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: import json
  import os
  import torch
  from pathlib import Path
  import pickle
  import logging
  import collections
  from io import open
  import shutil
  from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
  from torch.utils.data.distributed import DistributedSampler
  from transformers.tokenization_bert import BasicTokenizer, whitespace_tokenize
  from transformers import WEIGHTS_NAME, BertTokenizer, XLNetTokenizer, DistilBertTokenizer
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