code: def normalize_answer(s):
      """Lower text and remove punctuation, articles and extra whitespace."""
  
      def remove_articles(text):
          return re.sub(r"\b(a|an|the)\b", " ", text)
  
      def white_space_fix(text):
          return " ".join(text.split())
  
      def remove_punc(text):
          exclude = set(string.punctuation)
          return "".join(ch for ch in text if ch not in exclude)
  
      def lower(text):
          return text.lower()
  
      return white_space_fix(remove_articles(remove_punc(lower(s))))
  
imports: import itertools
  import json
  import linecache
  import os
  import pickle
  import re
  import socket
  import string
  from collections import Counter
  from logging import getLogger
  from pathlib import Path
  from typing import Callable, Dict, Iterable, List
  import git
  import torch
  from torch.utils.data import Dataset
  from transformers import BartTokenizer, RagTokenizer, T5Tokenizer
label_desc: Use image node_id 10 for calling a global function with example usage: normalize_answer(s) and returns: white_space_fix, re, str, str, text