the decision on that basis so I'm sort of I'm applying two random augmentations in order to induce the model to look at look at different parts of the image to to learn what features are relevant for identifying horses alright so fixed match is going to combine these two ideas of pseudo labeling and consistency regularization so we start off with like a small label data set only a few data points we're going to do as much as much learning on that on that data set as possible and then we're going to go and pick some