Generate Python docs from pytorch/pytorch@5cc511f

Author: pytorchbot

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           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.3.0a0+gitcac36e2 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.3.0a0+git5cc511f ) &#x25BC</a>
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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.3.0a0+gitcac36e2 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.3.0a0+git5cc511f ) &#x25BC</a>
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docs/main/_modules/torch.html

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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.3.0a0+gitcac36e2 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.3.0a0+git5cc511f ) &#x25BC</a>
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docs/main/_modules/torch/__config__.html

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+      <a href='https://pytorch.org/docs/versions.html'>main (2.3.0a0+git5cc511f ) &#x25BC</a>
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docs/main/_modules/torch/__future__.html

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docs/main/_modules/torch/_jit_internal.html

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     <div class="version">
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docs/main/_modules/torch/_lobpcg.html

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           <div class="pytorch-left-menu-search">
 
     <div class="version">
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docs/main/_modules/torch/_logging/_internal.html

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           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.3.0a0+gitcac36e2 ) &#x25BC</a>
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@@ -1193,7 +1193,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="o">.</span><span class="n">_typed_storage</span><span class="p">()</span><span class="o">.</span><span class="n">_share_memory_</span><span class="p">()</span>
         <span class="k">return</span> <span class="bp">self</span></div>
 
-<div class="viewcode-block" id="Tensor.module_load"><a class="viewcode-back" href="../../generated/torch.Tensor.module_load.html#torch.Tensor.module_load">[docs]</a>    <span class="k">def</span> <span class="nf">module_load</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
+<div class="viewcode-block" id="Tensor.module_load"><a class="viewcode-back" href="../../generated/torch.Tensor.module_load.html#torch.Tensor.module_load">[docs]</a>    <span class="k">def</span> <span class="nf">module_load</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">assign</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
 <span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Defines how to transform ``other`` when loading it into ``self`` in :meth:`~nn.Module.load_state_dict`.</span>
 
 <span class="sd">        Used when :func:`~torch.__future__.get_swap_module_params_on_conversion` is ``True``.</span>
@@ -1205,16 +1205,23 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
 
 <span class="sd">        .. note::</span>
 <span class="sd">            This method should always return a new object that is not ``self`` or ``other``.</span>
-<span class="sd">            For example, the default implementation returns ``self.copy_(other).detach()``.</span>
+<span class="sd">            For example, the default implementation returns ``self.copy_(other).detach()``</span>
+<span class="sd">            if ``assign`` is ``False`` or ``other.detach()`` if ``assign`` is ``True``.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            other (Tensor): value in state dict with key corresponding to ``self``</span>
+<span class="sd">            assign (bool): the assign argument passed to :meth:`nn.Module.load_state_dict`</span>
 
 <span class="sd">        &quot;&quot;&quot;</span>
         <span class="k">if</span> <span class="n">has_torch_function_variadic</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
-            <span class="k">return</span> <span class="n">handle_torch_function</span><span class="p">(</span><span class="n">Tensor</span><span class="o">.</span><span class="n">module_load</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">),</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span>
-        <span class="c1"># In the default case, swap_tensors becomes a no-op</span>
-        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">copy_</span><span class="p">(</span><span class="n">other</span><span class="p">)</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span></div>
+            <span class="k">return</span> <span class="n">handle_torch_function</span><span class="p">(</span>
+                <span class="n">Tensor</span><span class="o">.</span><span class="n">module_load</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">),</span> <span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">,</span> <span class="n">assign</span><span class="o">=</span><span class="n">assign</span>
+            <span class="p">)</span>
+
+        <span class="k">if</span> <span class="n">assign</span><span class="p">:</span>
+            <span class="k">return</span> <span class="n">other</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">copy_</span><span class="p">(</span><span class="n">other</span><span class="p">)</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span></div>
 
     <span class="k">def</span> <span class="fm">__reversed__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
 <span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Reverses the tensor along dimension 0.&quot;&quot;&quot;</span>