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@@ -1058,8 +1058,7 @@ <h1>Source code for torch._dynamo.eval_frame</h1><div class="highlight"><pre>
 
         <span class="k">return</span> <span class="n">result_capturing_wrapper</span>
 
-    <span class="c1"># TODO(voz): Handle kwargs properly?</span>
-    <span class="n">flat_args</span><span class="p">,</span> <span class="n">in_spec</span> <span class="o">=</span> <span class="n">pytree</span><span class="o">.</span><span class="n">tree_flatten</span><span class="p">(</span><span class="n">args</span><span class="p">)</span>
+    <span class="n">flat_args</span><span class="p">,</span> <span class="n">in_spec</span> <span class="o">=</span> <span class="n">pytree</span><span class="o">.</span><span class="n">tree_flatten</span><span class="p">((</span><span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">))</span>
 
     <span class="n">remove_from_cache</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
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@@ -1133,9 +1132,10 @@ <h1>Source code for torch._dynamo.eval_frame</h1><div class="highlight"><pre>
     <span class="p">)</span><span class="o">.</span><span class="n">transform</span><span class="p">()</span>
 
     <span class="c1"># Make dynamo graph to have same input/output spec as user code</span>
+    <span class="n">input_strs</span> <span class="o">=</span> <span class="p">[</span><span class="sa">f</span><span class="s2">&quot;orig_arg_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">&quot;</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">))]</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="n">kwargs</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
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         <span class="n">_PyTreeInfo</span><span class="p">(</span>
-            <span class="p">[</span><span class="sa">f</span><span class="s2">&quot;orig_arg_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">&quot;</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">))],</span>
+            <span class="n">input_strs</span><span class="p">,</span>
             <span class="n">in_spec</span><span class="p">,</span>
             <span class="n">out_spec_traced</span><span class="p">,</span>
         <span class="p">)</span>
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@@ -507,7 +507,6 @@ <h1>Source code for torch.ao.quantization.backend_config.backend_config</h1><div
 <span class="n">EXTRA_INPUTS_GETTER_DICT_KEY</span> <span class="o">=</span> <span class="s2">&quot;extra_inputs_getter&quot;</span>
 <span class="n">NUM_TENSOR_ARGS_TO_OBSERVATION_TYPE_DICT_KEY</span> <span class="o">=</span> <span class="s2">&quot;num_tensor_args_to_observation_type&quot;</span>
 <span class="n">INPUT_TYPE_TO_INDEX_DICT_KEY</span> <span class="o">=</span> <span class="s2">&quot;input_type_to_index&quot;</span>
-<span class="n">INPUT_OUTPUT_OBSERVED_DICT_KEY</span> <span class="o">=</span> <span class="s2">&quot;input_output_observed&quot;</span>
 
 
 <span class="c1"># TODO: maybe rename this to something that&#39;s not related to observer</span>
@@ -527,6 +526,11 @@ <h1>Source code for torch.ao.quantization.backend_config.backend_config</h1><div
     <span class="sd">&quot;&quot;&quot;this means the output will use the same observer instance as input, based</span>
 <span class="sd">    on qconfig.activation</span>
 <span class="sd">    example: torch.cat, maxpool</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+
+    <span class="n">INPUT_OUTPUT_NOT_OBSERVED</span> <span class="o">=</span> <span class="mi">2</span>
+    <span class="sd">&quot;&quot;&quot;this means the input and output are never observed</span>
+<span class="sd">    example: x.shape, x.size</span>
 <span class="sd">    &quot;&quot;&quot;</span></div>
 
 
@@ -883,7 +887,6 @@ <h1>Source code for torch.ao.quantization.backend_config.backend_config</h1><div
         <span class="bp">self</span><span class="o">.</span><span class="n">_extra_inputs_getter</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">_num_tensor_args_to_observation_type</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="n">ObservationType</span><span class="p">]</span> <span class="o">=</span> <span class="p">{}</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">_input_type_to_index</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="p">{}</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_input_output_observed</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">_pattern_complex_format</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Pattern</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
 
     <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
@@ -1024,10 +1027,6 @@ <h1>Source code for torch.ao.quantization.backend_config.backend_config</h1><div
         <span class="bp">self</span><span class="o">.</span><span class="n">_input_type_to_index</span> <span class="o">=</span> <span class="n">input_type_to_index</span>
         <span class="k">return</span> <span class="bp">self</span>
 
-    <span class="k">def</span> <span class="nf">_set_input_output_observed</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">input_output_observed</span><span class="p">:</span> <span class="nb">bool</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">BackendPatternConfig</span><span class="p">:</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_input_output_observed</span> <span class="o">=</span> <span class="n">input_output_observed</span>
-        <span class="k">return</span> <span class="bp">self</span>
-
     <span class="k">def</span> <span class="nf">_set_pattern_complex_format</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pattern</span><span class="p">:</span> <span class="n">Pattern</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">BackendPatternConfig</span><span class="p">:</span>
         <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Set the pattern to configure, using the reversed nested tuple format.</span>
@@ -1086,7 +1085,6 @@ <h1>Source code for torch.ao.quantization.backend_config.backend_config</h1><div
         <span class="n">conf</span><span class="o">.</span><span class="n">_set_num_tensor_args_to_observation_type</span><span class="p">(</span>
             <span class="n">backend_pattern_config_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">NUM_TENSOR_ARGS_TO_OBSERVATION_TYPE_DICT_KEY</span><span class="p">,</span> <span class="p">{}))</span>
         <span class="n">conf</span><span class="o">.</span><span class="n">_set_input_type_to_index</span><span class="p">(</span><span class="n">backend_pattern_config_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">INPUT_TYPE_TO_INDEX_DICT_KEY</span><span class="p">,</span> <span class="p">{}))</span>
-        <span class="n">conf</span><span class="o">.</span><span class="n">_set_input_output_observed</span><span class="p">(</span><span class="n">backend_pattern_config_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">INPUT_OUTPUT_OBSERVED_DICT_KEY</span><span class="p">,</span> <span class="kc">None</span><span class="p">))</span>
         <span class="k">if</span> <span class="n">PATTERN_COMPLEX_FORMAT_DICT_KEY</span> <span class="ow">in</span> <span class="n">backend_pattern_config_dict</span><span class="p">:</span>
             <span class="n">conf</span><span class="o">.</span><span class="n">_set_pattern_complex_format</span><span class="p">(</span><span class="n">backend_pattern_config_dict</span><span class="p">[</span><span class="n">PATTERN_COMPLEX_FORMAT_DICT_KEY</span><span class="p">])</span>
         <span class="k">return</span> <span class="n">conf</span></div>
@@ -1120,8 +1118,6 @@ <h1>Source code for torch.ao.quantization.backend_config.backend_config</h1><div
             <span class="n">backend_pattern_config_dict</span><span class="p">[</span><span class="n">NUM_TENSOR_ARGS_TO_OBSERVATION_TYPE_DICT_KEY</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_num_tensor_args_to_observation_type</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_input_type_to_index</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
             <span class="n">backend_pattern_config_dict</span><span class="p">[</span><span class="n">INPUT_TYPE_TO_INDEX_DICT_KEY</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_input_type_to_index</span>
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_input_output_observed</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">backend_pattern_config_dict</span><span class="p">[</span><span class="n">INPUT_OUTPUT_OBSERVED_DICT_KEY</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_input_output_observed</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pattern_complex_format</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
             <span class="n">backend_pattern_config_dict</span><span class="p">[</span><span class="n">PATTERN_COMPLEX_FORMAT_DICT_KEY</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pattern_complex_format</span>
         <span class="k">return</span> <span class="n">backend_pattern_config_dict</span></div></div>
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@@ -1088,17 +1088,49 @@ <h1>Source code for torch.fx.graph</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">pytree</span><span class="o">.</span><span class="n">tree_unflatten</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">out_spec</span><span class="p">)</span>
 
