I’am learning GAN recently with book GANs in Action and other programs on the Internet. And I jsut learned how to use GAN to generator mnist number. However, I noticed that neither the book nor other programs used shuffle when training discriminator(figure1). So I tried using shuffle, but the outcome was poor, almost was noise(figure2&3). And I increased the interation, the outcome using shuffle imporved, but it took a lot more time and even still worse than not using shuffle. I was told using shuffle dataset will accelerate the model to find better parameters, but why it was at opposite when training GAN?

figure1:this is keras code, but the result was same using pytorch