def forward(self, x, get_distances=False):
        r"""
        Forward computation.

        Parameters
        ----------
        x : Tensor
            The point coordinates. :math:`(N, D)` where :math:`N` means the
            number of points in the point set, and :math:`D` means the size of
            the features. It can be either on CPU or GPU. Device of the point
            coordinates specifies device of the radius graph.
        get_distances : bool, optional
            Whether to return the distances for the corresponding edges in the
            radius graph.

            (default: False)

        Returns
        -------
        DGLGraph
            The constructed graph. The node IDs are in the same order as :attr:`x`.
        torch.Tensor, optional
            The distances for the edges in the constructed graph. The distances
            are in the same order as edge IDs.
        """
        return radius_graph(
            x, self.r, self.p, self.self_loop, self.compute_mode, get_distances
        )

        Forward computation.

        Parameters
        ----------
        x : Tensor
            The point coordinates. :math:`(N, D)` where :math:`N` means the
            number of points in the point set, and :math:`D` means the size of
            the features. It can be either on CPU or GPU. Device of the point
            coordinates specifies device of the radius graph.
        get_distances : bool, optional
            Whether to return the distances for the corresponding edges in the
            radius graph.

            (default: False)

        Returns
        -------
        DGLGraph
            The constructed graph. The node IDs are in the same order as :attr:`x`.
        torch.Tensor, optional
            The distances for the edges in the constructed graph. The distances
            are in the same order as edge IDs.
        
python/dgl/nn/pytorch/factory.py