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

Training inference time and test data #61

Closed
prinshul opened this issue Apr 3, 2024 · 2 comments
Closed

Training inference time and test data #61

prinshul opened this issue Apr 3, 2024 · 2 comments

Comments

@prinshul
Copy link

prinshul commented Apr 3, 2024

What GPUs and how many of them are used for training/inference?

What is the total training and inference time?

Thanks

@prinshul prinshul changed the title Training inference time Training inference time and test data Apr 3, 2024
@prinshul
Copy link
Author

prinshul commented Apr 3, 2024

Also how exactly is testing/inference done? On the same four participants ?
Unable to find test script in the repo.

@evonneng
Copy link
Collaborator

evonneng commented May 8, 2024

Hi! Sorry for the delay in response.

I used a single A100 for all such. And total train time for each component can be parallelized but in general, face model = 1 day, body vq model = 1 day, body diffusion model = 3 days. Of course, everything can be gpu parallelized for faster run time as well.

Inference time depends on the length of sequences. but for instance, to run all sequences in our test set (8 s) for 3 iterations took ~30 minutes - 1 hour.

Inference script can be found here: https://github.com/facebookresearch/audio2photoreal/blob/main/sample/generate.py

@prinshul prinshul closed this as completed May 8, 2024
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