     <span class="k">def</span> <span class="nf">gen_fn_def</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">free_vars</span><span class="p">,</span> <span class="n">maybe_return_annotation</span><span class="p">):</span>
+        <span class="c1"># Given a user function/model:</span>
+        <span class="c1">#   myargs = [myargs0, myargs1]</span>
+        <span class="c1">#   mykwargs = {&#39;mykwargs0&#39;: ..., &#39;mykwargs1&#39;: ...}</span>
+        <span class="c1">#   def forward(self, mypos, *myargs, mykey=None, **mykwargs):</span>
+        <span class="c1">#</span>
+        <span class="c1"># The generated code flattens all keywords into positional arguments for `forward()`</span>
+        <span class="c1">#   e.g forward(self, mypos, myargs0, myargs1, mykey, mykwargs0, mykwargs1):</span>
+        <span class="c1">#</span>
+        <span class="c1"># Within `forward`, `tree_flatten_spec``still parses args and kwargs separately</span>
+        <span class="c1">#   e.g. tree_flatten_spec(([mypos, myargs0, myargs1],</span>
+        <span class="c1">#                           {&#39;mykey&#39;:mykey, &#39;mykwargs0&#39;:mykwargs0, &#39;mykwargs1&#39;:mykwargs1}),</span>
+        <span class="c1">#                          self._in_spec)</span>
+        <span class="c1">#</span>
+        <span class="c1"># If the user function/model does not have keywords, the dict is suppressed from tree_flatten_spec</span>
+        <span class="c1">#   e.g. tree_flatten_spec([mypos, myargs0, myargs1]), self._in_spec)</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">gen_fn_def</span><span class="p">(</span><span class="n">free_vars</span><span class="p">,</span> <span class="n">maybe_return_annotation</span><span class="p">)</span>
-        <span class="n">function_args</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">orig_args</span>
-        <span class="n">has_orig_self</span> <span class="o">=</span> <span class="p">(</span><span class="n">function_args</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;self&#39;</span><span class="p">)</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">function_args</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="kc">False</span>
+
+        <span class="n">fn_args</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">orig_args</span>
+        <span class="n">has_orig_self</span> <span class="o">=</span> <span class="p">(</span><span class="n">fn_args</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;self&#39;</span><span class="p">)</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">fn_args</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="kc">False</span>
         <span class="k">if</span> <span class="n">has_orig_self</span><span class="p">:</span>
             <span class="n">free_vars</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;self&#39;</span><span class="p">)</span>
-        <span class="n">function_definition</span> <span class="o">=</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">gen_fn_def</span><span class="p">(</span><span class="n">function_args</span><span class="p">[:],</span> <span class="n">maybe_return_annotation</span><span class="p">)</span>
+        <span class="n">fn_definition</span> <span class="o">=</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">gen_fn_def</span><span class="p">(</span><span class="n">fn_args</span><span class="p">[:],</span> <span class="n">maybe_return_annotation</span><span class="p">)</span>
+
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">free_vars</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>  <span class="c1"># pytree has placeholders in it</span>
-            <span class="n">function_definition</span> <span class="o">+=</span> <span class="sa">f</span><span class="s2">&quot;&quot;&quot;</span>
-<span class="s2">    </span><span class="si">{</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">free_vars</span><span class="p">)</span><span class="si">}</span><span class="s2">, = fx_pytree.tree_flatten_spec([</span><span class="si">{</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">function_args</span><span class="p">)</span><span class="si">}</span><span class="s2">], self._in_spec)&quot;&quot;&quot;</span>
-        <span class="k">return</span> <span class="n">function_definition</span>
+            <span class="c1"># when kwargs is present, in_spec is tuple(args, kwargs)</span>
+            <span class="n">has_args_kwargs_tuple</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">in_spec</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="nb">tuple</span> <span class="ow">and</span> \
+                <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">in_spec</span><span class="o">.</span><span class="n">children_specs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">2</span> <span class="ow">and</span> \
+                <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">in_spec</span><span class="o">.</span><span class="n">children_specs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="nb">tuple</span> <span class="ow">and</span> \
+                <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">in_spec</span><span class="o">.</span><span class="n">children_specs</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="nb">dict</span>
+            <span class="n">fn_kwargs</span> <span class="o">=</span> <span class="s1">&#39;</span><span class="si">{}</span><span class="s1">&#39;</span>
+            <span class="n">fn_signature</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;[</span><span class="si">{</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">fn_args</span><span class="p">)</span><span class="si">}</span><span class="s2">], self._in_spec&quot;</span>
+            <span class="k">if</span> <span class="n">has_args_kwargs_tuple</span><span class="p">:</span>
+                <span class="n">count_args</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">in_spec</span><span class="o">.</span><span class="n">children_specs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">children_specs</span><span class="p">)</span>
+                <span class="n">fn_args</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">orig_args</span><span class="p">[:</span><span class="n">count_args</span><span class="p">]</span>
+                <span class="n">fn_kwargs</span> <span class="o">=</span> <span class="s1">&#39;{&#39;</span> <span class="o">+</span> <span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;&#39;</span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2">&#39;:</span><span class="si">{</span><span class="n">v</span><span class="si">}</span><span class="s2">&quot;</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span>
+                                  <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">in_spec</span><span class="o">.</span><span class="n">children_specs</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">context</span><span class="p">,</span>
+                                  <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="o">.</span><span class="n">orig_args</span><span class="p">[</span><span class="n">count_args</span><span class="p">:]))</span> <span class="o">+</span> <span class="s1">&#39;}&#39;</span>
+                <span class="n">fn_signature</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;([</span><span class="si">{</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">fn_args</span><span class="p">)</span><span class="si">}</span><span class="s2">], </span><span class="si">{</span><span class="n">fn_kwargs</span><span class="si">}</span><span class="s2">), self._in_spec&quot;</span>
+
+            <span class="n">fn_definition</span> <span class="o">+=</span> <span class="sa">f</span><span class="s2">&quot;&quot;&quot;</span>
+<span class="s2">    </span><span class="si">{</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">free_vars</span><span class="p">)</span><span class="si">}</span><span class="s2">, = fx_pytree.tree_flatten_spec(</span><span class="si">{</span><span class="n">fn_signature</span><span class="si">}</span><span class="s2">)&quot;&quot;&quot;</span>
+        <span class="k">return</span> <span class="n">fn_definition</span>
 
     <span class="k">def</span> <span class="nf">generate_output</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">output_args</span><span class="p">):</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">pytree_info</span><span class="p">:</span>
diff --git a/docs/master/_modules/torch/fx/graph_module.html b/docs/master/_modules/torch/fx/graph_module.html
index 1f8369f63075..0b8dc2352fb5 100644
--- a/docs/master/_modules/torch/fx/graph_module.html
+++ b/docs/master/_modules/torch/fx/graph_module.html
@@ -235,7 +235,7 @@
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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+gitceb4435 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
     </div>
     
 
@@ -1171,11 +1171,12 @@ <h1>Source code for torch.fx.graph_module</h1><div class="highlight"><pre>
     <span class="c1"># and cause symbolic tracing to occur every time we try to copy the object</span>
     <span class="k">def</span> <span class="nf">__deepcopy__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">memo</span><span class="p">):</span>
         <span class="n">fake_mod</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">()</span>
-        <span class="n">fake_mod</span><span class="o">.</span><span class="vm">__dict__</span> <span class="o">=</span> <span class="n">copy</span><span class="o">.</span><span class="n">deepcopy</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">)</span>
+        <span class="n">fake_mod</span><span class="o">.</span><span class="vm">__dict__</span> <span class="o">=</span> <span class="n">copy</span><span class="o">.</span><span class="n">deepcopy</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">,</span> <span class="n">memo</span><span class="p">)</span>
         <span class="n">res</span> <span class="o">=</span> <span class="n">GraphModule</span><span class="p">(</span><span class="n">fake_mod</span><span class="p">,</span> <span class="n">fake_mod</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">[</span><span class="s1">&#39;_graph&#39;</span><span class="p">])</span>
-        <span class="n">res</span><span class="o">.</span><span class="n">meta</span> <span class="o">=</span> <span class="n">copy</span><span class="o">.</span><span class="n">deepcopy</span><span class="p">(</span><span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;meta&#39;</span><span class="p">,</span> <span class="p">{}))</span>
+        <span class="n">res</span><span class="o">.</span><span class="n">meta</span> <span class="o">=</span> <span class="n">copy</span><span class="o">.</span><span class="n">deepcopy</span><span class="p">(</span><span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;meta&#39;</span><span class="p">,</span> <span class="p">{}),</span> <span class="n">memo</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">res</span>
 
+
     <span class="k">def</span> <span class="nf">__copy__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
         <span class="n">res</span> <span class="o">=</span> <span class="n">GraphModule</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">graph</span><span class="p">)</span>
         <span class="n">res</span><span class="o">.</span><span class="n">meta</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;meta&#39;</span><span class="p">,</span> <span class="p">{})</span>
diff --git a/docs/master/_modules/torch/fx/interpreter.html b/docs/master/_modules/torch/fx/interpreter.html
index b8a292493b55..c34ca2e48a07 100644
--- a/docs/master/_modules/torch/fx/interpreter.html
+++ b/docs/master/_modules/torch/fx/interpreter.html
@@ -235,7 +235,7 @@
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     <div class="version">
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
     </div>
     
 
diff --git a/docs/master/_modules/torch/fx/node.html b/docs/master/_modules/torch/fx/node.html
index fba20564b734..10eaf296c9fa 100644
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+++ b/docs/master/_modules/torch/fx/node.html
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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diff --git a/docs/master/_modules/torch/fx/proxy.html b/docs/master/_modules/torch/fx/proxy.html
index 1e58d3f24eaf..e7d64a395401 100644
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+++ b/docs/master/_modules/torch/fx/proxy.html
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
     </div>
     
 
diff --git a/docs/master/_modules/torch/fx/subgraph_rewriter.html b/docs/master/_modules/torch/fx/subgraph_rewriter.html
index 592c70a4cfe0..a600b18e52ac 100644
--- a/docs/master/_modules/torch/fx/subgraph_rewriter.html
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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diff --git a/docs/master/_modules/torch/hub.html b/docs/master/_modules/torch/hub.html
index d12331c46c42..41eff05551de 100644
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+++ b/docs/master/_modules/torch/hub.html
@@ -235,7 +235,7 @@
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     <div class="version">
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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diff --git a/docs/master/_modules/torch/jit.html b/docs/master/_modules/torch/jit.html
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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+gitceb4435 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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diff --git a/docs/master/_modules/torch/jit/_async.html b/docs/master/_modules/torch/jit/_async.html
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@@ -235,7 +235,7 @@
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     <div class="version">
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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diff --git a/docs/master/_modules/torch/jit/_script.html b/docs/master/_modules/torch/jit/_script.html
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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diff --git a/docs/master/_modules/torch/jit/_serialization.html b/docs/master/_modules/torch/jit/_serialization.html
index 47fe287c72b9..5e28f519f5ca 100644
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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@@ -5328,7 +5328,7 @@ <h1>Source code for torch.nn.functional</h1><div class="highlight"><pre>
 <span class="k">def</span> <span class="nf">_scaled_dot_product_attention</span><span class="p">(</span>
         <span class="n">query</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span>
         <span class="n">key</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span>
-        <span class="n">value</span><span class="p">,</span>
+        <span class="n">value</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span>
         <span class="n">attn_mask</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Tensor</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">dropout_p</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
         <span class="n">need_attn_weights</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
@@ -5336,7 +5336,7 @@ <h1>Source code for torch.nn.functional</h1><div class="highlight"><pre>
     <span class="sa">r</span><span class="sd">&quot;&quot;&quot; TODO This function is for merge purposes only and needs to be removed</span>
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s2">&quot;This function is deprecated please rebuild your models with the public version of sdpa.&quot;</span><span class="p">)</span>
-    <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_nn</span><span class="o">.</span><span class="n">scaled_dot_product_attention</span><span class="p">(</span><span class="n">query</span><span class="p">,</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">attn_mask</span><span class="p">,</span> <span class="n">dropout_p</span><span class="p">,</span> <span class="n">need_attn_weights</span><span class="p">,</span> <span class="n">is_causal</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">_C</span><span class="o">.</span><span class="n">_nn</span><span class="o">.</span><span class="n">_scaled_dot_product_attention</span><span class="p">(</span><span class="n">query</span><span class="p">,</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">attn_mask</span><span class="p">,</span> <span class="n">dropout_p</span><span class="p">,</span> <span class="n">need_attn_weights</span><span class="p">,</span> <span class="n">is_causal</span><span class="p">)</span>
 
