recbole.model¶

recbole.model.context_aware_recommender
- AFM
- AFM
  - AFM.afm_layer()
  - AFM.build_cross()
  - AFM.calculate_loss()
  - AFM.forward()
  - AFM.predict()
  - AFM.training
- AutoInt
- AutoInt
  - AutoInt.autoint_layer()
  - AutoInt.calculate_loss()
  - AutoInt.forward()
  - AutoInt.predict()
  - AutoInt.training
- DCN
- DCN
  - DCN.calculate_loss()
  - DCN.cross_network()
  - DCN.forward()
  - DCN.predict()
  - DCN.training
- DCN V2
- DCNV2
  - DCNV2.calculate_loss()
  - DCNV2.cross_network()
  - DCNV2.cross_network_mix()
  - DCNV2.forward()
  - DCNV2.predict()
  - DCNV2.training
- DeepFM
- DeepFM
  - DeepFM.calculate_loss()
  - DeepFM.forward()
  - DeepFM.predict()
  - DeepFM.training
- DSSM
- DSSM
  - DSSM.calculate_loss()
  - DSSM.forward()
  - DSSM.predict()
  - DSSM.training
- EulerNet
- EulerInteractionLayer
  - EulerInteractionLayer.forward()
  - EulerInteractionLayer.training
- EulerNet
  - EulerNet.RegularLoss()
  - EulerNet.calculate_loss()
  - EulerNet.forward()
  - EulerNet.predict()
  - EulerNet.training
- FFM
- FFM
  - FFM.calculate_loss()
  - FFM.forward()
  - FFM.get_ffm_input()
  - FFM.predict()
  - FFM.training
- FieldAwareFactorizationMachine
  - FieldAwareFactorizationMachine.forward()
  - FieldAwareFactorizationMachine.training
- FiGNN
- FiGNN
  - FiGNN.calculate_loss()
  - FiGNN.fignn_layer()
  - FiGNN.forward()
  - FiGNN.input_type
  - FiGNN.predict()
  - FiGNN.training
- GraphLayer
  - GraphLayer.forward()
  - GraphLayer.training
- FM
- FM
  - FM.calculate_loss()
  - FM.forward()
  - FM.predict()
  - FM.training
- FNN
- FNN
  - FNN.calculate_loss()
  - FNN.forward()
  - FNN.predict()
  - FNN.training
- FwFM
- FwFM
  - FwFM.calculate_loss()
  - FwFM.forward()
  - FwFM.fwfm_layer()
  - FwFM.predict()
  - FwFM.training
- KD_DAGFM
- CIN
  - CIN.FeatureInteraction()
  - CIN.forward()
  - CIN.training
- CINComp
  - CINComp.forward()
  - CINComp.training
- CrossNet
  - CrossNet.FeatureInteraction()
  - CrossNet.forward()
  - CrossNet.training
- DAGFM
  - DAGFM.FeatureInteraction()
  - DAGFM.training
- KD_DAGFM
  - KD_DAGFM.FeatureInteraction()
  - KD_DAGFM.calculate_loss()
  - KD_DAGFM.forward()
  - KD_DAGFM.get_teacher_config()
  - KD_DAGFM.predict()
  - KD_DAGFM.training
- LR
- LR
  - LR.calculate_loss()
  - LR.forward()
  - LR.predict()
  - LR.training
- NFM
- NFM
  - NFM.calculate_loss()
  - NFM.forward()
  - NFM.predict()
  - NFM.training
- PNN
- InnerProductLayer
  - InnerProductLayer.forward()
  - InnerProductLayer.training
- OuterProductLayer
  - OuterProductLayer.forward()
  - OuterProductLayer.training
- PNN
  - PNN.calculate_loss()
  - PNN.forward()
  - PNN.predict()
  - PNN.reg_loss()
  - PNN.training
- WideDeep
- WideDeep
  - WideDeep.calculate_loss()
  - WideDeep.forward()
  - WideDeep.predict()
  - WideDeep.training
- xDeepFM
- xDeepFM
  - xDeepFM.calculate_loss()
  - xDeepFM.calculate_reg_loss()
  - xDeepFM.compressed_interaction_network()
  - xDeepFM.forward()
  - xDeepFM.predict()
  - xDeepFM.reg_loss()
