These works well for some svg that are simple and already in training data but doesn't work for harder svgs, even simple one if they are out of distribution of training data.

In simon's example whole purpose is to make it draw something that it has not seen before but can easily infer from geometry, spatial arrangement. I think it makes a fun problem.