MLTensor export to GPUBuffer with custom usages?
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 22/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Active
- Tech stack
- web-dev
- Domain
- api, machine-learning
Research direction
The payload names no source files; the spec is a Bikeshed document in the webmachinelearning/webnn repository, and the linked context is the discussion in PR #942. Read the MLTensor export-to-GPUBuffer section and the WebGPU buffer usage flags it references, then decide with the maintainers (cc'd bbernhar) which usages to allow. Done means a proposed API shape that the thread agrees on, not an implementation.
Written by the indexing model from the issue text.
Description
As suggested https://github.com/webmachinelearning/webnn/pull/942#discussion_r3868686914 it would be nice to allow custom GPUBufferUsage, e.g., GPUBufferUsage.MAP_READ or GPUBufferUsage.INDIRECT for instance
Otherwise it limits the areas where the exported buffer can be used, e.g., prevents mapAsync or indirect operations.
cc @bbernhar
- Dominant language
- Bikeshed
- Stars
- 566
- Forks
- 72
- Avg merge
- 6d 5h
- Merged PRs (30d)
- 1
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
- Read the contributing 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.
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