microsoft / microsoft/onnxruntime
[Feature Request] Offline optimization for CoreML
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- Dominant language
- C++
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Description
### Describe the feature request
When you load a model using CoreMLExecutionProvider it takes a very long time, even minutes for big models. If you look at the logging of onnxruntime you can see that it is saving .mlpackage files in a temp folder. Can the possibility of loading saved compiled model, with offline optimization, like as in other EPs be added to CoreML EP?
### Describe scenario use case
To speedup model loading when using CoreML provider.
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 at the CoreMLExecutionProvider implementation and compare how other execution providers support loading saved compiled models. Done means CoreML can reuse an offline-optimized compiled model instead of recompiling during model loading, with the behavior verified for the stated model-loading scenario.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- machine-learning, mobile-dev
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100