train.py
def adjust_learning_rate(optimizer, epoch):
    """Sets the learning rate to the initial LR decayed by 10 every 30 epochs"""
    lr = args.lr * (0.7 ** (epoch // 10))
    #for param_group in optimizer.param_groups:
        #param_group['lr'] = lr
    optimizer.param_groups[0]['lr'] = args.multi_lr*lr
    optimizer.param_groups[1]['lr'] = lr

    return lr
Sets the learning rate to the initial LR decayed by 10 every 30 epochs
Sets the learning rate to the initial LR decayed by 10 every 30 epochs
Sets the learning rate to the initial LR decayed by 10 every 30 epochs
def adjust_learning_rate(optimizer, epoch):
    lr = args.lr * (0.7 ** (epoch // 10))
    optimizer.param_groups[0]['lr'] = args.multi_lr*lr
    optimizer.param_groups[1]['lr'] = lr
    return lr
def adjust_learning_rate ( optimizer , epoch ) : lr = args . lr * ( 0.7 ** ( epoch // 10 ) ) optimizer . param_groups [ 0 ] [ 'lr' ] = args . multi_lr * lr optimizer . param_groups [ 1 ] [ 'lr' ] = lr return lr
Sets the learning rate to the initial LR decayed by 10 every 30 epochs
Sets the learning rate to the initial LR decayed by 10 every 30 epochs
"""Sets the learning rate to the initial LR decayed by 10 every 30 epochs""" #for param_group in optimizer.param_groups: #param_group['lr'] = lr
optimizer
epoch