Machine Learning, Data Science, Deep Learning, Artificial Intelligence, Towards Data Science.
dLossR=discriminator.train_on_batch(images,np.ones([halfSize,1])) dLossF=discriminator.train_on_batch(genImages,np.zeros([halfSize,1])) dLoss=np.add(dLossF,dLossR)*0.5 discriminator.trainable=False noise=np.random.normal(0,1,(batchSize,Noise_dim))