code: def score_logits(logits, tags, transitions, boundary_values):
      """Computes the likelihood score for the given sequence of tags, given
      the provided logits (and the transition weights in the CRF model)
      """
      # Start with transitions from START and to END
      total = boundary_values[tags[0]] + boundary_values[tags[-1]]
      # Add in all the intermediate transitions
      for tag, next_tag in zip(tags, tags[1:]):
          total += transitions[tag, next_tag]
      # Add in the logits for the observed tags
      for logit, tag in zip(logits, tags):
          total += logit[tag]
      return total
  
imports: import itertools
  import os
  import math
  import tempfile
  import pytest
  import numpy
  import tensorflow
  from tensorflow_addons.layers.crf import CRF
  from tensorflow_addons.text.crf import crf_log_likelihood
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 15 for calling a global function with example usage: score_logits(logits, tags, transitions, boundary_values) and returns: total