@AndreaSottana thank you for giving the insight. Particularly what I was looking for @ptrblck  mentioned in a link:
Some schedulers, e.g. ReduceLROnPlateau  expect to track a metric in order to lower the learning rate.
Usually you would split your dataset into training, validation (, and test) and use the validation loss to trigger the learning rate reduction.
The idea behind it is that once your validation loss doesn’t decrease anymore (or not significantly), lowering the learning rate might help decreasing it further.
However, you could use whatever metric you like to use. 
PS: other learning rate schedulers do not expect any input and use some other schedule, e.g. epochs as milestones.