





'''simple docstring'''




from __future__ import annotations



def 						__A						(   lowerCamelCase_       ,       lowerCamelCase_       ,       lowerCamelCase_     ):


		"""simple docstring"""



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

		SCREAMING_SNAKE_CASE      :							float						=       0
		SCREAMING_SNAKE_CASE      :							list[float]						=       [0] * len(__a     )
		for i in index:
				if weight[i] <= capacity:
						SCREAMING_SNAKE_CASE      :							Optional[int]						=       1
						max_value += value[i]
						capacity -= weight[i]
				else:
						SCREAMING_SNAKE_CASE      :							Optional[int]						=       capacity / weight[i]
						max_value += value[i] * capacity / weight[i]
						break

		return max_value, fractions


if __name__ == "__main__":
							import doctest

							doctest.testmod()










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A									=				{"configuration_ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig", "IBertOnnxConfig"]}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __A									=				[
         "IBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "IBertForMaskedLM",
         "IBertForMultipleChoice",
         "IBertForQuestionAnswering",
         "IBertForSequenceClassification",
         "IBertForTokenClassification",
         "IBertModel",
         "IBertPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_ibert import (
              IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              IBertForMaskedLM,
              IBertForMultipleChoice,
              IBertForQuestionAnswering,
              IBertForSequenceClassification,
              IBertForTokenClassification,
              IBertModel,
              IBertPreTrainedModel,
          )

else:
     import sys

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

