DCGAN is initialized with random weights, so a random code plugged in to the network would deliver a totally random graphic. Even so, as you might imagine, the network has millions of parameters that we will tweak, and the purpose is to locate a environment of such parameters that makes samples produced from random codes appear like the coaching fa