embossing over right now how to do this efficiently because computing a full normalization of the predictions over like a full million size vocabulary is very expensive so you often you can use a tree structure or a sub sampling algorithm where you might normalize over only a randomly selected subset and you can weight that subset and things like this all production negative sampling is a prediction some kind of inner product between WT & WT - - or yeah so that would be how you'd get the logit for the log problems it's a