Machine Learning, Data Science, Deep Learning, Artificial Intelligence, Towards Data Science.
gLoss=gan.train_on_batch(noise,np.ones([batchSize,1])) if e % 20 == 0: print("epoch： %d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (e, dLoss[0], 100 * dLoss[1], gLoss)) dLossReal.append([e,dLoss[0]]) dLossFake.append([e,dLoss[1]]) gLossLogs.append([e,gLoss]) if e % plotInternal == 0 and e!=0: