code: def test_cuda_value(self):
      img = torch.stack(
          [torch.ones(2, 2, 2, 2), torch.ones(2, 2, 2, 2) + 2]
      )
      expected_value = torch.ones(2, 2, 2, 2) * torch.tensor(
          [2.5, 1.5]
      ).reshape(1, 2, 1, 1)
      if torch.cuda.is_available():
          img = img.to(torch.device("cuda:0"))
          expected_value = expected_value.to(torch.device("cuda:0"))
      result = MeanEnsemble(torch.tensor([[[1, 3]], [[3, 1]]]))(img)
      assert_allclose(result, expected_value)
  
file_path: MONAI/tests/test_mean_ensemble.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.transforms import MeanEnsemble
  from tests.utils import TEST_NDARRAYS, assert_allclose
label_desc: Use image node_id 2 for calling the TestMeanEnsemble obj's underlying member method code with example usage: obj.test_cuda_value() without return types