egers that reflects milestone points.
        last_epoch (int): The index of last epoch. Default: -1.
        verbose (bool): Does nothing.

    Example:
        >>> # xdoctest: +SKIP
        >>> # Assuming optimizer uses lr = 1. for all groups
        >>> # lr = 0.1     if epoch == 0
        >>> # lr = 0.1     if epoch == 1
        >>> # lr = 0.9     if epoch == 2
        >>> # lr = 0.81    if epoch == 3
        >>> # lr = 0.729   if epoch == 4
        >>> scheduler1 = ConstantLR(self.opt, factor=0.1, total_iters=2)
        >>> scheduler2 = ExponentialLR(self.opt, gamma=0.9)
        >>> scheduler = SequentialLR(self.opt, schedulers=[scheduler1, scheduler2], milestones=[2])
        >>> for epoch in range(100):
        >>>     train(...)
        >>>     validate(...)
        >>>     scheduler.step()
    r