code: def test_set_map_across(self, device_0, device_1):
      set_determinism(0)
      model_one = _TestModelOne(10, 10, 3)
      model_two = _TestModelTwo(10, 10, 10, 4)
      model_one.to(device_0)
      model_two.to(device_1)
      # test weight map
      model_dict, ch, unch = copy_model_state(
          model_one,
          model_two,
          mapping={
              "layer_1.weight": "layer.weight",
              "layer_1.bias": "layer_1.weight",
          },
      )
      model_one.load_state_dict(model_dict)
      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(
          [
              [0.8244487, -0.19650555, 0.65723234],
              [0.71239626, 0.25617486, 0.5247122],
              [0.24168758, 1.0301148, 0.39089814],
              [0.25791705, 0.8653245, 0.14833644],
          ]
      )
      np.testing.assert_allclose(output, expected, atol=1e-3)
      self.assertEqual(len(ch), 2)
      self.assertEqual(len(unch), 2)
  
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 5 for calling the TestModuleState obj's underlying member method code with example usage: obj.test_set_map_across(device_0, device_1) without return types