  - xDeepFM.training
recbole.model.exlib_recommender
- recbole.model.exlib_recommender.xgboost
- XGBoost
- recbole.model.exlib_recommender.lightgbm
- LightGBM
recbole.model.general_recommender
- AsymKNN
  - AsymKNN.calculate_loss()
  - AsymKNN.forward()
  - AsymKNN.full_sort_predict()
  - AsymKNN.input_type
  - AsymKNN.predict()
  - AsymKNN.training
  - AsymKNN.type
- ComputeSimilarity
  - ComputeSimilarity.compute_asym_similarity()
- ADMMSLIM
- ADMMSLIM
  - ADMMSLIM.calculate_loss()
  - ADMMSLIM.forward()
  - ADMMSLIM.full_sort_predict()
  - ADMMSLIM.input_type
  - ADMMSLIM.predict()
  - ADMMSLIM.training
  - ADMMSLIM.type
- add_noise()
- soft_threshold()
- zero_mean_columns()
- BPR
- BPR
  - BPR.calculate_loss()
  - BPR.forward()
  - BPR.full_sort_predict()
  - BPR.get_item_embedding()
  - BPR.get_user_embedding()
  - BPR.input_type
  - BPR.predict()
  - BPR.training
- CDAE
- CDAE
  - CDAE.calculate_loss()
  - CDAE.forward()
  - CDAE.full_sort_predict()
  - CDAE.input_type
  - CDAE.predict()
  - CDAE.training
- ConvNCF
- ConvNCF
  - ConvNCF.calculate_loss()
  - ConvNCF.forward()
  - ConvNCF.input_type
  - ConvNCF.predict()
  - ConvNCF.reg_loss()
  - ConvNCF.training
- ConvNCFBPRLoss
  - ConvNCFBPRLoss.forward()
  - ConvNCFBPRLoss.training
- DGCF
- DGCF
  - DGCF.build_matrix()
  - DGCF.calculate_loss()
  - DGCF.create_cor_loss()
  - DGCF.forward()
  - DGCF.full_sort_predict()
  - DGCF.input_type
  - DGCF.predict()
  - DGCF.training
- sample_cor_samples()
- DMF
- DMF
  - DMF.calculate_loss()
  - DMF.forward()
  - DMF.full_sort_predict()
  - DMF.get_item_embedding()
  - DMF.get_user_embedding()
  - DMF.input_type
  - DMF.predict()
  - DMF.training
- DiffRec
- DNN
  - DNN.forward()
  - DNN.training
- DiffRec
  - DiffRec.SNR()
  - DiffRec.build_histroy_items()
  - DiffRec.calculate_for_diffusion()
  - DiffRec.calculate_loss()
  - DiffRec.full_sort_predict()
  - DiffRec.get_betas()
  - DiffRec.input_type
  - DiffRec.p_mean_variance()
  - DiffRec.p_sample()
  - DiffRec.predict()
  - DiffRec.q_posterior_mean_variance()
  - DiffRec.q_sample()
  - DiffRec.reweight_loss()
  - DiffRec.sample_timesteps()
  - DiffRec.training
  - DiffRec.update_Lt_history()
- ModelMeanType
  - ModelMeanType.EPSILON
  - ModelMeanType.START_X
- betas_for_alpha_bar()
- betas_from_linear_variance()
- mean_flat()
- normal_kl()
- timestep_embedding()
- EASE
- EASE
  - EASE.calculate_loss()
  - EASE.forward()
  - EASE.full_sort_predict()
  - EASE.input_type
  - EASE.predict()
  - EASE.training
  - EASE.type
- ENMF
- ENMF
  - ENMF.calculate_loss()
  - ENMF.forward()
  - ENMF.full_sort_predict()
  - ENMF.input_type
  - ENMF.predict()
  - ENMF.reg_loss()
  - ENMF.training
- FISM
- FISM
  - FISM.calculate_loss()
  - FISM.forward()
  - FISM.full_sort_predict()
  - FISM.get_history_info()
  - FISM.input_type
  - FISM.inter_forward()
  - FISM.predict()
  - FISM.reg_loss()
  - FISM.training
  - FISM.user_forward()
- GCMC
- BiDecoder
  - BiDecoder.forward()
  - BiDecoder.training
- GCMC
