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DCGAN is initialized with random weights, so a random code plugged in the network would make a completely random graphic. Nevertheless, as you might imagine, the network has millions of parameters that we will tweak, and the purpose is to locate a location of these parameters that makes samples created from random codes look like the teaching detai