Zehaos:

AFAIK, Tensorflow can export QAT model that contains FakeQuant Op, and transport the model to TFLite. In my opinion, we can export a quantized model that only contains FakeQuant Op(in ONNX Custom Op) and Standard ONNX Ops. This make the quantized model more flexible.


For qat we have fake quant ops, but for inference we don’t, we have quant/dequant ops instead.
If you are talking about preserving quant/dequant op without fusing them into quantized ops(like quantized::conv2d), we do have this support in graph mode quantization, which will come up pretty soon