




def 					A				(				_SCREAMING_SNAKE_CASE   )     ->			int:
       lowerCamelCase       :				Dict      			= str(_SCREAMING_SNAKE_CASE   ).strip()
       if not bin_string:
              raise ValueError("Empty string was passed to the function"   )
       lowerCamelCase       :				int      			= bin_string[0] == "-"
       if is_negative:
              lowerCamelCase       :				Union[str, Any]      			= bin_string[1:]
       if not all(char in "01" for char in bin_string   ):
              raise ValueError("Non-binary value was passed to the function"   )
       lowerCamelCase       :				Optional[int]      			= 0
       for char in bin_string:
              lowerCamelCase       :				Dict      			= 2 * decimal_number + int(_SCREAMING_SNAKE_CASE   )
       return -decimal_number if is_negative else decimal_number


if __name__ == "__main__":
       from doctest import testmod

       testmod()












import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


SCREAMING_SNAKE_CASE__	:				int  =       logging.get_logger(__name__)




class 		UpperCamelCase__     (lowerCAmelCase__					):

    '''simple docstring'''



    lowerCamelCase_				:     str     					=				"""speech-encoder-decoder"""
    lowerCamelCase_				:     List[str]     					=				True







    def __init__(   self					,  **UpperCamelCase__					)					->				Dict:
           super().__init__(**UpperCamelCase__					)
           if "encoder" not in kwargs or "decoder" not in kwargs:
                  raise ValueError(
                      F'''A configuraton of type {self.model_type} cannot be instantiated because not both `encoder` and'''
                      F''' `decoder` sub-configurations are passed, but only {kwargs}'''					)

           lowerCamelCase       :				Dict      			= kwargs.pop("encoder"					)
           lowerCamelCase       :				Tuple      			= encoder_config.pop("model_type"					)
           lowerCamelCase       :				int      			= kwargs.pop("decoder"					)
           lowerCamelCase       :				List[Any]      			= decoder_config.pop("model_type"					)

           lowerCamelCase       :				str      			= AutoConfig.for_model(UpperCamelCase__					,  **UpperCamelCase__					)
           lowerCamelCase       :				str      			= AutoConfig.for_model(UpperCamelCase__					,  **UpperCamelCase__					)
           lowerCamelCase       :				Tuple      			= True







    @classmethod
    def    _lowercase					(   cls					,  UpperCamelCase__					,  UpperCamelCase__					,  **UpperCamelCase__					)					->				PretrainedConfig:
           logger.info("Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"					)
           lowerCamelCase       :				Dict      			= True
           lowerCamelCase       :				Union[str, Any]      			= True

           return cls(encoder=encoder_config.to_dict()					,  decoder=decoder_config.to_dict()					,  **UpperCamelCase__					)







    def    _lowercase					(   self					)					->				Tuple:
           lowerCamelCase       :				Tuple      			= copy.deepcopy(self.__dict__					)
           lowerCamelCase       :				Optional[int]      			= self.encoder.to_dict()
           lowerCamelCase       :				List[str]      			= self.decoder.to_dict()
           lowerCamelCase       :				Dict      			= self.__class__.model_type
           return output






