recbole.modelΒΆ
- recbole.model.context_aware_recommender
- recbole.model.exlib_recommender
- recbole.model.general_recommender
- BPR
BPR- CDAE
CDAE- ConvNCF
ConvNCFConvNCFBPRLoss- DGCF
DGCFsample_cor_samples()- DMF
DMF- FISM
FISM- GCMC
BiDecoderGCMCGcEncoderorthogonal()- ItemKNN
ComputeSimilarityItemKNN- LightGCN
LightGCN- LINE
LINENegSamplingLoss- MacridVAE
MacridVAE- MultiDAE
MultiDAE- MultiVAE
MultiVAE- NAIS
NAIS- NeuMF
NeuMF- NGCF
NGCF- Pop
Pop- SGL
SGL- SimpleX
SimpleX- SpectralCF
SpectralCF- NCL
NCL
- recbole.model.knowledge_aware_recommender
- CFKG
CFKGInnerProductLoss- CKE
CKE- KGAT
AggregatorKGAT- KGCN
KGCN- KGNNLS
KGNNLSKGNNLS.aggregate()KGNNLS.calculate_loss()KGNNLS.calculate_ls_loss()KGNNLS.construct_adj()KGNNLS.forward()KGNNLS.full_sort_predict()KGNNLS.get_interaction_table()KGNNLS.get_neighbors()KGNNLS.input_typeKGNNLS.label_smoothness_predict()KGNNLS.predict()KGNNLS.sample_neg_interaction()KGNNLS.training
- KTUP
KTUPalignLoss()orthogonalLoss()- MKR
CrossCompressUnitMKR- RippleNet
RippleNet
- recbole.model.sequential_recommender
- BERT4Rec
BERT4Rec- Caser
Caser- CORE
CORETransNet- DIN
DIN- FDSA
FDSA- FOSSIL
FOSSIL- FPMC
FPMC- GCSAN
GCSANGNN- GRU4Rec
GRU4Rec- GRU4RecF
GRU4RecF- GRU4RecKG
GRU4RecKG- HGN
HGN- HRM
HRM- KSR
KSR- NARM
NARM- NextItNet
NextItNetResidualBlock_aResidualBlock_b- NPE
NPE- RepeatNet
Explore_Recommendation_DecoderRepeatNetRepeat_Explore_MechanismRepeat_Recommendation_Decoderbuild_map()- S3Rec
S3Rec- SASRec
SASRec- SASRecF
SASRecF- SHAN
SHAN- SRGNN
GNNSRGNN- STAMP
STAMP- TransRec
TransRec
- recbole.model.abstract_recommender
AbstractRecommenderAutoEncoderMixinContextRecommenderContextRecommender.concat_embed_input_fields()ContextRecommender.double_tower_embed_input_fields()ContextRecommender.embed_float_fields()ContextRecommender.embed_float_seq_fields()ContextRecommender.embed_input_fields()ContextRecommender.embed_token_fields()ContextRecommender.embed_token_seq_fields()ContextRecommender.input_typeContextRecommender.trainingContextRecommender.type
GeneralRecommenderKnowledgeRecommenderSequentialRecommender- recbole.model.init
xavier_normal_initialization()xavier_uniform_initialization()- recbole.model.layers
AttLayerBaseFactorizationMachineBiGNNLayerCNNLayersContextSeqEmbAbstractLayerContextSeqEmbAbstractLayer.embed_float_fields()ContextSeqEmbAbstractLayer.embed_float_seq_fields()ContextSeqEmbAbstractLayer.embed_input_fields()ContextSeqEmbAbstractLayer.embed_token_fields()ContextSeqEmbAbstractLayer.embed_token_seq_fields()ContextSeqEmbAbstractLayer.forward()ContextSeqEmbAbstractLayer.get_embedding()ContextSeqEmbAbstractLayer.get_fields_name_dim()ContextSeqEmbAbstractLayer.training
ContextSeqEmbLayerDiceFLEmbeddingFMEmbeddingFMFirstOrderLinearFeatureSeqEmbLayerFeedForwardItemToInterestAggregationLightMultiHeadAttentionLightTransformerEncoderLightTransformerLayerMLPLayersMultiHeadAttentionSequenceAttLayerSparseDropoutTransformerEncoderTransformerLayerVanillaAttentionactivation_layer()- recbole.model.loss
BPRLossEmbLossEmbMarginLossRegLoss