code: def test_constrained_viterbi_tags(self):
      constraints = {
          (0, 0),
          (0, 1),
          (1, 1),
          (1, 2),
          (2, 2),
          (2, 3),
          (3, 3),
          (3, 4),
          (4, 4),
          (4, 0),
      }
  
      # Add the transitions to the end tag
      # and from the start tag.
      for i in range(5):
          constraints.add((5, i))
          constraints.add((i, 6))
  
      crf = ConditionalRandomField(num_tags=5, constraints=constraints)
      crf.transitions = torch.nn.Parameter(self.transitions)
      crf.start_transitions = torch.nn.Parameter(
          self.transitions_from_start
      )
      crf.end_transitions = torch.nn.Parameter(self.transitions_to_end)
  
      mask = torch.tensor([[True, True, True], [True, True, False]])
  
      viterbi_path = crf.viterbi_tags(self.logits, mask)
  
      # Get just the tags from each tuple of (tags, score).
      viterbi_tags = [x for x, y in viterbi_path]
  
      # Now the tags should respect the constraints
      assert viterbi_tags == [[2, 3, 3], [2, 3]]
  
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 9 for calling the TestConditionalRandomField obj's underlying member method code with example usage: obj.test_constrained_viterbi_tags() without return types