






"""simple docstring"""



import warnings

from ..trainer import Trainer
from ..utils import logging


_UpperCamelCase		:  Union[str, Any]						=		logging.get_logger(__name__)

class        a     (   a_	):







    def __init__(			self							,		_lowerCamelCase=None							,		**_lowerCamelCase       ):
      warnings.warn(
          '`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` '
          'instead.'							,		_lowerCamelCase							,		)
      super().__init__(args=_lowerCamelCase							,		**_lowerCamelCase       )










"""simple docstring"""



import argparse
import json

from tqdm import tqdm
def 						_SCREAMING_SNAKE_CASE (    ):





  '''simple docstring'''





  lowercase							    =       argparse.ArgumentParser()

  # Required parameters
  parser.add_argument(
      '--src_path'		,					type=__snake_case		,					default='biencoder-nq-dev.json'		,					help='Path to raw DPR training data'		,					)
  parser.add_argument(
      '--evaluation_set'		,					type=__snake_case		,					help='where to store parsed evaluation_set file'		,					)
  parser.add_argument(
      '--gold_data_path'		,					type=__snake_case		,					help='where to store parsed gold_data_path file'		,					)
  lowercase							    =       parser.parse_args()

  with open(args.src_path		,					'r'    ) as src_file, open(args.evaluation_set		,					'w'    ) as eval_file, open(
      args.gold_data_path		,					'w'    ) as gold_file:
    lowercase							    =       json.load(__snake_case    )
    for dpr_record in tqdm(__snake_case    ):
      lowercase							    =       dpr_record['question']
      lowercase							    =       [context['title'] for context in dpr_record['positive_ctxs']]
      eval_file.write(question + '\n'    )
      gold_file.write('\t'.join(__snake_case    ) + '\n'    )


if __name__ == "__main__":
    main()


