Coverage for mlos_bench/mlos_bench/storage/base_tunable_config_data.py: 95%

1# 

2# Copyright (c) Microsoft Corporation. 

3# Licensed under the MIT License. 

4# 

5"""Base interface for accessing the stored benchmark (tunable) config data.""" 

6from abc import ABCMeta, abstractmethod 

7from typing import Any, Dict, Optional 

8 

9import pandas 

10 

11from mlos_bench.storage.util import kv_df_to_dict 

12from mlos_bench.tunables.tunable import TunableValue 

13 

14 

15class TunableConfigData(metaclass=ABCMeta): 

16 """ 

17 Base interface for accessing the stored experiment benchmark (tunable) config data. 

18 

19 A configuration in this context is the set of tunable parameter values. 

20 """ 

21 

22 def __init__(self, *, tunable_config_id: int): 

23 self._tunable_config_id = tunable_config_id 

24 

25 def __repr__(self) -> str: 

26 return f"TunableConfig :: {self._tunable_config_id}: {self.config_dict}" 

27 

28 def __eq__(self, other: Any) -> bool: 

29 if not isinstance(other, self.__class__): 

30 return False 

31 return self._tunable_config_id == other._tunable_config_id 

32 

33 @property 

34 def tunable_config_id(self) -> int: 

35 """Unique ID of the (tunable) configuration.""" 

36 return self._tunable_config_id 

37 

38 @property 

39 @abstractmethod 

40 def config_df(self) -> pandas.DataFrame: 

41 """ 

42 Retrieve the trials' tunable configuration from the storage. 

43 

44 Note: this corresponds to the Trial object's "tunables" property. 

45 

46 Returns 

47 ------- 

48 config : pandas.DataFrame 

49 A dataframe with the tunable configuration of the trial. 

50 It has two `str` columns, "parameter" and "value". 

51 """ 

52 

53 @property 

54 def config_dict(self) -> Dict[str, Optional[TunableValue]]: 

55 """ 

56 Retrieve the trials' tunable configuration from the storage as a dict. 

57 

58 Note: this corresponds to the Trial object's "tunables" property. 

59 

60 Returns 

61 ------- 

62 config : dict 

63 """ 

64 return kv_df_to_dict(self.config_df) 

65 

66 # TODO: add methods for retrieving 

67 # - trials by tunable config, even across experiments (e.g., for merging) 

68 # - trial config groups (i.e., all experiments' trials with the same tunable config)