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- main (2.5.0a0+git75fa100 ) ▼ + main (2.5.0a0+gitfb696bf ) ▼
diff --git a/main/_modules/torch.html b/main/_modules/torch.html index e2169e9117..91ae14e4b0 100644 --- a/main/_modules/torch.html +++ b/main/_modules/torch.html @@ -280,7 +280,7 @@
- main (2.5.0a0+git75fa100 ) ▼ + main (2.5.0a0+gitfb696bf ) ▼
@@ -3087,6 +3087,53 @@

Source code for torch

 from torch import _logging
 
 _logging._init_logs()
+
+
+def _import_device_backends():
+    """
+    Leverage the Python plugin mechanism to load out-of-the-tree device extensions.
+    See this RFC: https://github.com/pytorch/pytorch/issues/122468
+    """
+    from importlib.metadata import entry_points
+
+    group_name = "torch.backends"
+    if sys.version_info < (3, 10):
+        backend_extensions = entry_points().get(group_name, ())
+    else:
+        backend_extensions = entry_points(group=group_name)
+
+    for backend_extension in backend_extensions:
+        try:
+            # Load the extension
+            entrypoint = backend_extension.load()
+            # Call the entrypoint
+            entrypoint()
+        except Exception as err:
+            raise RuntimeError(
+                f"Failed to load the backend extension: {backend_extension.name}. "
+                f"You can disable extension auto-loading with TORCH_DEVICE_BACKEND_AUTOLOAD=0."
+            ) from err
+
+
+def _is_device_backend_autoload_enabled() -> builtins.bool:
+    """
+    Whether autoloading out-of-the-tree device extensions is enabled.
+    The switch depends on the value of the environment variable
+    `TORCH_DEVICE_BACKEND_AUTOLOAD`.
+
+    Returns:
+        bool: Whether to enable autoloading the extensions. Enabled by default.
+
+    Examples:
+        >>> torch._is_device_backend_autoload_enabled()
+        True
+    """
+    # enabled by default
+    return os.getenv("TORCH_DEVICE_BACKEND_AUTOLOAD", "1") == "1"
+
+
+if _is_device_backend_autoload_enabled():
+    _import_device_backends()
diff --git a/main/_modules/torch/__config__.html b/main/_modules/torch/__config__.html index d5e8e8706a..fc8048b2ea 100644 --- a/main/_modules/torch/__config__.html +++ b/main/_modules/torch/__config__.html @@ -280,7 +280,7 @@
- main (2.5.0a0+git75fa100 ) ▼ + main (2.5.0a0+gitfb696bf ) ▼
diff --git a/main/_modules/torch/__future__.html b/main/_modules/torch/__future__.html index b47924f0ac..f5b71d7ca6 100644 --- a/main/_modules/torch/__future__.html +++ b/main/_modules/torch/__future__.html @@ -280,7 +280,7 @@
- main (2.5.0a0+git75fa100 ) ▼ + main (2.5.0a0+gitfb696bf ) ▼
diff --git a/main/_modules/torch/_jit_internal.html b/main/_modules/torch/_jit_internal.html index 682dad74c5..542047755a 100644 --- a/main/_modules/torch/_jit_internal.html +++ b/main/_modules/torch/_jit_internal.html @@ -280,7 +280,7 @@
- main (2.5.0a0+git75fa100 ) ▼ + main (2.5.0a0+gitfb696bf ) ▼
@@ -2045,6 +2045,15 @@

Source code for torch._jit_internal

     return tensors
 
 
+def _get_model_id(obj) -> Optional[str]:
+    if isinstance(obj, torch.jit.ScriptModule):
+        return str(obj._c._type())
+    elif isinstance(obj, torch.jit.ScriptFunction):
+        return obj.qualified_name
+    else:
+        return None
+
+
 # In Python-3.11+ typed enums (i.e. IntEnum for example) retain number of base class methods in subclass
 # that were previously dropped. To preserve the behavior, explicitly drop them there
 
diff --git a/main/_modules/torch/_lobpcg.html b/main/_modules/torch/_lobpcg.html
index beeeb82700..35e4b8fe5f 100644
--- a/main/_modules/torch/_lobpcg.html
+++ b/main/_modules/torch/_lobpcg.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/_logging/_internal.html b/main/_modules/torch/_logging/_internal.html
index ef63fb1277..5bb7b0f40f 100644
--- a/main/_modules/torch/_logging/_internal.html
+++ b/main/_modules/torch/_logging/_internal.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/_lowrank.html b/main/_modules/torch/_lowrank.html
index e239abc59b..16162915dc 100644
--- a/main/_modules/torch/_lowrank.html
+++ b/main/_modules/torch/_lowrank.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/_tensor.html b/main/_modules/torch/_tensor.html
index 6e98e3f243..0cd18fb77d 100644
--- a/main/_modules/torch/_tensor.html
+++ b/main/_modules/torch/_tensor.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -1684,14 +1684,19 @@ 
Source code for torch._tensor
         typestr = {
             torch.complex64: "<c8",
             torch.complex128: "<c16",
+            torch.bfloat16: "<f2",
             torch.float16: "<f2",
             torch.float32: "<f4",
             torch.float64: "<f8",
             torch.uint8: "|u1",
             torch.int8: "|i1",
+            torch.uint16: "<u2",
             torch.int16: "<i2",
+            torch.uint32: "<u4",
             torch.int32: "<i4",
+            torch.uint64: "<u8",
             torch.int64: "<i8",
+            torch.bool: "|b1",
         }[self.dtype]
 
         itemsize = self.element_size()
diff --git a/main/_modules/torch/_tensor_str.html b/main/_modules/torch/_tensor_str.html
index e0ab8c2a9b..84001c779f 100644
--- a/main/_modules/torch/_tensor_str.html
+++ b/main/_modules/torch/_tensor_str.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/amp/autocast_mode.html b/main/_modules/torch/amp/autocast_mode.html
index 4e3675e95c..901fb4d0e8 100644
--- a/main/_modules/torch/amp/autocast_mode.html
+++ b/main/_modules/torch/amp/autocast_mode.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/ao/nn/intrinsic/modules/fused.html b/main/_modules/torch/ao/nn/intrinsic/modules/fused.html
index 3b40dea4bb..aa648a4d38 100644
--- a/main/_modules/torch/ao/nn/intrinsic/modules/fused.html
+++ b/main/_modules/torch/ao/nn/intrinsic/modules/fused.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/ao/nn/intrinsic/qat/modules/conv_fused.html b/main/_modules/torch/ao/nn/intrinsic/qat/modules/conv_fused.html
index 7391dea8f2..08cd711970 100644
--- a/main/_modules/torch/ao/nn/intrinsic/qat/modules/conv_fused.html
+++ b/main/_modules/torch/ao/nn/intrinsic/qat/modules/conv_fused.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/ao/nn/intrinsic/qat/modules/linear_relu.html b/main/_modules/torch/ao/nn/intrinsic/qat/modules/linear_relu.html
index b45fbf87eb..7eb689be93 100644
--- a/main/_modules/torch/ao/nn/intrinsic/qat/modules/linear_relu.html
+++ b/main/_modules/torch/ao/nn/intrinsic/qat/modules/linear_relu.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.html b/main/_modules/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.html
index 74ea0a5b94..0ee9660f9e 100644
--- a/main/_modules/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.html
+++ b/main/_modules/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/ao/nn/intrinsic/quantized/modules/bn_relu.html b/main/_modules/torch/ao/nn/intrinsic/quantized/modules/bn_relu.html
index 25eb13d91d..1e020c57b1 100644
--- a/main/_modules/torch/ao/nn/intrinsic/quantized/modules/bn_relu.html
+++ b/main/_modules/torch/ao/nn/intrinsic/quantized/modules/bn_relu.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/ao/nn/intrinsic/quantized/modules/conv_relu.html b/main/_modules/torch/ao/nn/intrinsic/quantized/modules/conv_relu.html
index cc25684507..60eb7eb9f9 100644
--- a/main/_modules/torch/ao/nn/intrinsic/quantized/modules/conv_relu.html
+++ b/main/_modules/torch/ao/nn/intrinsic/quantized/modules/conv_relu.html
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index 105506ec7e..69fbef8046 100644
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index 46b07423fe..a15f76a800 100644
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index 801d77dd28..ac4ad0abaa 100644
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index 1e598f2bf6..857d1c6e07 100644
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index 383a43a656..c90d7a2dba 100644
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index 1c57334e2e..e08fb01ff2 100644
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index 742486d30d..5bf79d4aaa 100644
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index b3872d99d0..84f17370e2 100644
--- a/main/_modules/torch/distributions/lkj_cholesky.html
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index 128a8a8335..04cb2c5112 100644
--- a/main/_modules/torch/distributions/log_normal.html
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index 18a11dfcb5..ef1230c466 100644
--- a/main/_modules/torch/distributions/lowrank_multivariate_normal.html
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index 439c748ff4..c707912669 100644
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index 3b20a9b44e..6c3fc77766 100644
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index 6f581674f0..bc5b91e471 100644
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index 448d26be81..d69f1b4983 100644
--- a/main/_modules/torch/distributions/negative_binomial.html
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index d8476b859d..c430bd5c4a 100644
--- a/main/_modules/torch/distributions/normal.html
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index 908878b0d0..1acc65a0e8 100644
--- a/main/_modules/torch/distributions/one_hot_categorical.html
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diff --git a/main/_modules/torch/distributions/pareto.html b/main/_modules/torch/distributions/pareto.html
index fd44d4dfd7..de2d88b255 100644
--- a/main/_modules/torch/distributions/pareto.html
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diff --git a/main/_modules/torch/distributions/poisson.html b/main/_modules/torch/distributions/poisson.html
index 64deed6fdd..1d58a7eb7a 100644
--- a/main/_modules/torch/distributions/poisson.html
+++ b/main/_modules/torch/distributions/poisson.html
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index 81feb6cfc0..f91b06c7a3 100644
--- a/main/_modules/torch/distributions/relaxed_bernoulli.html
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diff --git a/main/_modules/torch/distributions/relaxed_categorical.html b/main/_modules/torch/distributions/relaxed_categorical.html
index e76781b4d4..268dc4cc87 100644
--- a/main/_modules/torch/distributions/relaxed_categorical.html
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index 11994dc845..374f25e017 100644
--- a/main/_modules/torch/distributions/studentT.html
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diff --git a/main/_modules/torch/distributions/transformed_distribution.html b/main/_modules/torch/distributions/transformed_distribution.html
index 008a7c33f7..e346b8fbaf 100644
--- a/main/_modules/torch/distributions/transformed_distribution.html
+++ b/main/_modules/torch/distributions/transformed_distribution.html
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diff --git a/main/_modules/torch/distributions/transforms.html b/main/_modules/torch/distributions/transforms.html
index c9ba44a805..51bcc4e1c7 100644
--- a/main/_modules/torch/distributions/transforms.html
+++ b/main/_modules/torch/distributions/transforms.html
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diff --git a/main/_modules/torch/distributions/uniform.html b/main/_modules/torch/distributions/uniform.html
index 313de7a4f2..bae01bb4e4 100644
--- a/main/_modules/torch/distributions/uniform.html
+++ b/main/_modules/torch/distributions/uniform.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/distributions/utils.html b/main/_modules/torch/distributions/utils.html
index 893c00dc1f..1a56427c2a 100644
--- a/main/_modules/torch/distributions/utils.html
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diff --git a/main/_modules/torch/distributions/von_mises.html b/main/_modules/torch/distributions/von_mises.html
index 4adee5ec33..5558c30d15 100644
--- a/main/_modules/torch/distributions/von_mises.html
+++ b/main/_modules/torch/distributions/von_mises.html
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diff --git a/main/_modules/torch/distributions/weibull.html b/main/_modules/torch/distributions/weibull.html
index ebd550de0e..9add48832e 100644
--- a/main/_modules/torch/distributions/weibull.html
+++ b/main/_modules/torch/distributions/weibull.html
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diff --git a/main/_modules/torch/distributions/wishart.html b/main/_modules/torch/distributions/wishart.html
index 293b9b4604..f5611fa49f 100644
--- a/main/_modules/torch/distributions/wishart.html
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diff --git a/main/_modules/torch/export.html b/main/_modules/torch/export.html
index 2a5c86f2e5..0b90db0de8 100644
--- a/main/_modules/torch/export.html
+++ b/main/_modules/torch/export.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/export/dynamic_shapes.html b/main/_modules/torch/export/dynamic_shapes.html
index afb1ddb09b..e940396f42 100644
--- a/main/_modules/torch/export/dynamic_shapes.html
+++ b/main/_modules/torch/export/dynamic_shapes.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/export/exported_program.html b/main/_modules/torch/export/exported_program.html
index 250e1669fc..e700912cf2 100644
--- a/main/_modules/torch/export/exported_program.html
+++ b/main/_modules/torch/export/exported_program.html
@@ -280,7 +280,7 @@
           

             
     

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@@ -983,38 +983,6 @@ 
Source code for torch.export.exported_program
# propagate names to higher order op subgraphs
     _name_hoo_subgraph_placeholders(gm)
 
-    # Run this pass before creating input/output specs, since size-related CSE/DCE might affect output signature.
-    # Overwrite output specs afterwards.
-    from torch._dynamo import config as _dynamo_config
-    from torch._export.passes._node_metadata_hook import (
-        _node_metadata_hook,
-        _set_node_metadata_hook,
-    )
-    from torch._functorch._aot_autograd.input_output_analysis import _graph_output_names
-
-    if not _dynamo_config.do_not_emit_runtime_asserts:
-        stack_trace = (
-            'File "torch/fx/passes/runtime_assert.py", line 24, '
-            "in insert_deferred_runtime_asserts"
-        )
-        shape_env = _get_shape_env(gm)
-        if shape_env is not None:
-            with _set_node_metadata_hook(
-                gm, functools.partial(_node_metadata_hook, stack_trace=stack_trace)
-            ):
-                insert_deferred_runtime_asserts(
-                    gm,
-                    shape_env,
-                    f"exported program: {first_call_function_nn_module_stack(gm.graph)}",
-                    export=True,
-                )
-
-    # update output specs
-    gm.recompile()
-    for i, name in enumerate(_graph_output_names(gm)):
-        if isinstance(new_outputs[i], torch.fx.Node):
-            new_outputs[i].name = name
-
     # To match the output target with correct input for input mutations
     # need to find the old to new placeholder map
     old_new_placeholder_map = {
@@ -1098,6 +1066,12 @@ 
Source code for torch.export.exported_program
_preserve_ops: Tuple[torch._ops.OpOverload],
     joint_loss_index: Optional[int],
 ):
+    from torch._dynamo import config as _dynamo_config
+    from torch._export.passes._node_metadata_hook import (
+        _node_metadata_hook,
+        _set_node_metadata_hook,
+    )
+
     from torch._export.passes.lift_constants_pass import (
         ConstantAttrMap,
         lift_constants_pass,
@@ -1126,6 +1100,23 @@ 
Source code for torch.export.exported_program
assert k not in ep.constants
         ep.constants[k] = v
 
+    if not _dynamo_config.do_not_emit_runtime_asserts:
+        stack_trace = (
+            'File "torch/fx/passes/runtime_assert.py", line 24, '
+            "in insert_deferred_runtime_asserts"
+        )
+        shape_env = _get_shape_env(gm)
+        if shape_env is not None:
+            with _set_node_metadata_hook(
+                gm, functools.partial(_node_metadata_hook, stack_trace=stack_trace)
+            ):
+                insert_deferred_runtime_asserts(
+                    gm,
+                    shape_env,
+                    f"exported program: {first_call_function_nn_module_stack(gm.graph)}",
+                    export=True,
+                )
+
     exported_program = ExportedProgram(
         root=gm,
         graph=gm.graph,
diff --git a/main/_modules/torch/export/graph_signature.html b/main/_modules/torch/export/graph_signature.html
index c6df1a6a0a..a83d4e6d8b 100644
--- a/main/_modules/torch/export/graph_signature.html
+++ b/main/_modules/torch/export/graph_signature.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/export/unflatten.html b/main/_modules/torch/export/unflatten.html
index ed92af8ba4..b8695ca198 100644
--- a/main/_modules/torch/export/unflatten.html
+++ b/main/_modules/torch/export/unflatten.html
@@ -280,7 +280,7 @@
           

             
     

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@@ -548,6 +548,7 @@ 
Source code for torch.export.unflatten
     TensorArgument,
 )
 from torch.fx._symbolic_trace import is_fx_tracing
+from torch.fx.experimental.proxy_tensor import py_sym_types
 from torch.utils._pytree import GetAttrKey, SequenceKey
 
 from ._remove_effect_tokens_pass import _remove_effect_tokens
@@ -1326,6 +1327,7 @@ 
Source code for torch.export.unflatten
         # To avoid this we copy these call_function nodes with sym_type results.
         # This should however only be done for sym_type nodes - call_function nodes on tensors
         # should not be deduplicated in the first place.
+        assert isinstance(x.meta["val"], py_sym_types)
         args = tuple(
             self.remap_input(_x) if isinstance(_x, torch.fx.Node) else _x
             for _x in x.args
diff --git a/main/_modules/torch/func.html b/main/_modules/torch/func.html
index b5eb767534..cbf5bab14d 100644
--- a/main/_modules/torch/func.html
+++ b/main/_modules/torch/func.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/functional.html b/main/_modules/torch/functional.html
index 7698603b8a..d9f698e72c 100644
--- a/main/_modules/torch/functional.html
+++ b/main/_modules/torch/functional.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/futures.html b/main/_modules/torch/futures.html
index bc0d75f137..f2988da0f2 100644
--- a/main/_modules/torch/futures.html
+++ b/main/_modules/torch/futures.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/fx/_symbolic_trace.html b/main/_modules/torch/fx/_symbolic_trace.html
index 092ccf2bb2..c9ed789de9 100644
--- a/main/_modules/torch/fx/_symbolic_trace.html
+++ b/main/_modules/torch/fx/_symbolic_trace.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/fx/experimental/symbolic_shapes.html b/main/_modules/torch/fx/experimental/symbolic_shapes.html
index 3f4daefcff..623ad65c8f 100644
--- a/main/_modules/torch/fx/experimental/symbolic_shapes.html
+++ b/main/_modules/torch/fx/experimental/symbolic_shapes.html
@@ -280,7 +280,7 @@
           

