"""Learner experiment. Fill planned_configs and RATIONALE before running.
python -m exercises.capstone         -> train/validation selection only
python -m exercises.capstone --final -> require matching saved selection, test once
"""
from dlcourse.core import Config
RATIONALE = ''  # Explain candidate budget, metric and IID split assumption.

def planned_configs():
    raise NotImplementedError('Return a modest list of Config objects, including a linear baseline.')

if __name__=='__main__':
    from dlcourse.capstone_runner import main
    main(planned_configs, RATIONALE)