single pass through the walk through the model but the prediction of each token only depends on the things in front of it in the permutation order and they do this by having these kind of two stream is masked to stream attention where they basically have not only not one hidden representation like in classic transformers but they have at each step two hidden representations one they call H only called G so the HS are initialized with the embeddings of the tokens and the g's are just initialized randomly and then they get transformed