Wrong calculation of gradient penalty

[Philonoist]

https://github.com/preritj/progressive_growing_of_GANs/blob/04351d69b2e8e9616715f3ac8cb155488953777d/model.py#L85

I think there is a bug here, or at least an implementation of gradient penalty not consistent with the original paper. the alpha coefficient should be randomized per image, and not per pixel. It should be: alpha = tf.random_uniform(shape=[input_shape[0], 1, 1, 1], minval=0., maxval=1.)

We want to sample images along the lines connecting the real and fake images. This does something strange.