How is TorchBench applied to testing new versions of PyTorch?
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 1k
- Forks
- 346
- PR merge metrics
- No merged PRs in 30d
Description
Hello, may I ask what tasks will be used for end-to-end testing before the release of the new version of PyTorch?
Will the test focus on the consistency of metrics between the previous and subsequent versions, such as the loss of training tasks, iteration speed, etc
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
The issue names TorchBench and PyTorch but no file, test, or entry point. Start by identifying the release-testing workflow and the end-to-end tasks and metrics it uses; done means documenting whether comparisons cover loss, iteration speed, and other release checks.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- performance, testing
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100