reaches to 1.
            Default: 5.
        last_epoch (int): The index of the last epoch. Default: -1.
        verbose (bool): If ``True``, prints a message to stdout for
            each update. Default: ``False``.

    Example:
        >>> # xdoctest: +SKIP
        >>> # Assuming optimizer uses lr = 0.05 for all groups
        >>> # lr = 0.025    if epoch == 0
        >>> # lr = 0.03125  if epoch == 1
        >>> # lr = 0.0375   if epoch == 2
        >>> # lr = 0.04375  if epoch == 3
        >>> # lr = 0.05    if epoch >= 4
        >>> scheduler = LinearLR(self.opt, start_factor=0.5, total_iters=4)
        >>> for epoch in range(100):
        >>>     train(...)
        >>>     validate(...)
        >>>     scheduler.step()
    r¿