I am new and currently learning about GANs, I have a query as follows:

Suppose I have trained my conditional GAN on MNIST dataset where I have conditioned on gaussian noise with different means. Ex:

Gaussian noise with mean 1 will give output as image of 1.

Gaussian noise with mean 2 will give output as image of 2. and so on.

After training , suppose I give gaussian noise with mean 1.5, what output image should I expect?

This logic I am extending for an Image to Image translation task. Suppose I have conditioned my GAN(pix2pix) model to add *effect1* on input image for gaussian noise with mean 1, and add *effect2* on input image for gaussian noise with mean 2. What output image can I expect if I give input image with gaussian noise with mean 1.5? will it be combination of effect1 and effect2 or can be anyone of them or some random output?