Enhance data loading and transformation performance #68
Description
The data loaders most likely are pretty inefficient at the moment. Let's try to profile and optimise GPU utilisation.
Potential problems atm:
- data is concatenated from potentially many data loaders into a big batch
- distmap (for boundary loss) is calculated in the data loader
- one hot encoded representations are created multiple times
- tensors are potentially moved from gpu to cpu and back multiple times (plus some bumpy operations)