

def        __lowercase    (  UpperCAmelCase__		,					UpperCAmelCase__		,					UpperCAmelCase__		,					UpperCAmelCase__		,					UpperCAmelCase__      ):

					"""simple docstring"""






					if index == number_of_items:
										return 0
					__lowerCAmelCase					=							0
					__lowerCAmelCase					=							0
					__lowerCAmelCase					=							knapsack(UpperCAmelCase__		,					UpperCAmelCase__		,					UpperCAmelCase__		,					UpperCAmelCase__		,					index + 1      )
					if weights[index] <= max_weight:
										__lowerCAmelCase					=							values[index] + knapsack(
										    UpperCAmelCase__		,					UpperCAmelCase__		,					UpperCAmelCase__		,					max_weight - weights[index]		,					index + 1      )
					return max(UpperCAmelCase__		,					UpperCAmelCase__      )


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__)






