





"""simple docstring"""



from abc import ABC, abstractmethod
from typing import Optional, Union

from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


 def __init__(       self   ,		__lowerCamelCase = None   ,		__lowerCamelCase = None   ,		__lowerCamelCase = None   ,		__lowerCamelCase = None   ,		__lowerCamelCase = False   ,		__lowerCamelCase = False   ,		__lowerCamelCase = None   ,		**__lowerCamelCase   ,		):



     '''simple docstring'''




     __A       :		Union[str, Any]							=	path_or_paths
     __A       :		Union[str, Any]							=	split if split or isinstance(__lowerCamelCase   ,		__lowerCamelCase    ) else '''train'''
     __A       :		Optional[Any]							=	features
     __A       :		List[str]							=	cache_dir
     __A       :		Any							=	keep_in_memory
     __A       :		Optional[Any]							=	streaming
     __A       :		List[str]							=	num_proc
     __A       :		List[Any]							=	kwargs







 @abstractmethod
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     pass






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


 def __init__(       self   ,		__lowerCamelCase = None   ,		__lowerCamelCase = None   ,		__lowerCamelCase = False   ,		__lowerCamelCase = False   ,		__lowerCamelCase = None   ,		**__lowerCamelCase   ,		):



     '''simple docstring'''




     __A       :		str							=	features
     __A       :		int							=	cache_dir
     __A       :		Any							=	keep_in_memory
     __A       :		Optional[int]							=	streaming
     __A       :		str							=	num_proc
     __A       :		Dict							=	kwargs







 @abstractmethod
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     pass











"""simple docstring"""



def 						__lowercase	(  snake_case_    :    list		)  ->float:



    '''simple docstring'''







    __A       :		Tuple							=	0
    while len(snake_case_		) > 1:
        __A       :		List[Any]							=	0
        # Consider two files with minimum cost to be merged
        for _ in range(2		):
            __A       :		Dict							=	files.index(min(snake_case_		)		)
            temp += files[min_index]
            files.pop(snake_case_		)
        files.append(snake_case_		)
        optimal_merge_cost += temp
    return optimal_merge_cost


if __name__ == "__main__":
       import doctest

       doctest.testmod()




