code: def test_nans_class(self, params, input_data, expected_value):
      dice_metric = DiceMetric(**params)
      dice_metric(**input_data)
      result, _ = dice_metric.aggregate()
      if isinstance(result, dict):
          self.assertEqual(result, expected_value)
      else:
          np.testing.assert_allclose(
              result.cpu().numpy(), expected_value, atol=1e-4
          )
  
file_path: MONAI/tests/test_compute_meandice.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.metrics import DiceHelper, DiceMetric, compute_dice
label_desc: Use image node_id 5 for calling the TestComputeMeanDice obj's underlying member method code with example usage: obj.test_nans_class(params, input_data, expected_value) without return types