Fix page links in index.rst

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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: 7d08e3326f2a56b68e6548b213cdbdf9
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/_sources/index.rst.txt

@@ -3,12 +3,12 @@
 
 **PyTorch 新增教程**
 
-* `使用自定义的 Triton 内核与 torch.compile <https://pytorch.org/tutorials/recipes/torch_compile_user_defined_triton_kernel_tutorial.html>`__
-* `通过区域编译减少 torch.compile 冷启动编译时间 <https://pytorch-cn.org/tutorials/recipes/regional_compilation.html>`__
-* `使用 Tensor Parallel (TP) 进行大规模 Transformer 模型训练 <https://pytorch.org/tutorials/intermediate/TP_tutorial.html>`__
-* `利用半结构化(2:4)稀疏性加速 BERT <https://pytorch.org/tutorials/advanced/semi_structured_sparse.html>`__
-* `torch.export 教程 <https://pytorch.org/tutorials/intermediate/torch_export_tutorial.html>`__
-* `nn.Module 中 load_state_dict 和张量子类的扩展点 <https://pytorch.org/tutorials/recipes/recipes/swap_tensors.html>`__
+* `使用自定义的 Triton 内核与 torch.compile <https://pytorch-cn.com/tutorials/recipes/torch_compile_user_defined_triton_kernel_tutorial.html>`__
+* `通过区域编译减少 torch.compile 冷启动编译时间 <https://pytorch-cn.com/tutorials/recipes/regional_compilation.html>`__
+* `使用 Tensor Parallel (TP) 进行大规模 Transformer 模型训练 <https://pytorch-cn.com/tutorials/intermediate/TP_tutorial.html>`__
+* `利用半结构化(2:4)稀疏性加速 BERT <https://pytorch-cn.com/tutorials/advanced/semi_structured_sparse.html>`__
+* `torch.export 教程 <https://pytorch-cn.com/tutorials/intermediate/torch_export_tutorial.html>`__
+* `nn.Module 中 load_state_dict 和张量子类的扩展点 <https://pytorch-cn.com/tutorials/recipes/recipes/swap_tensors.html>`__
 
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docs/index.html

@@ -595,12 +595,12 @@
 <h1>欢迎来到 PyTorch 教程<a class="headerlink" href="#pytorch" title="Permalink to this heading">¶</a></h1>
 <p><strong>PyTorch 新增教程</strong></p>
 <ul class="simple">
-<li><p><a class="reference external" href="https://pytorch.org/tutorials/recipes/torch_compile_user_defined_triton_kernel_tutorial.html">使用自定义的 Triton 内核与 torch.compile</a></p></li>
-<li><p><a class="reference external" href="https://pytorch-cn.org/tutorials/recipes/regional_compilation.html">通过区域编译减少 torch.compile 冷启动编译时间</a></p></li>
-<li><p><a class="reference external" href="https://pytorch.org/tutorials/intermediate/TP_tutorial.html">使用 Tensor Parallel (TP) 进行大规模 Transformer 模型训练</a></p></li>
-<li><p><a class="reference external" href="https://pytorch.org/tutorials/advanced/semi_structured_sparse.html">利用半结构化(2:4)稀疏性加速 BERT</a></p></li>
-<li><p><a class="reference external" href="https://pytorch.org/tutorials/intermediate/torch_export_tutorial.html">torch.export 教程</a></p></li>
-<li><p><a class="reference external" href="https://pytorch.org/tutorials/recipes/recipes/swap_tensors.html">nn.Module 中 load_state_dict 和张量子类的扩展点</a></p></li>
+<li><p><a class="reference external" href="https://pytorch-cn.com/tutorials/recipes/torch_compile_user_defined_triton_kernel_tutorial.html">使用自定义的 Triton 内核与 torch.compile</a></p></li>
+<li><p><a class="reference external" href="https://pytorch-cn.com/tutorials/recipes/regional_compilation.html">通过区域编译减少 torch.compile 冷启动编译时间</a></p></li>
+<li><p><a class="reference external" href="https://pytorch-cn.com/tutorials/intermediate/TP_tutorial.html">使用 Tensor Parallel (TP) 进行大规模 Transformer 模型训练</a></p></li>
+<li><p><a class="reference external" href="https://pytorch-cn.com/tutorials/advanced/semi_structured_sparse.html">利用半结构化(2:4)稀疏性加速 BERT</a></p></li>
+<li><p><a class="reference external" href="https://pytorch-cn.com/tutorials/intermediate/torch_export_tutorial.html">torch.export 教程</a></p></li>
+<li><p><a class="reference external" href="https://pytorch-cn.com/tutorials/recipes/recipes/swap_tensors.html">nn.Module 中 load_state_dict 和张量子类的扩展点</a></p></li>
 </ul>
 <div class="tutorials-callout-container">
     <div class="row"><p><div class="col-md-6">

index.rst

@@ -3,12 +3,12 @@
 
 **PyTorch 新增教程**
 
-* `使用自定义的 Triton 内核与 torch.compile <https://pytorch.org/tutorials/recipes/torch_compile_user_defined_triton_kernel_tutorial.html>`__
-* `通过区域编译减少 torch.compile 冷启动编译时间 <https://pytorch-cn.org/tutorials/recipes/regional_compilation.html>`__
-* `使用 Tensor Parallel (TP) 进行大规模 Transformer 模型训练 <https://pytorch.org/tutorials/intermediate/TP_tutorial.html>`__
-* `利用半结构化(2:4)稀疏性加速 BERT <https://pytorch.org/tutorials/advanced/semi_structured_sparse.html>`__
-* `torch.export 教程 <https://pytorch.org/tutorials/intermediate/torch_export_tutorial.html>`__
-* `nn.Module 中 load_state_dict 和张量子类的扩展点 <https://pytorch.org/tutorials/recipes/recipes/swap_tensors.html>`__
+* `使用自定义的 Triton 内核与 torch.compile <https://pytorch-cn.com/tutorials/recipes/torch_compile_user_defined_triton_kernel_tutorial.html>`__
+* `通过区域编译减少 torch.compile 冷启动编译时间 <https://pytorch-cn.com/tutorials/recipes/regional_compilation.html>`__
+* `使用 Tensor Parallel (TP) 进行大规模 Transformer 模型训练 <https://pytorch-cn.com/tutorials/intermediate/TP_tutorial.html>`__
+* `利用半结构化(2:4)稀疏性加速 BERT <https://pytorch-cn.com/tutorials/advanced/semi_structured_sparse.html>`__
+* `torch.export 教程 <https://pytorch-cn.com/tutorials/intermediate/torch_export_tutorial.html>`__
+* `nn.Module 中 load_state_dict 和张量子类的扩展点 <https://pytorch-cn.com/tutorials/recipes/recipes/swap_tensors.html>`__
 
 .. raw:: html