  - GCMC.calculate_loss()
  - GCMC.forward()
  - GCMC.full_sort_predict()
  - GCMC.get_norm_adj_mat()
  - GCMC.get_sparse_eye_mat()
  - GCMC.input_type
  - GCMC.predict()
  - GCMC.training
- GcEncoder
  - GcEncoder.forward()
  - GcEncoder.training
- orthogonal()
- ItemKNN
- ComputeSimilarity
  - ComputeSimilarity.compute_similarity()
- ItemKNN
  - ItemKNN.calculate_loss()
  - ItemKNN.forward()
  - ItemKNN.full_sort_predict()
  - ItemKNN.input_type
  - ItemKNN.predict()
  - ItemKNN.training
  - ItemKNN.type
- DiffRec
- AutoEncoder
  - AutoEncoder.Decode()
  - AutoEncoder.Encode()
  - AutoEncoder.reparamterization()
  - AutoEncoder.training
- LDiffRec
  - LDiffRec.calculate_loss()
  - LDiffRec.full_sort_predict()
  - LDiffRec.predict()
  - LDiffRec.training
- compute_loss()
- LightGCN
- LightGCN
  - LightGCN.calculate_loss()
  - LightGCN.forward()
  - LightGCN.full_sort_predict()
  - LightGCN.get_ego_embeddings()
  - LightGCN.get_norm_adj_mat()
  - LightGCN.input_type
  - LightGCN.predict()
  - LightGCN.training
- LINE
- LINE
  - LINE.calculate_loss()
  - LINE.context_forward()
  - LINE.forward()
  - LINE.full_sort_predict()
  - LINE.get_used_ids()
  - LINE.get_user_id_list()
  - LINE.input_type
  - LINE.predict()
  - LINE.random_num()
  - LINE.sampler()
  - LINE.training
- NegSamplingLoss
  - NegSamplingLoss.forward()
  - NegSamplingLoss.training
- MacridVAE
- MacridVAE
  - MacridVAE.calculate_loss()
  - MacridVAE.forward()
  - MacridVAE.full_sort_predict()
  - MacridVAE.input_type
  - MacridVAE.mlp_layers()
  - MacridVAE.predict()
  - MacridVAE.reg_loss()
  - MacridVAE.reparameterize()
  - MacridVAE.training
- MultiDAE
- MultiDAE
  - MultiDAE.calculate_loss()
  - MultiDAE.forward()
  - MultiDAE.full_sort_predict()
  - MultiDAE.input_type
  - MultiDAE.mlp_layers()
  - MultiDAE.predict()
  - MultiDAE.training
- MultiVAE
- MultiVAE
  - MultiVAE.calculate_loss()
  - MultiVAE.forward()
  - MultiVAE.full_sort_predict()
  - MultiVAE.input_type
  - MultiVAE.mlp_layers()
  - MultiVAE.predict()
  - MultiVAE.reparameterize()
  - MultiVAE.training
- NAIS
- NAIS
  - NAIS.attention_mlp()
  - NAIS.calculate_loss()
  - NAIS.forward()
  - NAIS.full_sort_predict()
  - NAIS.get_history_info()
  - NAIS.input_type
  - NAIS.inter_forward()
  - NAIS.mask_softmax()
  - NAIS.predict()
  - NAIS.reg_loss()
  - NAIS.softmax()
  - NAIS.training
  - NAIS.user_forward()
- NCE-PLRec
- NCEPLRec
  - NCEPLRec.calculate_loss()
  - NCEPLRec.forward()
  - NCEPLRec.full_sort_predict()
  - NCEPLRec.input_type
  - NCEPLRec.predict()
  - NCEPLRec.training
- NCL
- NCL
  - NCL.ProtoNCE_loss()
  - NCL.calculate_loss()
  - NCL.e_step()
  - NCL.forward()
  - NCL.full_sort_predict()
  - NCL.get_ego_embeddings()
  - NCL.get_norm_adj_mat()
  - NCL.input_type
  - NCL.predict()
  - NCL.run_kmeans()
  - NCL.ssl_layer_loss()
  - NCL.training
- NeuMF
- NeuMF
  - NeuMF.calculate_loss()
  - NeuMF.dump_parameters()
  - NeuMF.forward()
  - NeuMF.input_type
  - NeuMF.load_pretrain()
  - NeuMF.predict()
  - NeuMF.training
