code: def test_distributed_accuracy_unequal_batches(self):
      predictions = [
          torch.tensor([[0, 1], [2, 3], [4, 5]]),
          torch.tensor([[6, 7]]),
      ]
      targets = [
          torch.tensor([[0, 1], [2, 2], [4, 5]]),
          torch.tensor([[7, 7]]),
      ]
      metric_kwargs = {
          "predictions": predictions,
          "gold_labels": targets,
      }
      desired_values = 0.5
      run_distributed_test(
          [-1, -1],
          global_distributed_metric,
          BooleanAccuracy(),
          metric_kwargs,
          desired_values,
          exact=True,
      )
  
file_path: allennlp/tests/training/metrics/boolean_accuracy_test.py
imports: from typing import Any, Dict, List, Tuple, Union
  import torch
  import pytest
  from allennlp.common.testing import AllenNlpTestCase, multi_device, global_distributed_metric, run_distributed_test
  from allennlp.training.metrics import BooleanAccuracy
label_desc: Use image node_id 7 for calling the BooleanAccuracyTest obj's underlying member method code with example usage: obj.test_distributed_accuracy_unequal_batches() without return types