code: def update_learning_rate(lr, trainer, epoch, ratio, steps):
      
      new_lr = lr * (ratio ** int(np.sum(np.array(steps) < epoch)))
      trainer.set_learning_rate(new_lr)
      return trainer
docs: Set the learning rate to the initial value decayed by ratio every N epochs.