How to Perform Static Quantization Directly on an ONNX Model Using Intel® Neural Compressor?

Hello,

I'm using Intel® Neural Compressor (INC) to perform static quantization on my custom PyTorch model. I followed this script which demonstrates how to apply static quantization using INC on a PyTorch model.

My goal is to obtain the final quantized model in ONNX format. However, after quantization, saving the q_model results in a .pt file (PyTorch format). I also found that exporting quantized PyTorch models to ONNX is problematic due to limited support and compatibility issues, especially with static quantization.

My Question:

Is there a way to perform static quantization directly on an ONNX model using Intel® Neural Compressor to produce a quantized ONNX model as the output?
Alternatively, is there a specific method to export the statically quantized PyTorch model to ONNX format while addressing the compatibility issues?
Any guidance or examples on how to achieve this would be greatly appreciated.

Thank you!

Comienza con el ejemplo enlazado quantize_with_inc.ipynb e inspecciona cómo guarda el modelo PyTorch cuantizado. Verifica si se admite la ruta de entrada/salida de ONNX solicitada y si este ejemplo debería incluir un ejemplo de exportación. Se considera terminado cuando haya una respuesta o un ejemplo claro y reproducible que cubra la cuantización directa de ONNX y la ruta de exportación alternativa.