Generate Python docs from pytorch/pytorch@a8da1dd

Author: pytorchbot

docs/master/__config__.html

@@ -188,7 +188,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+4b6fea9 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+a8da1dd &#x25BC</a>
                 </div>
 
 
@@ -234,6 +234,7 @@
 <li class="toctree-l1"><a class="reference internal" href="notes/extending.html">Extending PyTorch</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notes/faq.html">Frequently Asked Questions</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notes/modules.html">Modules</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notes/multiprocessing.html">Multiprocessing best practices</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notes/randomness.html">Reproducibility</a></li>
 <li class="toctree-l1"><a class="reference internal" href="notes/serialization.html">Serialization semantics</a></li>

docs/master/_modules/index.html

@@ -187,7 +187,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+4b6fea9 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+a8da1dd &#x25BC</a>
                 </div>
 
 
@@ -233,6 +233,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../notes/extending.html">Extending PyTorch</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/faq.html">Frequently Asked Questions</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../notes/modules.html">Modules</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/multiprocessing.html">Multiprocessing best practices</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/randomness.html">Reproducibility</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/serialization.html">Serialization semantics</a></li>
@@ -559,7 +560,9 @@ <h1>All modules for which code is available</h1>
 <li><a href="torch/sparse.html">torch.sparse</a></li>
 <li><a href="torch/storage.html">torch.storage</a></li>
 <li><a href="torch/tensor.html">torch.tensor</a></li>
+<li><a href="torch/utils/benchmark/utils/common.html">torch.utils.benchmark.utils.common</a></li>
 <li><a href="torch/utils/benchmark/utils/timer.html">torch.utils.benchmark.utils.timer</a></li>
+<li><a href="torch/utils/benchmark/utils/valgrind_wrapper/timer_interface.html">torch.utils.benchmark.utils.valgrind_wrapper.timer_interface</a></li>
 <li><a href="torch/utils/checkpoint.html">torch.utils.checkpoint</a></li>
 <li><a href="torch/utils/cpp_extension.html">torch.utils.cpp_extension</a></li>
 <li><a href="torch/utils/data/_utils/worker.html">torch.utils.data._utils.worker</a></li>

docs/master/_modules/torch.html

@@ -187,7 +187,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+4b6fea9 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+a8da1dd &#x25BC</a>
                 </div>
 
 
@@ -233,6 +233,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../notes/extending.html">Extending PyTorch</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/faq.html">Frequently Asked Questions</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../notes/modules.html">Modules</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/multiprocessing.html">Multiprocessing best practices</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/randomness.html">Reproducibility</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../notes/serialization.html">Serialization semantics</a></li>
@@ -654,7 +655,7 @@ <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>
@@ -675,10 +676,10 @@ <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>
 
@@ -706,7 +707,7 @@ <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>
 
 <span class="k">def</span> <span class="nf">use_deterministic_algorithms</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>
@@ -730,6 +731,10 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="sd">        * :class:`torch.nn.ConvTranspose2d` when called on CUDA tensor</span>
 <span class="sd">        * :class:`torch.nn.ConvTranspose3d` when called on CUDA tensor</span>
 <span class="sd">        * :func:`torch.bmm` when called on sparse-dense CUDA tensors</span>
+<span class="sd">        * :func:`torch.__getitem__` backward when `self` is a CPU tensor and</span>
+<span class="sd">          ``indices`` is a list of tensors</span>
+<span class="sd">        * :func:`torch.index_put` with ``accumulate=True`` when called on a CPU</span>
+<span class="sd">          tensor</span>
 
 <span class="sd">    The following normally-nondeterministic operations will throw a</span>
 <span class="sd">    :class:`RuntimeError` when `d=True`:</span>
@@ -957,14 +962,14 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="c1">################################################################################</span>
 
