Is my loss function right? WGAN
-
10-12-2020 - |
题
I am new to GANs, but I was able to train a DCGAN decently. I decided to try a WGAN (not the improved one). I seem to get outputs, but my loss doesn't seem to converge for the generator.
I am using the loss function
from keras import backend as K
def wasserstein_loss(y_true, y_pred):
return K.mean(y_true * y_pred)
for both the critic and generator. I am labelling real images as -1 and fake ones as 1.
Here's my loss over time:
Is the generator loss supposed to behave like that? Even though the discriminator loss seems to behave as expected, is a swing that large normal?