

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  str )   ->       str:







				if not isinstance(lowercase__  ,      lowercase__ ):
								raise ValueError("check_bouncy() accepts only integer arguments" )
				_UpperCAmelCase       :		int 		=    str(lowercase__ )
				_UpperCAmelCase       :		Dict 		=    "".join(sorted(lowercase__ ) )
				return sorted_str_n != str_n and sorted_str_n[::-1] != str_n

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  Any = 99 )   ->       Optional[Any]:







				if not 0 < percent < 100:
								raise ValueError("solution() only accepts values from 0 to 100" )
				_UpperCAmelCase       :		str 		=    0
				_UpperCAmelCase       :		str 		=    1

				while True:
								if check_bouncy(lowercase__ ):
												bouncy_num += 1
								if (bouncy_num / num) * 100 >= percent:
												return num
								num += 1


if __name__ == "__main__":
					from doctest import testmod

					testmod()
					print(F'''{solution(99)}''')





import warnings

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


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

class 				a  (	UpperCAmelCase				):


						def __init__(       self						,					*A_						,					**A_	):







										'''simple docstring'''


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


