def METHOD_NAME(self):
    """Test that the learning rate scheduler is correctly checkpointed."""
    # First run the entire test.
    trainer = self.__original_setup(test_checkpoint_name, 40,
                             learning_rate_scheduler="ReduceLROnPlateau",
                             learning_rate=0.1)
    trainer.train_network()
    original_learning_rate = trainer.optimizer.param_groups[0]['lr']
    # Now do the same, but cut at epoch 22 and see if it recovers the
    # correct result.
    trainer = self.__original_setup(test_checkpoint_name, 22,
                             learning_rate_scheduler="ReduceLROnPlateau",
                             learning_rate=0.1)
    trainer.train_network()
    trainer = self.__resume_checkpoint(test_checkpoint_name, 40)
    trainer.train_network()
    new_learning_rate = trainer.optimizer.param_groups[0]['lr']
    assert np.isclose(original_learning_rate, new_learning_rate,
                      atol=accuracy)