Coverage for mlos_bench/mlos_bench/tests/tunable_groups_fixtures.py: 100%

1# 

2# Copyright (c) Microsoft Corporation. 

3# Licensed under the MIT License. 

4# 

5""" 

6Common fixtures for mock TunableGroups. 

7""" 

8 

9from typing import Any, Dict 

10 

11import pytest 

12 

13import json5 as json 

14 

15from mlos_bench.config.schemas import ConfigSchema 

16from mlos_bench.tunables.covariant_group import CovariantTunableGroup 

17from mlos_bench.tunables.tunable_groups import TunableGroups 

18 

19# pylint: disable=redefined-outer-name 

20 

21TUNABLE_GROUPS_JSON = """ 

22{ 

23 "provision": { 

24 "cost": 1000, 

25 "params": { 

26 "vmSize": { 

27 "description": "Azure VM size", 

28 "type": "categorical", 

29 "default": "Standard_B4ms", 

30 "values": ["Standard_B2s", "Standard_B2ms", "Standard_B4ms"] 

31 } 

32 } 

33 }, 

34 "boot": { 

35 "cost": 300, 

36 "params": { 

37 "idle": { 

38 "description": "Idling method", 

39 "type": "categorical", 

40 "default": "halt", 

41 "values": ["halt", "mwait", "noidle"], 

42 "values_weights": [33, 33, 33] // FLAML requires uniform weights 

43 } 

44 } 

45 }, 

46 "kernel": { 

47 "cost": 1, 

48 "params": { 

49 "kernel_sched_migration_cost_ns": { 

50 "description": "Cost of migrating the thread to another core", 

51 "type": "int", 

52 "default": -1, 

53 "range": [0, 500000], 

54 "special": [-1, 0], 

55 // FLAML requires uniform weights, separately for 

56 // specials and switching between specials and range. 

57 "special_weights": [0.25, 0.25], 

58 "range_weight": 0.5, 

59 "log": false 

60 }, 

61 "kernel_sched_latency_ns": { 

62 "description": "Initial value for the scheduler period", 

63 "type": "int", 

64 "default": 2000000, 

65 "range": [0, 1000000000], 

66 "log": false 

67 } 

68 } 

69 } 

70} 

71""" 

72 

73 

74@pytest.fixture 

75def tunable_groups_config() -> Dict[str, Any]: 

76 """ 

77 Fixture to get the JSON string for the tunable groups. 

78 """ 

79 conf = json.loads(TUNABLE_GROUPS_JSON) 

80 assert isinstance(conf, dict) 

81 ConfigSchema.TUNABLE_PARAMS.validate(conf) 

82 return conf 

83 

84 

85@pytest.fixture 

86def tunable_groups(tunable_groups_config: dict) -> TunableGroups: 

87 """ 

88 A test fixture that produces a mock TunableGroups. 

89 

90 Returns 

91 ------- 

92 tunable_groups : TunableGroups 

93 A new TunableGroups object for testing. 

94 """ 

95 tunables = TunableGroups(tunable_groups_config) 

96 tunables.reset() 

97 return tunables 

98 

99 

100@pytest.fixture 

101def covariant_group(tunable_groups: TunableGroups) -> CovariantTunableGroup: 

102 """ 

103 Text fixture to get a CovariantTunableGroup from tunable_groups. 

104 

105 Returns 

106 ------- 

107 CovariantTunableGroup 

108 """ 

109 (_, covariant_group) = next(iter(tunable_groups)) 

110 return covariant_group 

111 

112 

113@pytest.fixture 

114def mixed_numerics_tunable_groups() -> TunableGroups: 

115 """ 

116 A test fixture with mixed numeric tunable groups to test type conversions. 

117 

118 Returns 

119 ------- 

120 tunable_groups : TunableGroups 

121 A new TunableGroups object for testing. 

122 """ 

123 tunables = TunableGroups({ 

124 "mix-numerics": { 

125 "cost": 1, 

126 "params": { 

127 "int": { 

128 "description": "An integer", 

129 "type": "int", 

130 "default": 0, 

131 "range": [0, 100], 

132 }, 

133 "float": { 

134 "description": "A float", 

135 "type": "float", 

136 "default": 0, 

137 "range": [0, 1], 

138 }, 

139 } 

140 }, 

141 }) 

142 tunables.reset() 

143 return tunables