- NGCF
- NGCF
  - NGCF.calculate_loss()
  - NGCF.forward()
  - NGCF.full_sort_predict()
  - NGCF.get_ego_embeddings()
  - NGCF.get_eye_mat()
  - NGCF.get_norm_adj_mat()
  - NGCF.input_type
  - NGCF.predict()
  - NGCF.training
- NNCF
- NNCF
  - NNCF.Max_ner()
  - NNCF.calculate_loss()
  - NNCF.forward()
  - NNCF.get_community_member()
  - NNCF.get_neigh_info()
  - NNCF.get_neigh_knn()
  - NNCF.get_neigh_louvain()
  - NNCF.get_neigh_random()
  - NNCF.input_type
  - NNCF.predict()
  - NNCF.prepare_vector_element()
  - NNCF.training
- Pop
- Pop
  - Pop.calculate_loss()
  - Pop.forward()
  - Pop.full_sort_predict()
  - Pop.input_type
  - Pop.predict()
  - Pop.training
  - Pop.type
- RaCT
- RaCT
  - RaCT.calculate_ac_loss()
  - RaCT.calculate_actor_loss()
  - RaCT.calculate_critic_loss()
  - RaCT.calculate_loss()
  - RaCT.calculate_ndcg()
  - RaCT.construct_critic_input()
  - RaCT.construct_critic_layers()
  - RaCT.critic_forward()
  - RaCT.forward()
  - RaCT.full_sort_predict()
  - RaCT.input_type
  - RaCT.mlp_layers()
  - RaCT.predict()
  - RaCT.reparameterize()
  - RaCT.training
- Random
- Random
  - Random.calculate_loss()
  - Random.forward()
  - Random.full_sort_predict()
  - Random.input_type
  - Random.predict()
  - Random.training
  - Random.type
- RecVAE
- CompositePrior
  - CompositePrior.forward()
  - CompositePrior.training
- Encoder
  - Encoder.forward()
  - Encoder.training
- RecVAE
  - RecVAE.calculate_loss()
  - RecVAE.forward()
  - RecVAE.full_sort_predict()
  - RecVAE.input_type
  - RecVAE.predict()
  - RecVAE.reparameterize()
  - RecVAE.training
  - RecVAE.update_prior()
- log_norm_pdf()
- swish()
- SGL
- SGL
  - SGL.calc_bpr_loss()
  - SGL.calc_ssl_loss()
  - SGL.calculate_loss()
  - SGL.create_adjust_matrix()
  - SGL.csr2tensor()
  - SGL.forward()
  - SGL.full_sort_predict()
  - SGL.graph_construction()
  - SGL.input_type
  - SGL.predict()
  - SGL.rand_sample()
  - SGL.train()
  - SGL.training
- SimpleX
- SimpleX
  - SimpleX.calculate_loss()
  - SimpleX.forward()
  - SimpleX.full_sort_predict()
  - SimpleX.get_UI_aggregation()
  - SimpleX.get_cos()
  - SimpleX.input_type
  - SimpleX.predict()
  - SimpleX.training
- SLIMElastic
- SLIMElastic
  - SLIMElastic.calculate_loss()
  - SLIMElastic.forward()
  - SLIMElastic.full_sort_predict()
  - SLIMElastic.input_type
  - SLIMElastic.predict()
  - SLIMElastic.training
  - SLIMElastic.type
- SpectralCF
- SpectralCF
  - SpectralCF.calculate_loss()
  - SpectralCF.forward()
  - SpectralCF.full_sort_predict()
  - SpectralCF.get_ego_embeddings()
  - SpectralCF.get_eye_mat()
  - SpectralCF.get_laplacian_matrix()
  - SpectralCF.input_type
  - SpectralCF.predict()
  - SpectralCF.training
recbole.model.knowledge_aware_recommender
- CFKG
- CFKG
  - CFKG.calculate_loss()
  - CFKG.forward()
  - CFKG.input_type
  - CFKG.predict()
  - CFKG.training
- InnerProductLoss
  - InnerProductLoss.forward()
  - InnerProductLoss.training
- CKE
- CKE
  - CKE.calculate_loss()
  - CKE.forward()
  - CKE.full_sort_predict()
