Simplify distributed training

[futurely]

🚀 Feature

Simplify distributed training so that users do not have to manually setup graph store, sampler and kvstore which is inefficient for development and error prone.

Motivation

The only difference between distributed and non-distributed training in PyTorch-BigGraph is adding an command line argument "--rank rank" and a few more configs.

The training script automatically handle the two situations.

Euler requires knowing the hosts in the cluster. But the training script is also very concise to run distributed training.

Pitch

The framework transparently starts distributed training so that users can use it with minimal effort and without worrying about the underlying details.

[zheng-da]

I totally agree with you that the training script should set up everything for distributed training. It's also in our plan.

[github-actions]

This issue has been automatically marked as stale due to lack of activity. It will be closed if no further activity occurs. Thank you

[github-actions]

This issue is closed due to lack of activity. Feel free to reopen it if you still have questions.