             
     

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+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/fx/graph.html b/main/_modules/torch/fx/graph.html
index 81eca81c08..25cc9e97e8 100644
--- a/main/_modules/torch/fx/graph.html
+++ b/main/_modules/torch/fx/graph.html
@@ -280,7 +280,7 @@
           

             
     

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@@ -747,8 +747,10 @@ 
Source code for torch.fx.graph
     torch.int64: 'i64',
     torch.bool: 'b8',
     torch.uint8: 'u8',
+    torch.uint16: 'u16',
     torch.uint32: 'u32',
     torch.uint64: 'u64',
+    torch.bits16: 'b16',
 }
 
 @compatibility(is_backward_compatible=True)
diff --git a/main/_modules/torch/fx/graph_module.html b/main/_modules/torch/fx/graph_module.html
index e7d939afde..3b7a04c861 100644
--- a/main/_modules/torch/fx/graph_module.html
+++ b/main/_modules/torch/fx/graph_module.html
@@ -280,7 +280,7 @@
           

             
     

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+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -1361,7 +1361,12 @@ 
Source code for torch.fx.graph_module
         submodule_code_list = [""]
         for submodule in self.children():
             if isinstance(submodule, GraphModule):
-                submodule_code_list.append(submodule.print_readable(print_output=False))
+                submodule_code_list.append(submodule.print_readable(
+                    print_output=False,
+                    include_stride=include_stride,
+                    include_device=include_device,
+                    colored=colored
+                ))
         submodule_code = "\n".join(submodule_code_list)
         submodule_code = _addindent(submodule_code, 4)
 
diff --git a/main/_modules/torch/fx/interpreter.html b/main/_modules/torch/fx/interpreter.html
index 7bfdb6c19a..0c06990170 100644
--- a/main/_modules/torch/fx/interpreter.html
+++ b/main/_modules/torch/fx/interpreter.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/fx/node.html b/main/_modules/torch/fx/node.html
index 075f18f06b..7fb7962c71 100644
--- a/main/_modules/torch/fx/node.html
+++ b/main/_modules/torch/fx/node.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/fx/proxy.html b/main/_modules/torch/fx/proxy.html
index a25614022a..929f04f4c8 100644
--- a/main/_modules/torch/fx/proxy.html
+++ b/main/_modules/torch/fx/proxy.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/fx/subgraph_rewriter.html b/main/_modules/torch/fx/subgraph_rewriter.html
index 0327a5d517..862ac01c40 100644
--- a/main/_modules/torch/fx/subgraph_rewriter.html
+++ b/main/_modules/torch/fx/subgraph_rewriter.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/hub.html b/main/_modules/torch/hub.html
index 99db3d6eca..6b895740ff 100644
--- a/main/_modules/torch/hub.html
+++ b/main/_modules/torch/hub.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/jit.html b/main/_modules/torch/jit.html
index ec65046fa0..947036338f 100644
--- a/main/_modules/torch/jit.html
+++ b/main/_modules/torch/jit.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/jit/_async.html b/main/_modules/torch/jit/_async.html
index 25b0780dfb..6b82a304bf 100644
--- a/main/_modules/torch/jit/_async.html
+++ b/main/_modules/torch/jit/_async.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/jit/_freeze.html b/main/_modules/torch/jit/_freeze.html
index 2eed0ce266..11b5c52651 100644
--- a/main/_modules/torch/jit/_freeze.html
+++ b/main/_modules/torch/jit/_freeze.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/jit/_fuser.html b/main/_modules/torch/jit/_fuser.html
index 98ff384347..64a62c6739 100644
--- a/main/_modules/torch/jit/_fuser.html
+++ b/main/_modules/torch/jit/_fuser.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/jit/_script.html b/main/_modules/torch/jit/_script.html
index d4105d1296..177762382c 100644
--- a/main/_modules/torch/jit/_script.html
+++ b/main/_modules/torch/jit/_script.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -545,7 +545,7 @@ 
Source code for torch.jit._script
 import torch
 import torch._jit_internal as _jit_internal
 from torch._classes import classes
-from torch._jit_internal import _qualified_name
+from torch._jit_internal import _get_model_id, _qualified_name
 from torch._utils_internal import log_torchscript_usage
 from torch.jit._builtins import _register_builtin
 from torch.jit._fuser import _graph_for, _script_method_graph_for
@@ -1948,21 +1948,22 @@ 
Source code for torch.jit._script
     """
     if not _enabled:
         return obj
-
-    global _TOPLEVEL
-    if _TOPLEVEL:
-        log_torchscript_usage("script")
-    prev = _TOPLEVEL
-    _TOPLEVEL = False
-
     try:
-        return _script_impl(
+        global _TOPLEVEL
+        prev = _TOPLEVEL
+        _TOPLEVEL = False
+        ret = _script_impl(
             obj=obj,
             optimize=optimize,
             _frames_up=_frames_up + 1,
             _rcb=_rcb,
             example_inputs=example_inputs,
         )
+
+        if prev:
+            log_torchscript_usage("script", model_id=_get_model_id(ret))
+
+        return ret
     finally:
         _TOPLEVEL = prev

 
diff --git a/main/_modules/torch/jit/_serialization.html b/main/_modules/torch/jit/_serialization.html
index c33e370c87..25fa1dc70a 100644
--- a/main/_modules/torch/jit/_serialization.html
+++ b/main/_modules/torch/jit/_serialization.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -539,6 +539,7 @@ 
Source code for torch.jit._serialization
 import os
 
 import torch
+from torch._jit_internal import _get_model_id
 from torch._utils_internal import log_torchscript_usage
 from torch.jit._recursive import wrap_cpp_module
 from torch.serialization import validate_cuda_device
@@ -603,7 +604,7 @@ 
Source code for torch.jit._serialization
         extra_files = {'foo.txt': b'bar'}
         torch.jit.save(m, 'scriptmodule.pt', _extra_files=extra_files)
     """
-    log_torchscript_usage("save")
+    log_torchscript_usage("save", model_id=_get_model_id(m))
     if _extra_files is None:
         _extra_files = {}
     if isinstance(f, (str, os.PathLike)):
@@ -674,7 +675,6 @@ 
Source code for torch.jit._serialization
         import os
         os.remove("scriptmodule.pt")
     """
-    log_torchscript_usage("load")
     if isinstance(f, (str, os.PathLike)):
         if not os.path.exists(f):  # type: ignore[type-var]
             raise ValueError(f"The provided filename {f} does not exist")  # type: ignore[str-bytes-safe]
@@ -694,7 +694,9 @@ 
Source code for torch.jit._serialization
         )  # type: ignore[call-arg]
 
     # TODO: Pretty sure this approach loses ConstSequential status and such
-    return wrap_cpp_module(cpp_module)

+    ret = wrap_cpp_module(cpp_module)
+    log_torchscript_usage("load", model_id=_get_model_id(ret))
+    return ret

 
 
 def validate_map_location(map_location=None):
diff --git a/main/_modules/torch/jit/_trace.html b/main/_modules/torch/jit/_trace.html
index 9e2395c22a..523b6c199b 100644
--- a/main/_modules/torch/jit/_trace.html
+++ b/main/_modules/torch/jit/_trace.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -550,6 +550,7 @@ 
Source code for torch.jit._trace
 
 import torch
 from torch._jit_internal import (
+    _get_model_id,
     _qualified_name,
     get_callable_argument_names,
     is_scripting,
@@ -1528,7 +1529,6 @@ 
Source code for torch.jit._trace
         log_torchscript_usage,
     )
 
-    log_torchscript_usage("trace")
     traced_func = _trace_impl(
         func,
         example_inputs,
@@ -1543,6 +1543,7 @@ 
Source code for torch.jit._trace
         example_kwarg_inputs,
         _store_inputs,
     )
+    log_torchscript_usage("trace", model_id=_get_model_id(traced_func))
 
     if check_if_torch_exportable():
         from torch._export.converter import TS2EPConverter
diff --git a/main/_modules/torch/library.html b/main/_modules/torch/library.html
index 7cee9d1f06..03fc676475 100644
--- a/main/_modules/torch/library.html
+++ b/main/_modules/torch/library.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -552,6 +552,7 @@ 
Source code for torch.library
     "fallthrough_kernel",
     "impl_abstract",
     "register_fake",
+    "register_torch_dispatch",
     "get_ctx",
     "custom_op",
 ]
@@ -1395,6 +1396,87 @@ 
Source code for torch.library
     lib.impl(opname, autograd_kernel, "Autograd", with_keyset=True)

 
 
+
[docs]def register_torch_dispatch(
+    op: _op_identifier,
+    torch_dispatch_class: Any,
+    func: Optional[Callable] = None,
+    /,
+    *,
+    lib: Optional[Library] = None,
+):
+    r"""Registers a torch_dispatch rule for the given operator and ``torch_dispatch_class``.
+
+    This allows for open registration to specify the behavior between the operator
+    and the ``torch_dispatch_class`` without needing to modify the ``torch_dispatch_class``
+    or the operator directly.
+
+    The ``torch_dispatch_class`` is either a Tensor subclass with ``__torch_dispatch__`` or a
+    TorchDispatchMode.
+
+    If it is a Tensor subclass, we expect ``func`` to have the following signature:
+    ``(cls, func: OpOverload, types: Tuple[type, ...], args, kwargs) -> Any``
+
+    If it is a TorchDispatchMode, we expect ``func`` to have the following signature:
+    ``(mode, func: OpOverload, types: Tuple[type, ...], args, kwargs) -> Any``
+
+    ``args`` and ``kwargs`` will have been normalized the same way they are
+    in ``__torch_dispatch__`` (see :ref:`torch-dispatch-calling-convention`).
+
+    Examples:
+
+        >>> import torch
+        >>>
+        >>> @torch.library.custom_op("mylib::foo", mutates_args={})
+        >>> def foo(x: torch.Tensor) -> torch.Tensor:
+        >>>     return x.clone()
+        >>>
+        >>> class MyMode(torch.utils._python_dispatch.TorchDispatchMode):
+        >>>     def __torch_dispatch__(self, func, types, args=(), kwargs=None):
+        >>>         return func(*args, **kwargs)
+        >>>
+        >>> @torch.library.register_torch_dispatch("mylib::foo", MyMode)
+        >>> def _(mode, func, types, args, kwargs):
+        >>>     x, = args
+        >>>     return x + 1
+        >>>
+        >>> x = torch.randn(3)
+        >>> y = foo(x)
+        >>> assert torch.allclose(y, x)
+        >>>
+        >>> with MyMode():
+        >>>     y = foo(x)
+        >>> assert torch.allclose(y, x + 1)
+
+    """
+    if not isinstance(
+        op, (str, torch._ops.OpOverload, torch._library.custom_ops.CustomOpDef)
+    ):
+        raise ValueError(
+            "register_torch_dispatch(op): got unexpected type for op: {type(op)}"
+        )
+    if isinstance(op, torch._ops.OpOverload):
+        op = op._name
+    opdef = _maybe_get_opdef(op)
+    if opdef is not None:
+        return opdef.register_torch_dispatch(torch_dispatch_class, func)
+    assert isinstance(op, str)
+
+    def register(func):
+        namespace, op_name = torch._library.utils.parse_namespace(op)
+        if lib is None:
+            use_lib = Library(namespace, "FRAGMENT")
+            _keep_alive.append(use_lib)
+        else:
+            use_lib = lib
+        use_lib._register_torch_dispatch_rule(op_name, torch_dispatch_class, func)
+        return func
+
+    if func is None:
+        return register
+    else:
+        return register(func)

+
+
 # If the op was defined in C++, then we want to make sure there was an
 # m.set_python_module(module, ...) call and that the module is the
 # same as the module that called torch.library.register_fake.
diff --git a/main/_modules/torch/monitor.html b/main/_modules/torch/monitor.html
index f1aade08c6..56a2ee75e3 100644
--- a/main/_modules/torch/monitor.html
+++ b/main/_modules/torch/monitor.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/mps.html b/main/_modules/torch/mps.html
index 3591809400..0b59578865 100644
--- a/main/_modules/torch/mps.html
+++ b/main/_modules/torch/mps.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/mps/event.html b/main/_modules/torch/mps/event.html
index b79d6187e2..f044309176 100644
--- a/main/_modules/torch/mps/event.html
+++ b/main/_modules/torch/mps/event.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/mps/profiler.html b/main/_modules/torch/mps/profiler.html
index 34c1b125af..4e415bafe1 100644
--- a/main/_modules/torch/mps/profiler.html
+++ b/main/_modules/torch/mps/profiler.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/mtia.html b/main/_modules/torch/mtia.html
index 69520f7ad7..691c0f0dc5 100644
--- a/main/_modules/torch/mtia.html
+++ b/main/_modules/torch/mtia.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/multiprocessing.html b/main/_modules/torch/multiprocessing.html
index f657cc0c40..52f5b0193f 100644
--- a/main/_modules/torch/multiprocessing.html
+++ b/main/_modules/torch/multiprocessing.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/multiprocessing/spawn.html b/main/_modules/torch/multiprocessing/spawn.html
index 6874535a58..a363a64c0e 100644
--- a/main/_modules/torch/multiprocessing/spawn.html
+++ b/main/_modules/torch/multiprocessing/spawn.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nested.html b/main/_modules/torch/nested.html
index 54dc70f8c1..cb506a1659 100644
--- a/main/_modules/torch/nested.html
+++ b/main/_modules/torch/nested.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/attention.html b/main/_modules/torch/nn/attention.html
index 7fb4cc2ccd..36f57841cc 100644
--- a/main/_modules/torch/nn/attention.html
+++ b/main/_modules/torch/nn/attention.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/attention/bias.html b/main/_modules/torch/nn/attention/bias.html
index 0acfb2b773..d171c0316e 100644
--- a/main/_modules/torch/nn/attention/bias.html
+++ b/main/_modules/torch/nn/attention/bias.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/functional.html b/main/_modules/torch/nn/functional.html
index 44efca43a4..8840d57467 100644
--- a/main/_modules/torch/nn/functional.html
+++ b/main/_modules/torch/nn/functional.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/init.html b/main/_modules/torch/nn/init.html
index 5c3ade62f8..6db29c98fc 100644
--- a/main/_modules/torch/nn/init.html
+++ b/main/_modules/torch/nn/init.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/modules/activation.html b/main/_modules/torch/nn/modules/activation.html
index 110495741d..f1390c1a03 100644
--- a/main/_modules/torch/nn/modules/activation.html
+++ b/main/_modules/torch/nn/modules/activation.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/modules/adaptive.html b/main/_modules/torch/nn/modules/adaptive.html
index ace6d8b177..aee3dd121c 100644
--- a/main/_modules/torch/nn/modules/adaptive.html
+++ b/main/_modules/torch/nn/modules/adaptive.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/modules/batchnorm.html b/main/_modules/torch/nn/modules/batchnorm.html
index ddc09fc623..d1f5c534b9 100644
--- a/main/_modules/torch/nn/modules/batchnorm.html
+++ b/main/_modules/torch/nn/modules/batchnorm.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
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diff --git a/main/_modules/torch/nn/modules/channelshuffle.html b/main/_modules/torch/nn/modules/channelshuffle.html
index 359a139b1b..4d7521963b 100644
--- a/main/_modules/torch/nn/modules/channelshuffle.html
+++ b/main/_modules/torch/nn/modules/channelshuffle.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/modules/container.html b/main/_modules/torch/nn/modules/container.html
index 7d106cf884..3b58f27036 100644
--- a/main/_modules/torch/nn/modules/container.html
+++ b/main/_modules/torch/nn/modules/container.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/modules/conv.html b/main/_modules/torch/nn/modules/conv.html
index e9d00dad44..62af657d6a 100644
--- a/main/_modules/torch/nn/modules/conv.html
+++ b/main/_modules/torch/nn/modules/conv.html
@@ -280,7 +280,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/modules/distance.html b/main/_modules/torch/nn/modules/distance.html
index d13200fe7b..3bff459ec2 100644
--- a/main/_modules/torch/nn/modules/distance.html
+++ b/main/_modules/torch/nn/modules/distance.html
@@ -280,7 +280,7 @@
           

             
     

