For > `relay.op.qnn`, e.g. `relay.op.qnn.conv2d` The `qnn` name is consistent with > QNNPack
and > My hope is that different frameworks converge to same qnn ops. QNNPACK takes the quantization approach of TensorFlow/TFLite. I think that when we talking about op in this scenario, it means the quantization arithmetic formula itself rather than how to translate it into code, which is same for QNNPACK and TensorFlow/TFLite. So I guess one dialect should be enough for them. And, I guess the **converge** is more reasonable, if, the `qnn` stands for simply _generic_ quantized nn, but not QNNPACK. -- 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-507098356
