and the general idea here is you you try and regularize a models prediction to be less sensitive to small perturbations applied to to the the input data so that in potato can be label or unlabeled and when we say perturbations we're basically talking about adding some sort of noise to the inputs ampuls and so yeah you want your model to given a sample and an Augmented sample or perturbed sample you want the models predictions to be similar on both I think that's what I just said so enforce the predictions to be similar