


from __future__ import annotations

from fractions import Fraction







def SCREAMING_SNAKE_CASE	(			__lowerCAmelCase							,   __lowerCAmelCase				)    ->				bool:
  return (
      num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
  )







def SCREAMING_SNAKE_CASE	(			__lowerCAmelCase				)    ->				list[str]:
  snake_case__						= []
  snake_case__						= 11
  snake_case__						= int('''1''' + '''0''' * digit_len				)
  for num in range(__lowerCAmelCase							,   __lowerCAmelCase				):
    while den <= 99:
      if (num != den) and (num % 10 == den // 10) and (den % 10 != 0):
        if is_digit_cancelling(__lowerCAmelCase							,   __lowerCAmelCase				):
          solutions.append(F"""{num}/{den}"""				)
      den += 1
    num += 1
    snake_case__						= 10
  return solutions







def SCREAMING_SNAKE_CASE	(			__lowerCAmelCase = 2				)    ->				int:
  snake_case__						= 1.0
  for fraction in fraction_list(__lowerCAmelCase				):
    snake_case__						= Fraction(__lowerCAmelCase				)
    result *= frac.denominator / frac.numerator
  return int(__lowerCAmelCase				)


if __name__ == "__main__":
   print(solution())





import warnings

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


lowerCamelCase__							:						int							     =   logging.get_logger(__name__)
class 		__magic_name__						(snake_case_				):





     '''simple docstring'''



     def __init__(					self:List[Any]     ,		*_a:Dict     ,		**_a:Tuple   ):
       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   )

