there are logos that are compositional, but most logos are abstractive - eg. the hammer and sickle logo only makes sense because we have prior knowledge of what

there are logos that are compositional, but most logos are abstractive - eg. the hammer and sickle logo only makes sense because we have prior knowledge of what hammers and sickles look like. You could learn an abstract representation of hammers from a dataset of hammers, but not from a dataset of logos. I think GANs work best on images with hierarchical composition like human faces.