Feature: Set universal seed / RNG for reproducibility

Make sure that everything is seeded. This plays a bigger role when checkpointing and resuming training, as this should never affect training performance.

Especially important is shuffling of the dataset, whatever initial random seed a model has for weights, any optimizer / trainer seeds.