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DCGAN is initialized with random weights, so a random code plugged into the network would crank out a totally random graphic. Nonetheless, when you may think, the network has a lot of parameters that we are able to tweak, and the purpose is to locate a setting of those parameters which makes samples produced from random codes appear to be the train