





from bisect import bisect
from itertools import accumulate




def    __UpperCAmelCase(      lowercase_ ,    lowercase_ ,    lowercase_ ,    lowercase_      ):
       _lowerCamelCase							:     Optional[int]	=		sorted(zip(a__ ,    a__      ) ,    key=lambda lowercase_      : x[0] / x[1] ,    reverse=a__      )
       _lowerCamelCase,  _lowerCamelCase							:     List[Any]	=		[i[0] for i in r], [i[1] for i in r]
       _lowerCamelCase							:     Tuple	=		list(accumulate(a__      )      )
       _lowerCamelCase							:     Union[str, Any]	=		bisect(a__ ,    a__      )
       return (
           0
           if k == 0
           else sum(vl[:k]      ) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
           if k != n
           else sum(vl[:k]      )
       )


if __name__ == "__main__":
    import doctest

    doctest.testmod()








import warnings

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


_lowerCamelCase			       =      logging.get_logger(__name__)







class 			__A       (      lowerCamelCase__  ):




      """simple docstring"""







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



             """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__)

