Closed flyuuu closed 7 years ago
In some GAN implementations, the discriminator is pre-trained before it is used. However, I think it is a bad idea since most of the time, the discriminator converges faster than the generator. So, having a pre-trained discriminator can no longer contribute much in the training of the generator. In fact, you should allow the generator to catch up to the discriminator during training.
ok, isee, thanks for you answer very much!
thanks for your article (https://medium.com/towards-data-science/gan-by-example-using-keras-on-tensorflow-backend-1a6d515a60d0), i like it. But i have a question want to ask you:
Do we need a fixed discriminator when training the generator in dcgan_mnist.py?
because i think it need fixed.
thanks