deepspeedai / deepspeedai/DeepSpeed
[REQUEST] Add automatic logging of parallelism and ZeRO config to WandbMonitor
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- Dominant language
- Python
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Description
Description
Currently, WandbMonitor in deepspeed/monitor/wandb.py initializes W&B and supports logging.
I would like to suggest adding a simple method (or automatic hook) in WandbMonitor that updates the W&B config with the core distributed training settings after initialization is complete. (Parallelism Rank & Zero Config)
Proposed approach
Add a method such as monitor.update_config(engine) (or update_config_once()) that extracts these values from the DeepSpeed engine (or other getter method) and updates W&B config once the engine is fully initialized.
This should keep overhead minimal while adding significant value (experiment settings) for users using distributed learning.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start in deepspeed/monitor/wandb.py and trace WandbMonitor initialization alongside the DeepSpeed engine initialization mentioned in the request. Identify which parallelism ranks and ZeRO configuration values are available after initialization. Done means W&B config is updated once with those distributed-training settings while keeping overhead minimal.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- distributed-systems, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100