code: def test_viterbi_tags(self):
      mask = torch.tensor([[True, True, True], [True, False, True]])
  
      viterbi_path = self.crf.viterbi_tags(self.logits, mask)
  
      # Separate the tags and scores.
      viterbi_tags = [x for x, y in viterbi_path]
      viterbi_scores = [y for x, y in viterbi_path]
  
      most_likely_tags, best_scores = self.naive_most_likely_sequence(
          self.logits, mask
      )
  
      assert viterbi_tags == most_likely_tags
      assert_allclose(viterbi_scores, best_scores, rtol=1e-5)
  
imports: import itertools
  import math
  from pytest import approx, raises
  import torch
  from numpy.testing import assert_allclose
  from allennlp.modules import ConditionalRandomField
  from allennlp.modules.conditional_random_field import ConditionalRandomFieldWeightEmission, ConditionalRandomFieldWeightTrans, ConditionalRandomFieldWeightLannoy
  from allennlp.modules.conditional_random_field.conditional_random_field import allowed_transitions
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase
label_desc: Use image node_id 6 for calling the TestConditionalRandomField obj's underlying member method code with example usage: obj.test_viterbi_tags() without return types