Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Discriminator loss function #12

Open
baumgach opened this issue Oct 24, 2017 · 1 comment
Open

Discriminator loss function #12

baumgach opened this issue Oct 24, 2017 · 1 comment

Comments

@baumgach
Copy link

baumgach commented Oct 24, 2017

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?

@haleqiu
Copy link

haleqiu commented Mar 25, 2019

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

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants