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discriminator.train_on_batch(real_data, valid) d_loss_fake = discriminator.train_on_batch(synthetic_data, fake) d_loss = 0.5 * np.add(d_loss_real, d_loss_fake) # --------------------- # Train Generator # --------------------- # Generate a batch of noise vectors noise = np.random.normal(0, 1,