



"""simple docstring"""





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


lowercase					=       logging.get_logger(__name__)

lowercase					=       {
    'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
    # See all Cvt models at https://huggingface.co/models?filter=cvt
}




class       lowercase__      (   _lowerCamelCase     ):
							'''simple docstring'''







							_UpperCAmelCase   					=       '''cvt'''






							def __init__(	self						,							snake_case=3						,							snake_case=[7, 3, 3]						,							snake_case=[4, 2, 2]						,							snake_case=[2, 1, 1]						,							snake_case=[64, 192, 384]						,							snake_case=[1, 3, 6]						,							snake_case=[1, 2, 10]						,							snake_case=[4.0, 4.0, 4.0]						,							snake_case=[0.0, 0.0, 0.0]						,							snake_case=[0.0, 0.0, 0.0]						,							snake_case=[0.0, 0.0, 0.1]						,							snake_case=[True, True, True]						,							snake_case=[False, False, True]						,							snake_case=["dw_bn", "dw_bn", "dw_bn"]						,							snake_case=[3, 3, 3]						,							snake_case=[1, 1, 1]						,							snake_case=[2, 2, 2]						,							snake_case=[1, 1, 1]						,							snake_case=[1, 1, 1]						,							snake_case=0.02						,							snake_case=1E-12						,							**snake_case						,							)      ->				List[str]:
									super().__init__(**_SCREAMING_SNAKE_CASE    )
									_UpperCAmelCase							=		num_channels
									_UpperCAmelCase							=		patch_sizes
									_UpperCAmelCase							=		patch_stride
									_UpperCAmelCase							=		patch_padding
									_UpperCAmelCase							=		embed_dim
									_UpperCAmelCase							=		num_heads
									_UpperCAmelCase							=		depth
									_UpperCAmelCase							=		mlp_ratio
									_UpperCAmelCase							=		attention_drop_rate
									_UpperCAmelCase							=		drop_rate
									_UpperCAmelCase							=		drop_path_rate
									_UpperCAmelCase							=		qkv_bias
									_UpperCAmelCase							=		cls_token
									_UpperCAmelCase							=		qkv_projection_method
									_UpperCAmelCase							=		kernel_qkv
									_UpperCAmelCase							=		padding_kv
									_UpperCAmelCase							=		stride_kv
									_UpperCAmelCase							=		padding_q
									_UpperCAmelCase							=		stride_q
									_UpperCAmelCase							=		initializer_range
									_UpperCAmelCase							=		layer_norm_eps







"""simple docstring"""

import argparse
import json

from tqdm import tqdm
def  __snake_case							(	)     ->       Any:






				'''simple docstring'''
				SCREAMING_SNAKE_CASE						:							str							=     argparse.ArgumentParser()

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


if __name__ == "__main__":
							main()





