






import copy

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


__UpperCAmelCase     							=						logging.get_logger(__name__)



class   lowerCamelCase				(_snake_case      ):







		'''simple docstring'''



		_snake_case   :   Union[str, Any]							=  '''encoder-decoder'''
		_snake_case   :   Optional[int]							=  True



		def __init__(							self    ,		**_UpperCamelCase       )     ->							Dict:
							super().__init__(**_UpperCamelCase       )
							assert (
							    "encoder" in kwargs and "decoder" in kwargs
							), "Config has to be initialized with encoder and decoder config"
							UpperCAmelCase_   :				int						=						kwargs.pop('encoder'       )
							UpperCAmelCase_   :				int						=						encoder_config.pop('model_type'       )
							UpperCAmelCase_   :				int						=						kwargs.pop('decoder'       )
							UpperCAmelCase_   :				List[Any]						=						decoder_config.pop('model_type'       )

							from ..auto.configuration_auto import AutoConfig

							UpperCAmelCase_   :				Optional[int]						=						AutoConfig.for_model(_UpperCamelCase    ,		**_UpperCamelCase       )
							UpperCAmelCase_   :				Optional[Any]						=						AutoConfig.for_model(_UpperCamelCase    ,		**_UpperCamelCase       )
							UpperCAmelCase_   :				Tuple						=						True



		@classmethod
		def  __UpperCAmelCase      (							cls    ,		_UpperCamelCase    ,		_UpperCamelCase    ,		**_UpperCamelCase       )     ->							PretrainedConfig:
							logger.info('Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'       )
							UpperCAmelCase_   :				int						=						True
							UpperCAmelCase_   :				Optional[int]						=						True

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



		def  __UpperCAmelCase      (							self       )     ->							str:
							UpperCAmelCase_   :				Any						=						copy.deepcopy(self.__dict__       )
							UpperCAmelCase_   :				int						=						self.encoder.to_dict()
							UpperCAmelCase_   :				Optional[Any]						=						self.decoder.to_dict()
							UpperCAmelCase_   :				List[Any]						=						self.__class__.model_type
							return output














def 					lowercase__				(					__snake_case   :							str					,	__snake_case   :							int					,	__snake_case   :							List[str]  ):


					'''simple docstring'''


					if n == 0:
										return 1

					elif n % 2 == 1:
										return (binary_exponentiation(__snake_case					,	n - 1					,	__snake_case  ) * a) % mod

					else:
										UpperCAmelCase_   :				Optional[int]						=						binary_exponentiation(__snake_case					,	n / 2					,	__snake_case  )
										return (b * b) % mod


# a prime number
__UpperCAmelCase     							=						701

__UpperCAmelCase     							=						1000000000
__UpperCAmelCase     							=						10

# using binary exponentiation function, O(log(p)):
print((a / b) % p == (a * binary_exponentiation(b, p - 2, p)) % p)






print((a / b) % p == (a * b ** (p - 2)) % p)






