Source code for ax.metrics.jenatton
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Any, Optional
import pandas as pd
from ax.core.base_trial import BaseTrial
from ax.core.data import Data
from ax.core.metric import Metric, MetricFetchE, MetricFetchResult
from ax.utils.common.result import Err, Ok
from ax.utils.common.typeutils import not_none
[docs]class JenattonMetric(Metric):
def __init__(
self,
name: str = "jenatton",
infer_noise: bool = True,
) -> None:
super().__init__(name=name)
self.infer_noise = infer_noise
@staticmethod
def _f(
x1: Optional[int] = None,
x2: Optional[int] = None,
x3: Optional[int] = None,
x4: Optional[float] = None,
x5: Optional[float] = None,
x6: Optional[float] = None,
x7: Optional[float] = None,
r8: Optional[float] = None,
r9: Optional[float] = None,
) -> float:
if x1 == 0:
if x2 == 0:
return not_none(x4) ** 2 + 0.1 + not_none(r8)
else:
return not_none(x5) ** 2 + 0.2 + not_none(r8)
else:
if x3 == 0:
return not_none(x6) ** 2 + 0.3 + not_none(r9)
else:
return not_none(x7) ** 2 + 0.4 + not_none(r9)
[docs] def fetch_trial_data(self, trial: BaseTrial, **kwargs: Any) -> MetricFetchResult:
try:
# pyre-ignore [6]
mean = [self._f(**arm.parameters) for _, arm in trial.arms_by_name.items()]
df = pd.DataFrame(
{
"arm_name": [name for name, _ in trial.arms_by_name.items()],
"metric_name": self.name,
"mean": mean,
"sem": None if self.infer_noise else 0,
"trial_index": trial.index,
}
)
return Ok(value=Data(df=df))
except Exception as e:
return Err(
MetricFetchE(message=f"Failed to fetch {self.name}", exception=e)
)