




import copy

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


__UpperCamelCase      : Tuple					      =   logging.get_logger(__name__)

class 	__lowerCAmelCase			(			__magic_name__				):
							UpperCamelCase__        =						'''speech-encoder-decoder'''
							UpperCamelCase__        =						True
							def __init__(		self		:Dict	,   **__magic_name__		:List[str]       ):







								'''simple docstring'''







								super().__init__(**__magic_name__       )
								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}'       )

								a		       =							kwargs.pop("""encoder"""       )
								a		       =							encoder_config.pop("""model_type"""       )
								a		       =							kwargs.pop("""decoder"""       )
								a		       =							decoder_config.pop("""model_type"""       )

								a		       =							AutoConfig.for_model(__magic_name__	,   **__magic_name__       )
								a		       =							AutoConfig.for_model(__magic_name__	,   **__magic_name__       )
								a		       =							True
							@classmethod
							def    lowerCamelCase__							(		cls		:Union[str, Any]	,   __magic_name__		:PretrainedConfig	,   __magic_name__		:PretrainedConfig	,   **__magic_name__		:Optional[Any]       ):







								'''simple docstring'''







								logger.info("""Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"""       )
								a		       =							True
								a		       =							True

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





							def    lowerCamelCase__							(		self		:str       ):







								'''simple docstring'''







								a		       =							copy.deepcopy(self.__dict__       )
								a		       =							self.encoder.to_dict()
								a		       =							self.decoder.to_dict()
								a		       =							self.__class__.model_type
								return output







import math





def 	__A	(			__lowerCamelCase					)   -> bool:

	if 1 < number < 4:
		# 2 and 3 are primes
		return True
	elif number < 2 or number % 2 == 0 or number % 3 == 0:
		# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
		return False

	# All primes number are in format of 6k +/- 1
	for i in range(5							,    int(math.sqrt(__lowerCamelCase					) + 1					)							,    6					):
		if number % i == 0 or number % (i + 2) == 0:
			return False
	return True





def 	__A	(			__lowerCamelCase = 6008_5147_5143					)   -> int:

	try:
		a		       =							int(__lowerCamelCase					)
	except (TypeError, ValueError):
		raise TypeError("""Parameter n must be int or castable to int."""					)
	if n <= 0:
		raise ValueError("""Parameter n must be greater than or equal to one."""					)
	a		       =							0
	if is_prime(__lowerCamelCase					):
		return n
	while n % 2 == 0:
		n //= 2
	if is_prime(__lowerCamelCase					):
		return n
	for i in range(3							,    int(math.sqrt(__lowerCamelCase					)					) + 1							,    2					):
		if n % i == 0:
			if is_prime(n // i					):
				a		       =							n // i
				break
			elif is_prime(__lowerCamelCase					):
				a		       =							i
	return max_number


if __name__ == "__main__":
		print(F'{solution() = }')

