def __init__(self, max_size: int, adaptive_size: bool = True, num_experiences=None):
        """
        :param max_size: max number of total input samples in the replay
            memory.
        :param adaptive_size: True if mem_size is divided equally over all
                              observed experiences (keys in replay_mem).
        :param num_experiences: If adaptive size is False, the fixed number
                                of experiences to divide capacity over.
        """
        super().__init__(max_size, adaptive_size, num_experiences)
        self._num_exps = 0

        :param max_size: max number of total input samples in the replay
            memory.
        :param adaptive_size: True if mem_size is divided equally over all
                              observed experiences (keys in replay_mem).
        :param num_experiences: If adaptive size is False, the fixed number
                                of experiences to divide capacity over.
        
avalanche/training/storage_policy.py