code: def parse_file(filename):
      with codecs.open(filename, encoding="ISO-8859-2") as file:
          file_content = file.readlines()
      questions = []
      last_question = None
      inside_question = False
      correct_answer = None
      for line in file_content:
          line = line.rstrip()
          if line == "":
              continue
          elif line[0] == "#":
              if last_question is not None:
                  last_question["correct_answer"] = last_question[
                      "answers"
                  ].index(correct_answer)
                  questions.append(last_question)
  
              last_question = {
                  "content": line[3:],
                  "answers": [],
              }
              inside_question = True
          elif line[0] == "^":
              correct_answer = line[2:]
              inside_question = False
          elif (
              line[0] == "A"
              or line[0] == "B"
              or line[0] == "C"
              or line[0] == "D"
          ):
              last_question["answers"].append(line[2:])
          elif inside_question:
              last_question["content"] += "\n" + line
          elif line.strip() != "":
              raise Exception(
                  "Can't parse line in file {0}: {1}".format(
                      filename, line
                  )
              )
  
      if last_question is not None:
          last_question["correct_answer"] = last_question[
              "answers"
          ].index(correct_answer)
          questions.append(last_question)
      return questions
  
file_path: finetune/finetune/datasets/multi_choice_qna.py
imports: import json
  import os
  import codecs
  import random
  import requests
  from pathlib import Path
  import finetune
  from finetune import MultipleChoice
  from sklearn.model_selection import train_test_split
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: parse_file(filename) and returns: questions