Bug in trainer.build_model()?

[anastasiadk]

Hi,

thanks for sharing the code. I have a question about the discriminator loss for real images - self.d_loss_real in trainer.build_model(). You compute it as
self.d_loss_real = tf.reduce_mean(tf.abs(AE_x - x))
Before that you compute x to be normalized versions of real images by using x = norm_img(self.x), but AE_x is a de-normalized version of the discriminator output for x. Is it a bug, or am I missing something? I'm talking about this commit.

Thanks in advance,
Anastasia