@smivv, could you share the code you used to enable QAT on the model?

We currently do support quantization of Sigmoid, Hardsigmoid and ReLU6. cc @jerryzh168 to confirm
QAT of UpsamplingBilinear2d isn’t supported so you will have to wrap it with Quant-Dequant block.
Maybe looking at the code will help, we also have a tutorial here https://github.com/pytorch/vision/blob/master/references/classification/train_quantization.py 8 for reference
QAT training takes longer, due to the insertion of observers and fake quant modules in the model
It is possible to do QAT on GPU, but you will need to move the model to CPU before running convert.