






"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A__	:    Optional[Any]			 = {
    'configuration_upernet': ['UperNetConfig'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__	:    int			 = [
						    'UperNetForSemanticSegmentation',
						    'UperNetPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_upernet import UperNetConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel


else:
						import sys

						A__	:    Dict			 = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)











"""simple docstring"""



def 			_snake_case    (					lowerCamelCase__     :   int  )    ->     int:

							if not isinstance(lowerCamelCase__    ,						lowerCamelCase__  ):
														raise TypeError("only integers accepted as input"  )
							else:
														lowerCamelCase_	:							str									=str(abs(lowerCamelCase__  )  )
														lowerCamelCase_	:							Tuple									=[list(lowerCamelCase__  ) for char in range(len(lowerCamelCase__  )  )]
														for index in range(len(lowerCamelCase__  )  ):
																					num_transpositions[index].pop(lowerCamelCase__  )
														return max(
														    int("".join(list(lowerCamelCase__  )  )  ) for transposition in num_transpositions  )


if __name__ == "__main__":
						__import__('doctest').testmod()



