code: def extract_text(prompt, remove_lines=True):
      token = '"""'
      start = token
      end = ">>>"
  
      start_idx = prompt.find(start) + len(start)
      end_idx = prompt.find(end)
  
      output = prompt[start_idx:end_idx]
      if remove_lines:
          output = output.replace("\n", " ")
      output = re.sub(r"\s+", " ", output).strip()
  
      return output
  
file_path: codet5/CodeT5+/humaneval/generate_codet5p.py
imports: import argparse
  import pprint
  import os
  import re
  from tqdm import tqdm
  import torch
  from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
  from human_eval.data import write_jsonl, read_problems, stream_jsonl
label_desc: Use image node_id 1 for calling a global function with example usage: extract_text(prompt, remove_lines) and returns: output