of number some sort of histogram that they produce and if the histogram is very spiky and close together around zero then they conclude that this network is good and if the histogram is very spread out like this they conclude that the network is bad now these histograms as you might expect they are computed not from the final trained Network but they are computed from the initial Network so here they show at least you know in this case it seems to be that there is a general correlation between the trained accuracy and how