have the network produces a representation here this is 2,000 dimensional and then it does it adds on top this classification layer this classification layer is simply a linear layer and then a softmax on top so how you have to imagine this is that there is a representation space this 2010 shell space and the representations are made in such a way that the labels such that sorry let's have three classes here the representations are made in such a way that a linear classifier can separate them correctly right so here