



def  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase):
					assert b != 0, "This cannot accept modulo that is == 0"
					if n == 0:
										return 1

					if n % 2 == 1:
										return (bin_exp_mod(_lowerCAmelCase ,						n - 1 ,						_lowerCAmelCase) * a) % b

					UpperCamelCase_			= bin_exp_mod(_lowerCAmelCase ,						n / 2 ,						_lowerCAmelCase)
					return (r * r) % b


if __name__ == "__main__":
	try:
		UpperCAmelCase :				List[Any]							=int(input("""Enter Base : """).strip())
		UpperCAmelCase :				Optional[Any]							=int(input("""Enter Power : """).strip())
		UpperCAmelCase :				Dict							=int(input("""Enter Modulo : """).strip())
	except ValueError:
		print("""Invalid literal for integer""")

	print(bin_exp_mod(BASE, POWER, MODULO))







import warnings

from ...utils import logging
from .image_processing_convnext import ConvNextImageProcessor


_UpperCAmelCase										=					logging.get_logger(__name__)



class 				_UpperCamelCase       (						lowerCAmelCase_  ):

       def __init__(		self:			Tuple       , *_SCREAMING_SNAKE_CASE:			List[Any]       , **_SCREAMING_SNAKE_CASE:			List[Any]		)							->			None:




              """simple docstring"""


              warnings.warn(
                  "The class ConvNextFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
                  " Please use ConvNextImageProcessor instead."       , _SCREAMING_SNAKE_CASE       , )
              super().__init__(*_SCREAMING_SNAKE_CASE       , **_SCREAMING_SNAKE_CASE		)

