

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCamelCase__  :      Optional[Any]			=    {
    "configuration_nezha": ["NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP", "NezhaConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      Optional[Any]			=    [
           "NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST",
           "NezhaForNextSentencePrediction",
           "NezhaForMaskedLM",
           "NezhaForPreTraining",
           "NezhaForMultipleChoice",
           "NezhaForQuestionAnswering",
           "NezhaForSequenceClassification",
           "NezhaForTokenClassification",
           "NezhaModel",
           "NezhaPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_nezha import (
                  NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
                  NezhaForMaskedLM,
                  NezhaForMultipleChoice,
                  NezhaForNextSentencePrediction,
                  NezhaForPreTraining,
                  NezhaForQuestionAnswering,
                  NezhaForSequenceClassification,
                  NezhaForTokenClassification,
                  NezhaModel,
                  NezhaPreTrainedModel,
              )


else:
       import sys

       UpperCamelCase__  :      Dict			=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)








def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		list ,   _SCREAMING_SNAKE_CASE					:		list ,   _SCREAMING_SNAKE_CASE					:		int ,   _SCREAMING_SNAKE_CASE					:		int ,   _SCREAMING_SNAKE_CASE					:		int       ):





    """simple docstring"""


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


if __name__ == "__main__":
       import doctest

       doctest.testmod()


