def predict_ratings(self,users=None,item_features=None):
        if isinstance(users,int):
            users = [users]

        if users is None:
            U = self.U
        else:
            U = np.asfortranarray(self.U[users,:])
        return U.dot(self.V.T)
Predict ratings/scores for all items for supplied users.
dataset/ETHPy150Open Mendeley/mrec/mrec/mf/recommender.py/MatrixFactorizationRecommender.predict_ratings