Lightning-AI / Lightning-AI/pytorch-lightning
MLflow logger to log config.yaml as artifact
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- Dominant language
- Python
- Stars
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- Avg merge
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- Merged PRs (30d)
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Description
### Description & Motivation
The MLflow logger does not currently log the config.yaml file when using LightningCLI, meaning MLflow does not contain a complete record of an experiment
### Pitch
The config.yaml file to be logged as an artifact
### Alternatives
None, currently use a confluence page to link the MLflow run and config.yaml which is tedious
### Additional context
_No response_
cc @borda
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 by locating the MLflow logger and the LightningCLI configuration handling in the repository. Confirm how config.yaml is produced and where logger artifacts are registered; the work is done when the configuration file appears as an artifact in the corresponding MLflow run.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100