"""The score every candidate is measured by.

Change it deliberately and rarely: results from before and after a change
cannot be compared.
"""

from data import Sample
from model import Model


def score(model: Model, rows: list[Sample]) -> float:
    """Mean squared error on rows the model never trained on; lower is better."""
    return model.loss(rows)
