code: def test_independence_with_wasserstein_distance(self):
      independence = Independence(4, 2, "wasserstein")
      A = torch.eye(3).long()
      C = 2 * A
  
      expected_distances = {0: 0.6667, 1: 1.3333}
  
      independence(C, A)
      test_distances = {
          k: v.item()
          for k, v in independence.get_metric(reset=True).items()
      }
      assert expected_distances == pytest.approx(
          test_distances, abs=1e-3
      )
  
imports: import pytest
  import torch
  import math
  import numpy
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase, multi_device, global_distributed_metric, run_distributed_test
  from allennlp.fairness.fairness_metrics import Independence, Separation, Sufficiency
label_desc: Use image node_id 4 for calling the IndependenceTest obj's underlying member method code with example usage: obj.test_independence_with_wasserstein_distance() without return types