from __future__ import annotations

import typing
from collections.abc import Iterable

import numpy as np

UpperCAmelCase_			    =							typing.Union[Iterable[float], Iterable[int], np.ndarray]  # noqa: UP007
UpperCAmelCase_			    =							typing.Union[np.floataa, int, float]  # noqa: UP007




def       lowerCAmelCase_   (		lowercase:							Vector  ,					lowercase:							Vector		)    ->				VectorOut:







 '''simple docstring'''
 return np.sqrt(np.sum((np.asarray(lowercase		) - np.asarray(lowercase		)) ** 2		)		)




def       lowerCAmelCase_   (		lowercase:							Vector  ,					lowercase:							Vector		)    ->				VectorOut:







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


if __name__ == "__main__":




  def       lowerCAmelCase_   (		)    ->				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()
import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


UpperCAmelCase_			    =							logging.get_logger(__name__)




class  __magic_name__  (		__a    ):





   """simple docstring"""




   def __init__(	self					:  str		,  *_lowercase					:  str		,  **_lowercase					:  int							):



    """simple docstring"""



    warnings.warn(
        '''The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
        ''' Please use PerceiverImageProcessor instead.'''		,  _lowercase		,  )
    super().__init__(*_lowercase		,  **_lowercase							)