






'''simple docstring'''




from torch import nn







class       __lowercase					(nn.Module    ):

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





	def      __UpperCamelCase							(      self   :						Tuple  ,					UpperCAmelCase_   :						Union[str, Any]):
			# hidden_state = nn.functional.relu(self.mlp1(hidden_state))
			# hidden_state = self.mlp2(hidden_state)
			UpperCamelCase__				:					int					=					self.mlp(UpperCAmelCase_)
			return logits












'''simple docstring'''




from ..utils import DummyObject, requires_backends







class       __lowercase					(metaclass=__lowerCamelCase    ):
	_lowerCamelCase              =  ['''torch''', '''scipy''']

	def __init__(      self   :						List[Any]  ,					*UpperCAmelCase_   :						Any  ,					**UpperCAmelCase_   :						int):
			requires_backends(self  ,					['torch', 'scipy'])

	@classmethod
	def      __UpperCamelCase							(      cls   :						Union[str, Any]  ,					*UpperCAmelCase_   :						Any  ,					**UpperCAmelCase_   :						List[Any]):
			requires_backends(cls  ,					['torch', 'scipy'])





	@classmethod
	def      __UpperCamelCase							(      cls   :						Union[str, Any]  ,					*UpperCAmelCase_   :						Optional[Any]  ,					**UpperCAmelCase_   :						Any):
			requires_backends(cls  ,					['torch', 'scipy'])




