Lightning-AI / Lightning-AI/pytorch-lightning
Add more logging options to `MLFlowLogger`
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- Dominant language
- Python
- Stars
- 31.4k
- Forks
- 3.8k
- Avg merge
- 6d 7h
- Merged PRs (30d)
- 6
Description
### Description & Motivation
The PL `MLFlowLogger` allows to log hyper-parameters and metrics. However, the core class (see [here](https://github.com/mlflow/mlflow/blob/master/mlflow/tracking/client.py#L61)) now allows to log images, tags, artifacts, text, table and figure.
It will be great if `MLFlowLogger` supports these functionalities natively as well!
### Pitch
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### Alternatives
_No response_
### Additional context
_No response_
cc @lantiga @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 inspecting the existing MLFlowLogger entry point and the MLflow tracking client linked in the issue. Compare the logger's current hyper-parameter and metric support with MLflow's image, tag, artifact, text, table, and figure APIs. Done means the requested capabilities are exposed natively by MLFlowLogger and verified for each listed type.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, observability
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100