Reviewed DataModule design+docs+types

In this MR, I try to review the use of the data module and go further in simplifications for the whole code:

• Slightly streamlined the datamodule approach
• Added documentation
• Added type annotations
• Added some TODOs for further discussion

Closes #7 (closed).

TODO:

• (@dcarron) Implement/document/type hint normaliser (ensure it is used correctly through all the models; integrate on the train script) and that train CLI works!
• (@andre.anjos) Deal with import reweight_BCEWithLogitsLoss

src/ptbench/data/datamodule.py

@@ -95,7 +95,11 @@ class _DelayedLoadingDataset(torch.utils.data.Dataset):
     ):
         self.split = split
         self.raw_data_loader = raw_data_loader
-        self.transform = torchvision.transforms.Compose(*transforms)
+        # Cannot unpack empty list
+        if len(transforms) > 0:
+            self.transform = torchvision.transforms.Compose([*transforms])
+        else:
+            self.transform = torchvision.transforms.Compose([])
 
     def __getitem__(self, key: int) -> tuple[torch.Tensor, typing.Mapping]:
         tensor, metadata = self.raw_data_loader(self.split[key])