Coverage for mlos_core/mlos_core/optimizers/bayesian_optimizers/bayesian_optimizer.py: 100%

1# 

2# Copyright (c) Microsoft Corporation. 

3# Licensed under the MIT License. 

4# 

5"""Contains the wrapper classes for base Bayesian optimizers.""" 

6 

7from abc import ABCMeta, abstractmethod 

8 

9import numpy.typing as npt 

10 

11from mlos_core.data_classes import Suggestion 

12from mlos_core.optimizers.optimizer import BaseOptimizer 

13 

14 

15class BaseBayesianOptimizer(BaseOptimizer, metaclass=ABCMeta): 

16 """Abstract base class defining the interface for Bayesian optimization.""" 

17 

18 @abstractmethod 

19 def surrogate_predict(self, suggestion: Suggestion) -> npt.NDArray: 

20 """ 

21 Obtain a prediction from this Bayesian optimizer's surrogate model for the given 

22 configuration(s). 

23 

24 Parameters 

25 ---------- 

26 suggestion: Suggestion 

27 The suggestion containing the configuration(s) to predict. 

28 """ 

29 pass # pylint: disable=unnecessary-pass # pragma: no cover 

30 

31 @abstractmethod 

32 def acquisition_function(self, suggestion: Suggestion) -> npt.NDArray: 

33 """ 

34 Invokes the acquisition function from this Bayesian optimizer for the given 

35 configuration. 

36 

37 Parameters 

38 ---------- 

39 suggestion: Suggestion 

40 The suggestion containing the configuration(s) to evaluate. 

41 """ 

42 pass # pylint: disable=unnecessary-pass # pragma: no cover