



import argparse
import json

from tqdm import tqdm






def 			lowerCAmelCase__	(					):





    '''simple docstring'''

    lowerCAmelCase__  :       int				=  argparse.ArgumentParser()

    # Required parameters
    parser.add_argument(
        '''--src_path''' ,type=lowerCamelCase_ ,default='''biencoder-nq-dev.json''' ,help='''Path to raw DPR training data''' ,)
    parser.add_argument(
        '''--evaluation_set''' ,type=lowerCamelCase_ ,help='''where to store parsed evaluation_set file''' ,)
    parser.add_argument(
        '''--gold_data_path''' ,type=lowerCamelCase_ ,help='''where to store parsed gold_data_path file''' ,)
    lowerCAmelCase__  :       str				=  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__  :       Optional[Any]				=  json.load(lowerCamelCase_)
        for dpr_record in tqdm(lowerCamelCase_):
            lowerCAmelCase__  :       Optional[Any]				=  dpr_record['''question''']
            lowerCAmelCase__  :       Dict				=  [context['''title'''] for context in dpr_record['''positive_ctxs''']]
            eval_file.write(question + '''\n''')
            gold_file.write('''\t'''.join(lowerCamelCase_) + '''\n''')


if __name__ == "__main__":
       main()






import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case       :	Any            =logging.get_logger(__name__)



class  lowerCamelCase__    (							lowerCamelCase__):




		'''simple docstring'''



		snake_case_			="""encoder-decoder"""
		snake_case_			=True



		def __init__(self	,**__lowerCamelCase				)  ->    Union[str, Any]:

						"""simple docstring"""






						super().__init__(**__lowerCamelCase				)
						assert (
						    "encoder" in kwargs and "decoder" in kwargs
						), "Config has to be initialized with encoder and decoder config"
						lowerCAmelCase__  :       Optional[Any]				=  kwargs.pop('''encoder'''				)
						lowerCAmelCase__  :       Any				=  encoder_config.pop('''model_type'''				)
						lowerCAmelCase__  :       str				=  kwargs.pop('''decoder'''				)
						lowerCAmelCase__  :       Tuple				=  decoder_config.pop('''model_type'''				)

						from ..auto.configuration_auto import AutoConfig

						lowerCAmelCase__  :       Tuple				=  AutoConfig.for_model(__lowerCamelCase	,**__lowerCamelCase				)
						lowerCAmelCase__  :       Any				=  AutoConfig.for_model(__lowerCamelCase	,**__lowerCamelCase				)
						lowerCAmelCase__  :       str				=  True



		@classmethod
		def 	lowerCAmelCase__   (cls	,__lowerCamelCase	,__lowerCamelCase	,**__lowerCamelCase				)  ->    PretrainedConfig:

						"""simple docstring"""






						logger.info('''Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'''				)
						lowerCAmelCase__  :       Optional[int]				=  True
						lowerCAmelCase__  :       List[str]				=  True

						return cls(encoder=encoder_config.to_dict()	,decoder=decoder_config.to_dict()	,**__lowerCamelCase				)



		def 	lowerCAmelCase__   (self				)  ->    Tuple:

						"""simple docstring"""






						lowerCAmelCase__  :       int				=  copy.deepcopy(self.__dict__				)
						lowerCAmelCase__  :       Optional[Any]				=  self.encoder.to_dict()
						lowerCAmelCase__  :       str				=  self.decoder.to_dict()
						lowerCAmelCase__  :       Optional[int]				=  self.__class__.model_type
						return output

