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DCGAN is initialized with random weights, so a random code plugged to the network would crank out a very random graphic. Nevertheless, as you might imagine, the network has a lot of parameters that we can easily tweak, and the aim is to find a location of such parameters that makes samples generated from random codes look like the instruction knowl