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+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/nn/modules/dropout.html b/main/_modules/torch/nn/modules/dropout.html
index 93fa7d67da..4f1a15f965 100644
--- a/main/_modules/torch/nn/modules/dropout.html
+++ b/main/_modules/torch/nn/modules/dropout.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/nn/modules/flatten.html b/main/_modules/torch/nn/modules/flatten.html
index b7f53b81de..4eac83a3f4 100644
--- a/main/_modules/torch/nn/modules/flatten.html
+++ b/main/_modules/torch/nn/modules/flatten.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/nn/modules/fold.html b/main/_modules/torch/nn/modules/fold.html
index d851fea0d6..45934b25ad 100644
--- a/main/_modules/torch/nn/modules/fold.html
+++ b/main/_modules/torch/nn/modules/fold.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/nn/modules/instancenorm.html b/main/_modules/torch/nn/modules/instancenorm.html
index 98401c98e1..c43f40f73f 100644
--- a/main/_modules/torch/nn/modules/instancenorm.html
+++ b/main/_modules/torch/nn/modules/instancenorm.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/nn/modules/lazy.html b/main/_modules/torch/nn/modules/lazy.html
index 5c94176f37..765e43e3a4 100644
--- a/main/_modules/torch/nn/modules/lazy.html
+++ b/main/_modules/torch/nn/modules/lazy.html
@@ -280,7 +280,7 @@
           

             
     

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index 5a5aa38e16..bc1fbbdd7c 100644
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index f432787d62..f3f2741ae4 100644
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index e5cda96934..e4d9d580e2 100644
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index ac79d55864..03b7962e42 100644
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index 9028093aaf..e03cd1236f 100644
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index 2717430069..5225629309 100644
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index 5848a5de90..759b3b880e 100644
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index ef233cc36b..5936edc7ab 100644
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index e312728a5b..be7cc899a7 100644
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index 2d0b7eec66..6a0beab6e4 100644
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index 639b8c8da5..bbcf464a5d 100644
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index 5726e10086..180e635952 100644
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index 0b98716cc8..2318cc0aff 100644
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index c121745ab7..56ad3f82a4 100644
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index 80080e383b..5752dfe4e7 100644
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index aacfb41252..2e6c09b022 100644
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index 504daffbc0..ad9d61ba49 100644
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index 1e9f16706b..ccf08eba05 100644
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index 0ad7024ea6..be84264dd1 100644
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diff --git a/main/_modules/torch/onnx.html b/main/_modules/torch/onnx.html
index 9b816f699f..f9430c22c8 100644
--- a/main/_modules/torch/onnx.html
+++ b/main/_modules/torch/onnx.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/onnx/_internal/exporter.html b/main/_modules/torch/onnx/_internal/exporter.html
index 2f71c7364b..84461c47a2 100644
--- a/main/_modules/torch/onnx/_internal/exporter.html
+++ b/main/_modules/torch/onnx/_internal/exporter.html
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@@ -2028,15 +2028,12 @@ 
Source code for torch.onnx._internal.exporter
_assert_dependencies(resolved_export_options)
 
     try:
-        from torch._dynamo import config as _dynamo_config
-
-        with _dynamo_config.patch(do_not_emit_runtime_asserts=True):
-            return Exporter(
-                options=resolved_export_options,
-                model=model,
-                model_args=model_args,
-                model_kwargs=model_kwargs,
-            ).export()
+        return Exporter(
+            options=resolved_export_options,
+            model=model,
+            model_args=model_args,
+            model_kwargs=model_kwargs,
+        ).export()
     except Exception as e:
         sarif_report_path = _DEFAULT_FAILED_EXPORT_SARIF_LOG_PATH
         resolved_export_options.diagnostic_context.dump(sarif_report_path)
diff --git a/main/_modules/torch/onnx/_type_utils.html b/main/_modules/torch/onnx/_type_utils.html
index 3d96b2349f..993f3208c9 100644
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diff --git a/main/_modules/torch/onnx/utils.html b/main/_modules/torch/onnx/utils.html
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index 80574ff449..5f64156e5b 100644
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index 486f508e2e..8b21094c16 100644
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index fefe593934..ed1551f5cd 100644
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diff --git a/main/_modules/torch/optim/asgd.html b/main/_modules/torch/optim/asgd.html
index c8b492fcb2..a8446080d7 100644
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diff --git a/main/_modules/torch/optim/lbfgs.html b/main/_modules/torch/optim/lbfgs.html
index 785b570865..8d43efba7b 100644
--- a/main/_modules/torch/optim/lbfgs.html
+++ b/main/_modules/torch/optim/lbfgs.html
@@ -280,7 +280,7 @@
           

             
     

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+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/_modules/torch/optim/lr_scheduler.html b/main/_modules/torch/optim/lr_scheduler.html
index e0b13eda52..56ed470c5a 100644
--- a/main/_modules/torch/optim/lr_scheduler.html
+++ b/main/_modules/torch/optim/lr_scheduler.html
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@@ -2464,7 +2464,7 @@ 
Source code for torch.optim.lr_scheduler
     Example:
         >>> # xdoctest: +SKIP
         >>> data_loader = torch.utils.data.DataLoader(...)
-        >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
+        >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9)
         >>> scheduler = torch.optim.lr_scheduler.OneCycleLR(optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10)
         >>> for epoch in range(10):
         >>>     for batch in data_loader:
diff --git a/main/_modules/torch/optim/nadam.html b/main/_modules/torch/optim/nadam.html
index 580c9c57d4..b12952ed4a 100644
--- a/main/_modules/torch/optim/nadam.html
+++ b/main/_modules/torch/optim/nadam.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_modules/torch/optim/optimizer.html b/main/_modules/torch/optim/optimizer.html
index 85ed7e07f9..73eded70fb 100644
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diff --git a/main/_modules/torch/optim/radam.html b/main/_modules/torch/optim/radam.html
index 760cd019dc..42ccbd0e4a 100644
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diff --git a/main/_modules/torch/optim/rmsprop.html b/main/_modules/torch/optim/rmsprop.html
index a022b57cee..03c17709ca 100644
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diff --git a/main/_modules/torch/optim/rprop.html b/main/_modules/torch/optim/rprop.html
index 45f24ff882..59367211cf 100644
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diff --git a/main/_modules/torch/optim/sgd.html b/main/_modules/torch/optim/sgd.html
index 96356757f7..50d806f4ed 100644
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diff --git a/main/_modules/torch/optim/sparse_adam.html b/main/_modules/torch/optim/sparse_adam.html
index 22ba4d1201..64c414d51e 100644
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diff --git a/main/_modules/torch/overrides.html b/main/_modules/torch/overrides.html
index b521539fa7..e9173ea359 100644
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index 611c843e3c..f6efd22956 100644
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index 12fed041b3..fd03d5da5d 100644
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index 9f74d82adb..702ed4d28d 100644
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index cc74956d3d..78b2a8d6f0 100644
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diff --git a/main/_modules/torch/utils.html b/main/_modules/torch/utils.html
index 2d2187349e..48f9e27742 100644
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index c24fb9112d..c7cd5808ca 100644
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index 028238b61e..4341fc08ee 100644
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index 87f6313c54..360d292c85 100644
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diff --git a/main/_modules/torch/utils/benchmark/utils/timer.html b/main/_modules/torch/utils/benchmark/utils/timer.html
index d9241201a1..ca7dbc4e9e 100644
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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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index e551e8bd1f..b9e033c90d 100644
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diff --git a/main/_modules/torch/utils/cpp_backtrace.html b/main/_modules/torch/utils/cpp_backtrace.html
index d57aabfcad..1bbb7ba5a5 100644
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diff --git a/main/_modules/torch/utils/cpp_extension.html b/main/_modules/torch/utils/cpp_extension.html
index 7240223c38..38ff37b4c0 100644
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diff --git a/main/_modules/torch/utils/data/_utils/collate.html b/main/_modules/torch/utils/data/_utils/collate.html
index 21b5981558..ca61efe3ef 100644
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diff --git a/main/_modules/torch/utils/data/_utils/worker.html b/main/_modules/torch/utils/data/_utils/worker.html
index 1dfc8d439d..ec513fbaa7 100644
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diff --git a/main/_modules/torch/utils/data/dataloader.html b/main/_modules/torch/utils/data/dataloader.html
index 10ff807da6..6d97e0dfc9 100644
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diff --git a/main/_modules/torch/utils/data/dataset.html b/main/_modules/torch/utils/data/dataset.html
index 6d6917f6fb..fcfaf17f86 100644
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diff --git a/main/_modules/torch/utils/data/distributed.html b/main/_modules/torch/utils/data/distributed.html
index 33c9b6352d..618ba72ff6 100644
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diff --git a/main/_modules/torch/utils/data/sampler.html b/main/_modules/torch/utils/data/sampler.html
index 4d937c5d24..ecd61a3b47 100644
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diff --git a/main/_modules/torch/utils/dlpack.html b/main/_modules/torch/utils/dlpack.html
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diff --git a/main/_modules/torch/utils/mobile_optimizer.html b/main/_modules/torch/utils/mobile_optimizer.html
index 194d6c5894..93b5d3c214 100644
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diff --git a/main/_modules/torch/utils/module_tracker.html b/main/_modules/torch/utils/module_tracker.html
index 473b677d47..994263d84d 100644
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diff --git a/main/_modules/torch/utils/tensorboard/writer.html b/main/_modules/torch/utils/tensorboard/writer.html
index 910aa7f2ff..1e6ff4c6ac 100644
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diff --git a/main/_modules/torch/xpu.html b/main/_modules/torch/xpu.html
index b5872aa5d6..52f3656d9d 100644
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diff --git a/main/_modules/torch/xpu/random.html b/main/_modules/torch/xpu/random.html
index 6cf853299e..fed6b8fab1 100644
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diff --git a/main/_modules/torch/xpu/streams.html b/main/_modules/torch/xpu/streams.html
index b50c0f7716..c7b661fe7b 100644
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+++ b/main/_modules/torch/xpu/streams.html
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diff --git a/main/_modules/typing.html b/main/_modules/typing.html
index 361a5cf4ec..94536ec696 100644
--- a/main/_modules/typing.html
+++ b/main/_modules/typing.html
@@ -280,7 +280,7 @@
           

             
     

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diff --git a/main/_sources/generated/exportdb/index.rst.txt b/main/_sources/generated/exportdb/index.rst.txt
index 8cd8463406..aef9bb4a77 100644
--- a/main/_sources/generated/exportdb/index.rst.txt
+++ b/main/_sources/generated/exportdb/index.rst.txt
@@ -290,13 +290,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             cos: "f32[3]" = torch.ops.aten.cos.default(x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    cos: "f32[3]" = torch.ops.aten.cos.default(x);  x = None
                     return (cos,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             sin: "f32[3]" = torch.ops.aten.sin.default(x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    sin: "f32[3]" = torch.ops.aten.sin.default(x);  x = None
                     return (sin,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -377,13 +379,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             add: "f32[3]" = torch.ops.aten.add.Tensor(x, x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    add: "f32[3]" = torch.ops.aten.add.Tensor(x, x);  x = None
                     return (add,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             sub: "f32[3]" = torch.ops.aten.sub.Tensor(x, x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    sub: "f32[3]" = torch.ops.aten.sub.Tensor(x, x);  x = None
                     return (sub,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -489,15 +493,17 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
-                             add_1: "f32[6]" = torch.ops.aten.add.Tensor(x, add);  x = add = None
-                    add_2: "f32[6]" = torch.ops.aten.add.Tensor(add_1, detach);  add_1 = detach = None
+                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
+                     # 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)
+                    add_1: "f32[6]" = torch.ops.aten.add.Tensor(x, add);  x = add = None
+                    add_2: "f32[6]" = torch.ops.aten.add.Tensor(add_1, detach);  add_1 = detach = None
                     return (add_2,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
-                             sub: "f32[6]" = torch.ops.aten.sub.Tensor(x, add);  x = add = None
-                    sub_1: "f32[6]" = torch.ops.aten.sub.Tensor(sub, detach);  sub = detach = None
+                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
+                     # 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)
+                    sub: "f32[6]" = torch.ops.aten.sub.Tensor(x, add);  x = add = None
+                    sub_1: "f32[6]" = torch.ops.aten.sub.Tensor(sub, detach);  sub = detach = None
                     return (sub_1,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='c_lifted_tensor_0'), target='lifted_tensor_0', persistent=None), InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -559,13 +565,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[3, 2]"):
-                             mul: "f32[3, 2]" = torch.ops.aten.mul.Tensor(x, 2);  x = None
+                def forward(self, x: "f32[3, 2]"):
+                     # 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)
+                    mul: "f32[3, 2]" = torch.ops.aten.mul.Tensor(x, 2);  x = None
                     return (mul,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[3, 2]"):
-                             sub: "f32[3, 2]" = torch.ops.aten.sub.Tensor(x, 2);  x = None
+                def forward(self, x: "f32[3, 2]"):
+                     # 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)
+                    sub: "f32[3, 2]" = torch.ops.aten.sub.Tensor(x, 2);  x = None
                     return (sub,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='pred'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -633,11 +641,9 @@ 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)
-                gt: "Sym(s0 > 2)" = sym_size_int_1 > 2;  sym_size_int_1 = None
+                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
                 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
@@ -645,13 +651,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
-                             add: "f32[s0, 2]" = torch.ops.aten.add.Tensor(x, y);  x = y = None
+                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
+                     # 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)
+                    add: "f32[s0, 2]" = torch.ops.aten.add.Tensor(x, y);  x = y = None
                     return (add,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
-                             sub: "f32[s0, 2]" = torch.ops.aten.sub.Tensor(x, y);  x = y = None
+                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
+                     # 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)
+                    sub: "f32[s0, 2]" = torch.ops.aten.sub.Tensor(x, y);  x = y = None
                     return (sub,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='y'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -716,13 +724,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[6, 4, 3]"):
-                             cos: "f32[6, 4, 3]" = torch.ops.aten.cos.default(x);  x = None
+                def forward(self, x: "f32[6, 4, 3]"):
+                     # 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)
+                    cos: "f32[6, 4, 3]" = torch.ops.aten.cos.default(x);  x = None
                     return (cos,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[6, 4, 3]"):
-                             sin: "f32[6, 4, 3]" = torch.ops.aten.sin.default(x);  x = None
+                def forward(self, x: "f32[6, 4, 3]"):
+                     # 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)
+                    sin: "f32[6, 4, 3]" = torch.ops.aten.sin.default(x);  x = None
                     return (sin,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -784,10 +794,13 @@ Result:
                 
                  # 
                 sym_constrain_range_for_size_default = torch.ops.aten.sym_constrain_range_for_size.default(item)
-                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
+                
+                # 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
                 
                  # 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
@@ -853,11 +866,12 @@ 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
                 
-                 # 
-                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
+                # 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
                 
                  # 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
@@ -1134,7 +1148,7 @@ dynamic_shape_map
 
 .. note::
 
-    Tags: :doc:`torch.dynamic-shape `, :doc:`torch.map `
+    Tags: :doc:`torch.map `, :doc:`torch.dynamic-shape `
 
     Support Level: SUPPORTED
 
@@ -1179,8 +1193,9 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, xs: "f32[2]", y: "f32[2]"):
-                             add: "f32[2]" = torch.ops.aten.add.Tensor(xs, y);  xs = y = None
+                def forward(self, xs: "f32[2]", y: "f32[2]"):
+                     # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/dynamic_shape_map.py:15 in forward, code: return map(body, xs, y)
+                    add: "f32[2]" = torch.ops.aten.add.Tensor(xs, y);  xs = y = None
                     return (add,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='xs'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='y'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -1370,7 +1385,7 @@ list_contains
 
 .. note::
 
-    Tags: :doc:`torch.dynamic-shape `, :doc:`python.assert `, :doc:`python.data-structure `
+    Tags: :doc:`python.data-structure `, :doc:`python.assert `, :doc:`torch.dynamic-shape `
 
     Support Level: SUPPORTED
 
@@ -1688,11 +1703,9 @@ 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
-                add: "Sym(s0 + 1)" = sym_size_int_1 + 1;  sym_size_int_1 = None
+                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
                 return (add,)
                 
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=SymIntArgument(name='add'), target=None)])
@@ -2211,6 +2224,6 @@ Result:
 
 .. code-block::
 
-    Unsupported: torch.* op returned non-Tensor int call_function 
+    Unsupported: torch.* op returned non-Tensor int call_function 
 
 
diff --git a/main/_sources/generated/exportdb/python.assert.rst.txt b/main/_sources/generated/exportdb/python.assert.rst.txt
index 1eb99aefc8..d2e7276097 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:`torch.dynamic-shape `, :doc:`python.assert `, :doc:`python.data-structure `
+    Tags: :doc:`python.data-structure `, :doc:`python.assert `, :doc:`torch.dynamic-shape `
 
     Support Level: SUPPORTED
 
diff --git a/main/_sources/generated/exportdb/python.closure.rst.txt b/main/_sources/generated/exportdb/python.closure.rst.txt
index 801570f84f..6908efc83b 100644
--- a/main/_sources/generated/exportdb/python.closure.rst.txt
+++ b/main/_sources/generated/exportdb/python.closure.rst.txt
@@ -54,13 +54,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[3, 2]"):
-                             mul: "f32[3, 2]" = torch.ops.aten.mul.Tensor(x, 2);  x = None
+                def forward(self, x: "f32[3, 2]"):
+                     # 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)
+                    mul: "f32[3, 2]" = torch.ops.aten.mul.Tensor(x, 2);  x = None
                     return (mul,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[3, 2]"):
-                             sub: "f32[3, 2]" = torch.ops.aten.sub.Tensor(x, 2);  x = None
+                def forward(self, x: "f32[3, 2]"):
+                     # 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)
+                    sub: "f32[3, 2]" = torch.ops.aten.sub.Tensor(x, 2);  x = None
                     return (sub,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='pred'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
diff --git a/main/_sources/generated/exportdb/python.data-structure.rst.txt b/main/_sources/generated/exportdb/python.data-structure.rst.txt
index 8c4595e121..41ba2070bd 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:`torch.dynamic-shape `, :doc:`python.assert `, :doc:`python.data-structure `
+    Tags: :doc:`python.data-structure `, :doc:`python.assert `, :doc:`torch.dynamic-shape `
 
