yes, you are right, its a kind of GAN
Because loss is a function of both B(A(x)) and A(x), so, even if I detach the prediction of A(x) for B(A(x)), I still get gradients from A(x)… (the networks actually learn something by doing this)
What makes me confused is that if I don’t do the detach, the networks just learns nothing…