<p>See <a href="http://bamos.github.io/2016/08/09/deep-completion/" rel="nofollow noreferrer">Image Completion with Deep Learning in TensorFlow</a> for a long answer.</p>

<p>In short: Suppose you make a CNN which has n filters of the size of its input and valid-padding. Then the output will be of shape n x 1 x 1. Then you can apply softmax to that shape and you have the probabilities in the channels.</p>

<p>You might also want to read <a href="https://arxiv.org/pdf/1707.09725.pdf" rel="nofollow noreferrer">2.2.1. Convolutional Layers</a> of my Masters thesis.</p>
How discriminator works on DCGAN?
<p>I studying about DCGAN, and I wonder something about it.</p>

<p>In Ian Goodfellow's natural GAN, discriminator Model outputs one scalar value what means the probability.
But DCGAN's discriminator has designed with CNN architecture. I know that CNN's output is vector of class probabilities.</p>

<p>So how discriminator works on DCGAN? And what output of DCGAN's discriminator is?</p>