lincc-frameworks / lincc-frameworks/hyrax
Mechanism for user-defined artifacts in MLFlow
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- Dominant language
- Python
- Stars
- 41
- Forks
- 7
- Avg merge
- 5d 1h
- Merged PRs (30d)
- 8
Description
Feature request
MLFlow does a good job of displaying any sort of artifact related to a training or inference run, however, Hyrax doesn't provide any sort of mechanism for users to define additional artifacts to be saved along side.
We've introduced a little bit of help for TensorFlow that allows users to save metrics related to training that are returned from train_step, but this request is more broad than that.
During the most recent Hyrax tech & science bi-weekly meeting, Peter Ferguson mentioned that there was a lot of effort put into saving sample images associated with training and inference. MLFlow can support this in a much more organized way, so we should investigate a friendly way to allow Hyrax users to exploit this.
Contributor guide
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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 reviewing the existing TensorFlow support for metrics returned from train_step and how MLFlow organizes artifacts. Investigate a user-facing mechanism for saving additional artifacts, including sample images from training or inference. Done means Hyrax users can define and persist these artifacts in an organized MLFlow-compatible way.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100