





from __future__ import annotations



def 		A_    (					_lowerCAmelCase					)						->			list[int]:
 return [ord(_lowerCAmelCase					) - 96 for elem in plain]



def 		A_    (					_lowerCAmelCase					)						->			str:
 return "".join(chr(elem + 96					) for elem in encoded					)



def 		A_    (					)						->			None:
 UpperCamelCase     : int	     =       encode(input("-> "					).strip().lower()					)
 print("Encoded: "							,       _lowerCAmelCase					)
 print("Decoded:"							,       decode(_lowerCAmelCase					)					)


if __name__ == "__main__":
    main()







from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCamelCase	:					Tuple			  =					logging.get_logger(__name__)



class  A__       (	__snake_case      ):
      _UpperCAmelCase     :List[Any]						   =       'timm_backbone'





      def __init__(			self	,							A_=None	,							A_=3	,							A_=True	,							A_=True	,							A_=None	,							**A_	,							):
       '''simple docstring'''




       super().__init__(**A_       )
       UpperCamelCase     : Tuple	     =       backbone
       UpperCamelCase     : Dict	     =       num_channels
       UpperCamelCase     : Tuple	     =       features_only
       UpperCamelCase     : Optional[int]	     =       use_pretrained_backbone
       UpperCamelCase     : Dict	     =       True
       UpperCamelCase     : List[str]	     =       out_indices if out_indices is not None else (-1,)
