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@@ -983,6 +983,38 @@ <h1>Source code for torch.export.exported_program</h1><div class="highlight"><pr
     <span class="c1"># propagate names to higher order op subgraphs</span>
     <span class="n">_name_hoo_subgraph_placeholders</span><span class="p">(</span><span class="n">gm</span><span class="p">)</span>
 
+    <span class="c1"># Run this pass before creating input/output specs, since size-related CSE/DCE might affect output signature.</span>
+    <span class="c1"># Overwrite output specs afterwards.</span>
+    <span class="kn">from</span> <span class="nn">torch._dynamo</span> <span class="kn">import</span> <span class="n">config</span> <span class="k">as</span> <span class="n">_dynamo_config</span>
+    <span class="kn">from</span> <span class="nn">torch._export.passes._node_metadata_hook</span> <span class="kn">import</span> <span class="p">(</span>
+        <span class="n">_node_metadata_hook</span><span class="p">,</span>
+        <span class="n">_set_node_metadata_hook</span><span class="p">,</span>
+    <span class="p">)</span>
+    <span class="kn">from</span> <span class="nn">torch._functorch._aot_autograd.input_output_analysis</span> <span class="kn">import</span> <span class="n">_graph_output_names</span>
+
+    <span class="k">if</span> <span class="ow">not</span> <span class="n">_dynamo_config</span><span class="o">.</span><span class="n">do_not_emit_runtime_asserts</span><span class="p">:</span>
+        <span class="n">stack_trace</span> <span class="o">=</span> <span class="p">(</span>
+            <span class="s1">&#39;File &quot;torch/fx/passes/runtime_assert.py&quot;, line 24, &#39;</span>
+            <span class="s2">&quot;in insert_deferred_runtime_asserts&quot;</span>
+        <span class="p">)</span>
+        <span class="n">shape_env</span> <span class="o">=</span> <span class="n">_get_shape_env</span><span class="p">(</span><span class="n">gm</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">shape_env</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="k">with</span> <span class="n">_set_node_metadata_hook</span><span class="p">(</span>
+                <span class="n">gm</span><span class="p">,</span> <span class="n">functools</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span><span class="n">_node_metadata_hook</span><span class="p">,</span> <span class="n">stack_trace</span><span class="o">=</span><span class="n">stack_trace</span><span class="p">)</span>
+            <span class="p">):</span>
+                <span class="n">insert_deferred_runtime_asserts</span><span class="p">(</span>
+                    <span class="n">gm</span><span class="p">,</span>
+                    <span class="n">shape_env</span><span class="p">,</span>
+                    <span class="sa">f</span><span class="s2">&quot;exported program: </span><span class="si">{</span><span class="n">first_call_function_nn_module_stack</span><span class="p">(</span><span class="n">gm</span><span class="o">.</span><span class="n">graph</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
+                    <span class="n">export</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+                <span class="p">)</span>
+
+    <span class="c1"># update output specs</span>
+    <span class="n">gm</span><span class="o">.</span><span class="n">recompile</span><span class="p">()</span>
+    <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">_graph_output_names</span><span class="p">(</span><span class="n">gm</span><span class="p">)):</span>
+        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">new_outputs</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">torch</span><span class="o">.</span><span class="n">fx</span><span class="o">.</span><span class="n">Node</span><span class="p">):</span>
+            <span class="n">new_outputs</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">name</span>
+
     <span class="c1"># To match the output target with correct input for input mutations</span>
     <span class="c1"># need to find the old to new placeholder map</span>
     <span class="n">old_new_placeholder_map</span> <span class="o">=</span> <span class="p">{</span>
@@ -1066,12 +1098,6 @@ <h1>Source code for torch.export.exported_program</h1><div class="highlight"><pr
     <span class="n">_preserve_ops</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">_ops</span><span class="o">.</span><span class="n">OpOverload</span><span class="p">],</span>
     <span class="n">joint_loss_index</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">],</span>
 <span class="p">):</span>
-    <span class="kn">from</span> <span class="nn">torch._dynamo</span> <span class="kn">import</span> <span class="n">config</span> <span class="k">as</span> <span class="n">_dynamo_config</span>
-    <span class="kn">from</span> <span class="nn">torch._export.passes._node_metadata_hook</span> <span class="kn">import</span> <span class="p">(</span>
-        <span class="n">_node_metadata_hook</span><span class="p">,</span>
-        <span class="n">_set_node_metadata_hook</span><span class="p">,</span>
-    <span class="p">)</span>
-
     <span class="kn">from</span> <span class="nn">torch._export.passes.lift_constants_pass</span> <span class="kn">import</span> <span class="p">(</span>
         <span class="n">ConstantAttrMap</span><span class="p">,</span>
         <span class="n">lift_constants_pass</span><span class="p">,</span>
@@ -1100,23 +1126,6 @@ <h1>Source code for torch.export.exported_program</h1><div class="highlight"><pr
         <span class="k">assert</span> <span class="n">k</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">ep</span><span class="o">.</span><span class="n">constants</span>
         <span class="n">ep</span><span class="o">.</span><span class="n">constants</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">v</span>
 
-    <span class="k">if</span> <span class="ow">not</span> <span class="n">_dynamo_config</span><span class="o">.</span><span class="n">do_not_emit_runtime_asserts</span><span class="p">:</span>
-        <span class="n">stack_trace</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="s1">&#39;File &quot;torch/fx/passes/runtime_assert.py&quot;, line 24, &#39;</span>
-            <span class="s2">&quot;in insert_deferred_runtime_asserts&quot;</span>
-        <span class="p">)</span>
-        <span class="n">shape_env</span> <span class="o">=</span> <span class="n">_get_shape_env</span><span class="p">(</span><span class="n">gm</span><span class="p">)</span>
-        <span class="k">if</span> <span class="n">shape_env</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="k">with</span> <span class="n">_set_node_metadata_hook</span><span class="p">(</span>
-                <span class="n">gm</span><span class="p">,</span> <span class="n">functools</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span><span class="n">_node_metadata_hook</span><span class="p">,</span> <span class="n">stack_trace</span><span class="o">=</span><span class="n">stack_trace</span><span class="p">)</span>
-            <span class="p">):</span>
-                <span class="n">insert_deferred_runtime_asserts</span><span class="p">(</span>
-                    <span class="n">gm</span><span class="p">,</span>
-                    <span class="n">shape_env</span><span class="p">,</span>
-                    <span class="sa">f</span><span class="s2">&quot;exported program: </span><span class="si">{</span><span class="n">first_call_function_nn_module_stack</span><span class="p">(</span><span class="n">gm</span><span class="o">.</span><span class="n">graph</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-                    <span class="n">export</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
-                <span class="p">)</span>
-
     <span class="n">exported_program</span> <span class="o">=</span> <span class="n">ExportedProgram</span><span class="p">(</span>
         <span class="n">root</span><span class="o">=</span><span class="n">gm</span><span class="p">,</span>
         <span class="n">graph</span><span class="o">=</span><span class="n">gm</span><span class="o">.</span><span class="n">graph</span><span class="p">,</span>
diff --git a/main/_modules/torch/export/graph_signature.html b/main/_modules/torch/export/graph_signature.html
index a83d4e6d8b..52b062f81e 100644
--- a/main/_modules/torch/export/graph_signature.html
+++ b/main/_modules/torch/export/graph_signature.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/export/unflatten.html b/main/_modules/torch/export/unflatten.html
index b8695ca198..8740ee56ca 100644
--- a/main/_modules/torch/export/unflatten.html
+++ b/main/_modules/torch/export/unflatten.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -548,7 +548,6 @@ <h1>Source code for torch.export.unflatten</h1><div class="highlight"><pre>
     <span class="n">TensorArgument</span><span class="p">,</span>
 <span class="p">)</span>
 <span class="kn">from</span> <span class="nn">torch.fx._symbolic_trace</span> <span class="kn">import</span> <span class="n">is_fx_tracing</span>
-<span class="kn">from</span> <span class="nn">torch.fx.experimental.proxy_tensor</span> <span class="kn">import</span> <span class="n">py_sym_types</span>
 <span class="kn">from</span> <span class="nn">torch.utils._pytree</span> <span class="kn">import</span> <span class="n">GetAttrKey</span><span class="p">,</span> <span class="n">SequenceKey</span>
 
 <span class="kn">from</span> <span class="nn">._remove_effect_tokens_pass</span> <span class="kn">import</span> <span class="n">_remove_effect_tokens</span>
@@ -1327,7 +1326,6 @@ <h1>Source code for torch.export.unflatten</h1><div class="highlight"><pre>
         <span class="c1"># To avoid this we copy these call_function nodes with sym_type results.</span>
         <span class="c1"># This should however only be done for sym_type nodes - call_function nodes on tensors</span>
         <span class="c1"># should not be deduplicated in the first place.</span>
-        <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">meta</span><span class="p">[</span><span class="s2">&quot;val&quot;</span><span class="p">],</span> <span class="n">py_sym_types</span><span class="p">)</span>
         <span class="n">args</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">remap_input</span><span class="p">(</span><span class="n">_x</span><span class="p">)</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">_x</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">fx</span><span class="o">.</span><span class="n">Node</span><span class="p">)</span> <span class="k">else</span> <span class="n">_x</span>
             <span class="k">for</span> <span class="n">_x</span> <span class="ow">in</span> <span class="n">x</span><span class="o">.</span><span class="n">args</span>
diff --git a/main/_modules/torch/func.html b/main/_modules/torch/func.html
index cbf5bab14d..99d41a0c84 100644
--- a/main/_modules/torch/func.html
+++ b/main/_modules/torch/func.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/functional.html b/main/_modules/torch/functional.html
index d9f698e72c..183cf0b842 100644
--- a/main/_modules/torch/functional.html
+++ b/main/_modules/torch/functional.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/futures.html b/main/_modules/torch/futures.html
index f2988da0f2..859ec1b6e0 100644
--- a/main/_modules/torch/futures.html
+++ b/main/_modules/torch/futures.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/fx/_symbolic_trace.html b/main/_modules/torch/fx/_symbolic_trace.html
index c9ed789de9..5619ac9bc9 100644
--- a/main/_modules/torch/fx/_symbolic_trace.html
+++ b/main/_modules/torch/fx/_symbolic_trace.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/fx/experimental/symbolic_shapes.html b/main/_modules/torch/fx/experimental/symbolic_shapes.html
index 623ad65c8f..183f85368b 100644
--- a/main/_modules/torch/fx/experimental/symbolic_shapes.html
+++ b/main/_modules/torch/fx/experimental/symbolic_shapes.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/fx/graph.html b/main/_modules/torch/fx/graph.html
index 25cc9e97e8..25021e2f0d 100644
--- a/main/_modules/torch/fx/graph.html
+++ b/main/_modules/torch/fx/graph.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/fx/graph_module.html b/main/_modules/torch/fx/graph_module.html
index 3b7a04c861..ba6171d576 100644
--- a/main/_modules/torch/fx/graph_module.html
+++ b/main/_modules/torch/fx/graph_module.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/fx/interpreter.html b/main/_modules/torch/fx/interpreter.html
index 0c06990170..fbbeff3060 100644
--- a/main/_modules/torch/fx/interpreter.html
+++ b/main/_modules/torch/fx/interpreter.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/fx/node.html b/main/_modules/torch/fx/node.html
index 7fb7962c71..e32941a929 100644
--- a/main/_modules/torch/fx/node.html
+++ b/main/_modules/torch/fx/node.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/fx/proxy.html b/main/_modules/torch/fx/proxy.html
index 929f04f4c8..bff3cd7d9b 100644
--- a/main/_modules/torch/fx/proxy.html
+++ b/main/_modules/torch/fx/proxy.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/fx/subgraph_rewriter.html b/main/_modules/torch/fx/subgraph_rewriter.html
index 862ac01c40..79e4917757 100644
--- a/main/_modules/torch/fx/subgraph_rewriter.html
+++ b/main/_modules/torch/fx/subgraph_rewriter.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/hub.html b/main/_modules/torch/hub.html
index 6b895740ff..c921615ec5 100644
--- a/main/_modules/torch/hub.html
+++ b/main/_modules/torch/hub.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/jit.html b/main/_modules/torch/jit.html
index 947036338f..4572d4c21a 100644
--- a/main/_modules/torch/jit.html
+++ b/main/_modules/torch/jit.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/jit/_async.html b/main/_modules/torch/jit/_async.html
index 6b82a304bf..bedba90275 100644
--- a/main/_modules/torch/jit/_async.html
+++ b/main/_modules/torch/jit/_async.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/jit/_freeze.html b/main/_modules/torch/jit/_freeze.html
index 11b5c52651..ad0fee0c50 100644
--- a/main/_modules/torch/jit/_freeze.html
+++ b/main/_modules/torch/jit/_freeze.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/jit/_fuser.html b/main/_modules/torch/jit/_fuser.html
index 64a62c6739..7e5eeadb74 100644
--- a/main/_modules/torch/jit/_fuser.html
+++ b/main/_modules/torch/jit/_fuser.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/jit/_script.html b/main/_modules/torch/jit/_script.html
index 177762382c..645a53e7c1 100644
--- a/main/_modules/torch/jit/_script.html
+++ b/main/_modules/torch/jit/_script.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/jit/_serialization.html b/main/_modules/torch/jit/_serialization.html
index 25fa1dc70a..5624afc12a 100644
--- a/main/_modules/torch/jit/_serialization.html
+++ b/main/_modules/torch/jit/_serialization.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/jit/_trace.html b/main/_modules/torch/jit/_trace.html
index 523b6c199b..00dcb949a5 100644
--- a/main/_modules/torch/jit/_trace.html
+++ b/main/_modules/torch/jit/_trace.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/library.html b/main/_modules/torch/library.html
index 03fc676475..99ca1b3c1b 100644
--- a/main/_modules/torch/library.html
+++ b/main/_modules/torch/library.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -552,7 +552,6 @@ <h1>Source code for torch.library</h1><div class="highlight"><pre>
     <span class="s2">&quot;fallthrough_kernel&quot;</span><span class="p">,</span>
     <span class="s2">&quot;impl_abstract&quot;</span><span class="p">,</span>
     <span class="s2">&quot;register_fake&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;register_torch_dispatch&quot;</span><span class="p">,</span>
     <span class="s2">&quot;get_ctx&quot;</span><span class="p">,</span>
     <span class="s2">&quot;custom_op&quot;</span><span class="p">,</span>
 <span class="p">]</span>
@@ -706,27 +705,6 @@ <h1>Source code for torch.library</h1><div class="highlight"><pre>
         <span class="n">handle</span> <span class="o">=</span> <span class="n">entry</span><span class="o">.</span><span class="n">fake_impl</span><span class="o">.</span><span class="n">register</span><span class="p">(</span><span class="n">func_to_register</span><span class="p">,</span> <span class="n">source</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">_registration_handles</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span>
 
-    <span class="k">def</span> <span class="nf">_register_torch_dispatch_rule</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">op_name</span><span class="p">,</span> <span class="n">torch_dispatch_class</span><span class="p">,</span> <span class="n">fn</span><span class="p">):</span>
-<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Registers a torch_dispatch rule for the given operator and torch_dispatch_class.</span>
-
-<span class="sd">        This allows for open registration to specify the behavior between the operator</span>
-<span class="sd">        and the torch_dispatch_class without needing to modify the torch_dispatch_class</span>
-<span class="sd">        or the operator directly.</span>
-
-<span class="sd">        The torch_dispatch_class is either a Tensor subclass with `__torch_dispatch__` or a</span>
-<span class="sd">        TorchDispatchMode.</span>
-
-<span class="sd">        If it is a Tensor subclass, we expect fn to have the following signature:</span>
-<span class="sd">        (cls, func: OpOverload, types: Tuple[type, ...], args, kwargs) -&gt; Any</span>
-
-<span class="sd">        If it is a TorchDispatchMode, we expect fn to have the following signature:</span>
-<span class="sd">        (mode, func: OpOverload, types: Tuple[type, ...], args, kwargs) -&gt; Any</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="n">qualname</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">ns</span><span class="si">}</span><span class="s2">::</span><span class="si">{</span><span class="n">op_name</span><span class="si">}</span><span class="s2">&quot;</span>
-        <span class="n">entry</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">_library</span><span class="o">.</span><span class="n">simple_registry</span><span class="o">.</span><span class="n">singleton</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="n">qualname</span><span class="p">)</span>
-        <span class="n">handle</span> <span class="o">=</span> <span class="n">entry</span><span class="o">.</span><span class="n">torch_dispatch_rules</span><span class="o">.</span><span class="n">register</span><span class="p">(</span><span class="n">torch_dispatch_class</span><span class="p">,</span> <span class="n">fn</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_registration_handles</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span>
-
     <span class="k">def</span> <span class="nf">_impl_with_aoti_compile</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">op_name</span><span class="p">,</span> <span class="n">dispatch_key</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">):</span>
 <span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Register the operator to use the AOTI-compiled implementation.</span>
 
@@ -1396,87 +1374,6 @@ <h1>Source code for torch.library</h1><div class="highlight"><pre>
     <span class="n">lib</span><span class="o">.</span><span class="n">impl</span><span class="p">(</span><span class="n">opname</span><span class="p">,</span> <span class="n">autograd_kernel</span><span class="p">,</span> <span class="s2">&quot;Autograd&quot;</span><span class="p">,</span> <span class="n">with_keyset</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
 
 
-<div class="viewcode-block" id="register_torch_dispatch"><a class="viewcode-back" href="../../library.html#torch.library.register_torch_dispatch">[docs]</a><span class="k">def</span> <span class="nf">register_torch_dispatch</span><span class="p">(</span>
-    <span class="n">op</span><span class="p">:</span> <span class="n">_op_identifier</span><span class="p">,</span>
-    <span class="n">torch_dispatch_class</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span>
-    <span class="n">func</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="p">,</span>
-    <span class="o">/</span><span class="p">,</span>
-    <span class="o">*</span><span class="p">,</span>
-    <span class="n">lib</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Library</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-<span class="p">):</span>
-<span class="w">    </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;Registers a torch_dispatch rule for the given operator and ``torch_dispatch_class``.</span>
-
-<span class="sd">    This allows for open registration to specify the behavior between the operator</span>
-<span class="sd">    and the ``torch_dispatch_class`` without needing to modify the ``torch_dispatch_class``</span>
-<span class="sd">    or the operator directly.</span>
-
-<span class="sd">    The ``torch_dispatch_class`` is either a Tensor subclass with ``__torch_dispatch__`` or a</span>
-<span class="sd">    TorchDispatchMode.</span>
-
-<span class="sd">    If it is a Tensor subclass, we expect ``func`` to have the following signature:</span>
-<span class="sd">    ``(cls, func: OpOverload, types: Tuple[type, ...], args, kwargs) -&gt; Any``</span>
-
-<span class="sd">    If it is a TorchDispatchMode, we expect ``func`` to have the following signature:</span>
-<span class="sd">    ``(mode, func: OpOverload, types: Tuple[type, ...], args, kwargs) -&gt; Any``</span>
-
-<span class="sd">    ``args`` and ``kwargs`` will have been normalized the same way they are</span>
-<span class="sd">    in ``__torch_dispatch__`` (see :ref:`torch-dispatch-calling-convention`).</span>
-
-<span class="sd">    Examples:</span>
-
-<span class="sd">        &gt;&gt;&gt; import torch</span>
-<span class="sd">        &gt;&gt;&gt;</span>
-<span class="sd">        &gt;&gt;&gt; @torch.library.custom_op(&quot;mylib::foo&quot;, mutates_args={})</span>
-<span class="sd">        &gt;&gt;&gt; def foo(x: torch.Tensor) -&gt; torch.Tensor:</span>
-<span class="sd">        &gt;&gt;&gt;     return x.clone()</span>
-<span class="sd">        &gt;&gt;&gt;</span>
-<span class="sd">        &gt;&gt;&gt; class MyMode(torch.utils._python_dispatch.TorchDispatchMode):</span>
-<span class="sd">        &gt;&gt;&gt;     def __torch_dispatch__(self, func, types, args=(), kwargs=None):</span>
-<span class="sd">        &gt;&gt;&gt;         return func(*args, **kwargs)</span>
-<span class="sd">        &gt;&gt;&gt;</span>
-<span class="sd">        &gt;&gt;&gt; @torch.library.register_torch_dispatch(&quot;mylib::foo&quot;, MyMode)</span>
-<span class="sd">        &gt;&gt;&gt; def _(mode, func, types, args, kwargs):</span>
-<span class="sd">        &gt;&gt;&gt;     x, = args</span>
-<span class="sd">        &gt;&gt;&gt;     return x + 1</span>
-<span class="sd">        &gt;&gt;&gt;</span>
-<span class="sd">        &gt;&gt;&gt; x = torch.randn(3)</span>
-<span class="sd">        &gt;&gt;&gt; y = foo(x)</span>
-<span class="sd">        &gt;&gt;&gt; assert torch.allclose(y, x)</span>
-<span class="sd">        &gt;&gt;&gt;</span>
-<span class="sd">        &gt;&gt;&gt; with MyMode():</span>
-<span class="sd">        &gt;&gt;&gt;     y = foo(x)</span>
-<span class="sd">        &gt;&gt;&gt; assert torch.allclose(y, x + 1)</span>
-
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span>
-        <span class="n">op</span><span class="p">,</span> <span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">_ops</span><span class="o">.</span><span class="n">OpOverload</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">_library</span><span class="o">.</span><span class="n">custom_ops</span><span class="o">.</span><span class="n">CustomOpDef</span><span class="p">)</span>
-    <span class="p">):</span>
-        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
-            <span class="s2">&quot;register_torch_dispatch(op): got unexpected type for op: {type(op)}&quot;</span>
-        <span class="p">)</span>
-    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">op</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">_ops</span><span class="o">.</span><span class="n">OpOverload</span><span class="p">):</span>
-        <span class="n">op</span> <span class="o">=</span> <span class="n">op</span><span class="o">.</span><span class="n">_name</span>
-    <span class="n">opdef</span> <span class="o">=</span> <span class="n">_maybe_get_opdef</span><span class="p">(</span><span class="n">op</span><span class="p">)</span>
-    <span class="k">if</span> <span class="n">opdef</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">opdef</span><span class="o">.</span><span class="n">register_torch_dispatch</span><span class="p">(</span><span class="n">torch_dispatch_class</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span>
-    <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">op</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span>
-
-    <span class="k">def</span> <span class="nf">register</span><span class="p">(</span><span class="n">func</span><span class="p">):</span>
-        <span class="n">namespace</span><span class="p">,</span> <span class="n">op_name</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">_library</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">parse_namespace</span><span class="p">(</span><span class="n">op</span><span class="p">)</span>
-        <span class="k">if</span> <span class="n">lib</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">use_lib</span> <span class="o">=</span> <span class="n">Library</span><span class="p">(</span><span class="n">namespace</span><span class="p">,</span> <span class="s2">&quot;FRAGMENT&quot;</span><span class="p">)</span>
-            <span class="n">_keep_alive</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">use_lib</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="n">use_lib</span> <span class="o">=</span> <span class="n">lib</span>
-        <span class="n">use_lib</span><span class="o">.</span><span class="n">_register_torch_dispatch_rule</span><span class="p">(</span><span class="n">op_name</span><span class="p">,</span> <span class="n">torch_dispatch_class</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span>
-        <span class="k">return</span> <span class="n">func</span>
-
-    <span class="k">if</span> <span class="n">func</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">register</span>
-    <span class="k">else</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">register</span><span class="p">(</span><span class="n">func</span><span class="p">)</span></div>
-
-
 <span class="c1"># If the op was defined in C++, then we want to make sure there was an</span>
 <span class="c1"># m.set_python_module(module, ...) call and that the module is the</span>
 <span class="c1"># same as the module that called torch.library.register_fake.</span>
diff --git a/main/_modules/torch/monitor.html b/main/_modules/torch/monitor.html
index 56a2ee75e3..ca93af9420 100644
--- a/main/_modules/torch/monitor.html
+++ b/main/_modules/torch/monitor.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/mps.html b/main/_modules/torch/mps.html
index 0b59578865..272da62938 100644
--- a/main/_modules/torch/mps.html
+++ b/main/_modules/torch/mps.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/mps/event.html b/main/_modules/torch/mps/event.html
index f044309176..e2cb08f95e 100644
--- a/main/_modules/torch/mps/event.html
+++ b/main/_modules/torch/mps/event.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/mps/profiler.html b/main/_modules/torch/mps/profiler.html
index 4e415bafe1..f96d568229 100644
--- a/main/_modules/torch/mps/profiler.html
+++ b/main/_modules/torch/mps/profiler.html
@@ -280,7 +280,7 @@
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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/mtia.html b/main/_modules/torch/mtia.html
index 691c0f0dc5..8ef789747f 100644
--- a/main/_modules/torch/mtia.html
+++ b/main/_modules/torch/mtia.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/multiprocessing.html b/main/_modules/torch/multiprocessing.html
index 52f5b0193f..19b4fa743a 100644
--- a/main/_modules/torch/multiprocessing.html
+++ b/main/_modules/torch/multiprocessing.html
@@ -280,7 +280,7 @@
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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/multiprocessing/spawn.html b/main/_modules/torch/multiprocessing/spawn.html
index a363a64c0e..e2cc5703c3 100644
--- a/main/_modules/torch/multiprocessing/spawn.html
+++ b/main/_modules/torch/multiprocessing/spawn.html
@@ -280,7 +280,7 @@
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/nested.html b/main/_modules/torch/nested.html
index cb506a1659..9120dcc30a 100644
--- a/main/_modules/torch/nested.html
+++ b/main/_modules/torch/nested.html
@@ -280,7 +280,7 @@
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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/nn/attention.html b/main/_modules/torch/nn/attention.html
index 36f57841cc..4529ef92eb 100644
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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index d171c0316e..1f21a051b3 100644
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index 8840d57467..1c6457f570 100644
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index 6db29c98fc..a8f1c88f57 100644
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@@ -280,7 +280,7 @@
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/nn/modules/activation.html b/main/_modules/torch/nn/modules/activation.html
index f1390c1a03..6388ea6fd7 100644
--- a/main/_modules/torch/nn/modules/activation.html
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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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index aee3dd121c..5597458572 100644
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index d1f5c534b9..dd632f2427 100644
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
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index 3b58f27036..d1cd81b68c 100644
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@@ -581,7 +581,7 @@ <h1>Source code for torch.nn.modules.sparse</h1><div class="highlight"><pre>
 <span class="sd">        :attr:`max_norm` is not ``None``. For example::</span>
 
 <span class="sd">            n, d, m = 3, 5, 7</span>
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 <span class="sd">            idx = torch.tensor([1, 2])</span>
 <span class="sd">            a = embedding.weight.clone() @ W.t()  # weight must be cloned for this to be differentiable</span>
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diff --git a/main/_modules/torch/nn/utils/weight_norm.html b/main/_modules/torch/nn/utils/weight_norm.html
index be84264dd1..dec320adda 100644
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+++ b/main/_modules/torch/nn/utils/weight_norm.html
@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/onnx.html b/main/_modules/torch/onnx.html
index f9430c22c8..415d13df34 100644
--- a/main/_modules/torch/onnx.html
+++ b/main/_modules/torch/onnx.html
@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/onnx/_internal/exporter.html b/main/_modules/torch/onnx/_internal/exporter.html
index 84461c47a2..bf3e073138 100644
--- a/main/_modules/torch/onnx/_internal/exporter.html
+++ b/main/_modules/torch/onnx/_internal/exporter.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -2028,12 +2028,15 @@ <h1>Source code for torch.onnx._internal.exporter</h1><div class="highlight"><pr
     <span class="n">_assert_dependencies</span><span class="p">(</span><span class="n">resolved_export_options</span><span class="p">)</span>
 
     <span class="k">try</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">Exporter</span><span class="p">(</span>
-            <span class="n">options</span><span class="o">=</span><span class="n">resolved_export_options</span><span class="p">,</span>
-            <span class="n">model</span><span class="o">=</span><span class="n">model</span><span class="p">,</span>
-            <span class="n">model_args</span><span class="o">=</span><span class="n">model_args</span><span class="p">,</span>
-            <span class="n">model_kwargs</span><span class="o">=</span><span class="n">model_kwargs</span><span class="p">,</span>
-        <span class="p">)</span><span class="o">.</span><span class="n">export</span><span class="p">()</span>
+        <span class="kn">from</span> <span class="nn">torch._dynamo</span> <span class="kn">import</span> <span class="n">config</span> <span class="k">as</span> <span class="n">_dynamo_config</span>
+
+        <span class="k">with</span> <span class="n">_dynamo_config</span><span class="o">.</span><span class="n">patch</span><span class="p">(</span><span class="n">do_not_emit_runtime_asserts</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
+            <span class="k">return</span> <span class="n">Exporter</span><span class="p">(</span>
+                <span class="n">options</span><span class="o">=</span><span class="n">resolved_export_options</span><span class="p">,</span>
+                <span class="n">model</span><span class="o">=</span><span class="n">model</span><span class="p">,</span>
+                <span class="n">model_args</span><span class="o">=</span><span class="n">model_args</span><span class="p">,</span>
+                <span class="n">model_kwargs</span><span class="o">=</span><span class="n">model_kwargs</span><span class="p">,</span>
+            <span class="p">)</span><span class="o">.</span><span class="n">export</span><span class="p">()</span>
     <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
         <span class="n">sarif_report_path</span> <span class="o">=</span> <span class="n">_DEFAULT_FAILED_EXPORT_SARIF_LOG_PATH</span>
         <span class="n">resolved_export_options</span><span class="o">.</span><span class="n">diagnostic_context</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">sarif_report_path</span><span class="p">)</span>
diff --git a/main/_modules/torch/onnx/_type_utils.html b/main/_modules/torch/onnx/_type_utils.html
index 993f3208c9..95191a554c 100644
--- a/main/_modules/torch/onnx/_type_utils.html
+++ b/main/_modules/torch/onnx/_type_utils.html
@@ -280,7 +280,7 @@
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/_modules/torch/onnx/utils.html b/main/_modules/torch/onnx/utils.html
index 3af155984e..6e8a106889 100644
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@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/onnx/verification.html b/main/_modules/torch/onnx/verification.html
index c2899742ec..54c1e770f5 100644
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+++ b/main/_modules/torch/onnx/verification.html
@@ -280,7 +280,7 @@
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index 5c0f583e61..c4a2ed139e 100644
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@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/optim/adagrad.html b/main/_modules/torch/optim/adagrad.html
index 5607257d3e..ac4e2d687d 100644
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@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/optim/adam.html b/main/_modules/torch/optim/adam.html
index 5f64156e5b..a59da02a3e 100644
--- a/main/_modules/torch/optim/adam.html
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@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/optim/adamax.html b/main/_modules/torch/optim/adamax.html
index 8b21094c16..3b2b0b9e53 100644
--- a/main/_modules/torch/optim/adamax.html
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@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/optim/adamw.html b/main/_modules/torch/optim/adamw.html
index ed1551f5cd..4f23c384f4 100644
--- a/main/_modules/torch/optim/adamw.html
+++ b/main/_modules/torch/optim/adamw.html
@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/optim/asgd.html b/main/_modules/torch/optim/asgd.html
index a8446080d7..2a3b9d5a85 100644
--- a/main/_modules/torch/optim/asgd.html
+++ b/main/_modules/torch/optim/asgd.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/optim/lbfgs.html b/main/_modules/torch/optim/lbfgs.html
index 8d43efba7b..b76f0b9356 100644
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+++ b/main/_modules/torch/optim/lbfgs.html
@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/optim/lr_scheduler.html b/main/_modules/torch/optim/lr_scheduler.html
index 56ed470c5a..a7420ea0d6 100644
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@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/optim/nadam.html b/main/_modules/torch/optim/nadam.html
index b12952ed4a..1d7ffba961 100644
--- a/main/_modules/torch/optim/nadam.html
+++ b/main/_modules/torch/optim/nadam.html
@@ -280,7 +280,7 @@
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     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/optim/optimizer.html b/main/_modules/torch/optim/optimizer.html
index 73eded70fb..bf2ca7c092 100644
--- a/main/_modules/torch/optim/optimizer.html
+++ b/main/_modules/torch/optim/optimizer.html
@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/optim/radam.html b/main/_modules/torch/optim/radam.html
index 42ccbd0e4a..01b80e1b2d 100644
--- a/main/_modules/torch/optim/radam.html
+++ b/main/_modules/torch/optim/radam.html
@@ -280,7 +280,7 @@
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
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diff --git a/main/_modules/torch/optim/rmsprop.html b/main/_modules/torch/optim/rmsprop.html
index 03c17709ca..f27e98796f 100644
--- a/main/_modules/torch/optim/rmsprop.html
+++ b/main/_modules/torch/optim/rmsprop.html
@@ -280,7 +280,7 @@
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
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diff --git a/main/_modules/torch/optim/rprop.html b/main/_modules/torch/optim/rprop.html
index 59367211cf..6839ba4646 100644
--- a/main/_modules/torch/optim/rprop.html
+++ b/main/_modules/torch/optim/rprop.html
@@ -280,7 +280,7 @@
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
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diff --git a/main/_modules/torch/optim/sgd.html b/main/_modules/torch/optim/sgd.html
index 50d806f4ed..689bc7b8a4 100644
--- a/main/_modules/torch/optim/sgd.html
+++ b/main/_modules/torch/optim/sgd.html
@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/optim/sparse_adam.html b/main/_modules/torch/optim/sparse_adam.html
index 64c414d51e..7eb04f9fee 100644
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diff --git a/main/_modules/torch/overrides.html b/main/_modules/torch/overrides.html
index e9173ea359..6bcd45b77c 100644
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@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/package/file_structure_representation.html b/main/_modules/torch/package/file_structure_representation.html
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diff --git a/main/_modules/torch/package/package_exporter.html b/main/_modules/torch/package/package_exporter.html
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diff --git a/main/_modules/torch/package/package_importer.html b/main/_modules/torch/package/package_importer.html
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diff --git a/main/_modules/torch/profiler/itt.html b/main/_modules/torch/profiler/itt.html
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+++ b/main/_modules/torch/sparse.html
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@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/utils/benchmark/utils/valgrind_wrapper/timer_interface.html b/main/_modules/torch/utils/benchmark/utils/valgrind_wrapper/timer_interface.html
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@@ -280,7 +280,7 @@
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@@ -280,7 +280,7 @@
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@@ -280,7 +280,7 @@
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@@ -280,7 +280,7 @@
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@@ -280,7 +280,7 @@
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+++ b/main/_modules/torch/utils/data/_utils/worker.html
@@ -280,7 +280,7 @@
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@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/utils/data/dataset.html b/main/_modules/torch/utils/data/dataset.html
index fcfaf17f86..7ab76c3122 100644
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+++ b/main/_modules/torch/utils/data/dataset.html
@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/utils/data/distributed.html b/main/_modules/torch/utils/data/distributed.html
index 618ba72ff6..342e4c4b97 100644
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@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/utils/data/sampler.html b/main/_modules/torch/utils/data/sampler.html
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@@ -280,7 +280,7 @@
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diff --git a/main/_modules/torch/utils/dlpack.html b/main/_modules/torch/utils/dlpack.html
index ec81d7deb7..3901d947ce 100644
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@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/utils/mobile_optimizer.html b/main/_modules/torch/utils/mobile_optimizer.html
index 93b5d3c214..9a29d3de53 100644
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@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/utils/module_tracker.html b/main/_modules/torch/utils/module_tracker.html
index 994263d84d..4e61fa7f12 100644
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+++ b/main/_modules/torch/utils/module_tracker.html
@@ -280,7 +280,7 @@
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/utils/tensorboard/writer.html b/main/_modules/torch/utils/tensorboard/writer.html
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+++ b/main/_modules/torch/utils/tensorboard/writer.html
@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/xpu.html b/main/_modules/torch/xpu.html
index 52f3656d9d..6818952bde 100644
--- a/main/_modules/torch/xpu.html
+++ b/main/_modules/torch/xpu.html
@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/xpu/random.html b/main/_modules/torch/xpu/random.html
index fed6b8fab1..f93efbf017 100644
--- a/main/_modules/torch/xpu/random.html
+++ b/main/_modules/torch/xpu/random.html
@@ -280,7 +280,7 @@
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+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/torch/xpu/streams.html b/main/_modules/torch/xpu/streams.html
index c7b661fe7b..27cd6be76a 100644
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+++ b/main/_modules/torch/xpu/streams.html
@@ -280,7 +280,7 @@
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-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_modules/typing.html b/main/_modules/typing.html
index 94536ec696..a5757ef48b 100644
--- a/main/_modules/typing.html
+++ b/main/_modules/typing.html
@@ -280,7 +280,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
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diff --git a/main/_sources/generated/exportdb/index.rst.txt b/main/_sources/generated/exportdb/index.rst.txt
index aef9bb4a77..bad823f600 100644
--- a/main/_sources/generated/exportdb/index.rst.txt
+++ b/main/_sources/generated/exportdb/index.rst.txt
@@ -19,8 +19,8 @@ support in export please create an issue in the pytorch/pytorch repo wih a modul
     :caption: Tags
 
     torch.escape-hatch
-    torch.cond
     torch.dynamic-shape
+    torch.cond
     python.closure
     torch.dynamic-value
     python.data-structure
@@ -219,7 +219,7 @@ cond_branch_class_method
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -311,7 +311,7 @@ cond_branch_nested_function
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -400,7 +400,7 @@ cond_branch_nonlocal_variables
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -586,7 +586,7 @@ cond_operands
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -641,9 +641,11 @@ Result:
     ExportedProgram:
         class GraphModule(torch.nn.Module):
             def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
+                 # 
+                sym_size_int_1: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 0)
+                
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_higher_order_ops/cond.py:108 in cond, code: return cond_op(pred, true_fn, false_fn, operands)
-                sym_size_int: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 0)
-                gt: "Sym(s0 > 2)" = sym_size_int > 2;  sym_size_int = None
+                gt: "Sym(s0 > 2)" = sym_size_int_1 > 2;  sym_size_int_1 = None
                 true_graph_0 = self.true_graph_0
                 false_graph_0 = self.false_graph_0
                 conditional = torch.ops.higher_order.cond(gt, true_graph_0, false_graph_0, [x, y]);  gt = true_graph_0 = false_graph_0 = x = y = None
@@ -672,7 +674,7 @@ cond_predicate
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -745,7 +747,7 @@ constrain_as_size_example
 
 .. note::
 
-    Tags: :doc:`torch.escape-hatch <torch.escape-hatch>`, :doc:`torch.dynamic-value <torch.dynamic-value>`
+    Tags: :doc:`torch.dynamic-value <torch.dynamic-value>`, :doc:`torch.escape-hatch <torch.escape-hatch>`
 
     Support Level: SUPPORTED
 
@@ -794,13 +796,10 @@ Result:
                 
                  # 
                 sym_constrain_range_for_size_default = torch.ops.aten.sym_constrain_range_for_size.default(item)
-                
-                # No stacktrace found for following nodes
-                sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-                ge: "Sym(u0 >= 0)" = item >= 0
-                _assert_scalar = torch.ops.aten._assert_scalar.default(ge, "Runtime assertion failed for expression 0 <= u0 on node 'ge'");  ge = None
-                le: "Sym(u0 <= 5)" = item <= 5
-                _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le = None
+                ge_1: "Sym(u0 >= 0)" = item >= 0
+                _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, "Runtime assertion failed for expression u0 >= 0 on node 'ge_1'");  ge_1 = None
+                le_1: "Sym(u0 <= 5)" = item <= 5
+                _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le_1 = None
                 
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_size_example.py:17 in forward, code: return torch.zeros((a, 5))
                 zeros: "f32[u0, 5]" = torch.ops.aten.zeros.default([item, 5], device = device(type='cpu'), pin_memory = False);  item = None
@@ -816,7 +815,7 @@ constrain_as_value_example
 
 .. note::
 
-    Tags: :doc:`torch.escape-hatch <torch.escape-hatch>`, :doc:`torch.dynamic-value <torch.dynamic-value>`
+    Tags: :doc:`torch.dynamic-value <torch.dynamic-value>`, :doc:`torch.escape-hatch <torch.escape-hatch>`
 
     Support Level: SUPPORTED
 
@@ -866,12 +865,11 @@ Result:
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:14 in forward, code: a = x.item()
                 item: "Sym(u0)" = torch.ops.aten.item.default(x);  x = None
                 
-                # No stacktrace found for following nodes
-                sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-                ge: "Sym(u0 >= 0)" = item >= 0
-                _assert_scalar = torch.ops.aten._assert_scalar.default(ge, "Runtime assertion failed for expression 0 <= u0 on node 'ge_1'");  ge = None
-                le: "Sym(u0 <= 5)" = item <= 5;  item = None
-                _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le = None
+                 # 
+                ge_1: "Sym(u0 >= 0)" = item >= 0
+                _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, "Runtime assertion failed for expression u0 >= 0 on node 'ge_1'");  ge_1 = None
+                le_1: "Sym(u0 <= 5)" = item <= 5;  item = None
+                _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le_1 = None
                 
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:19 in forward, code: return y.sin()
                 sin: "f32[5, 5]" = torch.ops.aten.sin.default(y);  y = None
@@ -1096,7 +1094,7 @@ dynamic_shape_if_guard
 
 .. note::
 
-    Tags: :doc:`python.control-flow <python.control-flow>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`python.control-flow <python.control-flow>`
 
     Support Level: SUPPORTED
 
@@ -1148,7 +1146,7 @@ dynamic_shape_map
 
 .. note::
 
-    Tags: :doc:`torch.map <torch.map>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.map <torch.map>`
 
     Support Level: SUPPORTED
 
@@ -1385,7 +1383,7 @@ list_contains
 
 .. note::
 
-    Tags: :doc:`python.data-structure <python.data-structure>`, :doc:`python.assert <python.assert>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`python.assert <python.assert>`, :doc:`python.data-structure <python.data-structure>`
 
     Support Level: SUPPORTED
 
@@ -1435,7 +1433,7 @@ list_unpack
 
 .. note::
 
-    Tags: :doc:`python.control-flow <python.control-flow>`, :doc:`python.data-structure <python.data-structure>`
+    Tags: :doc:`python.data-structure <python.data-structure>`, :doc:`python.control-flow <python.control-flow>`
 
     Support Level: SUPPORTED
 
@@ -1703,9 +1701,11 @@ Result:
     ExportedProgram:
         class GraphModule(torch.nn.Module):
             def forward(self, x: "f32[3, s0]"):
+                 # 
+                sym_size_int_1: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 1);  x = None
+                
                 # No stacktrace found for following nodes
-                sym_size_int: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 1);  x = None
-                add: "Sym(s0 + 1)" = sym_size_int + 1;  sym_size_int = None
+                add: "Sym(s0 + 1)" = sym_size_int_1 + 1;  sym_size_int_1 = None
                 return (add,)
                 
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=<OutputKind.USER_OUTPUT: 1>, arg=SymIntArgument(name='add'), target=None)])
@@ -2224,6 +2224,6 @@ Result:
 
 .. code-block::
 
-    Unsupported: torch.* op returned non-Tensor int call_function <function sym_min at 0x7f051a15b4c0>
+    Unsupported: torch.* op returned non-Tensor int call_function <function sym_min at 0x7f9173a9d4c0>
 
 
diff --git a/main/_sources/generated/exportdb/python.assert.rst.txt b/main/_sources/generated/exportdb/python.assert.rst.txt
index d2e7276097..1eb99aefc8 100644
--- a/main/_sources/generated/exportdb/python.assert.rst.txt
+++ b/main/_sources/generated/exportdb/python.assert.rst.txt
@@ -54,7 +54,7 @@ list_contains
 
 .. note::
 
-    Tags: :doc:`python.data-structure <python.data-structure>`, :doc:`python.assert <python.assert>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`python.assert <python.assert>`, :doc:`python.data-structure <python.data-structure>`
 
     Support Level: SUPPORTED
 
diff --git a/main/_sources/generated/exportdb/python.control-flow.rst.txt b/main/_sources/generated/exportdb/python.control-flow.rst.txt
index 8e1b37feba..fecec50be1 100644
--- a/main/_sources/generated/exportdb/python.control-flow.rst.txt
+++ b/main/_sources/generated/exportdb/python.control-flow.rst.txt
@@ -5,7 +5,7 @@ dynamic_shape_if_guard
 
 .. note::
 
-    Tags: :doc:`python.control-flow <python.control-flow>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`python.control-flow <python.control-flow>`
 
     Support Level: SUPPORTED
 
@@ -57,7 +57,7 @@ list_unpack
 
 .. note::
 
-    Tags: :doc:`python.control-flow <python.control-flow>`, :doc:`python.data-structure <python.data-structure>`
+    Tags: :doc:`python.data-structure <python.data-structure>`, :doc:`python.control-flow <python.control-flow>`
 
     Support Level: SUPPORTED
 
diff --git a/main/_sources/generated/exportdb/python.data-structure.rst.txt b/main/_sources/generated/exportdb/python.data-structure.rst.txt
index 41ba2070bd..8e3f00d945 100644
--- a/main/_sources/generated/exportdb/python.data-structure.rst.txt
+++ b/main/_sources/generated/exportdb/python.data-structure.rst.txt
@@ -133,7 +133,7 @@ list_contains
 
