Machine Learning, Data Science, Deep Learning, Artificial Intelligence, Towards Data Science.
d.train_on_batch(generated_images, y_train_fake) # Train generator d.trainable = False g_loss=gan.train_on_batch(noise, y_train_real) # evaluate test_path = np.array(val_path)[np.random.choice(len(val_path), eval_size, replace=False)] x_eval_real = np.array([preprocess(load_image(filename)) for