code: def test_top_k_categorical_accuracy(self):
      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]]
      )
      targets = torch.Tensor([0, 3])
      accuracy(predictions, targets)
      actual_accuracy = accuracy.get_metric()
      assert actual_accuracy == 1.0
  
imports: from __future__ import division
  from __future__ import with_statement
  from __future__ import absolute_import
  import torch
  import pytest
  import numpy
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.common.checks import ConfigurationError
  from allennlp.training.metrics import CategoricalAccuracy
label_desc: Use image node_id 2 for calling the CategoricalAccuracyTest obj's underlying member method code with example usage: obj.test_top_k_categorical_accuracy() without return types