 <span class="k">def</span> <span class="nf">_mha_shape_check</span><span class="p">(</span><span class="n">query</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">key</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span>
                      <span class="n">key_padding_mask</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Tensor</span><span class="p">],</span> <span class="n">attn_mask</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Tensor</span><span class="p">],</span> <span class="n">num_heads</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
@@ -5737,7 +5737,7 @@ <h1>Source code for torch.nn.functional</h1><div class="highlight"><pre>
         <span class="n">k</span> <span class="o">=</span> <span class="n">k</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">bsz</span><span class="p">,</span> <span class="n">num_heads</span><span class="p">,</span> <span class="n">src_len</span><span class="p">,</span> <span class="n">head_dim</span><span class="p">)</span>
         <span class="n">v</span> <span class="o">=</span> <span class="n">v</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">bsz</span><span class="p">,</span> <span class="n">num_heads</span><span class="p">,</span> <span class="n">src_len</span><span class="p">,</span> <span class="n">head_dim</span><span class="p">)</span>
 
-        <span class="n">attn_output</span> <span class="o">=</span> <span class="n">scaled_dot_product_attention</span><span class="p">(</span><span class="n">q</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">attn_mask</span><span class="p">,</span> <span class="n">dropout_p</span><span class="p">,</span> <span class="n">is_causal</span><span class="p">)</span>
+        <span class="n">attn_output</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">_scaled_dot_product_attention</span><span class="p">(</span><span class="n">q</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span><span class="p">,</span> <span class="n">attn_mask</span><span class="p">,</span> <span class="n">dropout_p</span><span class="p">,</span> <span class="kc">False</span><span class="p">,</span> <span class="n">is_causal</span><span class="p">)</span>
         <span class="n">attn_output</span> <span class="o">=</span> <span class="n">attn_output</span><span class="o">.</span><span class="n">permute</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span><span class="o">.</span><span class="n">contiguous</span><span class="p">()</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">bsz</span> <span class="o">*</span> <span class="n">tgt_len</span><span class="p">,</span> <span class="n">embed_dim</span><span class="p">)</span>
 
         <span class="n">attn_output</span> <span class="o">=</span> <span class="n">linear</span><span class="p">(</span><span class="n">attn_output</span><span class="p">,</span> <span class="n">out_proj_weight</span><span class="p">,</span> <span class="n">out_proj_bias</span><span class="p">)</span>
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+++ b/docs/master/_sources/notes/autograd.rst.txt
@@ -414,9 +414,10 @@ limit definition of a derivative and generalizes it to operate on
 complex numbers. Consider a function :math:`f: ℂ → ℂ`,
 
     .. math::
-        `f(z=x+yj) = u(x, y) + v(x, y)j`
+        f(z=x+yj) = u(x, y) + v(x, y)j
 
-where :math:`u` and :math:`v` are two variable real valued functions.
+where :math:`u` and :math:`v` are two variable real valued functions
+and :math:`j` is the imaginary unit.
 
 Using the derivative definition, we can write:
 
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@@ -476,6 +476,13 @@ <h1>ObservationType<a class="headerlink" href="#observationtype" title="Permalin
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torch.ao.quantization.backend_config.</span></span><span class="sig-name descname"><span class="pre">ObservationType</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">value</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/ao/quantization/backend_config/backend_config.html#ObservationType"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.ao.quantization.backend_config.ObservationType" title="Permalink to this definition">¶</a></dt>
 <dd><p>An enum that represents different ways of how an operator/operator pattern
 should be observed</p>
+<dl class="py attribute">
+<dt class="sig sig-object py" id="torch.ao.quantization.backend_config.ObservationType.INPUT_OUTPUT_NOT_OBSERVED">
+<span class="sig-name descname"><span class="pre">INPUT_OUTPUT_NOT_OBSERVED</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">2</span></em><a class="headerlink" href="#torch.ao.quantization.backend_config.ObservationType.INPUT_OUTPUT_NOT_OBSERVED" title="Permalink to this definition">¶</a></dt>
+<dd><p>this means the input and output are never observed
+example: x.shape, x.size</p>
+</dd></dl>
+
 <dl class="py attribute">
 <dt class="sig sig-object py" id="torch.ao.quantization.backend_config.ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT">
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diff --git a/docs/master/genindex.html b/docs/master/genindex.html
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diff --git a/docs/master/hub.html b/docs/master/hub.html
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diff --git a/docs/master/index.html b/docs/master/index.html
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diff --git a/docs/master/ir.html b/docs/master/ir.html
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@@ -522,114 +522,120 @@ <h2>Core Aten IR<a class="headerlink" href="#core-aten-ir" title="Permalink to t
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-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">aten.as_strided</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">aten.as_strided</span></code></p></td>
 <td><p>as_strided(Tensor(a) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -&gt; Tensor(a)</p></td>
 </tr>
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 <td><p>asin(Tensor self) -&gt; Tensor</p></td>
 </tr>
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 <td><p>convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -&gt; (Tensor, Tensor, Tensor)</p></td>
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-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">aten.cosh</span></code></p></td>
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 <td><p>cosh(Tensor self) -&gt; Tensor</p></td>
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-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">aten.div.Scalar</span></code></p></td>
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 <td><p>div.Scalar(Tensor self, Scalar other) -&gt; Tensor</p></td>
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@@ -806,10 +806,11 @@ <h3>What are complex derivatives?<a class="headerlink" href="#what-are-complex-d
 complex numbers. Consider a function <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi><mo>:</mo><mi mathvariant="normal">C</mi><mo>→</mo><mi mathvariant="normal">C</mi></mrow><annotation encoding="application/x-tex">f: ℂ → ℂ</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.10764em;">f</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">:</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6889em;"></span><span class="mord amsrm">C</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">→</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6889em;"></span><span class="mord amsrm">C</span></span></span></span></span>,</p>
 <blockquote>
 <div><div class="math">
-<span class="katex-display"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block"><semantics><mrow><mi mathvariant="normal">‘</mi><mi>f</mi><mo stretchy="false">(</mo><mi>z</mi><mo>=</mo><mi>x</mi><mo>+</mo><mi>y</mi><mi>j</mi><mo stretchy="false">)</mo><mo>=</mo><mi>u</mi><mo stretchy="false">(</mo><mi>x</mi><mo separator="true">,</mo><mi>y</mi><mo stretchy="false">)</mo><mo>+</mo><mi>v</mi><mo stretchy="false">(</mo><mi>x</mi><mo separator="true">,</mo><mi>y</mi><mo stretchy="false">)</mo><mi>j</mi><mi mathvariant="normal">‘</mi></mrow><annotation encoding="application/x-tex">`f(z=x+yj) = u(x, y) + v(x, y)j`
+<span class="katex-display"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block"><semantics><mrow><mi>f</mi><mo stretchy="false">(</mo><mi>z</mi><mo>=</mo><mi>x</mi><mo>+</mo><mi>y</mi><mi>j</mi><mo stretchy="false">)</mo><mo>=</mo><mi>u</mi><mo stretchy="false">(</mo><mi>x</mi><mo separator="true">,</mo><mi>y</mi><mo stretchy="false">)</mo><mo>+</mo><mi>v</mi><mo stretchy="false">(</mo><mi>x</mi><mo separator="true">,</mo><mi>y</mi><mo stretchy="false">)</mo><mi>j</mi></mrow><annotation encoding="application/x-tex">f(z=x+yj) = u(x, y) + v(x, y)j
 
-</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord">‘</span><span class="mord mathnormal" style="margin-right:0.10764em;">f</span><span class="mopen">(</span><span class="mord mathnormal" style="margin-right:0.04398em;">z</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6667em;vertical-align:-0.0833em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">y</span><span class="mord mathnormal" style="margin-right:0.05724em;">j</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">u</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">y</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">v</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">y</span><span class="mclose">)</span><span class="mord mathnormal" style="margin-right:0.05724em;">j</span><span class="mord">‘</span></span></span></span></span></div></div></blockquote>
-<p>where <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>u</mi></mrow><annotation encoding="application/x-tex">u</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">u</span></span></span></span></span> and <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi></mrow><annotation encoding="application/x-tex">v</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">v</span></span></span></span></span> are two variable real valued functions.</p>
+</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.10764em;">f</span><span class="mopen">(</span><span class="mord mathnormal" style="margin-right:0.04398em;">z</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6667em;vertical-align:-0.0833em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">y</span><span class="mord mathnormal" style="margin-right:0.05724em;">j</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">u</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">y</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">v</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">y</span><span class="mclose">)</span><span class="mord mathnormal" style="margin-right:0.05724em;">j</span></span></span></span></span></div></div></blockquote>
+<p>where <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>u</mi></mrow><annotation encoding="application/x-tex">u</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">u</span></span></span></span></span> and <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi></mrow><annotation encoding="application/x-tex">v</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal" style="margin-right:0.03588em;">v</span></span></span></span></span> are two variable real valued functions
+and <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>j</mi></mrow><annotation encoding="application/x-tex">j</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.854em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.05724em;">j</span></span></span></span></span> is the imaginary unit.</p>
 <p>Using the derivative definition, we can write:</p>
 <blockquote>
 <div><div class="math">
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diff --git a/docs/master/notes/modules.html b/docs/master/notes/modules.html
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diff --git a/docs/master/notes/mps.html b/docs/master/notes/mps.html
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diff --git a/docs/master/notes/multiprocessing.html b/docs/master/notes/multiprocessing.html
index 46d2f2deff29..6c7ac813ebd1 100644
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diff --git a/docs/master/notes/numerical_accuracy.html b/docs/master/notes/numerical_accuracy.html
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diff --git a/docs/master/notes/randomness.html b/docs/master/notes/randomness.html
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diff --git a/docs/master/notes/serialization.html b/docs/master/notes/serialization.html
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diff --git a/docs/master/notes/windows.html b/docs/master/notes/windows.html
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index 865d3a74d03f..3727c6f6b8af 100644
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diff --git a/docs/master/onnx_diagnostics.html b/docs/master/onnx_diagnostics.html
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diff --git a/docs/master/onnx_supported_aten_ops.html b/docs/master/onnx_supported_aten_ops.html
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     </div>
     
