pymc-devs / pymc-devs/pytensor
Restructure modules
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- Dominant language
- Python
- Stars
- 644
- Forks
- 208
- Avg merge
- 2d 14h
- Merged PRs (30d)
- 16
Description
Description
We have very long modules with arbitrary names like tensor.basic vs tensor.extra_ops, and nlinalg vs slinalg. We should organize the modules by operator functionality. I would error on the side of having too many modules than too few. tensor.array_creation, linalg.solve, linalg.decomposition, ..., or even at the level of individual ops when they are complex enough.
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 reviewing the existing tensor.basic, tensor.extra_ops, nlinalg, and slinalg modules and grouping their operators by functionality. Done would mean a consistent module structure such as tensor.array_creation and linalg.solve or linalg.decomposition, but the issue does not define the full grouping or migration scope.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- developer-experience
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100