
import copy

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


lowerCamelCase_  :       Tuple					      =     logging.get_logger(__name__)

class 				_UpperCamelCase (    _A     ):






			'''simple docstring'''

			__UpperCamelCase					:  Optional[Any]    					=       """speech-encoder-decoder"""
			__UpperCamelCase					:  str    					=       True

			def __init__(				self       :				str  ,		**snake_case_       :				str					):
							super().__init__(**snake_case_					)
							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}'''					)

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

							UpperCamelCase_:							Tuple		=  AutoConfig.for_model(snake_case_  ,		**snake_case_					)
							UpperCamelCase_:							Any		=  AutoConfig.for_model(snake_case_  ,		**snake_case_					)
							UpperCamelCase_:							Any		=  True

			@classmethod
			def 					lowerCAmelCase__		(				cls       :				Dict  ,		snake_case_       :				PretrainedConfig  ,		snake_case_       :				PretrainedConfig  ,		**snake_case_       :				Any					):
							logger.info("""Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"""					)
							UpperCamelCase_:							Any		=  True
							UpperCamelCase_:							List[str]		=  True

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




			def 					lowerCAmelCase__		(				self       :				Tuple					):
							UpperCamelCase_:							Dict		=  copy.deepcopy(self.__dict__					)
							UpperCamelCase_:							Optional[Any]		=  self.encoder.to_dict()
							UpperCamelCase_:							List[str]		=  self.decoder.to_dict()
							UpperCamelCase_:							List[str]		=  self.__class__.model_type
							return output








def 				A__    (  lowerCamelCase = 20  )     ->		int:

				try:
								UpperCamelCase_:							int		=  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."""  )
				UpperCamelCase_:							Any		=  0
				while 1:
								i += n * (n - 1)
								UpperCamelCase_:							List[Any]		=  0
								for j in range(2   ,			lowerCamelCase  ):
												if i % j != 0:
																UpperCamelCase_:							Union[str, Any]		=  1
																break
								if nfound == 0:
												if i == 0:
																UpperCamelCase_:							List[str]		=  1
												return i
				return None


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






