class_docstr: prompt format was inspired by [日本語に特化した60億パラメータ規模のGPTモデルの構築と評価](https://www.anlp.jp/proceedings/annual_meeting/2023/pdf_dir/H9-4.pdf)
docstr: [問題]:question
  [選択肢]:[choice0, choice1, ..., choice4]
  [答え]:
docstr_tok: ["[","\u554f\u984c","]",":","question","[","\u9078\u629e\u80a2","]",":","[","choice0",",","choice1",",","...",",","choice4","]","[","\u7b54\u3048","]",":"]
code: def doc_to_qa_prompt(self, doc):
      """
      [問題]:question
      [選択肢]:[choice0, choice1, ..., choice4]
      [答え]:
      """
      return (
          f"[質問]:{doc['goal']}\n"
          + f"[選択肢]:[{', '.join(doc['choices'])}]\n"
          "[答え]:"
      )
  
imports: import os
  import inspect
  import datasets
  from lm_eval.base import MultipleChoiceTask, rf
  import numpy
label_desc: Use image node_id 9 for calling the JAQKETV1 obj's underlying member method code with example usage: obj.doc_to_qa_prompt(doc) and returns: unknown