hmm, yes, it is tricky, the network should produce multiple ordered predictions, but you have only one observation for particular inputs (in usual case), so you unsqueeze the target. And as quantile specific gradients will still be different, prediction producing layer will eventually learn to output reasonable quantile grids, conditioned on input.