Feature: loss weights

This feature implements a mask on the loss for supervised methods (unsupervised can be added analogously). In order to use it for Rnns, just specify `weights=True` in the constructor, and of course, instead of providing the fit/evaluation data as (input, target), (input, target, weights) should be provided.

**Bonus**: there is also added a `OneLinePrinter` class, a reporter used in order to have a trainer output in the same fashion as the notebook examples (which don't use a reporter).