 
@@ -5331,370 +5331,373 @@ <h2>Unsupported operators<a class="headerlink" href="#unsupported-operators" tit
 <tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv1d_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_dilation</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_add</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_dynamic</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_dilation</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_groups</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_output_padding</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_groups</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_padding</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_output_padding</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_prepack</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_padding</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_stride</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_transpose</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_stride</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_unpack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_transpose</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_unpack_sizes</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv2d_unpack_sizes</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_dilation</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_dynamic</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_dilation</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_groups</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_output_padding</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_groups</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_padding</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_output_padding</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_prepack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_padding</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_relu</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_stride</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_relu</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_transpose</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_stride</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_unpack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_transpose</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_prepack</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv3d_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose1d</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose1d_dynamic</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose1d</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose1d_prepack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose1d_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose1d_unpack</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose1d_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose1d_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_dilation</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_dynamic</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_dilation</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_groups</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_output_padding</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_groups</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_padding</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_output_padding</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_prepack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_padding</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_stride</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_transpose</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_stride</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_unpack</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_transpose</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose2d_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_dilation</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_dynamic</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_dilation</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_groups</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_output_padding</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_groups</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_padding</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_output_padding</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_prepack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_padding</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_stride</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_transpose</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_stride</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_unpack</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_transpose</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_unpack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_transpose3d_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::dropout</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::conv_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::elu</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::dropout</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_4bit</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::elu</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_2bit_prepack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_4bit</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_2bit_rowwise_offsets</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_2bit_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_2bit_unpack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_2bit_rowwise_offsets</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_4bit</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_2bit_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_4bit_prepack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_4bit</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_4bit_rowwise_offsets</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_4bit_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_4bit_unpack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_4bit_rowwise_offsets</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_byte</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_4bit_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_byte_prepack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_byte</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_byte_rowwise_offsets</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_byte_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_byte_unpack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_byte_rowwise_offsets</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_prepack</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_byte_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_unpack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_byte</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_bag_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_dynamic</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::embedding_byte</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_dynamic_fp16</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_leaky_relu</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_dynamic_fp16</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_prepack</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_leaky_relu</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_prepack_fp16</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_prepack_fp16_legacy</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_prepack_fp16</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_prepack_legacy</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_prepack_fp16_legacy</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_relu</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_prepack_legacy</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_relu_dynamic</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_relu</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_relu_dynamic_fp16</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_relu_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_tanh</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_relu_dynamic_fp16</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_unpack</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_tanh</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_unpack_fp16</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_with_input_q_dq_qweight_dq_output_fp32</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_unpack_fp16</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_with_input_q_dq_qweight_dq_relu_output_fp32</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_with_input_q_dq_qweight_dq_output_fp32</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::make_quantized_cell_params</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::linear_with_input_q_dq_qweight_dq_relu_output_fp32</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::make_quantized_cell_params_dynamic</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::make_quantized_cell_params</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::make_quantized_cell_params_fp16</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::make_quantized_cell_params_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::matmul</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::make_quantized_cell_params_fp16</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::max_pool1d</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::matmul</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::max_pool2d</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::max_pool1d</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_out</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::max_pool2d</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_relu</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_out</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_relu_out</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_relu</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_scalar</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_relu_out</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_scalar_out</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_scalar</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_scalar_relu</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_scalar_out</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_scalar_relu_out</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_scalar_relu</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::prelu</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::mul_scalar_relu_out</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::quantized_gru_cell_dynamic</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::prelu</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::quantized_lstm_cell_dynamic</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::quantized_gru_cell_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::quantized_rnn_relu_cell_dynamic</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::quantized_lstm_cell_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::quantized_rnn_tanh_cell_dynamic</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::quantized_rnn_relu_cell_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::relu6</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::quantized_rnn_tanh_cell_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::softmax</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::relu6</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::threshold</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::softmax</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">quantized::threshold</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_dynamic</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_prepack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_relu</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