






'''simple docstring'''

class        a_		:

  def __init__(   self    ,	_SCREAMING_SNAKE_CASE   )						->   List[Any]:



        """simple docstring"""






        UpperCamelCase       						=      arr.split(""","""   )


  def 						A__		(   self   )						->   Optional[int]:



        """simple docstring"""






        UpperCamelCase       						=      [int(self.array[0]   )] * len(self.array   )
        UpperCamelCase       						=      [int(self.array[0]   )] * len(self.array   )
        for i in range(1    ,	len(self.array   )   ):
              UpperCamelCase       						=      max(
                  int(self.array[i]   ) + sum_value[i - 1]    ,	int(self.array[i]   )   )
              UpperCamelCase       						=      max(sum_value[i]    ,	rear[i - 1]   )
        return rear[len(self.array   ) - 1]


if __name__ == "__main__":
     SCREAMING_SNAKE_CASE__											=     input('please input some numbers:')
     SCREAMING_SNAKE_CASE__											=     SubArray(whole_array)
     SCREAMING_SNAKE_CASE__											=     array.solve_sub_array()
     print(('the results is:', re))








'''simple docstring'''

from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__											=     {
    'configuration_swiftformer': [
        'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SwiftFormerConfig',
        'SwiftFormerOnnxConfig',
    ]
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE__											=     [
         'SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'SwiftFormerForImageClassification',
         'SwiftFormerModel',
         'SwiftFormerPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_swiftformer import (
         SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
         SwiftFormerConfig,
         SwiftFormerOnnxConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_swiftformer import (
              SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              SwiftFormerForImageClassification,
              SwiftFormerModel,
              SwiftFormerPreTrainedModel,
          )

else:
     import sys

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