recbole.utils.enum_type¶
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class
recbole.utils.enum_type.DataLoaderType(value)[source]¶ Bases:
enum.EnumType of DataLoaders.
ORIGIN: Original DataLoaderFULL: DataLoader for full-sort evaluationNEGSAMPLE: DataLoader for negative sample evaluation
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FULL= 2¶
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NEGSAMPLE= 3¶
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ORIGIN= 1¶
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class
recbole.utils.enum_type.EvaluatorType(value)[source]¶ Bases:
enum.EnumType for evaluation metrics.
RANKING: Ranking metrics like NDCG, Recall, etc.INDIVIDUAL: Individual metrics like AUC, etc.
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INDIVIDUAL= 2¶
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RANKING= 1¶
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class
recbole.utils.enum_type.FeatureSource(value)[source]¶ Bases:
enum.EnumSource of features.
INTERACTION: Features from.inter(other thanuser_idanditem_id).USER: Features from.user(other thanuser_id).ITEM: Features from.item(other thanitem_id).USER_ID:user_idfeature ininter_featanduser_feat.ITEM_ID:item_idfeature ininter_featanditem_feat.KG: Features from.kg.NET: Features from.net.
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INTERACTION= 'inter'¶
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ITEM= 'item'¶
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ITEM_ID= 'item_id'¶
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KG= 'kg'¶
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NET= 'net'¶
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USER= 'user'¶
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USER_ID= 'user_id'¶
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class
recbole.utils.enum_type.FeatureType(value)[source]¶ Bases:
enum.EnumType of features.
TOKEN: Token features like user_id and item_id.FLOAT: Float features like rating and timestamp.TOKEN_SEQ: Token sequence features like review.FLOAT_SEQ: Float sequence features like pretrained vector.
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FLOAT= 'float'¶
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FLOAT_SEQ= 'float_seq'¶
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TOKEN= 'token'¶
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TOKEN_SEQ= 'token_seq'¶
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class
recbole.utils.enum_type.InputType(value)[source]¶ Bases:
enum.EnumType of Models’ input.
POINTWISE: Point-wise input, likeuid, iid, label.PAIRWISE: Pair-wise input, likeuid, pos_iid, neg_iid.
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LISTWISE= 3¶
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PAIRWISE= 2¶
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POINTWISE= 1¶
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class
recbole.utils.enum_type.KGDataLoaderState(value)[source]¶ Bases:
enum.EnumStates for Knowledge-based DataLoader.
RSKG: Return both knowledge graph information and user-item interaction information.RS: Only return the user-item interaction.KG: Only return the triplets with negative examples in a knowledge graph.
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KG= 3¶
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RS= 2¶
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RSKG= 1¶
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class
recbole.utils.enum_type.ModelType(value)[source]¶ Bases:
enum.EnumType of models.
GENERAL: General RecommendationSEQUENTIAL: Sequential RecommendationCONTEXT: Context-aware RecommendationKNOWLEDGE: Knowledge-based Recommendation
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CONTEXT= 3¶
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DECISIONTREE= 7¶
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GENERAL= 1¶
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KNOWLEDGE= 4¶
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SEQUENTIAL= 2¶
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SOCIAL= 5¶
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TRADITIONAL= 6¶