 .. note::
 
-    Tags: :doc:`python.data-structure <python.data-structure>`, :doc:`python.assert <python.assert>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`python.assert <python.assert>`, :doc:`python.data-structure <python.data-structure>`
 
     Support Level: SUPPORTED
 
@@ -183,7 +183,7 @@ list_unpack
 
 .. note::
 
-    Tags: :doc:`python.control-flow <python.control-flow>`, :doc:`python.data-structure <python.data-structure>`
+    Tags: :doc:`python.data-structure <python.data-structure>`, :doc:`python.control-flow <python.control-flow>`
 
     Support Level: SUPPORTED
 
diff --git a/main/_sources/generated/exportdb/torch.cond.rst.txt b/main/_sources/generated/exportdb/torch.cond.rst.txt
index c69b928fb4..863fd94a4b 100644
--- a/main/_sources/generated/exportdb/torch.cond.rst.txt
+++ b/main/_sources/generated/exportdb/torch.cond.rst.txt
@@ -5,7 +5,7 @@ cond_branch_class_method
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -97,7 +97,7 @@ cond_branch_nested_function
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -186,7 +186,7 @@ cond_branch_nonlocal_variables
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -372,7 +372,7 @@ cond_operands
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -427,9 +427,11 @@ Result:
     ExportedProgram:
         class GraphModule(torch.nn.Module):
             def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
+                 # 
+                sym_size_int_1: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 0)
+                
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_higher_order_ops/cond.py:108 in cond, code: return cond_op(pred, true_fn, false_fn, operands)
-                sym_size_int: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 0)
-                gt: "Sym(s0 > 2)" = sym_size_int > 2;  sym_size_int = None
+                gt: "Sym(s0 > 2)" = sym_size_int_1 > 2;  sym_size_int_1 = None
                 true_graph_0 = self.true_graph_0
                 false_graph_0 = self.false_graph_0
                 conditional = torch.ops.higher_order.cond(gt, true_graph_0, false_graph_0, [x, y]);  gt = true_graph_0 = false_graph_0 = x = y = None
@@ -458,7 +460,7 @@ cond_predicate
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
diff --git a/main/_sources/generated/exportdb/torch.dynamic-shape.rst.txt b/main/_sources/generated/exportdb/torch.dynamic-shape.rst.txt
index fb0984181d..ce5c20cb9b 100644
--- a/main/_sources/generated/exportdb/torch.dynamic-shape.rst.txt
+++ b/main/_sources/generated/exportdb/torch.dynamic-shape.rst.txt
@@ -5,7 +5,7 @@ cond_branch_class_method
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -97,7 +97,7 @@ cond_branch_nested_function
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -186,7 +186,7 @@ cond_branch_nonlocal_variables
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -302,7 +302,7 @@ cond_operands
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -357,9 +357,11 @@ Result:
     ExportedProgram:
         class GraphModule(torch.nn.Module):
             def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
+                 # 
+                sym_size_int_1: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 0)
+                
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_higher_order_ops/cond.py:108 in cond, code: return cond_op(pred, true_fn, false_fn, operands)
-                sym_size_int: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 0)
-                gt: "Sym(s0 > 2)" = sym_size_int > 2;  sym_size_int = None
+                gt: "Sym(s0 > 2)" = sym_size_int_1 > 2;  sym_size_int_1 = None
                 true_graph_0 = self.true_graph_0
                 false_graph_0 = self.false_graph_0
                 conditional = torch.ops.higher_order.cond(gt, true_graph_0, false_graph_0, [x, y]);  gt = true_graph_0 = false_graph_0 = x = y = None
@@ -388,7 +390,7 @@ cond_predicate
 
 .. note::
 
-    Tags: :doc:`torch.cond <torch.cond>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.cond <torch.cond>`
 
     Support Level: SUPPORTED
 
@@ -509,7 +511,7 @@ dynamic_shape_if_guard
 
 .. note::
 
-    Tags: :doc:`python.control-flow <python.control-flow>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`python.control-flow <python.control-flow>`
 
     Support Level: SUPPORTED
 
@@ -561,7 +563,7 @@ dynamic_shape_map
 
 .. note::
 
-    Tags: :doc:`torch.map <torch.map>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.map <torch.map>`
 
     Support Level: SUPPORTED
 
@@ -768,7 +770,7 @@ list_contains
 
 .. note::
 
-    Tags: :doc:`python.data-structure <python.data-structure>`, :doc:`python.assert <python.assert>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`python.assert <python.assert>`, :doc:`python.data-structure <python.data-structure>`
 
     Support Level: SUPPORTED
 
@@ -860,9 +862,11 @@ Result:
     ExportedProgram:
         class GraphModule(torch.nn.Module):
             def forward(self, x: "f32[3, s0]"):
+                 # 
+                sym_size_int_1: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 1);  x = None
+                
                 # No stacktrace found for following nodes
-                sym_size_int: "Sym(s0)" = torch.ops.aten.sym_size.int(x, 1);  x = None
-                add: "Sym(s0 + 1)" = sym_size_int + 1;  sym_size_int = None
+                add: "Sym(s0 + 1)" = sym_size_int_1 + 1;  sym_size_int_1 = None
                 return (add,)
                 
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=<InputKind.USER_INPUT: 1>, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=<OutputKind.USER_OUTPUT: 1>, arg=SymIntArgument(name='add'), target=None)])
diff --git a/main/_sources/generated/exportdb/torch.dynamic-value.rst.txt b/main/_sources/generated/exportdb/torch.dynamic-value.rst.txt
index f6ba186e56..12a7fd3df4 100644
--- a/main/_sources/generated/exportdb/torch.dynamic-value.rst.txt
+++ b/main/_sources/generated/exportdb/torch.dynamic-value.rst.txt
@@ -5,7 +5,7 @@ constrain_as_size_example
 
 .. note::
 
-    Tags: :doc:`torch.escape-hatch <torch.escape-hatch>`, :doc:`torch.dynamic-value <torch.dynamic-value>`
+    Tags: :doc:`torch.dynamic-value <torch.dynamic-value>`, :doc:`torch.escape-hatch <torch.escape-hatch>`
 
     Support Level: SUPPORTED
 
@@ -54,13 +54,10 @@ Result:
                 
                  # 
                 sym_constrain_range_for_size_default = torch.ops.aten.sym_constrain_range_for_size.default(item)
-                
-                # No stacktrace found for following nodes
-                sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-                ge: "Sym(u0 >= 0)" = item >= 0
-                _assert_scalar = torch.ops.aten._assert_scalar.default(ge, "Runtime assertion failed for expression 0 <= u0 on node 'ge'");  ge = None
-                le: "Sym(u0 <= 5)" = item <= 5
-                _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le = None
+                ge_1: "Sym(u0 >= 0)" = item >= 0
+                _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, "Runtime assertion failed for expression u0 >= 0 on node 'ge_1'");  ge_1 = None
+                le_1: "Sym(u0 <= 5)" = item <= 5
+                _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le_1 = None
                 
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_size_example.py:17 in forward, code: return torch.zeros((a, 5))
                 zeros: "f32[u0, 5]" = torch.ops.aten.zeros.default([item, 5], device = device(type='cpu'), pin_memory = False);  item = None
@@ -76,7 +73,7 @@ constrain_as_value_example
 
 .. note::
 
-    Tags: :doc:`torch.escape-hatch <torch.escape-hatch>`, :doc:`torch.dynamic-value <torch.dynamic-value>`
+    Tags: :doc:`torch.dynamic-value <torch.dynamic-value>`, :doc:`torch.escape-hatch <torch.escape-hatch>`
 
     Support Level: SUPPORTED
 
@@ -126,12 +123,11 @@ Result:
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:14 in forward, code: a = x.item()
                 item: "Sym(u0)" = torch.ops.aten.item.default(x);  x = None
                 
-                # No stacktrace found for following nodes
-                sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-                ge: "Sym(u0 >= 0)" = item >= 0
-                _assert_scalar = torch.ops.aten._assert_scalar.default(ge, "Runtime assertion failed for expression 0 <= u0 on node 'ge_1'");  ge = None
-                le: "Sym(u0 <= 5)" = item <= 5;  item = None
-                _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le = None
+                 # 
+                ge_1: "Sym(u0 >= 0)" = item >= 0
+                _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, "Runtime assertion failed for expression u0 >= 0 on node 'ge_1'");  ge_1 = None
+                le_1: "Sym(u0 <= 5)" = item <= 5;  item = None
+                _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le_1 = None
                 
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:19 in forward, code: return y.sin()
                 sin: "f32[5, 5]" = torch.ops.aten.sin.default(y);  y = None
diff --git a/main/_sources/generated/exportdb/torch.escape-hatch.rst.txt b/main/_sources/generated/exportdb/torch.escape-hatch.rst.txt
index c1e93bc724..84aa24a18e 100644
--- a/main/_sources/generated/exportdb/torch.escape-hatch.rst.txt
+++ b/main/_sources/generated/exportdb/torch.escape-hatch.rst.txt
@@ -58,7 +58,7 @@ constrain_as_size_example
 
 .. note::
 
-    Tags: :doc:`torch.escape-hatch <torch.escape-hatch>`, :doc:`torch.dynamic-value <torch.dynamic-value>`
+    Tags: :doc:`torch.dynamic-value <torch.dynamic-value>`, :doc:`torch.escape-hatch <torch.escape-hatch>`
 
     Support Level: SUPPORTED
 
@@ -107,13 +107,10 @@ Result:
                 
                  # 
                 sym_constrain_range_for_size_default = torch.ops.aten.sym_constrain_range_for_size.default(item)
-                
-                # No stacktrace found for following nodes
-                sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-                ge: "Sym(u0 >= 0)" = item >= 0
-                _assert_scalar = torch.ops.aten._assert_scalar.default(ge, "Runtime assertion failed for expression 0 <= u0 on node 'ge'");  ge = None
-                le: "Sym(u0 <= 5)" = item <= 5
-                _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le = None
+                ge_1: "Sym(u0 >= 0)" = item >= 0
+                _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, "Runtime assertion failed for expression u0 >= 0 on node 'ge_1'");  ge_1 = None
+                le_1: "Sym(u0 <= 5)" = item <= 5
+                _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le_1 = None
                 
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_size_example.py:17 in forward, code: return torch.zeros((a, 5))
                 zeros: "f32[u0, 5]" = torch.ops.aten.zeros.default([item, 5], device = device(type='cpu'), pin_memory = False);  item = None
@@ -129,7 +126,7 @@ constrain_as_value_example
 
 .. note::
 
-    Tags: :doc:`torch.escape-hatch <torch.escape-hatch>`, :doc:`torch.dynamic-value <torch.dynamic-value>`
+    Tags: :doc:`torch.dynamic-value <torch.dynamic-value>`, :doc:`torch.escape-hatch <torch.escape-hatch>`
 
     Support Level: SUPPORTED
 
@@ -179,12 +176,11 @@ Result:
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:14 in forward, code: a = x.item()
                 item: "Sym(u0)" = torch.ops.aten.item.default(x);  x = None
                 
-                # No stacktrace found for following nodes
-                sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-                ge: "Sym(u0 >= 0)" = item >= 0
-                _assert_scalar = torch.ops.aten._assert_scalar.default(ge, "Runtime assertion failed for expression 0 <= u0 on node 'ge_1'");  ge = None
-                le: "Sym(u0 <= 5)" = item <= 5;  item = None
-                _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le = None
+                 # 
+                ge_1: "Sym(u0 >= 0)" = item >= 0
+                _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, "Runtime assertion failed for expression u0 >= 0 on node 'ge_1'");  ge_1 = None
+                le_1: "Sym(u0 <= 5)" = item <= 5;  item = None
+                _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, "Runtime assertion failed for expression u0 <= 5 on node 'le_1'");  le_1 = None
                 
                  # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:19 in forward, code: return y.sin()
                 sin: "f32[5, 5]" = torch.ops.aten.sin.default(y);  y = None
diff --git a/main/_sources/generated/exportdb/torch.map.rst.txt b/main/_sources/generated/exportdb/torch.map.rst.txt
index c891e52cd4..cb4c0741e4 100644
--- a/main/_sources/generated/exportdb/torch.map.rst.txt
+++ b/main/_sources/generated/exportdb/torch.map.rst.txt
@@ -5,7 +5,7 @@ dynamic_shape_map
 
 .. note::
 
-    Tags: :doc:`torch.map <torch.map>`, :doc:`torch.dynamic-shape <torch.dynamic-shape>`
+    Tags: :doc:`torch.dynamic-shape <torch.dynamic-shape>`, :doc:`torch.map <torch.map>`
 
     Support Level: SUPPORTED
 
diff --git a/main/_sources/generated/exportdb/torch.operator.rst.txt b/main/_sources/generated/exportdb/torch.operator.rst.txt
index e53f4297a8..bcc4f85758 100644
--- a/main/_sources/generated/exportdb/torch.operator.rst.txt
+++ b/main/_sources/generated/exportdb/torch.operator.rst.txt
@@ -40,4 +40,4 @@ Result:
 
 .. code-block::
 
-    Unsupported: torch.* op returned non-Tensor int call_function <function sym_min at 0x7f051a15b4c0>
+    Unsupported: torch.* op returned non-Tensor int call_function <function sym_min at 0x7f9173a9d4c0>
diff --git a/main/_sources/library.rst.txt b/main/_sources/library.rst.txt
index e3b3bbc1ba..f632d93d1e 100644
--- a/main/_sources/library.rst.txt
+++ b/main/_sources/library.rst.txt
@@ -44,7 +44,6 @@ via PyTorch's C++ operator registration APIs).
 .. autofunction:: register_fake
 .. autofunction:: impl_abstract
 .. autofunction:: get_ctx
-.. autofunction:: register_torch_dispatch
 
 Low-level APIs
 --------------
diff --git a/main/_sources/notes/extending.rst.txt b/main/_sources/notes/extending.rst.txt
index 04c4e705e1..bf69d0e012 100644
--- a/main/_sources/notes/extending.rst.txt
+++ b/main/_sources/notes/extending.rst.txt
@@ -914,29 +914,6 @@ It is also possible to add `new` native functions using :mod:`torch.library`. Th
 
 You can find many examples of ``__torch_dispatch__``-based subclasses in the `subclass zoo <https://github.com/albanD/subclass_zoo>`_ repo.
 
-.. _torch-dispatch-calling-convention:
-
-``__torch_dispatch__`` calling convention
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-.. code-block:: python
-
-    @classmethod
-    def __torch_dispatch__(cls, func, types, args=(), kwargs=None):
-        pass
-
-When a user calls an operator with inputs that have ``__torch_dispatch__``, that call
-may be forwarded to the ``__torch_dispatch__``. args and kwargs get normalized before
-the call to ``__torch_dispatch__``, that is:
-
-- the ``kwargs`` consist of keyword-only arguments in the operator's schema.
-  If a kwarg is equal to its default value (in the schema), it will not be passed.
-- the ``args`` consists of all other arguments, no matter how they were passed
-  to the operator (positional vs keyword).
-  If an arg is equal to its default value, and
-  it is the right-most positional arg or all the args to the right of it
-  are not passed, it will not be passed.
-
 Extending all :mod:`torch` API with Modes
 -----------------------------------------
 
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+++ b/main/bottleneck.html
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index a1e56a2ad1..5a93559da1 100644
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index 3baee50e6b..aac315004f 100644
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+++ b/main/community/contribution_guide.html
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index 74b5e293cc..6855dc9b07 100644
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+++ b/main/community/design.html
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index 9d4e39c3d3..54f1de7095 100644
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index c43c3bc8c5..1c5215d70e 100644
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index fd743305b2..63361b3f54 100644
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index 0ebfbc020b..36dcf88eb0 100644
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index be26294b79..491e4b142a 100644
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 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1104,9 +1104,11 @@ <h3>cond_operands<a class="headerlink" href="#cond-operands" title="Permalink to
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span>ExportedProgram:
     class GraphModule(torch.nn.Module):
         def forward(self, x: &quot;f32[s0, 2]&quot;, y: &quot;f32[2]&quot;):
+             # 
+            sym_size_int_1: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 0)
+
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_higher_order_ops/cond.py:108 in cond, code: return cond_op(pred, true_fn, false_fn, operands)
-            sym_size_int: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 0)
-            gt: &quot;Sym(s0 &gt; 2)&quot; = sym_size_int &gt; 2;  sym_size_int = None
+            gt: &quot;Sym(s0 &gt; 2)&quot; = sym_size_int_1 &gt; 2;  sym_size_int_1 = None
             true_graph_0 = self.true_graph_0
             false_graph_0 = self.false_graph_0
             conditional = torch.ops.higher_order.cond(gt, true_graph_0, false_graph_0, [x, y]);  gt = true_graph_0 = false_graph_0 = x = y = None
@@ -1134,7 +1136,7 @@ <h3>cond_operands<a class="headerlink" href="#cond-operands" title="Permalink to
 <h3>cond_predicate<a class="headerlink" href="#cond-predicate" title="Permalink to this heading">¶</a></h3>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1200,7 +1202,7 @@ <h3>cond_predicate<a class="headerlink" href="#cond-predicate" title="Permalink
 <h3>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-example" title="Permalink to this heading">¶</a></h3>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a>, <a class="reference internal" href="torch.dynamic-value.html"><span class="doc">torch.dynamic-value</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-value.html"><span class="doc">torch.dynamic-value</span></a>, <a class="reference internal" href="torch.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1243,13 +1245,10 @@ <h3>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-exam
 
              # 
             sym_constrain_range_for_size_default = torch.ops.aten.sym_constrain_range_for_size.default(item)
-
-            # No stacktrace found for following nodes
-            sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-            ge: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
-            _assert_scalar = torch.ops.aten._assert_scalar.default(ge, &quot;Runtime assertion failed for expression 0 &lt;= u0 on node &#39;ge&#39;&quot;);  ge = None
-            le: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5
-            _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le = None
+            ge_1: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
+            _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, &quot;Runtime assertion failed for expression u0 &gt;= 0 on node &#39;ge_1&#39;&quot;);  ge_1 = None
+            le_1: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5
+            _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le_1 = None
 
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_size_example.py:17 in forward, code: return torch.zeros((a, 5))
             zeros: &quot;f32[u0, 5]&quot; = torch.ops.aten.zeros.default([item, 5], device = device(type=&#39;cpu&#39;), pin_memory = False);  item = None
@@ -1264,7 +1263,7 @@ <h3>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-exam
 <h3>constrain_as_value_example<a class="headerlink" href="#constrain-as-value-example" title="Permalink to this heading">¶</a></h3>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a>, <a class="reference internal" href="torch.dynamic-value.html"><span class="doc">torch.dynamic-value</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-value.html"><span class="doc">torch.dynamic-value</span></a>, <a class="reference internal" href="torch.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1308,12 +1307,11 @@ <h3>constrain_as_value_example<a class="headerlink" href="#constrain-as-value-ex
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:14 in forward, code: a = x.item()
             item: &quot;Sym(u0)&quot; = torch.ops.aten.item.default(x);  x = None
 
-            # No stacktrace found for following nodes
-            sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-            ge: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
-            _assert_scalar = torch.ops.aten._assert_scalar.default(ge, &quot;Runtime assertion failed for expression 0 &lt;= u0 on node &#39;ge_1&#39;&quot;);  ge = None
-            le: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5;  item = None
-            _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le = None
+             # 
+            ge_1: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
+            _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, &quot;Runtime assertion failed for expression u0 &gt;= 0 on node &#39;ge_1&#39;&quot;);  ge_1 = None
+            le_1: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5;  item = None
+            _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le_1 = None
 
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:19 in forward, code: return y.sin()
             sin: &quot;f32[5, 5]&quot; = torch.ops.aten.sin.default(y);  y = None
@@ -1509,7 +1507,7 @@ <h3>dynamic_shape_constructor<a class="headerlink" href="#dynamic-shape-construc
 <h3>dynamic_shape_if_guard<a class="headerlink" href="#dynamic-shape-if-guard" title="Permalink to this heading">¶</a></h3>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="python.control-flow.html"><span class="doc">python.control-flow</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="python.control-flow.html"><span class="doc">python.control-flow</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1554,7 +1552,7 @@ <h3>dynamic_shape_if_guard<a class="headerlink" href="#dynamic-shape-if-guard" t
 <h3>dynamic_shape_map<a class="headerlink" href="#dynamic-shape-map" title="Permalink to this heading">¶</a></h3>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.map.html"><span class="doc">torch.map</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="torch.map.html"><span class="doc">torch.map</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1763,7 +1761,7 @@ <h3>fn_with_kwargs<a class="headerlink" href="#fn-with-kwargs" title="Permalink
 <h3>list_contains<a class="headerlink" href="#list-contains" title="Permalink to this heading">¶</a></h3>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a>, <a class="reference internal" href="python.assert.html"><span class="doc">python.assert</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="python.assert.html"><span class="doc">python.assert</span></a>, <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1806,7 +1804,7 @@ <h3>list_contains<a class="headerlink" href="#list-contains" title="Permalink to
 <h3>list_unpack<a class="headerlink" href="#list-unpack" title="Permalink to this heading">¶</a></h3>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="python.control-flow.html"><span class="doc">python.control-flow</span></a>, <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a></p>
+<p>Tags: <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a>, <a class="reference internal" href="python.control-flow.html"><span class="doc">python.control-flow</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -2040,9 +2038,11 @@ <h3>scalar_output<a class="headerlink" href="#scalar-output" title="Permalink to
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span>ExportedProgram:
     class GraphModule(torch.nn.Module):
         def forward(self, x: &quot;f32[3, s0]&quot;):
+             # 
+            sym_size_int_1: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 1);  x = None
+
             # No stacktrace found for following nodes
-            sym_size_int: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 1);  x = None
-            add: &quot;Sym(s0 + 1)&quot; = sym_size_int + 1;  sym_size_int = None
+            add: &quot;Sym(s0 + 1)&quot; = sym_size_int_1 + 1;  sym_size_int_1 = None
             return (add,)
 
 Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=&lt;InputKind.USER_INPUT: 1&gt;, arg=TensorArgument(name=&#39;x&#39;), target=None, persistent=None)], output_specs=[OutputSpec(kind=&lt;OutputKind.USER_OUTPUT: 1&gt;, arg=SymIntArgument(name=&#39;add&#39;), target=None)])
@@ -2494,7 +2494,7 @@ <h3>torch_sym_min<a class="headerlink" href="#torch-sym-min" title="Permalink to
 </pre></div>
 </div>
 <p>Result:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">Unsupported</span><span class="p">:</span> <span class="n">torch</span><span class="o">.*</span> <span class="n">op</span> <span class="n">returned</span> <span class="n">non</span><span class="o">-</span><span class="n">Tensor</span> <span class="nb">int</span> <span class="n">call_function</span> <span class="o">&lt;</span><span class="n">function</span> <span class="n">sym_min</span> <span class="n">at</span> <span class="mh">0x7f051a15b4c0</span><span class="o">&gt;</span>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">Unsupported</span><span class="p">:</span> <span class="n">torch</span><span class="o">.*</span> <span class="n">op</span> <span class="n">returned</span> <span class="n">non</span><span class="o">-</span><span class="n">Tensor</span> <span class="nb">int</span> <span class="n">call_function</span> <span class="o">&lt;</span><span class="n">function</span> <span class="n">sym_min</span> <span class="n">at</span> <span class="mh">0x7f9173a9d4c0</span><span class="o">&gt;</span>
 </pre></div>
 </div>
 </div>
diff --git a/main/generated/exportdb/python.assert.html b/main/generated/exportdb/python.assert.html
index f81111a910..bf927b430d 100644
--- a/main/generated/exportdb/python.assert.html
+++ b/main/generated/exportdb/python.assert.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -575,7 +575,7 @@ <h2>dynamic_shape_assert<a class="headerlink" href="#dynamic-shape-assert" title
 <h2>list_contains<a class="headerlink" href="#list-contains" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a>, <a class="reference internal" href="#"><span class="doc">python.assert</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="#"><span class="doc">python.assert</span></a>, <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
diff --git a/main/generated/exportdb/python.builtin.html b/main/generated/exportdb/python.builtin.html
index 195cd33df9..b686534718 100644
--- a/main/generated/exportdb/python.builtin.html
+++ b/main/generated/exportdb/python.builtin.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/exportdb/python.closure.html b/main/generated/exportdb/python.closure.html
index 83cee590cb..67ba78a5d5 100644
--- a/main/generated/exportdb/python.closure.html
+++ b/main/generated/exportdb/python.closure.html
@@ -41,7 +41,7 @@
     <link rel="index" title="Index" href="../../genindex.html" />
     <link rel="search" title="Search" href="../../search.html" />
     <link rel="next" title="torch.dynamic-value" href="torch.dynamic-value.html" />
-    <link rel="prev" title="torch.dynamic-shape" href="torch.dynamic-shape.html" />
+    <link rel="prev" title="torch.cond" href="torch.cond.html" />
 
 <!--
   Search engines should not index the main version of documentation.
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -664,7 +664,7 @@ <h2>nested_function<a class="headerlink" href="#nested-function" title="Permalin
         <a href="torch.dynamic-value.html" class="btn btn-neutral float-right" title="torch.dynamic-value" accesskey="n" rel="next">Next <img src="../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="torch.dynamic-shape.html" class="btn btn-neutral" title="torch.dynamic-shape" accesskey="p" rel="prev"><img src="../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="torch.cond.html" class="btn btn-neutral" title="torch.cond" accesskey="p" rel="prev"><img src="../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
diff --git a/main/generated/exportdb/python.context-manager.html b/main/generated/exportdb/python.context-manager.html
index 72cb8f32ef..a189cd793f 100644
--- a/main/generated/exportdb/python.context-manager.html
+++ b/main/generated/exportdb/python.context-manager.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/exportdb/python.control-flow.html b/main/generated/exportdb/python.control-flow.html
index 370e14cde3..68e74cf435 100644
--- a/main/generated/exportdb/python.control-flow.html
+++ b/main/generated/exportdb/python.control-flow.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -533,7 +533,7 @@ <h1>python.control-flow<a class="headerlink" href="#python-control-flow" title="
 <h2>dynamic_shape_if_guard<a class="headerlink" href="#dynamic-shape-if-guard" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">python.control-flow</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="#"><span class="doc">python.control-flow</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -578,7 +578,7 @@ <h2>dynamic_shape_if_guard<a class="headerlink" href="#dynamic-shape-if-guard" t
 <h2>list_unpack<a class="headerlink" href="#list-unpack" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">python.control-flow</span></a>, <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a></p>
+<p>Tags: <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a>, <a class="reference internal" href="#"><span class="doc">python.control-flow</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
diff --git a/main/generated/exportdb/python.data-structure.html b/main/generated/exportdb/python.data-structure.html
index e3a495c952..8017900dd4 100644
--- a/main/generated/exportdb/python.data-structure.html
+++ b/main/generated/exportdb/python.data-structure.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -647,7 +647,7 @@ <h2>fn_with_kwargs<a class="headerlink" href="#fn-with-kwargs" title="Permalink
 <h2>list_contains<a class="headerlink" href="#list-contains" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">python.data-structure</span></a>, <a class="reference internal" href="python.assert.html"><span class="doc">python.assert</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="python.assert.html"><span class="doc">python.assert</span></a>, <a class="reference internal" href="#"><span class="doc">python.data-structure</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -690,7 +690,7 @@ <h2>list_contains<a class="headerlink" href="#list-contains" title="Permalink to
 <h2>list_unpack<a class="headerlink" href="#list-unpack" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="python.control-flow.html"><span class="doc">python.control-flow</span></a>, <a class="reference internal" href="#"><span class="doc">python.data-structure</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">python.data-structure</span></a>, <a class="reference internal" href="python.control-flow.html"><span class="doc">python.control-flow</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
diff --git a/main/generated/exportdb/python.object-model.html b/main/generated/exportdb/python.object-model.html
index 7b78d21099..217fcc61de 100644
--- a/main/generated/exportdb/python.object-model.html
+++ b/main/generated/exportdb/python.object-model.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/exportdb/torch.cond.html b/main/generated/exportdb/torch.cond.html
index dfe2a15b22..5330c99db2 100644
--- a/main/generated/exportdb/torch.cond.html
+++ b/main/generated/exportdb/torch.cond.html
@@ -40,8 +40,8 @@
   <link rel="stylesheet" href="../../_static/css/jit.css" type="text/css" />
     <link rel="index" title="Index" href="../../genindex.html" />
     <link rel="search" title="Search" href="../../search.html" />
-    <link rel="next" title="torch.dynamic-shape" href="torch.dynamic-shape.html" />
-    <link rel="prev" title="torch.escape-hatch" href="torch.escape-hatch.html" />
+    <link rel="next" title="python.closure" href="python.closure.html" />
+    <link rel="prev" title="torch.dynamic-shape" href="torch.dynamic-shape.html" />
 
 <!--
   Search engines should not index the main version of documentation.
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -533,7 +533,7 @@ <h1>torch.cond<a class="headerlink" href="#torch-cond" title="Permalink to this
 <h2>cond_branch_class_method<a class="headerlink" href="#cond-branch-class-method" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="#"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -618,7 +618,7 @@ <h2>cond_branch_class_method<a class="headerlink" href="#cond-branch-class-metho
 <h2>cond_branch_nested_function<a class="headerlink" href="#cond-branch-nested-function" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="#"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -700,7 +700,7 @@ <h2>cond_branch_nested_function<a class="headerlink" href="#cond-branch-nested-f
 <h2>cond_branch_nonlocal_variables<a class="headerlink" href="#cond-branch-nonlocal-variables" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="#"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -872,7 +872,7 @@ <h2>cond_closed_over_variable<a class="headerlink" href="#cond-closed-over-varia
 <h2>cond_operands<a class="headerlink" href="#cond-operands" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="#"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -921,9 +921,11 @@ <h2>cond_operands<a class="headerlink" href="#cond-operands" title="Permalink to
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span>ExportedProgram:
     class GraphModule(torch.nn.Module):
         def forward(self, x: &quot;f32[s0, 2]&quot;, y: &quot;f32[2]&quot;):
+             # 
+            sym_size_int_1: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 0)
+
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_higher_order_ops/cond.py:108 in cond, code: return cond_op(pred, true_fn, false_fn, operands)
-            sym_size_int: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 0)
-            gt: &quot;Sym(s0 &gt; 2)&quot; = sym_size_int &gt; 2;  sym_size_int = None
+            gt: &quot;Sym(s0 &gt; 2)&quot; = sym_size_int_1 &gt; 2;  sym_size_int_1 = None
             true_graph_0 = self.true_graph_0
             false_graph_0 = self.false_graph_0
             conditional = torch.ops.higher_order.cond(gt, true_graph_0, false_graph_0, [x, y]);  gt = true_graph_0 = false_graph_0 = x = y = None
@@ -951,7 +953,7 @@ <h2>cond_operands<a class="headerlink" href="#cond-operands" title="Permalink to
 <h2>cond_predicate<a class="headerlink" href="#cond-predicate" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="#"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1023,10 +1025,10 @@ <h2>cond_predicate<a class="headerlink" href="#cond-predicate" title="Permalink
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="torch.dynamic-shape.html" class="btn btn-neutral float-right" title="torch.dynamic-shape" accesskey="n" rel="next">Next <img src="../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="python.closure.html" class="btn btn-neutral float-right" title="python.closure" accesskey="n" rel="next">Next <img src="../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="torch.escape-hatch.html" class="btn btn-neutral" title="torch.escape-hatch" accesskey="p" rel="prev"><img src="../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="torch.dynamic-shape.html" class="btn btn-neutral" title="torch.dynamic-shape" accesskey="p" rel="prev"><img src="../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
diff --git a/main/generated/exportdb/torch.dynamic-shape.html b/main/generated/exportdb/torch.dynamic-shape.html
index fe336a2c4c..5e44b785bb 100644
--- a/main/generated/exportdb/torch.dynamic-shape.html
+++ b/main/generated/exportdb/torch.dynamic-shape.html
@@ -40,8 +40,8 @@
   <link rel="stylesheet" href="../../_static/css/jit.css" type="text/css" />
     <link rel="index" title="Index" href="../../genindex.html" />
     <link rel="search" title="Search" href="../../search.html" />
-    <link rel="next" title="python.closure" href="python.closure.html" />
-    <link rel="prev" title="torch.cond" href="torch.cond.html" />
+    <link rel="next" title="torch.cond" href="torch.cond.html" />
+    <link rel="prev" title="torch.escape-hatch" href="torch.escape-hatch.html" />
 
 <!--
   Search engines should not index the main version of documentation.
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -533,7 +533,7 @@ <h1>torch.dynamic-shape<a class="headerlink" href="#torch-dynamic-shape" title="
 <h2>cond_branch_class_method<a class="headerlink" href="#cond-branch-class-method" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -618,7 +618,7 @@ <h2>cond_branch_class_method<a class="headerlink" href="#cond-branch-class-metho
 <h2>cond_branch_nested_function<a class="headerlink" href="#cond-branch-nested-function" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -700,7 +700,7 @@ <h2>cond_branch_nested_function<a class="headerlink" href="#cond-branch-nested-f
 <h2>cond_branch_nonlocal_variables<a class="headerlink" href="#cond-branch-nonlocal-variables" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -809,7 +809,7 @@ <h2>cond_branch_nonlocal_variables<a class="headerlink" href="#cond-branch-nonlo
 <h2>cond_operands<a class="headerlink" href="#cond-operands" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -858,9 +858,11 @@ <h2>cond_operands<a class="headerlink" href="#cond-operands" title="Permalink to
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span>ExportedProgram:
     class GraphModule(torch.nn.Module):
         def forward(self, x: &quot;f32[s0, 2]&quot;, y: &quot;f32[2]&quot;):
+             # 
+            sym_size_int_1: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 0)
+
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_higher_order_ops/cond.py:108 in cond, code: return cond_op(pred, true_fn, false_fn, operands)
-            sym_size_int: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 0)
-            gt: &quot;Sym(s0 &gt; 2)&quot; = sym_size_int &gt; 2;  sym_size_int = None
+            gt: &quot;Sym(s0 &gt; 2)&quot; = sym_size_int_1 &gt; 2;  sym_size_int_1 = None
             true_graph_0 = self.true_graph_0
             false_graph_0 = self.false_graph_0
             conditional = torch.ops.higher_order.cond(gt, true_graph_0, false_graph_0, [x, y]);  gt = true_graph_0 = false_graph_0 = x = y = None
@@ -888,7 +890,7 @@ <h2>cond_operands<a class="headerlink" href="#cond-operands" title="Permalink to
 <h2>cond_predicate<a class="headerlink" href="#cond-predicate" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="torch.cond.html"><span class="doc">torch.cond</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -995,7 +997,7 @@ <h2>dynamic_shape_constructor<a class="headerlink" href="#dynamic-shape-construc
 <h2>dynamic_shape_if_guard<a class="headerlink" href="#dynamic-shape-if-guard" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="python.control-flow.html"><span class="doc">python.control-flow</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="python.control-flow.html"><span class="doc">python.control-flow</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1040,7 +1042,7 @@ <h2>dynamic_shape_if_guard<a class="headerlink" href="#dynamic-shape-if-guard" t
 <h2>dynamic_shape_map<a class="headerlink" href="#dynamic-shape-map" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.map.html"><span class="doc">torch.map</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="torch.map.html"><span class="doc">torch.map</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1220,7 +1222,7 @@ <h2>dynamic_shape_view<a class="headerlink" href="#dynamic-shape-view" title="Pe
 <h2>list_contains<a class="headerlink" href="#list-contains" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a>, <a class="reference internal" href="python.assert.html"><span class="doc">python.assert</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="python.assert.html"><span class="doc">python.assert</span></a>, <a class="reference internal" href="python.data-structure.html"><span class="doc">python.data-structure</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -1299,9 +1301,11 @@ <h2>scalar_output<a class="headerlink" href="#scalar-output" title="Permalink to
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span>ExportedProgram:
     class GraphModule(torch.nn.Module):
         def forward(self, x: &quot;f32[3, s0]&quot;):
+             # 
+            sym_size_int_1: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 1);  x = None
+
             # No stacktrace found for following nodes
-            sym_size_int: &quot;Sym(s0)&quot; = torch.ops.aten.sym_size.int(x, 1);  x = None
-            add: &quot;Sym(s0 + 1)&quot; = sym_size_int + 1;  sym_size_int = None
+            add: &quot;Sym(s0 + 1)&quot; = sym_size_int_1 + 1;  sym_size_int_1 = None
             return (add,)
 
 Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=&lt;InputKind.USER_INPUT: 1&gt;, arg=TensorArgument(name=&#39;x&#39;), target=None, persistent=None)], output_specs=[OutputSpec(kind=&lt;OutputKind.USER_OUTPUT: 1&gt;, arg=SymIntArgument(name=&#39;add&#39;), target=None)])
@@ -1319,10 +1323,10 @@ <h2>scalar_output<a class="headerlink" href="#scalar-output" title="Permalink to
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="python.closure.html" class="btn btn-neutral float-right" title="python.closure" accesskey="n" rel="next">Next <img src="../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="torch.cond.html" class="btn btn-neutral float-right" title="torch.cond" accesskey="n" rel="next">Next <img src="../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="torch.cond.html" class="btn btn-neutral" title="torch.cond" accesskey="p" rel="prev"><img src="../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="torch.escape-hatch.html" class="btn btn-neutral" title="torch.escape-hatch" accesskey="p" rel="prev"><img src="../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
diff --git a/main/generated/exportdb/torch.dynamic-value.html b/main/generated/exportdb/torch.dynamic-value.html
index a12873ddc6..26cfa18e8e 100644
--- a/main/generated/exportdb/torch.dynamic-value.html
+++ b/main/generated/exportdb/torch.dynamic-value.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -533,7 +533,7 @@ <h1>torch.dynamic-value<a class="headerlink" href="#torch-dynamic-value" title="
 <h2>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-example" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-value</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-value</span></a>, <a class="reference internal" href="torch.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -576,13 +576,10 @@ <h2>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-exam
 
              # 
             sym_constrain_range_for_size_default = torch.ops.aten.sym_constrain_range_for_size.default(item)
-
-            # No stacktrace found for following nodes
-            sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-            ge: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
-            _assert_scalar = torch.ops.aten._assert_scalar.default(ge, &quot;Runtime assertion failed for expression 0 &lt;= u0 on node &#39;ge&#39;&quot;);  ge = None
-            le: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5
-            _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le = None
+            ge_1: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
+            _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, &quot;Runtime assertion failed for expression u0 &gt;= 0 on node &#39;ge_1&#39;&quot;);  ge_1 = None
+            le_1: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5
+            _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le_1 = None
 
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_size_example.py:17 in forward, code: return torch.zeros((a, 5))
             zeros: &quot;f32[u0, 5]&quot; = torch.ops.aten.zeros.default([item, 5], device = device(type=&#39;cpu&#39;), pin_memory = False);  item = None
@@ -597,7 +594,7 @@ <h2>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-exam
 <h2>constrain_as_value_example<a class="headerlink" href="#constrain-as-value-example" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="torch.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a>, <a class="reference internal" href="#"><span class="doc">torch.dynamic-value</span></a></p>
+<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.dynamic-value</span></a>, <a class="reference internal" href="torch.escape-hatch.html"><span class="doc">torch.escape-hatch</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -641,12 +638,11 @@ <h2>constrain_as_value_example<a class="headerlink" href="#constrain-as-value-ex
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:14 in forward, code: a = x.item()
             item: &quot;Sym(u0)&quot; = torch.ops.aten.item.default(x);  x = None
 
-            # No stacktrace found for following nodes
-            sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-            ge: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
-            _assert_scalar = torch.ops.aten._assert_scalar.default(ge, &quot;Runtime assertion failed for expression 0 &lt;= u0 on node &#39;ge_1&#39;&quot;);  ge = None
-            le: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5;  item = None
-            _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le = None
+             # 
+            ge_1: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
+            _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, &quot;Runtime assertion failed for expression u0 &gt;= 0 on node &#39;ge_1&#39;&quot;);  ge_1 = None
+            le_1: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5;  item = None
+            _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le_1 = None
 
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:19 in forward, code: return y.sin()
             sin: &quot;f32[5, 5]&quot; = torch.ops.aten.sin.default(y);  y = None
diff --git a/main/generated/exportdb/torch.escape-hatch.html b/main/generated/exportdb/torch.escape-hatch.html
index cbcd28a22d..c25dd0fef5 100644
--- a/main/generated/exportdb/torch.escape-hatch.html
+++ b/main/generated/exportdb/torch.escape-hatch.html
@@ -40,7 +40,7 @@
   <link rel="stylesheet" href="../../_static/css/jit.css" type="text/css" />
     <link rel="index" title="Index" href="../../genindex.html" />
     <link rel="search" title="Search" href="../../search.html" />
-    <link rel="next" title="torch.cond" href="torch.cond.html" />
+    <link rel="next" title="torch.dynamic-shape" href="torch.dynamic-shape.html" />
     <link rel="prev" title="ExportDB" href="index.html" />
 
 <!--
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -579,7 +579,7 @@ <h2>assume_constant_result<a class="headerlink" href="#assume-constant-result" t
 <h2>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-example" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.escape-hatch</span></a>, <a class="reference internal" href="torch.dynamic-value.html"><span class="doc">torch.dynamic-value</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-value.html"><span class="doc">torch.dynamic-value</span></a>, <a class="reference internal" href="#"><span class="doc">torch.escape-hatch</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -622,13 +622,10 @@ <h2>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-exam
 
              # 
             sym_constrain_range_for_size_default = torch.ops.aten.sym_constrain_range_for_size.default(item)
-
-            # No stacktrace found for following nodes
-            sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-            ge: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
-            _assert_scalar = torch.ops.aten._assert_scalar.default(ge, &quot;Runtime assertion failed for expression 0 &lt;= u0 on node &#39;ge&#39;&quot;);  ge = None
-            le: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5
-            _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le = None
+            ge_1: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
+            _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, &quot;Runtime assertion failed for expression u0 &gt;= 0 on node &#39;ge_1&#39;&quot;);  ge_1 = None
+            le_1: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5
+            _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le_1 = None
 
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_size_example.py:17 in forward, code: return torch.zeros((a, 5))
             zeros: &quot;f32[u0, 5]&quot; = torch.ops.aten.zeros.default([item, 5], device = device(type=&#39;cpu&#39;), pin_memory = False);  item = None
@@ -643,7 +640,7 @@ <h2>constrain_as_size_example<a class="headerlink" href="#constrain-as-size-exam
 <h2>constrain_as_value_example<a class="headerlink" href="#constrain-as-value-example" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.escape-hatch</span></a>, <a class="reference internal" href="torch.dynamic-value.html"><span class="doc">torch.dynamic-value</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-value.html"><span class="doc">torch.dynamic-value</span></a>, <a class="reference internal" href="#"><span class="doc">torch.escape-hatch</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
@@ -687,12 +684,11 @@ <h2>constrain_as_value_example<a class="headerlink" href="#constrain-as-value-ex
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:14 in forward, code: a = x.item()
             item: &quot;Sym(u0)&quot; = torch.ops.aten.item.default(x);  x = None
 
-            # No stacktrace found for following nodes
-            sym_constrain_range = torch.ops.aten.sym_constrain_range.default(item, min = 0, max = 5)
-            ge: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
-            _assert_scalar = torch.ops.aten._assert_scalar.default(ge, &quot;Runtime assertion failed for expression 0 &lt;= u0 on node &#39;ge_1&#39;&quot;);  ge = None
-            le: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5;  item = None
-            _assert_scalar_1 = torch.ops.aten._assert_scalar.default(le, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le = None
+             # 
+            ge_1: &quot;Sym(u0 &gt;= 0)&quot; = item &gt;= 0
+            _assert_scalar_default = torch.ops.aten._assert_scalar.default(ge_1, &quot;Runtime assertion failed for expression u0 &gt;= 0 on node &#39;ge_1&#39;&quot;);  ge_1 = None
+            le_1: &quot;Sym(u0 &lt;= 5)&quot; = item &lt;= 5;  item = None
+            _assert_scalar_default_1 = torch.ops.aten._assert_scalar.default(le_1, &quot;Runtime assertion failed for expression u0 &lt;= 5 on node &#39;le_1&#39;&quot;);  le_1 = None
 
              # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/constrain_as_value_example.py:19 in forward, code: return y.sin()
             sin: &quot;f32[5, 5]&quot; = torch.ops.aten.sin.default(y);  y = None
@@ -713,7 +709,7 @@ <h2>constrain_as_value_example<a class="headerlink" href="#constrain-as-value-ex
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="torch.cond.html" class="btn btn-neutral float-right" title="torch.cond" accesskey="n" rel="next">Next <img src="../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="torch.dynamic-shape.html" class="btn btn-neutral float-right" title="torch.dynamic-shape" accesskey="n" rel="next">Next <img src="../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
         <a href="index.html" class="btn btn-neutral" title="ExportDB" accesskey="p" rel="prev"><img src="../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
diff --git a/main/generated/exportdb/torch.map.html b/main/generated/exportdb/torch.map.html
index 146a792a72..3a4a547963 100644
--- a/main/generated/exportdb/torch.map.html
+++ b/main/generated/exportdb/torch.map.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -533,7 +533,7 @@ <h1>torch.map<a class="headerlink" href="#torch-map" title="Permalink to this he
 <h2>dynamic_shape_map<a class="headerlink" href="#dynamic-shape-map" title="Permalink to this heading">¶</a></h2>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Tags: <a class="reference internal" href="#"><span class="doc">torch.map</span></a>, <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a></p>
+<p>Tags: <a class="reference internal" href="torch.dynamic-shape.html"><span class="doc">torch.dynamic-shape</span></a>, <a class="reference internal" href="#"><span class="doc">torch.map</span></a></p>
 <p>Support Level: SUPPORTED</p>
 </div>
 <p>Original source code:</p>
diff --git a/main/generated/exportdb/torch.mutation.html b/main/generated/exportdb/torch.mutation.html
index c434afd388..8e57434a2b 100644
--- a/main/generated/exportdb/torch.mutation.html
+++ b/main/generated/exportdb/torch.mutation.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/exportdb/torch.operator.html b/main/generated/exportdb/torch.operator.html
index 32884caf35..51314ae352 100644
--- a/main/generated/exportdb/torch.operator.html
+++ b/main/generated/exportdb/torch.operator.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
@@ -562,7 +562,7 @@ <h2>torch_sym_min<a class="headerlink" href="#torch-sym-min" title="Permalink to
 </pre></div>
 </div>
 <p>Result:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">Unsupported</span><span class="p">:</span> <span class="n">torch</span><span class="o">.*</span> <span class="n">op</span> <span class="n">returned</span> <span class="n">non</span><span class="o">-</span><span class="n">Tensor</span> <span class="nb">int</span> <span class="n">call_function</span> <span class="o">&lt;</span><span class="n">function</span> <span class="n">sym_min</span> <span class="n">at</span> <span class="mh">0x7f051a15b4c0</span><span class="o">&gt;</span>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">Unsupported</span><span class="p">:</span> <span class="n">torch</span><span class="o">.*</span> <span class="n">op</span> <span class="n">returned</span> <span class="n">non</span><span class="o">-</span><span class="n">Tensor</span> <span class="nb">int</span> <span class="n">call_function</span> <span class="o">&lt;</span><span class="n">function</span> <span class="n">sym_min</span> <span class="n">at</span> <span class="mh">0x7f9173a9d4c0</span><span class="o">&gt;</span>
 </pre></div>
 </div>
 </div>
diff --git a/main/generated/onnx_dynamo_diagnostics_rules/FXE0007:fx-graph-to-onnx.html b/main/generated/onnx_dynamo_diagnostics_rules/FXE0007:fx-graph-to-onnx.html
index 547e829877..7b150107c6 100644
--- a/main/generated/onnx_dynamo_diagnostics_rules/FXE0007:fx-graph-to-onnx.html
+++ b/main/generated/onnx_dynamo_diagnostics_rules/FXE0007:fx-graph-to-onnx.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/onnx_dynamo_diagnostics_rules/FXE0008:fx-node-to-onnx.html b/main/generated/onnx_dynamo_diagnostics_rules/FXE0008:fx-node-to-onnx.html
index 7f98b49059..cd18b52e76 100644
--- a/main/generated/onnx_dynamo_diagnostics_rules/FXE0008:fx-node-to-onnx.html
+++ b/main/generated/onnx_dynamo_diagnostics_rules/FXE0008:fx-node-to-onnx.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/onnx_dynamo_diagnostics_rules/FXE0010:fx-pass.html b/main/generated/onnx_dynamo_diagnostics_rules/FXE0010:fx-pass.html
index a7ee89d00b..d3f8f559d1 100644
--- a/main/generated/onnx_dynamo_diagnostics_rules/FXE0010:fx-pass.html
+++ b/main/generated/onnx_dynamo_diagnostics_rules/FXE0010:fx-pass.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/onnx_dynamo_diagnostics_rules/FXE0011:no-symbolic-function-for-call-function.html b/main/generated/onnx_dynamo_diagnostics_rules/FXE0011:no-symbolic-function-for-call-function.html
index fa3f53f996..5d1b278747 100644
--- a/main/generated/onnx_dynamo_diagnostics_rules/FXE0011:no-symbolic-function-for-call-function.html
+++ b/main/generated/onnx_dynamo_diagnostics_rules/FXE0011:no-symbolic-function-for-call-function.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/onnx_dynamo_diagnostics_rules/FXE0012:unsupported-fx-node-analysis.html b/main/generated/onnx_dynamo_diagnostics_rules/FXE0012:unsupported-fx-node-analysis.html
index e23fc1a894..48fc2cdc0f 100644
--- a/main/generated/onnx_dynamo_diagnostics_rules/FXE0012:unsupported-fx-node-analysis.html
+++ b/main/generated/onnx_dynamo_diagnostics_rules/FXE0012:unsupported-fx-node-analysis.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/onnx_dynamo_diagnostics_rules/FXE0013:op-level-debugging.html b/main/generated/onnx_dynamo_diagnostics_rules/FXE0013:op-level-debugging.html
index 9455aa9d38..643e9f1f40 100644
--- a/main/generated/onnx_dynamo_diagnostics_rules/FXE0013:op-level-debugging.html
+++ b/main/generated/onnx_dynamo_diagnostics_rules/FXE0013:op-level-debugging.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/onnx_dynamo_diagnostics_rules/FXE0014:find-opschema-matched-symbolic-function.html b/main/generated/onnx_dynamo_diagnostics_rules/FXE0014:find-opschema-matched-symbolic-function.html
index 2a80e4ae1c..abaceaf1c2 100644
--- a/main/generated/onnx_dynamo_diagnostics_rules/FXE0014:find-opschema-matched-symbolic-function.html
+++ b/main/generated/onnx_dynamo_diagnostics_rules/FXE0014:find-opschema-matched-symbolic-function.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/onnx_dynamo_diagnostics_rules/FXE0015:fx-node-insert-type-promotion.html b/main/generated/onnx_dynamo_diagnostics_rules/FXE0015:fx-node-insert-type-promotion.html
index 67b17aea42..4f9ad12a9c 100644
--- a/main/generated/onnx_dynamo_diagnostics_rules/FXE0015:fx-node-insert-type-promotion.html
+++ b/main/generated/onnx_dynamo_diagnostics_rules/FXE0015:fx-node-insert-type-promotion.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/onnx_dynamo_diagnostics_rules/FXE0016:find-operator-overloads-in-onnx-registry.html b/main/generated/onnx_dynamo_diagnostics_rules/FXE0016:find-operator-overloads-in-onnx-registry.html
index b414e46f4e..b2449778fe 100644
--- a/main/generated/onnx_dynamo_diagnostics_rules/FXE0016:find-operator-overloads-in-onnx-registry.html
+++ b/main/generated/onnx_dynamo_diagnostics_rules/FXE0016:find-operator-overloads-in-onnx-registry.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/torch.Generator.html b/main/generated/torch.Generator.html
index 6c7e0c8149..d2fc56c3ec 100644
--- a/main/generated/torch.Generator.html
+++ b/main/generated/torch.Generator.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/torch.Tensor.abs.html b/main/generated/torch.Tensor.abs.html
index ad689cbff9..242bb17c7c 100644
--- a/main/generated/torch.Tensor.abs.html
+++ b/main/generated/torch.Tensor.abs.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>
     
 
diff --git a/main/generated/torch.Tensor.abs_.html b/main/generated/torch.Tensor.abs_.html
index 6a92b175ea..9d7a56ac26 100644
--- a/main/generated/torch.Tensor.abs_.html
+++ b/main/generated/torch.Tensor.abs_.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
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diff --git a/main/generated/torch._foreach_exp.html b/main/generated/torch._foreach_exp.html
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diff --git a/main/generated/torch._foreach_expm1.html b/main/generated/torch._foreach_expm1.html
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diff --git a/main/generated/torch._foreach_floor.html b/main/generated/torch._foreach_floor.html
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diff --git a/main/generated/torch._foreach_floor_.html b/main/generated/torch._foreach_floor_.html
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diff --git a/main/generated/torch._foreach_frac.html b/main/generated/torch._foreach_frac.html
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diff --git a/main/generated/torch._foreach_frac_.html b/main/generated/torch._foreach_frac_.html
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diff --git a/main/generated/torch._foreach_log10_.html b/main/generated/torch._foreach_log10_.html
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diff --git a/main/generated/torch._foreach_log_.html b/main/generated/torch._foreach_log_.html
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diff --git a/main/generated/torch._foreach_neg.html b/main/generated/torch._foreach_neg.html
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diff --git a/main/generated/torch._foreach_round.html b/main/generated/torch._foreach_round.html
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diff --git a/main/generated/torch._foreach_sigmoid.html b/main/generated/torch._foreach_sigmoid.html
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diff --git a/main/generated/torch._foreach_sigmoid_.html b/main/generated/torch._foreach_sigmoid_.html
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diff --git a/main/generated/torch._foreach_sin.html b/main/generated/torch._foreach_sin.html
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diff --git a/main/generated/torch._foreach_sinh_.html b/main/generated/torch._foreach_sinh_.html
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diff --git a/main/generated/torch._foreach_sqrt.html b/main/generated/torch._foreach_sqrt.html
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diff --git a/main/generated/torch._foreach_sqrt_.html b/main/generated/torch._foreach_sqrt_.html
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diff --git a/main/generated/torch._foreach_tan.html b/main/generated/torch._foreach_tan.html
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diff --git a/main/generated/torch._foreach_tan_.html b/main/generated/torch._foreach_tan_.html
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diff --git a/main/generated/torch._foreach_trunc.html b/main/generated/torch._foreach_trunc.html
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diff --git a/main/generated/torch._foreach_trunc_.html b/main/generated/torch._foreach_trunc_.html
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diff --git a/main/generated/torch._foreach_zero_.html b/main/generated/torch._foreach_zero_.html
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diff --git a/main/generated/torch._logging.set_logs.html b/main/generated/torch._logging.set_logs.html
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diff --git a/main/generated/torch.abs.html b/main/generated/torch.abs.html
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diff --git a/main/generated/torch.absolute.html b/main/generated/torch.absolute.html
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diff --git a/main/generated/torch.acos.html b/main/generated/torch.acos.html
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diff --git a/main/generated/torch.acosh.html b/main/generated/torch.acosh.html
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diff --git a/main/generated/torch.add.html b/main/generated/torch.add.html
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diff --git a/main/generated/torch.addbmm.html b/main/generated/torch.addbmm.html
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diff --git a/main/generated/torch.ao.quantization.observer.MovingAveragePerChannelMinMaxObserver.html b/main/generated/torch.ao.quantization.observer.MovingAveragePerChannelMinMaxObserver.html
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diff --git a/main/generated/torch.ao.quantization.observer.default_dynamic_quant_observer.html b/main/generated/torch.ao.quantization.observer.default_dynamic_quant_observer.html
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diff --git a/main/generated/torch.ao.quantization.observer.load_observer_state_dict.html b/main/generated/torch.ao.quantization.observer.load_observer_state_dict.html
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diff --git a/main/generated/torch.bitwise_xor.html b/main/generated/torch.bitwise_xor.html
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diff --git a/main/generated/torch.broadcast_shapes.html b/main/generated/torch.broadcast_shapes.html
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diff --git a/main/generated/torch.cholesky.html b/main/generated/torch.cholesky.html
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diff --git a/main/generated/torch.cholesky_solve.html b/main/generated/torch.cholesky_solve.html
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diff --git a/main/generated/torch.chunk.html b/main/generated/torch.chunk.html
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diff --git a/main/generated/torch.clone.html b/main/generated/torch.clone.html
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diff --git a/main/generated/torch.compiler.is_compiling.html b/main/generated/torch.compiler.is_compiling.html
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diff --git a/main/generated/torch.compiler.list_backends.html b/main/generated/torch.compiler.list_backends.html
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diff --git a/main/generated/torch.compiler.reset.html b/main/generated/torch.compiler.reset.html
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diff --git a/main/generated/torch.complex.html b/main/generated/torch.complex.html
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diff --git a/main/generated/torch.concat.html b/main/generated/torch.concat.html
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diff --git a/main/generated/torch.concatenate.html b/main/generated/torch.concatenate.html
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diff --git a/main/generated/torch.cond.html b/main/generated/torch.cond.html
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diff --git a/main/generated/torch.conj.html b/main/generated/torch.conj.html
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diff --git a/main/generated/torch.conj_physical.html b/main/generated/torch.conj_physical.html
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diff --git a/main/generated/torch.copysign.html b/main/generated/torch.copysign.html
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diff --git a/main/generated/torch.corrcoef.html b/main/generated/torch.corrcoef.html
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diff --git a/main/generated/torch.cos.html b/main/generated/torch.cos.html
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diff --git a/main/generated/torch.cpu.Stream.html b/main/generated/torch.cpu.Stream.html
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diff --git a/main/generated/torch.cpu.synchronize.html b/main/generated/torch.cpu.synchronize.html
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diff --git a/main/generated/torch.cross.html b/main/generated/torch.cross.html
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diff --git a/main/generated/torch.erf.html b/main/generated/torch.erf.html
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diff --git a/main/generated/torch.erfinv.html b/main/generated/torch.erfinv.html
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diff --git a/main/generated/torch.exp.html b/main/generated/torch.exp.html
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diff --git a/main/generated/torch.fft.fft.html b/main/generated/torch.fft.fft.html
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diff --git a/main/generated/torch.fft.fft2.html b/main/generated/torch.fft.fft2.html
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diff --git a/main/generated/torch.fft.fftfreq.html b/main/generated/torch.fft.fftfreq.html
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diff --git a/main/generated/torch.fft.fftn.html b/main/generated/torch.fft.fftn.html
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diff --git a/main/generated/torch.fft.fftshift.html b/main/generated/torch.fft.fftshift.html
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diff --git a/main/generated/torch.fft.hfft.html b/main/generated/torch.fft.hfft.html
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diff --git a/main/generated/torch.fft.ifft.html b/main/generated/torch.fft.ifft.html
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diff --git a/main/generated/torch.fft.ifftshift.html b/main/generated/torch.fft.ifftshift.html
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diff --git a/main/generated/torch.fft.ihfft.html b/main/generated/torch.fft.ihfft.html
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diff --git a/main/generated/torch.fft.ihfft2.html b/main/generated/torch.fft.ihfft2.html
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diff --git a/main/generated/torch.fft.ihfftn.html b/main/generated/torch.fft.ihfftn.html
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diff --git a/main/generated/torch.fft.irfft.html b/main/generated/torch.fft.irfft.html
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diff --git a/main/generated/torch.fft.irfft2.html b/main/generated/torch.fft.irfft2.html
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diff --git a/main/generated/torch.fft.rfft.html b/main/generated/torch.fft.rfft.html
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diff --git a/main/generated/torch.fft.rfft2.html b/main/generated/torch.fft.rfft2.html
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diff --git a/main/generated/torch.floor.html b/main/generated/torch.floor.html
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diff --git a/main/generated/torch.from_dlpack.html b/main/generated/torch.from_dlpack.html
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diff --git a/main/generated/torch.from_file.html b/main/generated/torch.from_file.html
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diff --git a/main/generated/torch.from_numpy.html b/main/generated/torch.from_numpy.html
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diff --git a/main/generated/torch.frombuffer.html b/main/generated/torch.frombuffer.html
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diff --git a/main/generated/torch.full.html b/main/generated/torch.full.html
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diff --git a/main/generated/torch.func.functional_call.html b/main/generated/torch.func.functional_call.html
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diff --git a/main/generated/torch.func.hessian.html b/main/generated/torch.func.hessian.html
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diff --git a/main/generated/torch.func.jacfwd.html b/main/generated/torch.func.jacfwd.html
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diff --git a/main/generated/torch.func.jacrev.html b/main/generated/torch.func.jacrev.html
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diff --git a/main/generated/torch.func.jvp.html b/main/generated/torch.func.jvp.html
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diff --git a/main/generated/torch.func.linearize.html b/main/generated/torch.func.linearize.html
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diff --git a/main/generated/torch.func.replace_all_batch_norm_modules_.html b/main/generated/torch.func.replace_all_batch_norm_modules_.html
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diff --git a/main/generated/torch.func.stack_module_state.html b/main/generated/torch.func.stack_module_state.html
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diff --git a/main/generated/torch.func.vjp.html b/main/generated/torch.func.vjp.html
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diff --git a/main/generated/torch.func.vmap.html b/main/generated/torch.func.vmap.html
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diff --git a/main/generated/torch.fx.experimental.symbolic_shapes.CallMethodKey.html b/main/generated/torch.fx.experimental.symbolic_shapes.CallMethodKey.html
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diff --git a/main/generated/torch.fx.experimental.symbolic_shapes.ConvertIntKey.html b/main/generated/torch.fx.experimental.symbolic_shapes.ConvertIntKey.html
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diff --git a/main/generated/torch.fx.experimental.symbolic_shapes.DimConstraints.html b/main/generated/torch.fx.experimental.symbolic_shapes.DimConstraints.html
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diff --git a/main/generated/torch.isinf.html b/main/generated/torch.isinf.html
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diff --git a/main/generated/torch.jit.Attribute.html b/main/generated/torch.jit.Attribute.html
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diff --git a/main/generated/torch.logical_and.html b/main/generated/torch.logical_and.html
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diff --git a/main/generated/torch.logical_not.html b/main/generated/torch.logical_not.html
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diff --git a/main/generated/torch.logical_or.html b/main/generated/torch.logical_or.html
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diff --git a/main/generated/torch.logical_xor.html b/main/generated/torch.logical_xor.html
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diff --git a/main/generated/torch.logit.html b/main/generated/torch.logit.html
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diff --git a/main/generated/torch.logsumexp.html b/main/generated/torch.logsumexp.html
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diff --git a/main/generated/torch.lt.html b/main/generated/torch.lt.html
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diff --git a/main/generated/torch.lu.html b/main/generated/torch.lu.html
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diff --git a/main/generated/torch.lu_solve.html b/main/generated/torch.lu_solve.html
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diff --git a/main/generated/torch.lu_unpack.html b/main/generated/torch.lu_unpack.html
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diff --git a/main/generated/torch.max.html b/main/generated/torch.max.html
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diff --git a/main/generated/torch.mean.html b/main/generated/torch.mean.html
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diff --git a/main/generated/torch.median.html b/main/generated/torch.median.html
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diff --git a/main/generated/torch.min.html b/main/generated/torch.min.html
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diff --git a/main/generated/torch.mm.html b/main/generated/torch.mm.html
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diff --git a/main/generated/torch.mode.html b/main/generated/torch.mode.html
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diff --git a/main/generated/torch.movedim.html b/main/generated/torch.movedim.html
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diff --git a/main/generated/torch.mps.event.Event.html b/main/generated/torch.mps.event.Event.html
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diff --git a/main/generated/torch.nn.Embedding.html b/main/generated/torch.nn.Embedding.html
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@@ -579,7 +579,7 @@ <h1>Embedding<a class="headerlink" href="#embedding" title="Permalink to this he
 calling <a class="reference internal" href="#torch.nn.Embedding" title="torch.nn.Embedding"><code class="xref py py-class docutils literal notranslate"><span class="pre">Embedding</span></code></a>’s forward method requires cloning <code class="docutils literal notranslate"><span class="pre">Embedding.weight</span></code> when
 <code class="xref py py-attr docutils literal notranslate"><span class="pre">max_norm</span></code> is not <code class="docutils literal notranslate"><span class="pre">None</span></code>. For example:</p>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">n</span><span class="p">,</span> <span class="n">d</span><span class="p">,</span> <span class="n">m</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">7</span>
-<span class="n">embedding</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Embedding</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">d</span><span class="p">,</span> <span class="n">max_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">embedding</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Embedding</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">d</span><span class="p">,</span> <span class="n">max_norm</span><span class="o">=</span><span class="mf">1.0</span><span class="p">)</span>
 <span class="n">W</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">((</span><span class="n">m</span><span class="p">,</span> <span class="n">d</span><span class="p">),</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 <span class="n">idx</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span>
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diff --git a/main/generated/torch.outer.html b/main/generated/torch.outer.html
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diff --git a/main/generated/torch.pca_lowrank.html b/main/generated/torch.pca_lowrank.html
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diff --git a/main/generated/torch.permute.html b/main/generated/torch.permute.html
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diff --git a/main/generated/torch.pinverse.html b/main/generated/torch.pinverse.html
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diff --git a/main/generated/torch.poisson.html b/main/generated/torch.poisson.html
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diff --git a/main/generated/torch.polar.html b/main/generated/torch.polar.html
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diff --git a/main/generated/torch.polygamma.html b/main/generated/torch.polygamma.html
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diff --git a/main/generated/torch.positive.html b/main/generated/torch.positive.html
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diff --git a/main/generated/torch.pow.html b/main/generated/torch.pow.html
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diff --git a/main/generated/torch.prod.html b/main/generated/torch.prod.html
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diff --git a/main/generated/torch.promote_types.html b/main/generated/torch.promote_types.html
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diff --git a/main/generated/torch.qr.html b/main/generated/torch.qr.html
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diff --git a/main/generated/torch.quantile.html b/main/generated/torch.quantile.html
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diff --git a/main/generated/torch.quantize_per_channel.html b/main/generated/torch.quantize_per_channel.html
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diff --git a/main/generated/torch.quantize_per_tensor.html b/main/generated/torch.quantize_per_tensor.html
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diff --git a/main/generated/torch.quantized_batch_norm.html b/main/generated/torch.quantized_batch_norm.html
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diff --git a/main/generated/torch.quantized_max_pool1d.html b/main/generated/torch.quantized_max_pool1d.html
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diff --git a/main/generated/torch.quantized_max_pool2d.html b/main/generated/torch.quantized_max_pool2d.html
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diff --git a/main/generated/torch.quasirandom.SobolEngine.html b/main/generated/torch.quasirandom.SobolEngine.html
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diff --git a/main/generated/torch.rad2deg.html b/main/generated/torch.rad2deg.html
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diff --git a/main/generated/torch.rand.html b/main/generated/torch.rand.html
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diff --git a/main/generated/torch.rand_like.html b/main/generated/torch.rand_like.html
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diff --git a/main/generated/torch.randint.html b/main/generated/torch.randint.html
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diff --git a/main/generated/torch.randint_like.html b/main/generated/torch.randint_like.html
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diff --git a/main/generated/torch.randn.html b/main/generated/torch.randn.html
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diff --git a/main/generated/torch.randn_like.html b/main/generated/torch.randn_like.html
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diff --git a/main/generated/torch.randperm.html b/main/generated/torch.randperm.html
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diff --git a/main/generated/torch.range.html b/main/generated/torch.range.html
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diff --git a/main/generated/torch.ravel.html b/main/generated/torch.ravel.html
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diff --git a/main/generated/torch.real.html b/main/generated/torch.real.html
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diff --git a/main/generated/torch.reciprocal.html b/main/generated/torch.reciprocal.html
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diff --git a/main/generated/torch.remainder.html b/main/generated/torch.remainder.html
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diff --git a/main/generated/torch.renorm.html b/main/generated/torch.renorm.html
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diff --git a/main/generated/torch.repeat_interleave.html b/main/generated/torch.repeat_interleave.html
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diff --git a/main/generated/torch.reshape.html b/main/generated/torch.reshape.html
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diff --git a/main/generated/torch.sum.html b/main/generated/torch.sum.html
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diff --git a/main/generated/torch.svd.html b/main/generated/torch.svd.html
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diff --git a/main/generated/torch.svd_lowrank.html b/main/generated/torch.svd_lowrank.html
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diff --git a/main/generated/torch.swapaxes.html b/main/generated/torch.swapaxes.html
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diff --git a/main/generated/torch.swapdims.html b/main/generated/torch.swapdims.html
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diff --git a/main/generated/torch.sym_float.html b/main/generated/torch.sym_float.html
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diff --git a/main/generated/torch.sym_int.html b/main/generated/torch.sym_int.html
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diff --git a/main/generated/torch.sym_ite.html b/main/generated/torch.sym_ite.html
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diff --git a/main/generated/torch.sym_max.html b/main/generated/torch.sym_max.html
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diff --git a/main/generated/torch.sym_min.html b/main/generated/torch.sym_min.html
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diff --git a/main/generated/torch.sym_not.html b/main/generated/torch.sym_not.html
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diff --git a/main/generated/torch.t.html b/main/generated/torch.t.html
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diff --git a/main/generated/torch.take.html b/main/generated/torch.take.html
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diff --git a/main/generated/torch.take_along_dim.html b/main/generated/torch.take_along_dim.html
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diff --git a/main/generated/torch.tan.html b/main/generated/torch.tan.html
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diff --git a/main/generated/torch.tensor.html b/main/generated/torch.tensor.html
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diff --git a/main/generated/torch.tensordot.html b/main/generated/torch.tensordot.html
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diff --git a/main/generated/torch.tile.html b/main/generated/torch.tile.html
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diff --git a/main/generated/torch.topk.html b/main/generated/torch.topk.html
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diff --git a/main/generated/torch.trace.html b/main/generated/torch.trace.html
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diff --git a/main/generated/torch.transpose.html b/main/generated/torch.transpose.html
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diff --git a/main/generated/torch.trapezoid.html b/main/generated/torch.trapezoid.html
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diff --git a/main/generated/torch.trapz.html b/main/generated/torch.trapz.html
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diff --git a/main/generated/torch.triangular_solve.html b/main/generated/torch.triangular_solve.html
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diff --git a/main/generated/torch.tril.html b/main/generated/torch.tril.html
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diff --git a/main/generated/torch.tril_indices.html b/main/generated/torch.tril_indices.html
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diff --git a/main/generated/torch.triu.html b/main/generated/torch.triu.html
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diff --git a/main/generated/torch.triu_indices.html b/main/generated/torch.triu_indices.html
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@@ -9663,8 +9663,6 @@ <h2 id="R">R</h2>
   </ul></td>
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       <li><a href="elastic/timer.html#torch.distributed.elastic.timer.TimerServer.register_timers">register_timers() (torch.distributed.elastic.timer.TimerServer method)</a>
-</li>
-      <li><a href="library.html#torch.library.register_torch_dispatch">register_torch_dispatch() (in module torch.library)</a>
 </li>
       <li><a href="elastic/multiprocessing.html#torch.distributed.elastic.multiprocessing.api.DefaultLogsSpecs.reify">reify() (torch.distributed.elastic.multiprocessing.api.DefaultLogsSpecs method)</a>
 
diff --git a/main/hub.html b/main/hub.html
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diff --git a/main/library.html b/main/library.html
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@@ -959,50 +959,6 @@ <h2>Extending custom ops (created from Python or C++)<a class="headerlink" href=
 </dl>
 </dd></dl>
 
