nan loss for shallow networks

[numisveinsson]

When deep supervision is toggled on and you have two layer networks (for smaller patched datasets), the deep supervision weights end up being np.array([0]). When they get normalized, they become NaN which end up in NaN loss values. Should be easy to fix here.

Thank you!

Numi Sveinsson
numisveinsson.com