Lightning-AI / Lightning-AI/lightning-thunder
Add support for random ops in OpInfo
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- Dominant language
- Python
- Stars
- 1.5k
- Forks
- 121
- PR merge metrics
- No merged PRs in 30d
Description
## 🚀 Feature
Modify OpInfo test generation to seed random ops to properly test consistency.
### Motivation
OpInfos allow us to quickly test consistency of our ops against PyTorch's implementation. They don't currently support random operators.
### Pitch
### Alternatives
### Additional context
Came up when adding `exponential_` support to thunder
cc @apaz-cli
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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 locating the OpInfo test-generation entry point and existing consistency tests, then compare how deterministic and random operators are represented. Verify completion by exercising a random operator such as exponential_ and confirming seeded generation produces repeatable consistency checks against PyTorch.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- testing-qa
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100