def forward(self, input):
    center = input[:, -1, :].unsqueeze(1)
    delta_x = input[:, :, 0:3] - center[:, :, 0:3]  # (B, npoint, 3), normalized coordinates
    for case in switch(self.dataset):
        if case('3DMatch'):
            z_axis = cm.cal_Z_axis(delta_x, ref_point=input[:, -1, :3])
            z_axis = cm.l2_norm(z_axis, axis=1)
            R = cm.RodsRotatFormula(z_axis, torch.FloatTensor([0, 0, 1]).unsqueeze(0).repeat(z_axis.shape[0], 1))
            delta_x = torch.matmul(delta_x, R)
            break
        if case('KITTI'):
            break