_prepack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_relu_dynamic</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_relu</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_unpack</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_relu_dynamic</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::VarTupleUnpack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">sparse::qlinear_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::clamp_nan_to_num</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::VarTupleUnpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::create_owned_ref</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::clamp_nan_to_num</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::dequantize_copy</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::create_owned_ref</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::dict_unpack</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::dequantize_copy</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::embedding_bag</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::dict_unpack</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::expand_dims_copy</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::embedding_bag</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::flatten_copy</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::expand_dims_copy</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::fused_equally_split</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::flatten_copy</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::layer_norm</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::fused_equally_split</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::permute_copy</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::layer_norm</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::reshape_copy</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::permute_copy</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::select_tensor</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::reshape_copy</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::signed_log1p</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::select_tensor</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::to_copy</span></code></p></td>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::signed_log1p</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
-<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::to_maybe_copy_out</span></code></p></td>
+<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::to_copy</span></code></p></td>
+<td><p>Not yet supported</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">static_runtime::to_maybe_copy_out</span></code></p></td>
 <td><p>Not yet supported</p></td>
 </tr>
 </tbody>
diff --git a/docs/master/optim.html b/docs/master/optim.html
index 882a7cb12c42..7d9c960d7dbd 100644
--- a/docs/master/optim.html
+++ b/docs/master/optim.html
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diff --git a/docs/master/package.html b/docs/master/package.html
index c6c7b8d3da00..ee76bf441c5a 100644
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index 862a7fad387d..ead425b5e22c 100644
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diff --git a/docs/master/profiler.html b/docs/master/profiler.html
index 3883fcb733e0..df94ced6fb38 100644
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index 373b162fd616..c275374d1bfe 100644
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index ec25071aa007..78a9bc28849d 100644
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diff --git a/docs/master/quantization-backend-configuration.html b/docs/master/quantization-backend-configuration.html
index 9b44d3fe1c37..38b4dd75c1ff 100644
--- a/docs/master/quantization-backend-configuration.html
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+      <a href='https://pytorch.org/docs/versions.html'>master (2.0.0a0+git1e0c57b ) &#x25BC</a>
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@@ -490,7 +490,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method adaptive_avg_pool1d of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method adaptive_avg_pool1d of type object at 0x7fc46b5cb520&gt;,
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@@ -510,7 +510,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function adaptive_avg_pool2d at 0x7f0f4f18c040&gt;,
+  &#39;pattern&#39;: &lt;function adaptive_avg_pool2d at 0x7fc4197b1040&gt;,
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     {
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@@ -530,7 +530,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function adaptive_avg_pool3d at 0x7f0f4f18c0d0&gt;,
+  &#39;pattern&#39;: &lt;function adaptive_avg_pool3d at 0x7fc4197b10d0&gt;,
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@@ -555,7 +555,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method add of type object at 0x7f0fa0f9c520&gt;,
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@@ -580,7 +580,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method avg_pool1d of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method avg_pool1d of type object at 0x7fc46b5cb520&gt;,
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@@ -641,7 +641,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
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   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvBn1d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7f0f4e350dc0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7fc418978d30&gt;,
 },
 {
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@@ -656,7 +656,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
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-  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7f0f4e350f70&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7fc418978ee0&gt;,
 },
 {
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@@ -684,7 +684,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
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+  &#39;fuser_method&#39;: &lt;function fuse_linear_bn at 0x7fc418978e50&gt;,
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 {
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@@ -698,7 +698,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvBn2d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7f0f4e350dc0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7fc418978d30&gt;,
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 {
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@@ -713,7 +713,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;root_module&#39;: &lt;class &#39;torch.nn.modules.conv.ConvTranspose2d&#39;&gt;,
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-  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7f0f4e350f70&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7fc418978ee0&gt;,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm2d&#39;&gt;,
@@ -737,7 +737,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvBn3d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7f0f4e350dc0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7fc418978d30&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.ConvTranspose3d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm3d&#39;&gt;),
@@ -752,7 +752,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;root_module&#39;: &lt;class &#39;torch.nn.modules.conv.ConvTranspose3d&#39;&gt;,
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.conv.ConvTranspose3d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7f0f4e350f70&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7fc418978ee0&gt;,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm3d&#39;&gt;,
@@ -785,7 +785,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method cat of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method cat of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -795,7 +795,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method clamp of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method clamp of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -854,7 +854,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.conv.Conv1d&#39;&gt;,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method conv1d of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method conv1d of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -896,7 +896,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.conv.Conv2d&#39;&gt;,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method conv2d of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method conv2d of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -938,7 +938,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.conv.Conv3d&#39;&gt;,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method conv3d of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method conv3d of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1266,7 +1266,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function dropout at 0x7f0f4f18c160&gt;,
+  &#39;pattern&#39;: &lt;function dropout at 0x7fc4197b1160&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1286,7 +1286,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function elu at 0x7f0f4f18c790&gt;,
+  &#39;pattern&#39;: &lt;function elu at 0x7fc4197b1790&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1313,7 +1313,6 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;root_module&#39;: &lt;class &#39;torch.nn.modules.sparse.Embedding&#39;&gt;,
   &#39;qat_module&#39;: &lt;class &#39;torch.ao.nn.qat.modules.embedding_ops.Embedding&#39;&gt;,
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.sparse.Embedding&#39;&gt;,
-  &#39;input_output_observed&#39;: False,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.ao.nn.qat.modules.embedding_ops.Embedding&#39;&gt;,
@@ -1332,7 +1331,6 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;root_module&#39;: &lt;class &#39;torch.nn.modules.sparse.Embedding&#39;&gt;,
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.sparse.Embedding&#39;&gt;,
-  &#39;input_output_observed&#39;: False,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.nn.modules.sparse.EmbeddingBag&#39;&gt;,
@@ -1352,7 +1350,6 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;root_module&#39;: &lt;class &#39;torch.nn.modules.sparse.EmbeddingBag&#39;&gt;,
   &#39;qat_module&#39;: &lt;class &#39;torch.ao.nn.qat.modules.embedding_ops.EmbeddingBag&#39;&gt;,
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.sparse.EmbeddingBag&#39;&gt;,
-  &#39;input_output_observed&#39;: False,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.ao.nn.qat.modules.embedding_ops.EmbeddingBag&#39;&gt;,
@@ -1371,10 +1368,9 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;root_module&#39;: &lt;class &#39;torch.nn.modules.sparse.EmbeddingBag&#39;&gt;,
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.sparse.EmbeddingBag&#39;&gt;,
-  &#39;input_output_observed&#39;: False,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method flatten of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method flatten of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1394,7 +1390,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function group_norm at 0x7f0f4f18f670&gt;,
+  &#39;pattern&#39;: &lt;function group_norm at 0x7fc4197b4670&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1459,7 +1455,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function hardsigmoid at 0x7f0f4f18cf70&gt;,
+  &#39;pattern&#39;: &lt;function hardsigmoid at 0x7fc4197b1f70&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=0.00390625, zero_point_exact_match=0),
@@ -1499,7 +1495,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function hardswish at 0x7f0f4f18f160&gt;,
+  &#39;pattern&#39;: &lt;function hardswish at 0x7fc4197b4160&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1519,7 +1515,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function hardtanh at 0x7f0f4f18c670&gt;,
+  &#39;pattern&#39;: &lt;function hardtanh at 0x7fc4197b1670&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1549,7 +1545,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function instance_norm at 0x7f0f4f18f550&gt;,
