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DCGAN is initialized with random weights, so a random code plugged in the network would deliver a very random graphic. Even so, while you might imagine, the network has numerous parameters that we can easily tweak, and the objective is to locate a environment of those parameters that makes samples produced from random codes seem like the instructio