

def 		UpperCamelCase_(     snake_case__:    str  )			->					Optional[int]:



 if not isinstance(_UpperCamelCase    ,       _UpperCamelCase  ):
  raise ValueError('check_bouncy() accepts only integer arguments'  )
 UpperCAmelCase__     							=							str(_UpperCamelCase  )
 UpperCAmelCase__     							=							''''''.join(sorted(_UpperCamelCase  )  )
 return sorted_str_n != str_n and sorted_str_n[::-1] != str_n
def 		UpperCamelCase_(     snake_case__:    Optional[Any] = 99  )			->					Dict:



 if not 0 < percent < 1_00:
  raise ValueError('solution() only accepts values from 0 to 100'  )
 UpperCAmelCase__     							=							0
 UpperCAmelCase__     							=							1

 while True:
  if check_bouncy(_UpperCamelCase  ):
   bouncy_num += 1
  if (bouncy_num / num) * 1_00 >= percent:
   return num
  num += 1


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

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





"""simple docstring"""




import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


A__ :       List[Any]				= logging.get_logger(__name__)


class       __magic_name__							(							SCREAMING_SNAKE_CASE__			):
       def __init__(  self			,					*A_			,					**A_							)  ->						None:





         """simple docstring"""




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