def METHOD_NAME(self, runner):
    if self.by_epoch:
        return
    # save checkpoint for following cases:
    # 1. every ``self.interval`` iterations
    # 2. reach the last iteration of training
    if self.every_n_iters(
            runner, self.interval) or (self.save_last
                                       and self.is_last_iter(runner)):
        runner.logger.info(
            f'Saving checkpoint at {runner.iter + 1} iterations')
        if self.sync_buffer:
            allreduce_params(runner.model.buffers())
        self._save_checkpoint(runner)