code: def test_multiple_distributed_runs(self):
      predictions = [
          torch.tensor([[0.35, 0.25, 0.1, 0.1, 0.2]]),
          torch.tensor([[0.1, 0.6, 0.1, 0.2, 0.0]]),
      ]
      targets = [torch.tensor([0]), torch.tensor([3])]
      metric_kwargs = {
          "predictions": predictions,
          "gold_labels": targets,
      }
      desired_accuracy = 0.5
      run_distributed_test(
          [-1, -1],
          global_distributed_metric,
          CategoricalAccuracy(),
          metric_kwargs,
          desired_accuracy,
          exact=True,
          number_of_runs=200,
      )
  
imports: import pytest
  import torch
  from torch.testing import assert_allclose
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase, multi_device, global_distributed_metric, run_distributed_test
  from allennlp.training.metrics import CategoricalAccuracy
label_desc: Use image node_id 13 for calling the CategoricalAccuracyTest obj's underlying member method code with example usage: obj.test_multiple_distributed_runs() without return types