  - CKE.input_type
  - CKE.predict()
  - CKE.training
- KGAT
- Aggregator
  - Aggregator.forward()
  - Aggregator.training
- KGAT
  - KGAT.calculate_kg_loss()
  - KGAT.calculate_loss()
  - KGAT.forward()
  - KGAT.full_sort_predict()
  - KGAT.generate_transE_score()
  - KGAT.init_graph()
  - KGAT.input_type
  - KGAT.predict()
  - KGAT.training
  - KGAT.update_attentive_A()
- KGCN
- KGCN
  - KGCN.aggregate()
  - KGCN.calculate_loss()
  - KGCN.construct_adj()
  - KGCN.forward()
  - KGCN.full_sort_predict()
  - KGCN.get_neighbors()
  - KGCN.input_type
  - KGCN.mix_neighbor_vectors()
  - KGCN.predict()
  - KGCN.training
- KGIN
- Aggregator
  - Aggregator.forward()
  - Aggregator.training
- GraphConv
  - GraphConv.calculate_cor_loss()
  - GraphConv.edge_sampling()
  - GraphConv.forward()
  - GraphConv.training
- KGIN
  - KGIN.calculate_loss()
  - KGIN.forward()
  - KGIN.full_sort_predict()
  - KGIN.get_edges()
  - KGIN.get_norm_inter_matrix()
  - KGIN.input_type
  - KGIN.predict()
  - KGIN.training
- KGNNLS
- KGNNLS
  - KGNNLS.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_type
  - KGNNLS.label_smoothness_predict()
  - KGNNLS.predict()
  - KGNNLS.sample_neg_interaction()
  - KGNNLS.training
- KTUP
- KTUP
  - KTUP.calculate_kg_loss()
  - KTUP.calculate_loss()
  - KTUP.convert_to_one_hot()
  - KTUP.forward()
  - KTUP.input_type
  - KTUP.predict()
  - KTUP.st_gumbel_softmax()
  - KTUP.training
- alignLoss()
- orthogonalLoss()
- MCCLK
- Aggregator
  - Aggregator.calculate_sim_hrt()
  - Aggregator.forward()
  - Aggregator.training
- GraphConv
  - GraphConv.build_adj()
  - GraphConv.edge_sampling()
  - GraphConv.forward()
  - GraphConv.training
- MCCLK
  - MCCLK.calculate_loss()
  - MCCLK.forward()
  - MCCLK.full_sort_predict()
  - MCCLK.get_edges()
  - MCCLK.get_norm_inter_matrix()
  - MCCLK.global_level_loss_1()
  - MCCLK.global_level_loss_2()
  - MCCLK.input_type
  - MCCLK.light_gcn()
  - MCCLK.local_level_loss()
  - MCCLK.predict()
  - MCCLK.sim()
  - MCCLK.training
- MKR
- CrossCompressUnit
  - CrossCompressUnit.forward()
  - CrossCompressUnit.training
- MKR
  - MKR.calculate_kg_loss()
  - MKR.calculate_rs_loss()
  - MKR.forward()
  - MKR.input_type
  - MKR.predict()
  - MKR.training
- RippleNet
- RippleNet
  - RippleNet.calculate_loss()
  - RippleNet.forward()
  - RippleNet.full_sort_predict()
  - RippleNet.input_type
  - RippleNet.predict()
  - RippleNet.training
recbole.model.sequential_recommender
- BERT4Rec
- BERT4Rec
  - BERT4Rec.calculate_loss()
  - BERT4Rec.forward()
  - BERT4Rec.full_sort_predict()
  - BERT4Rec.multi_hot_embed()
  - BERT4Rec.predict()
  - BERT4Rec.reconstruct_test_data()
  - BERT4Rec.training
- Caser
- Caser
  - Caser.calculate_loss()
  - Caser.forward()
  - Caser.full_sort_predict()
  - Caser.predict()
  - Caser.reg_loss_conv_h()
  - Caser.training
- CORE
- CORE
  - CORE.ave_net()
  - CORE.calculate_loss()
  - CORE.forward()
  - CORE.full_sort_predict()
  - CORE.predict()
  - CORE.training
- TransNet
  - TransNet.forward()
