




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        UpperCamelCase_					(				UpperCAmelCase__  ):

    '''simple docstring'''






    def __init__(    self   :			List[Any]      ,				UpperCAmelCase__   :			Optional[NestedDataStructureLike[PathLike]] = None      ,				UpperCAmelCase__   :			Optional[NamedSplit] = None      ,				UpperCAmelCase__   :			Optional[Features] = None      ,				UpperCAmelCase__   :			str = None      ,				UpperCAmelCase__   :			bool = False      ,				UpperCAmelCase__   :			bool = False      ,				UpperCAmelCase__   :			Optional[int] = None      ,				**UpperCAmelCase__   :			Optional[Any]      ,				)		->int:





           '''simple docstring'''

           A__   				=					path_or_paths
           A__   				=					split if split or isinstance(UpperCAmelCase__      ,				UpperCAmelCase__) else '''train'''
           A__   				=					features
           A__   				=					cache_dir
           A__   				=					keep_in_memory
           A__   				=					streaming
           A__   				=					num_proc
           A__   				=					kwargs





    @abstractmethod
    def  SCREAMING_SNAKE_CASE							(    self   :			Tuple)		->Union[Dataset, DatasetDict, IterableDataset, IterableDatasetDict]:





           '''simple docstring'''

           pass


class        UpperCamelCase_					(				UpperCAmelCase__  ):

    '''simple docstring'''






    def __init__(    self   :			int      ,				UpperCAmelCase__   :			Optional[Features] = None      ,				UpperCAmelCase__   :			str = None      ,				UpperCAmelCase__   :			bool = False      ,				UpperCAmelCase__   :			bool = False      ,				UpperCAmelCase__   :			Optional[int] = None      ,				**UpperCAmelCase__   :			List[str]      ,				)		->List[str]:





           '''simple docstring'''

           A__   				=					features
           A__   				=					cache_dir
           A__   				=					keep_in_memory
           A__   				=					streaming
           A__   				=					num_proc
           A__   				=					kwargs





    @abstractmethod
    def  SCREAMING_SNAKE_CASE							(    self   :			str)		->Union[Dataset, IterableDataset]:





           '''simple docstring'''

           pass








from __future__ import annotations

import numpy as np







def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> List[Any]:



       """simple docstring"""

       return np.maximum(0				,       lowercase_		)


if __name__ == "__main__":
  print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]


