



from ..utils import DummyObject, requires_backends


class       a							(			metaclass=__lowerCamelCase				):
		__lowerCAmelCase	:    Dict											=					["""speech"""]



		def __init__(     self     :Optional[int]   ,*__lowercase     :Optional[Any]   ,**__lowercase     :int  ):
						requires_backends(self   ,['''speech''']  )


class       a							(			metaclass=__lowerCamelCase				):
		__lowerCAmelCase	:    int											=					["""speech"""]



		def __init__(     self     :Dict   ,*__lowercase     :List[Any]   ,**__lowercase     :Optional[Any]  ):
						requires_backends(self   ,['''speech''']  )






from torch import nn


class       a							(			nn.Module				):



		def __init__(     self     :Tuple   ,__lowercase     :Optional[int]   ,__lowercase     :int  ):
						super().__init__()
						snake_case__	:      Optional[Any]     		=	class_size
						snake_case__	:      Dict     		=	embed_size
						# self.mlp1 = nn.Linear(embed_size, embed_size)
						# self.mlp2 = (nn.Linear(embed_size, class_size))
						snake_case__	:      Dict     		=	nn.Linear(__lowercase   ,__lowercase  )






		def 	__lowerCamelCase			(     self     :str   ,__lowercase     :int  ):
						# hidden_state = nn.functional.relu(self.mlp1(hidden_state))
						# hidden_state = self.mlp2(hidden_state)
						snake_case__	:      Optional[Any]     		=	self.mlp(__lowercase  )
						return logits