  - TransNet.get_attention_mask()
  - TransNet.training
- DIN
- DIN
  - DIN.calculate_loss()
  - DIN.forward()
  - DIN.input_type
  - DIN.predict()
  - DIN.training
- FDSA
- FDSA
  - FDSA.calculate_loss()
  - FDSA.forward()
  - FDSA.full_sort_predict()
  - FDSA.predict()
  - FDSA.training
- FOSSIL
- FOSSIL
  - FOSSIL.calculate_loss()
  - FOSSIL.forward()
  - FOSSIL.full_sort_predict()
  - FOSSIL.get_high_order_Markov()
  - FOSSIL.get_similarity()
  - FOSSIL.init_weights()
  - FOSSIL.inverse_seq_item_embedding()
  - FOSSIL.predict()
  - FOSSIL.reg_loss()
  - FOSSIL.training
- FPMC
- FPMC
  - FPMC.calculate_loss()
  - FPMC.forward()
  - FPMC.full_sort_predict()
  - FPMC.input_type
  - FPMC.predict()
  - FPMC.training
- GCSAN
- GCSAN
  - GCSAN.calculate_loss()
  - GCSAN.forward()
  - GCSAN.full_sort_predict()
  - GCSAN.predict()
  - GCSAN.training
- GNN
  - GNN.GNNCell()
  - GNN.forward()
  - GNN.training
- GRU4Rec
- GRU4Rec
  - GRU4Rec.calculate_loss()
  - GRU4Rec.forward()
  - GRU4Rec.full_sort_predict()
  - GRU4Rec.predict()
  - GRU4Rec.training
- GRU4RecF
- GRU4RecF
  - GRU4RecF.calculate_loss()
  - GRU4RecF.forward()
  - GRU4RecF.full_sort_predict()
  - GRU4RecF.predict()
  - GRU4RecF.training
- GRU4RecKG
- GRU4RecKG
  - GRU4RecKG.calculate_loss()
  - GRU4RecKG.forward()
  - GRU4RecKG.full_sort_predict()
  - GRU4RecKG.predict()
  - GRU4RecKG.training
- HGN
- HGN
  - HGN.calculate_loss()
  - HGN.feature_gating()
  - HGN.forward()
  - HGN.full_sort_predict()
  - HGN.instance_gating()
  - HGN.predict()
  - HGN.reg_loss()
  - HGN.training
- HRM
- HRM
  - HRM.calculate_loss()
  - HRM.forward()
  - HRM.full_sort_predict()
  - HRM.inverse_seq_item()
  - HRM.predict()
  - HRM.training
- KSR
- KSR
  - KSR.calculate_loss()
  - KSR.forward()
  - KSR.full_sort_predict()
  - KSR.memory_read()
  - KSR.memory_update()
  - KSR.predict()
  - KSR.training
- NARM
- NARM
  - NARM.calculate_loss()
  - NARM.forward()
  - NARM.full_sort_predict()
  - NARM.predict()
  - NARM.training
- NextItNet
- NextItNet
  - NextItNet.calculate_loss()
  - NextItNet.forward()
  - NextItNet.full_sort_predict()
  - NextItNet.predict()
  - NextItNet.reg_loss_rb()
  - NextItNet.training
- ResidualBlock_a
  - ResidualBlock_a.conv_pad()
  - ResidualBlock_a.forward()
  - ResidualBlock_a.training
- ResidualBlock_b
  - ResidualBlock_b.conv_pad()
  - ResidualBlock_b.forward()
  - ResidualBlock_b.training
- NPE
- NPE
  - NPE.calculate_loss()
  - NPE.forward()
  - NPE.full_sort_predict()
  - NPE.predict()
  - NPE.training
- RepeatNet
- Explore_Recommendation_Decoder
  - Explore_Recommendation_Decoder.forward()
  - Explore_Recommendation_Decoder.training
- RepeatNet
  - RepeatNet.calculate_loss()
  - RepeatNet.forward()
  - RepeatNet.full_sort_predict()
  - RepeatNet.input_type
  - RepeatNet.predict()
  - RepeatNet.repeat_explore_loss()
  - RepeatNet.training
- Repeat_Explore_Mechanism
  - Repeat_Explore_Mechanism.forward()
  - Repeat_Explore_Mechanism.training
- Repeat_Recommendation_Decoder
