that allows us to do this very efficiently it's called the mask convolution or the pixel RNN fix the scene and style models and and and and it also makes sense because CNN's were also invented by the same first author so he just use pixel cnn's to aggregate the context of the top few rows of batches and once you lay that out on top of the grid of matches you can predict the bottom patches in a very parallel fashion so here is an example of how it would look like for an actual image when you grid it into patches so take this