Generate Python docs from pytorch/pytorch@bbaa063

Author: pytorchbot

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@@ -946,6 +946,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
 <span class="sd">          ``mode=&#39;max&#39;``</span>
 <span class="sd">        * :func:`torch.Tensor.put_` when ``accumulate=False``</span>
 <span class="sd">        * :func:`torch.Tensor.put_` when ``accumulate=True`` and called on a CUDA tensor</span>
+<span class="sd">        * :func:`torch.Tensor.scatter` when ``src`` is a tensor and ``reduce=None``</span>
 <span class="sd">        * :func:`torch.histc` when called on a CUDA tensor</span>
 <span class="sd">        * :func:`torch.bincount` when called on a CUDA tensor</span>
 <span class="sd">        * :func:`torch.kthvalue` with called on a CUDA tensor</span>

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@@ -1080,7 +1080,7 @@ <h1>Source code for torch._tensor_str</h1><div class="highlight"><pre>
 
 
 <span class="k">def</span> <span class="nf">_str</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">tensor_contents</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-    <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
+    <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">(),</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">_python_dispatch</span><span class="o">.</span><span class="n">_disable_current_modes</span><span class="p">():</span>
         <span class="n">guard</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_DisableFuncTorch</span><span class="p">()</span>
         <span class="k">return</span> <span class="n">_str_intern</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tensor_contents</span><span class="o">=</span><span class="n">tensor_contents</span><span class="p">)</span>
 </pre></div>

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