title: How to interpret the discriminator's loss and the generator's loss in Generative Adversarial Nets?
body: <p>I am reading people's implementation of DCGAN, especially <a href="https://github.com/carpedm20/DCGAN-tensorflow" rel="noreferrer">this one</a> in tensorflow.</p>
  
  <p>In that implementation, the author draws the losses of the discriminator and of the generator, which is shown below (images come from <a href="https://github.com/carpedm20/DCGAN-tensorflow" rel="noreferrer">https://github.com/carpedm20/DCGAN-tensorflow</a>):</p>
  
  <p><a href="https://i.stack.imgur.com/PZm29.png" rel="noreferrer"><img src="https://i.stack.imgur.com/PZm29.png" alt="enter image description here"></a></p>
  
  <p><a href="https://i.stack.imgur.com/WRpsu.png" rel="noreferrer"><img src="https://i.stack.imgur.com/WRpsu.png" alt="enter image description here"></a></p>
  
  <p>Both the losses of the discriminator and of the generator don't seem to follow any pattern. Unlike general neural networks, whose loss decreases along with the increase of training iteration. How to interpret the loss when training GANs?</p>