     Support Level: SUPPORTED
 
diff --git a/main/_sources/generated/exportdb/torch.cond.rst.txt b/main/_sources/generated/exportdb/torch.cond.rst.txt
index 2604661b06..c69b928fb4 100644
--- a/main/_sources/generated/exportdb/torch.cond.rst.txt
+++ b/main/_sources/generated/exportdb/torch.cond.rst.txt
@@ -76,13 +76,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             cos: "f32[3]" = torch.ops.aten.cos.default(x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    cos: "f32[3]" = torch.ops.aten.cos.default(x);  x = None
                     return (cos,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             sin: "f32[3]" = torch.ops.aten.sin.default(x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    sin: "f32[3]" = torch.ops.aten.sin.default(x);  x = None
                     return (sin,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -163,13 +165,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             add: "f32[3]" = torch.ops.aten.add.Tensor(x, x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    add: "f32[3]" = torch.ops.aten.add.Tensor(x, x);  x = None
                     return (add,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             sub: "f32[3]" = torch.ops.aten.sub.Tensor(x, x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    sub: "f32[3]" = torch.ops.aten.sub.Tensor(x, x);  x = None
                     return (sub,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -275,15 +279,17 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
-                             add_1: "f32[6]" = torch.ops.aten.add.Tensor(x, add);  x = add = None
-                    add_2: "f32[6]" = torch.ops.aten.add.Tensor(add_1, detach);  add_1 = detach = None
+                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
+                     # 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)
+                    add_1: "f32[6]" = torch.ops.aten.add.Tensor(x, add);  x = add = None
+                    add_2: "f32[6]" = torch.ops.aten.add.Tensor(add_1, detach);  add_1 = detach = None
                     return (add_2,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
-                             sub: "f32[6]" = torch.ops.aten.sub.Tensor(x, add);  x = add = None
-                    sub_1: "f32[6]" = torch.ops.aten.sub.Tensor(sub, detach);  sub = detach = None
+                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
+                     # 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)
+                    sub: "f32[6]" = torch.ops.aten.sub.Tensor(x, add);  x = add = None
+                    sub_1: "f32[6]" = torch.ops.aten.sub.Tensor(sub, detach);  sub = detach = None
                     return (sub_1,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='c_lifted_tensor_0'), target='lifted_tensor_0', persistent=None), InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -345,13 +351,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[3, 2]"):
-                             mul: "f32[3, 2]" = torch.ops.aten.mul.Tensor(x, 2);  x = None
+                def forward(self, x: "f32[3, 2]"):
+                     # 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)
+                    mul: "f32[3, 2]" = torch.ops.aten.mul.Tensor(x, 2);  x = None
                     return (mul,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[3, 2]"):
-                             sub: "f32[3, 2]" = torch.ops.aten.sub.Tensor(x, 2);  x = None
+                def forward(self, x: "f32[3, 2]"):
+                     # 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)
+                    sub: "f32[3, 2]" = torch.ops.aten.sub.Tensor(x, 2);  x = None
                     return (sub,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='pred'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -419,11 +427,9 @@ 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)
-                gt: "Sym(s0 > 2)" = sym_size_int_1 > 2;  sym_size_int_1 = None
+                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
                 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
@@ -431,13 +437,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
-                             add: "f32[s0, 2]" = torch.ops.aten.add.Tensor(x, y);  x = y = None
+                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
+                     # 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)
+                    add: "f32[s0, 2]" = torch.ops.aten.add.Tensor(x, y);  x = y = None
                     return (add,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
-                             sub: "f32[s0, 2]" = torch.ops.aten.sub.Tensor(x, y);  x = y = None
+                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
+                     # 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)
+                    sub: "f32[s0, 2]" = torch.ops.aten.sub.Tensor(x, y);  x = y = None
                     return (sub,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='y'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -502,13 +510,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[6, 4, 3]"):
-                             cos: "f32[6, 4, 3]" = torch.ops.aten.cos.default(x);  x = None
+                def forward(self, x: "f32[6, 4, 3]"):
+                     # 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)
+                    cos: "f32[6, 4, 3]" = torch.ops.aten.cos.default(x);  x = None
                     return (cos,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[6, 4, 3]"):
-                             sin: "f32[6, 4, 3]" = torch.ops.aten.sin.default(x);  x = None
+                def forward(self, x: "f32[6, 4, 3]"):
+                     # 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)
+                    sin: "f32[6, 4, 3]" = torch.ops.aten.sin.default(x);  x = None
                     return (sin,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
diff --git a/main/_sources/generated/exportdb/torch.dynamic-shape.rst.txt b/main/_sources/generated/exportdb/torch.dynamic-shape.rst.txt
index 72142b3063..fb0984181d 100644
--- a/main/_sources/generated/exportdb/torch.dynamic-shape.rst.txt
+++ b/main/_sources/generated/exportdb/torch.dynamic-shape.rst.txt
@@ -76,13 +76,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             cos: "f32[3]" = torch.ops.aten.cos.default(x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    cos: "f32[3]" = torch.ops.aten.cos.default(x);  x = None
                     return (cos,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             sin: "f32[3]" = torch.ops.aten.sin.default(x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    sin: "f32[3]" = torch.ops.aten.sin.default(x);  x = None
                     return (sin,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -163,13 +165,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             add: "f32[3]" = torch.ops.aten.add.Tensor(x, x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    add: "f32[3]" = torch.ops.aten.add.Tensor(x, x);  x = None
                     return (add,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[3]"):
-                             sub: "f32[3]" = torch.ops.aten.sub.Tensor(x, x);  x = None
+                def forward(self, x: "f32[3]"):
+                     # 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)
+                    sub: "f32[3]" = torch.ops.aten.sub.Tensor(x, x);  x = None
                     return (sub,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -275,15 +279,17 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
-                             add_1: "f32[6]" = torch.ops.aten.add.Tensor(x, add);  x = add = None
-                    add_2: "f32[6]" = torch.ops.aten.add.Tensor(add_1, detach);  add_1 = detach = None
+                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
+                     # 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)
+                    add_1: "f32[6]" = torch.ops.aten.add.Tensor(x, add);  x = add = None
+                    add_2: "f32[6]" = torch.ops.aten.add.Tensor(add_1, detach);  add_1 = detach = None
                     return (add_2,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
-                             sub: "f32[6]" = torch.ops.aten.sub.Tensor(x, add);  x = add = None
-                    sub_1: "f32[6]" = torch.ops.aten.sub.Tensor(sub, detach);  sub = detach = None
+                def forward(self, x: "f32[6]", add: "f32[6]", detach: "f32[]"):
+                     # 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)
+                    sub: "f32[6]" = torch.ops.aten.sub.Tensor(x, add);  x = add = None
+                    sub_1: "f32[6]" = torch.ops.aten.sub.Tensor(sub, detach);  sub = detach = None
                     return (sub_1,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='c_lifted_tensor_0'), target='lifted_tensor_0', persistent=None), InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -351,11 +357,9 @@ 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)
-                gt: "Sym(s0 > 2)" = sym_size_int_1 > 2;  sym_size_int_1 = None
+                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
                 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
@@ -363,13 +367,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
-                             add: "f32[s0, 2]" = torch.ops.aten.add.Tensor(x, y);  x = y = None
+                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
+                     # 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)
+                    add: "f32[s0, 2]" = torch.ops.aten.add.Tensor(x, y);  x = y = None
                     return (add,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
-                             sub: "f32[s0, 2]" = torch.ops.aten.sub.Tensor(x, y);  x = y = None
+                def forward(self, x: "f32[s0, 2]", y: "f32[2]"):
+                     # 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)
+                    sub: "f32[s0, 2]" = torch.ops.aten.sub.Tensor(x, y);  x = y = None
                     return (sub,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='y'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -434,13 +440,15 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, x: "f32[6, 4, 3]"):
-                             cos: "f32[6, 4, 3]" = torch.ops.aten.cos.default(x);  x = None
+                def forward(self, x: "f32[6, 4, 3]"):
+                     # 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)
+                    cos: "f32[6, 4, 3]" = torch.ops.aten.cos.default(x);  x = None
                     return (cos,)
                     
             class (torch.nn.Module):
-                def forward(self, x: "f32[6, 4, 3]"):
-                             sin: "f32[6, 4, 3]" = torch.ops.aten.sin.default(x);  x = None
+                def forward(self, x: "f32[6, 4, 3]"):
+                     # 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)
+                    sin: "f32[6, 4, 3]" = torch.ops.aten.sin.default(x);  x = None
                     return (sin,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -553,7 +561,7 @@ dynamic_shape_map
 
 .. note::
 
-    Tags: :doc:`torch.dynamic-shape `, :doc:`torch.map `
+    Tags: :doc:`torch.map `, :doc:`torch.dynamic-shape `
 
     Support Level: SUPPORTED
 
@@ -598,8 +606,9 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, xs: "f32[2]", y: "f32[2]"):
-                             add: "f32[2]" = torch.ops.aten.add.Tensor(xs, y);  xs = y = None
+                def forward(self, xs: "f32[2]", y: "f32[2]"):
+                     # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/dynamic_shape_map.py:15 in forward, code: return map(body, xs, y)
+                    add: "f32[2]" = torch.ops.aten.add.Tensor(xs, y);  xs = y = None
                     return (add,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='xs'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='y'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
@@ -759,7 +768,7 @@ list_contains
 
 .. note::
 
-    Tags: :doc:`torch.dynamic-shape `, :doc:`python.assert `, :doc:`python.data-structure `
+    Tags: :doc:`python.data-structure `, :doc:`python.assert `, :doc:`torch.dynamic-shape `
 
     Support Level: SUPPORTED
 
@@ -851,11 +860,9 @@ 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
-                add: "Sym(s0 + 1)" = sym_size_int_1 + 1;  sym_size_int_1 = None
+                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
                 return (add,)
                 
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='x'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, 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 9aace0491a..f6ba186e56 100644
--- a/main/_sources/generated/exportdb/torch.dynamic-value.rst.txt
+++ b/main/_sources/generated/exportdb/torch.dynamic-value.rst.txt
@@ -54,10 +54,13 @@ Result:
                 
                  # 
                 sym_constrain_range_for_size_default = torch.ops.aten.sym_constrain_range_for_size.default(item)
-                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
+                
+                # 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
                 
                  # 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
@@ -123,11 +126,12 @@ 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
                 
-                 # 
-                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
+                # 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
                 
                  # 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 df762a4ff9..c1e93bc724 100644
--- a/main/_sources/generated/exportdb/torch.escape-hatch.rst.txt
+++ b/main/_sources/generated/exportdb/torch.escape-hatch.rst.txt
@@ -107,10 +107,13 @@ Result:
                 
                  # 
                 sym_constrain_range_for_size_default = torch.ops.aten.sym_constrain_range_for_size.default(item)
-                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
+                
+                # 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
                 
                  # 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
@@ -176,11 +179,12 @@ 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
                 
-                 # 
-                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
+                # 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
                 
                  # 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 6a13593e81..c891e52cd4 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.dynamic-shape `, :doc:`torch.map `
+    Tags: :doc:`torch.map `, :doc:`torch.dynamic-shape `
 
     Support Level: SUPPORTED
 
@@ -50,8 +50,9 @@ Result:
                 return (getitem,)
                 
             class (torch.nn.Module):
-                def forward(self, xs: "f32[2]", y: "f32[2]"):
-                             add: "f32[2]" = torch.ops.aten.add.Tensor(xs, y);  xs = y = None
+                def forward(self, xs: "f32[2]", y: "f32[2]"):
+                     # File: /opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/_export/db/examples/dynamic_shape_map.py:15 in forward, code: return map(body, xs, y)
+                    add: "f32[2]" = torch.ops.aten.add.Tensor(xs, y);  xs = y = None
                     return (add,)
                     
     Graph signature: ExportGraphSignature(input_specs=[InputSpec(kind=, arg=TensorArgument(name='xs'), target=None, persistent=None), InputSpec(kind=, arg=TensorArgument(name='y'), target=None, persistent=None)], output_specs=[OutputSpec(kind=, arg=TensorArgument(name='getitem'), target=None)])
diff --git a/main/_sources/generated/exportdb/torch.operator.rst.txt b/main/_sources/generated/exportdb/torch.operator.rst.txt
index 9d0cc51612..e53f4297a8 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 
+    Unsupported: torch.* op returned non-Tensor int call_function 
diff --git a/main/_sources/library.rst.txt b/main/_sources/library.rst.txt
index f632d93d1e..e3b3bbc1ba 100644
--- a/main/_sources/library.rst.txt
+++ b/main/_sources/library.rst.txt
@@ -44,6 +44,7 @@ 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/miscellaneous_environment_variables.rst.txt b/main/_sources/miscellaneous_environment_variables.rst.txt
index 37b43d4946..f783f4c923 100644
--- a/main/_sources/miscellaneous_environment_variables.rst.txt
+++ b/main/_sources/miscellaneous_environment_variables.rst.txt
@@ -10,4 +10,6 @@ Miscellaneous Environment Variables
   * - ``TORCH_FORCE_WEIGHTS_ONLY_LOAD``
     - If set to [``1``, ``y``, ``yes``, ``true``], the torch.load will use ``weight_only=True``. For more documentation on this, see :func:`torch.load`.
   * - ``TORCH_AUTOGRAD_SHUTDOWN_WAIT_LIMIT``
-    - Under some conditions, autograd threads can hang on shutdown, therefore we do not wait for them to shutdown indefinitely but rely on timeout that is default set to ``10`` seconds. This environment variable can be used to set the timeout in seconds.
\ No newline at end of file
+    - Under some conditions, autograd threads can hang on shutdown, therefore we do not wait for them to shutdown indefinitely but rely on timeout that is default set to ``10`` seconds. This environment variable can be used to set the timeout in seconds.
+  * - ``TORCH_DEVICE_BACKEND_AUTOLOAD``
+    - If set to ``1``, out-of-tree backend extensions will be automatically imported when running ``import torch``.
diff --git a/main/_sources/notes/extending.rst.txt b/main/_sources/notes/extending.rst.txt
index bf69d0e012..04c4e705e1 100644
--- a/main/_sources/notes/extending.rst.txt
+++ b/main/_sources/notes/extending.rst.txt
@@ -914,6 +914,29 @@ 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 `_ 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
 -----------------------------------------
 
diff --git a/main/amp.html b/main/amp.html
index 9821a18289..4d0aa633a4 100644
--- a/main/amp.html
+++ b/main/amp.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/autograd.html b/main/autograd.html
index 3b6ac76af3..a12fa3b25f 100644
--- a/main/autograd.html
+++ b/main/autograd.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/backends.html b/main/backends.html
index e57cdb09e9..524aa6688c 100644
--- a/main/backends.html
+++ b/main/backends.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/benchmark_utils.html b/main/benchmark_utils.html
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+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/fx.experimental.html b/main/fx.experimental.html
index c907b8f3d1..35c4db5591 100644
--- a/main/fx.experimental.html
+++ b/main/fx.experimental.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/fx.html b/main/fx.html
index f076445fe7..064b2d292e 100644
--- a/main/fx.html
+++ b/main/fx.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/exportdb/index.html b/main/generated/exportdb/index.html
index 55499349e1..976d8b1745 100644
--- a/main/generated/exportdb/index.html
+++ b/main/generated/exportdb/index.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -781,13 +781,15 @@ 
cond_branch_class_method
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)
-            gt: "Sym(s0 > 2)" = sym_size_int_1 > 2;  sym_size_int_1 = None
+            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
             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
@@ -1108,13 +1114,15 @@ 
cond_operandsdynamic_shape_map¶

 

 
Note

-
Tags: torch.dynamic-shape, torch.map

+
Tags: torch.map, torch.dynamic-shape

 
Support Level: SUPPORTED

 

 
Original source code:

@@ -1579,8 +1593,9 @@ 
dynamic_shape_map¶

 

 
Note

-
Tags: torch.dynamic-shape, python.assert, python.data-structure

+
Tags: python.data-structure, python.assert, torch.dynamic-shape

 
Support Level: SUPPORTED

 

 
Original source code:

@@ -2025,11 +2040,9 @@ 
scalar_output
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
-            add: "Sym(s0 + 1)" = sym_size_int_1 + 1;  sym_size_int_1 = None
+            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
             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)])
@@ -2481,7 +2494,7 @@ 
torch_sym_min
Unsupported: torch.* op returned non-Tensor int call_function <function sym_min at 0x7f65dfc5f4c0>
+
Unsupported: torch.* op returned non-Tensor int call_function <function sym_min at 0x7f051a15b4c0>
 

 

 

diff --git a/main/generated/exportdb/python.assert.html b/main/generated/exportdb/python.assert.html
index 7c876eaf03..f81111a910 100644
--- a/main/generated/exportdb/python.assert.html
+++ b/main/generated/exportdb/python.assert.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -575,7 +575,7 @@ 
dynamic_shape_assertlist_contains¶

