Port HMM from Pyro
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- machine-learning
Research direction
Start by reading PRs 2273 and 2274 alongside the Pyro HMM distributions they port. Review the proof-of-concept implementation, tests, docstrings, documentation, and optimization work. Done means the HMM distributions are ported to NumPyro with the associated tests and documentation in a reviewable form.
Written by the indexing model from the issue text.
Description
I suggest porting the HMM distributions from Pyro to NumPyro.
I have to stacked PRs with the proof of concept:
I paired up with Claude work on the port and tests and optimization.
The PRs are long: mostly because docstrings and tests and docs. But I am aware this might be hard to review so now that the proof of concept is up, Im open for suggestions: stacked PRs or review as it is ... or any other options.
Thoughts @fehiepsi @Qazalbash ?
- Dominant language
- Python
- Stars
- 2.8k
- Forks
- 334
- Avg merge
- 2d 8h
- Merged PRs (30d)
- 67
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
- Read the contributing 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.
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