Hi @JoeyChou I am not sure what you mean by int8 -> uint8 conversion.
If you want your conv2d and dense inputs and weights to be of specific data type, yes that is certainly possible with QNN Legalize pass. An example of this is for Intel VNNI instructions which prefer `uint8` datatypes for feature maps and `int8` for the weights. Naturally, the pre-quantized models might not follow this rule. So, QNNLegalize inserts `requantize` node before the conv2d and dense to satisfy the datatype restrictions. Please look at an example here https://github.com/apache/incubator-tvm/blob/master/python/tvm/relay/qnn/op/legalizations.py#L296-L300 https://github.com/apache/incubator-tvm/blob/master/python/tvm/relay/qnn/transform.py#L71-L116 https://github.com/apache/incubator-tvm/blob/master/tests/python/relay/test_pass_qnn_legalize.py#L295 --- [Visit Topic](https://discuss.tvm.apache.org/t/support-for-pre-quantized-model-int8-uint8-conversion/8064/2) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/9a23daaf447ef77a359bb5d0cb9db6b330ce1dedfeff86ea901581861068561b).
