


'''simple docstring'''






from __future__ import annotations


def A_					(				__SCREAMING_SNAKE_CASE :					int	,   __SCREAMING_SNAKE_CASE :					Optional[Any]	,   __SCREAMING_SNAKE_CASE :					Optional[int]	,   __SCREAMING_SNAKE_CASE :					Optional[Any]       )     ->  Tuple:

					# Base Case
					if counter == 0 or capacity == 0:
										return 0

					# If weight of the nth item is more than Knapsack of capacity,
					#   then this item cannot be included in the optimal solution,
					# else return the maximum of two cases:
					#   (1) nth item included
					#   (2) not included
					if weights[counter - 1] > capacity:
										return knapsack(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__	,   counter - 1       )
					else:
										__SCREAMING_SNAKE_CASE					:							Optional[int]			   = capacity - weights[counter - 1]
										__SCREAMING_SNAKE_CASE					:							int			   = values[counter - 1] + knapsack(
										    lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__	,   counter - 1       )
										__SCREAMING_SNAKE_CASE					:							Optional[int]			   = knapsack(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__	,   counter - 1       )
										return max(lowerCAmelCase__	,   lowerCAmelCase__       )


if __name__ == "__main__":
						import doctest

						doctest.testmod()










'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A      =     {
    """configuration_decision_transformer""": [
        """DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """DecisionTransformerConfig""",
    ],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_A      =     [
						    """DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """DecisionTransformerGPT2Model""",
						    """DecisionTransformerGPT2PreTrainedModel""",
						    """DecisionTransformerModel""",
						    """DecisionTransformerPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_decision_transformer import (
						    DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    DecisionTransformerConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_decision_transformer import (
												    DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DecisionTransformerGPTaModel,
												    DecisionTransformerGPTaPreTrainedModel,
												    DecisionTransformerModel,
												    DecisionTransformerPreTrainedModel,
												)


else:
						import sys

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


