

import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


lowerCAmelCase__       = logging.get_logger(__name__)






class 						__magic_name__    (       _snake_case    ):


 def __init__(						self		: Any			,						*lowerCAmelCase__		: Optional[int]			,						**lowerCAmelCase__		: Union[str, Any]    )    ->      None:
   warnings.warn(
       "The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
       " use GLPNImageProcessor instead."			,						lowerCAmelCase__			,						)
   super().__init__(*lowerCAmelCase__			,						**lowerCAmelCase__    )






def      _lowerCAmelCase(	__A   ,       __A   ,       __A			):
  if n == 0:
    return 1

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

  else:
    UpperCAmelCase					      =  binary_exponentiation(__A   ,       n / 2   ,       __A			)
    return (b * b) % mod


# a prime number
lowerCAmelCase__       = 701

lowerCAmelCase__       = 1000000000
lowerCAmelCase__       = 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)



