def once(size):
    X = self.models[0].sample(size, random_state)
    nf = X.shape[(- 1)]
    lnprob = sum([model.score(X) for model in self.models[1:]])
    prob = numpy.exp(lnprob)
    prob /= prob.max()
    keep = (random_state.rand(len(X)) < prob)
    return X[keep].reshape((- 1), nf)
def once(size):
    X = self.models[0].sample(size, random_state)
    nf = X.shape[(- 1)]
    lnprob = sum([model.score(X) for model in self.models[1:]])
    prob = numpy.exp(lnprob)
    prob /= prob.max()
    keep = (random_state.rand(len(X)) < prob)
    return X[keep].reshape((- 1), nf)