code: def flatten_json(file, proc_func):
      """A multi-processing wrapper for loading SQuAD data file."""
      with open(file) as f:
          data = json.load(f)["data"]
      with ProcessPoolExecutor(max_workers=args.threads) as executor:
          rows = executor.map(proc_func, data)
      rows = sum(rows, [])
      return rows
  
imports: import re
  import json
  import spacy
  import msgpack
  import unicodedata
  import numpy
  import pandas
  import argparse
  import collections
  import multiprocessing
  from concurrent.futures import ProcessPoolExecutor
  import logging
label_desc: Use image node_id 3 for calling a global function with example usage: flatten_json(file, proc_func) and returns: rows