after makeqadd another functioninitializewhich initializes the model using normally-distributed values/ataribot/bot_ _ls py def makeq(modelnp array-callable[[np array]np array]"""returns -functionwhich takes state -distribution over actions""return lambda xx dot(modeldef initialize(shapetuple)"""initialize model"" np random normal( shapeq makeq(wreturn wq def print_report(rewardslistepisodeint)after the initialize blockadd train method that computes the ridge regression closed-form solutionthen weights the old model with the new one it returns both the model and the abstracted -function/ataribot/bot_ _ls py