Machine Learning, Data Science, Deep Learning, Artificial Intelligence, Towards Data Science.
np.ones((halfbatch_size, 1))) DlossFake = D.train_on_batch(fakeImg, np.zeros((halfbatch_size, 1))) DLoss=np.add(DlossTrue,DlossFake)*0.5 # DLoss=np.add(DlossTrue,DlossEnc) # DLoss=np.add(DLoss,DlossFake)*0.33 D.Trainable = False noise = np.random.normal(0, 1, (batch_size, latent_dim)) index =