Different optimizers for generator and discriminator in GAN
Maybe you can share the link to this advice, so we get the context or arguments, because it doesn’t make a lot of sense to me.

You specifically ask why it’s possible to choose different optimizers. The only requirement that the relation between the discriminator and the generator must meet, is that the discriminator must be able to handle the generator output. Everything else can be different, including the optimizer, prediction algorithm, any regularization, and so on. You could have a neural net for the generator and Mechanical Turk could be your discriminator.

There is something to be said for having different algorithms or architectures between the generator and the discriminator, essentially so the discriminator is able to pick up on the weaknesses of the generator. (Because they won’t share the same weaknesses, hopefully.) But to have everything the same and change only the optimizer? I don’t see the point in that.