Lightning-AI / Lightning-AI/pytorch-lightning
Add `CheckpointIO` classes to split checkpoints
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- Python
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Description
## 🚀 Feature
Create new `CheckpointIO` classes that allow:
- Splitting a checkpoint by keys, enabling #5339
- Splitting a checkpoint by size, relaxing the memory and storage constraints
### Motivation
See existing discussions in https://github.com/huggingface/transformers/issues/13548 for why these are interesting features to end-users.
### Pitch
`Trainer(plugins=CheckpointKeySplitterIO())` or `Trainer(plugins=CheckpointSizeSplitterIO(max_size="10GB"))`
### Alternatives
Have users create and maintain these solutions. The `Trainer` should allow it.
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cc @borda @tchaton @justusschock @awaelchli @jjenniferdai @rohitgr7
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 with the Trainer plugin entry point and review the linked discussion in issue #13548 for the intended use cases. Define the CheckpointIO interfaces for splitting checkpoints by keys and by size, then make the proposed Trainer plugin configurations work and verify that both splitting modes meet their stated goals.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100