 <span class="c1"># needs to be before the submodule imports to avoid circular dependencies</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>
+<div class="viewcode-block" id="_assert"><a class="viewcode-back" href="../generated/torch._assert.html#torch._assert">[docs]</a><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>
+    <span class="k">assert</span> <span class="n">condition</span><span class="p">,</span> <span class="n">message</span></div>
 
 <span class="c1">################################################################################</span>
 <span class="c1"># Import most common subpackages</span>
@@ -1009,9 +1014,9 @@ <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>
@@ -1039,7 +1044,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 
 <span class="c1"># These were previously defined in native_functions.yaml and appeared on the</span>
 <span class="c1"># `torch` namespace, but we moved them to c10 dispatch to facilitate custom</span>
-<span class="c1"># class usage. We add these lines here to preserve backward compatbility.</span>
+<span class="c1"># class usage. We add these lines here to preserve backward compatibility.</span>
 <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>
 </pre></div>

docs/master/_modules/torch/__config__.html

@@ -187,7 +187,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+4b6fea9 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+a8da1dd &#x25BC</a>
                 </div>
 
 
@@ -233,6 +233,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../notes/extending.html">Extending PyTorch</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/faq.html">Frequently Asked Questions</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notes/modules.html">Modules</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/multiprocessing.html">Multiprocessing best practices</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/randomness.html">Reproducibility</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/serialization.html">Serialization semantics</a></li>

docs/master/_modules/torch/_jit_internal.html

@@ -187,7 +187,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+4b6fea9 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+a8da1dd &#x25BC</a>
                 </div>
 
 
@@ -233,6 +233,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../notes/extending.html">Extending PyTorch</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/faq.html">Frequently Asked Questions</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notes/modules.html">Modules</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/multiprocessing.html">Multiprocessing best practices</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/randomness.html">Reproducibility</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/serialization.html">Serialization semantics</a></li>

docs/master/_modules/torch/_lobpcg.html

@@ -187,7 +187,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+4b6fea9 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+a8da1dd &#x25BC</a>
                 </div>
 
 
@@ -233,6 +233,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../notes/extending.html">Extending PyTorch</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/faq.html">Frequently Asked Questions</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notes/modules.html">Modules</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/multiprocessing.html">Multiprocessing best practices</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/randomness.html">Reproducibility</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/serialization.html">Serialization semantics</a></li>

docs/master/_modules/torch/_lowrank.html

@@ -187,7 +187,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+4b6fea9 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+a8da1dd &#x25BC</a>
                 </div>
 
 
@@ -233,6 +233,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../notes/extending.html">Extending PyTorch</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/faq.html">Frequently Asked Questions</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notes/modules.html">Modules</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/multiprocessing.html">Multiprocessing best practices</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/randomness.html">Reproducibility</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/serialization.html">Serialization semantics</a></li>

docs/master/_modules/torch/_tensor_str.html

@@ -187,7 +187,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+4b6fea9 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+a8da1dd &#x25BC</a>
                 </div>
 
 
@@ -233,6 +233,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../notes/extending.html">Extending PyTorch</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/faq.html">Frequently Asked Questions</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notes/modules.html">Modules</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/multiprocessing.html">Multiprocessing best practices</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/randomness.html">Reproducibility</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/serialization.html">Serialization semantics</a></li>

docs/master/_modules/torch/_utils.html

@@ -187,7 +187,7 @@
 
 
                 <div class="version">
-                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+4b6fea9 &#x25BC</a>
+                  <a href='http://pytorch.org/docs/versions.html'>1.8.0a0+a8da1dd &#x25BC</a>
                 </div>
 
 
@@ -233,6 +233,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../notes/extending.html">Extending PyTorch</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/faq.html">Frequently Asked Questions</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/large_scale_deployments.html">Features for large-scale deployments</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notes/modules.html">Modules</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/multiprocessing.html">Multiprocessing best practices</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/randomness.html">Reproducibility</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../notes/serialization.html">Serialization semantics</a></li>