59266e34e076ed25852bccf5ce13025b5408406f,stellargraph/layer/gcn.py,GCN,__call__,#GCN#Any#,262

Before Change

            Output tensor
        
        H = x[0]
        extra_in = x[1:]

        for layer in self._layers:
            if isinstance(layer, GraphConvolution):
                // It is a GCN layer add the extra inputs

After Change

        // Currently we require the batch dimension to be one for full-batch methods
        batch_dim, n_nodes, _ = K.int_shape(x_in)
        if batch_dim != 1:
            raise ValueError(
                "Currently full-batch methods only support a batch dimension of one"
            )

        // Convert input indices & values to a sparse matrix
        if self.use_sparse:
            A_indices, A_values = As
            Ainput = TFSparseConversion(shape=(n_nodes, n_nodes))([A_indices, A_values])

        // Otherwise, create dense matrix from input tensor
        else:
            Ainput = Lambda(lambda A: K.squeeze(A, 0))(As[0])

        // Remove singleton batch dimension
        h_layer = x_in
        for layer in self._layers:

Instances