


def       UpperCAmelCase__						(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_    ) ->    str:



     """simple docstring"""






     if n == 0:
          return 1

     elif n % 2 == 1:
          return (binary_exponentiation(UpperCamelCase_							,n - 1							,UpperCamelCase_    ) * a) % mod

     else:
          snake_case					=    binary_exponentiation(UpperCamelCase_							,n / 2							,UpperCamelCase_    )
          return (b * b) % mod


# a prime number
_SCREAMING_SNAKE_CASE      :			Dict      				=   7_01

_SCREAMING_SNAKE_CASE      :			Union[str, Any]      				=   10_00_00_00_00
_SCREAMING_SNAKE_CASE      :			Optional[int]      				=   10

# using binary exponentiation function, O(log(p)):
print((a / b) % p == (a * binary_exponentiation(b, p - 2, p)) % p)

print((a / b) % p == (a * b ** (p - 2)) % p)








import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


_SCREAMING_SNAKE_CASE      :			List[str]      				=   logging.get_logger(__name__)

class   A__ (   snake_case__     ):







    """simple docstring"""

    def __init__(	self      , *__snake_case      , **__snake_case   ):
         warnings.warn(
             '''The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
             ''' use BeitImageProcessor instead.'''      , __snake_case      , )
         super().__init__(*__snake_case      , **__snake_case   )




