Revert "Make dynamism code robust to NotImplementedException (pytorch#148823)"

This reverts commit 6057641.

Reverted pytorch#148823 on behalf of https://github.com/ZainRizvi due to Sorry but this is breaking internally, see D71042206 for details. To validate your fixes internally before relanding, you can follow the instructions here: https://fburl.com/fixing-ghfirst-reverts ([comment](pytorch#148823 (comment)))

Author: pytorchmergebot

test/fx/test_dynamism.py

@@ -110,42 +110,6 @@ def forward(self, x):
         }
         self.assertEqual(result, expected)
 
-    def test_property_not_implemented(self):
-        class ModuleWithNotImplementedProperty(torch.nn.Module):
-            def __init__(self, x, y):
-                super().__init__()
-                self.linear = torch.nn.Linear(x, y)
-
-            @property
-            def not_implemented_property(self):
-                raise NotImplementedError("This property is not implemented")
-
-        module1 = ModuleWithNotImplementedProperty(10, 10)
-        module2 = ModuleWithNotImplementedProperty(10, 10)
-
-        result = track_dynamism_across_examples(
-            [
-                {"self": module1},
-                {"self": module2},
-            ]
-        )
-
-        expected = {
-            "self": {
-                "L['self']['_modules']['linear']['_parameters']['weight']": (
-                    False,
-                    False,
-                ),
-                "L['self']['_modules']['linear']['_parameters']['bias']": (False,),
-                "L['self']['_modules']['linear']['bias']": (False,),
-                "L['self']['_modules']['linear']['in_features']": (False,),
-                "L['self']['_modules']['linear']['out_features']": (False,),
-                "L['self']['_modules']['linear']['weight']": (False, False),
-            }
-        }
-
-        self.assertEqual(result, expected)
-
 
 if __name__ == "__main__":
     run_tests()

torch/fx/experimental/_dynamism.py

@@ -29,21 +29,14 @@ def module_to_nested_dict(module: torch.nn.Module) -> dict[str, Any]:
     self_dict["_modules"] = {}
 
     for attr_name in dir(module):
-        try:
-            if not attr_name.startswith("_") and not callable(
-                getattr(module, attr_name)
+        if not attr_name.startswith("_") and not callable(getattr(module, attr_name)):
+            attr_value = getattr(module, attr_name)
+            if (
+                not isinstance(attr_value, torch.nn.Module)
+                and isinstance(attr_value, (int, float, torch.Tensor))
+                and type(attr_value) is not bool
             ):
-                attr_value = getattr(module, attr_name)
-                if (
-                    not isinstance(attr_value, torch.nn.Module)
-                    and isinstance(attr_value, (int, float, torch.Tensor))
-                    and type(attr_value) is not bool
-                ):
-                    self_dict[attr_name] = attr_value
-        except NotImplementedError:
-            # Skip attributes that raise NotImplementedError since they won't
-            # contain any dynamism anyways.
-            continue
+                self_dict[attr_name] = attr_value
 
     for name, param in module.named_parameters(recurse=False):
         self_dict["_parameters"][name] = param