Lightning-AI / Lightning-AI/pytorch-lightning
Resuming should allow to differentiate what to resume (steps/opti/weights)
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- Dominant language
- Python
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Description
Currently it is possible to either resume only the full training state (epoch/global steps / optimizer / scheduler options / and weights), or only the weights.
I would like to be able to switch the optimizer at some point, i.e. skip restoring optimizer/scheduler, but still load the epoch/global steps. I only see a way to do this with hacks at the moment. Any other way? Could this be a feature, to specify in the trainer.init function specifically what to restore/what not to restore?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
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- 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.init entry point and the existing resume behavior described in the issue. Trace how epoch/global steps, optimizer, scheduler, and weights are restored, then define a way to select each category independently. Done means resuming can restore steps and weights while skipping optimizer and scheduler state.
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
- 30/100