I'm going to use pytorch frontend to parse a pytorch model and quantize the model. However, It's not clear for me, how should I set the pytorch quantization API to get same arithmetic results as Relay.
For example, if I set the [QConfig API](https://pytorch.org/docs/stable/quantization.html#torch.quantization.QConfig) as below, and [convert](https://pytorch.org/docs/stable/quantization.html#torch.quantization.convert) the model to a quantized one, will Relay output same results as the quantized pytorch model? ``` my_qconfig = QConfig(activation=FakeQuantize.with_args(observer=MovingAverageMinMaxObserver, quant_min=0, quant_max=255, reduce_range=True), weight=FakeQuantize.with_args(observer=MovingAveragePerChannelMinMaxObserver, quant_min=-128, quant_max=127, dtype=torch.quint8, qscheme=torch.per_channel_symmetric, reduce_range=False, ch_axis=0)) ``` --- [Visit Topic](https://discuss.tvm.ai/t/quantization-pytorch-suitable-pytorch-api-setting-for-relay-quantization/6201/1) 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/3244e71aae2ac122020008ae931f1e552e127fd6228b842e38275219ed93e2e6).
