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

Make losses same as metrics? #226

Open
maxcw opened this issue Mar 12, 2022 · 0 comments
Open

Make losses same as metrics? #226

maxcw opened this issue Mar 12, 2022 · 0 comments

Comments

@maxcw
Copy link

maxcw commented Mar 12, 2022

In the training object, the default losses are MSE, binary cross-entropy, and MAE. Is this what the models are minimizing? If so, how can we make the losses the same as the super-resolution metrics? Why aren't they the super-resolution metrics like PSNR and perceptual loss?

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

1 participant