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Fix storage API having SMAC as a required dependency #899

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Dec 12, 2024
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Fix storage API having SMAC as a required dependency #899

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7 changes: 5 additions & 2 deletions mlos_core/mlos_core/optimizers/bayesian_optimizers/smac_optimizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,6 @@
import ConfigSpace
import numpy.typing as npt
import pandas as pd
from smac.utils.configspace import convert_configurations_to_array

from mlos_core.data_classes import Observation, Observations, Suggestion
from mlos_core.optimizers.bayesian_optimizers.bayesian_optimizer import (
Expand Down Expand Up @@ -121,6 +120,10 @@ def __init__(
from smac.main.config_selector import ConfigSelector
from smac.random_design.probability_design import ProbabilityRandomDesign
from smac.runhistory import TrialInfo
from smac.utils.configspace import convert_configurations_to_array

# Save util function here as a property for later usage, also to satisfy linter
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self._convert_configurations_to_array = convert_configurations_to_array

# Store for TrialInfo instances returned by .ask()
self.trial_info_map: Dict[ConfigSpace.Configuration, TrialInfo] = {}
Expand Down Expand Up @@ -411,7 +414,7 @@ def surrogate_predict(self, suggestion: Suggestion) -> npt.NDArray:
if self.base_optimizer._config_selector._model is None:
raise RuntimeError("Surrogate model is not yet trained")

config_array = convert_configurations_to_array(
config_array = self._convert_configurations_to_array(
[
ConfigSpace.Configuration(
self.optimizer_parameter_space, values=suggestion.config.to_dict()
Expand Down
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