: The GANs-in-Action GitHub contains Jupyter notebooks for every major GAN variant discussed in the book, including vanilla GANs, DCGANs, and CycleGAN using Keras/TensorFlow.
You can find the code and resources for GANs in Action: Deep Learning with Generative Adversarial Networks gans in action pdf github
# Define the GAN model def gan_model(generator, discriminator): discriminator.trainable = False model = keras.Sequential() model.add(generator) model.add(discriminator) return model : The GANs-in-Action GitHub contains Jupyter notebooks for