code: def _check_is_max_context(doc_spans, cur_span_index, position):
      """Check if this is the 'max context' doc span for the token."""
  
      # Because of the sliding window approach taken to scoring documents, a single
      # token can appear in multiple documents. E.g.
      #  Doc: the man went to the store and bought a gallon of milk
      #  Span A: the man went to the
      #  Span B: to the store and bought
      #  Span C: and bought a gallon of
      #  ...
      #
      # Now the word 'bought' will have two scores from spans B and C. We only
      # want to consider the score with "maximum context", which we define as
      # the *minimum* of its left and right context (the *sum* of left and
      # right context will always be the same, of course).
      #
      # In the example the maximum context for 'bought' would be span C since
      # it has 1 left context and 3 right context, while span B has 4 left context
      # and 0 right context.
      best_score = None
      best_span_index = None
      for span_index, doc_span in enumerate(doc_spans):
          end = doc_span.start + doc_span.length - 1
          if position < doc_span.start:
              continue
          if position > end:
              continue
          num_left_context = position - doc_span.start
          num_right_context = end - position
          score = (
              min(num_left_context, num_right_context)
              + 0.01 * doc_span.length
          )
          if best_score is None or score > best_score:
              best_score = score
              best_span_index = span_index
  
      return cur_span_index == best_span_index
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import json
  import math
  import os
  import random
  import mesh_tensorflow
  import mesh_tensorflow.bert.bert
  import mesh_tensorflow.bert.optimization
  import mesh_tensorflow.bert.tokenization
  import six
  from six.moves import range
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 4 for calling a global function with example usage: _check_is_max_context(doc_spans, cur_span_index, position) and returns: unknown