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DCGAN is initialized with random weights, so a random code plugged into the network would generate a very random graphic. Even so, as you may think, the network has millions of parameters that we can easily tweak, and the aim is to locate a placing of those parameters that makes samples created from random codes seem like the instruction facts.Firm