-<dl class="py function">
-<dt class="sig sig-object py" id="torch.library.register_torch_dispatch">
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-<dd><p>Registers a torch_dispatch rule for the given operator and <code class="docutils literal notranslate"><span class="pre">torch_dispatch_class</span></code>.</p>
-<p>This allows for open registration to specify the behavior between the operator
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-or the operator directly.</p>
-<p>The <code class="docutils literal notranslate"><span class="pre">torch_dispatch_class</span></code> is either a Tensor subclass with <code class="docutils literal notranslate"><span class="pre">__torch_dispatch__</span></code> or a
-TorchDispatchMode.</p>
-<p>If it is a Tensor subclass, we expect <code class="docutils literal notranslate"><span class="pre">func</span></code> to have the following signature:
-<code class="docutils literal notranslate"><span class="pre">(cls,</span> <span class="pre">func:</span> <span class="pre">OpOverload,</span> <span class="pre">types:</span> <span class="pre">Tuple[type,</span> <span class="pre">...],</span> <span class="pre">args,</span> <span class="pre">kwargs)</span> <span class="pre">-&gt;</span> <span class="pre">Any</span></code></p>
-<p>If it is a TorchDispatchMode, we expect <code class="docutils literal notranslate"><span class="pre">func</span></code> to have the following signature:
-<code class="docutils literal notranslate"><span class="pre">(mode,</span> <span class="pre">func:</span> <span class="pre">OpOverload,</span> <span class="pre">types:</span> <span class="pre">Tuple[type,</span> <span class="pre">...],</span> <span class="pre">args,</span> <span class="pre">kwargs)</span> <span class="pre">-&gt;</span> <span class="pre">Any</span></code></p>
-<p><code class="docutils literal notranslate"><span class="pre">args</span></code> and <code class="docutils literal notranslate"><span class="pre">kwargs</span></code> will have been normalized the same way they are
-in <code class="docutils literal notranslate"><span class="pre">__torch_dispatch__</span></code> (see <a class="reference internal" href="notes/extending.html#torch-dispatch-calling-convention"><span class="std std-ref">__torch_dispatch__ calling convention</span></a>).</p>
-<p class="rubric">Examples</p>
-<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">torch</span>
-<span class="go">&gt;&gt;&gt;</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="nd">@torch</span><span class="o">.</span><span class="n">library</span><span class="o">.</span><span class="n">custom_op</span><span class="p">(</span><span class="s2">&quot;mylib::foo&quot;</span><span class="p">,</span> <span class="n">mutates_args</span><span class="o">=</span><span class="p">{})</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">foo</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
-<span class="gp">&gt;&gt;&gt; </span>    <span class="k">return</span> <span class="n">x</span><span class="o">.</span><span class="n">clone</span><span class="p">()</span>
-<span class="go">&gt;&gt;&gt;</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="k">class</span> <span class="nc">MyMode</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">_python_dispatch</span><span class="o">.</span><span class="n">TorchDispatchMode</span><span class="p">):</span>
-<span class="gp">&gt;&gt;&gt; </span>    <span class="k">def</span> <span class="nf">__torch_dispatch__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">types</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="p">(),</span> <span class="n">kwargs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-<span class="gp">&gt;&gt;&gt; </span>        <span class="k">return</span> <span class="n">func</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
-<span class="go">&gt;&gt;&gt;</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="nd">@torch</span><span class="o">.</span><span class="n">library</span><span class="o">.</span><span class="n">register_torch_dispatch</span><span class="p">(</span><span class="s2">&quot;mylib::foo&quot;</span><span class="p">,</span> <span class="n">MyMode</span><span class="p">)</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">_</span><span class="p">(</span><span class="n">mode</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">types</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="gp">&gt;&gt;&gt; </span>    <span class="n">x</span><span class="p">,</span> <span class="o">=</span> <span class="n">args</span>
-<span class="gp">&gt;&gt;&gt; </span>    <span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="mi">1</span>
-<span class="go">&gt;&gt;&gt;</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">foo</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="k">assert</span> <span class="n">torch</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span>
-<span class="go">&gt;&gt;&gt;</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="k">with</span> <span class="n">MyMode</span><span class="p">():</span>
-<span class="gp">&gt;&gt;&gt; </span>    <span class="n">y</span> <span class="o">=</span> <span class="n">foo</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="k">assert</span> <span class="n">torch</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">x</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
-</pre></div>
-</div>
-<dl class="field-list simple">
-</dl>
-</dd></dl>
-
 </div>
 <div class="section" id="low-level-apis">
 <h2>Low-level APIs<a class="headerlink" href="#low-level-apis" title="Permalink to this heading">¶</a></h2>
@@ -1270,7 +1226,6 @@ <h2>Low-level APIs<a class="headerlink" href="#low-level-apis" title="Permalink
 <li><a class="reference internal" href="#torch.library.register_fake"><code class="docutils literal notranslate"><span class="pre">register_fake()</span></code></a></li>
 <li><a class="reference internal" href="#torch.library.impl_abstract"><code class="docutils literal notranslate"><span class="pre">impl_abstract()</span></code></a></li>
 <li><a class="reference internal" href="#torch.library.get_ctx"><code class="docutils literal notranslate"><span class="pre">get_ctx()</span></code></a></li>
-<li><a class="reference internal" href="#torch.library.register_torch_dispatch"><code class="docutils literal notranslate"><span class="pre">register_torch_dispatch()</span></code></a></li>
 </ul>
 </li>
 <li><a class="reference internal" href="#low-level-apis">Low-level APIs</a><ul>
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@@ -1386,26 +1386,6 @@ <h3>Testing Coverage of Overrides for the PyTorch API<a class="headerlink" href=
 Some more exotic functions or features are also registered in other places in the C++ codebase or in user-defined C++ extensions.</p>
 <p>It is also possible to add <cite>new</cite> native functions using <a class="reference internal" href="../library.html#module-torch.library" title="torch.library"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torch.library</span></code></a>. This Python feature allows defining and/or adding new implementations to native functions. This can be used to add missing kernels, replace existing ones or define brand new native functions.</p>
 <p>You can find many examples of <code class="docutils literal notranslate"><span class="pre">__torch_dispatch__</span></code>-based subclasses in the <a class="reference external" href="https://github.com/albanD/subclass_zoo">subclass zoo</a> repo.</p>
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-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@classmethod</span>
-<span class="k">def</span> <span class="nf">__torch_dispatch__</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">types</span><span class="p">,</span> <span class="n">args</span><span class="o">=</span><span class="p">(),</span> <span class="n">kwargs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
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 <div class="section" id="extending-all-torch-api-with-modes">
 <h2>Extending all <a class="reference internal" href="../torch.html#module-torch" title="torch"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torch</span></code></a> API with Modes<a class="headerlink" href="#extending-all-torch-api-with-modes" title="Permalink to this heading">¶</a></h2>
@@ -1550,10 +1530,7 @@ <h2>Extending all <a class="reference internal" href="../torch.html#module-torch
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-</ul>
-</li>
+<li><a class="reference internal" href="#extending-torch-native-api">Extending <code class="xref py py-mod docutils literal notranslate"><span class="pre">torch</span></code> native API</a></li>
 <li><a class="reference internal" href="#extending-all-torch-api-with-modes">Extending all <code class="xref py py-mod docutils literal notranslate"><span class="pre">torch</span></code> API with Modes</a></li>
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 {
-  &#39;pattern&#39;: &lt;function adaptive_avg_pool3d at 0x7ff8fafffa60&gt;,
+  &#39;pattern&#39;: &lt;function adaptive_avg_pool3d at 0x7fec4abffa60&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),
@@ -613,7 +613,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method add of type object at 0x7fec71887900&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),
@@ -638,7 +638,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method avg_pool1d of type object at 0x7fec71887900&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),
@@ -699,7 +699,7 @@ <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.ConvBn1d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7ff8f3fb8d30&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7fec487c2820&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.ConvTranspose1d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm1d&#39;&gt;),
@@ -714,7 +714,7 @@ <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.ConvTranspose1d&#39;&gt;,
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.conv.ConvTranspose1d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7ff8f3fb8ee0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7fec487c29d0&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.linear.Linear&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm1d&#39;&gt;),
@@ -742,7 +742,7 @@ <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.LinearBn1d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_linear_bn at 0x7ff8f3fb8e50&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_linear_bn at 0x7fec487c2940&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm2d&#39;&gt;),
@@ -756,7 +756,7 @@ <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 0x7ff8f3fb8d30&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7fec487c2820&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.ConvTranspose2d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm2d&#39;&gt;),
@@ -771,7 +771,7 @@ <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;,
   &#39;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.conv.ConvTranspose2d&#39;&gt;,
-  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7ff8f3fb8ee0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7fec487c29d0&gt;,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm2d&#39;&gt;,
@@ -795,7 +795,7 @@ <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 0x7ff8f3fb8d30&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn at 0x7fec487c2820&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.ConvTranspose3d&#39;&gt;, &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm3d&#39;&gt;),
@@ -810,7 +810,7 @@ <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 0x7ff8f3fb8ee0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_convtranspose_bn at 0x7fec487c29d0&gt;,
 },
 {
   &#39;pattern&#39;: &lt;class &#39;torch.nn.modules.batchnorm.BatchNorm3d&#39;&gt;,
@@ -843,7 +843,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method cat of type object at 0x7fec71887900&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),
@@ -853,7 +853,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method clamp of type object at 0x7fec71887900&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),
@@ -912,7 +912,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method conv1d of type object at 0x7fec71887900&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),
@@ -954,7 +954,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method conv2d of type object at 0x7fec71887900&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),
@@ -996,7 +996,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method conv3d of type object at 0x7fec71887900&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;reference_quantized_module_for_root&#39;: &lt;class &#39;torch.ao.nn.quantized.reference.modules.conv.ConvTranspose1d&#39;&gt;,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method conv_transpose1d of type object at 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method conv_transpose1d of type object at 0x7fec71887900&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),
@@ -1293,7 +1293,7 @@ <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.ConvTranspose2d&#39;&gt;,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method conv_transpose2d of type object at 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method conv_transpose2d of type object at 0x7fec71887900&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),
@@ -1320,7 +1320,7 @@ <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.ConvTranspose3d&#39;&gt;,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method conv_transpose3d of type object at 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method conv_transpose3d of type object at 0x7fec71887900&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),
@@ -1363,7 +1363,7 @@ <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 0x7ff8fafffaf0&gt;,
+  &#39;pattern&#39;: &lt;function dropout at 0x7fec4abffaf0&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),
@@ -1383,7 +1383,7 @@ <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 0x7ff8faf83160&gt;,
+  &#39;pattern&#39;: &lt;function elu at 0x7fec4ab85160&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),
@@ -1467,7 +1467,7 @@ <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.sparse.EmbeddingBag&#39;&gt;,
 },
 {
-  &#39;pattern&#39;: &lt;built-in method flatten of type object at 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method flatten of type object at 0x7fec71887900&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),
@@ -1487,7 +1487,7 @@ <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 0x7ff8faf850d0&gt;,
+  &#39;pattern&#39;: &lt;function group_norm at 0x7fec4ab870d0&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),
@@ -1552,7 +1552,7 @@ <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 0x7ff8faf83940&gt;,
+  &#39;pattern&#39;: &lt;function hardsigmoid at 0x7fec4ab85940&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),
@@ -1592,7 +1592,7 @@ <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 0x7ff8faf83af0&gt;,
+  &#39;pattern&#39;: &lt;function hardswish at 0x7fec4ab85af0&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 +1612,7 @@ <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 0x7ff8faf83040&gt;,
+  &#39;pattern&#39;: &lt;function hardtanh at 0x7fec4ab85040&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),
@@ -1642,7 +1642,7 @@ <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 0x7ff8faf83ee0&gt;,
+  &#39;pattern&#39;: &lt;function instance_norm at 0x7fec4ab85ee0&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),
@@ -1683,7 +1683,7 @@ <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 0x7ff8faf0f5e0&gt;,
+  &#39;pattern&#39;: &lt;function interpolate at 0x7fec4ab125e0&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),
@@ -1705,7 +1705,7 @@ <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 0x7ff8faf83f70&gt;,
+  &#39;pattern&#39;: &lt;function layer_norm at 0x7fec4ab85f70&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),
@@ -1728,7 +1728,7 @@ <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 0x7ff8faf83310&gt;,
+  &#39;pattern&#39;: &lt;function leaky_relu at 0x7fec4ab85310&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),
@@ -1980,7 +1980,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method matmul of type object at 0x7fec71887900&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),
@@ -2050,7 +2050,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method mean of type object at 0x7fec71887900&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),
@@ -2085,7 +2085,7 @@ <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 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method mul of type object at 0x7fec71887900&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),
@@ -2100,7 +2100,7 @@ <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 narrow of type object at 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method narrow of type object at 0x7fec71887900&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),
@@ -2130,7 +2130,7 @@ <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 pixel_shuffle of type object at 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method pixel_shuffle of type object at 0x7fec71887900&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),
@@ -2150,7 +2150,7 @@ <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 pixel_unshuffle of type object at 0x7ff921f25900&gt;,
+  &#39;pattern&#39;: &lt;built-in method pixel_unshuffle of type object at 0x7fec71887900&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),
@@ -2181,10 +2181,10 @@ <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 0x7ff929133430&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fec78a95430&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv1d&#39;&gt;, &lt;function relu at 0x7ff8fafffee0&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv1d&#39;&gt;, &lt;function relu at 0x7fec4abffee0&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),
@@ -2195,10 +2195,10 @@ <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 0x7ff8f31004c0&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fec42a58550&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method conv1d of type object at 0x7ff921f25900&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv1d of type object at 0x7fec71887900&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),
@@ -2210,7 +2210,7 @@ <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 0x7ff921f25900&gt;, &lt;function relu at 0x7ff8fafffee0&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv1d of type object at 0x7fec71887900&gt;, &lt;function relu at 0x7fec4abffee0&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),
@@ -2233,10 +2233,10 @@ <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 0x7ff8f3fb8dc0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fec487c28b0&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 0x7ff8fafffee0&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 0x7fec4abffee0&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),
@@ -2248,7 +2248,7 @@ <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 0x7ff8f3fb8dc0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fec487c28b0&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
@@ -2262,10 +2262,10 @@ <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 0x7ff8f3100550&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fec42a585e0&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;, &lt;function relu at 0x7ff8fafffee0&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv2d&#39;&gt;, &lt;function relu at 0x7fec4abffee0&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),
@@ -2276,10 +2276,10 @@ <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 0x7ff8f31005e0&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fec42a58670&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method conv2d of type object at 0x7ff921f25900&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv2d of type object at 0x7fec71887900&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),
@@ -2291,7 +2291,7 @@ <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 0x7ff921f25900&gt;, &lt;function relu at 0x7ff8fafffee0&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv2d of type object at 0x7fec71887900&gt;, &lt;function relu at 0x7fec4abffee0&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),
@@ -2314,10 +2314,10 @@ <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 0x7ff8f3fb8dc0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fec487c28b0&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 0x7ff8fafffee0&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 0x7fec4abffee0&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),
@@ -2329,7 +2329,7 @@ <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 0x7ff8f3fb8dc0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fec487c28b0&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv3d&#39;&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
@@ -2343,10 +2343,10 @@ <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 0x7ff8f3100670&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fec42a58700&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv3d&#39;&gt;, &lt;function relu at 0x7ff8fafffee0&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.conv.Conv3d&#39;&gt;, &lt;function relu at 0x7fec4abffee0&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),
@@ -2357,10 +2357,10 @@ <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 0x7ff8f3100700&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fec42a58790&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;built-in method conv3d of type object at 0x7ff921f25900&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv3d of type object at 0x7fec71887900&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),
@@ -2372,7 +2372,7 @@ <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 0x7ff921f25900&gt;, &lt;function relu at 0x7ff8fafffee0&gt;),
+  &#39;pattern&#39;: (&lt;built-in method conv3d of type object at 0x7fec71887900&gt;, &lt;function relu at 0x7fec4abffee0&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),
@@ -2395,10 +2395,10 @@ <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 0x7ff8f3fb8dc0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fec487c28b0&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 0x7ff8fafffee0&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 0x7fec4abffee0&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),
@@ -2410,7 +2410,7 @@ <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 0x7ff8f3fb8dc0&gt;,
+  &#39;fuser_method&#39;: &lt;function fuse_conv_bn_relu at 0x7fec487c28b0&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.linear.Linear&#39;&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
@@ -2438,10 +2438,10 @@ <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 0x7ff8f3100790&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fec42a58820&gt;,
 },
 {
-  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.linear.Linear&#39;&gt;, &lt;function relu at 0x7ff8fafffee0&gt;),
+  &#39;pattern&#39;: (&lt;class &#39;torch.nn.modules.linear.Linear&#39;&gt;, &lt;function relu at 0x7fec4abffee0&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),
@@ -2466,7 +2466,7 @@ <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 0x7ff8f3100820&gt;,
+  &#39;fuser_method&#39;: &lt;function _sequential_wrapper2.&lt;locals&gt;.fuser_method at 0x7fec42a588b0&gt;,
 },
 {
   &#39;pattern&#39;: (&lt;built-in function linear&gt;, &lt;class &#39;torch.nn.modules.activation.ReLU&#39;&gt;),
@@ -2495,7 +2495,7 @@ <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 0x7ff8fafffee0&gt;),
+  &#39;pattern&#39;: (&lt;built-in function linear&gt;, &lt;function relu at 0x7fec4abffee0&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),
@@ -2536,7 +2536,7 @@ <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 0x7ff8fafffee0&gt;),
+  &#39;pattern&#39;: (&lt;built-in function add&gt;, &lt;function relu at 0x7fec4abffee0&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),
@@ -2551,7 +2551,7 @@ <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 0x7ff921f25900&gt;),
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 {
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diff --git a/main/quantization-support.html b/main/quantization-support.html
index c0f9c71e1c..25d79af4f8 100644
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index cb64a43097..0607579b13 100644
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index b8a9594505..97797ca9db 100644
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1737, 1782, 1969, 2047, 2048, 2050, 2052, 2053, 2054, 2057, 2064, 2065, 2071, 2073, 2074, 2081, 2082, 2096, 2102, 2105, 2106, 2109], "op": [1, 4, 5, 24, 28, 30, 33, 52, 53, 55, 64, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 80, 84, 88, 89, 152, 505, 526, 606, 760, 795, 796, 797, 826, 829, 858, 865, 866, 897, 904, 907, 909, 910, 918, 966, 976, 978, 1015, 1031, 1033, 1037, 1038, 1052, 1053, 1079, 1083, 1085, 1168, 1225, 1275, 1288, 1290, 1291, 1346, 1352, 1402, 1406, 1411, 1412, 1413, 1547, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1796, 1797, 1798, 1799, 1800, 1801, 1818, 1876, 1955, 1987, 1990, 1992, 1994, 1995, 2007, 2010, 2011, 2016, 2020, 2026, 2027, 2030, 2033, 2035, 2038, 2039, 2049, 2050, 2052, 2053, 2063, 2069, 2074, 2075, 2076, 2077, 2078, 2079, 2086, 2088, 2090, 2092, 2097, 2102, 2103, 2107, 2108, 2109, 2110, 2112, 2115, 2116, 2117], "directli": [1, 3, 7, 9, 14, 15, 23, 24, 28, 30, 33, 34, 35, 36, 37, 46, 52, 53, 55, 59, 64, 66, 79, 559, 735, 750, 894, 904, 907, 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1716, 1717, 1718, 1720, 1721, 1734, 1735, 1737, 1738, 1740, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1797, 1798, 1799, 1800, 1801, 1969, 1971, 2024, 2033, 2037, 2050, 2052, 2053, 2060, 2061, 2066, 2069, 2071, 2074, 2081, 2098, 2105, 2107, 2110, 2113], "activ": [1, 5, 7, 9, 33, 34, 50, 52, 55, 61, 81, 83, 795, 797, 799, 806, 810, 845, 846, 855, 865, 866, 1019, 1035, 1048, 1066, 1167, 1169, 1179, 1347, 1438, 1468, 1469, 1470, 1474, 1484, 1502, 1529, 1531, 1549, 1560, 1574, 1576, 1578, 1629, 1667, 1691, 1720, 1738, 1740, 1770, 1775, 1980, 2016, 2030, 2037, 2050, 2053, 2054, 2056, 2061, 2071, 2073, 2075, 2076, 2077, 2078, 2081, 2086, 2096, 2097, 2102, 2107, 2112, 2117], "emit_nvtx": [1, 4, 1026], "vtune": [1, 4], "emit_itt": [1, 4], "use_cuda": [1, 2075], "use_devic": 1, "record_shap": [1, 2075], "with_flop": [1, 2075], "profile_memori": [1, 2075], "with_stack": [1, 2075], "with_modul": [1, 2075], "use_kineto": 1, "use_cpu": 1, "experimental_config": [1, 2075], "hold": [1, 28, 30, 45, 47, 50, 51, 52, 55, 59, 63, 64, 539, 1347, 1476, 1531, 1532, 1540, 1541, 1582, 1710, 1720, 1722, 1723, 1737, 1747, 1761, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1913, 1914, 1915, 1916, 1917, 1918, 2048, 2050, 2053, 2055, 2060, 2063, 2073, 2075, 2081, 2082, 2083, 2085, 2086, 2088, 2089, 2091, 2092, 2104, 2105, 2108], "summari": [1, 3, 48, 1026, 1067, 1878, 2016, 2033, 2056, 2091, 2097, 2105, 2111, 2117, 2119], "hood": [1, 52, 63, 2037, 2047, 2050, 2052, 2063, 2074, 2083, 2106, 2107], "just": [1, 2, 7, 14, 24, 28, 35, 37, 45, 52, 64, 591, 690, 700, 793, 826, 829, 893, 895, 909, 910, 932, 936, 991, 992, 1187, 1189, 1197, 1290, 1291, 1329, 1332, 1337, 1338, 1364, 1468, 1469, 1470, 1474, 1720, 1740, 1741, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1802, 1870, 1956, 1957, 1958, 1959, 1969, 2015, 2017, 2037, 2046, 2047, 2053, 2054, 2058, 2060, 2061, 2062, 2066, 2074, 2081, 2082, 2086, 2089, 2090, 2092, 2097, 2102, 2103, 2104, 2105, 2106, 2107, 2108, 2116], "record": [1, 5, 19, 20, 32, 38, 39, 40, 41, 45, 48, 52, 63, 64, 447, 448, 449, 450, 451, 488, 498, 822, 823, 824, 825, 828, 830, 869, 942, 945, 954, 1011, 1012, 1014, 1111, 1112, 1113, 1123, 1128, 1146, 1164, 1165, 1166, 1198, 1232, 1233, 1274, 1290, 1294, 1345, 1361, 1387, 1390, 1391, 1466, 1530, 1779, 1780, 1782, 1839, 1840, 1841, 1842, 1843, 1844, 1845, 1846, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1913, 1914, 1915, 1916, 1917, 1918, 1946, 1985, 1986, 2013, 2014, 2017, 2019, 2028, 2040, 2046, 2047, 2050, 2053, 2056, 2068, 2069, 2071, 2075, 2081, 2091, 2092, 2093, 2095, 2096, 2097, 2102, 2104, 2105, 2108, 2117, 2119, 2121], "event": [1, 31, 35, 37, 46, 50, 63, 488, 936, 937, 938, 1012, 1014, 1066, 1069, 1290, 1291, 1352, 1390, 1391, 1688, 1986, 2016, 2033, 2037, 2050, 2075, 2091, 2115, 2119, 2121], "being": [1, 3, 5, 9, 11, 12, 19, 20, 23, 28, 30, 32, 33, 35, 37, 40, 41, 47, 48, 50, 52, 53, 55, 59, 60, 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2054, 2064, 2066, 2076, 2081, 2086, 2102, 2107, 2108, 2110], "notic": [1, 12, 28, 53, 65, 692, 1130, 1144, 1183, 1369, 1379, 1442, 1583, 1653, 1803, 1804, 1809, 1810, 1816, 1964, 2016, 2017, 2047, 2086, 2105, 2108, 2111, 2113, 2115], "fit": [1, 9, 39, 59, 60, 501, 936, 1271, 1790, 1852, 2050, 2069, 2093, 2117], "evalu": [1, 4, 8, 9, 32, 35, 52, 58, 64, 696, 702, 801, 867, 923, 1066, 1174, 1175, 1187, 1189, 1209, 1210, 1213, 1274, 1434, 1438, 1444, 1445, 1446, 1467, 1484, 1492, 1493, 1494, 1502, 1530, 1544, 1549, 1570, 1680, 1688, 1703, 1738, 1790, 1806, 1837, 2020, 2021, 2053, 2061, 2068, 2069, 2086, 2095, 2098, 2104, 2106, 2107], "saved_tensors_hook": [1, 904, 907, 909, 2047], "pack_hook": [1, 2047], "unpack_hook": [1, 2047], "pair": [1, 28, 30, 34, 35, 47, 50, 52, 619, 738, 869, 943, 964, 998, 1144, 1185, 1189, 1288, 1338, 1376, 1522, 1531, 1536, 1540, 1677, 1799, 1846, 2019, 2020, 2026, 2038, 2047, 2050, 2081, 2082, 2083, 2091, 2093, 2097, 2108, 2115], "retriev": [1, 23, 24, 28, 32, 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1714, 1715, 1716, 1717, 1718, 1720, 1747, 1751, 1779, 1839, 1841, 1843, 1846, 1870, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 2013, 2017, 2020, 2021, 2024, 2032, 2041, 2046, 2053, 2060, 2061, 2063, 2065, 2066, 2076, 2081, 2082, 2083, 2086, 2089, 2091, 2105, 2106, 2107, 2108, 2109, 2116, 2117], "overridden": [2, 5, 14, 64, 893, 894, 895, 909, 910, 1052, 1530, 1906, 2020, 2047, 2053, 2064, 2117, 2118], "achiev": [2, 19, 23, 24, 28, 30, 34, 35, 48, 55, 1110, 1175, 1274, 1443, 1449, 1530, 1536, 1537, 1609, 1638, 1720, 2034, 2050, 2060, 2063, 2074, 2081, 2083, 2117], "better": [2, 3, 7, 8, 9, 14, 23, 27, 28, 37, 52, 59, 919, 976, 1079, 1167, 1171, 1172, 1183, 1261, 1290, 1465, 1564, 1688, 1694, 1720, 1727, 1728, 1812, 1837, 2020, 2046, 2047, 2049, 2050, 2056, 2058, 2065, 2067, 2071, 2073, 2075, 2076, 2077, 2086, 2091, 2097, 2099, 2103, 2105, 2106, 2114], "select": [2, 5, 15, 17, 19, 21, 23, 28, 30, 35, 37, 45, 53, 315, 317, 319, 323, 763, 966, 1000, 1002, 1006, 1015, 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1311, 1332, 2016, 2025], "decid": [2, 4, 7, 28, 37, 47, 59, 488, 1185, 1751, 2027, 2071, 2086, 2107, 2108, 2111], "pick": [2, 28, 46, 48, 515, 976, 2047, 2081, 2104, 2106, 2111], "torch_linalg_prefer_cusolv": 2, "linalg": [2, 11, 408, 966, 967, 968, 969, 1008, 1096, 1218, 1252, 1355, 1364, 1365, 1366, 1370, 1371, 1734, 1735, 1740, 1775, 1817, 1822, 1824, 1830, 1900, 1931, 1932, 1955, 1977, 2016], "inv": [2, 35, 1252, 1306, 1310, 1316, 1332, 1336, 1340], "inv_ex": [2, 1315], "cholesky_ex": [2, 1304], "lu_factor": [2, 1323, 1324, 1364, 1365, 1366], "lu": [2, 10, 1316, 1322, 1323, 1324, 1365, 1366, 2018], "eigh": [2, 1304, 1310, 1313, 1332, 1338, 2064], "eighval": 2, "svdval": [2, 1306, 1320, 1329, 1338, 1931, 2064], "_linalgbackend": 2, "sdpaparam": 2, "flash_sdp_en": 2, "flash": [2, 1589, 1594], "scale": [2, 7, 23, 33, 35, 37, 46, 48, 99, 175, 475, 477, 619, 688, 692, 693, 694, 741, 742, 743, 744, 745, 746, 747, 752, 753, 754, 755, 756, 757, 758, 759, 762, 773, 775, 776, 777, 778, 780, 783, 784, 798, 802, 805, 822, 823, 824, 825, 828, 944, 1124, 1125, 1128, 1146, 1178, 1179, 1361, 1438, 1467, 1472, 1473, 1474, 1490, 1502, 1558, 1583, 1584, 1585, 1589, 1594, 1627, 1628, 1629, 1645, 1647, 1688, 1689, 1694, 1785, 1806, 1832, 1833, 1834, 1835, 1836, 1909, 1910, 1928, 1980, 2016, 2018, 2039, 2045, 2050, 2055, 2057, 2061, 2069, 2076, 2077, 2079, 2087, 2108], "product": [2, 15, 28, 30, 35, 47, 152, 689, 692, 693, 694, 763, 897, 902, 913, 915, 916, 917, 918, 944, 956, 962, 966, 994, 1008, 1020, 1068, 1073, 1087, 1088, 1091, 1107, 1110, 1174, 1178, 1179, 1251, 1295, 1307, 1314, 1340, 1341, 1343, 1369, 1376, 1379, 1418, 1481, 1482, 1500, 1501, 1589, 1594, 1635, 1688, 1734, 1818, 1819, 1828, 1874, 1948, 1963, 1977, 1980, 2016, 2017, 2038, 2047, 2058, 2060, 2064, 2074, 2076, 2086, 2105, 2119], "attent": [2, 7, 34, 738, 1443, 1536, 1574, 1576, 1578, 1589, 1591, 1609, 1688, 2016, 2067, 2090, 2105], "enable_mem_efficient_sdp": [2, 1688], "mem_efficient_sdp_en": 2, 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2074, 2104, 2105, 2108, 2115, 2117, 2120], "scaled_dot_product_attent": [2, 1536, 1574, 1590, 1593, 1594, 2018, 2042, 2043, 2044, 2072], "_sdpaparam": 2, "kei": [2, 3, 23, 30, 33, 37, 45, 47, 48, 52, 53, 55, 62, 64, 417, 605, 683, 738, 858, 863, 931, 936, 943, 1076, 1167, 1177, 1190, 1274, 1290, 1291, 1346, 1530, 1531, 1536, 1540, 1574, 1575, 1576, 1577, 1578, 1591, 1688, 1754, 1770, 1969, 1971, 2016, 2018, 2019, 2020, 2024, 2032, 2050, 2053, 2060, 2061, 2066, 2071, 2072, 2073, 2075, 2076, 2079, 2081, 2082, 2088, 2091, 2093, 2096, 2098, 2109, 2114, 2115, 2116, 2120], "mask": [2, 45, 401, 402, 403, 404, 405, 546, 738, 923, 924, 1368, 1438, 1449, 1474, 1536, 1574, 1575, 1576, 1577, 1578, 1629, 1688, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1750, 1751, 1752, 1754, 1755, 1756, 1757, 1801, 2016, 2018, 2038, 2039, 2086, 2108], "dropout": [2, 5, 34, 64, 737, 738, 763, 1274, 1438, 1468, 1469, 1470, 1474, 1481, 1500, 1530, 1536, 1546, 1547, 1574, 1576, 1578, 1602, 1622, 1623, 1624, 1629, 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8, 9, 10, 35, 52, 64, 1490, 1647, 2027, 2047, 2053, 2056, 2061, 2065, 2081, 2083, 2086, 2105, 2106], "docstr": [3, 14, 64, 865, 866, 1274, 1530, 2015, 2050], "adapt": [3, 52, 769, 770, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1467, 1595, 1596, 1597, 1598, 1599, 1600, 1785, 1786, 1797, 1799, 1806, 2035, 2050, 2069, 2104], "field": [3, 7, 19, 28, 30, 32, 37, 40, 44, 45, 53, 55, 64, 490, 829, 897, 898, 941, 1272, 1274, 1434, 1442, 1443, 1463, 1465, 1489, 1495, 1496, 1521, 1522, 1530, 1533, 1534, 1535, 1537, 1544, 1562, 1563, 1579, 1601, 1608, 1609, 1619, 1636, 1648, 1672, 1680, 1761, 1795, 1801, 2033, 2047, 2052, 2063, 2071, 2081, 2082, 2091, 2105, 2116, 2117], "displai": [3, 18, 33, 1054, 1067, 1189, 1647, 1707, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 2015, 2021, 2026, 2031, 2071, 2091, 2093, 2099, 2108, 2117, 2120], "instruct": [3, 4, 11, 14, 50, 63, 683, 1874, 2017, 2020, 2050, 2064, 2071, 2076, 2093, 2101, 2105, 2107, 2117], "count": [3, 20, 23, 35, 44, 52, 64, 898, 932, 941, 947, 997, 1048, 1164, 1236, 1237, 1272, 1312, 1313, 1761, 1814, 1964, 1965, 2018, 2033, 2050, 2056, 2072, 2075, 2081, 2083, 2085, 2086, 2108, 2117], "wall": [3, 2111], "callgrind": 3, "analog": [3, 52, 64, 488, 697, 919, 1093, 1131, 1133, 1324, 1500, 1800, 1931, 1949, 2040, 2061, 2104], "constructor": [3, 14, 23, 24, 32, 47, 55, 64, 66, 75, 827, 865, 866, 1434, 1535, 1540, 1541, 1559, 1584, 1585, 1720, 1768, 1906, 2016, 2017, 2020, 2021, 2050, 2052, 2061, 2081, 2086, 2088, 2089, 2092, 2122], "snippet": [3, 48, 2015, 2061, 2066, 2099, 2110], "loop": [3, 19, 24, 30, 33, 50, 52, 53, 56, 60, 61, 64, 66, 71, 866, 867, 918, 1055, 1058, 1060, 1173, 1179, 1290, 1720, 1738, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1980, 2017, 2018, 2020, 2033, 2049, 2050, 2055, 2058, 2061, 2064, 2068, 2071, 2073, 2075, 2076, 2091, 2102, 2105, 2107, 2116], "callabl": [3, 5, 12, 23, 24, 28, 32, 33, 35, 37, 40, 45, 50, 52, 53, 55, 63, 64, 121, 400, 845, 976, 978, 990, 1052, 1053, 1055, 1168, 1169, 1170, 1175, 1178, 1179, 1274, 1277, 1280, 1286, 1290, 1346, 1347, 1530, 1574, 1576, 1578, 1580, 1713, 1720, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1795, 1797, 1798, 1799, 1800, 1801, 1808, 1811, 1980, 2015, 2017, 2019, 2020, 2021, 2024, 2033, 2050, 2053, 2061, 2066, 2069, 2071, 2074, 2075, 2081, 2093, 2096, 2097, 2103, 2106, 2109, 2116, 2118], "present": [3, 9, 23, 28, 30, 47, 53, 55, 898, 941, 943, 1223, 1272, 1274, 1364, 1434, 1500, 1530, 1540, 1761, 1781, 1927, 2015, 2031, 2037, 2038, 2039, 2046, 2047, 2050, 2053, 2058, 2061, 2066, 2071, 2074, 2082, 2085, 2086, 2089, 2105, 2109, 2113, 2119], "default_tim": 3, "dict": [3, 5, 12, 23, 24, 28, 29, 30, 32, 33, 34, 35, 37, 41, 45, 50, 52, 53, 55, 57, 59, 62, 64, 417, 683, 795, 796, 797, 818, 819, 820, 839, 858, 925, 932, 943, 976, 990, 1052, 1053, 1066, 1076, 1167, 1177, 1179, 1187, 1272, 1273, 1274, 1275, 1281, 1286, 1290, 1291, 1346, 1347, 1466, 1476, 1530, 1531, 1540, 1582, 1710, 1720, 1751, 1770, 1783, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1792, 1793, 1794, 1797, 1798, 1799, 1800, 1801, 1802, 1803, 1804, 1805, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1815, 1816, 1980, 1994, 2015, 2017, 2018, 2020, 2021, 2024, 2031, 2033, 2053, 2061, 2066, 2069, 2071, 2072, 2073, 2081, 2082, 2091, 2096, 2097, 2106, 2113, 2116, 2118], "summar": [3, 4, 48, 1878, 2020, 2040, 2056, 2073, 2086, 2105, 2106, 2117], "relu": [3, 24, 33, 52, 60, 61, 64, 703, 704, 708, 709, 710, 711, 712, 713, 714, 718, 719, 720, 721, 722, 723, 726, 727, 728, 729, 730, 731, 732, 768, 795, 796, 817, 858, 864, 1052, 1169, 1179, 1280, 1286, 1530, 1546, 1548, 1559, 1567, 1574, 1576, 1578, 1684, 1686, 1710, 1782, 1980, 2017, 2018, 2030, 2039, 2040, 2045, 2047, 2061, 2066, 2071, 2072, 2076, 2078, 2079, 2099, 2103, 2110, 2112, 2115, 2116, 2117], "readabl": [3, 13, 23, 45, 52, 64, 1054, 1067, 1946, 2071, 2073, 2106, 2117, 2118], "supplement": 3, "disambigu": [3, 45, 64, 1352, 2117], "ident": [3, 14, 23, 28, 30, 35, 64, 791, 817, 923, 924, 1098, 1202, 1312, 1313, 1314, 1315, 1328, 1340, 1343, 1347, 1364, 1421, 1422, 1438, 1467, 1677, 1727, 1728, 1734, 1737, 1973, 1977, 1983, 2021, 2045, 2064, 2065, 2074, 2078, 2086, 2107, 2117], "easi": [3, 23, 28, 30, 33, 47, 52, 1185, 2017, 2047, 2055, 2060, 2061, 2063, 2074, 2076, 2081, 2082, 2086, 2103, 2106, 2108, 2110], "differenti": [3, 35, 56, 61, 152, 354, 591, 805, 893, 895, 897, 902, 903, 904, 906, 909, 910, 912, 913, 914, 915, 916, 917, 918, 923, 924, 973, 1055, 1172, 1173, 1174, 1178, 1289, 1321, 1322, 1333, 1364, 1448, 1449, 1472, 1638, 1673, 1720, 1740, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1968, 2016, 2027, 2053, 2055, 2058, 2071, 2073, 2081, 2092, 2108], "distinguish": [3, 1188, 2076, 2086], "princip": [3, 1321, 1820], "signal": [3, 11, 30, 37, 47, 50, 741, 742, 743, 769, 770, 785, 786, 1126, 1127, 1128, 1129, 1131, 1132, 1133, 1134, 1135, 1136, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1271, 1337, 1431, 1432, 1433, 1435, 1436, 1437, 1439, 1440, 1441, 1457, 1458, 1459, 1477, 1478, 1497, 1498, 1499, 1518, 1523, 1524, 1525, 1584, 1585, 1595, 1596, 1597, 1598, 1599, 1600, 1603, 1611, 1614, 1631, 1632, 1654, 1657, 1658, 1659, 1661, 1662, 1663, 1927, 2016, 2037, 2063, 2075, 2081], "form": [3, 7, 9, 11, 23, 28, 33, 35, 46, 47, 48, 52, 53, 55, 60, 64, 763, 782, 788, 967, 1098, 1138, 1140, 1182, 1185, 1274, 1314, 1317, 1322, 1333, 1338, 1432, 1433, 1436, 1437, 1449, 1477, 1478, 1481, 1500, 1530, 1546, 1582, 1583, 1620, 1631, 1632, 1635, 1647, 1675, 1688, 1707, 1740, 1800, 1802, 1814, 1815, 1818, 1948, 2015, 2017, 2021, 2040, 2047, 2053, 2061, 2069, 2071, 2074, 2076, 2086, 2091, 2105, 2106, 2110, 2116], "treat": [3, 35, 46, 52, 58, 64, 66, 71, 72, 323, 473, 796, 923, 924, 978, 1052, 1167, 1203, 1274, 1327, 1330, 1332, 1344, 1346, 1356, 1357, 1358, 1359, 1376, 1424, 1473, 1483, 1502, 1534, 1535, 1536, 1537, 1540, 1545, 1559, 1564, 1628, 1719, 1720, 1770, 1774, 1806, 1859, 1874, 1927, 1942, 1943, 1949, 1964, 2019, 2020, 2038, 2040, 2047, 2069, 2071, 2081, 2086, 2089, 2097, 2105, 2108, 2109, 2113, 2116], "distinct": [3, 11, 82, 1167, 1310, 1311, 1355, 1443, 2020, 2053, 2066, 2071, 2073, 2081, 2082, 2104], "workload": [3, 8, 19, 23, 28, 55, 1055, 2050, 2056, 2060, 2064, 2075, 2081, 2101, 2115], "good": [3, 