code: def read_prediction(prediction_file):
      prediction_list = []
      print("reading %s" % prediction_file)
      with open(prediction_file, "r") as f:
          for i, line in enumerate(tqdm(f)):
              if prediction_file.endswith("jsonl"):
                  line = json.loads(line)["pred"]
                  # print(line)
              line = line.replace("Answer:", "")
              line = line.replace("Answer: ", "")
              line = line.replace("????  ", "")
              line = line.replace("A: ", "")
              line = line.replace("A:", "")
  
              line = line.strip()
  
              if "<|endoftext|>" in line:
                  line = line.replace("<|endoftext|>", "")
              line = normalize_answer(line)  # normalize the answer
              prediction_list.append(line)
  
      return prediction_list
  
file_path: megatron-lm/tools/retro/text_generation/evaluate.py
imports: import sys
  import os
  from tqdm import tqdm
  import string
  import json
  import regex
  import numpy
  from tools.retro.text_generation.metrics import F1Metric
label_desc: Use image node_id 4 for calling a global function with example usage: read_prediction(prediction_file) and returns: prediction_list