 

 
Note

-
Tags: torch.dynamic-shape, python.assert, python.data-structure

+
Tags: python.data-structure, python.assert, torch.dynamic-shape

 
Support Level: SUPPORTED

 

 
Original source code:

diff --git a/main/generated/exportdb/python.builtin.html b/main/generated/exportdb/python.builtin.html
index 79598c9e44..195cd33df9 100644
--- a/main/generated/exportdb/python.builtin.html
+++ b/main/generated/exportdb/python.builtin.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/exportdb/python.closure.html b/main/generated/exportdb/python.closure.html
index 4eea95f870..83cee590cb 100644
--- a/main/generated/exportdb/python.closure.html
+++ b/main/generated/exportdb/python.closure.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -576,13 +576,15 @@ 
cond_closed_over_variable
             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/exportdb/python.control-flow.html b/main/generated/exportdb/python.control-flow.html
index bde501a615..370e14cde3 100644
--- a/main/generated/exportdb/python.control-flow.html
+++ b/main/generated/exportdb/python.control-flow.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/exportdb/python.data-structure.html b/main/generated/exportdb/python.data-structure.html
index c22a67d0fb..e3a495c952 100644
--- a/main/generated/exportdb/python.data-structure.html
+++ b/main/generated/exportdb/python.data-structure.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -647,7 +647,7 @@ 
fn_with_kwargs¶

 

 
Note

-
Tags: torch.dynamic-shape, python.assert, python.data-structure

+
Tags: python.data-structure, python.assert, torch.dynamic-shape

 
Support Level: SUPPORTED

 

 
Original source code:

diff --git a/main/generated/exportdb/python.object-model.html b/main/generated/exportdb/python.object-model.html
index 60d0628193..7b78d21099 100644
--- a/main/generated/exportdb/python.object-model.html
+++ b/main/generated/exportdb/python.object-model.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/exportdb/torch.cond.html b/main/generated/exportdb/torch.cond.html
index f6998fa6f9..dfe2a15b22 100644
--- a/main/generated/exportdb/torch.cond.html
+++ b/main/generated/exportdb/torch.cond.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -598,13 +598,15 @@ 
cond_branch_class_method
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)
-            gt: "Sym(s0 > 2)" = sym_size_int_1 > 2;  sym_size_int_1 = None
+            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
             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
@@ -925,13 +931,15 @@ 
cond_operands
             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -598,13 +598,15 @@ 
cond_branch_class_method
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)
-            gt: "Sym(s0 > 2)" = sym_size_int_1 > 2;  sym_size_int_1 = None
+            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
             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
@@ -864,13 +868,15 @@ 
cond_operandsdynamic_shape_map¶

 

 
Note

-
Tags: torch.dynamic-shape, torch.map

+
Tags: torch.map, torch.dynamic-shape

 
Support Level: SUPPORTED

 

 
Original source code:

@@ -1071,8 +1079,9 @@ 
dynamic_shape_map¶

 

 
Note

-
Tags: torch.dynamic-shape, python.assert, python.data-structure

+
Tags: python.data-structure, python.assert, torch.dynamic-shape

 
Support Level: SUPPORTED

 

 
Original source code:

@@ -1290,11 +1299,9 @@ 
scalar_output
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
-            add: "Sym(s0 + 1)" = sym_size_int_1 + 1;  sym_size_int_1 = None
+            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
             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/generated/exportdb/torch.dynamic-value.html b/main/generated/exportdb/torch.dynamic-value.html
index 7257544c7c..a12873ddc6 100644
--- a/main/generated/exportdb/torch.dynamic-value.html
+++ b/main/generated/exportdb/torch.dynamic-value.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -576,10 +576,13 @@ 
constrain_as_size_example
             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -622,10 +622,13 @@ 
constrain_as_size_example
             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -533,7 +533,7 @@ 
torch.map¶

 

 
Note

-
Tags: torch.dynamic-shape, torch.map

+
Tags: torch.map, torch.dynamic-shape

 
Support Level: SUPPORTED

 

 
Original source code:

@@ -572,8 +572,9 @@ 
dynamic_shape_map
             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/exportdb/torch.operator.html b/main/generated/exportdb/torch.operator.html
index ab3388c9fe..32884caf35 100644
--- a/main/generated/exportdb/torch.operator.html
+++ b/main/generated/exportdb/torch.operator.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
@@ -562,7 +562,7 @@ 
torch_sym_min
Unsupported: torch.* op returned non-Tensor int call_function <function sym_min at 0x7f65dfc5f4c0>
+
Unsupported: torch.* op returned non-Tensor int call_function <function sym_min at 0x7f051a15b4c0>
 

 

 

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 1c632652ea..547e829877 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 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
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 74290f5f4f..7f98b49059 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 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
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 34d79c3f97..a7ee89d00b 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 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
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 c634c9d4c2..fa3f53f996 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 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
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 09b7bd5b78..e23fc1a894 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 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
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 dd2e47419b..9455aa9d38 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 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
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 ce0e9035fa..2a80e4ae1c 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 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
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 86b135b898..67b17aea42 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 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
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 5ee421633c..b414e46f4e 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 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Generator.html b/main/generated/torch.Generator.html
index 125b991bae..6c7e0c8149 100644
--- a/main/generated/torch.Generator.html
+++ b/main/generated/torch.Generator.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Tensor.abs.html b/main/generated/torch.Tensor.abs.html
index 1ff4850654..ad689cbff9 100644
--- a/main/generated/torch.Tensor.abs.html
+++ b/main/generated/torch.Tensor.abs.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Tensor.abs_.html b/main/generated/torch.Tensor.abs_.html
index d33dc9117b..6a92b175ea 100644
--- a/main/generated/torch.Tensor.abs_.html
+++ b/main/generated/torch.Tensor.abs_.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Tensor.absolute.html b/main/generated/torch.Tensor.absolute.html
index 7e4c145737..ae0cbd6acd 100644
--- a/main/generated/torch.Tensor.absolute.html
+++ b/main/generated/torch.Tensor.absolute.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Tensor.absolute_.html b/main/generated/torch.Tensor.absolute_.html
index 4d6398f6fc..4c48d21cd6 100644
--- a/main/generated/torch.Tensor.absolute_.html
+++ b/main/generated/torch.Tensor.absolute_.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Tensor.acos.html b/main/generated/torch.Tensor.acos.html
index 0c21212029..718d303a12 100644
--- a/main/generated/torch.Tensor.acos.html
+++ b/main/generated/torch.Tensor.acos.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Tensor.acos_.html b/main/generated/torch.Tensor.acos_.html
index 74dbd29800..3ac59a79e5 100644
--- a/main/generated/torch.Tensor.acos_.html
+++ b/main/generated/torch.Tensor.acos_.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Tensor.acosh.html b/main/generated/torch.Tensor.acosh.html
index 30107a5ee5..a66a8a54b5 100644
--- a/main/generated/torch.Tensor.acosh.html
+++ b/main/generated/torch.Tensor.acosh.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Tensor.acosh_.html b/main/generated/torch.Tensor.acosh_.html
index b558fecca1..65bb000be0 100644
--- a/main/generated/torch.Tensor.acosh_.html
+++ b/main/generated/torch.Tensor.acosh_.html
@@ -281,7 +281,7 @@
           

             
     

-      main (2.5.0a0+git75fa100 ) ▼
+      main (2.5.0a0+gitfb696bf ) ▼
     

     
 
diff --git a/main/generated/torch.Tensor.add.html b/main/generated/torch.Tensor.add.html
index f700170196..ad97380769 100644
--- a/main/generated/torch.Tensor.add.html
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@@ -281,7 +281,7 @@
           

             
     

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diff --git a/main/generated/torch.optim.Adam.html b/main/generated/torch.optim.Adam.html
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diff --git a/main/generated/torch.optim.AdamW.html b/main/generated/torch.optim.AdamW.html
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diff --git a/main/generated/torch.optim.Adamax.html b/main/generated/torch.optim.Adamax.html
index a5cc33fa6f..f3e6e544d5 100644
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diff --git a/main/generated/torch.optim.LBFGS.html b/main/generated/torch.optim.LBFGS.html
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diff --git a/main/generated/torch.optim.Optimizer.add_param_group.html b/main/generated/torch.optim.Optimizer.add_param_group.html
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diff --git a/main/generated/torch.optim.RAdam.html b/main/generated/torch.optim.RAdam.html
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diff --git a/main/generated/torch.optim.RMSprop.html b/main/generated/torch.optim.RMSprop.html
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diff --git a/main/generated/torch.optim.Rprop.html b/main/generated/torch.optim.Rprop.html
index 3f7f1e6396..28e090b36c 100644
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diff --git a/main/generated/torch.optim.SGD.html b/main/generated/torch.optim.SGD.html
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diff --git a/main/generated/torch.optim.SparseAdam.html b/main/generated/torch.optim.SparseAdam.html
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diff --git a/main/generated/torch.optim.lr_scheduler.ConstantLR.html b/main/generated/torch.optim.lr_scheduler.ConstantLR.html
index 8724448d42..0ca79c7328 100644
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diff --git a/main/generated/torch.optim.lr_scheduler.CosineAnnealingLR.html b/main/generated/torch.optim.lr_scheduler.CosineAnnealingLR.html
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diff --git a/main/generated/torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.html b/main/generated/torch.optim.lr_scheduler.CosineAnnealingWarmRestarts.html
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@@ -281,7 +281,7 @@
           

             
     

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diff --git a/main/generated/torch.optim.lr_scheduler.CyclicLR.html b/main/generated/torch.optim.lr_scheduler.CyclicLR.html
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diff --git a/main/generated/torch.optim.lr_scheduler.ExponentialLR.html b/main/generated/torch.optim.lr_scheduler.ExponentialLR.html
index b754a28e5d..b295ed9501 100644
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diff --git a/main/generated/torch.optim.lr_scheduler.LambdaLR.html b/main/generated/torch.optim.lr_scheduler.LambdaLR.html
index 8b928a435e..dc19ff3c4a 100644
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diff --git a/main/generated/torch.optim.lr_scheduler.LinearLR.html b/main/generated/torch.optim.lr_scheduler.LinearLR.html
index 8be745fddf..1328ee04b9 100644
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diff --git a/main/generated/torch.optim.lr_scheduler.MultiStepLR.html b/main/generated/torch.optim.lr_scheduler.MultiStepLR.html
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diff --git a/main/generated/torch.optim.lr_scheduler.MultiplicativeLR.html b/main/generated/torch.optim.lr_scheduler.MultiplicativeLR.html
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diff --git a/main/generated/torch.optim.lr_scheduler.OneCycleLR.html b/main/generated/torch.optim.lr_scheduler.OneCycleLR.html
index e1cf136d37..6cb2cff30e 100644
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@@ -621,7 +621,7 @@ 
OneCycleLRExample

 
>>> data_loader = torch.utils.data.DataLoader(...)
->>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
+>>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9)
 >>> scheduler = torch.optim.lr_scheduler.OneCycleLR(optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10)
 >>> for epoch in range(10):
 >>>     for batch in data_loader:
diff --git a/main/generated/torch.optim.lr_scheduler.PolynomialLR.html b/main/generated/torch.optim.lr_scheduler.PolynomialLR.html
index c351bbf48c..25266e4611 100644
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diff --git a/main/generated/torch.optim.lr_scheduler.ReduceLROnPlateau.html b/main/generated/torch.optim.lr_scheduler.ReduceLROnPlateau.html
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diff --git a/main/generated/torch.optim.lr_scheduler.SequentialLR.html b/main/generated/torch.optim.lr_scheduler.SequentialLR.html
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diff --git a/main/generated/torch.optim.lr_scheduler.StepLR.html b/main/generated/torch.optim.lr_scheduler.StepLR.html
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diff --git a/main/generated/torch.orgqr.html b/main/generated/torch.orgqr.html
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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.pinverse.html b/main/generated/torch.pinverse.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.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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@@ -554,7 +554,7 @@ 
torch.rangeTensor, optional) – the output tensor.

 
  • dtype (torch.dtype, optional) – the desired data type of returned tensor.
 Default: if None, uses a global default (see torch.set_default_dtype()). If dtype is not given, infer the data type from the other input
-arguments. If any of start, end, or stop are floating-point, the
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 get_default_dtype(). Otherwise, the dtype is inferred to
 be torch.int64.
    • 
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    R
    
   
   
 
 