+  &#39;pattern&#39;: &lt;function instance_norm at 0x7fc4197b4550&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1590,7 +1586,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function interpolate at 0x7f0f4f107820&gt;,
+  &#39;pattern&#39;: &lt;function interpolate at 0x7fc41972c790&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1612,7 +1608,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function layer_norm at 0x7f0f4f18f5e0&gt;,
+  &#39;pattern&#39;: &lt;function layer_norm at 0x7fc4197b45e0&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1635,7 +1631,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function leaky_relu at 0x7f0f4f18c940&gt;,
+  &#39;pattern&#39;: &lt;function leaky_relu at 0x7fc4197b1940&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1887,7 +1883,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.rnn.LSTMCell&#39;&gt;,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method matmul of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method matmul of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1957,7 +1953,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method mean of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method mean of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -1992,7 +1988,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method mul of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method mul of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2038,10 +2034,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvReLU1d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0fa80a3430&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc4726d2430&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv1d&#39;&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv1d&#39;&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2052,10 +2048,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvReLU1d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c85bd30&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e80dc0&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method conv1d of type object at 0x7f0fa0f9c520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv1d of type object at 0x7fc46b5cb520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2067,7 +2063,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method conv1d of type object at 0x7f0fa0f9c520&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv1d of type object at 0x7fc46b5cb520&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2090,10 +2086,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvBnReLU1d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7f0f4e350e50&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fc418978dc0&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv1d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm1d&#39;&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv1d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm1d&#39;&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2105,7 +2101,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;root_module&#39;: &lt;class &#39;torch.nn.modules.conv.Conv1d&#39;&gt;,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvBnReLU1d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7f0f4e350e50&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fc418978dc0&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
@@ -2119,10 +2115,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvReLU2d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c85bdc0&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e80e50&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2133,10 +2129,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvReLU2d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c85be50&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e80ee0&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method conv2d of type object at 0x7f0fa0f9c520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv2d of type object at 0x7fc46b5cb520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2148,7 +2144,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method conv2d of type object at 0x7f0fa0f9c520&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv2d of type object at 0x7fc46b5cb520&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2171,10 +2167,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvBnReLU2d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7f0f4e350e50&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fc418978dc0&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm2d&#39;&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm2d&#39;&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2186,7 +2182,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;root_module&#39;: &lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvBnReLU2d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7f0f4e350e50&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fc418978dc0&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv3d&#39;&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
@@ -2200,10 +2196,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvReLU3d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c85bee0&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e80f70&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv3d&#39;&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv3d&#39;&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2214,10 +2210,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvReLU3d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c85bf70&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e90040&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method conv3d of type object at 0x7f0fa0f9c520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv3d of type object at 0x7fc46b5cb520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2229,7 +2225,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method conv3d of type object at 0x7f0fa0f9c520&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv3d of type object at 0x7fc46b5cb520&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2252,10 +2248,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvBnReLU3d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7f0f4e350e50&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fc418978dc0&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv3d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm3d&#39;&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv3d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm3d&#39;&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2267,7 +2263,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;root_module&#39;: &lt;class &#39;torch.nn.modules.conv.Conv3d&#39;&gt;,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.ConvBnReLU3d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7f0f4e350e50&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fc418978dc0&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.linear.Linear&#39;&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
@@ -2295,10 +2291,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.LinearReLU&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c7ec040&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e900d0&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.linear.Linear&#39;&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.linear.Linear&#39;&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2323,7 +2319,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.LinearReLU&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c7ec0d0&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e90160&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;built-in function linear&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
@@ -2352,7 +2348,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in function linear&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;built-in function linear&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2393,7 +2389,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in function add&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;built-in function add&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2408,7 +2404,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in function add&gt;, &lt;built-in method relu of type object at 0x7f0fa0f9c520&gt;),
+  &#39;pattern&#39;: (&lt;built-in function add&gt;, &lt;built-in method relu of type object at 0x7fc46b5cb520&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2423,7 +2419,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method add of type object at 0x7f0fa0f9c520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
+  &#39;pattern&#39;: (&lt;built-in method add of type object at 0x7fc46b5cb520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2438,7 +2434,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method add of type object at 0x7f0fa0f9c520&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;built-in method add of type object at 0x7fc46b5cb520&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2453,7 +2449,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method add of type object at 0x7f0fa0f9c520&gt;, &lt;built-in method relu of type object at 0x7f0fa0f9c520&gt;),
+  &#39;pattern&#39;: (&lt;built-in method add of type object at 0x7fc46b5cb520&gt;, &lt;built-in method relu of type object at 0x7fc46b5cb520&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2483,7 +2479,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in function mul&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;built-in function mul&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2498,7 +2494,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in function mul&gt;, &lt;built-in method relu of type object at 0x7f0fa0f9c520&gt;),
+  &#39;pattern&#39;: (&lt;built-in function mul&gt;, &lt;built-in method relu of type object at 0x7fc46b5cb520&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2513,7 +2509,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method mul of type object at 0x7f0fa0f9c520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
+  &#39;pattern&#39;: (&lt;built-in method mul of type object at 0x7fc46b5cb520&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2528,7 +2524,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method mul of type object at 0x7f0fa0f9c520&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;built-in method mul of type object at 0x7fc46b5cb520&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2543,7 +2539,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method mul of type object at 0x7f0fa0f9c520&gt;, &lt;built-in method relu of type object at 0x7f0fa0f9c520&gt;),
+  &#39;pattern&#39;: (&lt;built-in method mul of type object at 0x7fc46b5cb520&gt;, &lt;built-in method relu of type object at 0x7fc46b5cb520&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2568,7 +2564,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function relu at 0x7f0f4f18c550&gt;,
+  &#39;pattern&#39;: &lt;function relu at 0x7fc4197b1550&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2607,10 +2603,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.BNReLU2d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c7ec160&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e901f0&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.batchnorm.BatchNorm2d&#39;&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.batchnorm.BatchNorm2d&#39;&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2619,7 +2615,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.BNReLU2d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c7ec1f0&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e90280&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.batchnorm.BatchNorm3d&#39;&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
@@ -2631,10 +2627,10 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.BNReLU3d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c7ec280&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e90310&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.batchnorm.BatchNorm3d&#39;&gt;, &lt;function relu at 0x7f0f4f18c550&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.batchnorm.BatchNorm3d&#39;&gt;, &lt;function relu at 0x7fc4197b1550&gt;),
