algorithm the next idea introduced in the meta pseudo labels is to avoid this memory requirement of having two high capacity classification models in memory because say you have an efficient net as the teacher network as well as the student network now you have to keep both these models in memory especially when you're doing the gradient update for the teacher Network si idea to avoid that is do first train a large teacher network on the label dataset and then use it to produce this new distribution on the unlabeled data and then you use a