[dynamo] Fix support for classmethod(property(...)) (#134968)

Fixes #134451

Pull Request resolved: https://github.com/pytorch/pytorch/pull/134968
Approved by: https://github.com/yanboliang

test/dynamo/test_repros.py

@@ -20,7 +20,7 @@ import weakref
 from abc import ABC
 from collections import namedtuple
 from copy import deepcopy
-from enum import Enum
+from enum import Enum, IntEnum
 from functools import wraps
 from typing import Any, Dict, Iterator, List, Tuple
 from unittest import mock
@@ -4546,6 +4546,84 @@ class ReproTests(torch._dynamo.test_case.TestCase):
             f(*args)
         self.assertEqual(num_compiles, 1)
 
+    def test_issue134451(self):
+        class BoundingBox2DIndex(IntEnum):
+            _X = 0
+            _Y = 1
+            _HEADING = 2
+            _LENGTH = 3
+            _WIDTH = 4
+
+            @classmethod
+            def size(cls):
+                return 5
+
+            @classmethod
+            @property
+            def X(cls):
+                return cls._X
+
+            @classmethod
+            @property
+            def Y(cls):
+                return cls._Y
+
+            @classmethod
+            @property
+            def HEADING(cls):
+                return cls._HEADING
+
+            @classmethod
+            @property
+            def LENGTH(cls):
+                return cls._LENGTH
+
+            @classmethod
+            @property
+            def WIDTH(cls):
+                return cls._WIDTH
+
+            @classmethod
+            @property
+            def POINT(cls):
+                # assumes X, Y have subsequent indices
+                return slice(cls._X, cls._Y + 1)
+
+            @classmethod
+            @property
+            def STATE_SE2(cls):
+                # assumes X, Y, HEADING have subsequent indices
+                return slice(cls._X, cls._HEADING + 1)
+
+        class SimpleModel(nn.Module):
+            def __init__(self):
+                super().__init__()
+                self._mlp_states = nn.Sequential(
+                    nn.Linear(10, 20),
+                    nn.ReLU(),
+                    nn.Linear(20, BoundingBox2DIndex.size()),
+                )
+
+            def forward(self, x):
+                agent_states = self._mlp_states(x)
+                agent_states[..., BoundingBox2DIndex.POINT] = (
+                    agent_states[..., BoundingBox2DIndex.POINT].tanh() * 32
+                )
+                agent_states[..., BoundingBox2DIndex.HEADING] = (
+                    agent_states[..., BoundingBox2DIndex.HEADING].tanh() * torch.pi
+                )
+                return agent_states
+
+        model = SimpleModel().eval()
+        input_tensor = torch.randn(1, 10, dtype=torch.float32)
+        opt = torch.compile(model.eval(), backend="eager", fullgraph=True)
+        actual = opt(input_tensor)
+        try:
+            expected = model(input_tensor)
+        except Exception as e:
+            raise unittest.SkipTest("eager failed, requires Python>=3.12") from e
+        self.assertEqual(actual, expected)
+
     def test_invalid_seq_unpack(self):
         def myfn(arg):
             (a, b) = arg

torch/_dynamo/variables/constant.py

@@ -222,6 +222,8 @@ class EnumVariable(VariableTracker):
         unimplemented("Enum variable is constructed with non constant values")
 
     def as_proxy(self):
+        if isinstance(self.value, int):
+            return int(self.value)  # convert IntEnum to a normal int
         return self.value
 
     def __str__(self) -> str:

torch/_dynamo/variables/user_defined.py

@@ -193,6 +193,10 @@ class UserDefinedClassVariable(UserDefinedVariable):
             else:
                 return SourcelessBuilder.create(tx, func)
         elif isinstance(obj, classmethod):
+            if isinstance(obj.__func__, property):
+                return variables.UserFunctionVariable(obj.__func__.fget).call_function(
+                    tx, [self], {}
+                )
             return variables.UserMethodVariable(obj.__func__, self, source=source)
         elif isinstance(obj, types.ClassMethodDescriptorType):
             # e.g.: inspect.getattr_static(dict, "fromkeys")