


'''simple docstring'''



from __future__ import annotations







def     _UpperCamelCase      (		UpperCamelCase__ ,      UpperCamelCase__ ,      UpperCamelCase__					):

			'''simple docstring'''





			UpperCAmelCase__  :					int        =     list(range(len(UpperCamelCase__					)					)					)
			UpperCAmelCase__  :					List[str]        =     [v / w for v, w in zip(UpperCamelCase__ ,      UpperCamelCase__					)]
			index.sort(key=lambda UpperCamelCase__					: ratio[i] ,      reverse=UpperCamelCase__					)

			UpperCAmelCase__  :					Dict        =     0
			UpperCAmelCase__  :					Union[str, Any]        =     [0] * len(UpperCamelCase__					)
			for i in index:
						if weight[i] <= capacity:
									UpperCAmelCase__  :					List[Any]        =     1
									max_value += value[i]
									capacity -= weight[i]
						else:
									UpperCAmelCase__  :					Optional[int]        =     capacity / weight[i]
									max_value += value[i] * capacity / weight[i]
									break

			return max_value, fractions


if __name__ == "__main__":
		import doctest

		doctest.testmod()



'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__A	={
    'configuration_encodec': [
        'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EncodecConfig',
    ],
    'feature_extraction_encodec': ['EncodecFeatureExtractor'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__A	=[
		    'ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'EncodecModel',
		    'EncodecPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_encodec import (
		    ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    EncodecConfig,
		)
		from .feature_extraction_encodec import EncodecFeatureExtractor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_encodec import (
				    ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
				    EncodecModel,
				    EncodecPreTrainedModel,
				)

else:
		import sys

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