





'''simple docstring'''







import copy

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


snake_case_  :							Any            =	logging.get_logger(__name__)


class        __a   (lowerCamelCase  ):
							__a       : List[str]          =							"speech-encoder-decoder"
							__a       : Any          =							True

							def __init__(				self				:  Optional[int]							,  **__magic_name__				:  List[str] )       ->							Optional[Any]:







													"""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}""" )

													UpperCAmelCase_      :   List[Any]      =	kwargs.pop('''encoder''' )
													UpperCAmelCase_      :   Any      =	encoder_config.pop('''model_type''' )
													UpperCAmelCase_      :   str      =	kwargs.pop('''decoder''' )
													UpperCAmelCase_      :   Optional[Any]      =	decoder_config.pop('''model_type''' )

													UpperCAmelCase_      :   str      =	AutoConfig.for_model(__magic_name__							,  **__magic_name__ )
													UpperCAmelCase_      :   Any      =	AutoConfig.for_model(__magic_name__							,  **__magic_name__ )
													UpperCAmelCase_      :   int      =	True

							@classmethod
							def      UpperCAmelCase__						(				cls				:  str							,  __magic_name__				:  PretrainedConfig							,  __magic_name__				:  PretrainedConfig							,  **__magic_name__				:  Optional[Any] )       ->							Dict:







													"""simple docstring"""
													logger.info('''Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config''' )
													UpperCAmelCase_      :   Any      =	True
													UpperCAmelCase_      :   Optional[int]      =	True

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



							def      UpperCAmelCase__						(				self				:  Any )       ->							Tuple:







													"""simple docstring"""
													UpperCAmelCase_      :   str      =	copy.deepcopy(self.__dict__ )
													UpperCAmelCase_      :   str      =	self.encoder.to_dict()
													UpperCAmelCase_      :   Tuple      =	self.decoder.to_dict()
													UpperCAmelCase_      :   List[str]      =	self.__class__.model_type
													return output













"""simple docstring"""



from itertools import combinations, product




def   _lowerCAmelCase		(				UpperCAmelCase__							:       int,    UpperCAmelCase__							:       int,    UpperCAmelCase__							:       int,    UpperCAmelCase__							:       int   )		->bool:
						if xa == ya == 0 or xa == ya == 0:
												return False
						A__    :	List[str]			=	xa * xa + ya * ya
						A__    :	List[Any]			=	xa * xa + ya * ya
						A__    :	Optional[int]			=	(xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
						return (
						    a_square + b_square == c_square
						    or a_square + c_square == b_square
						    or b_square + c_square == a_square
						)




def   _lowerCAmelCase		(				UpperCAmelCase__							:       int = 5_0   )		->int:
						return sum(
						    1
						    for pta, pta in combinations(product(range(limit + 1   ),    repeat=2   ),    2   )
						    if is_right(*UpperCAmelCase__,    *UpperCAmelCase__   )   )


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






