code: def test_skips_completely_masked_instances(self, device: str):
      accuracy = BooleanAccuracy()
      predictions = torch.tensor(
          [[0, 1], [2, 3], [4, 5], [6, 7]], device=device
      )
      targets = torch.tensor(
          [[0, 1], [2, 2], [4, 5], [7, 7]], device=device
      )
  
      mask = torch.tensor(
          [[False, False], [True, False], [True, True], [True, True]],
          device=device,
      )
      accuracy(predictions, targets, mask)
  
      # First example should be skipped, second is correct with mask, third is correct, fourth is wrong.
      assert accuracy.get_metric() == 2 / 3
  
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 2 for calling the BooleanAccuracyTest obj's underlying member method code with example usage: obj.test_skips_completely_masked_instances(device) without return types