Model finetune with LiftPool

[ghost]

Hi! In semantic segmentation section you've mentionned: "We replace all down-pooling and up-pooling layers with LiftDownPool and LiftUpPool". What about encoders where instead of MaxPool strided convolution is used? Should we replace it by the same convolution with stride=1 and LiftDownPool layer? What about norm/activation layers between them?