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

About the memory #36

Closed
YiningWang2 opened this issue Dec 20, 2021 · 1 comment
Closed

About the memory #36

YiningWang2 opened this issue Dec 20, 2021 · 1 comment

Comments

@YiningWang2
Copy link

Well done!I am quitly wondering that using 4 TITAN 2080 with 12G, can i train this model? will i meet the error on out of the memory?

@gahdritz
Copy link
Collaborator

gahdritz commented Dec 20, 2021

You'll likely be able to train the model using AlphaFold's initial training settings (256 crop size, 128 MSA sequences, 1024 extra MSA sequences), which work even on our 11GB 2080 Ti's. You'll probably need to keep the "clear_cache_between_blocks" option enabled in the extra MSA stack, which comes with a minor performance hit. Training on the full finetuning settings, though (crops of size 384, extra MSAs of size 5120, etc.) is currently out of the question with just 12GB. We're working on fused or low-memory versions of components of the model, so that may change in the future, but even then, 12 GB will probably be a stretch. Of course, the model is fully configurable, so you may also reduce the numbers of blocks, etc., if you want.

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