> > We can certainly start with symmetric to flush the flow, while keeping in > > mind that we can share as much infrastructure as possible between them. > > All the tflite quantized models I've tested use the asymmetric uint8 > quantization. If you are planning to use those as examples, it will be hard > to debug if you throw in the change to symmetric.
TensorFlow quantization-aware training supports both asymmetric/symmetric. We are seeing asymmetric models because it is the default. If we'd like to start from symmetric approach, set the [symmetric](https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/contrib/quantize/python/quantize_graph.py#L149) and go on. Which, requires extra effort I think... -- You are receiving this because you are subscribed to this thread. Reply to this email directly or view it on GitHub: https://github.com/dmlc/tvm/issues/2351#issuecomment-497648135
