Wrong normalization on Kitti?

[autosquid]

Around https://github.com/chenfengxu714/SqueezeSegV3/blob/master/src/tasks/semantic/dataset/kitti/parser.py#L171:

proj = torch.cat([proj_range.unsqueeze(0).clone(),
                      proj_xyz.clone().permute(2,0,1),
                      proj_remission.unsqueeze(0).clone()])
proj = (proj - self.sensor_img_means[:, None, None]) / self.sensor_img_stds[:, None, None]

The order of channels in proj is (range, z, x, y, remission), but sensor_image_means is in the order of (range,x,y,z,signal) or something else (based if it's V321 or V353)?

So I guess here's something wrong?