7, 8, 14, 64, 976, 1171, 1196, 1538, 1814, 1894, 2015, 2024, 2037, 2050, 2053, 2056, 2060, 2061, 2063, 2071, 2074, 2076, 2104, 2105, 2106, 2107, 2114], "intrins": [3, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 795, 796, 2077, 2078], "contrast": [3, 35, 37, 52, 763, 1185, 1481, 1800, 2045, 2047, 2054, 2056, 2086, 2112], "adaptive_autorang": 3, "threshold": [3, 24, 64, 1329, 1332, 1490, 1562, 1567, 1696, 1702, 1814, 1878, 2018, 2046, 2050, 2072, 2091], "min_run_tim": 3, "01": [3, 29, 32, 50, 490, 758, 783, 824, 825, 1111, 1153, 1516, 1651, 1652, 1710, 1782, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1806, 1812, 1832, 1885, 1887, 1888, 1893, 1894, 2018, 2045, 2060, 2071, 2073, 2112], "max_run_tim": 3, "callback": [3, 24, 37, 50, 63, 64, 1720, 2033, 2053, 2060, 2075, 2081], "similar": [3, 7, 9, 11, 20, 23, 28, 33, 35, 44, 53, 55, 60, 63, 64, 495, 517, 715, 716, 717, 718, 719, 720, 723, 733, 734, 735, 736, 748, 749, 759, 767, 805, 881, 896, 909, 910, 957, 962, 975, 976, 1156, 1157, 1274, 1463, 1464, 1476, 1489, 1492, 1493, 1494, 1530, 1579, 1618, 1761, 1775, 1776, 1801, 1824, 1852, 1859, 1908, 1943, 1949, 1965, 2019, 2020, 2037, 2038, 2040, 2047, 2049, 2050, 2053, 2054, 2058, 2064, 2071, 2074, 2076, 2081, 2082, 2086, 2087, 2092, 2104, 2107, 2108, 2110, 2113, 2117, 2122], "blocked_autorang": 3, "variablil": 3, "until": [3, 5, 7, 23, 24, 28, 30, 32, 37, 47, 55, 63, 64, 488, 1011, 1012, 1014, 1046, 1164, 1295, 1347, 1387, 1390, 1391, 1636, 1710, 1720, 1803, 1805, 1809, 1949, 1985, 1986, 1999, 2032, 2037, 2045, 2050, 2055, 2056, 2057, 2066, 2069, 2071, 2075, 2081, 2083, 2088, 2102, 2105, 2108], "iqr": 3, "smaller": [3, 19, 23, 64, 501, 547, 998, 1500, 1720, 1814, 1829, 1874, 1919, 2050, 2066, 2074, 2103, 2119, 2122], "reach": [3, 7, 8, 9, 23, 24, 28, 29, 37, 47, 52, 56, 1347, 1720, 1803, 1806, 1809, 1810, 2047, 2053, 2063, 2077, 2081, 2106], "At": [3, 5, 6, 7, 15, 17, 19, 23, 33, 1144, 1444, 1445, 1446, 1457, 1458, 1459, 1460, 1461, 1462, 1497, 1498, 1499, 1969, 1973, 2030, 2040, 2049, 2058, 2076, 2081, 2087, 2105, 2106, 2108, 2117], "high": [3, 4, 7, 8, 9, 10, 15, 24, 28, 35, 37, 44, 46, 48, 64, 121, 1449, 1577, 1841, 1842, 1874, 1973, 2018, 2028, 2033, 2035, 2037, 2053, 2058, 2059, 2061, 2062, 2063, 2073, 2076, 2077, 2081, 2086, 2091, 2092, 2093, 2097, 2101, 2102, 2105, 2112, 2117, 2120, 2121], "pseudo": [3, 90], "block_siz": 3, "enough_data": 3, "len": [3, 23, 30, 64, 66, 71, 220, 547, 696, 698, 699, 702, 1129, 1133, 1136, 1140, 1143, 1147, 1178, 1278, 1341, 1362, 1374, 1421, 1424, 1466, 1675, 1746, 1748, 1764, 1805, 1812, 1916, 1919, 1925, 1926, 1930, 1974, 1975, 1976, 2017, 2018, 2020, 2053, 2072, 2085, 2086, 2091, 2105, 2116], "small_iqr": 3, "break": [3, 7, 28, 35, 58, 64, 683, 897, 976, 978, 1189, 1274, 1320, 1530, 1859, 1878, 2016, 2021, 2026, 2028, 2052, 2073, 2086, 2095, 2099, 2102, 2104, 2106, 2109, 2111, 2113], "stop": [3, 5, 28, 35, 37, 47, 48, 50, 53, 869, 898, 941, 1048, 1189, 1272, 1347, 1449, 1761, 1814, 2017, 2020, 2075, 2081, 2085, 2105, 2109], "repetit": [3, 1852, 1949], "statist": [3, 24, 28, 35, 802, 803, 823, 824, 825, 827, 828, 1020, 1058, 1060, 1061, 1062, 1064, 1066, 1067, 1068, 1073, 1074, 1075, 1076, 1087, 1088, 1352, 1444, 1445, 1446, 1484, 1492, 1493, 1494, 1502, 1503, 1504, 1505, 1512, 1513, 1514, 1570, 2033, 2047, 2055, 2073, 2076, 2079, 2108, 2117], "minimum": [3, 14, 19, 24, 47, 48, 52, 699, 700, 774, 798, 823, 824, 825, 828, 829, 879, 947, 1090, 1157, 1235, 1236, 1237, 1377, 1449, 1488, 1580, 1804, 1805, 1812, 1894, 1913, 1914, 1915, 1916, 1917, 1918, 2018, 2045, 2047, 2058, 2072, 2079, 2089, 2112], "total_tim": 3, "choic": [3, 8, 9, 28, 1290, 1338, 1531, 1540, 1837, 2049, 2071, 2079, 2086, 2104, 2105, 2117], "block": [3, 7, 8, 20, 23, 28, 30, 32, 34, 47, 50, 55, 63, 64, 488, 585, 586, 587, 939, 955, 1011, 1066, 1295, 1347, 1457, 1458, 1459, 1460, 1461, 1462, 1476, 1506, 1507, 1508, 1509, 1510, 1511, 1533, 1582, 1630, 1706, 1720, 1913, 1914, 1915, 2017, 2019, 2020, 2033, 2037, 2041, 2047, 2050, 2052, 2056, 2058, 2071, 2076, 2081, 2086, 2098, 2115, 2119, 2121], "qualiti": [3, 7, 24], "balanc": [3, 976], "compet": [3, 2063], "amort": 3, "invoc": [3, 5, 64, 845, 976, 981, 1187, 1277, 1290, 2017, 2020, 2050, 2053, 2060, 2071, 2081, 2083, 2102, 2115], "less": [3, 6, 7, 14, 23, 24, 28, 35, 50, 52, 55, 366, 683, 912, 914, 923, 924, 998, 1062, 1080, 1110, 1154, 1158, 1167, 1299, 1311, 1347, 1363, 1364, 1434, 1490, 1544, 1553, 1562, 1568, 1764, 1850, 1957, 1959, 2015, 2018, 2020, 2040, 2050, 2053, 2056, 2063, 2064, 2072, 2076, 2105, 2108, 2115], "bias": [3, 24, 737, 763, 797, 1444, 1445, 1446, 1481, 1482, 1484, 1492, 1493, 1494, 1500, 1501, 1502, 1545, 1546, 1548, 1570, 1590, 1591, 1719, 2073], "trivial": [3, 37, 40, 738, 966, 1182, 1189, 1734, 1916, 2071, 2083, 2105, 2107], "low": [3, 7, 18, 24, 35, 55, 501, 915, 1199, 1218, 1449, 1820, 1837, 1841, 1842, 1859, 1932, 2016, 2018, 2033, 2035, 2037, 2050, 2063, 2075, 2093, 2105, 2111, 2112, 2118], "digit": [3, 960, 1878, 2015, 2031, 2060, 2064], "microsecond": [3, 2050], "bia": [3, 9, 28, 33, 52, 66, 715, 716, 717, 718, 719, 720, 721, 722, 723, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 741, 742, 743, 744, 745, 746, 752, 754, 755, 756, 757, 759, 763, 764, 767, 768, 775, 776, 777, 784, 795, 1177, 1274, 1284, 1434, 1447, 1457, 1458, 1459, 1460, 1461, 1462, 1481, 1482, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1517, 1530, 1536, 1546, 1547, 1548, 1574, 1576, 1578, 1591, 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2086, 2091, 2093, 2097, 2105, 2108, 2116, 2118], "modulo": [3, 35, 1158, 1202, 1850], "determin": [3, 5, 8, 11, 14, 17, 18, 22, 23, 24, 28, 33, 35, 37, 45, 47, 55, 60, 64, 87, 88, 89, 826, 829, 912, 914, 923, 924, 945, 954, 961, 966, 1056, 1112, 1131, 1141, 1166, 1167, 1191, 1192, 1232, 1233, 1236, 1237, 1288, 1308, 1320, 1331, 1334, 1355, 1369, 1473, 1477, 1478, 1500, 1536, 1539, 1546, 1589, 1628, 1631, 1632, 1647, 1681, 1707, 1739, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1770, 1780, 1812, 1840, 1842, 1844, 1871, 1913, 1914, 1915, 1916, 1917, 1918, 1927, 2003, 2014, 2020, 2021, 2039, 2050, 2052, 2053, 2056, 2061, 2069, 2071, 2074, 2076, 2081, 2083, 2086, 2088, 2089, 2091, 2093, 2104, 2107, 2108, 2116, 2117, 2124], "itself": [3, 5, 7, 8, 19, 28, 29, 52, 55, 61, 64, 490, 696, 702, 883, 998, 1172, 1173, 1274, 1286, 1290, 1530, 1564, 1694, 1720, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1758, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 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2077, 2081, 2083, 2102, 2108, 2113, 2117, 2119, 2121], "amelior": 3, "suffici": [3, 14, 24, 28, 35, 39, 47, 48, 53, 55, 488, 1787, 1788, 1800, 1932, 2015, 2024, 2086, 2089, 2108], "callgrind_control": 3, "callgrind_annot": 3, "boundari": [3, 33, 64, 782, 788, 960, 1228, 1451, 1452, 1453, 1454, 1455, 1456, 1552, 1553, 1554, 1555, 1556, 1557, 1583, 1586, 1587, 1588, 1647, 1707, 1806, 1812, 2018, 2052, 2074, 2081, 2108], "caller": [3, 37, 47, 64, 858, 1274, 1530, 1578, 1916, 2047, 2050, 2081, 2083], "structur": [3, 5, 9, 12, 23, 24, 28, 33, 36, 37, 40, 48, 52, 53, 55, 64, 66, 67, 71, 75, 896, 909, 910, 942, 976, 990, 1161, 1174, 1179, 1187, 1194, 1195, 1290, 1530, 1590, 1747, 1751, 1783, 1820, 1932, 1980, 2016, 2019, 2021, 2027, 2033, 2040, 2050, 2052, 2053, 2054, 2056, 2063, 2066, 2067, 2069, 2071, 2073, 2074, 2081, 2091, 2092, 2093, 2095, 2097, 2099, 2104, 2105, 2106, 2108, 2109, 2113, 2119], "restrict": [3, 8, 12, 23, 35, 53, 55, 60, 61, 978, 990, 1346, 1369, 1465, 2019, 2020, 2021, 2039, 2040, 2047, 2050, 2058, 2076, 2104], "builtin": [3, 28, 64, 66, 75, 1287, 1346, 1846, 1938, 2017, 2019, 2021, 2081, 2083, 2105, 2108, 2117], "surpris": [3, 8, 55, 2015, 2058, 2064, 2107], "serial": [3, 15, 23, 28, 30, 32, 47, 1274, 1284, 1285, 1346, 1530, 1710, 1862, 2015, 2016, 2018, 2031, 2039, 2047, 2050, 2056, 2060, 2061, 2063, 2069, 2074, 2076, 2081, 2082], "subsequ": [3, 7, 14, 15, 17, 28, 52, 55, 64, 976, 1012, 1274, 1286, 1290, 1457, 1458, 1459, 1460, 1461, 1462, 1530, 1559, 2050, 2065, 2071, 2081, 2086, 2099, 2102, 2108], "deseri": [3, 30, 1346, 1710, 2015, 2031, 2066, 2081], "globalsbridg": 3, "care": [3, 7, 14, 28, 35, 55, 63, 64, 1131, 1133, 1188, 1189, 1530, 2037, 2049, 2050, 2052, 2053, 2055, 2061, 2063, 2066, 2071, 2081, 2086, 2102, 2107, 2108, 2109], "reli": [3, 9, 14, 23, 24, 28, 33, 37, 40, 55, 64, 152, 897, 923, 1110, 1466, 1801, 2029, 2047, 2049, 2052, 2053, 2056, 2065, 2066, 2086, 2090, 2107, 2108, 2109, 2111], "pickl": [3, 23, 24, 28, 1274, 1346, 1530, 1862, 2015, 2031, 2037, 2066, 2074, 2081, 2119], "transfer": [3, 23, 28, 55, 2030, 2037, 2050, 2059, 2061, 2074, 2081, 2089], "properli": [3, 7, 23, 24, 30, 32, 37, 47, 63, 978, 1131, 1132, 1133, 1141, 1142, 1143, 1376, 1531, 1532, 1540, 1541, 1720, 1969, 2015, 2027, 2053, 2057, 2058, 2061, 2063, 2066, 2069, 2081, 2082, 2089], "profil": [3, 4, 17, 19, 44, 64, 488, 931, 932, 939, 976, 1026, 1288, 1713, 1714, 1715, 1716, 1878, 2016, 2035, 2056, 2072, 2081, 2098, 2108], "empti": [3, 27, 28, 30, 37, 45, 53, 55, 60, 64, 235, 323, 515, 517, 525, 539, 547, 820, 943, 946, 947, 957, 963, 1110, 1112, 1272, 1274, 1275, 1300, 1320, 1321, 1326, 1333, 1356, 1357, 1358, 1359, 1366, 1443, 1465, 1473, 1530, 1537, 1609, 1628, 1675, 1768, 1780, 1781, 1916, 1931, 1946, 2014, 2017, 2018, 2019, 2020, 2022, 2030, 2032, 2038, 2039, 2040, 2045, 2048, 2050, 2053, 2065, 2071, 2072, 2074, 2086, 2087, 2092, 2095, 2104, 2105, 2107, 2112, 2115], "drive": [3, 9, 28, 2047], "facil": [3, 25, 1346, 2037], "analyz": [3, 4, 18, 52, 64, 2052, 2053, 2056, 2064, 2117], "manipul": [3, 19, 55, 63, 1278, 2016, 2046, 2055, 2061, 2079, 2116], "1000000": [3, 1784], "mirror": [3, 141, 1720], "semant": [3, 9, 11, 17, 28, 47, 48, 52, 53, 55, 62, 64, 152, 797, 878, 879, 880, 897, 918, 958, 1014, 1066, 1168, 1179, 1187, 1202, 1203, 1278, 1285, 1344, 1443, 1609, 1681, 1727, 1728, 1801, 1965, 1980, 2016, 2019, 2020, 2024, 2027, 2040, 2054, 2061, 2071, 2081, 2086, 2108], "number_per_run": 3, "raw_tim": 3, "task_spec": 3, "serializ": [3, 24, 2017], "consum": [3, 23, 30, 33, 36, 50, 53, 63, 437, 1110, 2037, 2050, 2056, 2063, 2068, 2069, 2071, 2091], "extrapol": 3, "sinc": [3, 7, 23, 24, 28, 30, 34, 35, 40, 50, 52, 55, 64, 317, 490, 536, 750, 788, 796, 811, 812, 966, 1058, 1060, 1062, 1110, 1150, 1151, 1152, 1167, 1271, 1274, 1279, 1285, 1288, 1364, 1442, 1472, 1526, 1527, 1528, 1530, 1583, 1591, 1601, 1636, 1638, 1707, 1710, 1713, 1751, 1770, 1775, 1783, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1801, 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1800, 1801, 2020, 2040, 2045, 2047, 2061, 2074], "interquartil": 3, "mitig": [3, 66, 2056, 2088], "tail": [3, 23, 45], "645": 3, "conjunct": [3, 23, 28, 32, 55, 827, 1601, 1636, 1720, 2079, 2081], "trim_sigfig": 3, "human": [3, 13, 33, 45, 52, 1054, 1067, 2045, 2071, 2106, 2118], "raw": [3, 64, 1164, 1333, 2050, 2074, 2075], "built_with_debug_symbol": 3, "baseline_inclusive_stat": 3, "baseline_exclusive_stat": 3, "stmt_inclusive_stat": 3, "stmt_exclusive_stat": 3, "stmt_callgrind_out": 3, "done": [3, 15, 23, 28, 30, 32, 33, 35, 37, 45, 53, 55, 63, 64, 488, 498, 683, 763, 923, 930, 1127, 1129, 1132, 1133, 1135, 1136, 1139, 1140, 1142, 1143, 1145, 1147, 1290, 1364, 1444, 1445, 1446, 1466, 1469, 1481, 1492, 1493, 1494, 1504, 1505, 1512, 1513, 1514, 1515, 1540, 1570, 1576, 1578, 1628, 1720, 1803, 1809, 1922, 2020, 2030, 2032, 2037, 2047, 2049, 2050, 2052, 2053, 2054, 2055, 2057, 2061, 2064, 2069, 2071, 2073, 2076, 2077, 2081, 2083, 2089, 2103, 2104, 2105, 2107, 2114, 2116], 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1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 2022, 2033, 2037, 2038, 2047, 2059, 2067, 2071, 2081, 2103, 2104, 2105, 2108, 2110, 2116, 2117, 2118], "resembl": [3, 15, 2099], "23234231": 3, "first_build_dir": 3, "foo": [3, 14, 28, 44, 45, 52, 63, 64, 66, 74, 75, 827, 858, 863, 976, 1167, 1168, 1177, 1272, 1277, 1282, 1285, 1286, 1289, 1290, 1770, 1969, 1971, 2015, 2017, 2019, 2020, 2024, 2028, 2053, 2061, 2071, 2074, 2093, 2102, 2105, 2108, 2117], "9823794": 3, "bar": [3, 7, 44, 52, 64, 66, 74, 75, 858, 863, 998, 1167, 1277, 1285, 1925, 1926, 1975, 1976, 2015, 2017, 2019, 2024, 2031, 2061, 2071, 2074, 2093], "53453": 3, "src": [3, 28, 64, 198, 230, 315, 323, 473, 514, 515, 516, 517, 518, 519, 521, 540, 1101, 1168, 1574, 1577, 1578, 1781, 1863, 1864, 1865, 1869, 1899, 1942, 1968, 2018, 2035, 2074, 2112], "function_that_actually_chang": 3, "second_build_dir": 3, "cancel": [3, 1271], "site": [3, 7, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 2099], "denois": 3, "explan": [3, 9, 20, 25, 40, 866, 1274, 1530, 2016, 2052, 2053, 2061, 2108, 2114, 2117], "delta": [3, 35, 763, 998, 1481, 1490, 1500, 1562, 1645, 1785, 1925, 1926, 1953, 1975, 1976, 2018, 2045], "inclus": [3, 35, 52, 90, 515, 1193, 1199, 1235, 1237, 1345, 1361, 1367, 1592, 1593, 1841, 1842, 1924, 2080, 2093], "diff": [3, 7, 2017, 2018, 2072], "One": [3, 8, 14, 28, 30, 52, 53, 58, 60, 64, 585, 955, 978, 1168, 1179, 1265, 1583, 1674, 1727, 1728, 1734, 1738, 1801, 1806, 1814, 1841, 1842, 1963, 1980, 2017, 2019, 2020, 2039, 2040, 2048, 2049, 2050, 2053, 2060, 2075, 2083, 2091, 2103, 2104, 2106, 2107, 2115, 2121], "reason": [3, 8, 9, 23, 28, 30, 37, 52, 55, 60, 65, 83, 683, 845, 909, 910, 1131, 1133, 1274, 1290, 1291, 1310, 1311, 1338, 1375, 1442, 1469, 1530, 1638, 1688, 1740, 1862, 2017, 2019, 2020, 2024, 2026, 2047, 2052, 2054, 2056, 2064, 2066, 2071, 2081, 2089, 2103, 2104, 2105, 2107, 2108, 2111, 2117, 2118], "unit": [3, 11, 14, 35, 37, 48, 55, 64, 763, 764, 1128, 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7, 8, 9, 12, 15, 28, 35, 46, 47, 52, 53, 57, 60, 64, 66, 76, 77, 488, 866, 912, 914, 990, 1187, 1198, 1274, 1369, 1434, 1530, 1627, 1753, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1913, 1914, 1915, 1917, 1918, 2017, 2019, 2024, 2038, 2046, 2047, 2050, 2054, 2060, 2061, 2063, 2067, 2071, 2074, 2076, 2081, 2082, 2097, 2102, 2103, 2104, 2105, 2108, 2109, 2110, 2111, 2114, 2115, 2116, 2117, 2119], "autom": [3, 8, 64, 2017, 2076, 2099, 2108, 2117], "easili": [3, 7, 8, 11, 24, 28, 30, 33, 52, 1168, 1537, 1636, 1675, 1801, 1859, 1969, 2032, 2053, 2054, 2058, 2061, 2066, 2073, 2080, 2081, 2083, 2091, 2108, 2116, 2117], "exclus": [3, 23, 28, 35, 37, 47, 52, 55, 64, 738, 1237, 1720, 1841, 1842, 1845, 2047, 2093], "basi": [3, 9, 10, 35, 683, 1347, 1806, 2050, 2060, 2076, 2081, 2102], "thought": [3, 44, 64, 1128, 1130, 1146, 1193, 2105], "path_and_function_nam": 3, "children": [3, 33, 40, 55, 64, 794, 1274, 1530, 2037, 2056, 2061, 2074, 2083], "identifi": 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2016, 2024, 2050, 2053, 2054, 2058, 2060, 2066, 2076, 2077, 2081, 2089, 2104], "filter": [3, 20, 546, 775, 776, 777, 1271, 1294, 1457, 1458, 1459, 1460, 1461, 1462, 1611, 1612, 1613, 1614, 1615, 1616, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1927, 2020, 2074, 2117], "transform": [3, 12, 23, 30, 33, 34, 52, 55, 60, 62, 81, 82, 83, 417, 784, 800, 841, 842, 861, 862, 967, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1147, 1167, 1168, 1169, 1173, 1178, 1196, 1271, 1284, 1447, 1484, 1492, 1493, 1494, 1502, 1517, 1559, 1575, 1576, 1577, 1578, 1601, 1607, 1636, 1653, 1673, 1710, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1797, 1798, 1799, 1800, 1801, 1894, 1927, 2016, 2028, 2054, 2056, 2057, 2069, 2076, 2086, 2091, 2097, 2098, 2099, 2106, 2110], "rather": [3, 8, 9, 14, 28, 37, 40, 50, 52, 55, 64, 66, 75, 782, 788, 936, 966, 1272, 1275, 1346, 1426, 1601, 1636, 1647, 1707, 1735, 1874, 1878, 2017, 2020, 2039, 2040, 2048, 2050, 2053, 2054, 2071, 2074, 2076, 2081, 2086, 2091, 2102, 2103, 2105, 2107, 2108, 2109, 2110], "unicod": [3, 2021], "dictionari": [3, 14, 23, 24, 30, 33, 35, 59, 64, 417, 683, 795, 796, 797, 800, 818, 819, 820, 841, 842, 843, 858, 862, 868, 943, 976, 1066, 1167, 1177, 1182, 1189, 1274, 1275, 1282, 1286, 1290, 1291, 1346, 1347, 1472, 1473, 1530, 1531, 1540, 1627, 1751, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1994, 2019, 2021, 2053, 2061, 2069, 2071, 2073, 2081, 2091, 2096, 2113, 2118, 2119], "lookup": [3, 30, 35, 47, 1472, 1627, 2017, 2021, 2049, 2082, 2111], "map": [3, 14, 28, 30, 35, 37, 44, 45, 47, 48, 52, 53, 55, 60, 61, 64, 66, 75, 82, 687, 738, 795, 796, 800, 802, 817, 818, 820, 842, 843, 858, 859, 860, 861, 862, 868, 889, 957, 1162, 1168, 1179, 1185, 1187, 1189, 1194, 1228, 1237, 1282, 1285, 1346, 1347, 1460, 1461, 1462, 1468, 1469, 1470, 1474, 1476, 1526, 1527, 1528, 1531, 1540, 1622, 1623, 1624, 1629, 1734, 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2056, 2061, 2064, 2067, 2069, 2074, 2081, 2083, 2086, 2088, 2089, 2093, 2103, 2105, 2107, 2115, 2116, 2119, 2121], "filter_fn": 3, "map_fn": 3, "coalesc": [3, 325, 330, 546, 616, 1022, 1912, 1916, 1963, 2018, 2052, 2072, 2086, 2108], "entri": [3, 19, 28, 29, 32, 35, 37, 38, 45, 47, 48, 317, 738, 862, 863, 936, 1052, 1053, 1100, 1151, 1152, 1249, 1274, 1295, 1472, 1473, 1530, 1536, 1627, 1628, 1746, 1747, 1755, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1802, 1803, 1804, 1805, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1815, 1816, 1910, 2017, 2020, 2021, 2027, 2040, 2047, 2052, 2053, 2058, 2061, 2066, 2079, 2086, 2091, 2096, 2103, 2104, 2105, 2106], "color": [3, 64, 1494, 2019, 2020, 2091, 2109], "rowwis": [3, 34], "columnwis": 3, "extend_result": 3, "highlight_warn": 3, "highlight": [3, 53, 733, 734, 2020], "trim_significant_figur": 3, "trim": [3, 945, 954, 1126, 1127, 1129, 1131, 1132, 1133, 1134, 1135, 1136, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1147, 1232, 1233, 1271], "h": [4, 10, 14, 33, 35, 489, 490, 744, 745, 746, 763, 968, 969, 1304, 1311, 1314, 1324, 1338, 1432, 1433, 1440, 1441, 1443, 1445, 1446, 1450, 1458, 1459, 1461, 1469, 1470, 1472, 1474, 1481, 1482, 1493, 1494, 1500, 1501, 1502, 1513, 1514, 1524, 1525, 1542, 1543, 1546, 1548, 1565, 1581, 1584, 1585, 1601, 1609, 1636, 1672, 1678, 1679, 1734, 1735, 1769, 1781, 1820, 1931, 1932, 2018, 2035, 2038, 2039, 2047, 2050, 2052, 2053, 2055, 2058, 2071, 2090, 2091, 2092, 2099, 2104, 2114], "finit": [4, 35, 923, 924, 1263, 1264, 1310, 1311, 1321, 1322, 1338, 1364, 1416, 1420, 1442, 1931, 2053, 2058, 2093], "natur": [4, 7, 8, 11, 30, 35, 55, 66, 68, 86, 923, 924, 1303, 1308, 1334, 1348, 1350, 1355, 1434, 1578, 1688, 2056, 2058, 2068, 2069, 2086, 2087], "against": [4, 5, 14, 28, 37, 47, 797, 869, 923, 924, 1138, 1139, 1140, 1144, 1145, 1147, 1215, 1265, 1274, 1290, 1291, 1530, 1536, 1782, 2015, 2020, 2074, 2097, 2105, 2114], "cprofil": 4, "mode": [4, 8, 23, 24, 28, 30, 35, 47, 50, 52, 60, 61, 64, 81, 223, 224, 490, 749, 750, 775, 776, 777, 782, 788, 789, 790, 818, 820, 826, 829, 863, 864, 893, 895, 899, 902, 903, 904, 909, 910, 912, 913, 914, 915, 919, 920, 921, 923, 976, 981, 1009, 1043, 1084, 1085, 1114, 1126, 1127, 1129, 1131, 1132, 1133, 1134, 1135, 1136, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1147, 1168, 1171, 1172, 1173, 1174, 1177, 1178, 1183, 1188, 1222, 1257, 1258, 1272, 1274, 1275, 1278, 1290, 1292, 1333, 1346, 1376, 1390, 1391, 1413, 1444, 1445, 1446, 1457, 1458, 1459, 1473, 1484, 1492, 1493, 1494, 1502, 1503, 1504, 1505, 1512, 1513, 1514, 1530, 1547, 1570, 1583, 1584, 1611, 1612, 1613, 1628, 1636, 1647, 1675, 1688, 1707, 1708, 1709, 1721, 1729, 1731, 1735, 1740, 1773, 1806, 1814, 1830, 1873, 1875, 1968, 2016, 2018, 2024, 2030, 2038, 2045, 2050, 2052, 2054, 2055, 2056, 2057, 2061, 2068, 2069, 2072, 2075, 2077, 2078, 2079, 2081, 2092, 2095, 2099, 2102, 2106, 2107, 2108, 2109, 2110, 2112, 2117, 2118], "correct": [4, 5, 6, 7, 24, 28, 29, 30, 33, 35, 47, 52, 207, 208, 211, 223, 557, 582, 605, 606, 617, 625, 904, 905, 909, 924, 998, 1131, 1133, 1141, 1142, 1143, 1194, 1249, 1272, 1275, 1290, 1291, 1310, 1466, 1483, 1495, 1710, 1720, 1761, 1877, 1925, 1926, 1975, 1976, 2017, 2018, 2019, 2024, 2028, 2038, 2039, 2050, 2053, 2058, 2088, 2105, 2112, 2116], "launch": [4, 14, 23, 31, 33, 37, 39, 40, 45, 46, 47, 51, 63, 1012, 1720, 2016, 2047, 2049, 2050, 2052, 2053, 2081, 2102, 2110], "spent": [4, 28, 937, 1812, 2049, 2061, 2108, 2115, 2117], "appear": [4, 24, 28, 35, 52, 53, 64, 858, 1055, 1110, 1151, 1152, 1179, 1346, 1380, 1382, 1721, 1852, 1880, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1980, 2017, 2020, 2038, 2039, 2053, 2054, 2061, 2071, 2074, 2105, 2108, 2115], "extrem": [4, 28, 1720, 2047, 2071, 2107], "expens": [4, 23, 35, 55, 1734, 2050, 2058, 2060, 2075, 2081, 2092, 2104, 2108, 2111, 2114, 2117], "bound": [4, 15, 24, 28, 52, 55, 483, 798, 960, 971, 1124, 1125, 1182, 1189, 1193, 1198, 1274, 1439, 1440, 1441, 1523, 1524, 1525, 1530, 1549, 1636, 1814, 1845, 1866, 2020, 2021, 2045, 2047, 2056, 2074, 2076, 2087, 2104, 2105, 2107, 2117], "greater": [4, 28, 47, 66, 67, 294, 619, 683, 952, 965, 966, 971, 1126, 1127, 1129, 1131, 1132, 1133, 1134, 1135, 1136, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1147, 1217, 1231, 1329, 1395, 1442, 1579, 1636, 1647, 1674, 1688, 1704, 1707, 1735, 1769, 1814, 1968, 2018, 2047, 2050, 2065, 2072, 2086, 2087], "spend": [4, 7, 19, 33, 1347, 2028, 2111], "sens": [4, 35, 47, 64, 1751, 1964, 1965, 2020, 2047, 2056], "respons": [4, 7, 9, 28, 30, 32, 33, 35, 37, 44, 50, 55, 63, 978, 1012, 1191, 1518, 1654, 1720, 1916, 2047, 2050, 2053, 2054, 2061, 2069, 2081, 2107], "Of": [4, 1774, 2015, 2052, 2053, 2098, 2105, 2108], "cours": [4, 19, 64, 2015, 2052, 2053, 2081, 2105, 2108], "realiti": [4, 2056], "complic": [4, 24, 34, 52, 64, 796, 1874, 2024, 2039, 2048, 2074, 2081, 2083, 2105, 2107], "account": [4, 33, 45, 64, 1443, 1720, 2045, 2049, 2056, 2086, 2102], "heavili": [4, 65, 1790, 2049, 2053, 2074], "similarli": [4, 7, 30, 33, 52, 63, 64, 763, 793, 797, 862, 967, 1130, 1274, 1330, 1530, 1578, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1758, 1956, 1957, 1958, 1959, 2019, 2047, 2053, 2055, 2058, 2064, 2086, 2107, 2110, 2115], "platform": [4, 8, 9, 14, 28, 39, 40, 44, 1321, 1322, 1333, 1830, 1931, 2030, 2057, 2059, 2064, 2065, 2076], "startup": [4, 19], "slower": [4, 14, 28, 33, 880, 913, 1150, 1151, 1152, 1304, 1311, 1655, 1734, 1785, 2053, 2065, 2073, 2087, 2107], "rerun": [5, 28, 2050], "segment": [5, 1066, 1164, 1562, 2050, 2074, 2108, 2113, 2119], "persist": [5, 21, 30, 52, 55, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 763, 818, 819, 820, 1274, 1481, 1500, 1530, 1546, 2061, 2066, 2067, 2069, 2088, 2102, 2107, 2111], "rng": [5, 23, 1041, 1081, 1388, 1396, 1867, 1997, 2008, 2050, 2065, 2080], "advanc": [5, 15, 23, 24, 37, 1574, 1576, 1578, 1774, 1932, 1971, 2024, 2027, 2039, 2050, 2053, 2059, 2063, 2069, 2090, 2091, 2108], "juggl": 5, "moder": 5, "hit": [5, 8, 14, 1191, 1720, 2015, 2050, 2102, 2105, 2108, 2111, 2117], "preserve_rng_st": 5, "checkpoint_sequenti": [5, 2016], "omit": [5, 14, 28, 48, 152, 1144, 1145, 1147, 1189, 1483, 1544, 2067, 2071, 2081, 2093, 2105, 2109], "exclud": [5, 9, 24, 47, 64, 985, 1237, 1473, 1628, 1677, 1782, 1874, 1956, 1957, 1958, 1959, 2047, 2059, 2066, 2074, 2082, 2106, 2108], "_infer_device_typ": 5, "remain": [5, 8, 19, 35, 47, 64, 1382, 1472, 1473, 1627, 1628, 1710, 1720, 1727, 1728, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1758, 1814, 1831, 1853, 2032, 2033, 2037, 2046, 2055, 2061, 2088, 2099, 2106], "consequ": [5, 60, 1338, 1500, 1931, 2020, 2047, 2050, 2063, 2065, 2068], "random": [5, 35, 37, 47, 48, 56, 64, 86, 90, 156, 763, 896, 909, 910, 946, 1041, 1042, 1047, 1056, 1057, 1077, 1078, 1081, 1082, 1172, 1179, 1227, 1250, 1347, 1367, 1388, 1389, 1394, 1396, 1438, 1449, 1474, 1481, 1500, 1549, 1629, 1680, 1686, 1710, 1735, 1742, 1748, 1749, 1756, 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"placeholder"]], "output": [[53, "output"]], "get_attr": [[53, "get-attr"]], "References": [[53, "references"], [2017, "references"]], "SymInt": [[53, "symint"]], "FakeTensor": [[53, "faketensor"]], "Pytree-able Types": [[53, "pytree-able-types"]], "torch.func": [[56, "torch-func"]], "What are composable function transforms?": [[56, "what-are-composable-function-transforms"]], "FXE0008:fx-node-to-onnx": [[82, "fxe0008-fx-node-to-onnx"]], "torch.Tensor.abs": [[91, "torch-tensor-abs"]], "torch.fx.experimental": [[65, "torch-fx-experimental"]], "torch.fx.experimental.symbolic_shapes": [[65, "module-torch.fx.experimental.symbolic_shapes"]], "torch.Tensor.add_": [[100, "torch-tensor-add"]], "torch.Tensor.addbmm": [[101, "torch-tensor-addbmm"]], "FXE0015:fx-node-insert-type-promotion": [[88, "fxe0015-fx-node-insert-type-promotion"]], "python.closure": [[69, "python-closure"]], "cond_closed_over_variable": [[69, "cond-closed-over-variable"], [74, "cond-closed-over-variable"], [66, 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"examples-of-the-interpreter-pattern"]], "Debugging": [[64, "debugging"], [2017, "debugging"]], "Introduction": [[64, "introduction"], [2027, "introduction"], [2040, "introduction"]], "Common Pitfalls in Transform Authoring": [[64, "common-pitfalls-in-transform-authoring"]], "Checking Correctness of Modules": [[64, "checking-correctness-of-modules"]], "Debugging the Generated Code": [[64, "debugging-the-generated-code"]], "Use pdb": [[64, "use-pdb"]], "Print the Generated Code": [[64, "print-the-generated-code"]], "Use the to_folder Function From GraphModule": [[64, "use-the-to-folder-function-from-graphmodule"]], "Debugging the Transformation": [[64, "debugging-the-transformation"]], "Available Debuggers": [[64, "available-debuggers"]], "Limitations of Symbolic Tracing": [[64, "limitations-of-symbolic-tracing"]], "Dynamic Control Flow": [[64, "dynamic-control-flow"]], "Static Control Flow": [[64, "static-control-flow"]], "Non-torch Functions": [[64, "non-torch-functions"]], "Customizing Tracing with the Tracer class": [[64, "customizing-tracing-with-the-tracer-class"]], "Leaf Modules": [[64, "leaf-modules"]], "Miscellanea": [[64, "miscellanea"]], "FXE0016:find-operator-overloads-in-onnx-registry": [[89, "fxe0016-find-operator-overloads-in-onnx-registry"]], "torch.cond": [[74, "torch-cond"], [990, "torch-cond"]], "FXE0012:unsupported-fx-node-analysis": [[85, "fxe0012-unsupported-fx-node-analysis"]], "torch.mutation": [[79, "torch-mutation"]], "user_input_mutation": [[79, "user-input-mutation"], [66, "user-input-mutation"]], "torch.Tensor.acos_": [[96, "torch-tensor-acos"]], "FXE0007:fx-graph-to-onnx": [[81, "fxe0007-fx-graph-to-onnx"]], "Key Representations:": [[81, "key-representations"]], "Additional Notes:": [[81, "additional-notes"]], "torch.escape-hatch": [[77, "torch-escape-hatch"]], "assume_constant_result": [[77, "assume-constant-result"], [66, "assume-constant-result"]], "constrain_as_size_example": [[77, "constrain-as-size-example"], [76, 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"Unsupported Typing Constructs": [[2019, "unsupported-typing-constructs"], [2020, "unsupported-typing-constructs"]], "Default Types": [[2019, "default-types"]], "Optional Type Refinement": [[2019, "optional-type-refinement"]], "TorchScript Classes": [[2019, "id2"], [2017, "torchscript-classes"]], "TorchScript Enums": [[2019, "id4"]], "Named Tuples": [[2019, "named-tuples"]], "Iterables": [[2019, "iterables"]], "Expressions": [[2019, "expressions"], [2020, "expressions"]], "Literals": [[2019, "literals"], [2020, "literals"]], "List Construction": [[2019, "list-construction"]], "Tuple Construction": [[2019, "tuple-construction"]], "Dict Construction": [[2019, "dict-construction"]], "Variables": [[2019, "variables"], [2017, "variables"]], "Arithmetic Operators": [[2019, "arithmetic-operators"]], "Comparison Operators": [[2019, "comparison-operators"]], "Logical Operators": [[2019, "logical-operators"]], "Subscripts and Slicing": [[2019, "subscripts-and-slicing"]], "Function Calls": [[2019, "function-calls"]], "Method Calls": [[2019, "method-calls"]], "Ternary Expressions": [[2019, "ternary-expressions"]], "Casts": [[2019, "casts"]], "Accessing Module Parameters": [[2019, "accessing-module-parameters"]], "Statements": [[2019, "statements"]], "Simple Assignments": [[2019, "simple-assignments"]], "Pattern Matching Assignments": [[2019, "pattern-matching-assignments"]], "Print Statements": [[2019, "print-statements"]], "If Statements": [[2019, "if-statements"]], "While Loops": [[2019, "while-loops"]], "For loops with range": [[2019, "for-loops-with-range"]], "For loops over tuples": [[2019, "for-loops-over-tuples"]], "For loops over constant nn.ModuleList": [[2019, "for-loops-over-constant-nn-modulelist"]], "Break and Continue": [[2019, "break-and-continue"]], "Return": [[2019, "return"]], "Variable Resolution": [[2019, "variable-resolution"]], "Use of Python Values": [[2019, "use-of-python-values"]], "Functions": [[2019, "functions"], [2017, "functions"], [2118, "functions"], [2071, "functions"], [2087, "functions"]], "Attribute Lookup On Python Modules": [[2019, "attribute-lookup-on-python-modules"]], "Python-defined Constants": [[2019, "python-defined-constants"]], "Module Attributes": [[2019, "module-attributes"]], "torch.xpu.init": [[1999, "torch-xpu-init"]], "torch.xpu.get_device_name": [[1995, "torch-xpu-get-device-name"]], "Meta device": [[2028, "meta-device"]], "Idioms for working with meta tensors": [[2028, "idioms-for-working-with-meta-tensors"]], "torch.xpu.seed": [[2005, "torch-xpu-seed"]], "TorchScript Unsupported PyTorch Constructs": [[2022, "torchscript-unsupported-pytorch-constructs"]], "Torch and Tensor Unsupported Attributes": [[2022, "torch-and-tensor-unsupported-attributes"]], "Unsupported Tensor Methods": [[2022, "unsupported-tensor-methods"]], "Unsupported Tensor Properties": [[2022, "unsupported-tensor-properties"]], "Functions Not Correctly Bound on Torch": [[2022, "functions-not-correctly-bound-on-torch"]], "Ops With Divergent Schemas Between Torch & Python": [[2022, "ops-with-divergent-schemas-between-torch-python"]], "PyTorch Unsupported Modules and Classes": [[2022, "pytorch-unsupported-modules-and-classes"]], "torch.xpu.set_device": [[2007, "torch-xpu-set-device"]], "torch.xpu.empty_cache": [[1993, "torch-xpu-empty-cache"]], "Named Tensors operator coverage": [[2038, "named-tensors-operator-coverage"]], "Supported Operations": [[2038, "id1"]], "Keeps input names": [[2038, "keeps-input-names"]], "Removes dimensions": [[2038, "removes-dimensions"]], "Unifies names from inputs": [[2038, "unifies-names-from-inputs"]], "Permutes dimensions": [[2038, "permutes-dimensions"]], "Contracts away dims": [[2038, "contracts-away-dims"]], "Factory functions": [[2038, "factory-functions"]], "out function and in-place variants": [[2038, "out-function-and-in-place-variants"]], "MPS Environment Variables": [[2035, "mps-environment-variables"]], "torch.xpu.synchronize": [[2012, "torch-xpu-synchronize"]], "torch.xpu.seed_all": [[2006, "torch-xpu-seed-all"]], "torch.xpu.set_rng_state_all": [[2009, "torch-xpu-set-rng-state-all"]], "torch.masked": [[2027, "torch-masked"]], "Motivation": [[2027, "motivation"], [2104, "motivation"], [2107, "motivation"]], "What is a MaskedTensor?": [[2027, "what-is-a-maskedtensor"]], "Supported Operators": [[2027, "supported-operators"]], "Unary Operators": [[2027, "unary-operators"]], "Binary Operators": [[2027, "binary-operators"]], "Reductions": [[2027, "reductions"]], "View and select functions": [[2027, "view-and-select-functions"]], "torch._logging": [[2026, "torch-logging"]], "device_of": [[1992, "device-of"], [1033, "device-of"]], "torch.xpu.get_device_properties": [[1996, "torch-xpu-get-device-properties"]], "torch.xpu.is_available": [[2001, "torch-xpu-is-available"]], "Python Language Reference Coverage": [[2021, "python-language-reference-coverage"]], "torch.xpu.current_stream": [[1989, "torch-xpu-current-stream"]], "torch.xpu.set_stream": [[2010, "torch-xpu-set-stream"]], "torch.xpu.manual_seed": [[2003, "torch-xpu-manual-seed"]], "torch.library": [[2024, "module-torch.library"]], "Testing custom ops": [[2024, "testing-custom-ops"]], "Creating new custom ops in Python": [[2024, "creating-new-custom-ops-in-python"]], "Extending custom ops (created from Python or C++)": [[2024, "extending-custom-ops-created-from-python-or-c"]], "Low-level APIs": [[2024, "low-level-apis"]], "torch.zeros": [[2013, "torch-zeros"]], "Miscellaneous Environment Variables": [[2029, "miscellaneous-environment-variables"]], "device": [[1990, "device"], [1406, "device"], [1031, "device"]], "torch.xpu.initial_seed": [[2000, "torch-xpu-initial-seed"]], "Terminology": [[2020, "terminology"]], "Type System": [[2020, "id1"]], "TorchScript Types": [[2020, "torchscript-types"]], "Meta Types": [[2020, "meta-types"]], "Any Type": [[2020, "any-type"]], "Operators Supported for Any Type": [[2020, "operators-supported-for-any-type"]], "Design Notes": [[2020, "design-notes"], [2081, "design-notes"]], "Primitive Types": [[2020, "primitive-types"]], "Structural Types": [[2020, "structural-types"]], "Nominal Types": [[2020, "nominal-types"]], "Built-in Class": [[2020, "built-in-class"]], "Special Note on torch.nn.ModuleList and torch.nn.ModuleDict": [[2020, "special-note-on-torch-nn-modulelist-and-torch-nn-moduledict"]], "Custom Class": [[2020, "custom-class"]], "Enum Type": [[2020, "enum-type"]], "TorchScript Module Class": [[2020, "torchscript-module-class"]], "Module Instance Class": [[2020, "module-instance-class"]], "Type Annotation": [[2020, "type-annotation"]], "When to Annotate Types": [[2020, "when-to-annotate-types"]], "Annotate Function Signature": [[2020, "annotate-function-signature"]], "Annotate Variables and Data Attributes": [[2020, "annotate-variables-and-data-attributes"]], "Local Variables": [[2020, "local-variables"]], "Instance Data Attributes": [[2020, "instance-data-attributes"]], "Type Annotation APIs": [[2020, "type-annotation-apis"]], "torch.jit.annotate(T, expr)": [[2020, "torch-jit-annotate-t-expr"]], "Type Annotation Appendix": [[2020, "type-annotation-appendix"]], "TorchScript Type System Definition": [[2020, "torchscript-type-system-definition"]], "Arithmetic Conversions": [[2020, "arithmetic-conversions"]], "Atoms": [[2020, "atoms"]], "Identifiers": [[2020, "identifiers"]], "Parenthesized Forms": [[2020, "parenthesized-forms"]], "List and Dictionary Displays": [[2020, "list-and-dictionary-displays"]], "Primaries": [[2020, "primaries"]], "Attribute References": [[2020, "attribute-references"]], "Subscriptions": [[2020, "subscriptions"]], "Slicings": [[2020, "slicings"]], "Calls": [[2020, "calls"]], "Power Operator": [[2020, "power-operator"]], "Unary and Arithmetic Bitwise Operations": [[2020, "unary-and-arithmetic-bitwise-operations"]], "Binary Arithmetic Operations": [[2020, "binary-arithmetic-operations"]], "Shifting Operations": [[2020, "shifting-operations"]], "Binary Bitwise Operations": [[2020, "binary-bitwise-operations"]], "Comparisons": [[2020, "comparisons"], [2102, "comparisons"]], "Value Comparisons": [[2020, "value-comparisons"]], "Membership Test Operations": [[2020, "membership-test-operations"]], "Identity Comparisons": [[2020, "identity-comparisons"]], "Boolean Operations": [[2020, "boolean-operations"]], "Conditional Expressions": [[2020, "conditional-expressions"]], "Expression Lists": [[2020, "expression-lists"]], "Simple Statements": [[2020, "simple-statements"]], "Expression Statements": [[2020, "expression-statements"]], "Assignment Statements": [[2020, "assignment-statements"]], "Augmented Assignment Statements": [[2020, "augmented-assignment-statements"]], "Annotated Assignment Statements": [[2020, "annotated-assignment-statements"]], "The raise Statement": [[2020, "the-raise-statement"]], "The assert Statement": [[2020, "the-assert-statement"]], "The return Statement": [[2020, "the-return-statement"]], "The del Statement": [[2020, "the-del-statement"]], "The pass Statement": [[2020, "the-pass-statement"]], "The print Statement": [[2020, "the-print-statement"]], "The break Statement": [[2020, "the-break-statement"]], "The continue Statement:": [[2020, "the-continue-statement"]], "Compound Statements": [[2020, "compound-statements"]], "The if Statement": [[2020, "the-if-statement"]], "Basic if/else Statement": [[2020, "basic-if-else-statement"]], "Ternary if/else Statement": [[2020, "ternary-if-else-statement"]], "The while Statement": [[2020, "the-while-statement"]], "The for-in Statement": [[2020, "the-for-in-statement"]], "The with Statement": [[2020, "the-with-statement"]], "The tuple Statement": [[2020, "the-tuple-statement"]], "The getattr Statement": [[2020, "the-getattr-statement"]], "The hasattr Statement": [[2020, "the-hasattr-statement"]], "The zip Statement": [[2020, "the-zip-statement"]], "The enumerate Statement": [[2020, "the-enumerate-statement"]], "Python Values": [[2020, "python-values"]], "Resolution Rules": [[2020, "resolution-rules"]], "Python Built-in Functions Support": [[2020, "python-built-in-functions-support"]], "TorchScript Support for Python Built-in Functions": [[2020, "id5"]], "Python Built-in Values Support": [[2020, "python-built-in-values-support"]], "TorchScript Support for Python Built-in Values": [[2020, "id6"]], "torch.