Sorry, I am probably getting concepts confused. I know that in the realm of autoencoders, there lies a bottleneck between the decoder and encoder; the encoder, when is fed with an input image, brings the data into a compressed representation of the image, i.e. the latent space representation.
Isn’t there such a bottleneck in GAN’s as well?  This is what I want to extract.