that I optimized right this is my loss consists of two parts namely a supervised loss which is your classic classification loss right plus an unsupervised loss right and then you have like some sort of a trade-off parameter in front now your supervised loss here this is where this is just the the cross-entropy let's call it h between your predicted labels and your the actual true labels right and the predicted labels say they can be you know kind of a distribution over labels now the magic of course is here in the unsupervised loss and this