nothing right now for some reason it doesn't do that and I have the feeling that this is a super delicate balance that you have to do because when you train when you start out it's probably not the constant function right it's probably some some distribution and then simply by the fact that you train it and kind of keep it in the so this is certainly an optimal solution but you might be like in some sort of local minimum once you start training and you simply don't get out of it during training and that's why the network has