  • Low-level APIs
 
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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, 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19, 23, 24, 25, 28, 29, 30, 34, 35, 40, 45, 46, 47, 48, 52, 53, 55, 63, 64, 66, 74, 75, 99, 341, 501, 732, 771, 772, 775, 776, 777, 796, 855, 896, 903, 909, 910, 913, 914, 915, 916, 917, 944, 982, 998, 1033, 1066, 1105, 1111, 1112, 1113, 1126, 1156, 1157, 1158, 1167, 1216, 1218, 1228, 1235, 1251, 1264, 1265, 1271, 1274, 1288, 1296, 1297, 1345, 1361, 1369, 1375, 1390, 1391, 1439, 1440, 1444, 1445, 1446, 1454, 1457, 1458, 1459, 1460, 1461, 1462, 1476, 1484, 1490, 1492, 1493, 1494, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1523, 1524, 1525, 1530, 1536, 1570, 1578, 1582, 1583, 1586, 1603, 1604, 1605, 1611, 1612, 1613, 1614, 1615, 1616, 1661, 1662, 1663, 1688, 1720, 1729, 1731, 1740, 1770, 1787, 1788, 1800, 1812, 1835, 1836, 1874, 1879, 1904, 1906, 1908, 1927, 1931, 1952, 1953, 1992, 2017, 2019, 2020, 2024, 2027, 2038, 2039, 2041, 2046, 2047, 2048, 2053, 2054, 2056, 2057, 2058, 2061, 2064, 2065, 2066, 2071, 2074, 2076, 2079, 2080, 2081, 2083, 2086, 2087, 2088, 2093, 2096, 2097, 2098, 2102, 2104, 2106, 2107, 2108, 2109, 2110, 2114, 2117], "cpu": [1, 4, 5, 14, 17, 23, 28, 30, 53, 55, 66, 71, 75, 76, 77, 90, 121, 198, 291, 328, 337, 447, 448, 449, 450, 451, 460, 488, 582, 591, 869, 884, 937, 939, 945, 954, 996, 999, 1000, 1011, 1021, 1022, 1023, 1025, 1111, 1113, 1123, 1128, 1146, 1158, 1162, 1164, 1165, 1223, 1225, 1226, 1227, 1232, 1233, 1250, 1274, 1282, 1284, 1285, 1294, 1304, 1306, 1310, 1311, 1312, 1313, 1315, 1317, 1320, 1322, 1323, 1329, 1332, 1335, 1338, 1339, 1345, 1346, 1361, 1364, 1375, 1387, 1466, 1472, 1530, 1703, 1720, 1725, 1726, 1761, 1762, 1776, 1779, 1786, 1830, 1839, 1841, 1843, 1845, 1846, 1870, 1875, 1876, 1877, 1879, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1898, 1908, 1913, 1914, 1915, 1916, 1917, 1918, 1931, 1946, 1947, 1948, 1957, 1959, 1964, 1968, 1985, 2013, 2016, 2017, 2018, 2020, 2024, 2028, 2030, 2035, 2037, 2038, 2040, 2050, 2053, 2054, 2056, 2059, 2061, 2064, 2065, 2067, 2071, 2072, 2073, 2075, 2077, 2080, 2081, 2086, 2088, 2089, 2092, 2093, 2095, 2098, 2099, 2102, 2106, 2107, 2108, 2110, 2111, 2114, 2115, 2117], "There": [1, 5, 6, 7, 9, 12, 14, 19, 22, 28, 30, 47, 52, 53, 55, 56, 60, 61, 64, 86, 87, 89, 683, 737, 796, 894, 909, 910, 976, 1168, 1466, 1500, 1546, 1688, 1720, 1727, 1728, 1768, 1773, 2015, 2017, 2019, 2020, 2026, 2027, 2039, 2047, 2050, 2053, 2054, 2055, 2060, 2063, 2067, 2068, 2071, 2074, 2075, 2076, 2077, 2081, 2083, 2092, 2095, 2102, 2104, 2105, 2107, 2108, 2115, 2116, 2117], "moment": [1, 66, 72, 775, 776, 777, 994, 1787, 1788, 1789, 1791, 1797, 1801, 2030, 2037, 2040, 2075, 2081, 2114], "nvprof": [1, 4, 933, 1026, 2050], "regist": [1, 15, 19, 24, 28, 32, 35, 47, 50, 52, 53, 55, 64, 82, 84, 85, 86, 87, 89, 489, 490, 683, 795, 796, 858, 928, 929, 976, 1055, 1189, 1274, 1346, 1530, 1531, 1532, 1540, 1541, 1559, 1711, 1712, 1713, 1714, 1715, 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, 63, 64, 66, 75, 83, 99, 152, 404, 417, 763, 796, 802, 896, 909, 910, 912, 918, 974, 978, 990, 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2069, 2074, 2076, 2106, 2107, 2108, 2109], "common": [1, 3, 8, 23, 33, 37, 47, 60, 66, 83, 88, 688, 796, 869, 949, 952, 957, 978, 993, 1105, 1110, 1155, 1156, 1157, 1158, 1199, 1216, 1297, 1346, 1415, 1444, 1445, 1446, 1449, 1570, 1618, 1711, 1712, 1714, 1715, 1716, 1717, 1718, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1850, 1862, 1928, 1971, 2016, 2020, 2025, 2039, 2047, 2050, 2053, 2054, 2055, 2061, 2063, 2066, 2071, 2074, 2085, 2086, 2087, 2090, 2093, 2102, 2103, 2104, 2108, 2113, 2115, 2116, 2117, 2119], "trade": [1, 5, 8, 55, 1338, 1443, 1874, 2049, 2055, 2077], "leav": [1, 8, 37, 48, 152, 897, 1182, 1279, 1292, 1738, 1741, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1922, 2017, 2019, 2020, 2028, 2047, 2050, 2069, 2074, 2077, 2105], "especi": [1, 9, 11, 23, 28, 53, 64, 256, 958, 976, 986, 1706, 2019, 2028, 2047, 2053, 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, 33, 47, 64, 90, 539, 893, 894, 909, 910, 1026, 1187, 1205, 1472, 1476, 1582, 1627, 1720, 1762, 1782, 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2109], "undefin": [1, 28, 36, 40, 321, 473, 619, 882, 904, 908, 909, 910, 923, 924, 952, 960, 978, 1113, 1163, 1164, 1442, 1781, 1824, 2024, 2047, 2050, 2053, 2054, 2065, 2081], "recurs": [1, 35, 52, 55, 64, 978, 982, 1102, 1187, 1196, 1214, 1274, 1286, 1288, 1530, 1727, 1728, 1804, 2019, 2053, 2057, 2061, 2074, 2081, 2105, 2106, 2108, 2109], "inner": [1, 3, 55, 56, 61, 818, 820, 912, 1093, 1169, 1173, 1178, 1186, 1194, 1953, 2018, 2053, 2072, 2081, 2097], "save_on_cpu": 1, "pin_memori": [1, 23, 66, 71, 75, 76, 77, 447, 448, 449, 450, 451, 1111, 1113, 1162, 1839, 1843, 1845, 1946, 2017, 2018, 2040, 2050, 2053, 2072, 2088, 2112], "within": [1, 5, 9, 12, 19, 23, 24, 28, 32, 33, 34, 35, 47, 48, 50, 52, 53, 55, 63, 64, 81, 82, 90, 490, 882, 899, 923, 924, 930, 976, 990, 1015, 1093, 1187, 1193, 1274, 1278, 1367, 1402, 1439, 1440, 1441, 1449, 1468, 1469, 1470, 1474, 1476, 1523, 1524, 1525, 1530, 1536, 1570, 1582, 1636, 1646, 1661, 1662, 1663, 1720, 1738, 1742, 1743, 1744, 1745, 1746, 1747, 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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, 1016, 1020, 1028, 1029, 1030, 1031, 1033, 1054, 1058, 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, 1753, 1763, 1782, 1783, 1906, 1913, 1914, 1915, 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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, 1688, 2016, 2018, 2030, 2039, 2040, 2047, 2050, 2072, 2078], "causal": [2, 738, 1536, 1574, 1575, 1576, 1577, 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1790, 1791, 1797, 1798, 1799, 1801, 1820, 1859, 1874, 1931, 1932, 1968, 2016, 2047, 2050, 2064, 2081, 2086], "are_deterministic_algorithms_en": [2, 2102], "use_deterministic_algorithm": [2, 27, 501, 877, 1111, 1112, 1113, 1255, 1873, 2065], "benchmark": [2, 19, 2016, 2018, 2050, 2059, 2075, 2102, 2108, 2114], "fastest": [2, 17, 19, 881, 1720, 1774, 1787, 1788, 1800, 2058, 2065, 2073], "benchmark_limit": 2, "maximum": [2, 27, 35, 47, 48, 52, 501, 698, 700, 774, 798, 823, 824, 825, 828, 829, 878, 1022, 1058, 1060, 1066, 1074, 1075, 1089, 1090, 1111, 1112, 1113, 1156, 1173, 1235, 1236, 1237, 1347, 1372, 1395, 1488, 1627, 1628, 1726, 1804, 1812, 1837, 1851, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1970, 2018, 2026, 2035, 2045, 2046, 2050, 2063, 2072, 2079, 2093, 2094, 2104, 2112, 2119, 2121], "try": [2, 3, 4, 7, 8, 28, 30, 39, 40, 44, 47, 52, 59, 60, 84, 85, 976, 978, 1080, 1164, 1173, 1179, 1189, 1213, 1279, 1281, 1290, 1311, 1395, 1449, 1457, 1458, 1459, 1460, 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[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, 1846, 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, 1606, 1607, 1611, 1612, 1613, 1614, 1615, 1616, 1637, 1646, 1650, 1653, 1688, 1710, 1720, 1730, 1732, 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"tupl": [3, 5, 12, 14, 19, 23, 28, 30, 33, 34, 37, 44, 45, 47, 52, 53, 55, 64, 235, 321, 447, 449, 451, 499, 522, 539, 562, 585, 586, 587, 696, 698, 699, 700, 702, 738, 769, 770, 771, 772, 775, 776, 777, 782, 788, 789, 790, 796, 820, 821, 858, 865, 866, 882, 883, 890, 891, 892, 893, 894, 896, 909, 910, 912, 913, 914, 915, 916, 917, 918, 923, 924, 927, 928, 929, 943, 959, 978, 985, 990, 997, 1021, 1022, 1025, 1037, 1055, 1061, 1089, 1090, 1108, 1111, 1113, 1127, 1129, 1130, 1132, 1133, 1135, 1136, 1137, 1139, 1140, 1142, 1143, 1145, 1147, 1150, 1160, 1165, 1167, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1177, 1178, 1179, 1187, 1189, 1198, 1214, 1218, 1236, 1238, 1274, 1281, 1286, 1290, 1291, 1296, 1305, 1310, 1311, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1327, 1331, 1333, 1334, 1336, 1338, 1341, 1344, 1362, 1364, 1366, 1372, 1374, 1376, 1377, 1380, 1382, 1421, 1424, 1431, 1432, 1433, 1435, 1436, 1437, 1439, 1440, 1441, 1449, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 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2117], "jitter": 3, "interpret": [3, 23, 28, 32, 35, 37, 47, 50, 52, 53, 782, 788, 884, 918, 1065, 1131, 1132, 1133, 1138, 1140, 1141, 1142, 1143, 1164, 1187, 1225, 1237, 1274, 1279, 1286, 1290, 1327, 1347, 1469, 1636, 1647, 1648, 1707, 1871, 1876, 2015, 2019, 2020, 2024, 2037, 2049, 2050, 2071, 2086, 2088, 2090, 2105, 2106], "ideal": [3, 46, 48, 1290, 1801, 2039, 2108], "analysi": [3, 24, 35, 52, 64, 1294, 1820, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 2021, 2028, 2061, 2068, 2069, 2097, 2103, 2105, 2106, 2107, 2111], "valgrind": 3, "degrad": [3, 14, 55, 2049, 2052, 2053, 2086], "due": [3, 4, 5, 7, 24, 28, 30, 35, 46, 55, 60, 64, 66, 68, 86, 488, 884, 912, 913, 918, 994, 1287, 1310, 1311, 1338, 1364, 1469, 1483, 1574, 1583, 1647, 1688, 1768, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1801, 1932, 2017, 2050, 2058, 2059, 2065, 2069, 2071, 2076, 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, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 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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], "functioncount": [3, 2016], "stat": [3, 58, 829, 839, 840, 1066, 1074, 1075, 1076, 1570, 1720, 2033, 2050, 2096, 2108, 2117], "as_standard": 3, "strip": [3, 1638, 1720, 2017, 2072, 2086], "prefix": [3, 28, 30, 37, 47, 55, 64, 751, 760, 1274, 1530, 1720, 2015, 2026, 2047, 2071, 2074, 2076, 2096, 2115], "stumbl": 3, "filepath": 3, "dif": 3, "compon": [3, 7, 9, 15, 18, 19, 28, 35, 64, 683, 898, 923, 978, 1130, 1131, 1133, 1141, 1142, 1143, 1314, 1574, 1575, 1576, 1577, 1578, 1710, 1820, 1927, 1978, 1979, 2021, 2026, 2047, 2052, 2053, 2057, 2060, 2061, 2069, 2086, 2103, 2109, 2117], "locat": [3, 9, 14, 28, 30, 33, 35, 44, 89, 156, 256, 488, 515, 683, 958, 960, 1023, 1089, 1090, 1296, 1346, 1372, 1377, 1380, 1416, 1466, 1476, 1565, 1582, 1601, 1636, 1703, 1706, 1720, 1740, 1831, 1866, 1887, 1909, 1912, 1968, 2015, 2017, 2031, 2050, 2057, 2066, 2071, 2074, 2075, 2081, 2083, 2086, 2091, 2096, 2099, 2102, 2107], "someth": [3, 7, 52, 53, 57, 64, 912, 914, 1110, 1189, 1199, 1274, 1290, 1530, 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, 1146, 1438, 1448, 1471, 1474, 1479, 1480, 1481, 1482, 1549, 1550, 1560, 1601, 1625, 1629, 1634, 1635, 1682, 1691, 1744, 1745, 1749, 1752, 1754, 1757, 1843, 1955, 2034, 2047, 2049, 2056, 2058, 2074, 2101, 2102], "next": [3, 23, 28, 35, 47, 53, 55, 64, 562, 763, 1187, 1278, 1430, 1482, 1501, 1548, 1720, 1763, 2037, 2046, 2047, 2049, 2050, 2053, 2054, 2056, 2061, 2063, 2069, 2075, 2081, 2082, 2086, 2089, 2091, 2099, 2102, 2105, 2106, 2108], "logic": [3, 5, 12, 14, 23, 38, 51, 55, 64, 948, 950, 951, 953, 983, 984, 1127, 1129, 1132, 1133, 1135, 1136, 1139, 1140, 1142, 1143, 1145, 1147, 1168, 1209, 1210, 1278, 1356, 1357, 1358, 1359, 1369, 1536, 1720, 1829, 1856, 1940, 2020, 2021, 2050, 2052, 2053, 2054, 2058, 2076, 2105], "question": [3, 10, 23, 64, 1197, 1772, 2016, 2047, 2056, 2098, 2104, 2107], "involv": [3, 5, 7, 9, 11, 23, 28, 52, 55, 58, 60, 64, 82, 1185, 1720, 1874, 2020, 2038, 2040, 2047, 2050, 2052, 2055, 2061, 2071, 2076, 2081, 2082, 2083, 2086, 2104, 2107, 2115], "look": [3, 4, 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": [3, 7, 9, 28, 30, 37, 41, 44, 47, 48, 50, 64, 488, 820, 1237, 1346, 1570, 2021, 2024, 2037, 2048, 2060, 2061, 2074, 2081, 2082, 2083, 2091, 2104, 2115], "hot": [3, 35, 1638, 1674, 2058, 2102], "spot": [3, 1727, 1728], "_data": 3, "truncate_row": 3, "_linewidth": 3, "subtract": [3, 315, 566, 869, 1164, 1638, 1913, 1914, 1915, 1917, 1918, 1928, 2018, 2040, 2072, 2086], "index": [3, 15, 19, 23, 24, 28, 30, 33, 35, 45, 52, 64, 193, 210, 283, 314, 315, 316, 317, 318, 319, 321, 323, 324, 473, 474, 514, 515, 516, 517, 518, 519, 520, 521, 698, 699, 820, 858, 881, 896, 898, 909, 910, 941, 960, 1028, 1031, 1089, 1090, 1130, 1171, 1172, 1173, 1177, 1179, 1215, 1246, 1247, 1248, 1249, 1272, 1291, 1296, 1304, 1322, 1340, 1354, 1362, 1364, 1368, 1372, 1375, 1376, 1377, 1380, 1403, 1406, 1416, 1422, 1425, 1426, 1434, 1449, 1465, 1472, 1473, 1531, 1532, 1537, 1540, 1541, 1580, 1582, 1627, 1628, 1674, 1746, 1748, 1755, 1756, 1761, 1774, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1815, 1816, 1831, 1863, 1864, 1865, 1866, 1868, 1869, 1870, 1899, 1910, 1911, 1913, 1914, 1915, 1917, 1918, 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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, 1751, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1831, 1833, 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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, 1757, 1776, 1820, 1837, 1839, 1840, 1841, 1842, 1843, 1844, 1845, 1867, 1879, 1932, 1971, 1980, 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1131, 1133, 1141, 1142, 1143, 1245, 1264, 1266, 1267, 1270, 1843, 1927, 1978, 1979, 2021, 2047, 2058, 2093], "satisfi": [11, 21, 24, 35, 53, 64, 619, 697, 763, 797, 913, 923, 924, 960, 1126, 1127, 1129, 1131, 1133, 1141, 1142, 1143, 1158, 1188, 1288, 1314, 1340, 1341, 1434, 1449, 1476, 1481, 1500, 1546, 1751, 1768, 1850, 1866, 1906, 1927, 2020, 2024, 2047, 2050, 2056, 2058, 2073, 2075, 2086, 2089, 2102, 2106], "equat": [11, 969, 1110, 1182, 1193, 1218, 1232, 1318, 1319, 1320, 1321, 1322, 1324, 1335, 1337, 1442, 1891, 1955, 2018, 2047, 2058, 2073, 2087], "frequent": [11, 30, 1434, 2016, 2035, 2050, 2063, 2064, 2066, 2086, 2098, 2099, 2102, 2110], "occur": [11, 23, 28, 40, 41, 47, 55, 60, 84, 86, 198, 317, 899, 932, 976, 1069, 1110, 1189, 1271, 1277, 1288, 1318, 1449, 1570, 1589, 1620, 1775, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1801, 2019, 2033, 2035, 2039, 2046, 2047, 2050, 2055, 2064, 2069, 2071, 2075, 2081, 2083, 2090, 2093, 2104, 2105, 2108, 2110, 2113, 2115, 2117, 2118, 2119], "mathemat": [11, 64, 912, 913, 914, 915, 916, 917, 1158, 1228, 1442, 1444, 1445, 1446, 1492, 1493, 1494, 1495, 1570, 1655, 1695, 1720, 1775, 1850, 1908, 1909, 2020, 2024, 2047, 2064, 2087, 2095], "topic": [11, 52, 2060, 2061, 2106], "tradition": 11, "torchaudio": [11, 2016, 2057], "mimick": 11, "assembli": 11, "lapack": [11, 1218, 1305, 1316, 1317, 1318, 1320, 1323, 1336, 1830, 1931], "spectral": [11, 1294, 1310, 1338, 1735, 1759, 1769, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 2064], "fft": [11, 2016, 2050], "4621": 11, "0303j": 11, "2438": [11, 1320, 1627], "5874j": 11, "7706": 11, "1421j": 11, "2110": 11, "1918j": 11, "complex128": [11, 177, 987, 1153, 1163, 1253, 1274, 1304, 1305, 1310, 1311, 1312, 1313, 1314, 1315, 1457, 1458, 1459, 1530, 1611, 1612, 1613, 1781, 1824, 1871, 2088, 2089, 2092, 2093, 2108], "complex64": [11, 180, 968, 969, 987, 1127, 1129, 1130, 1135, 1136, 1163, 1253, 1306, 1329, 1332, 1457, 1458, 1459, 1611, 1612, 1613, 1781, 1824, 1871, 2088, 2089, 2092, 2093, 2108], "apart": [11, 2020, 2047], "linspac": [11, 947, 971, 1131, 1141, 1376, 2018, 2022, 2072], "logspac": [11, 2018, 2022, 2072], "arang": [11, 23, 28, 36, 515, 609, 694, 695, 696, 700, 702, 890, 891, 892, 958, 970, 974, 1093, 1108, 1126, 1130, 1138, 1144, 1146, 1150, 1151, 1152, 1153, 1160, 1161, 1238, 1295, 1296, 1300, 1303, 1327, 1330, 1331, 1344, 1426, 1450, 1451, 1452, 1552, 1553, 1554, 1555, 1556, 1583, 1584, 1585, 1674, 1775, 1776, 1819, 1827, 1831, 1846, 1853, 1858, 1878, 1911, 1919, 1930, 1947, 1948, 1950, 1951, 1953, 1981, 2018, 2027, 2040, 2066, 2072, 2087, 2091, 2092, 2102, 2105, 2110, 2112], "switch": [11, 19, 23, 30, 58, 63, 64, 81, 1317, 1318, 1319, 1469, 1636, 1675, 1725, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1862, 1968, 2037, 2047, 2050, 2061, 2063, 2073, 2109], "view_as_r": [11, 1927, 2018, 2072, 2090], "6125": 11, "1681": 11, "3773": 11, "3487": 11, "0861": 11, "7981": 11, "1681j": 11, 