Hello,
I have seen in many GAN repositories, where tanh is used as a generator activation function, input images not be in the range [-1,1] but in [0,1].
I noticed the same thing when I tried to replicate some networks and train them. When using images normalized in range [-1,1] I get bad images in the first epoch whilst in the other case training, regarding losses and generated images “seems” to be more stable.
More specifically, I want to ask:


Is it “valid” to train such a network, with images in the range [0,1] and tanh as an activation?


Is it valid to use instead (tanh+1)/2 in the outermost layer activation in the generator to enforce the values be in the range [0,1]