def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    _validate_point(SCREAMING_SNAKE_CASE	)
    _validate_point(SCREAMING_SNAKE_CASE	)
    if len(SCREAMING_SNAKE_CASE	) != len(SCREAMING_SNAKE_CASE	):
        raise ValueError('''Both points must be in the same n-dimensional space'''	)

    return float(sum(abs(a - b	) for a, b in zip(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)	)	)



def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    if point:
        if isinstance(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
            for item in point:
                if not isinstance(SCREAMING_SNAKE_CASE  ,			(int, float)	):
                    __UpperCamelCase     :Optional[int]			  =		(
                        '''Expected a list of numbers as input, found '''
                        f"""{type(SCREAMING_SNAKE_CASE	).__name__}"""
                    )
                    raise TypeError(SCREAMING_SNAKE_CASE	)
        else:
            __UpperCamelCase     :List[str]			  =		f"""Expected a list of numbers as input, found {type(SCREAMING_SNAKE_CASE	).__name__}"""
            raise TypeError(SCREAMING_SNAKE_CASE	)
    else:
        raise ValueError('''Missing an input'''	)



def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    _validate_point(SCREAMING_SNAKE_CASE	)
    _validate_point(SCREAMING_SNAKE_CASE	)
    if len(SCREAMING_SNAKE_CASE	) != len(SCREAMING_SNAKE_CASE	):
        raise ValueError('''Both points must be in the same n-dimensional space'''	)

    return float(sum(abs(x - y	) for x, y in zip(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)	)	)


if __name__ == "__main__":
    import doctest

    doctest.testmod()












"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


_snake_case     :		Optional[int]       						= logging.get_logger(__name__)

_snake_case     :		Optional[int]       						= {
    'google/vivit-b-16x2-kinetics400': (
        'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json'
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}






class 					_UpperCAmelCase   (	lowercase_ ):
					UpperCamelCase      =							'''vivit'''


					def __init__(					self			:Optional[Any]     ,       __UpperCamelCase			:Dict=2_24     ,       __UpperCamelCase			:int=32     ,       __UpperCamelCase			:Union[str, Any]=[2, 16, 16]     ,       __UpperCamelCase			:Optional[Any]=3     ,       __UpperCamelCase			:Optional[Any]=7_68     ,       __UpperCamelCase			:Any=12     ,       __UpperCamelCase			:List[str]=12     ,       __UpperCamelCase			:List[str]=30_72     ,       __UpperCamelCase			:Any="gelu_fast"     ,       __UpperCamelCase			:List[Any]=0.0     ,       __UpperCamelCase			:str=0.0     ,       __UpperCamelCase			:Dict=0.02     ,       __UpperCamelCase			:Optional[Any]=1e-06     ,       __UpperCamelCase			:Dict=True     ,       **__UpperCamelCase			:Tuple     ,       ):
												A		=  hidden_size
												A		=  num_hidden_layers
												A		=  num_attention_heads
												A		=  intermediate_size
												A		=  hidden_act
												A		=  hidden_dropout_prob
												A		=  attention_probs_dropout_prob
												A		=  initializer_range
												A		=  layer_norm_eps

												A		=  image_size
												A		=  num_frames
												A		=  tubelet_size
												A		=  num_channels
												A		=  qkv_bias

												super().__init__(**__UpperCamelCase		)


