Coverage for hopwise/utils/enum_type.py: 97%

1# @Time : 2020/8/9 

2# @Author : Yupeng Hou 

3# @Email : houyupeng@ruc.edu.cn 

4 

5# UPDATE 

6# @Time : 2025 

7# @Author : Giacomo Medda 

8# @Email : giacomo.medda@unica.it 

9 

10"""hopwise.utils.enum_type 

11####################### 

12""" 

13 

14from enum import Enum 

15 

16 

17class ModelType(Enum): 

18 """Type of models. 

19 

20 - ``GENERAL``: General Recommendation 

21 - ``SEQUENTIAL``: Sequential Recommendation 

22 - ``CONTEXT``: Context-aware Recommendation 

23 - ``KNOWLEDGE``: Knowledge-based Recommendation 

24 - ``PATH_LANGUAGE_MODELING``: Path Language Modeling Recommendation 

25 """ 

26 

27 GENERAL = 1 

28 SEQUENTIAL = 2 

29 CONTEXT = 3 

30 KNOWLEDGE = 4 

31 TRADITIONAL = 5 

32 DECISIONTREE = 6 

33 PATH_LANGUAGE_MODELING = 7 

34 

35 

36class KGDataLoaderState(Enum): 

37 """States for Knowledge-based DataLoader. 

38 

39 - ``RSKG``: Return both knowledge graph information and user-item interaction information. 

40 - ``RS``: Only return the user-item interaction. 

41 - ``KG``: Only return the triplets with negative examples in a knowledge graph. 

42 """ 

43 

44 RSKG = 1 

45 RS = 2 

46 KG = 3 

47 

48 

49class KnowledgeEvaluationType(Enum): 

50 """Type of evaluation task: Recommendation or Link Prediction 

51 

52 - ``REC``: Evaluate on Recommendation 

53 - ``LP``: Evaluate on Link Prediction 

54 """ 

55 

56 REC = 1 

57 LP = 2 

58 

59 def __str__(self): 

60 _descriptions = {KnowledgeEvaluationType.REC: "recommendation", KnowledgeEvaluationType.LP: "link prediction"} 

61 

62 return _descriptions[self] 

63 

64 

65class EvaluatorType(Enum): 

66 """Type for evaluation metrics. 

67 

68 - ``RANKING``: Ranking-based metrics like NDCG, Recall, etc. 

69 - ``VALUE``: Value-based metrics like AUC, etc. 

70 """ 

71 

72 RANKING = 1 

73 VALUE = 2 

74 

75 

76class InputType(Enum): 

77 """Type of Models' input. 

78 

79 - ``POINTWISE``: Point-wise input, like ``uid, iid, label``. 

80 - ``PAIRWISE``: Pair-wise input, like ``uid, pos_iid, neg_iid``. 

81 - ``LISTWISE``: List-wise input, like ``uid, [iid1, iid2, ...]``. 

82 - ``PATHWISE``: KG Path-wise input, like ``uid, pos_iid, eid1, eid2, next_pos_iid``. 

83 - ``USERWISE``: User-wise input, like ``uid0, uid1, ...., uidn``. 

84 """ 

85 

86 POINTWISE = 1 

87 PAIRWISE = 2 

88 LISTWISE = 3 

89 PATHWISE = 4 

90 USERWISE = 5 

91 

92 

93class FeatureType(Enum): 

94 """Type of features. 

95 

96 - ``TOKEN``: Token features like user_id and item_id. 

97 - ``FLOAT``: Float features like rating and timestamp. 

98 - ``TOKEN_SEQ``: Token sequence features like review. 

99 - ``FLOAT_SEQ``: Float sequence features like pretrained vector. 

100 """ 

101 

102 TOKEN = "token" 

103 FLOAT = "float" 

104 TOKEN_SEQ = "token_seq" 

105 FLOAT_SEQ = "float_seq" 

106 

107 

108class FeatureSource(Enum): 

109 """Source of features. 

110 

111 - ``INTERACTION``: Features from ``.inter`` (other than ``user_id`` and ``item_id``). 

112 - ``USER``: Features from ``.user`` (other than ``user_id``). 

113 - ``ITEM``: Features from ``.item`` (other than ``item_id``). 

114 - ``USER_ID``: ``user_id`` feature in ``inter_feat`` and ``user_feat``. 

115 - ``ITEM_ID``: ``item_id`` feature in ``inter_feat`` and ``item_feat``. 

116 - ``KG``: Features from ``.kg``. 

117 - ``NET``: Features from ``.net``. 

118 """ 

119 

120 INTERACTION = "inter" 

121 USER = "user" 

122 ITEM = "item" 

123 USER_ID = "user_id" 

124 ITEM_ID = "item_id" 

125 KG = "kg" 

126 NET = "net" 

127 

128 

129class PathLanguageModelingTokenType(Enum): 

130 """Type of tokens in paths for Path Language Modeling. 

131 

132 - ``SPECIAL``: Special tokens, like start and end of a path. 

133 - ``ENTITY``: Entity tokens. 

134 - ``RELATION``: Relation tokens. 

135 - ``USER``: User tokens. 

136 - ``ITEM``: Item tokens. 

137 """ 

138 

139 SPECIAL = ("S", 0) 

140 ENTITY = ("E", 1) 

141 RELATION = ("R", 2) 

142 USER = ("U", 3) 

143 ITEM = ("I", 4) 

144 

145 def __init__(self, token, token_id): 

146 self.token = token 

147 self.token_id = token_id 

148 

149 def __str__(self): 

150 return self.token 

151 

152 

153class PathSamplingStrategy(Enum): 

154 """Strategy for sampling paths from the knowledge graph. 

155 

156 - ``WEIGHTED_RW``: Weighted random walk with sampling-and-discarding approach. 

157 - ``CONSTRAINED_RW``: Constrained random walk with type constraints. 

158 - ``SIMPLE_UI``: Per-interaction coverage sampling; random walks anchored at each user-item interaction, ending at 

159 another positive item, re-sampled until each interaction reaches its path quota (MAX_PATHS_PER_USER per pair). 

160 

161 """ 

162 

163 WEIGHTED_RW = "weighted-rw" 

164 CONSTRAINED_RW = "constrained-rw" 

165 SIMPLE_UI = "simple-ui" 

166 

167 def __str__(self): 

168 return self.value