




from __future__ import annotations

def 			_SCREAMING_SNAKE_CASE			(							lowercase	:       list[int]	,							lowercase	:       list[int]	,							lowercase	:       int     ):


      '''simple docstring'''



      lowerCamelCase_		     =    list(range(len(lowercase     )     )     )
      lowerCamelCase_		     =    [v / w for v, w in zip(lowercase	,							lowercase     )]
      index.sort(key=lambda lowercase     : ratio[i]	,							reverse=lowercase     )

      lowerCamelCase_		     =    0
      lowerCamelCase_		     =    [0] * len(lowercase     )
      for i in index:
            if weight[i] <= capacity:
                  lowerCamelCase_		     =    1
                  max_value += value[i]
                  capacity -= weight[i]
            else:
                  lowerCamelCase_		     =    capacity / weight[i]
                  max_value += value[i] * capacity / weight[i]
                  break

      return max_value, fractions


if __name__ == "__main__":
 import doctest

 doctest.testmod()









import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


lowerCamelCase				:		Any     =   logging.get_logger(__name__)







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 def __init__(				self					:  Dict						,							*A_					:  Optional[int]						,							**A_					:  int  )   ->	None:

       """simple docstring"""






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



