📖 [Story] Caching and Compile time improvements
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Story
Story: Runtime & Memory & Serialization
- Dominant language
- Python
- Stars
- 3k
- Forks
- 410
- Avg merge
- 3d 18h
- Merged PRs (30d)
- 78
Description
TL;DR
There are a collection of features which work together to improve compile times
Goal(s)
We want to reduce the time it takes to compile models. Some parts are out of our control (dynamo graph capture) but we can improve on the TensorRT side.
Tasks
### Tasks
- [ ] https://github.com/pytorch/TensorRT/issues/2674
- [ ] Weight Refit
- [ ] Engine Caching
Additional context
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 linked issue 2674 and the TensorRT repository context for the two unlinked tasks, Weight Refit and Engine Caching. The story is complete when the compile-time improvements are implemented and their performance impact is demonstrated, but it does not identify files, entry points, or tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- compilers, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100