



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


__UpperCAmelCase          =       logging.get_logger(__name__)

# TODO: upload to AWS
__UpperCAmelCase          =       {
    '''yjernite/retribert-base-uncased''': (
        '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json'''
    ),
}



class 				lowerCAmelCase_		(  a__							):
       UpperCAmelCase__				:					str        =  "retribert"
       def __init__(			self,			SCREAMING_SNAKE_CASE_=3_0522,			SCREAMING_SNAKE_CASE_=768,			SCREAMING_SNAKE_CASE_=8,			SCREAMING_SNAKE_CASE_=12,			SCREAMING_SNAKE_CASE_=3072,			SCREAMING_SNAKE_CASE_="gelu",			SCREAMING_SNAKE_CASE_=0.1,			SCREAMING_SNAKE_CASE_=0.1,			SCREAMING_SNAKE_CASE_=512,			SCREAMING_SNAKE_CASE_=2,			SCREAMING_SNAKE_CASE_=0.02,			SCREAMING_SNAKE_CASE_=1e-12,			SCREAMING_SNAKE_CASE_=True,			SCREAMING_SNAKE_CASE_=128,			SCREAMING_SNAKE_CASE_=0,			**SCREAMING_SNAKE_CASE_,			)     ->		Optional[int]:
          super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_,			**SCREAMING_SNAKE_CASE_       )

          UpperCamelCase    :  List[str]							=	vocab_size
          UpperCamelCase    :  Optional[int]							=	hidden_size
          UpperCamelCase    :  str							=	num_hidden_layers
          UpperCamelCase    :  Optional[Any]							=	num_attention_heads
          UpperCamelCase    :  Optional[int]							=	hidden_act
          UpperCamelCase    :  Dict							=	intermediate_size
          UpperCamelCase    :  List[str]							=	hidden_dropout_prob
          UpperCamelCase    :  int							=	attention_probs_dropout_prob
          UpperCamelCase    :  List[Any]							=	max_position_embeddings
          UpperCamelCase    :  List[Any]							=	type_vocab_size
          UpperCamelCase    :  Any							=	initializer_range
          UpperCamelCase    :  str							=	layer_norm_eps
          UpperCamelCase    :  Tuple							=	share_encoders
          UpperCamelCase    :  Union[str, Any]							=	projection_dim








import argparse
import json

from tqdm import tqdm
def 		UpperCamelCase	(   )	->     Optional[int]:
   UpperCamelCase    :  List[Any]							=	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'       ,     )
   UpperCamelCase    :  int							=	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:
      UpperCamelCase    :  int							=	json.load(snake_case__	)
      for dpr_record in tqdm(snake_case__	):
         UpperCamelCase    :  Union[str, Any]							=	dpr_record['question']
         UpperCamelCase    :  Dict							=	[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()