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2643,7 +2639,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   ],
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
   &#39;fused_module&#39;: &lt;class &#39;torch.ao.nn.intrinsic.modules.fused.BNReLU3d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7f0f4c7ec310&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fc416e903a0&gt;,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.nn.modules.activation.ReLU6&#39;&gt;,
@@ -2656,7 +2652,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;function relu6 at 0x7f0f4f18c700&gt;,
+  &#39;pattern&#39;: &lt;function relu6 at 0x7fc4197b1700&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2676,7 +2672,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method repeat_interleave of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method repeat_interleave of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2745,7 +2741,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
       &#39;output_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
     },
   ],
-  &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
+  &#39;observation_type&#39;: ObservationType.INPUT_OUTPUT_NOT_OBSERVED,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.nn.modules.activation.Sigmoid&#39;&gt;,
@@ -2758,7 +2754,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method sigmoid of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method sigmoid of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=0.00390625, zero_point_exact_match=0),
@@ -2795,7 +2791,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
       &#39;output_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
     },
   ],
-  &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
+  &#39;observation_type&#39;: ObservationType.INPUT_OUTPUT_NOT_OBSERVED,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.nn.modules.activation.Softmax&#39;&gt;,
@@ -2808,7 +2804,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method squeeze of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method squeeze of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2838,7 +2834,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method stack of type object at 0x7f0fa0f9c520&gt;,
+  &#39;pattern&#39;: &lt;built-in method stack of type object at 0x7fc46b5cb520&gt;,
   &#39;dtype_configs&#39;: [
     {
       &#39;input_dtype&#39;: DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exact_match=None),
@@ -2858,7 +2854,7 @@ <h2>Default values for native configurations<a class="headerlink" href="#default
   &#39;observation_type&#39;: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
 },
 {
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1859, 1860], "localhost": [21, 23, 48, 49, 1833, 1852, 1859, 1860], "master_port": [21, 23, 39, 49, 51, 1833, 1852, 1859, 1860], "12355": 21, "init_process_group": [21, 23, 24, 27, 39, 49, 51, 1487, 1832, 1833, 1859], "cleanup": 21, "destroy_process_group": 21, "run_demo": 21, "demo_fn": 21, "mp": [21, 23, 24, 50, 1487, 1806, 1833, 1842, 1854, 1860, 1865, 1866, 1873], "nproc": [21, 23, 46, 1821, 1833, 1860], "demo_seri": 21, "gettempdir": 21, "device_id": [21, 23, 24, 27, 49, 53, 1165, 1251, 1353, 1475, 1487, 1833], "powersgd_st": 21, "lr": [21, 24, 27, 53, 1482, 1487, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1832, 1833, 1840, 1850, 1860, 1868], "001": [21, 813, 814, 1103, 1542, 1546, 1547, 1556, 1560, 1572, 1833, 1847], "comm_hook": 21, "comm_hook_st": 21, "hook_stat": 21, "barrier": [21, 39, 48, 1849], "map_loc": [21, 1098, 1101, 1165, 1487, 1805, 1819, 1851], "n_gpu": 21, "device_count": [21, 23, 1806], "got": [21, 23, 796, 1834], "thank": [21, 29, 1834, 1852], "author": [21, 32, 34, 38, 48, 49, 1035, 1556, 1661, 1798, 1828], "thij": 21, "par": 21, "home": [22, 1832], "brief": [23, 1487, 1821, 1859], "introduct": [23, 29, 905, 1487, 1806, 1808, 1812, 1822, 1830, 1840, 1847, 1859, 1863, 1868], "mpi": [23, 1487], "gloo": [23, 49, 1487, 1833, 1838, 1859], "recv": [23, 1487, 1849, 1860], "broadcast": [23, 27, 29, 33, 53, 58, 75, 174, 374, 376, 378, 486, 488, 490, 538, 657, 658, 659, 660, 661, 662, 663, 669, 789, 826, 831, 834, 838, 839, 840, 841, 865, 884, 962, 963, 968, 973, 1013, 1014, 1015, 1016, 1036, 1038, 1050, 1060, 1118, 1119, 1126, 1139, 1143, 1148, 1149, 1151, 1154, 1162, 1182, 1187, 1188, 1198, 1203, 1206, 1215, 1218, 1249, 1268, 1320, 1393, 1455, 1487, 1492, 1542, 1578, 1586, 1674, 1676, 1752, 1772, 1777, 1801, 1806, 1807, 1811, 1822, 1823, 1824, 1833, 1847, 1849, 1864], "all_reduc": [23, 50, 1487], "all_gath": 23, "scatter": 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25, 39, 61, 1847], "effort": [23, 1859], "socket": [23, 1821, 1859], "nccl_socket_nthread": 23, "nccl_nsocks_perthread": 23, "cloud": [23, 1863, 1868], "aw": [23, 40, 870], "gcp": 23, "primit": [23, 27, 48, 1165, 1807, 1808, 1810, 1812, 1831, 1841, 1847, 1859], "kind": [23, 35, 42, 61, 1113, 1488, 1541, 1588, 1718, 1805, 1815, 1834, 1842, 1847, 1851, 1854, 1864, 1866], "connect": [23, 39, 48, 1242, 1243, 1244, 1245, 1246, 1247, 1290, 1291, 1292, 1293, 1294, 1295, 1342, 1821, 1859], "advantag": [23, 48, 49, 1231, 1275, 1833, 1836, 1859, 1863], "redund": [23, 53, 984, 985, 987, 989, 1003, 1005, 1751], "averag": [23, 27, 736, 737, 738, 739, 822, 824, 870, 1094, 1219, 1220, 1221, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1248, 1250, 1258, 1268, 1274, 1280, 1281, 1282, 1283, 1287, 1288, 1289, 1305, 1306, 1314, 1317, 1318, 1319, 1320, 1321, 1328, 1345, 1346, 1353, 1362, 1370, 1371, 1372, 1378, 1379, 1380, 1383, 1384, 1394, 1408, 1423, 1432, 1433, 1446, 1454, 1487, 1492, 1543, 1544, 1546, 1547, 1548, 1550, 1556, 1557, 1560, 1615, 1616, 1777, 1806, 1833, 1853], "elimin": [23, 34, 61, 583, 1788, 1789, 1844], "thrash": 23, "recurr": [23, 730, 731, 1109, 1237, 1251, 1266, 1267, 1284, 1329, 1499, 1525, 1557, 1806, 1832], "use_distribut": 23, "datetim": [23, 1820], "timedelta": [23, 48, 1820], "1800": 23, "group_nam": [23, 45], "pg_option": 23, "url": [23, 37, 48, 821, 1805, 1819, 1859], "discov": [23, 1859], "encod": [23, 39, 45, 48, 61, 1141, 1165, 1230, 1231, 1357, 1358, 1359, 1360, 1361, 1487, 1737, 1738, 1739, 1741, 1742, 1808, 1811, 1812, 1834, 1845, 1851, 1860, 1863], "ucc": 23, "lowercas": 23, "deadlock": [23, 1487], "job": [23, 39, 41, 42, 44, 45, 47, 48, 49, 50, 1487, 1565, 1571, 1839, 1853, 1868], "exchang": [23, 48, 875, 956, 1832, 1847], "nccl_blocking_wait": 23, "nccl_async_error_handl": [23, 1832], "throw": [23, 24, 33, 34, 38, 53, 60, 61, 168, 300, 305, 517, 587, 1079, 1094, 1134, 1183, 1314, 1487, 1489, 1490, 1525, 1534, 1585, 1791, 1824, 1829, 1844, 1859, 1869], "abort": [23, 1832], "crash": [23, 41, 48, 1821, 1829, 1859, 1861, 1868], "caught": [23, 1487, 1821], "littl": [23, 35, 1834, 1861], "watch": 23, "dog": 23, "deprec": [23, 39, 48, 49, 53, 57, 382, 529, 576, 755, 756, 757, 759, 812, 848, 849, 920, 924, 1040, 1094, 1148, 1151, 1183, 1184, 1230, 1231, 1248, 1250, 1273, 1274, 1280, 1281, 1305, 1306, 1314, 1317, 1318, 1319, 1321, 1328, 1345, 1346, 1362, 1367, 1368, 1383, 1384, 1394, 1423, 1446, 1454, 1479, 1480, 1481, 1483, 1487, 1528, 1529, 1534, 1589, 1620, 1670, 1751, 1755, 1764, 1779, 1806, 1808, 1813, 1821, 1830, 1853, 1865, 1869, 1870], "processgroupopt": 23, "processgroupnccl": [23, 1833], "is_high_priority_stream": 23, "is_initi": [23, 1806], "is_mpi_avail": 23, "is_nccl_avail": 23, "is_gloo_avail": 23, "is_torchelastic_launch": 23, "elast": [23, 40, 41, 42, 43, 44, 45, 46, 47, 48, 50, 51, 1806], "aka": [23, 822, 1275, 1829, 1866], "torchelast": [23, 26, 39, 40, 41, 42, 45, 47, 48, 49, 50, 51], "torchelastic_run_id": 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"brand": 23, "succe": [23, 38, 48, 58, 1832, 1834, 1846], "unexpect": [23, 30, 33, 35, 61, 871, 1019, 1021, 1094, 1314, 1542, 1746, 1808, 1829, 1834, 1843], "unsuccess": 23, "mnt": 23, "sharedfil": 23, "port": [23, 39, 47, 48, 49, 1838], "backend_str": 23, "uppercas": 23, "classmethod": [23, 48, 704, 708, 709, 710, 715, 716, 726, 734, 758, 759, 760, 763, 764, 765, 767, 874, 1257, 1258, 1353, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1540, 1618, 1811, 1812, 1834, 1854, 1859, 1865, 1874], "register_backend": [23, 1859], "func": [23, 56, 58, 61, 797, 799, 803, 804, 805, 806, 807, 808, 809, 810, 811, 813, 814, 1069, 1097, 1109, 1110, 1411, 1529, 1653, 1798, 1806, 1811, 1828, 1859, 1861, 1874], "extended_api": 23, "instanti": [23, 27, 47, 48, 49, 61, 972, 1069, 1258, 1403, 1498, 1522, 1527, 1532, 1635, 1805, 1808, 1810, 1811, 1832, 1834, 1840, 1865], "3rd": [23, 29, 48, 590, 1573, 1830], "processgroup": [23, 25, 27, 53, 1487], "four": [23, 1139, 1243, 1834, 1837, 1859, 1861], "c10d": [23, 39, 47, 49, 51, 1487, 1833, 1849], "distributedbackendopt": 23, "get_backend": [23, 48], "get_rank": [23, 1353], "uniqu": [23, 39, 45, 48, 49, 50, 486, 490, 1085, 1129, 1130, 1134, 1140, 1141, 1143, 1152, 1154, 1156, 1157, 1194, 1201, 1755, 1789, 1805, 1808, 1819, 1834, 1851, 1853, 1859, 1860, 1861, 1863, 1868], "get_world_s": 23, "filestor": [23, 48], "hashstor": 23, "client": [23, 27, 33, 48, 1851], "host_nam": 23, "hostnam": [23, 39, 48, 1853], "listen": 23, "is_mast": 23, "300": [23, 39, 1171, 1231, 1526, 1850], "wait_for_work": 23, "server_stor": 23, "127": [23, 760, 1603, 1604, 1606, 1607, 1625, 1626, 1639, 1640, 1641, 1642, 1643, 1823, 1854, 1868], "1234": [23, 48, 1071], "client_stor": 23, "first_kei": 23, "first_valu": 23, "underli": [23, 25, 27, 29, 35, 39, 58, 61, 75, 288, 303, 353, 376, 378, 447, 448, 449, 450, 457, 472, 493, 496, 529, 530, 531, 586, 718, 727, 783, 874, 1064, 1068, 1094, 1165, 1213, 1454, 1672, 1776, 1790, 1808, 1811, 1824, 1832, 1836, 1838, 1852, 1859, 1867], "hashmap": 23, "file_nam": [23, 1805, 1819, 1851], "store1": 23, "store2": 23, "prefixstor": 23, "old": [23, 30, 35, 61, 767, 1019, 1254, 1539, 1573, 1686, 1804, 1806, 1808, 1829, 1832, 1834, 1846, 1854, 1868], "whose": [23, 29, 38, 53, 61, 516, 800, 848, 865, 956, 968, 973, 1021, 1038, 1047, 1050, 1056, 1094, 1110, 1118, 1164, 1180, 1182, 1215, 1314, 1487, 1535, 1583, 1650, 1706, 1773, 1811, 1829, 1834, 1837, 1851, 1863, 1868, 1870], "quantiti": [23, 54, 59, 1129, 1130, 1157, 1280, 1506, 1507, 1509, 1510, 1512, 1515, 1516, 1517, 1518, 1573, 1837], "compare_set": 23, "arg2": 23, "expected_valu": 23, "desired_valu": 23, "second_valu": 23, "overload": [23, 61, 590, 1810, 1811, 1815], "bad_kei": 23, "num_kei": 23, "written": [23, 34, 38, 41, 58, 821, 929, 1251, 1559, 1808, 1810, 1817, 1818, 1829, 1833, 1834, 1835, 1840, 1845, 1847, 1851, 1865, 1868], "destruct": [23, 1820, 1859, 1861], "delete_kei": 23, "successfulli": [23, 38, 39, 45, 1100, 1699, 1821, 1840, 1845, 1859], "set_timeout": 23, "grain": [23, 1649, 1652, 1829, 1847], "plai": 23, "new_group": [23, 53, 1353], "opaqu": [23, 30, 872, 905, 906, 1019], "pattern": [23, 25, 758, 759, 760, 762, 767, 913, 1251, 1525, 1652, 1733, 1808, 1811, 1829, 1832, 1834, 1836, 1838, 1845, 1855, 1856], "enqueu": [23, 60, 875, 877, 878, 1832, 1860], "get_group_rank": 23, "global_rank": [23, 39], "translat": [23, 35, 63, 64, 1047, 1829, 1861], "queri": [23, 35, 48, 61, 874, 875, 877, 929, 946, 1094, 1314, 1320, 1492, 1500, 1809, 1832, 1851], "get_global_rank": 23, "group_rank": [23, 39, 49], "get_process_group_rank": 23, "dst": [23, 1805, 1851], "destin": [23, 25, 42, 45, 53, 187, 391, 392, 576, 885, 886, 1036, 1094, 1200, 1201, 1314, 1809, 1859, 1860, 1865], "unspecifi": [23, 455, 1347, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1512, 1515, 1516, 1543, 1544, 1545, 1547, 1548, 1550, 1556, 1557, 1558, 1559, 1614, 1615, 1616, 1619, 1734, 1817, 1863, 1868], "sender": [23, 1861], "isend": 23, "irecv": 23, 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[4, 1024, 1129, 1130, 1174, 1764, 1811, 1834, 1845, 1859, 1860], "workload": [4, 9, 20, 23, 53, 916, 1832, 1839, 1843, 1859], "good": [4, 8, 9, 14, 35, 53, 61, 66, 1028, 1322, 1719, 1805, 1815, 1821, 1834, 1839, 1840, 1847, 1851, 1852, 1854], "intrins": [4, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 758, 759, 1855, 1856], "contrast": [4, 29, 39, 1559, 1807, 1827, 1829, 1835, 1863], "blocked_autorang": 4, "callback": [4, 21, 48, 50, 60, 61, 1487, 1820, 1839, 1853, 1859], "min_run_tim": 4, "minimum": [4, 14, 21, 39, 48, 49, 668, 669, 741, 761, 780, 829, 948, 1015, 1054, 1055, 1056, 1196, 1237, 1273, 1363, 1563, 1564, 1571, 1614, 1615, 1616, 