Use swap_tensors path in nn.Module.to for all subclasses that override __torch_dispatch__ (#152539)

Fixes https://github.com/pytorch/pytorch/issues/148977

Pull Request resolved: https://github.com/pytorch/pytorch/pull/152539
Approved by: https://github.com/albanD

test/test_fake_tensor.py

@@ -1487,6 +1487,20 @@ class FakeTensorOperatorInvariants(TestCase):
 
         self.assertEqual(mode.count, 0)
 
+    # PropagateRealTensors installs weakrefs
+    @expectedFailurePropagateRealTensors
+    @unittest.skipIf(not RUN_CUDA, "requires cuda")
+    def test_module_to(self):
+
+        def _check_device(sd, device_type):
+            for v in sd.values():
+                self.assertEqual(v.device.type, device_type)
+
+        with FakeTensorMode():
+            m = torch.nn.Linear(2, 2)
+            _check_device(m.state_dict(), 'cpu')
+            m.to('cuda')
+            _check_device(m.state_dict(), 'cuda')
 
 make_propagate_real_tensors_cls(FakeTensorOperatorInvariants)
 

torch/nn/modules/module.py

@@ -14,7 +14,6 @@ import torch
 from torch import device, dtype, Tensor
 from torch._prims_common import DeviceLikeType
 from torch.nn.parameter import Buffer, Parameter
-from torch.utils._python_dispatch import is_traceable_wrapper_subclass
 from torch.utils.hooks import BackwardHook, RemovableHandle
 
 
@@ -943,8 +942,10 @@ class Module:
             p_should_use_set_data = compute_should_use_set_data(param, param_applied)
 
             # subclasses may have multiple child tensors so we need to use swap_tensors
-            p_should_use_swap_tensors = (
-                should_use_swap_tensors or is_traceable_wrapper_subclass(param_applied)
+            p_should_use_swap_tensors = should_use_swap_tensors or (
+                hasattr(param, "__torch_dispatch__")
+                and param.__torch_dispatch__  # type: ignore[misc]
+                is not torch._C._disabled_torch_dispatch_impl
             )
 
             param_grad = param.grad