  - Repeat_Recommendation_Decoder.forward()
  - Repeat_Recommendation_Decoder.training
- S3Rec
- S3Rec
  - S3Rec.calculate_loss()
  - S3Rec.forward()
  - S3Rec.full_sort_predict()
  - S3Rec.predict()
  - S3Rec.pretrain()
  - S3Rec.reconstruct_pretrain_data()
  - S3Rec.training
- SASRec
- SASRec
  - SASRec.calculate_loss()
  - SASRec.forward()
  - SASRec.full_sort_predict()
  - SASRec.predict()
  - SASRec.training
- SASRecF
- SASRecF
  - SASRecF.calculate_loss()
  - SASRecF.forward()
  - SASRecF.full_sort_predict()
  - SASRecF.predict()
  - SASRecF.training
- SHAN
- SHAN
  - SHAN.calculate_loss()
  - SHAN.forward()
  - SHAN.full_sort_predict()
  - SHAN.init_weights()
  - SHAN.long_and_short_term_attention_based_pooling_layer()
  - SHAN.long_term_attention_based_pooling_layer()
  - SHAN.predict()
  - SHAN.reg_loss()
  - SHAN.training
- SRGNN
- GNN
  - GNN.GNNCell()
  - GNN.forward()
  - GNN.training
- SRGNN
  - SRGNN.calculate_loss()
  - SRGNN.forward()
  - SRGNN.full_sort_predict()
  - SRGNN.predict()
  - SRGNN.training
- STAMP
- STAMP
  - STAMP.calculate_loss()
  - STAMP.count_alpha()
  - STAMP.forward()
  - STAMP.full_sort_predict()
  - STAMP.predict()
  - STAMP.training
- TransRec
- TransRec
  - TransRec.calculate_loss()
  - TransRec.forward()
  - TransRec.full_sort_predict()
  - TransRec.gather_last_items()
  - TransRec.input_type
  - TransRec.predict()
  - TransRec.training
- FEARec
- FEABlock
  - FEABlock.forward()
  - FEABlock.training
- FEAEncoder
  - FEAEncoder.forward()
  - FEAEncoder.training
- FEARec
  - FEARec.alignment()
  - FEARec.calculate_loss()
  - FEARec.decompose()
  - FEARec.forward()
  - FEARec.full_sort_predict()
  - FEARec.get_attention_mask()
  - FEARec.get_bi_attention_mask()
  - FEARec.get_same_item_index()
  - FEARec.info_nce()
  - FEARec.mask_correlated_samples()
  - FEARec.predict()
  - FEARec.training
  - FEARec.truncated_normal_()
  - FEARec.uniformity()
- FeedForward
  - FeedForward.forward()
  - FeedForward.gelu()
  - FeedForward.get_hidden_act()
  - FeedForward.swish()
  - FeedForward.training
- HybridAttention
  - HybridAttention.forward()
  - HybridAttention.time_delay_agg_inference()
  - HybridAttention.time_delay_agg_training()
  - HybridAttention.training
  - HybridAttention.transpose_for_scores()
- GRU4Rec + Softmax-CPR
- GRU4RecCPR
  - GRU4RecCPR.calculate_loss()
  - GRU4RecCPR.calculate_loss_prob()
  - GRU4RecCPR.forward()
  - GRU4RecCPR.full_sort_predict()
  - GRU4RecCPR.get_facet_emb()
  - GRU4RecCPR.predict()
  - GRU4RecCPR.training
- gelu()
- SASRec + Softmax-CPR
- SASRecCPR
  - SASRecCPR.calculate_loss()
  - SASRecCPR.calculate_loss_prob()
  - SASRecCPR.forward()
  - SASRecCPR.full_sort_predict()
  - SASRecCPR.get_facet_emb()
  - SASRecCPR.predict()
  - SASRecCPR.training
- gelu()
recbole.model.abstract_recommender
AbstractRecommender
- AbstractRecommender.calculate_loss()
- AbstractRecommender.full_sort_predict()
- AbstractRecommender.load_other_parameter()
- AbstractRecommender.other_parameter()
- AbstractRecommender.predict()
