Hands-On Deep Learning Algorithms with Python

Total loss

We just learned the loss function of the generator and the discriminator combining these two losses, and we write our final loss function as follows:

So, our objective function is basically a min-max objective function, that is, a maximization for the discriminator and minimization for the generator, and we find the optimal generator parameter, , and discriminator parameter, , through backpropagating the respective networks.

So, we ...