Fixed
- Fixes the problem identified in issue 890, where the lr_scheduler
does not behave as expected when continuing training. The problem is
that the lr_scheduler is kept as part of the optimizer, but the
optimizer is not saved when saving state. Therefore, every time
training is restarted, a new lr_scheduler is created with initial
parameter settings. Fix by saving and restoring the lr_scheduling
separately.