* APIs": [[2020, "torch-apis"]], "Remote Procedure Calls": [[2020, "remote-procedure-calls"]], "Asynchronous Execution": [[2020, "asynchronous-execution"]], "Type Annotations": [[2020, "type-annotations"]], "Meta Programming": [[2020, "meta-programming"]], "Type Refinement": [[2020, "type-refinement"]], "Named Tensors": [[2039, "named-tensors"]], "Creating named tensors": [[2039, "creating-named-tensors"]], "Named dimensions": [[2039, "named-dimensions"]], "Name propagation semantics": [[2039, "name-propagation-semantics"]], "match semantics": [[2039, "match-semantics"]], "Basic name inference rules": [[2039, "basic-name-inference-rules"]], "Explicit alignment by names": [[2039, "explicit-alignment-by-names"]], "Manipulating dimensions": [[2039, "manipulating-dimensions"]], "Autograd support": [[2039, "autograd-support"]], "Currently supported operations and subsystems": [[2039, "currently-supported-operations-and-subsystems"]], "Operators": [[2039, "operators"]], "Subsystems": [[2039, "subsystems"]], "Named tensor API reference": [[2039, "named-tensor-api-reference"]], "TorchScript Builtins": [[2018, "torchscript-builtins"]], "Supported Tensor Methods": [[2018, "supported-tensor-methods"]], "Supported PyTorch Functions": [[2018, "supported-pytorch-functions"]], "TorchScript Builtin Functions": [[2018, "torchscript-builtin-functions"]], "Python Built-in Functions": [[2018, "python-built-in-functions"]], "math Module": [[2018, "math-module"]], "torch.xpu.is_initialized": [[2002, "torch-xpu-is-initialized"]], "torch.utils.mobile_optimizer": [[2030, "torch-utils-mobile-optimizer"]], "JIT Utils 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tables": [[2016, "indices-and-tables"]], "TorchScript": [[2017, "torchscript"]], "Creating TorchScript Code": [[2017, "creating-torchscript-code"]], "Mixing Tracing and Scripting": [[2017, "mixing-tracing-and-scripting"]], "TorchScript Language": [[2017, "torchscript-language"]], "Built-in Functions and Modules": [[2017, "built-in-functions-and-modules"]], "PyTorch Functions and Modules": [[2017, "pytorch-functions-and-modules"]], "Python Functions and Modules": [[2017, "python-functions-and-modules"]], "Python Language Reference Comparison": [[2017, "python-language-reference-comparison"]], "Disable JIT for Debugging": [[2017, "disable-jit-for-debugging"]], "Inspecting Code": [[2017, "inspecting-code"]], "Interpreting Graphs": [[2017, "interpreting-graphs"]], "Tracer": [[2017, "tracer"]], "Tracing Edge Cases": [[2017, "tracing-edge-cases"]], "Automatic Trace Checking": [[2017, "automatic-trace-checking"]], "Tracer Warnings": [[2017, "tracer-warnings"]], "Frequently Asked Questions": [[2017, "frequently-asked-questions"], [2108, "frequently-asked-questions"], [2055, "frequently-asked-questions"], [2071, "frequently-asked-questions"], [2076, "frequently-asked-questions"], [7, "frequently-asked-questions"]], "Known Issues": [[2017, "known-issues"]], "Appendix": [[2017, "appendix"]], "Migrating to PyTorch 1.2 Recursive Scripting API": [[2017, "migrating-to-pytorch-1-2-recursive-scripting-api"]], "Modules": [[2017, "modules"], [2061, "modules"]], "Attributes": [[2017, "attributes"]], "Constants": [[2017, "constants"]], "Fusion Backends": [[2017, "fusion-backends"]], "torch.mtia": [[2036, "torch-mtia"]], "Streams and events": [[2036, "streams-and-events"], [2124, "streams-and-events"], [17, "streams-and-events"], [16, "streams-and-events"]], "torch.xpu.get_device_capability": [[1994, "torch-xpu-get-device-capability"]], "torch.utils.model_zoo": [[2031, "torch-utils-model-zoo"]], "torch.xpu.manual_seed_all": [[2004, "torch-xpu-manual-seed-all"]], "Multiprocessing package 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"dropout2d"]], "Dropout": [[1467, "dropout"]], "Conv3d": [[1459, "conv3d"], [743, "conv3d"], [734, "conv3d"]], "AvgPool2d": [[1440, "avgpool2d"]], "CrossEntropyLoss": [[1465, "crossentropyloss"]], "ChannelShuffle": [[1450, "channelshuffle"]], "Flatten": [[1475, "flatten"]], "ConvTranspose1d": [[1460, "convtranspose1d"], [744, "convtranspose1d"]], "CosineEmbeddingLoss": [[1463, "cosineembeddingloss"]], "FractionalMaxPool3d": [[1478, "fractionalmaxpool3d"]], "EmbeddingBag": [[1473, "embeddingbag"], [749, "embeddingbag"]], "AdaptiveAvgPool3d": [[1433, "adaptiveavgpool3d"]], "Conv1d": [[1457, "conv1d"], [741, "conv1d"]], "AdaptiveAvgPool2d": [[1432, "adaptiveavgpool2d"]], "CosineSimilarity": [[1464, "cosinesimilarity"]], "ConvTranspose2d": [[1461, "convtranspose2d"], [745, "convtranspose2d"]], "AvgPool1d": [[1439, "avgpool1d"]], "Embedding": [[1472, "embedding"], [748, "embedding"]], "Bilinear": [[1447, "bilinear"]], "ConvTranspose3d": [[1462, "convtranspose3d"], [746, "convtranspose3d"]], "torch.negative": [[1429, "torch-negative"]], "BCEWithLogitsLoss": [[1443, "bcewithlogitsloss"]], "AvgPool3d": [[1441, "avgpool3d"]], "ConstantPad3d": [[1456, "constantpad3d"]], "CircularPad2d": [[1452, "circularpad2d"]], "torch.neg": [[1428, "torch-neg"]], "Conv2d": [[1458, "conv2d"], [733, "conv2d"], [742, "conv2d"]], "CircularPad1d": [[1451, "circularpad1d"]], "BatchNorm2d": [[1445, "batchnorm2d"], [739, "batchnorm2d"]], "CircularPad3d": [[1453, "circularpad3d"]], "Dropout1d": [[1468, "dropout1d"]], "DataParallel": [[1466, "dataparallel"]], "Fold": [[1476, "fold"]], "CTCLoss": [[1449, "ctcloss"]], "CELU": [[1448, "celu"]], "ConstantPad1d": [[1454, "constantpad1d"]], "AlphaDropout": [[1438, "alphadropout"]], "torch.nextafter": [[1430, "torch-nextafter"]], "AdaptiveAvgPool1d": [[1431, "adaptiveavgpool1d"]], "AdaptiveMaxPool1d": [[1435, "adaptivemaxpool1d"]], "BatchNorm3d": [[1446, "batchnorm3d"], [740, "batchnorm3d"]], "AdaptiveMaxPool3d": [[1437, "adaptivemaxpool3d"]], "FeatureAlphaDropout": [[1474, "featurealphadropout"]], "AdaptiveLogSoftmaxWithLoss": [[1434, "adaptivelogsoftmaxwithloss"]], "ELU": [[1471, "elu"], [747, "elu"]], "Dropout3d": [[1470, "dropout3d"]], "BCELoss": [[1442, "bceloss"]], "ConstantPad2d": [[1455, "constantpad2d"]], "AdaptiveMaxPool2d": [[1436, "adaptivemaxpool2d"]], "torch.linspace": [[1345, "torch-linspace"]], "torch.linalg.vander": [[1342, "torch-linalg-vander"]], "torch.log": [[1348, "torch-log"]], "torch.lobpcg": [[1347, "torch-lobpcg"]], "torch.logical_or": [[1358, "torch-logical-or"]], "torch.log10": [[1349, "torch-log10"]], "torch.linalg.multi_dot": [[1330, "torch-linalg-multi-dot"]], "torch.log1p": [[1350, "torch-log1p"]], "torch.linalg.qr": [[1333, "torch-linalg-qr"]], "torch.logcumsumexp": [[1354, "torch-logcumsumexp"]], "torch.maximum": [[1373, "torch-maximum"]], "torch.linalg.solve_triangular": [[1337, "torch-linalg-solve-triangular"]], "torch.linalg.matrix_rank": [[1329, "torch-linalg-matrix-rank"]], "torch.max": [[1372, "torch-max"]], "torch.meshgrid": [[1376, "torch-meshgrid"]], "torch.logaddexp2": [[1353, "torch-logaddexp2"]], "torch.manual_seed": [[1367, "torch-manual-seed"]], "torch.lu_unpack": [[1366, "torch-lu-unpack"]], "torch.linalg.matrix_power": [[1328, "torch-linalg-matrix-power"]], "torch.linalg.slogdet": [[1334, "torch-linalg-slogdet"]], "torch.linalg.norm": [[1331, "torch-linalg-norm"]], "torch.logspace": [[1361, "torch-logspace"]], "torch.matrix_exp": [[1370, "torch-matrix-exp"]], "torch.linalg.vecdot": [[1343, "torch-linalg-vecdot"]], "torch.linalg.tensorsolve": [[1341, "torch-linalg-tensorsolve"]], "torch.logsumexp": [[1362, "torch-logsumexp"]], "torch.logical_xor": [[1359, "torch-logical-xor"]], "torch.lt": [[1363, "torch-lt"]], "torch.matrix_power": [[1371, "torch-matrix-power"]], "torch.log2": [[1351, "torch-log2"]], "torch.lu": [[1364, "torch-lu"]], "torch.logical_not": [[1357, "torch-logical-not"]], "torch.lu_solve": [[1365, "torch-lu-solve"]], "torch.linalg.svd": [[1338, "torch-linalg-svd"]], "torch.logdet": [[1355, "torch-logdet"]], "torch.linalg.vector_norm": [[1344, "torch-linalg-vector-norm"]], "torch.linalg.tensorinv": [[1340, "torch-linalg-tensorinv"]], "torch.logit": [[1360, "torch-logit"]], "torch.linalg.matrix_exp": [[1326, "torch-linalg-matrix-exp"]], "torch.linalg.svdvals": [[1339, "torch-linalg-svdvals"]], "torch.linalg.matrix_norm": [[1327, "torch-linalg-matrix-norm"]], "torch.logaddexp": [[1352, "torch-logaddexp"]], "torch.linalg.solve_ex": [[1336, "torch-linalg-solve-ex"]], "torch.load": [[1346, "torch-load"]], "torch.logical_and": [[1356, "torch-logical-and"]], "torch.median": [[1375, "torch-median"]], "torch.matmul": [[1369, "torch-matmul"]], "torch.linalg.pinv": [[1332, "torch-linalg-pinv"]], "torch.mean": [[1374, "torch-mean"]], "torch.masked_select": [[1368, "torch-masked-select"]], "torch.linalg.solve": [[1335, "torch-linalg-solve"]], "PYTORCH ProcessGroupNCCL Environment Variables": [[2121, "pytorch-processgroupnccl-environment-variables"]], "TorchInductor GPU Profiling": [[2111, "torchinductor-gpu-profiling"]], "Relevant Environment Variables": [[2111, "relevant-environment-variables"]], "Breakdown Model GPU Time": [[2111, "breakdown-model-gpu-time"]], "Benchmark Individual Triton Kernel": [[2111, "benchmark-individual-triton-kernel"]], "Torch Environment Variables": [[2120, "torch-environment-variables"]], "torch.compiler API reference": [[2100, "torch-compiler-api-reference"]], "Getting Started": [[2110, "getting-started"], [7, "getting-started"]], "Using a pretrained model": [[2110, "using-a-pretrained-model"]], "Next Steps": [[2110, "next-steps"]], "Dynamo Deep-Dive": [[2105, "dynamo-deep-dive"]], "A Gentle Introduction to Dynamo": [[2105, "a-gentle-introduction-to-dynamo"]], "PEP 523: Adding a frame evaluation API to CPython": [[2105, "pep-523-adding-a-frame-evaluation-api-to-cpython"]], "Implementing CPython in Python": [[2105, "implementing-cpython-in-python"]], "Generating the Output Graph": [[2105, "generating-the-output-graph"]], "Making Dynamo Sound: Guards": [[2105, "making-dynamo-sound-guards"]], "Symbolic Shapes": [[2105, "symbolic-shapes"]], "Static by default": [[2105, "static-by-default"]], "0, 1 are always specialized": [[2105, "are-always-specialized"]], "Duck shaping": [[2105, "duck-shaping"]], "Guards on symbolic ints": [[2105, "guards-on-symbolic-ints"]], "Making Dynamo Complete: Graph Breaks": [[2105, "making-dynamo-complete-graph-breaks"]], "Conclusion": [[2105, "conclusion"]], "Footnotes": [[2105, "footnotes"]], "Does torch.compile support training?": [[2108, "does-torch-compile-support-training"]], "Do you support Distributed code?": [[2108, "do-you-support-distributed-code"]], "Do I still need to export whole graphs?": [[2108, "do-i-still-need-to-export-whole-graphs"]], "Why is my code crashing?": [[2108, "why-is-my-code-crashing"]], "Why is compilation slow?": [[2108, "why-is-compilation-slow"]], "Why are you recompiling in production?": [[2108, "why-are-you-recompiling-in-production"]], "How are you speeding up my code?": [[2108, "how-are-you-speeding-up-my-code"]], "Why am I not seeing speedups?": [[2108, "why-am-i-not-seeing-speedups"]], "Identifying the cause of a graph break": [[2108, "identifying-the-cause-of-a-graph-break"]], "Why didn\u2019t my code recompile when I changed it?": [[2108, "why-didnt-my-code-recompile-when-i-changed-it"]], "Why am I getting incorrect results?": [[2108, "why-am-i-getting-incorrect-results"]], "Why am I getting OOMs?": [[2108, "why-am-i-getting-ooms"]], "Does torch.func work with torch.compile (for grad and vmap transforms)?": [[2108, "does-torch-func-work-with-torch-compile-for-grad-and-vmap-transforms"]], "Calling torch.func transform inside of a function handled with torch.compile": [[2108, "calling-torch-func-transform-inside-of-a-function-handled-with-torch-compile"]], "Compiling torch.func.grad with torch.compile": [[2108, "compiling-torch-func-grad-with-torch-compile"]], "Compiling torch.vmap with torch.compile": [[2108, "compiling-torch-vmap-with-torch-compile"]], "Compiling functions besides the ones which are supported (escape hatch)": [[2108, "compiling-functions-besides-the-ones-which-are-supported-escape-hatch"]], "Does NumPy work with torch.compile?": [[2108, "does-numpy-work-with-torch-compile"]], "Which NumPy features does torch.compile support?": [[2108, "which-numpy-features-does-torch-compile-support"]], "Can I compile NumPy code using torch.compile?": [[2108, "can-i-compile-numpy-code-using-torch-compile"]], "Can I execute NumPy code on CUDA and compute gradients via torch.compile?": [[2108, "can-i-execute-numpy-code-on-cuda-and-compute-gradients-via-torch-compile"]], "How do I debug NumPy code under torch.compile?": [[2108, "how-do-i-debug-numpy-code-under-torch-compile"]], "I torch.compile some NumPy code and I did not see any speed-up.": [[2108, "i-torch-compile-some-numpy-code-and-i-did-not-see-any-speed-up"]], "Which API to use for fine grain tracing?": [[2108, "which-api-to-use-for-fine-grain-tracing"]], "How do I graph break on a function?": [[2108, "how-do-i-graph-break-on-a-function"]], "What\u2019s the difference between torch._dynamo.disable and torch._dynamo.disallow_in_graph": [[2108, "what-s-the-difference-between-torch-dynamo-disable-and-torch-dynamo-disallow-in-graph"]], "What\u2019s the difference between torch._dynamo.disable and torch._dynamo_skip": [[2108, "what-s-the-difference-between-torch-dynamo-disable-and-torch-dynamo-skip"]], "Writing Graph Transformations on ATen IR": [[2116, "writing-graph-transformations-on-aten-ir"]], "Passes": [[2116, "passes"]], "One-to-One Pass": [[2116, "one-to-one-pass"]], "One-to-X Pass": [[2116, "one-to-x-pass"]], "One-to-None Pass": [[2116, "one-to-none-pass"]], "Utilizing Local Information": [[2116, "utilizing-local-information"]], "Subgraph Rewriter": [[2116, "subgraph-rewriter"]], "Pass Manager": [[2116, "pass-manager"]], "Partitioner": [[2116, "partitioner"]], "Subgraph Matcher": [[2116, "subgraph-matcher"]], "Capability Based Partitioner": [[2116, "capability-based-partitioner"]], "Dynamic shapes": [[2104, "dynamic-shapes"]], "Abridged public API": [[2104, "abridged-public-api"]], "The Guard Model": [[2104, "the-guard-model"]], "Overall architecture": [[2104, "overall-architecture"], [2107, "overall-architecture"]], "Abridged internal API": [[2104, "abridged-internal-api"]], "DimDynamic policy": [[2104, "dimdynamic-policy"]], "Unbacked SymInts": [[2104, "unbacked-symints"]], "PyTorch 2.0 Troubleshooting": [[2117, "pytorch-2-0-troubleshooting"]], "Title": [[2117, "id1"]], "Diagnosing Runtime Errors": [[2117, "diagnosing-runtime-errors"]], "Torchdynamo Errors": [[2117, "torchdynamo-errors"]], "Diagnosing TorchInductor Errors": [[2117, "diagnosing-torchinductor-errors"]], "Minifying TorchInductor Errors": [[2117, "minifying-torchinductor-errors"]], "Minifying Backend Compiler Errors": [[2117, "minifying-backend-compiler-errors"]], "Performance Profiling": [[2117, "performance-profiling"]], "Accessing TorchDynamo Profiler": [[2117, "accessing-torchdynamo-profiler"]], "TorchInductor Debugging using TORCH_COMPILE_DEBUG": [[2117, "torchinductor-debugging-using-torch-compile-debug"]], "Identifying the Cause of a Graph Break": [[2117, "identifying-the-cause-of-a-graph-break"]], "Excessive Recompilation": [[2117, "excessive-recompilation"]], "Accuracy Debugging": [[2117, "accuracy-debugging"]], "Extended Debugging": [[2117, "extended-debugging"]], "Cold Start Timing and Cache Corruption Debugging": [[2117, "cold-start-timing-and-cache-corruption-debugging"]], "torch.overrides": [[2118, "module-torch.overrides"]], "torch.ao.ns._numeric_suite": [[2096, "torch-ao-ns-numeric-suite"]], "Fake tensor": [[2107, "fake-tensor"]], "Related work": [[2107, "related-work"]], "API: the important bits": [[2107, "api-the-important-bits"]], "Details": [[2107, "details"]], "About the tensor subclass": [[2107, "about-the-tensor-subclass"]], "How is each individual operator implemented?": [[2107, "how-is-each-individual-operator-implemented"]], "How does the converter work?": [[2107, "how-does-the-converter-work"]], "Performance characteristics": [[2107, "performance-characteristics"]], "Fake tensor of fake tensor?": [[2107, "fake-tensor-of-fake-tensor"]], "Interaction with dynamic shapes": [[2107, "interaction-with-dynamic-shapes"]], "Other resources": [[2107, "other-resources"]], "Dynamo Overview": [[2106, "dynamo-overview"]], "Dynamo Internals": [[2106, "dynamo-internals"]], "What is a guard?": [[2106, "what-is-a-guard"]], "What is Dynamo doing?": [[2106, "what-is-dynamo-doing"]], "How to inspect artifacts generated by Dynamo?": [[2106, "how-to-inspect-artifacts-generated-by-dynamo"]], "PyTorch 2.0 Performance Dashboard": [[2114, "pytorch-2-0-performance-dashboard"]], "How to read the dashboard?": [[2114, "how-to-read-the-dashboard"]], "What is measured on the dashboard?": [[2114, "what-is-measured-on-the-dashboard"]], "Can I check if my PR affects TorchInductor\u2019s performance on the dashboard before merging?": [[2114, "can-i-check-if-my-pr-affects-torchinductor-s-performance-on-the-dashboard-before-merging"]], "How can I run any performance test locally?": [[2114, "how-can-i-run-any-performance-test-locally"]], "torch.utils.tensorboard": [[2091, "module-torch.utils.tensorboard"]], "torch.utils": [[2123, "module-torch.utils"]], "Custom Backends": [[2103, "custom-backends"]], "Registering Custom Backends": [[2103, "registering-custom-backends"]], "Custom Backends after AOTAutograd": [[2103, "custom-backends-after-aotautograd"]], "Examples": [[2103, "examples"], [2057, "examples"], [42, "examples"], [12, "examples"]], "Debugging Backend": [[2103, "debugging-backend"]], "Speedy Backend": [[2103, "speedy-backend"]], "Composable Backends": [[2103, "composable-backends"]], "torch.xpu": [[2124, "module-torch.xpu"]], "Random Number Generator": [[2124, "random-number-generator"], [17, "random-number-generator"]], "torch.compiler": [[2098, "torch-compiler"]], "Getting Started for PyTorch Users": [[2098, null]], "HowTo for PyTorch Backend Vendors": [[2098, null]], "torch": [[2095, "module-torch"]], "Tensors": [[2095, "tensors"]], "Creation Ops": [[2095, "creation-ops"]], "Indexing, Slicing, Joining, Mutating Ops": [[2095, "indexing-slicing-joining-mutating-ops"]], "Generators": [[2095, "generators"]], "Random sampling": [[2095, "random-sampling"]], "In-place random sampling": [[2095, "in-place-random-sampling"]], "Quasi-random sampling": [[2095, "quasi-random-sampling"]], "Parallelism": [[2095, "parallelism"]], "Locally disabling gradient computation": [[2095, "locally-disabling-gradient-computation"], [2047, "locally-disabling-gradient-computation"], [1, "locally-disabling-gradient-computation"]], "Math operations": [[2095, "math-operations"]], "Pointwise Ops": [[2095, "pointwise-ops"]], "Reduction Ops": [[2095, "reduction-ops"]], "Comparison Ops": [[2095, "comparison-ops"]], "Spectral Ops": [[2095, "spectral-ops"]], "Other Operations": [[2095, "other-operations"]], "BLAS and LAPACK Operations": [[2095, "blas-and-lapack-operations"]], "Foreach Operations": [[2095, "foreach-operations"]], "Utilities": [[2095, "utilities"], [2041, "module-torch.nn.utils"]], "Symbolic Numbers": [[2095, "symbolic-numbers"]], "Export Path": [[2095, "export-path"]], "Control Flow": [[2095, "control-flow"]], "Optimizations": [[2095, "optimizations"]], "Operator Tags": [[2095, "operator-tags"]], "PyTorch 2.0 NNModule Support": [[2113, "pytorch-2-0-nnmodule-support"]], "NNModule Hooks Support": [[2113, "nnmodule-hooks-support"]], "nn.Module.__call__ Hooks Usage and limitations": [[2113, "nn-module-call-hooks-usage-and-limitations"]], "state_dict Hooks": [[2113, "state-dict-hooks"]], "Profiling to understand torch.compile performance": [[2115, "profiling-to-understand-torch-compile-performance"]], "What to use torch.profiler for:": [[2115, "what-to-use-torch-profiler-for"]], "Basics of using torch.profiler and viewing traces": [[2115, "basics-of-using-torch-profiler-and-viewing-traces"]], "Working around CUDA Graph profiling issues": [[2115, "working-around-cuda-graph-profiling-issues"]], "Understanding compilation time": [[2115, "understanding-compilation-time"]], "Finding graph breaks: \u201cTorch-Compiled Region\u201d and \u201cCompiledFunction\u201d": [[2115, "finding-graph-breaks-torch-compiled-region-and-compiledfunction"]], "Operator Kernels": [[2115, "operator-kernels"]], "Launch overhead": [[2115, "launch-overhead"]], "torch.Tensor": [[2092, "torch-tensor"]], "Data types": [[2092, "data-types"]], "Initializing and basic operations": [[2092, "initializing-and-basic-operations"]], "Tensor class reference": [[2092, "tensor-class-reference"]], "torch.ao.ns._numeric_suite_fx": [[2097, "torch-ao-ns-numeric-suite-fx"]], "torch.ao.ns.fx.utils": [[2097, "torch-ao-ns-fx-utils"]], "torch.testing": [[2093, "module-torch.testing"]], "TorchDynamo APIs for fine-grained tracing": [[2109, "torchdynamo-apis-for-fine-grained-tracing"]], "TorchDynamo APIs to control fine-grained tracing": [[2109, "id1"]], "torch.compiler.disable": [[2109, "torch-compiler-disable"], [982, "torch-compiler-disable"]], "torch._dynamo.disallow_in_graph": [[2109, "torch-dynamo-disallow-in-graph"]], "torch.compiler.allow_in_graph": [[2109, "torch-compiler-allow-in-graph"], [978, "torch-compiler-allow-in-graph"]], "Limitations": [[2109, "limitations"], [2102, "limitations"], [2071, "limitations"]], "Understanding CUDA Memory Usage": [[2119, "understanding-cuda-memory-usage"]], "Generating a Snapshot": [[2119, "generating-a-snapshot"]], "Using the visualizer": [[2119, "using-the-visualizer"]], "Active Memory Timeline": [[2119, "active-memory-timeline"]], "Allocator State History": [[2119, 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"tensorpipe-backend"]], "RRef": [[2081, "rref"]], "More Information about RRef": [[2081, null]], "RemoteModule": [[2081, "remotemodule"]], "Distributed Autograd Framework": [[2081, "distributed-autograd-framework"]], "More Information about RPC Autograd": [[2081, null]], "Distributed Optimizer": [[2081, "distributed-optimizer"], [2082, "distributed-optimizer"]], "Tutorials": [[2081, "tutorials"], [2074, "tutorials"], [7, "tutorials"]], "torch.signal": [[2084, "module-torch.signal"]], "torch.signal.windows": [[2084, "module-torch.signal.windows"]], "Features for large-scale deployments": [[2060, "features-for-large-scale-deployments"]], "Fleet-wide operator profiling": [[2060, "fleet-wide-operator-profiling"]], "API usage logging": [[2060, "api-usage-logging"]], "Attaching metadata to saved TorchScript models": [[2060, "attaching-metadata-to-saved-torchscript-models"]], "Build environment considerations": [[2060, "build-environment-considerations"]], "Common extension points": [[2060, "common-extension-points"]], "torch.sparse": [[2086, "torch-sparse"]], "Why and when to use sparsity": [[2086, "why-and-when-to-use-sparsity"]], "Functionality overview": [[2086, "functionality-overview"]], "Operator overview": [[2086, "operator-overview"]], "Sparse Semi-Structured Tensors": [[2086, "sparse-semi-structured-tensors"]], "Constructing Sparse Semi-Structured Tensors": [[2086, "constructing-sparse-semi-structured-tensors"]], "Sparse Semi-Structured Tensor Operations": [[2086, "sparse-semi-structured-tensor-operations"]], "Accelerating nn.Linear with semi-structured sparsity": [[2086, "accelerating-nn-linear-with-semi-structured-sparsity"]], "Sparse COO tensors": [[2086, "sparse-coo-tensors"]], "Construction": [[2086, "construction"], [2040, "construction"]], "Sparse hybrid COO tensors": [[2086, "sparse-hybrid-coo-tensors"]], "Uncoalesced sparse COO tensors": [[2086, "uncoalesced-sparse-coo-tensors"]], "Working with sparse COO tensors": [[2086, "working-with-sparse-coo-tensors"]], "Sparse Compressed Tensors": [[2086, "sparse-compressed-tensors"]], "Sparse CSR Tensor": [[2086, "sparse-csr-tensor"]], "Construction of CSR tensors": [[2086, "construction-of-csr-tensors"]], "CSR Tensor Operations": [[2086, "csr-tensor-operations"]], "Sparse CSC Tensor": [[2086, "sparse-csc-tensor"]], "Construction of CSC tensors": [[2086, "construction-of-csc-tensors"]], "Sparse BSR Tensor": [[2086, "sparse-bsr-tensor"]], "Construction of BSR tensors": [[2086, "construction-of-bsr-tensors"]], "Sparse BSC Tensor": [[2086, "sparse-bsc-tensor"]], "Construction of BSC tensors": [[2086, "construction-of-bsc-tensors"]], "Tools for working with sparse compressed tensors": [[2086, "tools-for-working-with-sparse-compressed-tensors"]], "Construction of sparse compressed tensors": [[2086, "construction-of-sparse-compressed-tensors"]], "Supported operations": [[2086, "supported-operations"], [2040, "supported-operations"]], "Linear Algebra operations": [[2086, "linear-algebra-operations"]], "Tensor methods and sparse": [[2086, "tensor-methods-and-sparse"]], "Torch functions specific to sparse Tensors": [[2086, "torch-functions-specific-to-sparse-tensors"]], "Other functions": [[2086, "other-functions"]], "Unary functions": [[2086, "unary-functions"]], "Automatic Mixed Precision examples": [[2046, "automatic-mixed-precision-examples"]], "Typical Mixed Precision Training": [[2046, "typical-mixed-precision-training"]], "Working with Unscaled Gradients": [[2046, "working-with-unscaled-gradients"]], "Gradient clipping": [[2046, "gradient-clipping"]], "Working with Scaled Gradients": [[2046, "working-with-scaled-gradients"]], "Gradient accumulation": [[2046, "gradient-accumulation"]], "Gradient penalty": [[2046, "gradient-penalty"]], "Working with Multiple Models, Losses, and Optimizers": [[2046, "working-with-multiple-models-losses-and-optimizers"]], "Working with Multiple GPUs": [[2046, "working-with-multiple-gpus"]], "DataParallel in a single process": [[2046, "dataparallel-in-a-single-process"]], "DistributedDataParallel, one GPU per process": [[2046, "distributeddataparallel-one-gpu-per-process"]], "DistributedDataParallel, multiple GPUs per process": [[2046, "distributeddataparallel-multiple-gpus-per-process"]], "Autocast and Custom Autograd Functions": [[2046, "autocast-and-custom-autograd-functions"]], "Functions with multiple inputs or autocastable ops": [[2046, "functions-with-multiple-inputs-or-autocastable-ops"]], "Functions that need a particular dtype": [[2046, "functions-that-need-a-particular-dtype"]], "Broadcasting semantics": [[2048, "broadcasting-semantics"]], "General semantics": [[2048, "general-semantics"]], "In-place semantics": [[2048, "in-place-semantics"]], "Backwards compatibility": [[2048, "backwards-compatibility"]], "Numerical accuracy": [[2064, "numerical-accuracy"]], "Batched computations or slice computations": [[2064, "batched-computations-or-slice-computations"]], "Extremal values": [[2064, "extremal-values"]], "Linear algebra (torch.linalg)": [[2064, "linear-algebra-torch-linalg"]], "Non-finite values": [[2064, "non-finite-values"]], "Extremal values in linalg": [[2064, "extremal-values-in-linalg"]], "TensorFloat-32(TF32) on Nvidia Ampere (and later) devices": [[2064, "tensorfloat-32-tf32-on-nvidia-ampere-and-later-devices"]], "Reduced Precision Reduction for FP16 and BF16 GEMMs": [[2064, "reduced-precision-reduction-for-fp16-and-bf16-gemms"]], "Reduced Precision FP16 and BF16 GEMMs and Convolutions on AMD Instinct MI200 devices": [[2064, "reduced-precision-fp16-and-bf16-gemms-and-convolutions-on-amd-instinct-mi200-devices"]], "Serialization semantics": [[2066, "serialization-semantics"]], "Table of Contents": [[2066, "table-of-contents"]], "Saving and loading tensors": [[2066, "saving-and-loading-tensors"]], "Saving and loading tensors preserves views": [[2066, "saving-and-loading-tensors-preserves-views"]], "Saving and loading torch.nn.Modules": [[2066, "saving-and-loading-torch-nn-modules"]], "Serialized file format for torch.save": [[2066, "serialized-file-format-for-torch-save"]], "Serializing torch.nn.Modules and loading them in C++": [[2066, "serializing-torch-nn-modules-and-loading-them-in-c"]], "Saving and loading ScriptModules across PyTorch versions": [[2066, "saving-and-loading-scriptmodules-across-pytorch-versions"]], "torch.div performing integer division": [[2066, "torch-div-performing-integer-division"]], "torch.full always inferring a float dtype": [[2066, "torch-full-always-inferring-a-float-dtype"]], "Utility functions": [[2066, "utility-functions"], [2079, "utility-functions"]], "My model reports \u201ccuda runtime error(2): out of memory\u201d": [[2055, "my-model-reports-cuda-runtime-error-2-out-of-memory"]], "My GPU memory isn\u2019t freed properly": [[2055, "my-gpu-memory-isn-t-freed-properly"]], "My out of memory exception handler can\u2019t allocate memory": [[2055, "my-out-of-memory-exception-handler-can-t-allocate-memory"]], "My data loader workers return identical random numbers": [[2055, "my-data-loader-workers-return-identical-random-numbers"]], "My recurrent network doesn\u2019t work with data parallelism": [[2055, "my-recurrent-network-doesn-t-work-with-data-parallelism"]], "Autograd mechanics": [[2047, "autograd-mechanics"]], "How autograd encodes the history": [[2047, "how-autograd-encodes-the-history"]], "Saved tensors": [[2047, "saved-tensors"]], "Gradients for non-differentiable functions": [[2047, "gradients-for-non-differentiable-functions"]], "Setting requires_grad": [[2047, "setting-requires-grad"]], "Grad Modes": [[2047, "grad-modes"]], "Default Mode (Grad Mode)": [[2047, "default-mode-grad-mode"]], "No-grad Mode": [[2047, "no-grad-mode"]], "Inference Mode": [[2047, "inference-mode"]], "Evaluation Mode (nn.Module.eval())": [[2047, "evaluation-mode-nn-module-eval"]], "In-place operations with autograd": [[2047, "in-place-operations-with-autograd"]], "In-place correctness checks": [[2047, "in-place-correctness-checks"], [1, "in-place-correctness-checks"]], "Multithreaded Autograd": [[2047, "multithreaded-autograd"]], "Concurrency on CPU": [[2047, "concurrency-on-cpu"]], "Non-determinism": [[2047, "non-determinism"]], "Graph retaining": [[2047, "graph-retaining"]], "Thread Safety on Autograd Node": [[2047, "thread-safety-on-autograd-node"]], "No thread safety on C++ hooks": [[2047, "no-thread-safety-on-c-hooks"]], "Autograd for Complex Numbers": [[2047, "autograd-for-complex-numbers"]], "What are complex derivatives?": [[2047, "what-are-complex-derivatives"]], "Wirtinger Calculus comes into the picture \u2026": [[2047, "wirtinger-calculus-comes-into-the-picture"]], "How is Wirtinger Calculus useful in optimization?": [[2047, "how-is-wirtinger-calculus-useful-in-optimization"]], "How does PyTorch compute the conjugate Wirtinger derivative?": [[2047, "how-does-pytorch-compute-the-conjugate-wirtinger-derivative"]], "How can I write my own derivative formula for a complex function?": [[2047, "how-can-i-write-my-own-derivative-formula-for-a-complex-function"]], "What about cross-domain functions?": [[2047, "what-about-cross-domain-functions"]], "Hooks for saved tensors": [[2047, "hooks-for-saved-tensors"]], "Registering hooks for a saved tensor": [[2047, "registering-hooks-for-a-saved-tensor"]], "Registering default hooks for saved tensors": [[2047, "registering-default-hooks-for-saved-tensors"]], "Backward Hooks execution": [[2047, "backward-hooks-execution"]], "Whether a particular hook will be fired": [[2047, "whether-a-particular-hook-will-be-fired"]], "The order in which the different hooks are fired": [[2047, "the-order-in-which-the-different-hooks-are-fired"]], "Special hooks": [[2047, "special-hooks"]], "Behavior of Tensor hooks when Tensor is modified in-place": [[2047, "behavior-of-tensor-hooks-when-tensor-is-modified-in-place"]], "Quantization API Reference": [[2079, "quantization-api-reference"], [2076, "quantization-api-reference"]], "torch.ao.quantization": [[2079, "torch-ao-quantization"]], "Top level APIs": [[2079, "top-level-apis"]], "Preparing model for quantization": [[2079, "preparing-model-for-quantization"]], "torch.ao.quantization.quantize_fx": [[2079, "torch-ao-quantization-quantize-fx"]], "torch.ao.quantization.qconfig_mapping": [[2079, "torch-ao-quantization-qconfig-mapping"]], "torch.ao.quantization.backend_config": [[2079, "torch-ao-quantization-backend-config"]], "torch.ao.quantization.fx.custom_config": [[2079, "torch-ao-quantization-fx-custom-config"]], "torch.ao.quantization.quantizer": [[2079, "module-torch.ao.quantization.quantizer"]], "torch.ao.quantization.pt2e (quantization in pytorch 2.0 export implementation)": [[2079, "module-torch.ao.quantization.pt2e"]], "torch.ao.quantization.pt2e.export_utils": [[2079, "torch-ao-quantization-pt2e-export-utils"]], "torch (quantization related functions)": [[2079, "torch-quantization-related-functions"]], "torch.Tensor (quantization related methods)": [[2079, "torch-tensor-quantization-related-methods"]], "torch.ao.quantization.observer": [[2079, "torch-ao-quantization-observer"]], "torch.ao.quantization.fake_quantize": [[2079, "torch-ao-quantization-fake-quantize"]], "torch.ao.quantization.qconfig": [[2079, "torch-ao-quantization-qconfig"]], "torch.ao.nn.intrinsic": [[2079, "module-torch.ao.nn.intrinsic"]], "torch.ao.nn.intrinsic.qat": [[2079, "module-torch.ao.nn.intrinsic.qat"]], "torch.ao.nn.intrinsic.quantized": [[2079, "module-torch.ao.nn.intrinsic.quantized"]], "torch.ao.nn.intrinsic.quantized.dynamic": [[2079, "module-torch.ao.nn.intrinsic.quantized.dynamic"]], "torch.ao.nn.qat": [[2079, "module-torch.ao.nn.qat"]], "torch.ao.nn.qat.dynamic": [[2079, "module-torch.ao.nn.qat.dynamic"]], "torch.ao.nn.quantized": [[2079, "module-torch.ao.nn.quantized.modules"]], "torch.ao.nn.quantized.functional": [[2079, "module-torch.ao.nn.quantized.functional"]], "torch.ao.nn.quantizable": [[2079, "torch-ao-nn-quantizable"]], "torch.ao.nn.quantized.dynamic": [[2079, "module-torch.ao.nn.quantized.dynamic"]], "Quantized dtypes and quantization schemes": [[2079, "quantized-dtypes-and-quantization-schemes"]], "TorchScript-based ONNX Exporter": [[2071, "torchscript-based-onnx-exporter"], [2068, "torchscript-based-onnx-exporter"]], "Example: AlexNet from PyTorch to ONNX": [[2071, "example-alexnet-from-pytorch-to-onnx"]], "Tracing vs Scripting": [[2071, "tracing-vs-scripting"]], "Avoiding Pitfalls": [[2071, "avoiding-pitfalls"]], "Avoid NumPy and built-in Python types": [[2071, "avoid-numpy-and-built-in-python-types"]], "Avoid Tensor.data": [[2071, "avoid-tensor-data"]], "Avoid in-place operations when using tensor.shape in tracing mode": [[2071, "avoid-in-place-operations-when-using-tensor-shape-in-tracing-mode"]], "Differences in Operator Implementations": [[2071, "differences-in-operator-implementations"]], "Unsupported Tensor Indexing Patterns": [[2071, "unsupported-tensor-indexing-patterns"]], "Reads / Gets": [[2071, "reads-gets"]], "Writes / Sets": [[2071, "writes-sets"]], "Adding support for operators": [[2071, "adding-support-for-operators"]], "ONNX exporter internals": [[2071, "onnx-exporter-internals"]], "ATen operators": [[2071, "aten-operators"]], "List of supported operators": [[2071, "list-of-supported-operators"]], "Adding support for an aten or quantized operator": [[2071, "adding-support-for-an-aten-or-quantized-operator"]], "torch.autograd.Functions": [[2071, "torch-autograd-functions"]], "Static Symbolic Method": [[2071, "static-symbolic-method"]], "Inline Autograd Function": [[2071, "inline-autograd-function"]], "Custom operators": [[2071, "custom-operators"]], "ONNX-script functions": [[2071, "onnx-script-functions"]], "C++ Operators": [[2071, "c-operators"]], "Discovering all unconvertible ATen ops at once": [[2071, "discovering-all-unconvertible-aten-ops-at-once"]], "Classes": [[2071, "classes"]], "torch.profiler": [[2075, "torch-profiler"]], "Intel Instrumentation and Tracing Technology APIs": [[2075, "intel-instrumentation-and-tracing-technology-apis"]], "ONNX Backend for TorchDynamo": [[2070, "onnx-backend-for-torchdynamo"]], "Reproducibility": [[2065, "reproducibility"]], "Controlling sources of randomness": [[2065, "controlling-sources-of-randomness"]], "PyTorch random number generator": [[2065, "pytorch-random-number-generator"]], "Python": [[2065, "python"]], "Random number generators in other libraries": [[2065, "random-number-generators-in-other-libraries"]], "CUDA convolution benchmarking": [[2065, "cuda-convolution-benchmarking"]], "Avoiding nondeterministic algorithms": [[2065, "avoiding-nondeterministic-algorithms"]], "CUDA convolution determinism": [[2065, "cuda-convolution-determinism"]], "CUDA RNN and LSTM": [[2065, "cuda-rnn-and-lstm"]], "Filling uninitialized memory": [[2065, "filling-uninitialized-memory"]], "DataLoader": [[2065, "dataloader"]], "torch.nn": [[2041, "module-torch.nn"], [2041, "id1"]], "Containers": [[2041, "containers"]], "Convolution Layers": [[2041, "convolution-layers"]], "Pooling layers": [[2041, "pooling-layers"]], "Padding Layers": [[2041, "padding-layers"]], "Non-linear Activations (weighted sum, nonlinearity)": [[2041, "non-linear-activations-weighted-sum-nonlinearity"]], "Non-linear Activations (other)": [[2041, "non-linear-activations-other"]], "Normalization Layers": [[2041, "normalization-layers"]], "Recurrent Layers": [[2041, "recurrent-layers"]], "Transformer Layers": [[2041, "transformer-layers"]], "Linear Layers": [[2041, "linear-layers"]], "Dropout Layers": [[2041, "dropout-layers"]], "Sparse Layers": [[2041, "sparse-layers"]], "Distance Functions": [[2041, "distance-functions"]], "Loss Functions": [[2041, "loss-functions"]], "Vision Layers": [[2041, "vision-layers"]], "Shuffle Layers": [[2041, "shuffle-layers"]], "DataParallel Layers (multi-GPU, distributed)": [[2041, "module-torch.nn.parallel"]], "Quantized Functions": [[2041, "quantized-functions"]], "Lazy Modules Initialization": [[2041, "lazy-modules-initialization"]], "Aliases": [[2041, "aliases"]], "torch.Storage": [[2088, "torch-storage"]], "torch.nn.functional": [[2044, "torch-nn-functional"]], "Convolution functions": [[2044, "convolution-functions"]], "Pooling functions": [[2044, "pooling-functions"]], "Attention Mechanisms": [[2044, "attention-mechanisms"]], "Non-linear activation functions": [[2044, "non-linear-activation-functions"]], "Linear functions": [[2044, "linear-functions"]], "Dropout functions": [[2044, "dropout-functions"]], "Sparse functions": [[2044, "sparse-functions"]], "Distance functions": [[2044, "distance-functions"]], "Loss functions": [[2044, "loss-functions"]], "Vision functions": [[2044, "vision-functions"]], "DataParallel functions (multi-GPU, distributed)": [[2044, "dataparallel-functions-multi-gpu-distributed"]], "data_parallel": [[2044, "data-parallel"]], "CUDA semantics": [[2050, "cuda-semantics"]], "TensorFloat-32 (TF32) on Ampere (and later) devices": [[2050, "tensorfloat-32-tf32-on-ampere-and-later-devices"]], "Reduced Precision Reduction in FP16 GEMMs": [[2050, "reduced-precision-reduction-in-fp16-gemms"]], "Reduced Precision Reduction in BF16 GEMMs": [[2050, "reduced-precision-reduction-in-bf16-gemms"]], "Asynchronous execution": [[2050, "asynchronous-execution"]], "CUDA streams": [[2050, "cuda-streams"]], "Stream semantics of backward passes": [[2050, "stream-semantics-of-backward-passes"]], "BC note: Using grads on the default stream": [[2050, "bc-note-using-grads-on-the-default-stream"]], "Memory management": [[2050, "memory-management"], [2059, "memory-management"], [17, "memory-management"]], "Optimizing memory usage  with PYTORCH_CUDA_ALLOC_CONF": [[2050, "optimizing-memory-usage-with-pytorch-cuda-alloc-conf"]], "Using custom memory 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1710, 1719, 1720, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1751, 1752, 1765, 1767, 1770, 1780, 1781, 1834, 1851, 1869, 1874, 1899, 1949, 1953, 1971, 1983, 2018, 2020, 2022, 2024, 2028, 2038, 2039, 2047, 2048, 2050, 2053, 2062, 2064, 2065, 2071, 2072, 2073, 2074, 2076, 2081, 2083, 2085, 2087, 2089, 2092, 2111, 2116, 2117], "autograd_tensor": 1, "kwarg": [1, 5, 14, 23, 28, 29, 30, 32, 33, 34, 47, 52, 53, 55, 64, 66, 582, 605, 750, 763, 765, 766, 822, 823, 824, 825, 827, 828, 894, 909, 910, 980, 1012, 1014, 1052, 1053, 1070, 1167, 1178, 1179, 1183, 1187, 1189, 1274, 1277, 1279, 1338, 1364, 1491, 1519, 1530, 1561, 1565, 1569, 1571, 1572, 1710, 1720, 1742, 1747, 1751, 1761, 1768, 1770, 1773, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1797, 1798, 1799, 1800, 1801, 1862, 1965, 1980, 1986, 2015, 2020, 2021, 2024, 2053, 2054, 2061, 2069, 2073, 2081, 2088, 2092, 2097, 2103, 2106, 2116, 2117, 2118], "base": [1, 3, 7, 9, 12, 14, 15, 20, 23, 28, 29, 30, 32, 33, 34, 35, 37, 40, 45, 47, 48, 50, 52, 53, 55, 60, 64, 87, 88, 89, 683, 794, 799, 803, 805, 823, 824, 825, 827, 828, 865, 866, 904, 907, 909, 920, 921, 930, 976, 998, 1071, 1072, 1087, 1108, 1110, 1153, 1195, 1205, 1228, 1238, 1276, 1288, 1300, 1338, 1349, 1351, 1353, 1361, 1443, 1466, 1503, 1530, 1533, 1534, 1535, 1539, 1545, 1547, 1574, 1576, 1578, 1653, 1688, 1719, 1720, 1725, 1726, 1734, 1742, 1746, 1748, 1789, 1800, 1801, 1827, 1837, 1862, 1874, 1931, 1932, 1947, 1957, 1959, 1981, 2016, 2018, 2020, 2049, 2050, 2052, 2053, 2056, 2061, 2075, 2076, 2081, 2082, 2086, 2087, 2090, 2091, 2093, 2096, 2097, 2104, 2105, 2106, 2108, 2110], "static": [1, 3, 8, 14, 29, 33, 35, 37, 47, 52, 53, 55, 66, 71, 72, 75, 797, 802, 818, 820, 827, 829, 835, 861, 863, 893, 894, 895, 896, 909, 910, 1182, 1183, 1189, 1195, 1213, 1288, 1574, 1720, 1906, 2017, 2018, 2019, 2020, 2050, 2056, 2057, 2060, 2068, 2069, 2077, 2081, 2088, 2102, 2104, 2106], "Then": [1, 29, 33, 48, 64, 932, 1476, 1582, 1737, 1782, 1969, 2047, 2048, 2050, 2052, 2053, 2054, 2057, 2064, 2065, 2071, 2073, 2074, 2081, 2082, 2096, 2102, 2105, 2106, 2109], "op": [1, 4, 5, 24, 28, 30, 33, 52, 53, 55, 64, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 80, 84, 88, 89, 152, 505, 526, 606, 760, 795, 796, 797, 826, 829, 858, 865, 866, 897, 904, 907, 909, 910, 918, 966, 976, 978, 1015, 1031, 1033, 1037, 1038, 1052, 1053, 1079, 1083, 1085, 1168, 1225, 1275, 1288, 1290, 1291, 1346, 1352, 1402, 1406, 1411, 1412, 1413, 1547, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1796, 1797, 1798, 1799, 1800, 1801, 1818, 1876, 1955, 1987, 1990, 1992, 1994, 1995, 2007, 2010, 2011, 2016, 2020, 2026, 2027, 2030, 2033, 2035, 2038, 2039, 2049, 2050, 2052, 2053, 2063, 2069, 2074, 2075, 2076, 2077, 2078, 2079, 2086, 2088, 2090, 2092, 2097, 2102, 2103, 2107, 2108, 2109, 2110, 2112, 2115, 2116, 2117], "directli": [1, 3, 7, 9, 14, 15, 23, 24, 28, 30, 33, 34, 35, 36, 37, 46, 52, 53, 55, 59, 64, 66, 79, 559, 735, 750, 894, 904, 907, 909, 978, 1093, 1161, 1168, 1175, 1177, 1185, 1218, 1305, 1536, 1564, 1583, 1647, 1694, 1762, 1953, 2017, 2019, 2020, 2024, 2028, 2033, 2040, 2047, 2050, 2052, 2053, 2054, 2056, 2058, 2060, 2061, 2062, 2063, 2066, 2074, 2075, 2076, 2081, 2086, 2091, 2093, 2099, 2104, 2106, 2107, 2108, 2110, 2111, 2116, 2117], "ctx": [1, 5, 45, 66, 70, 893, 894, 895, 904, 905, 906, 907, 908, 909, 910, 2024, 2046, 2053, 2054, 2071], "gradcheck": [1, 1905, 2016, 2024, 2053, 2086], "extend": [1, 23, 28, 30, 33, 35, 39, 50, 64, 865, 894, 896, 904, 907, 909, 910, 1532, 1541, 1905, 1969, 2016, 2040, 2047, 2060, 2062, 2063, 2071, 2072, 2074, 2079, 2086, 2104, 2105, 2118], "staticmethod": [1, 66, 894, 896, 904, 905, 906, 907, 908, 909, 910, 2020, 2046, 2053, 2071, 2081], "result": [1, 3, 4, 5, 7, 8, 9, 12, 14, 18, 19, 23, 24, 28, 30, 33, 35, 37, 40, 45, 48, 52, 53, 55, 60, 61, 63, 64, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 86, 87, 89, 155, 223, 224, 256, 257, 317, 337, 400, 498, 500, 501, 558, 585, 586, 587, 589, 590, 620, 689, 690, 691, 692, 693, 696, 698, 699, 700, 702, 763, 796, 881, 883, 902, 903, 912, 913, 914, 915, 916, 917, 923, 924, 932, 944, 947, 958, 962, 967, 973, 975, 976, 978, 979, 990, 994, 996, 1021, 1023, 1025, 1026, 1052, 1053, 1066, 1089, 1090, 1091, 1092, 1093, 1105, 1110, 1128, 1131, 1137, 1146, 1153, 1155, 1158, 1163, 1164, 1167, 1168, 1169, 1172, 1173, 1178, 1179, 1183, 1187, 1198, 1203, 1211, 1214, 1218, 1236, 1237, 1239, 1251, 1265, 1274, 1277, 1278, 