Allow pytorch backend when available in PyMC
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Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 207
- Forks
- 28
- Avg merge
- 7d 21h
- Merged PRs (30d)
- 1
Description
The barebones PyTorch backend should be in in the next PyTensor release and subsequent PyMC.
I think the best way to test it out and gather info on what Ops are most needed is to give access from nutpie, as it will:
- Feel like experimental on experimental
- Be tested by more code-savy people
What do you think?
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 how nutpie exposes backend support and how the barebones PyTorch backend is expected to arrive in PyTensor and PyMC. Confirm the intended scope and the Ops that need support before implementing; done should mean PyTorch can be selected when available and its behavior has been tested across representative nutpie code.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- backend, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100