class_docstr: prompt template is taken from [ChatGPT vs BERT: どちらが日本語をより理解できるのか?](https://fintan.jp/page/9126/)
class_docstr_tok: ["prompt","template","is","taken","from","[","ChatGPT","vs","BERT",":","\u3069\u3061\u3089\u304c\u65e5\u672c\u8a9e\u3092\u3088\u308a\u7406\u89e3\u3067\u304d\u308b\u306e\u304b","?","]","(","https",":","\/\/fintan.jp\/page\/9126\/",")"]
docstr: 質問:question
  選択肢:0.choice0,1.choice1, ...,4.choice4
  回答:
docstr_tok: ["\u8cea\u554f",":","question","\u9078\u629e\u80a2:0.choice0,1.choice1",",","...",",4.choice4","\u56de\u7b54",":"]
code: def doc_to_text(self, doc):
      """
      質問:question
      選択肢:0.choice0,1.choice1, ...,4.choice4
      回答:
      """
      if not self.DID_WARNING:
          warnings.warn(
              "#" * 100
              + "\n\nprompt version `0.2` for JCommonsenseQA tends to output low scores! We highly recommend using `0.2.1` instead!\n\n"
              + "#" * 100
          )
          self.DID_WARNING = True
          time.sleep(5)
      choices = ",".join(
          [
              f"{idx}.{choice}"
              for idx, choice in enumerate(doc["choices"])
          ]
      )
      return f"質問:{doc['goal']}\n" f"選択肢:{choices}\n" "回答:"
  
imports: import os
  import warnings
  import time
  from lm_eval.base import MultipleChoiceTask, rf
  import numpy
label_desc: Use image node_id 1 for calling the JCommonsenseQAWithFintanPrompt obj's underlying member method code with example usage: obj.doc_to_text(doc) and returns: str, doc, str, choices, str