code: def test_set_exclude_vars(self, device_0, device_1):
      set_determinism(0)
      model_one = _TestModelOne(10, 20, 3)
      model_two = _TestModelTwo(10, 20, 10, 4)
      model_one.to(device_0)
      model_two.to(device_1)
      # test skip layer.bias
      model_dict, ch, unch = copy_model_state(
          model_one, model_two, exclude_vars="layer.bias"
      )
      x = np.random.randn(4, 10)
      x = torch.tensor(x, device=device_0, dtype=torch.float32)
      output = model_one(x).detach().cpu().numpy()
      expected = np.array(
          [
              [-0.34172416, 0.0375042, -0.98340976],
              [-0.03364138, -0.08927619, -0.2246768],
              [-0.35700908, -0.15556987, -0.27658707],
              [0.61680925, -0.6106281, -0.02123314],
          ]
      )
      np.testing.assert_allclose(output, expected, atol=1e-3)
      self.assertEqual(len(ch), 1)
      self.assertEqual(len(unch), 3)
  
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.networks.utils import copy_model_state
  from monai.utils import set_determinism
label_desc: Use image node_id 4 for calling the TestModuleState obj's underlying member method code with example usage: obj.test_set_exclude_vars(device_0, device_1) without return types