microsoft / microsoft/onnxruntime-inference-examples
Yolov8 Static Quantization
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Description
Used the static quantizer on yolov8 architecture and the resulting model have changes in the shape of the weights which is not logical for example a layer original shape is (96,96,1,1) and the resulting shape is (3,)
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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
No source files or tests are named. Start by reproducing the YOLOv8 static-quantization case described in the issue and compare the original (96,96,1,1) weight shape with the resulting (3,) shape. Done means determining whether the shape change is expected and documenting or correcting the behavior with validation.
Written by the indexing model from the issue text.
Assessment
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100