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Discriminator loss function

Open baumgach opened this issue 6 years ago • 1 comments

I don't understand how exactly the loss function in line 5 of algorithm 1 in the original WGAN paper is implemented here. In your code you minimise

self.discriminator_loss = discriminator_loss_fake + discriminator_loss_real

However, according to the paper shouldn't it be maximising:

self.discriminator_loss = discriminator_loss_real - discriminator_loss_fake

or alternatively minimising:

self.discriminator_loss = discriminator_loss_fake - discriminator_loss_real

That is, should this be a minus in your total loss?

baumgach avatar Oct 24 '17 10:10 baumgach

I thought the first algorithm is implemented for cross entropy, which discriminator_loss_fake + discriminator_loss_real

haleqiu avatar Mar 25 '19 04:03 haleqiu