Question: Suppose p theta ( x ) and pdata ( x ) both place probability mass in only a very small part of the domain;

Suppose p\theta (x) and pdata(x) both place probability mass in only a very small part of the domain; that is, consider the limit ->0. What happens to KL(p\theta (x)|| pdata(x)) and its derivative with respect to \theta , assuming that \theta =\theta 0? Why is this problematic for a GAN trained with the loss function LG defined in problem 3c?

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