




from bisect import bisect
from itertools import accumulate



def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Optional[Any]:
  lowerCAmelCase__				:  Tuple		       =     sorted(zip(UpperCamelCase	,      UpperCamelCase      )	,      key=lambda UpperCamelCase      : x[0] / x[1]	,      reverse=UpperCamelCase      )
  lowerCAmelCase__				:  int		       =     [i[0] for i in r], [i[1] for i in r]
  lowerCAmelCase__				:  List[Any]		       =     list(accumulate(UpperCamelCase      )      )
  lowerCAmelCase__				:  Dict		       =     bisect(UpperCamelCase	,      UpperCamelCase      )
  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()







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase_					    = {
    """configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase_					    = [
         """LILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """LiltForQuestionAnswering""",
         """LiltForSequenceClassification""",
         """LiltForTokenClassification""",
         """LiltModel""",
         """LiltPreTrainedModel""",
     ]

if TYPE_CHECKING:
     from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_lilt import (
              LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
              LiltForQuestionAnswering,
              LiltForSequenceClassification,
              LiltForTokenClassification,
              LiltModel,
              LiltPreTrainedModel,
          )

else:
     import sys

     lowerCAmelCase_					    = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

