code: def test_distributed_sufficiency_masked_computation(self):
      C = torch.zeros(3, 3).long()
      Y = torch.eye(3).long()
      A = Y
      mask = torch.ones_like(C).bool()
  
      expected_kl_divs = {
          0: {0: 0.4055, 1: 1.0986},
          1: {0: np.nan, 1: np.nan},
      }
      metric_kwargs = {
          "predicted_labels": C,
          "gold_labels": Y,
          "protected_variable_labels": A,
          "mask": mask,
      }
      run_distributed_test(
          [-1, -1],
          global_distributed_metric,
          Sufficiency(2, 2),
          metric_kwargs,
          expected_kl_divs,
          exact=False,
      )
  
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 SufficiencyTest obj's underlying member method code with example usage: obj.test_distributed_sufficiency_masked_computation() without return types