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

Synchronize quantizer setups for DistributedDataParallel cases #431

Open
vshampor opened this issue Jan 22, 2021 · 1 comment
Open

Synchronize quantizer setups for DistributedDataParallel cases #431

vshampor opened this issue Jan 22, 2021 · 1 comment
Assignees

Comments

@vshampor
Copy link
Contributor

Now that the quantizer setup is being decided during create_compressed_model, and for precision init cases the resulting setup is dependent on the data loaders used for initialization, there is a possibility for DDP that each process may receive significantly different data values, and then compute a different quantizer setup each; since the entire quantizer setup is not technically a torch.Tensor, it cannot be broadcasted to all processes using PyTorch facilities.
A special tensor-only synchronization object is required so that the precision init (determining the quantizer setup) only happens in one process of the DDP group, and then the resulting quantizer setup is broadcasted to other processes in the group.

@vshampor vshampor self-assigned this Feb 3, 2021
@fxmarty
Copy link

fxmarty commented Apr 18, 2023

Hi @vshampor , was this implemented in nncf?

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