def __init__(
self,
name: str,
f: Callable[[TParameterization], float],
noise_sd: Optional[float] = 0.0,
lower_is_better: Optional[bool] = None,
) -> None:
"""
Metric is computed by evaluating a deterministic function, implemented in f.
Args:
name: Name of the metric.
f: A callable accepting a dictionary from parameter names to
values and returning a float metric value.
noise_sd: Scale of normal noise added to the function result. If
None, interpret the function as nosiy with unknown noise level.
lower_is_better: Flag for metrics which should be minimized.
Note: Since this metric setup uses a generic callable it cannot be serialized
and will not play well with storage.
"""
self._f = f
self.noise_sd = noise_sd
Metric.__init__(self, name=name, lower_is_better=lower_is_better)
