code: def test_flatten_unflatten_return_types(self, pytree_impl, op):
      x = torch.randn(3, 3)
      expected = op(x, dim=0)
  
      values, spec = pytree_impl.tree_flatten(expected)
      # Check that values is actually List[Tensor] and not (ReturnType(...),)
      for value in values:
          self.assertIsInstance(value, torch.Tensor)
      result = pytree_impl.tree_unflatten(values, spec)
  
      self.assertEqual(type(result), type(expected))
      self.assertEqual(result, expected)
  
imports: import inspect
  import re
  import unittest
  from collections import defaultdict, deque, namedtuple, OrderedDict, UserDict
  import torch
  import torch.utils._pytree
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, IS_FBCODE, parametrize, run_tests, subtest, TEST_WITH_TORCHDYNAMO, TestCase
label_desc: Use image node_id 11 for calling the TestGenericPytree obj's underlying member method code with example usage: obj.test_flatten_unflatten_return_types(pytree_impl, op) without return types