WGAN-GP loss: averaging penalties or not?

Hi @akanimax

First of all many thanks for this amazing contribution.

In the paper, it is stated `we modified the gradient penalty to be the average of the penalties over each input`.
I didn't see any of that in the original MSG-GAN tensorflow implementation, neither in the BMSG-GAN implementation: it seems rather like only the gradient penalty of the higher resolution image is used.

Did I miss something, or is it a slight variation between the paper and the implementation?

Cheers

edit: related to #35