def get_lr(epoch_size, step_size, lr_init):
    """
     generate learning rate for each step, which decays in every 10 epoch

     Args:
        epoch_size(int): total epoch number
        step_size(int): total step number in each step
        lr_init(int): initial learning rate

     Returns:
        List, learning rate array
     """
    lr = lr_init
    lrs = []
    for i in range(1, epoch_size + 1):
        if i % 10 == 0:
            lr *= 0.1
        lrs.extend([lr for _ in range(step_size)])
    return lrs