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

The papar doesn't use the sigmoid function. #7

Open
dongdong092 opened this issue May 20, 2018 · 3 comments
Open

The papar doesn't use the sigmoid function. #7

dongdong092 opened this issue May 20, 2018 · 3 comments

Comments

@dongdong092
Copy link

While in your code,i see the sigmoid function in the last layer of the discrimator. I've noticed that you may have try the model with the linear layer instead of the sigmoid function.Does it work well?

@godisboy
Copy link
Owner

godisboy commented May 21, 2018

Hi @dongdong092
In the original paper, the author had claimed that they used the standard objective function for GAN.
image

@dongdong092
Copy link
Author

But with Cross entropy it will become JS divergence again, why not use WGAN's method to use D(X) as the loss function directly?

@zhangqianhui
Copy link

@dongdong092 It use the original loss: -log d(sigmoid(x)) = softplus(-x). You can use wgan loss. But it may not get better results.

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

3 participants