The above example after annotation: ``` data | | sim_quantize(QINPUT) sim_quantize(QINPUT) | | add(bn_bias) | ... / | add ``` data is usually output of previous conv2d. There are duplicated simulated_quantize. Followed add in both branches will convert the int8 to int32. So simulated_quantize + add in both branches which will be translated to `right_shift + cast(i8) + cast(i32)` We use stop_fusion to ensure that previous conv2d result will be casted to int8 before saving in global memory.
You will see the difference running quantized ResNet-50 v2. --- [Visit Topic](https://discuss.tvm.ai/t/improving-quantization-accuracy-with-more-precise-bias/2444/9) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.ai/email/unsubscribe/9c1b4289f3c2f4ab9d9ff2f427d8e04f42aac1dc4c8734fd7507d9c1cb99825e). Tianqi Chen, UW, Seattle, WA, 98105, United States http://tracking.discuss.tvm.ai/tracking/unsubscribe?msgid=c2p7vXW3rOvqHpEkdLxa0w2
