Remove training with iterable datasets?

[VarIr]

As discussed in #43 training with iterable datasets is rarely used. In particular, training without shuffling might never be useful.
Due to that, the corresponding functionality is not subject to many tests, and was broken for some time, until this was pointed out in PR #43.

While for the time being, the bug is fixed, and additional tests have been put in place, we might want to remove these functions altogether. This could reduce maintenance cost, and improve quality.

[VarIr]

While at it, we might want to let our ShuffledProteinIterableDataset inherit from the BufferedShuffleDataset newly introduced in PyTorch 1.8. From a first glance, it does exactly the same thing.