def next(self, reward, ask_id, lbl):
        # first run don't have reward, TODO exception on reward == -1 only once
        if reward == -1:
            return next(self.exp4p_gen)
        else:
        # TODO exception on reward in [0, 1]
            return self.exp4p_gen.send((reward, ask_id, lbl))
Taking the label and the reward value of last question and returns
dataset/ETHPy150Open ntucllab/libact/libact/query_strategies/active_learning_by_learning.py/Exp4P.next