not used for adaptation they're just used for metal learning so D test is where X tests and Y tests will be sampled from so the game that you're playing then is read in D train output Phi and make sure that Phi is good for classifying points from D test for that same task so now we can actually complete the meta learning problem definition so the adaptation step we can write more compactly as some function f theta star of D train so f theta star reads in D train and outputs Phi star so now all we have to do is learn theta