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