Generate Python docs from pytorch/pytorch@70f8816

Author: pytorchbot

docs/master/__config__.html

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docs/master/_modules/index.html

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docs/master/_modules/torch.html

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@@ -805,11 +805,11 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 
     <span class="n">use_deterministic_algorithms</span><span class="p">(</span><span class="n">d</span><span class="p">)</span>
 
-<span class="k">def</span> <span class="nf">are_deterministic_algorithms_enabled</span><span class="p">():</span>
+<div class="viewcode-block" id="are_deterministic_algorithms_enabled"><a class="viewcode-back" href="../generated/torch.are_deterministic_algorithms_enabled.html#torch.are_deterministic_algorithms_enabled">[docs]</a><span class="k">def</span> <span class="nf">are_deterministic_algorithms_enabled</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>
 <span class="sd">    :func:`torch.use_deterministic_algorithms` documentation for more details.</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">return</span> <span class="n">_C</span><span class="o">.</span><span class="n">_get_deterministic_algorithms</span><span class="p">()</span>
+    <span class="k">return</span> <span class="n">_C</span><span class="o">.</span><span class="n">_get_deterministic_algorithms</span><span class="p">()</span></div>
 
 <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;This function is deprecated and will be removed in a future release.</span>
@@ -1035,9 +1035,9 @@ <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>

docs/master/_modules/torch/__config__.html

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@@ -465,7 +465,7 @@ <h1>Source code for torch.autograd.grad_mode</h1><div class="highlight"><pre>
         <span class="k">raise</span> <span class="ne">NotImplementedError</span>
 
 
-<div class="viewcode-block" id="no_grad"><a class="viewcode-back" href="../../../generated/torch.no_grad.html#torch.no_grad">[docs]</a><span class="k">class</span> <span class="nc">no_grad</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>
+<span class="k">class</span> <span class="nc">no_grad</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot;Context-manager that disabled gradient calculation.</span>
 
 <span class="sd">    Disabling gradient calculation is useful for inference, when you are sure</span>
@@ -505,7 +505,7 @@ <h1>Source code for torch.autograd.grad_mode</h1><div class="highlight"><pre>
         <span class="n">torch</span><span class="o">.</span><span class="n">set_grad_enabled</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
 
     <span class="k">def</span> <span class="fm">__exit__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">exc_type</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">exc_value</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">traceback</span><span class="p">:</span> <span class="n">Any</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="n">torch</span><span class="o">.</span><span class="n">set_grad_enabled</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">prev</span><span class="p">)</span></div>
+        <span class="n">torch</span><span class="o">.</span><span class="n">set_grad_enabled</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">prev</span><span class="p">)</span>
 
 
 <div class="viewcode-block" id="enable_grad"><a class="viewcode-back" href="../../../generated/torch.enable_grad.html#torch.enable_grad">[docs]</a><span class="k">class</span> <span class="nc">enable_grad</span><span class="p">(</span><span class="n">_DecoratorContextManager</span><span class="p">):</span>

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