code: def group_by_count(iterable, count, default_value):
      """
      Takes a list and groups it into sublists of size ``count``, using ``default_value`` to pad the
      list at the end if the list is not divisable by ``count``.
  
      For example:
      >>> group_by_count([1, 2, 3, 4, 5, 6, 7], 3, 0)
      [[1, 2, 3], [4, 5, 6], [7, 0, 0]]
  
      This is a short method, but it's complicated and hard to remember as a one-liner, so we just
      make a function out of it.
      """
      return [
          list(l)
          for l in zip_longest(
              *[iter(iterable)] * count, fillvalue=default_value
          )
      ]
  
imports: from __future__ import division
  from __future__ import absolute_import
  import importlib
  import logging
  import pkgutil
  import random
  import subprocess
  import sys
  import os
  import torch
  import numpy
  import spacy
  from spacy.cli.download import download
  from spacy.language import Language
  import allennlp
  from allennlp.common.checks import log_pytorch_version_info
  from allennlp.common.params import Params
  from allennlp.common.tqdm import Tqdm
  from allennlp.common.tee_logger import TeeLogger
label_desc: Use image node_id 2 for calling a global function with example usage: group_by_count(iterable, count, default_value) and returns: unknown