code: def test_distributed_nli(self):
      nli_probabilities = 0.6 * torch.eye(3)
      expected_scores = {
          "net_neutral": 0.6 / 3,
          "fraction_neutral": 1 / 3,
          "threshold_0.5": 1 / 3,
          "threshold_0.7": 0.0,
      }
      metric_kwargs = {
          "nli_probabilities": [nli_probabilities, nli_probabilities]
      }
      run_distributed_test(
          [-1, -1],
          global_distributed_metric,
          NaturalLanguageInference(0),
          metric_kwargs,
          expected_scores,
          exact=False,
      )
  
imports: import pytest
  import torch
  import json
  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.bias_metrics import WordEmbeddingAssociationTest, EmbeddingCoherenceTest, NaturalLanguageInference, AssociationWithoutGroundTruth
label_desc: Use image node_id 3 for calling the NaturalLanguageInferenceTest obj's underlying member method code with example usage: obj.test_distributed_nli() without return types