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DCGAN is initialized with random weights, so a random code plugged in to the network would create a very random image. Nonetheless, while you might imagine, the network has many parameters that we can tweak, as well as the purpose is to find a setting of those parameters which makes samples created from random codes look like the instruction facts.

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