



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowerCamelCase								=   {
    """configuration_switch_transformers""": [
        """SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SwitchTransformersConfig""",
        """SwitchTransformersOnnxConfig""",
    ]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase								=   [
        """SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """SwitchTransformersEncoderModel""",
        """SwitchTransformersForConditionalGeneration""",
        """SwitchTransformersModel""",
        """SwitchTransformersPreTrainedModel""",
        """SwitchTransformersTop1Router""",
        """SwitchTransformersSparseMLP""",
    ]


if TYPE_CHECKING:
    from .configuration_switch_transformers import (
        SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP,
        SwitchTransformersConfig,
        SwitchTransformersOnnxConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_switch_transformers import (
            SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST,
            SwitchTransformersEncoderModel,
            SwitchTransformersForConditionalGeneration,
            SwitchTransformersModel,
            SwitchTransformersPreTrainedModel,
            SwitchTransformersSparseMLP,
            SwitchTransformersTopaRouter,
        )


else:
    import sys

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




from __future__ import annotations




def       UpperCAmelCase__	(							__snake_case  ,			__snake_case  ,			__snake_case  ,			__snake_case							)				->	int:

  # 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(__snake_case  ,			__snake_case  ,			__snake_case  ,			counter - 1							)
  else:
    _A          =      capacity - weights[counter - 1]
    _A          =      values[counter - 1] + knapsack(
        __snake_case  ,			__snake_case  ,			__snake_case  ,			counter - 1							)
    _A          =      knapsack(__snake_case  ,			__snake_case  ,			__snake_case  ,			counter - 1							)
    return max(__snake_case  ,			__snake_case							)


if __name__ == "__main__":
    import doctest

    doctest.testmod()