Method get_association_matrix

hflayers/__init__.py:240–255

Fetch Hopfield association matrix gathered by passing through the specified data. :param input: data to be passed through the Hopfield association :param stored_pattern_padding_mask: mask to be applied on stored patterns :param association_mask: mask to be applied o

(self, input: Union[Tensor, Tuple[Tensor, Tensor, Tensor]],
                               stored_pattern_padding_mask: Optional[Tensor] = None,
                               association_mask: Optional[Tensor] = None)

        return association_output

    def get_association_matrix(self, input: Union[Tensor, Tuple[Tensor, Tensor, Tensor]],
                               stored_pattern_padding_mask: Optional[Tensor] = None,
                               association_mask: Optional[Tensor] = None) -> Tensor:
        """
        Fetch Hopfield association matrix gathered by passing through the specified data.

        :param input: data to be passed through the Hopfield association
        :param stored_pattern_padding_mask: mask to be applied on stored patterns
        :param association_mask: mask to be applied on inner association matrix
        :return: association matrix as computed by the Hopfield core module
        """
        with torch.no_grad():
            return self._associate(
                data=input, return_raw_associations=True,
                stored_pattern_padding_mask=stored_pattern_padding_mask,
                association_mask=association_mask)[2]

    def get_projected_pattern_matrix(self, input: Union[Tensor, Tuple[Tensor, Tensor, Tensor]],
                                     stored_pattern_padding_mask: Optional[Tensor] = None,