Read a chapter, then run the code. For example, when learning about (where the generator produces one single output repeatedly), the GitHub repo contains specific notebook cells that visualize this failure. Seeing the loss graphs misbehave is more valuable than reading about it.
stante/gans-in-action-pytorch : Idiomatic PyTorch implementations tested with Python 3.6+ . gans in action pdf github
GANs in Action is a 5-star book for practitioners. However, relying on a GitHub-sourced PDF is risky: you may get a low-quality, incomplete, or infringing copy. Use GitHub for the , and obtain the PDF through legitimate channels (Manning, Amazon, or your institution’s library). Your learning experience will be much better for it. Read a chapter, then run the code
The most critical resource for the book is its Official GitHub Repository . This companion repo contains: Use GitHub for the , and obtain the
# Define the GAN model def gan_model(generator, discriminator): discriminator.trainable = False model = keras.Sequential() model.add(generator) model.add(discriminator) return model