code: def test_difference_with_torch(self):
      model = Model()
      torch.save(model.state_dict(), "tmp2.bin")
  
      model2 = NoSharedModel()
      # This passes on torch.
      # The tensors are shared on disk, they are *not* shared within the model
      # The model happily loads the tensors, and ends up *not* sharing the tensors by.
      # doing copies
      self.assertEqual(
          _find_shared_tensors(model2.state_dict()),
          [{"a.weight"}, {"a.bias"}, {"b.weight"}, {"b.bias"}],
      )
      model2.load_state_dict(torch.load("tmp2.bin"))
      self.assertEqual(
          _find_shared_tensors(model2.state_dict()),
          [{"a.weight"}, {"a.bias"}, {"b.weight"}, {"b.bias"}],
      )
  
      # However safetensors cannot save those, so we cannot
      # reload the saved file with the different model
      save_model(model, "tmp2.safetensors")
      with self.assertRaises(RuntimeError) as ctx:
          load_model(model2, "tmp2.safetensors")
      self.assertIn(
          """Missing key(s) in state_dict: "b.bias", "b.weight""",
          str(ctx.exception),
      )
  
imports: import copy
  import unittest
  import torch
  from safetensors import safe_open
  from safetensors.torch import _end_ptr, _find_shared_tensors, _is_complete, _remove_duplicate_names, load_model, save_file, save_model
label_desc: Use image node_id 12 for calling the TorchModelTestCase obj's underlying member method code with example usage: obj.test_difference_with_torch() without return types