class_docstr: prompt format is taken from [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)
class_docstr_tok: ["prompt","format","is","taken","from","[","\u65e5\u672c\u8a9e\u306b\u7279\u5316\u3057\u305f60\u5104\u30d1\u30e9\u30e1\u30fc\u30bf\u898f\u6a21\u306eGPT\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9\u3068\u8a55\u4fa1","]","(","https",":","\/\/www.anlp.jp\/proceedings\/annual_meeting\/2023\/pdf_dir\/H9-4.pdf",")"]
code: def training_docs(self):
      if self._training_docs is None:
          self._training_docs = list(
              map(self._process_doc, self.dataset["train"])
          )
      return self._training_docs
  
imports: import os
  import warnings
  import time
  from lm_eval.base import MultipleChoiceTask, rf
  import numpy
label_desc: Use image node_id 4 for calling the JCommonsenseQA obj's underlying member method code with example usage: obj.training_docs() and returns: self