="k">pass</span></div>
 
 
 <span class="k">class</span> <span class="nc">HalfStorage</span><span class="p">(</span><span class="n">_C</span><span class="o">.</span><span class="n">HalfStorageBase</span><span class="p">,</span> <span class="n">_StorageBase</span><span class="p">):</span>
@@ -928,9 +928,9 @@ <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="../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="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>
-    <span class="k">return</span> <span class="n">_C</span><span class="o">.</span><span class="n">_GLIBCXX_USE_CXX11_ABI</span></div>
+    <span class="k">return</span> <span class="n">_C</span><span class="o">.</span><span class="n">_GLIBCXX_USE_CXX11_ABI</span>
 
 
 <span class="c1"># Import the ops &quot;namespace&quot;</span>
@@ -962,11 +962,12 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="n">quantized_lstm</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ops</span><span class="o">.</span><span class="n">aten</span><span class="o">.</span><span class="n">quantized_lstm</span>
 <span class="n">quantized_gru</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ops</span><span class="o">.</span><span class="n">aten</span><span class="o">.</span><span class="n">quantized_gru</span>
 
-<span class="kn">from</span> <span class="nn">.overrides</span> <span class="kn">import</span> <span class="n">has_torch_function</span><span class="p">,</span> <span class="n">handle_torch_function</span>
 
 <span class="k">def</span> <span class="nf">Assert</span><span class="p">(</span><span class="n">condition</span><span class="p">,</span> <span class="n">message</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;A wrapper around Python&#39;s assert which is symbolically traceable.</span>
 <span class="sd">    &quot;&quot;&quot;</span>
+    <span class="kn">from</span> <span class="nn">.overrides</span> <span class="kn">import</span> <span class="n">has_torch_function</span><span class="p">,</span> <span class="n">handle_torch_function</span>
+
     <span class="k">if</span> <span class="nb">type</span><span class="p">(</span><span class="n">condition</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span> <span class="ow">and</span> <span class="n">has_torch_function</span><span class="p">((</span><span class="n">condition</span><span class="p">,)):</span>
         <span class="k">return</span> <span class="n">handle_torch_function</span><span class="p">(</span><span class="n">Assert</span><span class="p">,</span> <span class="p">(</span><span class="n">condition</span><span class="p">,),</span> <span class="n">condition</span><span class="p">,</span> <span class="n">message</span><span class="p">)</span>
     <span class="k">assert</span> <span class="n">condition</span><span class="p">,</span> <span class="n">message</span>

docs/master/_modules/torch/__config__.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#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'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>
 
 
@@ -652,7 +652,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
         <span class="s2">&quot;if this method is not scripted, copy the python method onto the scripted model&quot;</span>
 
 
-<div class="viewcode-block" id="export"><a class="viewcode-back" href="../../jit.html#torch.jit.export">[docs]</a><span class="k">def</span> <span class="nf">export</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">export</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 that a method on an ``nn.Module`` is used as an entry point into a</span>
 <span class="sd">    :class:`ScriptModule` and should be compiled.</span>
@@ -695,7 +695,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
 <span class="sd">        m = torch.jit.script(MyModule())</span>
 <span class="sd">    &quot;&quot;&quot;</span>
     <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">EXPORT</span>
-    <span class="k">return</span> <span class="n">fn</span></div>
+    <span class="k">return</span> <span class="n">fn</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>
@@ -1076,7 +1076,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
     <span class="nb">globals</span><span class="p">()[</span><span class="sa">f</span><span class="s2">&quot;BroadcastingList</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">BroadcastingList1</span>
 
 
-<span class="k">def</span> <span class="nf">is_scripting</span><span class="p">():</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>
@@ -1095,7 +1095,7 @@ <h1>Source code for torch._jit_internal</h1><div class="highlight"><pre>
 <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>
+    <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>

docs/master/_modules/torch/_lobpcg.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/_lowrank.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/_tensor_str.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/_utils.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/_vmap_internals.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>
 
 

docs/master/_modules/torch/autograd.html

@@ -158,7 +158,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#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'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#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'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#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'>1.8.0a0+96741a8 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+7a69d3f &#x25BC</a>
                 </div>