simple_repro_89395.py

import torch
import torch._dynamo as torchdynamo

torchdynamo.config.verbose = True
torchdynamo.config.suppress_errors = True

class TestCasePlaceholder:
    def assertTrue(self, v):
        assert v, "Expected True"

    def assertFalse(self, v):
        assert not v, "Expected False"

DEVICE = 'cpu'
DTYPE = torch.float64
SELF = TestCasePlaceholder()


@torchdynamo.optimize()
def test_coalesce_reference_cycle(self, device, dtype):
     # Test coalesce doesn't create autograd graph cycles (gh-52253)
     # Sanity check that the helper class works as expected
     t = torch.rand(2)
     t_ref = torch._C._WeakTensorRef(t)
     self.assertFalse(t_ref.expired())

     del t
     self.assertTrue(t_ref.expired())

     def test_sparse_sum():
         i = torch.tensor([[0], [4]], dtype=torch.long, device=device)
         v = torch.tensor([[[-0.4567, -1.8797, 0.0380, 1.4316]]],
                          dtype=dtype, device=device)
         S = torch.sparse_coo_tensor(i, v)
         S = S.coalesce()
         S.requires_grad_(True)
         S2 = S.coalesce()
         self.assertTrue(S2.is_coalesced())
         return torch._C._WeakTensorRef(S2)

     ref = test_sparse_sum()
     self.assertTrue(ref.expired())


test_coalesce_reference_cycle(SELF, DEVICE, DTYPE)