Method smoothing_with_GCN

easygraph/classes/graph.py:498–509

r"""Return the smoothed feature matrix with GCN Laplacian matrix :math:`\mathcal{L}_{GCN}`. Args: ``X`` (``torch.Tensor``): Vertex feature matrix. Size :math:`(|\mathcal{V}|, C)`. ``drop_rate`` (``float``): Dropout rate. Randomly dropout the connections in adjacency

(self, X, drop_rate=0.0)

        return self.cache["L_GCN"]

    def smoothing_with_GCN(self, X, drop_rate=0.0):
        r"""Return the smoothed feature matrix with GCN Laplacian matrix :math:`\mathcal{L}_{GCN}`.

        Args:
            ``X`` (``torch.Tensor``): Vertex feature matrix. Size :math:`(|\mathcal{V}|, C)`.
            ``drop_rate`` (``float``): Dropout rate. Randomly dropout the connections in adjacency matrix with probability ``drop_rate``. Default: ``0.0``.
        """
        if drop_rate > 0.0:
            L_GCN = sparse_dropout(self.L_GCN, drop_rate)
        else:
            L_GCN = self.L_GCN
        return L_GCN.mm(X)

    def number_of_edges(self, u=None, v=None):
        """Returns the number of edges between two nodes.