code: def test_type_propagation(self, tensor_cls, as_param):
      x = self._create_tensor(tensor_cls)
      if as_param:
          x = nn.Parameter(x)
  
      # Call the add operator to produce an output tensor.
      output = x + self._create_tensor(torch.Tensor)
  
      # Custom type should be propagated across operations if closed under the op, but
      # "parameter-ness" should not be.
      if subclass_db[tensor_cls].closed_under_ops:
          self.assertIsInstance(output, tensor_cls)
      else:
          self.assertIsInstance(output, torch.Tensor)
      self.assertNotIsInstance(output, 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 6 for calling the TestSubclass obj's underlying member method code with example usage: obj.test_type_propagation(tensor_cls, as_param) without return types