Most architectures are released following some painful engineering. So I also +1 others that suggest starting off with an architecture that made its name for classification task

Having two gans is not a problem. Although for different purpose it exists since a long time (cyclegan). What's important is that your loss and/or other constraints must be precise to make sure to avoid one gan learns both and other learns identity. It's also double the concerns for instability during training. Good luck!