from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin



class  UpperCamelCase				( UpperCamelCase_   ,  UpperCamelCase_ ):

					'''simple docstring'''

					@register_to_config
					def __init__(					self				,				A_ = 7_68				,				) ->				Optional[Any]:






											"""simple docstring"""
											super().__init__()

											_lowerCamelCase			    =				nn.Parameter(torch.zeros(1				,				_a						)						)
											_lowerCamelCase			    =				nn.Parameter(torch.ones(1				,				_a						)						)



					def 		UpperCamelCase_						(					self				,				A_ = None				,				A_ = None				,				) ->				str:






											"""simple docstring"""
											_lowerCamelCase			    =				nn.Parameter(self.mean.to(_a						).to(_a						)						)
											_lowerCamelCase			    =				nn.Parameter(self.std.to(_a						).to(_a						)						)
											return self



					def 		UpperCamelCase_						(					self				,				A_						) ->				Optional[Any]:






											"""simple docstring"""
											_lowerCamelCase			    =				(embeds - self.mean) * 1.0 / self.std
											return embeds





					def 		UpperCamelCase_						(					self				,				A_						) ->				Union[str, Any]:






											"""simple docstring"""
											_lowerCamelCase			    =				(embeds * self.std) + self.mean
											return embeds
import argparse
import json

from tqdm import tqdm
def       __magic_name__(  )						->    List[str]:



      '''simple docstring'''

      _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()