1286, 1290, 1291, 1293, 1295, 1296, 1300, 1314, 1316, 1318, 1319, 1327, 1331, 1333, 1335, 1336, 1337, 1344, 1354, 1355, 1362, 1372, 1374, 1375, 1376, 1377, 1379, 1380, 1421, 1424, 1439, 1440, 1441, 1466, 1468, 1469, 1470, 1474, 1476, 1481, 1495, 1500, 1530, 1536, 1546, 1574, 1575, 1576, 1577, 1578, 1582, 1618, 1636, 1647, 1703, 1706, 1707, 1720, 1734, 1737, 1770, 1773, 1774, 1775, 1776, 1782, 1785, 1812, 1818, 1820, 1827, 1828, 1831, 1837, 1850, 1856, 1871, 1886, 1898, 1909, 1911, 1912, 1916, 1923, 1925, 1926, 1927, 1930, 1931, 1932, 1942, 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2104, 2105, 2107, 2108, 2110, 2114, 2116, 2117, 2124], "via": [2, 7, 14, 15, 23, 28, 30, 34, 35, 38, 45, 52, 53, 55, 59, 62, 64, 417, 488, 519, 619, 923, 924, 932, 963, 984, 1009, 1046, 1066, 1114, 1171, 1187, 1191, 1192, 1194, 1196, 1346, 1347, 1444, 1445, 1446, 1466, 1484, 1492, 1493, 1494, 1502, 1570, 1734, 1769, 1772, 1812, 2017, 2019, 2020, 2024, 2032, 2033, 2037, 2040, 2045, 2047, 2050, 2053, 2054, 2055, 2059, 2061, 2063, 2064, 2071, 2074, 2076, 2081, 2082, 2086, 2088, 2089, 2090, 2103, 2104, 2105, 2107, 2109, 2113, 2118], "readonli": 2, "int": [2, 3, 12, 18, 19, 23, 24, 28, 30, 32, 33, 34, 35, 37, 41, 44, 45, 47, 48, 51, 52, 53, 55, 64, 66, 74, 75, 77, 80, 90, 218, 220, 234, 235, 244, 256, 315, 317, 319, 323, 439, 446, 447, 449, 451, 459, 474, 478, 495, 499, 501, 515, 517, 519, 522, 539, 545, 547, 548, 560, 562, 568, 585, 586, 587, 589, 590, 609, 619, 683, 696, 698, 699, 700, 702, 758, 759, 778, 780, 782, 783, 788, 789, 790, 822, 878, 879, 880, 882, 896, 904, 907, 909, 910, 927, 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2086, 2089, 2095, 2096, 2097, 2099, 2104, 2114], "rocm": [2, 17, 689, 692, 944, 956, 1369, 1379, 1457, 1458, 1459, 1460, 1461, 1462, 1482, 1501, 1517, 2016], "hipbla": [2, 17, 19], "hipblaslt": [2, 17, 19], "offer": [2, 28, 30, 55, 58, 1720, 1968, 2050, 2053, 2059, 2074, 2075, 2081, 2086, 2103, 2108, 2112, 2120], "wherev": [2, 9, 2038], "prefer": [2, 5, 9, 23, 28, 30, 37, 48, 55, 866, 882, 914, 1202, 1272, 1315, 1328, 1332, 1340, 1347, 1537, 1688, 1866, 1927, 1946, 2017, 2028, 2047, 2050, 2073, 2074, 2086, 2108], "environ": [2, 3, 7, 14, 15, 18, 19, 22, 24, 30, 33, 35, 37, 40, 45, 51, 52, 64, 81, 83, 683, 1026, 1187, 1189, 1211, 1284, 1290, 1500, 1546, 1968, 2015, 2016, 2017, 2026, 2047, 2049, 2050, 2052, 2059, 2064, 2065, 2067, 2081, 2099, 2101, 2103, 2108, 2117], "variabl": [2, 3, 5, 12, 14, 18, 19, 22, 24, 33, 35, 37, 40, 45, 47, 51, 53, 55, 60, 64, 66, 69, 74, 75, 81, 83, 450, 683, 715, 716, 717, 718, 719, 720, 721, 722, 723, 726, 727, 728, 729, 731, 732, 733, 734, 735, 737, 741, 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1060, 1061, 1062, 1064, 1066, 1067, 1068, 1073, 1074, 1075, 1076, 1079, 1080, 1083, 1085, 1087, 1088, 1130, 1347, 1376, 1402, 1403, 1404, 1405, 1406, 1411, 1412, 1413, 1449, 1457, 1458, 1459, 1460, 1461, 1462, 1481, 1500, 1546, 1594, 1611, 1612, 1613, 1614, 1615, 1616, 1620, 1688, 1756, 1757, 1869, 1943, 1971, 1983, 1987, 1988, 1989, 1990, 1992, 2007, 2010, 2011, 2017, 2018, 2020, 2037, 2038, 2039, 2040, 2047, 2049, 2050, 2058, 2065, 2072, 2076, 2086, 2090, 2093, 2106, 2112, 2114, 2119], "incorrect": [2, 4, 5, 55, 64, 86, 87, 89, 256, 515, 558, 904, 907, 909, 923, 932, 958, 978, 1290, 1333, 1346, 1536, 1574, 1575, 1576, 1577, 1578, 1706, 1775, 1916, 1927, 2017, 2020, 2024, 2050, 2064, 2071, 2105, 2120], "_blasbackend": 2, "preferred_linalg_librari": [2, 1311], "heurist": [2, 14, 23, 47, 48, 64, 981, 1110, 2056, 2102, 2111], "cusolv": [2, 1338, 1339, 1931], "magma": [2, 1320, 1364, 1830, 1931, 2067, 2086], "algebra": [2, 9, 1110, 1311, 1332, 2016, 2025], "decid": [2, 4, 7, 28, 37, 47, 59, 488, 1185, 1751, 2027, 2071, 2086, 2107, 2108, 2111], "pick": [2, 28, 46, 48, 515, 976, 2047, 2081, 2104, 2106, 2111], "torch_linalg_prefer_cusolv": 2, "linalg": [2, 11, 408, 966, 967, 968, 969, 1008, 1096, 1218, 1252, 1355, 1364, 1365, 1366, 1370, 1371, 1734, 1735, 1740, 1775, 1817, 1822, 1824, 1830, 1900, 1931, 1932, 1955, 1977, 2016], "inv": [2, 35, 1252, 1306, 1310, 1316, 1332, 1336, 1340], "inv_ex": [2, 1315], "cholesky_ex": [2, 1304], "lu_factor": [2, 1323, 1324, 1364, 1365, 1366], "lu": [2, 10, 1316, 1322, 1323, 1324, 1365, 1366, 2018], "eigh": [2, 1304, 1310, 1313, 1332, 1338, 2064], "eighval": 2, "svdval": [2, 1306, 1320, 1329, 1338, 1931, 2064], "_linalgbackend": 2, "sdpaparam": 2, "flash_sdp_en": 2, "flash": [2, 1589, 1594], "scale": [2, 7, 23, 33, 35, 37, 46, 48, 99, 175, 475, 477, 619, 688, 692, 693, 694, 741, 742, 743, 744, 745, 746, 747, 752, 753, 754, 755, 756, 757, 758, 759, 762, 773, 775, 776, 777, 778, 780, 783, 784, 798, 802, 805, 822, 823, 824, 825, 828, 944, 1124, 1125, 1128, 1146, 1178, 1179, 1361, 1438, 1467, 1472, 1473, 1474, 1490, 1502, 1558, 1583, 1584, 1585, 1589, 1594, 1627, 1628, 1629, 1645, 1647, 1688, 1689, 1694, 1785, 1806, 1832, 1833, 1834, 1835, 1836, 1909, 1910, 1928, 1980, 2016, 2018, 2039, 2045, 2050, 2055, 2057, 2061, 2069, 2076, 2077, 2079, 2087, 2108], "product": [2, 15, 28, 30, 35, 47, 152, 689, 692, 693, 694, 763, 897, 902, 913, 915, 916, 917, 918, 944, 956, 962, 966, 994, 1008, 1020, 1068, 1073, 1087, 1088, 1091, 1107, 1110, 1174, 1178, 1179, 1251, 1295, 1307, 1314, 1340, 1341, 1343, 1369, 1376, 1379, 1418, 1481, 1482, 1500, 1501, 1589, 1594, 1635, 1688, 1734, 1818, 1819, 1828, 1874, 1948, 1963, 1977, 1980, 2016, 2017, 2038, 2047, 2058, 2060, 2064, 2074, 2076, 2086, 2105, 2119], "attent": [2, 7, 34, 738, 1443, 1536, 1574, 1576, 1578, 1589, 1591, 1609, 1688, 2016, 2067, 2090, 2105], "enable_mem_efficient_sdp": [2, 1688], "mem_efficient_sdp_en": 2, "enable_flash_sdp": [2, 1688], "math_sdp_en": 2, "math": [2, 23, 64, 1120, 1326, 1589, 1594, 1648, 1688, 1820, 1837, 1932, 2016, 2017, 2019, 2020, 2035, 2056, 2064, 2086, 2087, 2093, 2117], "enable_math_sdp": [2, 1688], "cudnn_sdp_en": 2, "enable_cudnn_sdp": 2, "can_use_flash_attent": 2, "debug": [2, 4, 5, 8, 19, 20, 23, 33, 38, 44, 52, 81, 83, 683, 830, 831, 835, 847, 923, 924, 976, 978, 985, 1009, 1043, 1084, 1222, 1304, 1713, 1714, 1715, 1716, 1873, 1880, 2016, 2019, 2026, 2047, 2049, 2050, 2052, 2059, 2060, 2061, 2065, 2067, 2069, 2071, 2074, 2096, 2104, 2105, 2106, 2109, 2110, 2113, 2119, 2120, 2121], "check": [2, 3, 4, 5, 11, 14, 19, 20, 23, 28, 29, 30, 35, 47, 55, 66, 67, 72, 75, 223, 342, 501, 697, 865, 904, 905, 907, 908, 909, 910, 923, 924, 930, 978, 1011, 1012, 1014, 1018, 1048, 1066, 1185, 1189, 1197, 1198, 1206, 1207, 1261, 1271, 1274, 1290, 1291, 1304, 1305, 1310, 1311, 1313, 1316, 1318, 1323, 1329, 1332, 1336, 1338, 1339, 1364, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1530, 1710, 1720, 1737, 1740, 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2045, 2047, 2058, 2072, 2079, 2089, 2112], "total_tim": 3, "choic": [3, 8, 9, 28, 1290, 1338, 1531, 1540, 1837, 2049, 2071, 2079, 2086, 2104, 2105, 2117], "block": [3, 7, 8, 20, 23, 28, 30, 32, 34, 47, 50, 55, 63, 64, 488, 585, 586, 587, 939, 955, 1011, 1066, 1295, 1347, 1457, 1458, 1459, 1460, 1461, 1462, 1476, 1506, 1507, 1508, 1509, 1510, 1511, 1533, 1582, 1630, 1706, 1720, 1913, 1914, 1915, 2017, 2019, 2020, 2033, 2037, 2041, 2047, 2050, 2052, 2056, 2058, 2071, 2076, 2081, 2086, 2098, 2115, 2119, 2121], "qualiti": [3, 7, 24], "balanc": [3, 976], "compet": [3, 2063], "amort": 3, "invoc": [3, 5, 64, 845, 976, 981, 1187, 1277, 1290, 2017, 2020, 2050, 2053, 2060, 2071, 2081, 2083, 2102, 2115], "less": [3, 6, 7, 14, 23, 24, 28, 35, 50, 52, 55, 366, 683, 912, 914, 923, 924, 998, 1062, 1080, 1110, 1154, 1158, 1167, 1299, 1311, 1347, 1363, 1364, 1434, 1490, 1544, 1553, 1562, 1568, 1764, 1850, 1957, 1959, 2015, 2018, 2020, 2040, 2050, 2053, 2056, 2063, 2064, 2072, 2076, 2105, 2108, 2115], 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2121], "amelior": 3, "suffici": [3, 14, 24, 28, 35, 39, 47, 48, 53, 55, 488, 1787, 1788, 1800, 1932, 2015, 2024, 2086, 2089, 2108], "callgrind_control": 3, "callgrind_annot": 3, "boundari": [3, 33, 64, 782, 788, 960, 1228, 1451, 1452, 1453, 1454, 1455, 1456, 1552, 1553, 1554, 1555, 1556, 1557, 1583, 1586, 1587, 1588, 1647, 1707, 1806, 1812, 2018, 2052, 2074, 2081, 2108], "caller": [3, 37, 47, 64, 858, 1274, 1530, 1578, 1916, 2047, 2050, 2081, 2083], "structur": [3, 5, 9, 12, 23, 24, 28, 33, 36, 37, 40, 48, 52, 53, 55, 64, 66, 67, 71, 75, 896, 909, 910, 942, 976, 990, 1161, 1174, 1179, 1187, 1194, 1195, 1290, 1530, 1590, 1747, 1751, 1783, 1820, 1932, 1980, 2016, 2019, 2021, 2027, 2033, 2040, 2050, 2052, 2053, 2054, 2056, 2063, 2066, 2067, 2069, 2071, 2073, 2074, 2081, 2091, 2092, 2093, 2095, 2097, 2099, 2104, 2105, 2106, 2108, 2109, 2113, 2119], "restrict": [3, 8, 12, 23, 35, 53, 55, 60, 61, 978, 990, 1346, 1369, 1465, 2019, 2020, 2021, 2039, 2040, 2047, 2050, 2058, 2076, 2104], 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490, 749, 750, 775, 776, 777, 782, 788, 789, 790, 818, 820, 826, 829, 863, 864, 893, 895, 899, 902, 903, 904, 909, 910, 912, 913, 914, 915, 919, 920, 921, 923, 976, 981, 1009, 1043, 1084, 1085, 1114, 1126, 1127, 1129, 1131, 1132, 1133, 1134, 1135, 1136, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1147, 1168, 1171, 1172, 1173, 1174, 1177, 1178, 1183, 1188, 1222, 1257, 1258, 1272, 1274, 1275, 1278, 1290, 1292, 1333, 1346, 1376, 1390, 1391, 1413, 1444, 1445, 1446, 1457, 1458, 1459, 1473, 1484, 1492, 1493, 1494, 1502, 1503, 1504, 1505, 1512, 1513, 1514, 1530, 1547, 1570, 1583, 1584, 1611, 1612, 1613, 1628, 1636, 1647, 1675, 1688, 1707, 1708, 1709, 1721, 1729, 1731, 1735, 1740, 1773, 1806, 1814, 1830, 1873, 1875, 1968, 2016, 2018, 2024, 2030, 2038, 2045, 2050, 2052, 2054, 2055, 2056, 2057, 2061, 2068, 2069, 2072, 2075, 2077, 2078, 2079, 2081, 2092, 2095, 2099, 2102, 2106, 2107, 2108, 2109, 2110, 2112, 2117, 2118], "correct": [4, 5, 6, 7, 24, 28, 29, 30, 33, 35, 47, 52, 207, 208, 211, 223, 557, 582, 605, 606, 617, 625, 904, 905, 909, 924, 998, 1131, 1133, 1141, 1142, 1143, 1194, 1249, 1272, 1275, 1290, 1291, 1310, 1466, 1483, 1495, 1710, 1720, 1761, 1877, 1925, 1926, 1975, 1976, 2017, 2018, 2019, 2024, 2028, 2038, 2039, 2050, 2053, 2058, 2088, 2105, 2112, 2116], "launch": [4, 14, 23, 31, 33, 37, 39, 40, 45, 46, 47, 51, 63, 1012, 1720, 2016, 2047, 2049, 2050, 2052, 2053, 2081, 2102, 2110], "spent": [4, 28, 937, 1812, 2049, 2061, 2108, 2115, 2117], "appear": [4, 24, 28, 35, 52, 53, 64, 858, 1055, 1110, 1151, 1152, 1179, 1346, 1380, 1382, 1721, 1852, 1880, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1980, 2017, 2020, 2038, 2039, 2053, 2054, 2061, 2071, 2074, 2105, 2108, 2115], "extrem": [4, 28, 1720, 2047, 2071, 2107], "expens": [4, 23, 35, 55, 1734, 2050, 2058, 2060, 2075, 2081, 2092, 2104, 2108, 2111, 2114, 2117], "bound": [4, 15, 24, 28, 52, 55, 483, 798, 960, 971, 1124, 1125, 1182, 1189, 1193, 1198, 1274, 1439, 1440, 1441, 1523, 1524, 1525, 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1473, 1720, 1727, 1728, 2020, 2049], "limit": [5, 8, 9, 12, 20, 23, 33, 53, 55, 56, 61, 83, 990, 1080, 1168, 1288, 1395, 1449, 1472, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1688, 1720, 1751, 1878, 2016, 2020, 2024, 2035, 2037, 2039, 2040, 2047, 2050, 2052, 2057, 2061, 2064, 2065, 2066, 2068, 2074, 2076, 2079, 2081, 2082, 2086, 2092, 2093, 2104, 2107, 2108, 2114, 2117], "reentrant": [5, 1720], "soon": [5, 47, 52, 55, 796, 2047, 2076, 2081, 2083, 2108], "intermedi": [5, 12, 14, 33, 36, 52, 53, 60, 64, 83, 957, 990, 1161, 1168, 1175, 1364, 1473, 1574, 1576, 1578, 1628, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 2017, 2020, 2024, 2050, 2053, 2054, 2055, 2064, 2097, 2104, 2105, 2107], "set_checkpoint_early_stop": 5, "entireti": 5, "graph": [5, 8, 12, 28, 30, 33, 35, 55, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 82, 83, 84, 85, 90, 141, 152, 223, 224, 683, 750, 795, 796, 818, 819, 820, 826, 829, 897, 904, 907, 909, 918, 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10, 65, 1168, 2053, 2118], "resolut": [9, 1542, 1543, 1601, 1636, 1678, 1679, 1953, 2021, 2074, 2122], "conclus": 9, "publicli": [9, 2118], "vision": [9, 1284, 1465, 1619, 2015, 2016, 2057, 2110], "roadmap": [9, 10], "parti": [9, 47, 2015, 2016, 2017, 2024, 2050, 2054, 2057, 2061, 2074, 2105], "triag": [9, 10], "meet": [9, 10, 12, 30, 46, 990, 1304, 2050, 2108], "Their": [9, 1102, 2053, 2107], "articul": 9, "cohes": 9, "negoti": [9, 2081], "contenti": 9, "broad": [9, 2061, 2120], "stakehold": 9, "power": [9, 12, 46, 1073, 1126, 1127, 1129, 1131, 1132, 1133, 1134, 1135, 1136, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1147, 1153, 1298, 1328, 1342, 1497, 1498, 1499, 1657, 1658, 1659, 1735, 1769, 1784, 1813, 1827, 1851, 1974, 2021, 2050, 2086], "veto": 9, "admin": 9, "amongst": 9, "commonli": [9, 35, 55, 1376, 2020, 2022, 2046, 2047, 2056, 2073, 2076, 2089, 2098, 2101, 2104], "merit": 9, "demonstr": [9, 33, 48, 52, 64, 66, 74, 75, 1449, 2017, 2061, 2066, 2069, 2081, 2099, 2106, 2108, 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2090], "6125": 11, "1681": 11, "3773": 11, "3487": 11, "0861": 11, "7981": 11, "1681j": 11, "3487j": 11, "7981j": 11, "mul_": [11, 66, 79, 2018, 2038, 2040, 2086], "2250": [11, 1331, 1775], "7546": 11, "1722": 11, "x1": [11, 52, 964, 1322, 1464, 1522, 1579, 1580, 1618, 1676, 2018, 2112], "3j": [11, 28, 701, 991, 992, 1854, 1855, 1871], "4j": [11, 28, 1881], "0000": [11, 35, 515, 869, 912, 914, 947, 967, 971, 994, 1091, 1097, 1098, 1099, 1124, 1125, 1128, 1130, 1131, 1137, 1138, 1141, 1146, 1158, 1159, 1160, 1228, 1234, 1237, 1241, 1300, 1303, 1304, 1305, 1317, 1318, 1321, 1326, 1327, 1331, 1333, 1345, 1361, 1421, 1472, 1473, 1583, 1584, 1586, 1587, 1627, 1628, 1775, 1824, 1830, 1835, 1836, 1837, 1846, 1850, 1851, 1875, 1881, 1883, 1884, 1886, 1889, 1890, 1891, 1892, 1909, 1955, 1956, 1958, 1983, 2027, 2040, 2050, 2086, 2087, 2092], "6569": [11, 1241], "5708": [11, 1094], "7854": 11, "complex_tensor": 11, "pt": [11, 24, 30, 55, 1162, 1279, 1282, 1285, 1292, 1346, 1862, 2017, 2028, 2061, 2066, 2074, 2110], "conjug": [11, 332, 460, 695, 923, 968, 969, 991, 992, 1254, 1304, 1305, 1311, 1314, 1317, 1324, 1338, 1343, 1347, 1734, 1818, 1854, 1927, 1931, 1977, 2058, 2073, 2092], "wirting": [11, 923, 2058], "deriv": [11, 28, 33, 52, 55, 152, 741, 742, 743, 744, 745, 746, 784, 803, 827, 897, 918, 923, 924, 1174, 1178, 1185, 1228, 1271, 1332, 1364, 1578, 1710, 2016, 2019, 2053, 2054, 2058, 2081, 2086, 2087], "steepest": [11, 2047], "descent": [11, 35, 1784, 1800, 1804, 1805, 2047, 2061], "box": [11, 28, 48, 64, 978, 1179, 1187, 1980, 2039, 2047, 2052, 2069, 2103, 2104, 2109, 2110], "real_param": 11, "p": [11, 24, 30, 35, 55, 64, 156, 236, 288, 427, 428, 455, 490, 493, 494, 689, 692, 944, 946, 956, 964, 1104, 1295, 1306, 1312, 1313, 1321, 1322, 1364, 1366, 1369, 1379, 1419, 1438, 1467, 1468, 1469, 1470, 1472, 1473, 1474, 1495, 1497, 1498, 1499, 1535, 1539, 1541, 1579, 1580, 1602, 1621, 1622, 1623, 1624, 1627, 1628, 1629, 1657, 1658, 1659, 1669, 1673, 1676, 1677, 1688, 1704, 1725, 1738, 1740, 1746, 1755, 1775, 1800, 1851, 1908, 2018, 2019, 2046, 2047, 2050, 2055, 2058, 2063, 2073, 2075, 2086, 2087, 2111, 2112], "complex_optim": 11, "adamw": [11, 1787, 1791, 1797, 2073], "real_optim": 11, "slight": [11, 1870, 2086, 2089], "discrep": [11, 1720, 1837, 2058], "foreach": [11, 1724, 1725, 1726, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 2073], "v": [11, 30, 44, 52, 59, 64, 489, 490, 546, 902, 913, 915, 916, 917, 943, 960, 1167, 1177, 1179, 1189, 1271, 1288, 1310, 1314, 1338, 1342, 1347, 1536, 1579, 1580, 1590, 1627, 1673, 1736, 1767, 1772, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1820, 1853, 1912, 1916, 1931, 1932, 1980, 2017, 2018, 2019, 2020, 2033, 2047, 2058, 2067, 2074, 2086, 2091, 2101], "forloop": 11, "numerical_accuraci": 11, "impact": [11, 24, 28, 83, 1066, 1874, 2030, 2033, 2047, 2076, 2090, 2108, 2113, 2117], "pointwis": [11, 35, 976, 1172, 1173, 1352, 1353, 1495, 2038, 2048, 2107, 2110, 2111], "lbfg": [11, 2073], "yet": [11, 29, 33, 37, 52, 53, 55, 60, 63, 64, 73, 82, 84, 85, 488, 1011, 1084, 1200, 1277, 1279, 1292, 1380, 1720, 1742, 1746, 1748, 1787, 1788, 2016, 2019, 2020, 2026, 2032, 2039, 2040, 2050, 2071, 2072, 2076, 2081, 2083, 2086, 2087, 2089, 2102, 2105, 2107, 2108, 2113, 2115, 2117], "fulli": [11, 14, 23, 28, 30, 32, 33, 34, 52, 59, 64, 683, 1073, 1187, 1274, 1526, 1527, 1528, 1530, 2020, 2026, 2032, 2053, 2074, 2076, 2104, 2105, 2112], "quantiz": [11, 27, 64, 221, 328, 340, 474, 475, 476, 477, 478, 480, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 862, 863, 864, 865, 866, 867, 868, 936, 1095, 1124, 1125, 1832, 1833, 1834, 1835, 1836, 1968, 2016, 2072, 2089, 2092, 2093, 2096, 2097], "pred": [12, 66, 69, 74, 75, 990, 1495, 1720, 2062, 2073, 2081, 2112], "union": [12, 14, 23, 30, 33, 34, 37, 41, 45, 48, 52, 53, 55, 64, 976, 990, 1185, 1187, 1260, 1286, 1346, 1431, 1432, 1433, 1435, 1436, 1437, 1439, 1440, 1441, 1477, 1478, 1497, 1498, 1499, 1523, 1524, 1525, 1530, 1574, 1576, 1578, 1581, 1594, 1740, 1781, 1862, 1971, 2018, 2019, 2020, 2024, 2066, 2069, 2071, 2074, 2088, 2091, 2093, 2097], "true_fn": [12, 53, 66, 69, 74, 75, 990], "false_fn": [12, 53, 66, 69, 74, 75, 990], "operand": [12, 66, 69, 74, 75, 952, 990, 1110, 2020, 2021, 2053, 2086, 2089], "Its": [12, 28, 53, 64, 998, 1023, 1274, 1322, 1340, 1341, 1366, 1530, 1775, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1977, 2020, 2052], "uniqu": [12, 28, 37, 44, 47, 48, 50, 515, 519, 1265, 1310, 1311, 1315, 1321, 1322, 1324, 1333, 1335, 1337, 1338, 1375, 1382, 1908, 1931, 1965, 2015, 2017, 2026, 2031, 2053, 2074, 2075, 2081, 2082, 2083, 2086, 2091, 2102, 2119], "predic": [12, 66, 71, 74, 75, 1189], "unlock": [12, 2027], "flexibilti": 12, "architectur": [12, 34, 64, 1036, 1126, 1127, 1129, 1131, 1132, 1133, 1134, 1135, 1136, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1147, 1465, 1574, 1619, 1875, 2050, 2064, 2076, 2086, 2101], "prototyp": [12, 18, 19, 28, 52, 683, 912, 914, 918, 923, 924, 990, 1284, 1578, 1590, 1591, 1787, 1788, 2016, 2027, 2033, 2039, 2040, 2061, 2066, 2079, 2081, 2086, 2089, 2095, 2096, 2097, 2099], "classif": [12, 990, 1443, 1449, 1465, 1533, 1535, 1537, 1563, 1620, 2016, 2045, 2077], "co": [12, 52, 53, 61, 66, 70, 71, 74, 75, 76, 77, 79, 203, 638, 639, 686, 954, 976, 990, 1052, 1169, 1172, 1173, 1178, 1232, 1233, 1326, 1463, 1464, 1467, 1804, 1805, 1812, 1824, 1885, 1889, 1890, 1891, 1892, 1894, 1913, 1914, 1915, 1917, 1918, 2018, 2024, 2038, 2072, 2073, 2086, 2091, 2093, 2103, 2110, 2112], "sin": [12, 14, 52, 53, 60, 61, 66, 70, 71, 74, 75, 76, 77, 534, 672, 673, 885, 976, 990, 1052, 1169, 1171, 1172, 1173, 1175, 1178, 1233, 1326, 1376, 1824, 1886, 1892, 2018, 2024, 2038, 2047, 2072, 2086, 2087, 2091, 2103, 2108, 2110, 2112, 2115], "dynamicshapecondpred": 12, "dyn_shape_mod": 12, "eagerli": [12, 33, 1041, 1047, 1997, 2000, 2050, 2104, 2108], "vari": [12, 52, 1280, 1443, 1562, 1761, 1887, 2033, 2050, 2063, 2064, 2073, 2076, 2077, 2086, 2099, 2102, 2104, 2105, 2107, 2108, 2117, 2119], "inp2": 12, "assert": [12, 23, 24, 30, 33, 35, 57, 59, 60, 61, 64, 66, 72, 75, 76, 77, 627, 926, 928, 929, 1169, 1171, 1172, 1173, 1174, 1177, 1178, 1179, 1188, 1189, 1272, 1277, 1278, 1284, 1688, 1781, 1980, 2019, 2021, 2024, 2053, 2054, 2061, 2066, 2074, 2076, 2093, 2104, 2108, 2116, 2117], "export": [12, 15, 18, 28, 33, 36, 51, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 83, 683, 844, 935, 978, 983, 990, 1011, 1183, 1193, 1277, 1279, 1280, 1286, 1292, 1762, 1763, 1782, 1783, 2016, 2017, 2019, 2020, 2024, 2053, 2057, 2072, 2075, 2081, 2098, 2104, 2109, 2115, 2116], "deploy": [12, 37, 47, 52, 2016, 2030, 2099, 2109], "dim_batch": 12, "dim": [12, 28, 34, 35, 52, 60, 61, 64, 66, 68, 74, 75, 114, 116, 117, 118, 120, 136, 137, 138, 186, 206, 209, 212, 213, 214, 215, 216, 217, 231, 235, 262, 266, 283, 314, 315, 316, 317, 318, 319, 323, 324, 356, 382, 394, 409, 411, 412, 413, 416, 431, 432, 433, 434, 438, 439, 455, 464, 472, 481, 493, 494, 496, 507, 508, 514, 515, 516, 517, 518, 519, 520, 521, 539, 540, 543, 544, 546, 549, 554, 555, 557, 562, 567, 575, 580, 581, 585, 586, 587, 589, 590, 592, 607, 608, 611, 612, 613, 614, 617, 619, 696, 698, 699, 700, 702, 878, 879, 880, 914, 915, 917, 963, 970, 988, 990, 997, 1008, 1023, 1025, 1089, 1090, 1091, 1092, 1093, 1102, 1108, 1126, 1127, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1147, 1149, 1150, 1169, 1179, 1183, 1215, 1228, 1238, 1246, 1247, 1248, 1249, 1251, 1296, 1306, 1307, 1327, 1331, 1341, 1343, 1344, 1354, 1362, 1372, 1374, 1375, 1377, 1380, 1382, 1398, 1421, 1422, 1423, 1424, 1425, 1426, 1434, 1464, 1465, 1466, 1469, 1473, 1475, 1480, 1495, 1501, 1520, 1536, 1537, 1538, 1564, 1566, 1578, 1580, 1581, 1618, 1619, 1635, 1638, 1647, 1655, 1661, 1662, 1663, 1672, 1673, 1675, 1677, 1681, 1688, 1694, 1695, 1703, 1720, 1735, 1736, 1742, 1746, 1748, 1755, 1756, 1769, 1772, 1775, 1821, 1828, 1831, 1851, 1852, 1857, 1858, 1863, 1864, 1865, 1868, 1869, 1899, 1902, 1903, 1907, 1910, 1912, 1919, 1922, 1924, 1925, 1926, 1927, 1930, 1943, 1947, 1948, 1949, 1950, 1953, 1954, 1962, 1963, 1964, 1965, 1967, 1975, 1976, 1980, 1981, 2016, 2017, 2018, 2024, 2039, 2040, 2054, 2055, 2066, 2069, 2071, 2072, 2086, 2087, 2089, 2096, 2099, 2104, 2112], "batch": [12, 24, 28, 33, 35, 48, 51, 52, 55, 56, 57, 60, 61, 64, 66, 74, 75, 585, 586, 587, 589, 590, 689, 705, 706, 707, 708, 709, 710, 738, 763, 782, 788, 918, 923, 924, 944, 956, 957, 964, 967, 968, 969, 976, 1008, 1098, 1100, 1110, 1172, 1173, 1179, 1271, 1304, 1305, 1306, 1307, 1308, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1342, 1343, 1344, 1347, 1355, 1364, 1365, 1369, 1442, 1443, 1444, 1445, 1446, 1449, 1457, 1458, 1463, 1465, 1466, 1468, 1469, 1470, 1472, 1473, 1474, 1476, 1481, 1482, 1483, 1484, 1489, 1490, 1492, 1493, 1494, 1495, 1496, 1500, 1501, 1502, 1503, 1504, 1505, 1512, 1513, 1514, 1521, 1522, 1533, 1534, 1535, 1536, 1537, 1539, 1542, 1543, 1544, 1545, 1546, 1548, 1562, 1563, 1570, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1582, 1601, 1606, 1608, 1609, 1619, 1620, 1622, 1623, 1624, 1627, 1628, 1629, 1630, 1633, 1646, 1647, 1648, 1672, 1680, 1688, 1706, 1707, 1710, 1719, 1720, 1734, 1761, 1762, 1764, 1765, 1767, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1805, 1806, 1812, 1818, 1820, 1830, 1834, 1913, 1914, 1915, 1917, 1918, 1922, 1927, 1931, 1932, 1952, 1955, 1956, 1958, 1977, 1980, 2016, 2038, 2039, 2040, 2046, 2050, 2054, 2055, 2061, 2063, 2076, 2081, 2086, 2091, 2092, 2099, 2102, 2104, 2105, 2107, 2108, 2111, 2115, 2117], "min": [12, 23, 28, 40, 47, 52, 64, 118, 187, 188, 189, 190, 302, 698, 699, 700, 759, 761, 773, 774, 783, 805, 822, 823, 824, 825, 828, 879, 971, 972, 1052, 1090, 1124, 1125, 1199, 1235, 1306, 1320, 1321, 1327, 1331, 1333, 1338, 1344, 1364, 1416, 1448, 1488, 1516, 1518, 1538, 1551, 1558, 1610, 1647, 1651, 1681, 1683, 1689, 1707, 1799, 1804, 1805, 1814, 1818, 1820, 1830, 1931, 1932, 1939, 1956, 1957, 1958, 1959, 2018, 2033, 2038, 2071, 2072, 2076, 2079, 2081, 2099, 2104, 2108, 2112, 2122], "ep": [12, 52, 715, 716, 717, 718, 719, 720, 726, 727, 739, 740, 752, 754, 755, 756, 757, 798, 822, 823, 824, 825, 828, 829, 923, 924, 1284, 1360, 1430, 1444, 1445, 1446, 1464, 1483, 1484, 1492, 1493, 1494, 1502, 1503, 1504, 1505, 1512, 1513, 1514, 1539, 1544, 1545, 1570, 1574, 1576, 1578, 1579, 1606, 1618, 1633, 1637, 1638, 1646, 1650, 1673, 1676, 1680, 1685, 1704, 1719, 1735, 1769, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1801, 1814, 1834, 2018, 2053, 2058, 2087, 2112, 2122], "dynamic_shap": [12, 52, 66, 68, 74, 75, 1182, 2069, 2099, 2114], "graphmodul": [12, 33, 52, 53, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 83, 863, 864, 865, 866, 2076, 2097, 2103, 2106, 2107, 2116, 2117], "arg0_1": [12, 52], "f32": [12, 52], "s0": [12, 52, 53, 66, 74, 75, 488, 1189, 2104, 2105, 2117], "sym_siz": [12, 53, 66, 74, 75, 2072, 2112], "sym": [12, 66, 74, 75, 76, 77, 1189, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894], "gt": [12, 66, 74, 75, 298, 1229, 2018, 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2081, 2082], "localhost": [24, 28, 47, 48, 2052, 2081, 2082], "master_port": [24, 28, 37, 47, 48, 51, 2052, 2081, 2082], "12355": 24, "init_process_group": [24, 28, 29, 32, 37, 48, 51, 1720, 2050, 2052, 2081], "cleanup": [24, 1189, 2088], "destroy_process_group": [24, 28], "run_demo": 24, "demo_fn": 24, "nproc": [24, 28, 45, 46, 48, 2037, 2052, 2082], "demo_seri": 24, "gettempdir": 24, "device_id": [24, 28, 29, 32, 48, 55, 1346, 1466, 1570, 1703, 1720, 2052], "powersgd_st": 24, "lr": [24, 29, 30, 32, 55, 490, 1710, 1720, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 2050, 2052, 2057, 2061, 2063, 2073, 2082, 2091], "001": [24, 923, 924, 1284, 1783, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1813, 2052, 2057, 2071], "state_dict": [24, 30, 32, 52, 53, 55, 62, 839, 840, 1274, 1530, 1710, 1754, 1772, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1793, 1797, 1798, 1799, 1800, 1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 2015, 2031, 2032, 2052, 2057, 2061, 2063, 2066, 2069, 2071, 2076, 2096], "comm_hook": 24, "comm_hook_st": 24, "barrier": [24, 37, 47, 2072], "map_loc": [24, 1278, 1282, 1346, 1720, 2015, 2028, 2031, 2074], "new_ddp_model": 24, "load_state_dict": [24, 30, 32, 55, 62, 417, 1274, 1346, 1530, 1710, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1797, 1798, 1799, 1800, 1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 2015, 2016, 2061, 2066, 2076], "n_gpu": 24, "device_count": [24, 1971, 2016], "got": [24, 28, 895, 909, 910, 932, 2053, 2093], "thank": [24, 35, 2053], "author": [24, 47, 48, 55, 1179, 1797, 1837, 1980, 2046, 2099, 2106, 2108, 2110, 2113, 2114, 2115, 2117], "thij": 24, "par": 24, "torch_show_cpp_stacktrac": [25, 28], "torch_cpp_log_level": [25, 28], "c10": [25, 47, 2060, 2099, 2104], "glog": 25, "logger": [25, 28, 37, 2096, 2097], "info": [25, 28, 33, 41, 45, 47, 55, 683, 896, 909, 910, 1011, 1012, 1014, 1189, 1305, 1316, 1318, 1319, 1323, 1336, 1364, 1390, 1391, 1781, 2016, 2018, 2024, 2026, 2052, 2053, 2054, 2071, 2074, 2104, 2106, 2107, 2117, 2121], "fatal": [25, 52, 2037, 2063], "torch_log": [25, 33, 81, 83, 683, 976, 2026, 2052, 2104, 2105, 2106, 2108, 2117], "_log": [25, 33, 2016, 2020, 2117, 2120], "home": [26, 2050], "fill_uninitialized_memori": [27, 501, 1111, 1112, 1113, 1968, 2016, 2065], "fill": [27, 28, 33, 156, 175, 260, 261, 262, 288, 319, 323, 379, 402, 447, 448, 449, 451, 456, 483, 515, 610, 626, 947, 1098, 1111, 1112, 1113, 1165, 1166, 1305, 1316, 1318, 1473, 1574, 1628, 1675, 1779, 1780, 1839, 1840, 1841, 1842, 1843, 1844, 1931, 1968, 2013, 2014, 2018, 2028, 2039, 2040, 2045, 2050, 2053, 2066, 2072, 2086, 2093, 2107, 2112], "detriment": [27, 2065], "resize_": [27, 502, 1168, 1296, 1968, 2017, 2018, 2019, 2038, 2065, 2078, 2088, 2112], "empty_strid": [27, 2018, 2022, 2072, 2104, 2112], "empty_permut": [27, 2018, 2072, 2112], "empty_lik": [27, 30, 2018, 2022, 2024, 2028, 2038, 2040, 2072, 2086], "brief": [28, 33, 1720, 2037, 2081], "introduct": [28, 35, 1044, 1720, 2016, 2017, 2021, 2038, 2048, 2061, 2071, 2081, 2086, 2091], "mpi": [28, 1720], "gloo": [28, 48, 1720, 2052, 2059, 2081], "recv": [28, 33, 1720, 2072, 2082], "broadcast": [28, 30, 32, 34, 35, 55, 60, 99, 198, 400, 402, 403, 404, 515, 517, 519, 568, 688, 689, 690, 691, 692, 693, 694, 700, 738, 888, 944, 949, 952, 956, 957, 958, 959, 993, 1022, 1052, 1104, 1105, 1110, 1115, 1155, 1156, 1157, 1158, 1215, 1217, 1231, 1241, 1299, 1300, 1307, 1320, 1324, 1329, 1330, 1332, 1335, 1343, 1363, 1368, 1369, 1379, 1415, 1418, 1427, 1430, 1443, 1464, 1483, 1536, 1609, 1618, 1681, 1688, 1720, 1783, 1819, 1827, 1850, 1852, 1928, 1932, 1948, 1953, 1983, 2016, 2020, 2038, 2039, 2040, 2052, 2071, 2072, 2087, 2108, 2112], "all_reduc": [28, 50, 1720, 2072, 2102], "all_gath": 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2086, 2091], "aw": [28, 39, 998], "gcp": [28, 2114], "primit": [28, 32, 33, 47, 1346, 2017, 2019, 2021, 2049, 2062, 2071, 2081, 2112], "kind": [28, 41, 52, 64, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 683, 1185, 1294, 1721, 1782, 1829, 1893, 2015, 2024, 2053, 2063, 2065, 2069, 2071, 2074, 2076, 2087, 2089], "connect": [28, 37, 47, 1457, 1458, 1459, 1460, 1461, 1462, 1506, 1507, 1508, 1509, 1510, 1511, 1559, 2037, 2081, 2115], "advantag": [28, 47, 48, 1443, 1490, 2052, 2055, 2068, 2069, 2081, 2086, 2102], "redund": [28, 55, 1126, 1127, 1129, 1131, 1145, 1147, 1927], "elimin": [28, 52, 64, 612, 1182, 1964, 1965, 2065, 2110, 2116], "thrash": 28, "recurr": [28, 763, 764, 1290, 1449, 1466, 1481, 1482, 1500, 1546, 1738, 1764, 1798, 2016, 2050], "device_mesh": [28, 34, 55, 1720], "init_device_mesh": [28, 34], "use_distribut": 28, "group_nam": [28, 44], "pg_option": 28, "url": [28, 47, 935, 2015, 2031, 2081], "encod": [28, 37, 44, 47, 64, 1322, 1346, 1390, 1391, 1442, 1443, 1574, 1575, 1576, 1577, 1578, 1720, 1874, 1913, 1914, 1915, 1917, 1918, 2017, 2020, 2021, 2053, 2066, 2074, 2082, 2086], "ucc": 28, "lowercas": 28, "deadlock": [28, 1720], "job": [28, 37, 40, 41, 43, 44, 46, 47, 48, 50, 1414, 1720, 1806, 1812, 2050, 2060, 2075, 2091, 2105, 2119, 2121], "exchang": [28, 47, 1012, 1098, 2050, 2068], "timedelta": [28, 47, 2033], "abort": [28, 2050, 2121], "crash": [28, 40, 47, 1311, 2037, 2047, 2081, 2083, 2091, 2104], "corrupt": [28, 47, 1466, 2050, 2063], "torch_nccl_blocking_wait": [28, 2121], "processgroupopt": 28, "processgroupnccl": [28, 2016, 2052, 2120], "is_high_priority_stream": 28, "ncclcomminit": 28, "lazi": [28, 991, 1287, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1710, 1999, 2016, 2104], "ncclcommsplit": 28, "unnecessari": [28, 32, 1727, 1728, 1768, 2020, 2047, 2050, 2053, 2066, 2074, 2090], "backend_nam": [28, 1971], "custom_backend": 28, "mesh_shap": 28, "mesh_dim_nam": 28, "dimension": [28, 35, 53, 515, 517, 884, 890, 891, 892, 955, 962, 974, 1098, 1100, 1101, 1110, 1126, 1127, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1138, 1139, 1140, 1141, 1144, 1145, 1147, 1149, 1151, 1152, 1164, 1228, 1237, 1238, 1239, 1307, 1312, 1313, 1314, 1315, 1340, 1345, 1361, 1369, 1376, 1434, 1451, 1452, 1453, 1454, 1455, 1456, 1465, 1466, 1472, 1473, 1502, 1520, 1537, 1545, 1552, 1553, 1554, 1555, 1556, 1557, 1564, 1566, 1570, 1586, 1587, 1588, 1619, 1672, 1675, 1708, 1709, 1719, 1734, 1774, 1837, 1913, 1914, 1915, 1916, 1917, 1918, 1927, 1943, 1946, 1947, 1953, 2020, 2040, 2045, 2048, 2058, 2064, 2086, 2088, 2089, 2092, 2095, 2104], "layout": [28, 34, 53, 64, 152, 193, 210, 235, 344, 345, 437, 447, 448, 449, 450, 451, 460, 546, 583, 584, 585, 586, 587, 589, 590, 619, 692, 869, 897, 902, 945, 954, 1024, 1111, 1112, 1113, 1123, 1128, 1146, 1162, 1165, 1166, 1187, 1232, 1233, 1294, 1345, 1361, 1369, 1379, 1426, 1653, 1779, 1780, 1801, 1839, 1840, 1841, 1842, 1843, 1844, 1845, 1846, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1908, 1909, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1952, 1957, 1959, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2022, 2040, 2050, 2072, 2074, 2086, 2091, 2092, 2093, 2112], "spmd": [28, 30], "nd": [28, 1330, 2056, 2064], "inconsist": [28, 55, 869, 1846, 2053], "scene": [28, 2066, 2091], "mesh": [28, 34, 2091], "mesh_1d": 28, "mesh_2d": 28, "dp": 28, "is_initi": [28, 2016], "is_mpi_avail": 28, "is_nccl_avail": 28, "is_gloo_avail": 28, "is_torchelastic_launch": 28, "elast": [28, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 49, 50, 51, 2016], "torchelast": [28, 31, 37, 39, 40, 41, 44, 46, 47, 48, 50, 51], "torchelastic_run_id": [28, 48], "proxi": [28, 30, 978, 2076, 2081, 2105], "rendezv": [28, 31, 37, 41, 44, 46, 51, 2052, 2081], "null": [28, 39, 41, 44, 66, 70], "discoveri": [28, 47, 2050, 2074], "reachabl": 28, "multicast": 28, "20": [28, 32, 35, 66, 323, 688, 723, 731, 732, 737, 741, 742, 743, 744, 745, 746, 749, 759, 763, 764, 765, 766, 767, 768, 775, 1092, 1228, 1272, 1275, 1286, 1297, 1331, 1415, 1438, 1440, 1441, 1443, 1444, 1445, 1446, 1447, 1449, 1456, 1457, 1458, 1459, 1461, 1462, 1467, 1468, 1469, 1470, 1474, 1477, 1478, 1481, 1482, 1484, 1491, 1492, 1493, 1494, 1497, 1498, 1499, 1500, 1501, 1502, 1517, 1523, 1524, 1525, 1527, 1528, 1530, 1546, 1548, 1559, 1567, 1570, 1573, 1574, 1575, 1576, 1588, 1611, 1613, 1614, 1616, 1620, 1631, 1632, 1638, 1696, 1734, 1735, 1736, 1760, 1769, 1772, 1790, 1805, 1833, 1943, 2017, 2018, 2028, 2040, 2052, 2053, 2064, 2069, 2072, 2073, 2081, 2085, 2086, 2105, 2106, 2107], "23456": 28, "clean": [28, 33, 37, 52, 64, 986, 1048, 2015, 2037, 2074], "fcntl": 28, "nf": 28, "init": [28, 34, 37, 40, 41, 55, 1274, 1530, 1538, 1558, 1768, 2016, 2022, 2047, 2053, 2057, 2060, 2061, 2104], "brand": [28, 30, 2053], "succe": [28, 47, 52, 60, 2050, 2053, 2067, 2117, 2119], "unexpect": [28, 30, 36, 64, 1008, 1161, 1164, 1167, 1274, 1530, 1770, 1783, 1922, 2017, 2047, 2053, 2064, 2105, 2107, 2108], "unsuccess": 28, "mnt": 28, "sharedfil": 28, "port": [28, 37, 46, 47, 48, 2028, 2059], "backend_str": 28, "uppercas": 28, "classmethod": [28, 30, 47, 66, 68, 735, 741, 742, 743, 748, 749, 759, 767, 795, 796, 797, 818, 819, 820, 827, 858, 932, 1011, 1472, 1473, 1570, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1781, 2020, 2021, 2053, 2076, 2081, 2088, 2118], "register_backend": [28, 2081, 2103], "extended_api": 28, "instanti": [28, 32, 46, 47, 48, 55, 64, 845, 1473, 1628, 1737, 1761, 1768, 2015, 2017, 2019, 2020, 2050, 2053, 2061, 2066, 2069, 2088], "3rd": [28, 35, 47, 619, 2048], "processgroup": [28, 30, 32, 33, 55, 1720], "four": [28, 1320, 1458, 2053, 2058, 2081, 2083], "c10d": [28, 37, 46, 48, 51, 683, 1720, 2052, 2072], "distributedbackendopt": 28, "get_backend": [28, 47], "get_rank": [28, 55, 1570], "consecut": [28, 55, 612, 1763, 1802, 1953, 1964, 1965, 2039, 2071], "get_world_s": 28, "pattern": [28, 30, 33, 795, 796, 797, 799, 858, 865, 1052, 1202, 1466, 1590, 1764, 1909, 2017, 2020, 2047, 2050, 2053, 2055, 2059, 2066, 2077, 2078, 2086, 2102, 2104, 2105, 2107, 2116, 2119], "launcher": [28, 33, 48], "pg": [28, 1720], "destructor": [28, 2037, 2083], "ncclcommabort": 28, "gc": [28, 488, 2083], "fault": [28, 31, 37, 46, 47, 1164], "toler": [28, 31, 37, 46, 47, 64, 697, 923, 924, 1263, 1290, 1291, 1329, 1332, 1347, 1783, 1790, 2017, 2093], "_after_": [28, 2052], "unsupport": [28, 37, 52, 60, 66, 80, 83, 84, 86, 89, 2017, 2021, 2039, 2066, 2069, 2073, 2081, 2086, 2108, 2113], "untest": [28, 2039], "filestor": [28, 47], "hashstor": 28, "client": [28, 32, 47, 1066, 1188, 1193, 2074, 2108], "host_nam": 28, "hostnam": [28, 37, 41, 47, 2075], "listen": 28, "is_mast": 28, "300": [28, 37, 1352, 1443, 1765, 1767, 2073], "wait_for_work": 28, "multi_ten": 28, "underli": [28, 30, 32, 35, 37, 52, 55, 60, 64, 99, 313, 328, 379, 402, 404, 475, 476, 477, 478, 485, 501, 522, 526, 559, 560, 561, 615, 751, 760, 882, 1011, 1162, 1189, 1205, 1206, 1207, 1245, 1249, 1274, 1346, 1425, 1680, 1848, 1952, 1967, 1985, 2017, 2020, 2040, 2050, 2055, 2059, 2081, 2088, 2090, 2098, 2107], "tcpserver": 28, "master_listen_fd": 28, "use_libuv": 28, "libuv": 28, "datetim": [28, 2033, 2108], "server_stor": 28, "127": [28, 797, 2039, 2076, 2091], "1234": [28, 47, 1251, 1966], "client_stor": 28, "first_kei": 28, "first_valu": 28, "hashmap": 28, "file_nam": [28, 2015, 2031, 2074], "store1": 28, "store2": 28, "prefixstor": 28, "old": [28, 36, 52, 64, 488, 858, 1161, 1197, 1211, 1469, 1772, 1780, 1814, 1862, 2014, 2016, 2017, 2047, 2050, 2053, 2067, 2076, 2091, 2107], "throw": [28, 29, 63, 64, 192, 325, 330, 547, 616, 1259, 1274, 1315, 1364, 1530, 1720, 1722, 1723, 1764, 1775, 1826, 1968, 2040, 2047, 2065, 2081, 2092, 2105, 2108, 2117, 2121], "whose": [28, 35, 55, 64, 546, 863, 902, 966, 993, 1098, 1110, 1115, 1164, 1217, 1228, 1231, 1237, 1274, 1280, 1291, 1299, 1345, 1361, 1363, 1427, 1530, 1720, 1776, 1824, 1881, 1949, 2020, 2047, 2053, 2056, 2058, 2074, 2086, 2091, 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torch.func.grad with torch.compile": [[2108, "compiling-torch-func-grad-with-torch-compile"]], "Compiling torch.vmap with torch.compile": [[2108, "compiling-torch-vmap-with-torch-compile"]], "Compiling functions besides the ones which are supported (escape hatch)": [[2108, "compiling-functions-besides-the-ones-which-are-supported-escape-hatch"]], "Does NumPy work with torch.compile?": [[2108, "does-numpy-work-with-torch-compile"]], "Which NumPy features does torch.compile support?": [[2108, "which-numpy-features-does-torch-compile-support"]], "Can I compile NumPy code using torch.compile?": [[2108, "can-i-compile-numpy-code-using-torch-compile"]], "Can I execute NumPy code on CUDA and compute gradients via torch.compile?": [[2108, "can-i-execute-numpy-code-on-cuda-and-compute-gradients-via-torch-compile"]], "How do I debug NumPy code under torch.compile?": [[2108, "how-do-i-debug-numpy-code-under-torch-compile"]], "I torch.compile some NumPy code and I did not see any speed-up.": [[2108, "i-torch-compile-some-numpy-code-and-i-did-not-see-any-speed-up"]], "Which API to use for fine grain tracing?": [[2108, "which-api-to-use-for-fine-grain-tracing"]], "How do I graph break on a function?": [[2108, "how-do-i-graph-break-on-a-function"]], "What\u2019s the difference between torch._dynamo.disable and torch._dynamo.disallow_in_graph": [[2108, "what-s-the-difference-between-torch-dynamo-disable-and-torch-dynamo-disallow-in-graph"]], "What\u2019s the difference between torch._dynamo.disable and torch._dynamo_skip": [[2108, "what-s-the-difference-between-torch-dynamo-disable-and-torch-dynamo-skip"]], "PYTORCH ProcessGroupNCCL Environment Variables": [[2121, "pytorch-processgroupnccl-environment-variables"]], "Type Info": [[2122, "type-info"]], "torch.finfo": [[2122, "torch-finfo"]], "torch.iinfo": [[2122, "torch-iinfo"]], "torch.compiler API reference": [[2100, "torch-compiler-api-reference"]], "Profiling to understand torch.compile performance": [[2115, "profiling-to-understand-torch-compile-performance"]], "What to use torch.profiler for:": [[2115, "what-to-use-torch-profiler-for"]], "Basics of using torch.profiler and viewing traces": [[2115, "basics-of-using-torch-profiler-and-viewing-traces"]], "Working around CUDA Graph profiling issues": [[2115, "working-around-cuda-graph-profiling-issues"]], "Understanding compilation time": [[2115, "understanding-compilation-time"]], "Finding graph breaks: \u201cTorch-Compiled Region\u201d and \u201cCompiledFunction\u201d": [[2115, "finding-graph-breaks-torch-compiled-region-and-compiledfunction"]], "Operator Kernels": [[2115, "operator-kernels"]], "Launch overhead": [[2115, "launch-overhead"]], "Threading Environment Variables": [[2094, "threading-environment-variables"]], "Fake tensor": [[2107, "fake-tensor"]], "Related work": [[2107, "related-work"]], "Overall architecture": [[2107, "overall-architecture"], [2104, "overall-architecture"]], "API: the important bits": [[2107, "api-the-important-bits"]], "Details": [[2107, "details"]], "About the tensor subclass": [[2107, "about-the-tensor-subclass"]], "How is each individual operator implemented?": [[2107, "how-is-each-individual-operator-implemented"]], "How does the converter work?": [[2107, "how-does-the-converter-work"]], "Performance characteristics": [[2107, "performance-characteristics"]], "Fake tensor of fake tensor?": [[2107, "fake-tensor-of-fake-tensor"]], "Interaction with dynamic shapes": [[2107, "interaction-with-dynamic-shapes"]], "Other resources": [[2107, "other-resources"]], "TorchDynamo APIs for fine-grained tracing": [[2109, "torchdynamo-apis-for-fine-grained-tracing"]], "TorchDynamo APIs to control fine-grained tracing": [[2109, "id1"]], "torch.compiler.disable": [[2109, "torch-compiler-disable"], [982, "torch-compiler-disable"]], "torch._dynamo.disallow_in_graph": [[2109, "torch-dynamo-disallow-in-graph"]], "torch.compiler.allow_in_graph": [[2109, "torch-compiler-allow-in-graph"], [978, "torch-compiler-allow-in-graph"]], "Limitations": [[2109, "limitations"], [2102, "limitations"], [2071, "limitations"]], "CUDAGraph Trees": [[2102, "cudagraph-trees"]], "Background": [[2102, "background"], [2083, "background"], [2082, "background"]], "CUDAGraph": [[2102, "cudagraph"], [1009, "cudagraph"]], "PyTorch CUDAGraph Integration": [[2102, "pytorch-cudagraph-integration"]], "Make Graphed Callables": [[2102, "make-graphed-callables"]], "TorchDynamo Previous CUDA Graphs Integration": [[2102, "torchdynamo-previous-cuda-graphs-integration"]], "CUDAGraph Trees Integration": [[2102, "cudagraph-trees-integration"]], "Input Mutation Support": [[2102, "input-mutation-support"]], "Dynamic Shape Support": [[2102, "dynamic-shape-support"]], "NCCL Support": [[2102, "nccl-support"]], "Reasons for Skipping CUDAGraph": [[2102, "reasons-for-skipping-cudagraph"]], "PyTorch 2.0 Performance Dashboard": [[2114, "pytorch-2-0-performance-dashboard"]], "How to read the dashboard?": [[2114, "how-to-read-the-dashboard"]], "What is measured on the dashboard?": [[2114, "what-is-measured-on-the-dashboard"]], "Can I check if my PR affects TorchInductor\u2019s performance on the dashboard before merging?": [[2114, "can-i-check-if-my-pr-affects-torchinductor-s-performance-on-the-dashboard-before-merging"]], "How can I run any performance test locally?": [[2114, "how-can-i-run-any-performance-test-locally"]], "Dynamo Deep-Dive": [[2105, "dynamo-deep-dive"]], "A Gentle Introduction to Dynamo": [[2105, "a-gentle-introduction-to-dynamo"]], "PEP 523: Adding a frame evaluation API to CPython": [[2105, "pep-523-adding-a-frame-evaluation-api-to-cpython"]], "Implementing CPython in Python": [[2105, "implementing-cpython-in-python"]], "Generating the Output Graph": [[2105, "generating-the-output-graph"]], "Making Dynamo Sound: Guards": [[2105, "making-dynamo-sound-guards"]], "Symbolic Shapes": [[2105, "symbolic-shapes"]], "Static by default": [[2105, "static-by-default"]], "0, 1 are always specialized": [[2105, "are-always-specialized"]], "Duck shaping": [[2105, "duck-shaping"]], "Guards on symbolic ints": [[2105, "guards-on-symbolic-ints"]], "Making Dynamo Complete: Graph Breaks": [[2105, "making-dynamo-complete-graph-breaks"]], "Conclusion": [[2105, "conclusion"]], "Footnotes": [[2105, "footnotes"]], "Custom Backends": [[2103, "custom-backends"]], "Registering Custom Backends": [[2103, "registering-custom-backends"]], "Custom Backends after AOTAutograd": [[2103, "custom-backends-after-aotautograd"]], "Examples": [[2103, "examples"], [2057, "examples"], [12, "examples"], [42, "examples"]], "Debugging Backend": [[2103, "debugging-backend"]], "Speedy Backend": [[2103, "speedy-backend"]], "Composable Backends": [[2103, "composable-backends"]], "Dynamo Overview": [[2106, "dynamo-overview"]], "Dynamo Internals": [[2106, "dynamo-internals"]], "What is a guard?": [[2106, "what-is-a-guard"]], "What is Dynamo doing?": [[2106, "what-is-dynamo-doing"]], "How to inspect artifacts generated by Dynamo?": [[2106, "how-to-inspect-artifacts-generated-by-dynamo"]], "Getting Started": [[2110, "getting-started"], [7, "getting-started"]], "Using a pretrained model": [[2110, "using-a-pretrained-model"]], "Next Steps": [[2110, "next-steps"]], "torch": [[2095, "module-torch"]], "Tensors": [[2095, "tensors"]], "Creation Ops": [[2095, "creation-ops"]], "Indexing, Slicing, Joining, Mutating Ops": [[2095, "indexing-slicing-joining-mutating-ops"]], "Generators": [[2095, "generators"]], "Random sampling": [[2095, "random-sampling"]], "In-place random sampling": [[2095, "in-place-random-sampling"]], "Quasi-random sampling": [[2095, "quasi-random-sampling"]], "Parallelism": [[2095, "parallelism"]], "Locally disabling gradient computation": [[2095, "locally-disabling-gradient-computation"], [2047, "locally-disabling-gradient-computation"], [1, "locally-disabling-gradient-computation"]], "Math operations": [[2095, "math-operations"]], "Pointwise Ops": [[2095, "pointwise-ops"]], "Reduction Ops": [[2095, "reduction-ops"]], "Comparison Ops": [[2095, "comparison-ops"]], "Spectral Ops": [[2095, "spectral-ops"]], "Other Operations": [[2095, "other-operations"]], "BLAS and LAPACK Operations": [[2095, "blas-and-lapack-operations"]], "Foreach Operations": [[2095, "foreach-operations"]], "Utilities": [[2095, "utilities"], [2041, "module-torch.nn.utils"]], "Symbolic Numbers": [[2095, "symbolic-numbers"]], "Export Path": [[2095, "export-path"]], "Control Flow": [[2095, "control-flow"]], "Optimizations": [[2095, "optimizations"]], "Operator Tags": [[2095, "operator-tags"]], "Writing Graph Transformations on ATen IR": [[2116, "writing-graph-transformations-on-aten-ir"]], "Passes": [[2116, "passes"]], "One-to-One Pass": [[2116, "one-to-one-pass"]], "One-to-X Pass": [[2116, "one-to-x-pass"]], "One-to-None Pass": [[2116, "one-to-none-pass"]], "Utilizing Local Information": [[2116, "utilizing-local-information"]], "Subgraph Rewriter": [[2116, "subgraph-rewriter"]], "Pass Manager": [[2116, "pass-manager"]], "Partitioner": [[2116, "partitioner"]], "Subgraph Matcher": [[2116, "subgraph-matcher"]], "Capability Based Partitioner": [[2116, "capability-based-partitioner"]], "torch.utils.tensorboard": [[2091, "module-torch.utils.tensorboard"]], "torch.compiler": [[2098, "torch-compiler"]], "Getting Started for PyTorch Users": [[2098, null]], "HowTo for PyTorch Backend Vendors": [[2098, null]], "PyTorch 2.0 NNModule Support": [[2113, "pytorch-2-0-nnmodule-support"]], "NNModule Hooks Support": [[2113, "nnmodule-hooks-support"]], "nn.Module.