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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, 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[[2009, "torch-xpu-set-rng-state-all"]], "torch.xpu.get_device_properties": [[1996, "torch-xpu-get-device-properties"]], "device": [[1990, "device"], [1406, "device"], [1031, "device"]], "torch.utils.model_zoo": [[2031, "torch-utils-model-zoo"]], "JIT Utils - torch.utils.jit": [[2023, "module-torch.utils.jit"]], "torch.xpu.stream": [[2011, "torch-xpu-stream"]], "torch.xpu.is_available": [[2001, "torch-xpu-is-available"]], "torch.xpu.set_device": [[2007, "torch-xpu-set-device"]], "torch.xpu.get_device_name": [[1995, "torch-xpu-get-device-name"]], "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 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"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"]], 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"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"], [2076, "frequently-asked-questions"], [2055, "frequently-asked-questions"], [2071, "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"]], "Functions": [[2017, "functions"], [2019, "functions"], [2118, "functions"], [2071, "functions"], [2087, "functions"]], "TorchScript Classes": [[2017, "torchscript-classes"], [2019, "id2"]], "Attributes": [[2017, "attributes"]], "Constants": [[2017, "constants"]], "Variables": [[2017, "variables"], [2019, "variables"]], "Fusion Backends": [[2017, "fusion-backends"]], "torch.xpu.init": [[1999, "torch-xpu-init"]], "torch.mps": [[2034, "module-torch.mps"]], "MPS Profiler": [[2034, "mps-profiler"]], "MPS Event": [[2034, "mps-event"]], "torch.xpu.seed": [[2005, "torch-xpu-seed"]], "torch.xpu.get_rng_state": [[1997, "torch-xpu-get-rng-state"]], "torch.utils.mobile_optimizer": [[2030, "torch-utils-mobile-optimizer"]], "device_of": [[1992, "device-of"], [1033, "device-of"]], "MPS Environment Variables": [[2035, "mps-environment-variables"]], "torch.mtia": [[2036, "torch-mtia"]], "Streams and events": [[2036, "streams-and-events"], [2124, "streams-and-events"], [17, "streams-and-events"], [16, "streams-and-events"]], "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"]], "torch.masked": [[2027, "torch-masked"]], "Motivation": [[2027, "motivation"], [2104, "motivation"], [2107, "motivation"]], "What is a MaskedTensor?": 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"TripletMarginWithDistanceLoss": [[1580, "tripletmarginwithdistanceloss"]], "RReLU": [[1549, "rrelu"]], "ModuleDict": [[1531, "moduledict"]], "Tanhshrink": [[1572, "tanhshrink"]], "ReplicationPad1d": [[1555, "replicationpad1d"]], "PairwiseDistance": [[1539, "pairwisedistance"]], "ParameterList": [[1541, "parameterlist"]], "Transformer": [[1574, "transformer"], [2116, "transformer"]], "CrossEntropyLoss": [[1465, "crossentropyloss"]], "ConvTranspose2d": [[1461, "convtranspose2d"], [745, "convtranspose2d"]], "torch.nextafter": [[1430, "torch-nextafter"]], "AdaptiveLogSoftmaxWithLoss": [[1434, "adaptivelogsoftmaxwithloss"]], "CELU": [[1448, "celu"]], "ConstantPad1d": [[1454, "constantpad1d"]], "FeatureAlphaDropout": [[1474, "featurealphadropout"]], "FractionalMaxPool3d": [[1478, "fractionalmaxpool3d"]], "EmbeddingBag": [[1473, "embeddingbag"], [749, "embeddingbag"]], "AvgPool1d": [[1439, "avgpool1d"]], "ChannelShuffle": [[1450, "channelshuffle"]], "BatchNorm1d": [[1444, "batchnorm1d"]], "ConvTranspose3d": [[1462, "convtranspose3d"], [746, "convtranspose3d"]], "DataParallel": [[1466, "dataparallel"]], "Conv1d": [[1457, "conv1d"], [741, "conv1d"]], "CircularPad2d": [[1452, "circularpad2d"]], "CTCLoss": [[1449, "ctcloss"]], "AvgPool2d": [[1440, "avgpool2d"]], "AdaptiveAvgPool1d": [[1431, "adaptiveavgpool1d"]], "FractionalMaxPool2d": [[1477, "fractionalmaxpool2d"]], "Dropout": [[1467, "dropout"]], "BCELoss": [[1442, "bceloss"]], "Dropout1d": [[1468, "dropout1d"]], "BCEWithLogitsLoss": [[1443, "bcewithlogitsloss"]], "CosineEmbeddingLoss": [[1463, "cosineembeddingloss"]], "AlphaDropout": [[1438, "alphadropout"]], "AdaptiveMaxPool3d": [[1437, "adaptivemaxpool3d"]], "torch.negative": [[1429, "torch-negative"]], "AvgPool3d": [[1441, "avgpool3d"]], "AdaptiveAvgPool3d": [[1433, "adaptiveavgpool3d"]], "AdaptiveMaxPool1d": [[1435, "adaptivemaxpool1d"]], "ConstantPad2d": [[1455, "constantpad2d"]], "BatchNorm2d": [[1445, "batchnorm2d"], [739, "batchnorm2d"]], "Conv2d": [[1458, "conv2d"], [742, "conv2d"], [733, "conv2d"]], "Dropout2d": [[1469, "dropout2d"]], "Flatten": [[1475, "flatten"]], "CircularPad1d": [[1451, "circularpad1d"]], "Embedding": [[1472, "embedding"], [748, "embedding"]], "CosineSimilarity": [[1464, "cosinesimilarity"]], "torch.neg": [[1428, "torch-neg"]], "Bilinear": [[1447, "bilinear"]], "ConvTranspose1d": [[1460, "convtranspose1d"], [744, "convtranspose1d"]], "AdaptiveMaxPool2d": [[1436, "adaptivemaxpool2d"]], "Conv3d": [[1459, "conv3d"], [743, "conv3d"], [734, "conv3d"]], "ELU": [[1471, "elu"], [747, "elu"]], "ConstantPad3d": [[1456, "constantpad3d"]], "BatchNorm3d": [[1446, "batchnorm3d"], [740, "batchnorm3d"]], "Dropout3d": [[1470, "dropout3d"]], "Fold": [[1476, "fold"]], "CircularPad3d": [[1453, "circularpad3d"]], "AdaptiveAvgPool2d": [[1432, "adaptiveavgpool2d"]], "torch.utils.tensorboard": [[2091, "module-torch.utils.tensorboard"]], "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.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"]], "PYTORCH ProcessGroupNCCL Environment Variables": [[2121, "pytorch-processgroupnccl-environment-variables"]], "torch.overrides": [[2118, "module-torch.overrides"]], "Threading Environment Variables": [[2094, "threading-environment-variables"]], "torch.xpu": [[2124, "module-torch.xpu"]], "Random Number Generator": [[2124, "random-number-generator"], [17, "random-number-generator"]], "torch.compiler API reference": [[2100, "torch-compiler-api-reference"]], "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"]], "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"]], "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"]], "Getting Started": [[2110, "getting-started"], [7, "getting-started"]], "Using a pretrained model": [[2110, "using-a-pretrained-model"]], "Next Steps": [[2110, "next-steps"]], "torch.ao.ns._numeric_suite_fx": [[2097, "torch-ao-ns-numeric-suite-fx"]], "torch.ao.ns.fx.utils": [[2097, "torch-ao-ns-fx-utils"]], "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"]], "torch.compiler": [[2098, "torch-compiler"]], "Getting Started for PyTorch Users": [[2098, null]], "HowTo for PyTorch Backend Vendors": [[2098, null]], "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"]], "Type Info": [[2122, "type-info"]], "torch.finfo": [[2122, "torch-finfo"]], "torch.iinfo": [[2122, "torch-iinfo"]], "IRs": [[2112, "irs"]], "Core Aten IR": [[2112, "core-aten-ir"]], "Prims IR": [[2112, "prims-ir"]], "torch.testing": [[2093, "module-torch.testing"]], "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"]], "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"]], "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"]], "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"]], "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"]], "CUDAGraph Trees": [[2102, "cudagraph-trees"]], "Background": [[2102, "background"], [2082, "background"], [2083, "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"]], "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": [[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"]], "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"]], "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"]], "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"]], "Best Practices for Backends": [[2101, "best-practices-for-backends"]], "x86 CPU": [[2101, "x86-cpu"]], "Torch Environment Variables": [[2120, "torch-environment-variables"]], "torch.ao.ns._numeric_suite": [[2096, "torch-ao-ns-numeric-suite"]], "torch.linalg.slogdet": [[1334, "torch-linalg-slogdet"]], "torch.linalg.solve_ex": [[1336, "torch-linalg-solve-ex"]], "torch.median": [[1375, "torch-median"]], "torch.linalg.qr": [[1333, "torch-linalg-qr"]], "torch.maximum": [[1373, "torch-maximum"]], "torch.matrix_exp": [[1370, "torch-matrix-exp"]], "torch.log10": [[1349, "torch-log10"]], "torch.logit": [[1360, "torch-logit"]], "torch.linalg.matrix_norm": [[1327, "torch-linalg-matrix-norm"]], "torch.logaddexp2": [[1353, "torch-logaddexp2"]], "torch.manual_seed": [[1367, "torch-manual-seed"]], "torch.linalg.tensorinv": [[1340, "torch-linalg-tensorinv"]], "torch.linalg.vander": [[1342, "torch-linalg-vander"]], "torch.logaddexp": [[1352, 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"inference-with-torch-compile"]], "Training Examples": [[2057, "training-examples"]], "Train with FP32": [[2057, "train-with-fp32"]], "Train with AMP": [[2057, "train-with-amp"]], "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, 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"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"]], "Broadcasting semantics": [[2048, "broadcasting-semantics"]], "General semantics": [[2048, "general-semantics"]], "In-place semantics": [[2048, "in-place-semantics"]], "Backwards compatibility": [[2048, "backwards-compatibility"]], "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 Backend Configuration": [[2076, "quantization-backend-configuration"], [2078, "quantization-backend-configuration"]], "Quantization Accuracy Debugging": [[2076, "quantization-accuracy-debugging"], [2077, "quantization-accuracy-debugging"]], "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"]], "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"]], "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"]], "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, "distributed-training"]], "Profiling Performance": [[2061, "profiling-performance"]], "Improving Performance with Quantization": [[2061, "improving-performance-with-quantization"]], "Improving Memory Usage with Pruning": [[2061, "improving-memory-usage-with-pruning"]], "Parametrizations": [[2061, "parametrizations"]], "Transforming Modules with FX": [[2061, "transforming-modules-with-fx"]], "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"]], "Windows FAQ": [[2067, "windows-faq"]], "Building from source": [[2067, "building-from-source"]], "Include optional components": [[2067, "include-optional-components"]], "Speeding CUDA build for Windows": [[2067, "speeding-cuda-build-for-windows"]], "One key install script": [[2067, "one-key-install-script"]], "Extension": [[2067, "extension"]], "CFFI Extension": [[2067, "cffi-extension"]], "Cpp Extension": [[2067, "cpp-extension"]], "Installation": [[2067, "installation"]], "Package not found in win-32 channel.": [[2067, "package-not-found-in-win-32-channel"]], "Import error": [[2067, "import-error"]], "Usage (multiprocessing)": [[2067, "usage-multiprocessing"]], "Multiprocessing error without if-clause protection": [[2067, "multiprocessing-error-without-if-clause-protection"]], "Multiprocessing error \u201cBroken pipe\u201d": [[2067, "multiprocessing-error-broken-pipe"]], "Multiprocessing error \u201cdriver shut down\u201d": [[2067, "multiprocessing-error-driver-shut-down"]], "CUDA IPC operations": [[2067, "cuda-ipc-operations"]], "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 allocators for CUDA": [[2050, "using-custom-memory-allocators-for-cuda"]], "cuBLAS workspaces": [[2050, "cublas-workspaces"]], "cuFFT plan cache": [[2050, "cufft-plan-cache"]], "Just-in-Time Compilation": [[2050, "just-in-time-compilation"]], "Best practices": [[2050, "best-practices"]], "Device-agnostic code": [[2050, "device-agnostic-code"]], "Use pinned memory buffers": [[2050, "use-pinned-memory-buffers"]], "Use nn.parallel.DistributedDataParallel instead of multiprocessing or nn.DataParallel": [[2050, "use-nn-parallel-distributeddataparallel-instead-of-multiprocessing-or-nn-dataparallel"]], "CUDA Graphs": [[2050, "cuda-graphs"]], "Why CUDA Graphs?": [[2050, "why-cuda-graphs"]], "PyTorch API": [[2050, "pytorch-api"]], "Constraints": [[2050, "constraints"], [35, "module-torch.distributions.constraints"]], "Non-constraints": [[2050, "non-constraints"]], "Whole-network capture": [[2050, "whole-network-capture"]], "Partial-network capture": [[2050, "partial-network-capture"]], "Usage with torch.cuda.amp": [[2050, "usage-with-torch-cuda-amp"]], "Usage with multiple streams": [[2050, "usage-with-multiple-streams"]], "Usage with DistributedDataParallel": [[2050, "usage-with-distributeddataparallel"]], "NCCL < 2.9.6": [[2050, "nccl-2-9-6"]], "NCCL >= 2.9.6": [[2050, "id5"]], "Graph memory management": [[2050, "graph-memory-management"]], "Sharing memory across captures": [[2050, "sharing-memory-across-captures"]], "ONNX Backend for TorchDynamo": [[2070, "onnx-backend-for-torchdynamo"]], "Data insensitive error": [[2077, "data-insensitive-error"]], "General tips": [[2077, "general-tips"]], "Int8 quantization tips": [[2077, "int8-quantization-tips"]], "Data sensitive error": [[2077, "data-sensitive-error"]], "Implementation error": [[2077, "implementation-error"]], "Numerical Debugging Tooling (prototype)": [[2077, "numerical-debugging-tooling-prototype"]], "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"]], "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.onnx": [[2068, "torch-onnx"]], "TorchDynamo-based ONNX Exporter": 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"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"]], "torch.special": [[2087, "torch-special"]], "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"]], "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"]], "Distributed Data Parallel": [[2052, "distributed-data-parallel"]], "Internal Design": [[2052, "internal-design"]], "Implementation": [[2052, "implementation"], [2083, "implementation"]], "ProcessGroup": [[2052, "processgroup"]], "TorchDynamo DDPOptimizer": [[2052, "id1"]], "HIP (ROCm) semantics": [[2059, "hip-rocm-semantics"]], "HIP Interfaces Reuse the CUDA Interfaces": [[2059, "hip-interfaces-reuse-the-cuda-interfaces"]], "Checking for HIP": [[2059, "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"]], "torch.profiler": [[2075, "torch-profiler"]], "Intel Instrumentation and Tracing Technology APIs": [[2075, "intel-instrumentation-and-tracing-technology-apis"]], "torch.nn.init": [[2045, "torch-nn-init"]], "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"]], "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.