unsupervised loss this is what's described here in this part right so the unsupervised loss is going to be this age between P and Q and we'll see what P and Q is so if for the unsupervised loss you two of course want to start with an unlabeled example then you have the same sample go into two different pipelines in the first pipeline up here what you do is you so-called weekly augmented and here we're dealing with images so we have to talk about image augmentation so image augmentation has long been used in supervised learning to kind of give you