






'''simple docstring'''

from __future__ import annotations

import typing
from collections.abc import Iterable

import numpy as np

UpperCAmelCase__						:List[str]          =			typing.Union[Iterable[float], Iterable[int], np.ndarray]  # noqa: UP007
UpperCAmelCase__						:Optional[int]          =			typing.Union[np.floataa, int, float]  # noqa: UP007
def     __lowercase  (_lowercase,						_lowercase     )   ->     VectorOut:


     """simple docstring"""
     return np.sqrt(np.sum((np.asarray(_lowercase     ) - np.asarray(_lowercase     )) ** 2     )     )
def     __lowercase  (_lowercase,						_lowercase     )   ->     VectorOut:


     """simple docstring"""
     return sum((va - va) ** 2 for va, va in zip(_lowercase,						_lowercase     )     ) ** (1 / 2)


if __name__ == "__main__":
   def     __lowercase  ()   ->     None:


        """simple docstring"""
        from timeit import timeit

        print("""Without Numpy"""     )
        print(
            timeit(
                """euclidean_distance_no_np([1, 2, 3], [4, 5, 6])""",						number=10_000,						globals=globals(),						)     )
        print("""With Numpy"""     )
        print(
            timeit(
                """euclidean_distance([1, 2, 3], [4, 5, 6])""",						number=10_000,						globals=globals(),						)     )
   benchmark()











'''simple docstring'''

import argparse
import json

from tqdm import tqdm
def     __lowercase  ()   ->     Tuple:


     """simple docstring"""
     __lowerCamelCase						:       Union[str, Any]				   =				argparse.ArgumentParser()

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


if __name__ == "__main__":
   main()



