code: def filter_answers(answers_dset, min_occurence):
      """This will change the answer to preprocessed version"""
      occurence = {}
      answer_list = []
      evalai_answer_processor = EvalAIAnswerProcessor()
      for ans_entry in answers_dset:
          gtruth = ans_entry["multiple_choice_answer"]
          gtruth = evalai_answer_processor(gtruth)
          if gtruth not in occurence:
              occurence[gtruth] = set()
          occurence[gtruth].add(ans_entry["question_id"])
      for answer in occurence.keys():
          if len(occurence[answer]) >= min_occurence:
              answer_list.append(answer)
  
      print(
          "Num of answers that appear >= %d times: %d"
          % (min_occurence, len(answer_list))
      )
      return answer_list
  
imports: import argparse
  import json
  import os
  from mmf.datasets.processors.processors import EvalAIAnswerProcessor
label_desc: Use image node_id 3 for calling a global function with example usage: filter_answers(answers_dset, min_occurence) and returns: answer_list