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Jessica Lin
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Merge pull request pytorch#458 from pytorch/site-v1.6.0
v1.6.0 docs redo for stable (0.7) vision
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‎docs/stable/.buildinfo

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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: 892a2ec27a03fe01b7f360c8920a2882
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tags: 645f666f9bcd5a90fca523b33c5a78b7

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‎docs/stable/_modules/index.html

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@@ -494,7 +494,6 @@ <h1>All modules for which code is available</h1>
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<li><a href="torch/utils/data/distributed.html">torch.utils.data.distributed</a></li>
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<li><a href="torch/utils/data/sampler.html">torch.utils.data.sampler</a></li>
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<li><a href="torch/utils/mobile_optimizer.html">torch.utils.mobile_optimizer</a></li>
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<li><a href="torch/utils/tensorboard/writer.html">torch.utils.tensorboard.writer</a></li>
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</ul><li><a href="torchvision.html">torchvision</a></li>
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<ul><li><a href="torchvision/datasets/celeba.html">torchvision.datasets.celeba</a></li>
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<li><a href="torchvision/datasets/cifar.html">torchvision.datasets.cifar</a></li>

‎docs/stable/_modules/torch.html

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<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>
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<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>
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<span class="k">def</span> <span class="nf">compiled_with_cxx11_abi</span><span class="p">():</span>
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<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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<span class="k">return</span> <span class="n">_C</span><span class="o">.</span><span class="n">_GLIBCXX_USE_CXX11_ABI</span></div>
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<span class="k">return</span> <span class="n">_C</span><span class="o">.</span><span class="n">_GLIBCXX_USE_CXX11_ABI</span>
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<span class="c1"># Import the ops &quot;namespace&quot;</span>

‎docs/stable/_modules/torch/_jit_internal.html

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<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>
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<span class="k">return</span> <span class="n">fn</span></div>
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<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>
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<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>
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<span class="sd">&quot;&quot;&quot;</span>
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<span class="sd"> This decorator indicates to the compiler that a function or method should</span>
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<span class="sd"> be ignored and left as a Python function. This allows you to leave code in</span>
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<span class="k">else</span><span class="p">:</span>
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<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">IGNORE</span>
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<span class="k">return</span> <span class="n">fn</span>
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<span class="k">return</span> <span class="n">decorator</span>
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<span class="k">return</span> <span class="n">decorator</span></div>
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<span class="k">def</span> <span class="nf">_copy_to_script_wrapper</span><span class="p">(</span><span class="n">fn</span><span class="p">):</span>

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