code: def test_serialization(self, tensor_cls, as_param):
      with tempfile.TemporaryFile() as f:
          x = self._create_tensor(tensor_cls)
          if as_param:
              x = nn.Parameter(x)
          torch.save(x, f)
          f.seek(0)
          x_loaded = torch.load(f)
  
          self.assertEqual(x, x_loaded)
          self.assertIsNot(x, x_loaded)
          self.assertIsInstance(x_loaded, tensor_cls)
          if as_param:
              # Serialization should preserve both custom type and "parameter-ness".
              self.assertIsInstance(x_loaded, nn.Parameter)
  
imports: import tempfile
  from copy import deepcopy
  from functools import partial
  from unittest import expectedFailure
  import torch
  from torch import nn
  from torch.nn.modules.lazy import LazyModuleMixin
  from torch.nn.utils.parametrize import register_parametrization, remove_parametrizations
  from torch.testing._internal.common_subclass import DiagTensorBelow, subclass_db
  from torch.testing._internal.common_utils import TestCase, instantiate_parametrized_tests, parametrize, run_tests, skipIfTorchDynamo, subtest
  from torch.testing._internal.logging_tensor import LoggingTensor
  from torch.utils._pytree import tree_map
label_desc: Use image node_id 4 for calling the TestSubclass obj's underlying member method code with example usage: obj.test_serialization(tensor_cls, as_param) without return types