From the course: AI Workshop: Hands-on with GANs with Deep Convolutional Networks
Unlock this course with a free trial
Join today to access over 23,300 courses taught by industry experts.
Viewing GAN training results
From the course: AI Workshop: Hands-on with GANs with Deep Convolutional Networks
Viewing GAN training results
We set up the code for the training loop. All we have to do is run this code and let's see how our GAN performs. Now here we are in the very first epoch, epoch 0. This is where the results are completely random, both the generator and discriminator weights are completely untrained. Now let's iterate through a few epochs and then take a look at how these perform. The next output will be at around 200 batches of training. We are still on epoch 0, though you can't really see the epoch there. If you look at the generated images now, you can no longer call them complete noise. The generator has improved tremendously with just 200 iterations of training, but it's still pretty bad. The discriminator's total loss is 0.412. It's still low. The generator loss is 7.63, quite high. The real score of the discriminator is close to one, the fake score is close to zero, indicating the discriminator is doing a good job. The fake score after discriminator update is also close to zero, so the…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Contents
-
-
-
-
-
Generator and discriminator1m 43s
-
(Locked)
Deep convolutional GANs (DCGANs)6m 16s
-
(Locked)
Setting up data for GAN training4m 8s
-
(Locked)
Setting up the generator and discriminator6m 18s
-
(Locked)
Output from an untrained generator and discriminator2m 17s
-
(Locked)
Setting up the GAN training loop7m 9s
-
(Locked)
Viewing GAN training results4m 34s
-
-