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"]], "MPS backend": [[2062, "mps-backend"]], "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"]], "Remote Reference Protocol": [[2083, "remote-reference-protocol"]], "RRef Lifetime": [[2083, "rref-lifetime"]], "Design Reasoning": [[2083, "design-reasoning"]], "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"]], "Dependencies": [[2069, "dependencies"]], "A simple example": [[2069, "a-simple-example"]], "Inspecting the ONNX model using GUI": [[2069, "inspecting-the-onnx-model-using-gui"]], "Diagnosing issues with SARIF": [[2069, "diagnosing-issues-with-sarif"]], "ONNX Diagnostic SARIF Rules": [[2069, null]], "torch.Size": [[2085, "torch-size"]], "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"]], "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"]], "torch.Storage": [[2088, "torch-storage"]], "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"]], "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"]], "Default values for native configurations": [[2078, "default-values-for-native-configurations"]], "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"]], "torch.nn.attention.bias": [[2043, "module-torch.nn.attention.bias"]], "CausalBias": [[2043, "causalbias"]], "PyTorch Custom Operators Landing Page": [[2051, "pytorch-custom-operators-landing-page"]], "Tensor Views": [[2090, "tensor-views"]], "torch.signal": [[2084, "module-torch.signal"]], "torch.signal.windows": [[2084, "module-torch.signal.windows"]], "torch.cuda.init": [[1046, "torch-cuda-init"]], "torch.cuda.comm.broadcast_coalesced": [[1022, "torch-cuda-comm-broadcast-coalesced"]], "torch.cuda.comm.reduce_add": [[1024, "torch-cuda-comm-reduce-add"]], "torch.cuda.cudart": [[1026, "torch-cuda-cudart"]], "torch.cuda.comm.scatter": [[1025, "torch-cuda-comm-scatter"]], "torch.cuda.jiterator._create_multi_output_jit_fn": [[1053, "torch-cuda-jiterator-create-multi-output-jit-fn"]], "torch.cuda.current_device": [[1028, "torch-cuda-current-device"]], "torch.cuda.max_memory_cached": [[1059, "torch-cuda-max-memory-cached"]], "torch.cuda.max_memory_reserved": [[1060, "torch-cuda-max-memory-reserved"]], "torch.cuda.graph_pool_handle": [[1045, "torch-cuda-graph-pool-handle"]], "torch.cuda.current_blas_handle": [[1027, "torch-cuda-current-blas-handle"]], "torch.cuda.get_allocator_backend": [[1035, "torch-cuda-get-allocator-backend"]], "torch.cuda.ipc_collect": [[1048, "torch-cuda-ipc-collect"]], "torch.cuda.get_device_properties": [[1039, "torch-cuda-get-device-properties"]], "torch.cuda.initial_seed": [[1047, "torch-cuda-initial-seed"]], "torch.cuda.get_device_capability": [[1037, "torch-cuda-get-device-capability"]], "torch.cuda.max_memory_allocated": [[1058, "torch-cuda-max-memory-allocated"]], "torch.cuda.device_count": [[1032, "torch-cuda-device-count"]], "torch.cuda.get_gencode_flags": [[1040, "torch-cuda-get-gencode-flags"]], "torch.cuda.default_stream": [[1030, "torch-cuda-default-stream"]], "torch.cuda.memory_summary": [[1067, "torch-cuda-memory-summary"]], "torch.cuda.manual_seed": [[1056, "torch-cuda-manual-seed"]], "torch.cuda.get_sync_debug_mode": [[1043, "torch-cuda-get-sync-debug-mode"]], "torch.cuda.get_rng_state_all": [[1042, "torch-cuda-get-rng-state-all"]], "torch.cuda.nvtx.mark": [[1069, "torch-cuda-nvtx-mark"]], "torch.cuda.get_rng_state": [[1041, "torch-cuda-get-rng-state"]], "torch.cuda.list_gpu_processes": [[1054, "torch-cuda-list-gpu-processes"]], "torch.cuda.is_available": [[1049, "torch-cuda-is-available"]], "torch.cuda.memory_usage": [[1068, "torch-cuda-memory-usage"]], "torch.cuda.manual_seed_all": [[1057, "torch-cuda-manual-seed-all"]], "graph": [[1044, "graph"]], "torch.cuda.nvtx.range": [[1070, "torch-cuda-nvtx-range"]], "torch.cuda.clock_rate": [[1020, "torch-cuda-clock-rate"]], "torch.cuda.make_graphed_callables": [[1055, "torch-cuda-make-graphed-callables"]], "torch.cuda.get_arch_list": [[1036, "torch-cuda-get-arch-list"]], "torch.cuda.current_stream": [[1029, "torch-cuda-current-stream"]], "torch.cuda.comm.gather": [[1023, "torch-cuda-comm-gather"]], "torch.cuda.memory_reserved": [[1064, "torch-cuda-memory-reserved"]], "torch.cuda.get_device_name": [[1038, "torch-cuda-get-device-name"]], "torch.cuda.memory_stats": [[1066, "torch-cuda-memory-stats"]], "torch.cuda.memory_snapshot": [[1065, "torch-cuda-memory-snapshot"]], "torch.cuda.jiterator._create_jit_fn": [[1052, "torch-cuda-jiterator-create-jit-fn"]], "torch.cuda.memory_allocated": [[1062, "torch-cuda-memory-allocated"]], "torch.cuda.empty_cache": [[1034, "torch-cuda-empty-cache"]], "torch.cuda.comm.broadcast": [[1021, "torch-cuda-comm-broadcast"]], "torch.cuda.mem_get_info": [[1061, "torch-cuda-mem-get-info"]], "torch.cuda.memory_cached": [[1063, "torch-cuda-memory-cached"]], "torch.cuda.is_current_stream_capturing": [[1050, "torch-cuda-is-current-stream-capturing"]], "torch.cuda.is_initialized": [[1051, "torch-cuda-is-initialized"]], "torch.cuda.change_current_allocator": [[1019, "torch-cuda-change-current-allocator"]], "torch.conj": [[991, "torch-conj"]], "torch.combinations": [[975, "torch-combinations"]], "ExternalStream": [[1012, "externalstream"]], "torch.clone": [[973, "torch-clone"]], "torch.cpu.current_stream": [[1002, 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1483, 1484, 1492, 1493, 1494, 1502, 1570, 1633, 1834, 1976, 2018, 2020, 2038, 2072, 2104, 2112, 2117], "thing": [1, 3, 7, 8, 28, 33, 52, 60, 64, 1168, 1284, 1376, 1442, 1638, 1904, 2019, 2024, 2047, 2050, 2053, 2054, 2055, 2058, 2063, 2071, 2074, 2076, 2077, 2083, 2102, 2105, 2107, 2108, 2115, 2117], "detach": [1, 5, 66, 74, 75, 224, 417, 450, 460, 973, 1167, 1274, 1449, 1530, 1620, 1638, 1908, 1946, 2017, 2018, 2038, 2040, 2053, 2055, 2071, 2072, 2078, 2086, 2090, 2092, 2116], "register_hook": [1, 2038, 2047], "name": [1, 2, 3, 14, 19, 24, 28, 30, 33, 34, 35, 37, 40, 41, 44, 45, 47, 50, 52, 53, 55, 64, 66, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 89, 683, 700, 750, 751, 760, 795, 817, 818, 819, 820, 827, 843, 858, 862, 936, 939, 941, 985, 1026, 1038, 1162, 1167, 1177, 1180, 1182, 1187, 1189, 1272, 1274, 1275, 1282, 1285, 1290, 1291, 1305, 1310, 1311, 1317, 1318, 1320, 1321, 1322, 1323, 1333, 1334, 1336, 1338, 1339, 1346, 1530, 1581, 1589, 1712, 1717, 1718, 1720, 1734, 1735, 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1582, 1591, 1592, 1593, 1627, 1688, 1706, 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, 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2077, 2079, 2081, 2083, 2091, 2092, 2099, 2101, 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, 932, 939, 945, 947, 954, 961, 963, 970, 975, 976, 978, 997, 998, 1002, 1003, 1007, 1008, 1012, 1014, 1016, 1017, 1020, 1021, 1022, 1023, 1024, 1025, 1028, 1029, 1030, 1031, 1032, 1037, 1038, 1039, 1041, 1043, 1047, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1066, 1067, 1068, 1073, 1074, 1075, 1076, 1079, 1080, 1081, 1084, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1097, 1098, 1099, 1100, 1101, 1102, 1108, 1111, 1113, 1123, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1149, 1162, 1164, 1165, 1169, 1170, 1171, 1172, 1173, 1179, 1181, 1184, 1187, 1205, 1207, 1215, 1222, 1225, 1226, 1228, 1232, 1233, 1235, 1236, 1237, 1238, 1249, 1250, 1271, 1272, 1274, 1275, 1277, 1280, 1281, 1286, 1294, 1296, 1306, 1307, 1327, 1328, 1331, 1340, 1341, 1342, 1343, 1344, 1345, 1347, 1354, 1361, 1362, 1367, 1372, 1374, 1375, 1377, 1380, 1382, 1383, 1384, 1385, 1388, 1389, 1393, 1396, 1403, 1404, 1405, 1406, 1407, 1411, 1416, 1421, 1422, 1423, 1424, 1425, 1426, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1439, 1440, 1441, 1444, 1445, 1446, 1447, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1464, 1465, 1466, 1472, 1473, 1475, 1476, 1477, 1478, 1480, 1482, 1484, 1492, 1493, 1494, 1497, 1498, 1499, 1501, 1502, 1506, 1507, 1508, 1509, 1510, 1511, 1515, 1517, 1518, 1520, 1523, 1524, 1525, 1526, 1527, 1528, 1530, 1532, 1535, 1537, 1538, 1541, 1542, 1543, 1545, 1548, 1552, 1553, 1554, 1555, 1556, 1557, 1564, 1566, 1570, 1574, 1575, 1576, 1577, 1578, 1579, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1618, 1619, 1620, 1627, 1628, 1635, 1638, 1647, 1655, 1672, 1673, 1674, 1678, 1679, 1694, 1695, 1703, 1707, 1708, 1709, 1719, 1720, 1735, 1736, 1745, 1746, 1748, 1749, 1751, 1754, 1755, 1756, 1757, 1762, 1764, 1769, 1772, 1775, 1776, 1778, 1779, 1781, 1782, 1783, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1794, 1797, 1798, 1799, 1800, 1801, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 1820, 1821, 1828, 1831, 1832, 1833, 1834, 1835, 1836, 1837, 1839, 1841, 1842, 1843, 1845, 1851, 1852, 1853, 1856, 1857, 1858, 1859, 1862, 1867, 1868, 1869, 1873, 1876, 1877, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1899, 1903, 1907, 1910, 1911, 1912, 1919, 1922, 1924, 1925, 1926, 1927, 1930, 1932, 1936, 1938, 1943, 1947, 1948, 1950, 1952, 1953, 1956, 1957, 1958, 1959, 1962, 1963, 1964, 1965, 1966, 1967, 1970, 1971, 1974, 1975, 1976, 1980, 1981, 1986, 1988, 1989, 1990, 1991, 1994, 1995, 1996, 1997, 2000, 2003, 2004, 2007, 2008, 2012, 2013, 2017, 2018, 2019, 2020, 2021, 2024, 2033, 2037, 2038, 2040, 2045, 2050, 2054, 2063, 2066, 2069, 2071, 2072, 2075, 2076, 2080, 2081, 2085, 2087, 2088, 2089, 2091, 2092, 2093, 2095, 2099, 2104, 2108, 2112, 2116, 2119, 2122], "show": [2, 4, 7, 13, 18, 23, 24, 28, 30, 33, 36, 52, 55, 64, 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2038, 2039, 2047, 2053, 2071, 2075, 2076, 2077, 2081, 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, 742, 743, 744, 745, 746, 748, 749, 759, 763, 767, 802, 904, 905, 909, 978, 990, 994, 998, 1079, 1111, 1179, 1189, 1288, 1290, 1347, 1447, 1457, 1458, 1459, 1460, 1461, 1462, 1466, 1472, 1473, 1481, 1482, 1500, 1501, 1502, 1515, 1517, 1530, 1533, 1538, 1546, 1548, 1720, 1761, 1762, 1763, 1764, 1765, 1766, 1767, 1779, 1783, 1785, 1802, 1803, 1804, 1805, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1815, 1816, 1839, 1841, 1843, 1968, 1980, 2013, 2015, 2016, 2026, 2027, 2039, 2040, 2047, 2049, 2050, 2052, 2055, 2058, 2064, 2065, 2067, 2069, 2071, 2073, 2076, 2081, 2088, 2091, 2099, 2104, 2105, 2106, 2108, 2110, 2117], "torch_blas_prefer_cublaslt": 2, "global": [2, 3, 5, 8, 11, 12, 20, 23, 28, 30, 32, 35, 37, 48, 55, 60, 63, 64, 66, 69, 74, 75, 858, 865, 869, 877, 932, 945, 954, 990, 1009, 1044, 1061, 1068, 1111, 1113, 1123, 1128, 1146, 1162, 1165, 1168, 1232, 1233, 1255, 1262, 1274, 1277, 1290, 1294, 1345, 1361, 1530, 1688, 1712, 1713, 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, 1016, 1020, 1028, 1029, 1030, 1031, 1033, 1054, 1058, 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, 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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, 1905, 2017, 2037, 2053, 2061, 2063, 2065, 2068, 2071, 2074, 2081, 2086, 2090, 2103, 2105, 2107, 2117], "jitter": 3, "interpret": [3, 23, 28, 32, 35, 37, 47, 50, 52, 53, 782, 788, 884, 918, 1065, 1131, 1132, 1133, 1138, 1140, 1141, 1142, 1143, 1164, 1187, 1225, 1237, 1274, 1279, 1286, 1290, 1327, 1347, 1469, 1636, 1647, 1648, 1707, 1871, 1876, 2015, 2019, 2020, 2024, 2037, 2049, 2050, 2071, 2086, 2088, 2090, 2105, 2106], "ideal": [3, 46, 48, 1290, 1801, 2039, 2108], "analysi": [3, 24, 35, 52, 64, 1294, 1820, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 2021, 2028, 2061, 2068, 2069, 2097, 2103, 2105, 2106, 2107, 2111], "valgrind": 3, "degrad": [3, 14, 55, 2049, 2052, 2053, 2086], "due": [3, 4, 5, 7, 24, 28, 30, 35, 46, 55, 60, 64, 66, 68, 86, 488, 884, 912, 913, 918, 994, 1287, 1310, 1311, 1338, 1364, 1469, 1483, 1574, 1583, 1647, 1688, 1768, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 1801, 1932, 2017, 2050, 2058, 2059, 2065, 2069, 2071, 2076, 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, 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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, 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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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2071], "consider": [5, 7, 83, 888, 1271, 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, 976, 978, 981, 983, 984, 1009, 1045, 1050, 1055, 1168, 1183, 1187, 1189, 1193, 1199, 1211, 1274, 1277, 1278, 1284, 1286, 1290, 1720, 1782, 1784, 1785, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 2016, 2020, 2024, 2026, 2030, 2035, 2041, 2046, 2052, 2053, 2056, 2058, 2061, 2062, 2068, 2069, 2071, 2074, 2075, 2077, 2078, 2079, 2081, 2082, 2083, 2086, 2091, 2097, 2098, 2099, 2103, 2104, 2106, 2107, 2109, 2110, 2111, 2113, 2114], "no_grad": [5, 490, 865, 919, 1114, 1169, 1173, 1178, 1274, 1472, 1530, 1536, 1578, 1721, 1784, 1785, 1786, 1787, 1788, 1789, 1791, 1797, 1798, 1799, 1800, 2045, 2047, 2057, 2061, 2076, 2095, 2099], "unmet": 5, "particip": [5, 9, 23, 28, 29, 32, 47, 48, 1574, 1720, 2082, 2104], "wherea": [5, 11, 33, 35, 52, 288, 1330, 1390, 1391, 1421, 1801, 1931, 2020, 2047, 2073, 2093, 2107], "avoid": [5, 8, 9, 19, 20, 23, 28, 30, 33, 35, 45, 48, 55, 64, 66, 74, 75, 193, 210, 450, 784, 869, 897, 957, 976, 1066, 1209, 1210, 1274, 1320, 1346, 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2109], "view_as_r": [11, 1927, 2018, 2072, 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, 2053, 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, 66, 76, 77, 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, 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"master_addr": [24, 28, 37, 47, 48, 51, 2052, 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": 28, "scatter": [28, 32, 55, 515, 517, 519, 1466, 1968, 2018, 2055, 2056, 2072, 2081, 2112], "reduce_scatt": [28, 2072], "all_to_al": 28, "v1": [28, 55, 1343, 1819, 2015, 2052, 2081], "init_method": [28, 1720, 2081], "adher": [28, 978, 2020, 2086], "some_fil": 28, "machine_nam": 28, "share_folder_nam": 28, "tcpstore": [28, 47], "past": [28, 52, 64, 1020, 1068, 1073, 1087, 1088, 1720, 2055, 2110, 2111, 2114], "ask": [28, 59, 60, 2015, 2016, 2054, 2058, 2098, 2105, 2119], "infiniband": [28, 1720, 2081], "interconnect": [28, 33], "gpudirect": 28, "ethernet": 28, "ip": [28, 47], "ib": 28, "upcom": [28, 2046], "nccl_socket_ifnam": 28, "eth0": 28, "gloo_socket_ifnam": 28, "eth1": 28, "eth2": 28, "eth3": 28, "imper": 28, "nccl_debug": 28, "nccl_debug_subsi": 28, "coll": 28, "hang": [28, 29, 32, 35, 1720, 2029, 2052, 2121], "topologi": [28, 30, 34, 37], "effort": [28, 52, 2081, 2105, 2111], "socket": [28, 38, 2037, 2081], "nccl_socket_nthread": 28, "nccl_nsocks_perthread": 28, "cloud": [28, 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, 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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, 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"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, 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"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": 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"Adam": [[1787, "adam"]], "torch.optim.Optimizer.zero_grad": [[1796, "torch-optim-optimizer-zero-grad"]], "RAdam": [[1797, "radam"]], "torch.promote_types": [[1829, "torch-promote-types"]], "torch.quantize_per_channel": [[1832, "torch-quantize-per-channel"]], "torch.polar": [[1824, "torch-polar"]], "NAdam": [[1791, "nadam"]], "PolynomialLR": [[1813, "polynomiallr"]], "MultiplicativeLR": [[1811, "multiplicativelr"]], "SGD": [[1800, "sgd"]], "LambdaLR": [[1808, "lambdalr"]], "torch.positive": [[1826, "torch-positive"]], "MultiStepLR": [[1810, "multisteplr"]], "CosineAnnealingLR": [[1804, "cosineannealinglr"]], "RMSprop": [[1798, "rmsprop"]], "torch.permute": [[1821, "torch-permute"]], "CosineAnnealingWarmRestarts": [[1805, "cosineannealingwarmrestarts"]], "torch.optim.Optimizer.state_dict": [[1794, "torch-optim-optimizer-state-dict"]], "ExponentialLR": [[1807, "exponentiallr"]], "torch.orgqr": [[1817, "torch-orgqr"]], "torch.ormqr": [[1818, "torch-ormqr"]], "torch.pow": [[1827, 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"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, 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"threading-environment-variables"]], "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"]], "Type Info": [[2122, "type-info"]], "torch.finfo": [[2122, "torch-finfo"]], "torch.iinfo": [[2122, "torch-iinfo"]], "IRs": [[2112, "irs"]], "Core Aten IR": [[2112, "core-aten-ir"]], "Prims IR": [[2112, "prims-ir"]], "torch.jit.save": [[1285, "torch-jit-save"]], "torch.jit.isinstance": [[1281, "torch-jit-isinstance"]], "torch.ldexp": [[1298, "torch-ldexp"]], "torch.linalg.inv_ex": [[1316, "torch-linalg-inv-ex"]], "torch.le": [[1299, "torch-le"]], "torch.linalg.eigvals": [[1312, "torch-linalg-eigvals"]], "torch.jit.optimize_for_inference": [[1284, "torch-jit-optimize-for-inference"]], "torch.less": [[1301, "torch-less"]], "torch.jit.script": [[1286, "torch-jit-script"]], "torch.linalg.cholesky_ex": [[1305, 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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, 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SARIF": [[2069, "diagnosing-issues-with-sarif"]], "ONNX Diagnostic SARIF Rules": [[2069, null]], "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"]], "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"]], 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