code: def test_top_k_categorical_accuracy_respects_mask(self, device: str):
      accuracy = CategoricalAccuracy(top_k=2)
      predictions = torch.tensor(
          [
              [0.35, 0.25, 0.1, 0.1, 0.2],
              [0.1, 0.6, 0.1, 0.2, 0.0],
              [0.1, 0.2, 0.5, 0.2, 0.0],
          ],
          device=device,
      )
      targets = torch.tensor([0, 3, 0], device=device)
      mask = torch.tensor([False, True, True], device=device)
      accuracy(predictions, targets, mask)
      actual_accuracy = accuracy.get_metric()
      assert_allclose(actual_accuracy, 0.50)
  
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 4 for calling the CategoricalAccuracyTest obj's underlying member method code with example usage: obj.test_top_k_categorical_accuracy_respects_mask(device) without return types