I was reading Image to Image Translation with Conditional Adversarial Networks. On its third page, it states that
Without z, the net could still learn a mapping from x to y, but would produce deterministic outputs, and therefore fail to match any distribution other than a delta function.
Here z is the random noise given to the generator as input. x refers to the labels fed as input for Conditional Adversarial Networks.
Can somebody please explain the above paragraph.