Formalize MLCube interface for FL
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 160
- Forks
- 31
- PR merge metrics
- No merged PRs in 30d
Description
As suggested by @msheller here, it'd be helpful to MLCube authors interested in federated {learning, evaluation} to follow a formal interface description. Having a formal interface specification would also allow us to write tooling, for example, to automatically assess compatibility between a given MLCube and the FL framework intending to run it.
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
No files, tests, or entry points are named. Start by reviewing the discussion referenced from MLCube examples pull request #40, then establish the formal interface for federated learning and evaluation and the compatibility tooling; done means the specification and tooling requirements are agreed and documented.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, tooling
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100