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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_similar_users(self, users=None, k=10):
 """Get the k most similar users for each entry in `users`. Each type of recommender has its own model for the similarity between users. For example, the factorization_recommender will return the nearest users based on the cosine similarity between latent user factors. (This method is not currently available for item_similarity models.) Parameters users : SArray or list; optional An :class:`~turicreate.SArray` or list of user ids for which to get similar users. If 'None', then return the `k` most similar users for all users in the training set. k : int, optional The number of neighbors to return for each user. Returns ------- out : SFrame A SFrame with the top ranked similar users for each user. The columns `user`, 'similar', 'score' and 'rank', where `user` matches the user column name specified at training time. The 'rank' is between 1 and `k` and 'score' gives the similarity score of that user. The value of the score depends on the method used for computing user similarities. Examples -------- 'item_id': ["a", "b", "c", "a", "b", "b", "c", "d"]}) """


        if users is None:
            get_all_users = True
            users = _SArray()
        else:
            get_all_users = False

        if isinstance(users, list):
            users = _SArray(users)

        def check_type(arg, arg_name, required_type, allowed_types):
            if not isinstance(arg, required_type):
                raise TypeError("Parameter " + arg_name + " must be of type(s) "
                                + (", ".join(allowed_types) )
                                + "; Type '" + str(type(arg)) + "' not recognized.")

        check_type(users, "users", _SArray, ["SArray", "list"])
        check_type(k, "k", int, ["int"])

        opt = {'model': self.__proxy__,
               'users': users,
               'get_all_users' : get_all_users,
               'k': k}

        response = self.__proxy__.get_similar_users(users, k, get_all_users)
        return response