- AbstractRecommender.training
AutoEncoderMixin
- AutoEncoderMixin.build_histroy_items()
- AutoEncoderMixin.get_rating_matrix()
ContextRecommender
- ContextRecommender.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_type
- ContextRecommender.training
- ContextRecommender.type
GeneralRecommender
- GeneralRecommender.training
- GeneralRecommender.type
KnowledgeRecommender
- KnowledgeRecommender.training
- KnowledgeRecommender.type
SequentialRecommender
- SequentialRecommender.gather_indexes()
- SequentialRecommender.get_attention_mask()
- SequentialRecommender.training
- SequentialRecommender.type
recbole.model.init
xavier_normal_initialization()
xavier_uniform_initialization()
recbole.model.layers
AttLayer
- AttLayer.forward()
- AttLayer.training
BaseFactorizationMachine
- BaseFactorizationMachine.forward()
- BaseFactorizationMachine.training
BiGNNLayer
- BiGNNLayer.forward()
- BiGNNLayer.training
CNNLayers
- CNNLayers.forward()
- CNNLayers.init_weights()
- CNNLayers.training
ContextSeqEmbAbstractLayer
- ContextSeqEmbAbstractLayer.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
ContextSeqEmbLayer
- ContextSeqEmbLayer.training
Dice
- Dice.forward()
- Dice.training
FLEmbedding
- FLEmbedding.forward()
- FLEmbedding.training
FMEmbedding
- FMEmbedding.forward()
- FMEmbedding.training
FMFirstOrderLinear
- FMFirstOrderLinear.embed_float_fields()
- FMFirstOrderLinear.embed_float_seq_fields()
- FMFirstOrderLinear.embed_token_fields()
- FMFirstOrderLinear.embed_token_seq_fields()
- FMFirstOrderLinear.forward()
- FMFirstOrderLinear.training
FeatureSeqEmbLayer
- FeatureSeqEmbLayer.training
FeedForward
- FeedForward.forward()
- FeedForward.gelu()
- FeedForward.get_hidden_act()
- FeedForward.swish()
- FeedForward.training
ItemToInterestAggregation
- ItemToInterestAggregation.forward()
- ItemToInterestAggregation.training
LightMultiHeadAttention
- LightMultiHeadAttention.forward()
- LightMultiHeadAttention.training
- LightMultiHeadAttention.transpose_for_scores()
LightTransformerEncoder
- LightTransformerEncoder.forward()
- LightTransformerEncoder.training
LightTransformerLayer
- LightTransformerLayer.forward()
- LightTransformerLayer.training
MLPLayers
- MLPLayers.forward()
- MLPLayers.init_weights()
- MLPLayers.training
MultiHeadAttention
- MultiHeadAttention.forward()
- MultiHeadAttention.training
- MultiHeadAttention.transpose_for_scores()
SequenceAttLayer
- SequenceAttLayer.forward()
- SequenceAttLayer.training
SparseDropout
- SparseDropout.forward()
- SparseDropout.training
TransformerEncoder
- TransformerEncoder.forward()
- TransformerEncoder.training
TransformerLayer
- TransformerLayer.forward()
- TransformerLayer.training
VanillaAttention
- VanillaAttention.forward()
- VanillaAttention.training
activation_layer()
recbole.model.loss
BPRLoss
- BPRLoss.forward()
- BPRLoss.training
EmbLoss
- EmbLoss.forward()
- EmbLoss.training
EmbMarginLoss
- EmbMarginLoss.forward()
- EmbMarginLoss.training
RegLoss
- RegLoss.forward()
- RegLoss.training