

def _a			(	SCREAMING_SNAKE_CASE		:      List[str]		)   ->   Any:

 """simple docstring"""






 return int(__UpperCamelCase		) if x - int(__UpperCamelCase		) >= 0 else int(__UpperCamelCase		) - 1


if __name__ == "__main__":
  import doctest

  doctest.testmod()








import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig






class 							A_			(		snake_case__ ):
     _lowercase      :					Any       =     CustomConfig


     def __init__(							self      :		List[Any]      ,  UpperCAmelCase      :		Optional[Any] )							->     int:
      super().__init__(UpperCAmelCase )
      __lowerCAmelCase:       Tuple            =				torch.nn.Linear(config.hidden_size      ,  config.hidden_size )


     def   UpperCAmelCase  (							self      :		Optional[int]      ,  UpperCAmelCase      :		Tuple )							->     Union[str, Any]:
      return self.linear(UpperCAmelCase )


     def   UpperCAmelCase  (							self      :		str      ,  UpperCAmelCase      :		str )							->     Optional[int]:
      pass







class 							A_			(		snake_case__ ):
     _lowercase      :					str       =     NoSuperInitConfig


     def __init__(							self      :		List[Any]      ,  UpperCAmelCase      :		Union[str, Any] )							->     int:
      super().__init__(UpperCAmelCase )
      __lowerCAmelCase:       int            =				torch.nn.Linear(config.attribute      ,  config.attribute )


     def   UpperCAmelCase  (							self      :		Tuple      ,  UpperCAmelCase      :		Tuple )							->     Tuple:
      return self.linear(UpperCAmelCase )


     def   UpperCAmelCase  (							self      :		Optional[Any]      ,  UpperCAmelCase      :		Any )							->     str:
      pass





