are being updated so the gradient is passing through these I'm pretty sure that the idea with theta tilde is those parameters are frozen so they're they're not they're not updated in the objective function data here yeah yeah so this is the instead of thing yeah these would be these are two different settings but but yeah in both cases they're the model parameters question here is the transformation function so so the augmentation function basically the way that you're adjusting your input samples so the first version sees X's or actual