Using `bayeux` to organize `numpyro` models and access features
Open
Nobody has claimed this yet.
enhancement
wontfix
- Dominant language
- Python
- Stars
- 13
- Forks
- 3
- Avg merge
- 19h 43m
- Merged PRs (30d)
- 1
Description
@dylanhmorris has put me onto bayeux. I think this would be a useful addition.
bayeux has some handy features:
- A
from_numpyromethod that coverts anumpyromodel into abayeuxmodel object. bayeuxmodels have a debug mode https://jax-ml.github.io/bayeux/debug_mode/ which covers #197 and makes #199 obsolete.bayeuxmodels can be cast to other libraries, e.g.optimistixwhich can find their MAP values (which can be handy).
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 with bayeux’s from_numpyro method and the debug-mode and model-casting documentation linked in the issue. Review how DynODE currently organizes NumPyro models, then define and verify the integration scope, including whether it addresses #197 and makes #199 unnecessary.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100