1619, 1620, 1719, 1737, 1738, 1739, 1740, 1741, 1742, 1807, 1809, 1827, 1829, 1837, 1848, 1849, 1857, 1866], "At": [4, 6, 7, 8, 15, 20, 32, 33, 35, 38, 1002, 1242, 1243, 1244, 1245, 1246, 1247, 1282, 1283, 1818, 1824, 1831, 1837, 1854, 1859, 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"retain_out_fil": 4, "callgrindstat": 4, "tupl": [4, 6, 14, 20, 25, 35, 39, 45, 46, 48, 53, 61, 296, 419, 421, 423, 470, 493, 509, 532, 556, 557, 558, 667, 668, 669, 736, 737, 738, 739, 742, 743, 744, 749, 755, 756, 757, 759, 765, 766, 767, 783, 784, 791, 792, 793, 794, 795, 797, 806, 807, 808, 809, 810, 811, 812, 813, 814, 817, 818, 819, 841, 869, 883, 884, 887, 898, 916, 922, 947, 948, 966, 969, 971, 985, 987, 988, 990, 991, 993, 994, 995, 997, 998, 1000, 1001, 1003, 1005, 1008, 1018, 1022, 1024, 1026, 1027, 1028, 1029, 1030, 1031, 1033, 1034, 1035, 1039, 1055, 1057, 1094, 1100, 1105, 1109, 1110, 1115, 1124, 1129, 1130, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1146, 1150, 1152, 1153, 1155, 1157, 1160, 1163, 1181, 1183, 1185, 1191, 1193, 1195, 1196, 1199, 1201, 1209, 1212, 1219, 1220, 1221, 1223, 1224, 1225, 1227, 1228, 1229, 1237, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1251, 1261, 1262, 1263, 1282, 1283, 1290, 1291, 1292, 1293, 1294, 1295, 1307, 1308, 1309, 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"world_siz": [20, 21, 23, 24, 27, 39, 48, 49, 51, 53, 1487, 1833, 1852, 1859, 1860], "evenli": [20, 556, 557, 558, 667, 668, 966, 1057, 1164, 1180, 1799], "set_epoch": 20, "is_distribut": [20, 1809, 1849], "start_epoch": 20, "n_epoch": 20, "vanilla": [21, 1817], "allreduc": [21, 23, 1487, 1832, 1833, 1849], "besid": [21, 23, 1832, 1833, 1868], "register_comm_hook": [21, 27, 53, 1487], "mainli": [21, 29, 1237, 1395, 1621, 1872], "bucket": [21, 27, 33, 38, 1222, 1487, 1809, 1833, 1849], "gradbucket": [21, 1487], "flatten": [21, 53, 61, 779, 780, 957, 1056, 1150, 1163, 1365, 1534, 1542, 1590, 1671, 1676, 1681, 1787, 1788, 1789, 1809, 1822, 1823, 1827, 1847, 1849, 1856, 1867], "decompos": [21, 61, 1018, 1025, 1138, 1807, 1829, 1847], "get_per_parameter_tensor": 21, "wise": [21, 23, 29, 659, 660, 670, 728, 740, 741, 750, 754, 789, 864, 968, 973, 1014, 1015, 1037, 1038, 1050, 1059, 1116, 1118, 1175, 1176, 1177, 1178, 1182, 1192, 1195, 1197, 1215, 1236, 1247, 1254, 1256, 1270, 1271, 1272, 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1237, 1326, 1327, 1362, 1363, 1559, 1719, 1756, 1827], "neurip": [21, 29], "2019": [21, 29, 927], "bandwidth": [21, 23, 34, 47, 49, 1854, 1859], "hyperparamet": [21, 61, 1868], "1000": [21, 983, 988, 1014, 1015, 1222, 1257, 1363, 1656, 1683, 1703, 1770, 1829, 1845, 1847, 1868], "min_compression_r": 21, "use_error_feedback": 21, "warm_start": 21, "orthogonalization_epsilon": 21, "random_se": 21, "compression_stats_logging_frequ": 21, "batch_tensors_with_same_shap": 21, "tune": [21, 23, 27, 33, 38, 858, 927, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1556, 1557, 1558, 1559, 1560, 1829, 1832, 1841, 1854], "stronger": 21, "threshold": [21, 61, 858, 1148, 1151, 1275, 1345, 1350, 1468, 1474, 1573, 1703, 1809, 1828, 1832, 1849, 1868], "exponenti": [21, 235, 978, 1145, 1171, 1172, 1173, 1181, 1236, 1256, 1400, 1806, 1811, 1849, 1850, 1864, 1871], "grid": [21, 988, 1195, 1376, 1411, 1807, 1809, 1832, 1868], "satisfactori": 21, "nlp": [21, 33, 1277, 1278, 1279, 1286], "appendix": [21, 1806], "defer": [21, 53, 1832, 1852], "hybrid": [21, 53, 196, 515, 556, 557, 558, 560, 561, 1058], "scheme": [21, 48, 452, 1600, 1613, 1614, 1615, 1616, 1619, 1621, 1840], "sensit": [21, 1275, 1345, 1847, 1851, 1860], "suboptim": [21, 34], "trajectori": 21, "irrecover": 21, "impact": [21, 23, 33, 38, 927, 1698, 1818, 1820, 1829, 1854, 1867], "warm": [21, 27, 33, 916, 1563, 1564, 1832, 1853], "num_row": 21, "num_col": 21, "1e": [21, 61, 91, 321, 666, 684, 685, 686, 687, 688, 689, 695, 696, 706, 707, 719, 721, 722, 723, 724, 725, 813, 814, 849, 850, 1083, 1109, 1110, 1160, 1232, 1233, 1234, 1249, 1268, 1269, 1277, 1278, 1279, 1286, 1287, 1288, 1289, 1296, 1297, 1298, 1300, 1323, 1328, 1353, 1357, 1359, 1361, 1362, 1381, 1393, 1408, 1412, 1413, 1421, 1425, 1447, 1450, 1454, 1476, 1497, 1528, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1556, 1557, 1558, 1560, 1573, 1581, 1699, 1808, 1809, 1834, 1840, 1847, 1850, 1864, 1870], "orthogon": [21, 1130, 1133, 1152, 1157, 1166, 1577, 1589, 1827, 1829, 1840, 1863], "div": [21, 213, 964, 1013, 1016, 1222, 1326, 1327, 1674, 1784, 1807, 1809, 1815, 1822, 1849, 1863, 1866], "0s": [21, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1555, 1556, 1557, 1558, 1559, 1560], "batch": [21, 23, 29, 33, 38, 49, 51, 54, 55, 58, 59, 61, 556, 557, 558, 560, 561, 658, 674, 675, 676, 677, 678, 679, 730, 749, 755, 812, 813, 814, 826, 838, 839, 846, 849, 850, 851, 871, 956, 958, 968, 1029, 1030, 1035, 1123, 1124, 1125, 1126, 1127, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1161, 1162, 1163, 1166, 1174, 1183, 1184, 1188, 1230, 1231, 1232, 1233, 1234, 1237, 1242, 1243, 1248, 1250, 1251, 1253, 1254, 1255, 1257, 1258, 1259, 1261, 1266, 1267, 1268, 1269, 1274, 1275, 1277, 1278, 1279, 1280, 1281, 1284, 1285, 1286, 1287, 1288, 1289, 1296, 1297, 1298, 1305, 1306, 1317, 1318, 1319, 1320, 1321, 1323, 1326, 1327, 1328, 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263, 400, 401, 427, 464, 465, 581, 658, 661, 826, 828, 838, 846, 962, 1114, 1125, 1131, 1132, 1140, 1141, 1183, 1185, 1188, 1198, 1207, 1226, 1252, 1253, 1254, 1255, 1257, 1258, 1259, 1280, 1282, 1283, 1319, 1323, 1325, 1362, 1363, 1377, 1396, 1397, 1398, 1399, 1402, 1403, 1404, 1432, 1433, 1443, 1447, 1450, 1451, 1476, 1493, 1499, 1501, 1507, 1516, 1534, 1559, 1675, 1732, 1807, 1809, 1810, 1828, 1829, 1832, 1837, 1842, 1853, 1863, 1864], "pq": 21, "ps": [21, 1836], "mq": [21, 1854, 1873], "qs": 21, "tp": 21, "speedup": [21, 34, 35, 1320, 1361], "awai": [21, 61, 1411, 1806, 1823, 1829, 1835], "config": [21, 32, 33, 34, 35, 38, 53, 61, 758, 759, 760, 761, 1650, 1652, 1833, 1846, 1857], "comm": [21, 23, 1833], "handler": [21, 23, 41, 42, 1508, 1820, 1839, 1851, 1874], "batched_powersgd_hook": 21, "destroi": [21, 48, 1251, 1829, 1859], "squar": [21, 29, 523, 709, 710, 711, 712, 749, 755, 760, 870, 955, 957, 1091, 1125, 1127, 1129, 1130, 1131, 1134, 1135, 1139, 1141, 1143, 1145, 1147, 1151, 1153, 1154, 1156, 1157, 1161, 1174, 1183, 1220, 1224, 1228, 1229, 1243, 1244, 1246, 1247, 1262, 1263, 1275, 1283, 1305, 1308, 1309, 1312, 1345, 1357, 1378, 1387, 1390, 1406, 1407, 1411, 1420, 1422, 1442, 1464, 1479, 1496, 1544, 1546, 1547, 1548, 1550, 1556, 1557, 1560, 1685, 1744, 1779, 1792, 1809, 1849, 1863], "truncat": [21, 1013, 1785, 1824, 1827, 1836, 1843], "impli": [21, 48, 1821, 1829, 1847, 1852, 1857, 1859], "debugging_hook": 21, "noop_hook": 21, "noop": [21, 1487], "headroom": 21, "desynchron": [21, 23], "trainer": [21, 39, 41, 46, 49, 50, 1487, 1859], "restart": [21, 32, 39, 47, 49, 51, 1563, 1564, 1821, 1868], "__setstate__": 21, "__getstate__": 21, "reload": [21, 27, 1805], "os": [21, 23, 24, 38, 49, 50, 51, 61, 1165, 1487, 1686, 1805, 1821, 1829, 1832, 1833, 1846, 1851, 1852, 1859], "sy": [21, 40, 49, 51, 1805, 1832, 1851], "tempfil": 21, "simplemodel": 21, "24": [21, 23, 29, 32, 831, 1152, 1302, 1376, 1527, 1589, 1772, 1808, 1827, 1831, 1864], "fc2": [21, 1482, 1852], "master_addr": [21, 23, 39, 49, 51, 1833, 1852, 1859, 1860], "localhost": [21, 23, 48, 49, 1833, 1852, 1859, 1860], "master_port": [21, 23, 39, 49, 51, 1833, 1852, 1859, 1860], "12355": 21, "init_process_group": [21, 23, 24, 27, 39, 49, 51, 1487, 1832, 1833, 1859], "cleanup": 21, "destroy_process_group": 21, "run_demo": 21, "demo_fn": 21, "mp": [21, 23, 24, 50, 1487, 1806, 1833, 1842, 1854, 1860, 1865, 1866, 1873], "nproc": [21, 23, 46, 1821, 1833, 1860], "demo_seri": 21, "gettempdir": 21, "device_id": [21, 23, 24, 27, 49, 53, 1165, 1251, 1353, 1475, 1487, 1833], "powersgd_st": 21, "lr": [21, 24, 27, 53, 1482, 1487, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1832, 1833, 1840, 1850, 1860, 1868], "001": [21, 813, 814, 1103, 1542, 1546, 1547, 1556, 1560, 1572, 1833, 1847], "comm_hook": 21, "comm_hook_st": 21, "hook_stat": 21, "barrier": [21, 39, 48, 1849], "map_loc": [21, 1098, 1101, 1165, 1487, 1805, 1819, 1851], "n_gpu": 21, "device_count": [21, 23, 1806], "got": [21, 23, 796, 1834], "thank": [21, 29, 1834, 1852], "author": [21, 32, 34, 38, 48, 49, 1035, 1556, 1661, 1798, 1828], "thij": 21, "par": 21, "home": [22, 1832], "brief": [23, 1487, 1821, 1859], "introduct": [23, 29, 905, 1487, 1806, 1808, 1812, 1822, 1830, 1840, 1847, 1859, 1863, 1868], "mpi": [23, 1487], "gloo": [23, 49, 1487, 1833, 1838, 1859], "recv": [23, 1487, 1849, 1860], "broadcast": [23, 27, 29, 33, 53, 58, 75, 174, 374, 376, 378, 486, 488, 490, 538, 657, 658, 659, 660, 661, 662, 663, 669, 789, 826, 831, 834, 838, 839, 840, 841, 865, 884, 962, 963, 968, 973, 1013, 1014, 1015, 1016, 1036, 1038, 1050, 1060, 1118, 1119, 1126, 1139, 1143, 1148, 1149, 1151, 1154, 1162, 1182, 1187, 1188, 1198, 1203, 1206, 1215, 1218, 1249, 1268, 1320, 1393, 1455, 1487, 1492, 1542, 1578, 1586, 1674, 1676, 1752, 1772, 1777, 1801, 1806, 1807, 1811, 1822, 1823, 1824, 1833, 1847, 1849, 1864], "all_reduc": [23, 50, 1487], "all_gath": 23, "scatter": [23, 27, 53, 486, 488, 490, 1251, 1809, 1836, 1849, 1859], "reduce_scatt": [23, 1849], "all_to_al": 23, "v1": [23, 53, 1162, 1578, 1805, 1833, 1859], "init_method": [23, 1487, 1859], "adher": [23, 1811], "some_fil": 23, "machine_nam": 23, "share_folder_nam": 23, "tcpstore": [23, 48], "past": [23, 34, 61, 929, 946, 1487, 1836], "ask": [23, 57, 58, 1805, 1806, 1835, 1837], "infiniband": [23, 1487, 1859], "interconnect": 23, "gpudirect": 23, "ethernet": 23, "encount": [23, 31, 33, 35, 38, 58, 60, 61, 1487, 1808, 1811, 1813, 1831, 1843, 1851, 1854], "ip": [23, 48], "ib": 23, "upcom": [23, 33, 38, 53, 1828], "nccl_socket_ifnam": 23, "eth0": 23, "gloo_socket_ifnam": 23, "comma": [23, 968, 1811], "eth1": 23, "eth2": 23, "eth3": 23, "imper": 23, "nccl_debug": 23, "info": [23, 32, 33, 38, 39, 42, 46, 797, 874, 875, 877, 1124, 1135, 1137, 1138, 1142, 1155, 1183, 1540, 1806, 1809, 1833, 1834, 1835, 1847, 1851], "nccl_debug_subsi": 23, 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1408, 1423, 1432, 1433, 1446, 1454, 1487, 1492, 1543, 1544, 1546, 1547, 1548, 1550, 1556, 1557, 1560, 1615, 1616, 1777, 1806, 1833, 1853], "elimin": [23, 34, 61, 583, 1788, 1789, 1844], "thrash": 23, "recurr": [23, 730, 731, 1109, 1237, 1251, 1266, 1267, 1284, 1329, 1499, 1525, 1557, 1806, 1832], "use_distribut": 23, "datetim": [23, 1820], "timedelta": [23, 48, 1820], "1800": 23, "group_nam": [23, 45], "pg_option": 23, "url": [23, 37, 48, 821, 1805, 1819, 1859], "discov": [23, 1859], "encod": [23, 39, 45, 48, 61, 1141, 1165, 1230, 1231, 1357, 1358, 1359, 1360, 1361, 1487, 1737, 1738, 1739, 1741, 1742, 1808, 1811, 1812, 1834, 1845, 1851, 1860, 1863], "ucc": 23, "lowercas": 23, "deadlock": [23, 1487], "job": [23, 39, 41, 42, 44, 45, 47, 48, 49, 50, 1487, 1565, 1571, 1839, 1853, 1868], "exchang": [23, 48, 875, 956, 1832, 1847], "nccl_blocking_wait": 23, "nccl_async_error_handl": [23, 1832], "throw": [23, 24, 33, 34, 38, 53, 60, 61, 168, 300, 305, 517, 587, 1079, 1094, 1134, 1183, 1314, 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diff --git a/docs/master/torch.html b/docs/master/torch.html
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@@ -2133,15 +2133,15 @@ <h2>Operator Tags<a class="headerlink" href="#operator-tags" title="Permalink to
 <dt class="sig sig-object py" id="torch.Tag">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">torch.</span></span><span class="sig-name descname"><span class="pre">Tag</span></span><a class="headerlink" href="#torch.Tag" title="Permalink to this definition">¶</a></dt>
 <dd><p>Members:</p>
-<p>generated</p>
-<p>nondeterministic_seeded</p>
 <p>pointwise</p>
-<p>nondeterministic_bitwise</p>
-<p>core</p>
 <p>view_copy</p>
+<p>core</p>
 <p>dynamic_output_shape</p>
+<p>nondeterministic_seeded</p>
 <p>data_dependent_output</p>
+<p>generated</p>
 <p>inplace_view</p>
+<p>nondeterministic_bitwise</p>
 <dl class="py property">
 <dt class="sig sig-object py" id="torch.Tag.name">
 <em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">name</span></span><a class="headerlink" href="#torch.Tag.name" title="Permalink to this definition">¶</a></dt>
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