@anijain2305 For the `q_conv2d`, we will add two more arguments. ```python output_min=0, output_max=0 ``` These will be used for restrict the output range, which could be calculated previously. see TFLite's `CalculateActivationRangeUint8` function.
>From my experience, we needn't `q_relu`. But we need `q_add` / `q_concate` and >so on. I suggest we use `MobilenetV2` quant model for example, which is used >very widely and have common ops we should consider. For example, `depthwise >convolution / add / pool and so on`. -- 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-496763873
