





import argparse
import json

from tqdm import tqdm





def      _lowercase					(						)						->  Optional[Any]:
				lowerCamelCase	 =argparse.ArgumentParser()

				# Required parameters
				parser.add_argument(
				    """--src_path"""			,      type=_UpperCAmelCase			,      default="""biencoder-nq-dev.json"""			,      help="""Path to raw DPR training data"""			,      )
				parser.add_argument(
				    """--evaluation_set"""			,      type=_UpperCAmelCase			,      help="""where to store parsed evaluation_set file"""			,      )
				parser.add_argument(
				    """--gold_data_path"""			,      type=_UpperCAmelCase			,      help="""where to store parsed gold_data_path file"""			,      )
				lowerCamelCase	 =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:
								lowerCamelCase	 =json.load(_UpperCAmelCase				)
								for dpr_record in tqdm(_UpperCAmelCase				):
												lowerCamelCase	 =dpr_record["""question"""]
												lowerCamelCase	 =[context["""title"""] for context in dpr_record["""positive_ctxs"""]]
												eval_file.write(question + """\n"""				)
												gold_file.write("""\t""".join(_UpperCAmelCase				) + """\n"""				)


if __name__ == "__main__":
							main()












def      _lowercase					(						_UpperCAmelCase			,      _UpperCAmelCase				)						->  list[str]:
				return [sentence[i : i + ngram_size] for i in range(len(_UpperCAmelCase				) - ngram_size + 1				)]


if __name__ == "__main__":
							from doctest import testmod

							testmod()





