



'''simple docstring'''





import os
from argparse import ArgumentParser
from typing import List

import torch.utils.data

from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node


lowercase_									=    4
lowercase_									=    3






class __A     (    A		):



 '''simple docstring'''







 pass





def lowerCAmelCase    (__A):



     """simple docstring"""



     for shard in shards:
          for i in range(__A):
               yield {"i": i, "shard": shard}




def lowerCAmelCase    ():



     """simple docstring"""



     _a           =    int(os.environ['''RANK'''])
     _a           =    int(os.environ['''WORLD_SIZE'''])

     _a           =    ArgumentParser()
     parser.add_argument('''--streaming'''    ,      type=__A)
     parser.add_argument('''--local_rank'''    ,      type=__A)
     parser.add_argument('''--num_workers'''    ,      type=__A    ,      default=0)
     _a           =    parser.parse_args()
     _a           =    args.streaming
     _a           =    args.num_workers

     _a           =    {'''shards''': [F'''shard_{shard_idx}''' for shard_idx in range(__A)]}
     _a           =    IterableDataset.from_generator(__A    ,      gen_kwargs=__A)
     if not streaming:
          _a           =    Dataset.from_list(list(__A))

     _a           =    split_dataset_by_node(__A    ,      rank=__A    ,      world_size=__A)
     _a           =    torch.utils.data.DataLoader(__A    ,      num_workers=__A)

     _a           =    NUM_SHARDS * NUM_ITEMS_PER_SHARD
     _a           =    full_size // world_size
     expected_local_size += int(rank < (full_size % world_size))

     _a           =    sum(1 for _ in dataloader)
     if local_size != expected_local_size:
          raise FailedTestError(F'''local_size {local_size} != expected_local_size {expected_local_size}''')


if __name__ == "__main__":
  main()










"""simple docstring"""



def 						__lowercase	(  snake_case_    :    str							,snake_case_    :    str		)  ->float:



    '''simple docstring'''







    def get_matched_characters(snake_case_    :    str							,snake_case_    :    str		) -> str:
        __A       :		Any							=	[]
        __A       :		Any							=	min(len(_stra		)							,len(_stra		)		) // 2
        for i, l in enumerate(_stra		):
            __A       :		Dict							=	int(max(0							,i - limit		)		)
            __A       :		Tuple							=	int(min(i + limit + 1							,len(_stra		)		)		)
            if l in _stra[left:right]:
                matched.append(snake_case_		)
                __A       :		Any							=	F"""{_stra[0:_stra.index(snake_case_		)]} {_stra[_stra.index(snake_case_		) + 1:]}"""

        return "".join(snake_case_		)

    # matching characters
    __A       :		int							=	get_matched_characters(snake_case_							,snake_case_		)
    __A       :		Tuple							=	get_matched_characters(snake_case_							,snake_case_		)
    __A       :		str							=	len(snake_case_		)

    # transposition
    __A       :		Dict							=	(
        len([(ca, ca) for ca, ca in zip(snake_case_							,snake_case_		) if ca != ca]		) // 2
    )

    if not match_count:
        __A       :		List[str]							=	0.0
    else:
        __A       :		Tuple							=	(
            1
            / 3
            * (
                match_count / len(snake_case_		)
                + match_count / len(snake_case_		)
                + (match_count - transpositions) / match_count
            )
        )

    # common prefix up to 4 characters
    __A       :		Tuple							=	0
    for ca, ca in zip(stra[:4]							,stra[:4]		):
        if ca == ca:
            prefix_len += 1
        else:
            break

    return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(jaro_winkler("""hello""", """world"""))