__call__ Hooks Usage and limitations": [[2113, "nn-module-call-hooks-usage-and-limitations"]], "state_dict Hooks": [[2113, "state-dict-hooks"]], "IRs": [[2112, "irs"]], "Core Aten IR": [[2112, "core-aten-ir"]], "Prims IR": [[2112, "prims-ir"]], "TorchInductor GPU Profiling": [[2111, "torchinductor-gpu-profiling"]], "Relevant Environment Variables": [[2111, "relevant-environment-variables"]], "Breakdown Model GPU Time": [[2111, "breakdown-model-gpu-time"]], "Benchmark Individual Triton Kernel": [[2111, "benchmark-individual-triton-kernel"]], "torch.Tensor": [[2092, "torch-tensor"]], "Data types": [[2092, "data-types"]], "Initializing and basic operations": [[2092, "initializing-and-basic-operations"]], "Tensor class reference": [[2092, "tensor-class-reference"]], "Understanding CUDA Memory Usage": [[2119, "understanding-cuda-memory-usage"]], "Generating a Snapshot": [[2119, "generating-a-snapshot"]], "Using the visualizer": [[2119, "using-the-visualizer"]], "Active Memory Timeline": [[2119, "active-memory-timeline"]], "Allocator State History": [[2119, "allocator-state-history"]], "Snapshot API Reference": [[2119, "snapshot-api-reference"]], "Dynamic shapes": [[2104, "dynamic-shapes"]], "Abridged public API": [[2104, "abridged-public-api"]], "The Guard Model": [[2104, "the-guard-model"]], "Abridged internal API": [[2104, "abridged-internal-api"]], "DimDynamic policy": [[2104, "dimdynamic-policy"]], "Unbacked SymInts": [[2104, "unbacked-symints"]], "torch.ao.ns._numeric_suite_fx": [[2097, "torch-ao-ns-numeric-suite-fx"]], "torch.ao.ns.fx.utils": [[2097, "torch-ao-ns-fx-utils"]], "torch.xpu": [[2124, "module-torch.xpu"]], "Random Number Generator": [[2124, "random-number-generator"], [17, "random-number-generator"]], "PyTorch 2.0 Troubleshooting": [[2117, "pytorch-2-0-troubleshooting"]], "Title": [[2117, "id1"]], "Diagnosing Runtime Errors": [[2117, "diagnosing-runtime-errors"]], "Torchdynamo Errors": [[2117, "torchdynamo-errors"]], "Diagnosing TorchInductor Errors": [[2117, "diagnosing-torchinductor-errors"]], "Minifying TorchInductor Errors": [[2117, "minifying-torchinductor-errors"]], "Minifying Backend Compiler Errors": [[2117, "minifying-backend-compiler-errors"]], "Performance Profiling": [[2117, "performance-profiling"]], "Accessing TorchDynamo Profiler": [[2117, "accessing-torchdynamo-profiler"]], "TorchInductor Debugging using TORCH_COMPILE_DEBUG": [[2117, "torchinductor-debugging-using-torch-compile-debug"]], "Identifying the Cause of a Graph Break": [[2117, "identifying-the-cause-of-a-graph-break"]], "Excessive Recompilation": [[2117, "excessive-recompilation"]], "Accuracy Debugging": [[2117, "accuracy-debugging"]], "Extended Debugging": [[2117, "extended-debugging"]], "Cold Start Timing and Cache Corruption Debugging": [[2117, "cold-start-timing-and-cache-corruption-debugging"]], "torch.utils": [[2123, "module-torch.utils"]], "AOTInductor: Ahead-Of-Time Compilation for Torch.Export-ed Models": [[2099, "aotinductor-ahead-of-time-compilation-for-torch-export-ed-models"]], "Model Compilation": [[2099, "model-compilation"]], "Inference in C++": [[2099, "inference-in-c"]], "Torch Environment Variables": [[2120, "torch-environment-variables"]], "torch.overrides": [[2118, "module-torch.overrides"]], "torch.jit.wait": [[1293, "torch-jit-wait"]], "torch.linalg.eigh": [[1311, "torch-linalg-eigh"]], "torch.less": [[1301, "torch-less"]], "torch.linalg.eig": [[1310, "torch-linalg-eig"]], "torch.jit.script": [[1286, "torch-jit-script"]], "torch.linalg.cond": [[1306, "torch-linalg-cond"]], "torch.jit.freeze": [[1278, "torch-jit-freeze"]], "torch.jit.interface": [[1280, "torch-jit-interface"]], "torch.jit.annotate": [[1275, "torch-jit-annotate"]], "torch.linalg.lstsq": [[1320, "torch-linalg-lstsq"]], "torch.jit.fork": [[1277, "torch-jit-fork"]], "torch.linalg.diagonal": [[1309, "torch-linalg-diagonal"]], "torch.jit.isinstance": [[1281, "torch-jit-isinstance"]], "torch.jit.set_fusion_strategy": [[1288, "torch-jit-set-fusion-strategy"]], "torch.lcm": [[1297, "torch-lcm"]], "torch.linalg.cholesky": [[1304, "torch-linalg-cholesky"]], "torch.linalg.eigvals": [[1312, "torch-linalg-eigvals"]], "torch.linalg.lu_solve": [[1324, "torch-linalg-lu-solve"]], "torch.linalg.eigvalsh": [[1313, "torch-linalg-eigvalsh"]], "torch.jit.script_if_tracing": [[1287, "torch-jit-script-if-tracing"]], "torch.jit.unused": [[1292, "torch-jit-unused"]], "torch.lerp": [[1300, "torch-lerp"]], "torch.jit.trace_module": [[1291, "torch-jit-trace-module"]], "torch.linalg.det": [[1308, "torch-linalg-det"]], "torch.linalg.householder_product": [[1314, "torch-linalg-householder-product"]], "torch.linalg.cholesky_ex": [[1305, "torch-linalg-cholesky-ex"]], "torch.kaiser_window": [[1294, "torch-kaiser-window"]], "torch.jit.load": [[1282, "torch-jit-load"]], "torch.jit.trace": [[1290, "torch-jit-trace"]], "torch.linalg.ldl_factor": [[1317, "torch-linalg-ldl-factor"]], "torch.jit.save": [[1285, "torch-jit-save"]], "torch.linalg.cross": [[1307, "torch-linalg-cross"]], "torch.jit.enable_onednn_fusion": [[1276, "torch-jit-enable-onednn-fusion"]], "torch.linalg.inv": [[1315, "torch-linalg-inv"]], "torch.linalg.lu": [[1321, "torch-linalg-lu"]], "torch.le": [[1299, "torch-le"]], "torch.linalg.lu_factor_ex": [[1323, "torch-linalg-lu-factor-ex"]], "strict_fusion": [[1289, "strict-fusion"]], "torch.lgamma": [[1303, "torch-lgamma"]], "torch.linalg.ldl_factor_ex": [[1318, "torch-linalg-ldl-factor-ex"]], "torch.linalg.ldl_solve": [[1319, "torch-linalg-ldl-solve"]], "torch.jit.onednn_fusion_enabled": [[1283, "torch-jit-onednn-fusion-enabled"]], "torch.kthvalue": [[1296, "torch-kthvalue"]], "torch.jit.ignore": [[1279, "torch-jit-ignore"]], "torch.ldexp": [[1298, "torch-ldexp"]], "torch.less_equal": [[1302, "torch-less-equal"]], "torch.linalg.matmul": [[1325, "torch-linalg-matmul"]], "torch.linalg.lu_factor": [[1322, "torch-linalg-lu-factor"]], "torch.kron": [[1295, "torch-kron"]], "torch.jit.optimize_for_inference": [[1284, "torch-jit-optimize-for-inference"]], "torch.linalg.inv_ex": [[1316, "torch-linalg-inv-ex"]], "torch.get_num_threads": [[1226, "torch-get-num-threads"]], "torch.is_conj": [[1254, "torch-is-conj"]], "torch.hann_window": [[1233, "torch-hann-window"]], "torch.is_nonzero": [[1259, "torch-is-nonzero"]], "torch.isneginf": [[1268, "torch-isneginf"]], "torch.histogramdd": [[1237, "torch-histogramdd"]], "torch.igammac": [[1244, "torch-igammac"]], "torch.greater": [[1229, "torch-greater"]], "torch.index_reduce": [[1248, "torch-index-reduce"]], "torch.histc": [[1235, "torch-histc"]], "torch.igamma": [[1243, "torch-igamma"]], "torch.inner": [[1251, "torch-inner"]], "torch.get_num_interop_threads": [[1225, "torch-get-num-interop-threads"]], "torch.gt": [[1231, "torch-gt"]], "torch.is_deterministic_algorithms_warn_only_enabled": [[1255, "torch-is-deterministic-algorithms-warn-only-enabled"]], "torch.isclose": [[1263, "torch-isclose"]], "torch.is_complex": [[1253, "torch-is-complex"]], "torch.get_float32_matmul_precision": [[1224, "torch-get-float32-matmul-precision"]], "torch.imag": [[1245, "torch-imag"]], "torch.greater_equal": [[1230, "torch-greater-equal"]], "torch.is_warn_always_enabled": [[1262, "torch-is-warn-always-enabled"]], "torch.i0": [[1242, "torch-i0"]], "torch.is_tensor": [[1261, "torch-is-tensor"]], "torch.index_add": [[1246, "torch-index-add"]], "torch.inverse": [[1252, "torch-inverse"]], "torch.initial_seed": [[1250, "torch-initial-seed"]], "torch.isinf": [[1266, "torch-isinf"]], "torch.istft": [[1271, "torch-istft"]], "torch.is_inference_mode_enabled": [[1258, "torch-is-inference-mode-enabled"]], "torch.histogram": [[1236, "torch-histogram"]], "torch.isfinite": [[1264, "torch-isfinite"]], "torch.index_copy": [[1247, "torch-index-copy"]], "torch.isreal": [[1270, "torch-isreal"]], "ScriptFunction": [[1273, "scriptfunction"]], "torch.isposinf": [[1269, "torch-isposinf"]], "torch.hsplit": [[1238, "torch-hsplit"]], "torch.is_grad_enabled": [[1257, "torch-is-grad-enabled"]], "torch.heaviside": [[1234, "torch-heaviside"]], "torch.isin": [[1265, "torch-isin"]], "torch.is_floating_point": [[1256, "torch-is-floating-point"]], "torch.hypot": [[1241, "torch-hypot"]], "torch.hamming_window": [[1232, "torch-hamming-window"]], "ScriptModule": [[1274, "scriptmodule"]], "torch.gradient": [[1228, "torch-gradient"]], "torch.index_select": [[1249, "torch-index-select"]], "torch.get_rng_state": [[1227, "torch-get-rng-state"]], "torch.is_storage": [[1260, "torch-is-storage"]], "torch.isnan": [[1267, "torch-isnan"]], "Attribute": [[1272, "attribute"]], "torch.hspmm": [[1239, "torch-hspmm"]], "torch.hstack": [[1240, "torch-hstack"]], "ShapeEnvSettings": [[1190, "shapeenvsettings"]], "torch.get_deterministic_debug_mode": [[1222, "torch-get-deterministic-debug-mode"]], "torch.geqrf": [[1218, "torch-geqrf"]], "torch.func.replace_all_batch_norm_modules_": [[1176, "torch-func-replace-all-batch-norm-modules"]], "torch.func.vjp": [[1178, "torch-func-vjp"]], "torch.fx.experimental.symbolic_shapes.constrain_unify": [[1200, "torch-fx-experimental-symbolic-shapes-constrain-unify"]], "StatelessSymbolicContext": [[1192, "statelesssymboliccontext"]], "StatefulSymbolicContext": [[1191, "statefulsymboliccontext"]], "RelaxedUnspecConstraint": [[1188, "relaxedunspecconstraint"]], "torch.fx.experimental.symbolic_shapes.compute_unbacked_bindings": [[1198, "torch-fx-experimental-symbolic-shapes-compute-unbacked-bindings"]], "torch.func.vmap": [[1179, "torch-func-vmap"]], "torch.func.jacrev": [[1173, "torch-func-jacrev"]], "torch.fx.experimental.symbolic_shapes.parallel_or": [[1210, "torch-fx-experimental-symbolic-shapes-parallel-or"]], "torch.fx.experimental.symbolic_shapes.canonicalize_bool_expr": [[1196, "torch-fx-experimental-symbolic-shapes-canonicalize-bool-expr"]], "torch.fx.experimental.symbolic_shapes.rebind_unbacked": [[1211, "torch-fx-experimental-symbolic-shapes-rebind-unbacked"]], "SubclassSymbolicContext": [[1194, "subclasssymboliccontext"]], "torch.get_device_module": [[1223, "torch-get-device-module"]], "ConvertIntKey": [[1181, "convertintkey"]], "torch.fx.experimental.symbolic_shapes.statically_known_true": [[1213, "torch-fx-experimental-symbolic-shapes-statically-known-true"]], "EqualityConstraint": [[1185, "equalityconstraint"]], 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"checking-for-hip"]], "TensorFloat-32(TF32) on ROCm": [[2059, "tensorfloat-32-tf32-on-rocm"]], "hipFFT/rocFFT plan cache": [[2059, "hipfft-rocfft-plan-cache"]], "torch.distributed backends": [[2059, "torch-distributed-backends"]], "CUDA API to HIP API mappings in C++": [[2059, "cuda-api-to-hip-api-mappings-in-c"]], "Refer to CUDA Semantics doc": [[2059, "refer-to-cuda-semantics-doc"]], "Enabling kernel asserts": [[2059, "enabling-kernel-asserts"]], "Serialization semantics": [[2066, "serialization-semantics"]], "Table of Contents": [[2066, "table-of-contents"]], "Saving and loading tensors": [[2066, "saving-and-loading-tensors"]], "Saving and loading tensors preserves views": [[2066, "saving-and-loading-tensors-preserves-views"]], "Saving and loading torch.nn.Modules": [[2066, "saving-and-loading-torch-nn-modules"]], "Serialized file format for torch.save": [[2066, "serialized-file-format-for-torch-save"]], "Serializing torch.nn.Modules and loading them in C++": [[2066, "serializing-torch-nn-modules-and-loading-them-in-c"]], "Saving and loading ScriptModules across PyTorch versions": [[2066, "saving-and-loading-scriptmodules-across-pytorch-versions"]], "torch.div performing integer division": [[2066, "torch-div-performing-integer-division"]], "torch.full always inferring a float dtype": [[2066, "torch-full-always-inferring-a-float-dtype"]], "Utility functions": [[2066, "utility-functions"], [2079, "utility-functions"]], "Broadcasting semantics": [[2048, "broadcasting-semantics"]], "General semantics": [[2048, "general-semantics"]], "In-place semantics": [[2048, "in-place-semantics"]], "Backwards compatibility": [[2048, "backwards-compatibility"]], "FSDP Notes": [[2056, "fsdp-notes"]], "FSDP Prefetch Nuances": [[2056, "fsdp-prefetch-nuances"]], "Communication payload size": [[2056, "communication-payload-size"]], "FSDP buffers sizes": [[2056, "fsdp-buffers-sizes"]], "Remote Reference Protocol": [[2083, "remote-reference-protocol"]], "RRef Lifetime": [[2083, "rref-lifetime"]], "Design Reasoning": [[2083, "design-reasoning"]], "Implementation": [[2083, "implementation"], [2052, "implementation"]], "Protocol Scenarios": [[2083, "protocol-scenarios"]], "User Share RRef with Owner as Return Value": [[2083, "user-share-rref-with-owner-as-return-value"]], "User Share RRef with Owner as Argument": [[2083, "user-share-rref-with-owner-as-argument"]], "Owner Share RRef with User": [[2083, "owner-share-rref-with-user"]], "User Share RRef with User": [[2083, "user-share-rref-with-user"]], "torch.nested": [[2040, "module-torch.nested"]], "Construction": [[2040, "construction"], [2086, "construction"]], "size": [[2040, "size"]], "unbind": [[2040, "unbind"]], "Nested tensor constructor and conversion functions": [[2040, "nested-tensor-constructor-and-conversion-functions"]], "Supported operations": [[2040, "supported-operations"], [2086, "supported-operations"]], "Numerical accuracy": [[2064, "numerical-accuracy"]], "Batched computations or slice computations": [[2064, "batched-computations-or-slice-computations"]], "Extremal values": [[2064, "extremal-values"]], "Linear algebra (torch.linalg)": [[2064, "linear-algebra-torch-linalg"]], "Non-finite values": [[2064, "non-finite-values"]], "Extremal values in linalg": [[2064, "extremal-values-in-linalg"]], "TensorFloat-32(TF32) on Nvidia Ampere (and later) devices": [[2064, "tensorfloat-32-tf32-on-nvidia-ampere-and-later-devices"]], "Reduced Precision Reduction for FP16 and BF16 GEMMs": [[2064, "reduced-precision-reduction-for-fp16-and-bf16-gemms"]], "Reduced Precision FP16 and BF16 GEMMs and Convolutions on AMD Instinct MI200 devices": [[2064, "reduced-precision-fp16-and-bf16-gemms-and-convolutions-on-amd-instinct-mi200-devices"]], "torch.signal": [[2084, "module-torch.signal"]], "torch.signal.windows": [[2084, "module-torch.signal.windows"]], "Distributed Data Parallel": [[2052, "distributed-data-parallel"]], "Internal Design": [[2052, "internal-design"]], "ProcessGroup": [[2052, "processgroup"]], "TorchDynamo DDPOptimizer": [[2052, "id1"]], "Quantization API Reference": [[2079, "quantization-api-reference"], [2076, "quantization-api-reference"]], "torch.ao.quantization": [[2079, "torch-ao-quantization"]], "Top level APIs": [[2079, "top-level-apis"]], "Preparing model for quantization": [[2079, "preparing-model-for-quantization"]], "torch.ao.quantization.quantize_fx": [[2079, "torch-ao-quantization-quantize-fx"]], "torch.ao.quantization.qconfig_mapping": [[2079, "torch-ao-quantization-qconfig-mapping"]], "torch.ao.quantization.backend_config": [[2079, "torch-ao-quantization-backend-config"]], "torch.ao.quantization.fx.custom_config": [[2079, "torch-ao-quantization-fx-custom-config"]], "torch.ao.quantization.quantizer": [[2079, "module-torch.ao.quantization.quantizer"]], "torch.ao.quantization.pt2e (quantization in pytorch 2.0 export implementation)": [[2079, "module-torch.ao.quantization.pt2e"]], "torch.ao.quantization.pt2e.export_utils": [[2079, "torch-ao-quantization-pt2e-export-utils"]], "torch (quantization related functions)": [[2079, "torch-quantization-related-functions"]], "torch.Tensor (quantization related methods)": [[2079, "torch-tensor-quantization-related-methods"]], "torch.ao.quantization.observer": [[2079, "torch-ao-quantization-observer"]], "torch.ao.quantization.fake_quantize": [[2079, "torch-ao-quantization-fake-quantize"]], "torch.ao.quantization.qconfig": [[2079, "torch-ao-quantization-qconfig"]], "torch.ao.nn.intrinsic": [[2079, "module-torch.ao.nn.intrinsic"]], "torch.ao.nn.intrinsic.qat": [[2079, "module-torch.ao.nn.intrinsic.qat"]], "torch.ao.nn.intrinsic.quantized": [[2079, "module-torch.ao.nn.intrinsic.quantized"]], "torch.ao.nn.intrinsic.quantized.dynamic": [[2079, "module-torch.ao.nn.intrinsic.quantized.dynamic"]], "torch.ao.nn.qat": [[2079, "module-torch.ao.nn.qat"]], "torch.ao.nn.qat.dynamic": [[2079, "module-torch.ao.nn.qat.dynamic"]], "torch.ao.nn.quantized": [[2079, "module-torch.ao.nn.quantized.modules"]], "torch.ao.nn.quantized.functional": [[2079, "module-torch.ao.nn.quantized.functional"]], "torch.ao.nn.quantizable": [[2079, "torch-ao-nn-quantizable"]], "torch.ao.nn.quantized.dynamic": [[2079, "module-torch.ao.nn.quantized.dynamic"]], "Quantized dtypes and quantization schemes": [[2079, "quantized-dtypes-and-quantization-schemes"]], "torch.random": [[2080, "module-torch.random"]], "Quantization": [[2076, "module-torch.ao.quantization"]], "Introduction to Quantization": [[2076, "introduction-to-quantization"]], "Quantization API Summary": [[2076, "quantization-api-summary"]], "Eager Mode Quantization": [[2076, "eager-mode-quantization"]], "Post Training Dynamic Quantization": [[2076, "post-training-dynamic-quantization"]], "Post Training Static Quantization": [[2076, "post-training-static-quantization"]], "Quantization Aware Training for Static Quantization": [[2076, "quantization-aware-training-for-static-quantization"]], "Model Preparation for Eager Mode Static Quantization": [[2076, "model-preparation-for-eager-mode-static-quantization"]], "(Prototype - maintenance mode) FX Graph Mode Quantization": [[2076, "prototype-maintenance-mode-fx-graph-mode-quantization"]], "(Prototype) PyTorch 2 Export Quantization": [[2076, "prototype-pytorch-2-export-quantization"]], "Quantization Stack": [[2076, "quantization-stack"]], "Quantized Model": [[2076, "quantized-model"]], "Quantized Tensor": [[2076, "quantized-tensor"]], "Quantize and Dequantize": [[2076, "quantize-and-dequantize"]], "Quantized Operators/Modules": [[2076, "quantized-operators-modules"]], "Quantized Engine": [[2076, "quantized-engine"]], "Quantization Flow": [[2076, "quantization-flow"]], "Observer and FakeQuantize": [[2076, "observer-and-fakequantize"]], "QConfig": [[2076, "qconfig"], [845, "qconfig"]], "General Quantization Flow": [[2076, "general-quantization-flow"]], "Quantization Support Matrix": [[2076, "quantization-support-matrix"]], "Quantization Mode Support": [[2076, "quantization-mode-support"]], "Quantization Flow Support": [[2076, "quantization-flow-support"]], "Backend/Hardware Support": [[2076, "backend-hardware-support"]], "Note for native CPU backends": [[2076, "note-for-native-cpu-backends"]], "Operator Support": [[2076, "operator-support"]], "Quantization Customizations": [[2076, "quantization-customizations"]], "Quantization Custom Module API": [[2076, "quantization-custom-module-api"]], "Best Practices": [[2076, "best-practices"]], "Common Errors": [[2076, "common-errors"]], "Passing a non-quantized Tensor into a quantized kernel": [[2076, "passing-a-non-quantized-tensor-into-a-quantized-kernel"]], "Passing a quantized Tensor into a non-quantized kernel": [[2076, "passing-a-quantized-tensor-into-a-non-quantized-kernel"]], "Saving and Loading Quantized models": [[2076, "saving-and-loading-quantized-models"]], "Symbolic Trace Error when using FX Graph Mode Quantization": [[2076, "symbolic-trace-error-when-using-fx-graph-mode-quantization"]], "Tensor Views": [[2090, "tensor-views"]], "Extending torch.func with autograd.Function": [[2054, "extending-torch-func-with-autograd-function"]], "Basic Usage": [[2054, "basic-usage"]], "Example 1: autograd.Function calls into another system": [[2054, "example-1-autograd-function-calls-into-another-system"]], "Example 2: autograd.Function specifies custom gradient rules": [[2054, "example-2-autograd-function-specifies-custom-gradient-rules"]], "Limitations and gotchas": [[2054, "limitations-and-gotchas"]], "torch.vmap() Support": [[2054, "torch-vmap-support"]], "Automatically generate a vmap rule": [[2054, "automatically-generate-a-vmap-rule"]], "Defining the vmap staticmethod": [[2054, "defining-the-vmap-staticmethod"]], "torch.func.jvp() Support": [[2054, "torch-func-jvp-support"]], "torch.profiler": [[2075, "torch-profiler"]], "Intel Instrumentation and Tracing Technology APIs": [[2075, "intel-instrumentation-and-tracing-technology-apis"]], "torch.Size": [[2085, "torch-size"]], "torch.sparse": [[2086, "torch-sparse"]], "Why and when to use sparsity": [[2086, "why-and-when-to-use-sparsity"]], "Functionality overview": [[2086, "functionality-overview"]], "Operator overview": [[2086, "operator-overview"]], "Sparse Semi-Structured Tensors": [[2086, "sparse-semi-structured-tensors"]], "Constructing Sparse Semi-Structured Tensors": [[2086, "constructing-sparse-semi-structured-tensors"]], "Sparse Semi-Structured Tensor Operations": [[2086, "sparse-semi-structured-tensor-operations"]], "Accelerating nn.Linear with semi-structured sparsity": [[2086, "accelerating-nn-linear-with-semi-structured-sparsity"]], "Sparse COO tensors": [[2086, "sparse-coo-tensors"]], "Sparse hybrid COO tensors": [[2086, "sparse-hybrid-coo-tensors"]], "Uncoalesced sparse COO tensors": [[2086, "uncoalesced-sparse-coo-tensors"]], "Working with sparse COO tensors": [[2086, "working-with-sparse-coo-tensors"]], "Sparse Compressed Tensors": [[2086, "sparse-compressed-tensors"]], "Sparse CSR Tensor": [[2086, "sparse-csr-tensor"]], "Construction of CSR tensors": [[2086, "construction-of-csr-tensors"]], "CSR Tensor Operations": [[2086, "csr-tensor-operations"]], "Sparse CSC Tensor": [[2086, "sparse-csc-tensor"]], "Construction of CSC tensors": [[2086, "construction-of-csc-tensors"]], "Sparse BSR Tensor": [[2086, "sparse-bsr-tensor"]], "Construction of BSR tensors": [[2086, "construction-of-bsr-tensors"]], "Sparse BSC Tensor": [[2086, "sparse-bsc-tensor"]], "Construction of BSC tensors": [[2086, "construction-of-bsc-tensors"]], "Tools for working with sparse compressed tensors": [[2086, "tools-for-working-with-sparse-compressed-tensors"]], "Construction of sparse compressed tensors": [[2086, "construction-of-sparse-compressed-tensors"]], "Linear Algebra operations": [[2086, "linear-algebra-operations"]], "Tensor methods and sparse": [[2086, "tensor-methods-and-sparse"]], "Torch functions specific to sparse Tensors": [[2086, "torch-functions-specific-to-sparse-tensors"]], "Other functions": [[2086, "other-functions"]], "Unary functions": [[2086, "unary-functions"]], "torch.optim": [[2073, "module-torch.optim"]], "How to use an optimizer": [[2073, "how-to-use-an-optimizer"]], "Constructing it": [[2073, "constructing-it"]], "Per-parameter options": [[2073, "per-parameter-options"]], "Taking an optimization step": [[2073, "taking-an-optimization-step"]], "optimizer.step()": [[2073, "optimizer-step"]], "optimizer.step(closure)": [[2073, "optimizer-step-closure"]], "Base class": [[2073, "base-class"]], "Algorithms": [[2073, "algorithms"]], "How to adjust learning rate": [[2073, "how-to-adjust-learning-rate"]], "Weight Averaging (SWA and EMA)": [[2073, "weight-averaging-swa-and-ema"]], "Constructing averaged models": [[2073, "constructing-averaged-models"]], "Custom averaging strategies": [[2073, "custom-averaging-strategies"]], "SWA learning rate schedules": [[2073, "swa-learning-rate-schedules"]], "Taking care of batch normalization": [[2073, "taking-care-of-batch-normalization"]], "Putting it all together: SWA": [[2073, "putting-it-all-together-swa"]], "Putting it all together: EMA": [[2073, "putting-it-all-together-ema"]], "Tensor Attributes": [[2089, "tensor-attributes"]], "torch.dtype": [[2089, "torch-dtype"]], "torch.device": [[2089, "torch-device"]], "torch.layout": [[2089, "torch-layout"]], "torch.memory_format": [[2089, "torch-memory-format"]], "Multiprocessing best practices": [[2063, "multiprocessing-best-practices"]], "CUDA in multiprocessing": [[2063, "cuda-in-multiprocessing"]], "Best practices and tips": [[2063, "best-practices-and-tips"]], "Avoiding and fighting deadlocks": [[2063, "avoiding-and-fighting-deadlocks"]], "Reuse buffers passed through a Queue": [[2063, "reuse-buffers-passed-through-a-queue"]], "Asynchronous multiprocess training (e.g. Hogwild)": [[2063, "asynchronous-multiprocess-training-e-g-hogwild"]], "Hogwild": [[2063, "hogwild"]], "CPU in multiprocessing": [[2063, "cpu-in-multiprocessing"]], "CPU oversubscription": [[2063, "cpu-oversubscription"]], "Avoid CPU oversubscription": [[2063, "avoid-cpu-oversubscription"]], "Distributed RPC Framework": [[2081, "distributed-rpc-framework"]], "Basics": [[2081, "basics"], [28, "basics"]], "RPC": [[2081, "rpc"]], "Backends": [[2081, "backends"], [28, "backends"]], "TensorPipe Backend": [[2081, "tensorpipe-backend"]], "RRef": [[2081, "rref"]], "More Information about RRef": [[2081, null]], "RemoteModule": [[2081, "remotemodule"]], "Distributed Autograd Framework": [[2081, "distributed-autograd-framework"]], "More Information about RPC Autograd": [[2081, null]], "Distributed Optimizer": [[2081, "distributed-optimizer"], [2082, "distributed-optimizer"]], "Tutorials": [[2081, "tutorials"], [2074, "tutorials"], [7, "tutorials"]], "torch.nn.init": [[2045, "torch-nn-init"]], "CPU threading and TorchScript inference": [[2049, "cpu-threading-and-torchscript-inference"]], "Build options": [[2049, "build-options"]], "Runtime API": [[2049, "runtime-api"]], "Tuning the number of threads": [[2049, "tuning-the-number-of-threads"]], "Distributed Autograd Design": [[2082, "distributed-autograd-design"]], "Autograd recording during the forward pass": [[2082, "autograd-recording-during-the-forward-pass"]], "Distributed Autograd Context": [[2082, "distributed-autograd-context"]], "Distributed Backward Pass": [[2082, "distributed-backward-pass"]], "Computing dependencies": [[2082, "computing-dependencies"]], "FAST mode algorithm": [[2082, "fast-mode-algorithm"]], "SMART mode algorithm": [[2082, "smart-mode-algorithm"]], "Simple end to end example": [[2082, "simple-end-to-end-example"]], "torch.package": [[2074, "torch-package"]], "Packaging your first model": [[2074, "packaging-your-first-model"]], "How do I\u2026": [[2074, "how-do-i"]], "See what is inside a package?": [[2074, "see-what-is-inside-a-package"]], "Treat the package like a ZIP archive": [[2074, "treat-the-package-like-a-zip-archive"]], "Use the file_structure() API": [[2074, "use-the-file-structure-api"]], "See why a given module was included as a dependency?": [[2074, "see-why-a-given-module-was-included-as-a-dependency"]], "Include arbitrary resources with my package and access them later?": [[2074, "include-arbitrary-resources-with-my-package-and-access-them-later"]], "Customize how a class is packaged?": [[2074, "customize-how-a-class-is-packaged"]], "Test in my source code whether or not it is executing inside a package?": [[2074, "test-in-my-source-code-whether-or-not-it-is-executing-inside-a-package"]], "Patch code into a package?": [[2074, "patch-code-into-a-package"]], "Access package contents from packaged code?": [[2074, "access-package-contents-from-packaged-code"]], "Distinguish between packaged code and non-packaged code?": [[2074, "distinguish-between-packaged-code-and-non-packaged-code"]], "Re-export an imported object?": [[2074, "re-export-an-imported-object"]], "Package a TorchScript module?": [[2074, "package-a-torchscript-module"]], "Explanation": [[2074, "explanation"]], "torch.package Format Overview": [[2074, "torch-package-format-overview"]], "Framework files": [[2074, "framework-files"]], "User files": [[2074, "user-files"]], "How torch.package finds your code\u2019s dependencies": [[2074, "how-torch-package-finds-your-code-s-dependencies"]], "Analyzing an object\u2019s dependencies": [[2074, "analyzing-an-object-s-dependencies"]], "Analyzing a module\u2019s dependencies": [[2074, "analyzing-a-module-s-dependencies"]], "Dependency Management": [[2074, "dependency-management"]], "intern": [[2074, "intern"]], "extern": [[2074, "extern"]], "mock": [[2074, "mock"]], "Refactoring": [[2074, "refactoring"]], "Patterns": [[2074, "patterns"]], "torch.package sharp edges": [[2074, "torch-package-sharp-edges"]], "Avoid global state in your modules": [[2074, "avoid-global-state-in-your-modules"]], "Types are not shared between packages and the loading environment": [[2074, "types-are-not-shared-between-packages-and-the-loading-environment"]], "How torch.package keeps packages isolated from each other": [[2074, "how-torch-package-keeps-packages-isolated-from-each-other"]], "Mangling": [[2074, "mangling"]], "PyTorch Custom Operators Landing Page": [[2051, "pytorch-custom-operators-landing-page"]], "Features for large-scale deployments": [[2060, "features-for-large-scale-deployments"]], "Fleet-wide operator profiling": [[2060, "fleet-wide-operator-profiling"]], "API usage logging": [[2060, "api-usage-logging"]], "Attaching metadata to saved TorchScript models": [[2060, "attaching-metadata-to-saved-torchscript-models"]], "Build environment considerations": [[2060, "build-environment-considerations"]], "Common extension points": [[2060, "common-extension-points"]], "torch.Storage": [[2088, "torch-storage"]], "Reproducibility": [[2065, "reproducibility"]], "Controlling sources of randomness": [[2065, "controlling-sources-of-randomness"]], "PyTorch random number generator": [[2065, "pytorch-random-number-generator"]], "Python": [[2065, "python"]], "Random number generators in other libraries": [[2065, "random-number-generators-in-other-libraries"]], "CUDA convolution benchmarking": [[2065, "cuda-convolution-benchmarking"]], "Avoiding nondeterministic algorithms": [[2065, "avoiding-nondeterministic-algorithms"]], "CUDA convolution determinism": [[2065, "cuda-convolution-determinism"]], "CUDA RNN and LSTM": [[2065, "cuda-rnn-and-lstm"]], "Filling uninitialized memory": [[2065, "filling-uninitialized-memory"]], "DataLoader": [[2065, "dataloader"]], "torch.nn.attention": [[2042, "module-torch.nn.attention"]], "Utils": [[2042, "utils"]], "Submodules": [[2042, "submodules"]], "Gradcheck mechanics": [[2058, "gradcheck-mechanics"]], "Notations and background information": [[2058, "notations-and-background-information"]], "Default backward mode gradcheck behavior": [[2058, "default-backward-mode-gradcheck-behavior"]], "Real-to-real functions": [[2058, "real-to-real-functions"]], "Default real input numerical evaluation": [[2058, "default-real-input-numerical-evaluation"]], "Default real input analytical evaluation": [[2058, "default-real-input-analytical-evaluation"]], "Complex-to-real functions": [[2058, "complex-to-real-functions"]], "Default complex input numerical evaluation": [[2058, "default-complex-input-numerical-evaluation"]], "Default complex input analytical evaluation": [[2058, "default-complex-input-analytical-evaluation"]], "Functions with complex outputs": [[2058, "functions-with-complex-outputs"]], "Fast backward mode gradcheck": [[2058, "fast-backward-mode-gradcheck"]], "Fast gradcheck for real-to-real functions": [[2058, "fast-gradcheck-for-real-to-real-functions"]], "Fast gradcheck for complex-to-real functions": [[2058, "fast-gradcheck-for-complex-to-real-functions"]], "Fast complex input numerical evaluation": [[2058, "fast-complex-input-numerical-evaluation"]], "Fast complex input analytical evaluation": [[2058, "fast-complex-input-analytical-evaluation"]], "Why not use a complex u": [[2058, "why-not-use-a-complex-u"]], "Fast gradcheck for functions with complex outputs": [[2058, "fast-gradcheck-for-functions-with-complex-outputs"]], "Gradgradcheck implementation": [[2058, "gradgradcheck-implementation"]], "torch.special": [[2087, "torch-special"]], "A Simple Custom Module": [[2061, "a-simple-custom-module"]], "Modules as Building Blocks": [[2061, "modules-as-building-blocks"]], "Neural Network Training with Modules": [[2061, "neural-network-training-with-modules"]], "Module State": [[2061, "module-state"]], "Module Initialization": [[2061, "module-initialization"]], "Module Hooks": [[2061, "module-hooks"]], "Advanced Features": [[2061, "advanced-features"]], "Distributed Training": [[2061, 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"Platform-specific behaviors": [[23, "platform-specific-behaviors"]], "Randomness in multi-process data loading": [[23, "randomness-in-multi-process-data-loading"]], "Memory Pinning": [[23, "memory-pinning"]], "Tensor Parallelism - torch.distributed.tensor.parallel": [[34, "tensor-parallelism-torch-distributed-tensor-parallel"]], "Probability distributions - torch.distributions": [[35, "module-torch.distributions"]], "Score function": [[35, "score-function"]], "Pathwise derivative": [[35, "pathwise-derivative"]], "Distribution": [[35, "distribution"]], "ExponentialFamily": [[35, "exponentialfamily"]], "Bernoulli": [[35, "bernoulli"]], "Beta": [[35, "beta"]], "Binomial": [[35, "binomial"]], "Categorical": [[35, "categorical"]], "Cauchy": [[35, "cauchy"]], "Chi2": [[35, "chi2"]], "ContinuousBernoulli": [[35, "continuousbernoulli"]], "Dirichlet": [[35, "dirichlet"]], "Exponential": [[35, "exponential"]], "FisherSnedecor": [[35, "fishersnedecor"]], "Gamma": [[35, "gamma"]], "Geometric": [[35, "geometric"]], "Gumbel": [[35, "gumbel"]], "HalfCauchy": [[35, "halfcauchy"]], "HalfNormal": [[35, "halfnormal"]], "Independent": [[35, "independent"]], "InverseGamma": [[35, "inversegamma"]], "Kumaraswamy": [[35, "kumaraswamy"]], "LKJCholesky": [[35, "lkjcholesky"]], "Laplace": [[35, "laplace"]], "LogNormal": [[35, "lognormal"]], "LowRankMultivariateNormal": [[35, "lowrankmultivariatenormal"]], "MixtureSameFamily": [[35, "mixturesamefamily"]], "Multinomial": [[35, "multinomial"]], "MultivariateNormal": [[35, "multivariatenormal"]], "NegativeBinomial": [[35, "negativebinomial"]], "Normal": [[35, "normal"]], "OneHotCategorical": [[35, "onehotcategorical"]], "Pareto": [[35, "pareto"]], "Poisson": [[35, "poisson"]], "RelaxedBernoulli": [[35, "relaxedbernoulli"]], "LogitRelaxedBernoulli": [[35, "logitrelaxedbernoulli"]], "RelaxedOneHotCategorical": [[35, "relaxedonehotcategorical"]], "StudentT": [[35, "studentt"]], "TransformedDistribution": [[35, "transformeddistribution"]], "Uniform": [[35, "uniform"]], "VonMises": [[35, "vonmises"]], "Weibull": [[35, "weibull"]], "Wishart": [[35, "wishart"]], "KL Divergence": [[35, "module-torch.distributions.kl"]], "Transforms": [[35, "module-torch.distributions.transforms"]], "Constraint Registry": [[35, "module-torch.distributions.constraint_registry"]], "Pipeline Parallelism": [[33, "pipeline-parallelism"]], "Why Pipeline Parallel?": [[33, "why-pipeline-parallel"]], "What is torch.distributed.pipelining?": [[33, "what-is-torch-distributed-pipelining"]], "Step 1: build PipelineStage": [[33, "step-1-build-pipelinestage"]], "Step 2: use PipelineSchedule for execution": [[33, "step-2-use-pipelineschedule-for-execution"]], "Options for Splitting a Model": [[33, "options-for-splitting-a-model"]], "Option 1: splitting a model manually": [[33, "option-1-splitting-a-model-manually"]], "Option 2: splitting a model automatically": [[33, "option-2-splitting-a-model-automatically"]], "Hugging Face Examples": [[33, 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diff --git a/main/xpu.html b/main/xpu.html
index 656de6fce1..c41f469bff 100644
--- a/main/xpu.html
+++ b/main/xpu.html
@@ -281,7 +281,7 @@
           <div class="pytorch-left-menu-search">
             
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+gitfb696bf ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.5.0a0+git6adc725 ) &#x25BC</a>
     </div>