Learning rate scheduler

lr_schedule.py

from keras.callbacks import LearningRateScheduler

def scheduler(schedule):
    def lr_schedule(epoch):
        epoch += 1
        for ep,lr in sorted(schedule, reverse=True):
            if epoch >= ep:
                return lr
        raise ValueError()
    return lr_schedule

def test_scheduler():
  truth = [1e-4, 1e-4, 3e-5, 3e-5, 3e-5]
  for epoch in range(0,5):
      lr = scheduler([(1, 1e-4), (3, 3e-5)])(epoch)
      assert lr == truth[epoch]

# Used in Keras model.fit()
callbacks = [LearningRateScheduler(scheduler([(1, 1e-4), (10, 3e-5), (15, 1e-5)]))]