Coverage for mlos_core/mlos_core/optimizers/random_optimizer.py: 94%

1# 

2# Copyright (c) Microsoft Corporation. 

3# Licensed under the MIT License. 

4# 

5"""RandomOptimizer class.""" 

6 

7from typing import Optional 

8from warnings import warn 

9 

10import pandas as pd 

11 

12from mlos_core.data_classes import Observations, Suggestion 

13from mlos_core.optimizers.optimizer import BaseOptimizer 

14 

15 

16class RandomOptimizer(BaseOptimizer): 

17 """ 

18 Optimizer class that produces random suggestions. 

19 

20 Useful for baseline comparison against Bayesian optimizers. 

21 """ 

22 

23 def _register( 

24 self, 

25 observations: Observations, 

26 ) -> None: 

27 """ 

28 Registers the given config/score pairs. 

29 

30 Notes 

31 ----- 

32 Doesn't do anything on the RandomOptimizer except storing configs for logging. 

33 

34 Parameters 

35 ---------- 

36 observations : Observations 

37 The observations to register. 

38 """ 

39 if observations.contexts is not None: 

40 warn( 

41 f"Not Implemented: Ignoring context {list(observations.contexts.index)}", 

42 UserWarning, 

43 ) 

44 if observations.metadata is not None: 

45 warn( 

46 f"Not Implemented: Ignoring context {list(observations.metadata.index)}", 

47 UserWarning, 

48 ) 

49 # should we pop them from self.pending_observations? 

50 

51 def _suggest( 

52 self, 

53 *, 

54 context: Optional[pd.Series] = None, 

55 ) -> Suggestion: 

56 """ 

57 Suggests a new configuration. 

58 

59 Sampled at random using ConfigSpace. 

60 

61 Parameters 

62 ---------- 

63 context : None 

64 Not Yet Implemented. 

65 

66 Returns 

67 ------- 

68 suggestion: Suggestion 

69 The suggestion to evaluate. 

70 """ 

71 if context is not None: 

72 # not sure how that works here? 

73 warn(f"Not Implemented: Ignoring context {list(context.index)}", UserWarning) 

74 return Suggestion( 

75 config=pd.Series(self.optimizer_parameter_space.sample_configuration(), dtype=object), 

76 context=context, 

77 metadata=None, 

78 ) 

79 

80 def register_pending(self, pending: Suggestion) -> None: 

81 raise NotImplementedError() 

82 # self._pending_observations.append((configs, context))