Sorry for not giving enough context.
This is the problem for using multiple pretrained models, where your data transformation depends on the datasets that you trained the original networks on, not the current dataset that you use.
Right now, I am trying to put the same data through 2 networks trained with different dataset (hence with different normalization) and this become a problem that would be solved if we don’t put the transformation inside the dataset.
But I can see how non-differentiable can be a huge issue here, and my use case probably isn’t the most popular one.
Thank you.