Onnx to tensorrt conversion for input layer: cast uint8 to fp32
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Description
My pytorch and onnx model has an uint8 to fp32 cast layer which divides by 255. This cast layer is applied to the input tensor. When i convert the onnx model to tensorrt INT8 i get the following warning:
“Missing scale and zero-point for tensor input, expect fall back to non-int8 implementation for any layer consuming or producing given tensor”
For INT8 should i remove the cast layer before exporting the onnx model or does tensorrt deal with it itself? What is the recommended approach for best INT8 performance?
Platform is Jetson Orin AGX, Xavier NX and Orin NX
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Research direction
The issue names no repository files, entry points, or tests. Start by investigating the ONNX export and TensorRT INT8 conversion path for the input cast and its missing scale warning. Done would require a confirmed recommendation for handling the cast and its effect on INT8 performance.
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Assessment
- Tech stack
- pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100