




def 					A				(				_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE = 1000   )     ->			str:
       if (not isinstance(_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )) or (digit_position <= 0):
              raise ValueError("Digit position must be a positive integer"   )
       elif (not isinstance(_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )) or (precision < 0):
              raise ValueError("Precision must be a nonnegative integer"   )

       # compute an approximation of (16 ** (n - 1)) * pi whose fractional part is mostly
       # accurate
       lowerCamelCase       :				List[str]      			= (
           4 * _subsum(_SCREAMING_SNAKE_CASE			,1			,_SCREAMING_SNAKE_CASE   )
           - 2 * _subsum(_SCREAMING_SNAKE_CASE			,4			,_SCREAMING_SNAKE_CASE   )
           - _subsum(_SCREAMING_SNAKE_CASE			,5			,_SCREAMING_SNAKE_CASE   )
           - _subsum(_SCREAMING_SNAKE_CASE			,6			,_SCREAMING_SNAKE_CASE   )
       )

       # return the first hex digit of the fractional part of the result
       return hex(int((sum_result % 1) * 16   )   )[2:]

def 					A				(				_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )     ->			float:
       lowerCamelCase       :				Tuple      			= 0.0
       for sum_index in range(digit_pos_to_extract + precision   ):
              lowerCamelCase       :				List[Any]      			= 8 * sum_index + denominator_addend
              if sum_index < digit_pos_to_extract:
                     # if the exponential term is an integer and we mod it by the denominator
                     # before dividing, only the integer part of the sum will change;
                     # the fractional part will not
                     lowerCamelCase       :				Dict      			= pow(
                         16			,digit_pos_to_extract - 1 - sum_index			,_SCREAMING_SNAKE_CASE   )
              else:
                     lowerCamelCase       :				Union[str, Any]      			= pow(16			,digit_pos_to_extract - 1 - sum_index   )
              total += exponential_term / denominator
       return total


if __name__ == "__main__":
       import doctest

       doctest.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






