Scaling of learning rate

[nexus1203]

In the train.py there is a code of scaling the learning rate:

utils.opt.adjust_learning_rate(optimizer, epoch)

however in the comments you wrote scale it by 1/10 every 30 epoches but your scale is set to 2 by default. is this the way used in the research paper? the scale is 2 epochs or 30 epochs?

def adjust_learning_rate(optimizer, epoch, scale=2):
    # Sets the learning rate to the initial LR decayed by 10 every 30 epochs
    for param_group in optimizer.param_groups:
        lr =  param_group['lr']
        lr = lr * (0.1 ** (epoch // scale))
        param_group['lr'] = lr