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

Optional fusion of convolution and BatchNorm layers during inference #185

Open
theabhirath opened this issue Jul 26, 2022 · 0 comments
Open
Labels
enhancement New feature or request layers Related to the Layers module - generic layers for reuse by models

Comments

@theabhirath
Copy link
Member

theabhirath commented Jul 26, 2022

Convolution and BatchNorm layers have been fused during inference in many models, most notably LeViT. It would be a good idea to have this as an option in the conv_norm function in Layers with a dispatch specifically for BatchNorm.

@theabhirath theabhirath added enhancement New feature or request layers Related to the Layers module - generic layers for reuse by models labels Jul 26, 2022
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request layers Related to the Layers module - generic layers for reuse by models
Projects
No open projects
Development

No branches or pull requests

1 participant