of the mini batch whichever one is the most realistic because of that we don't usually use the maximum likelihood cost with generative adversarial networks we use one of the other costs that has nicer saturation properties and nicer variance properties but it is a perfectly legitimate cost and when we go ahead and we use that cost to Train there's actually there's a few other ways of approximating the KL divergence but none of the different ways of approximating the KL divergence give us blurry samples like we get with a V ie