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Functions2,023 in github.com/THUDM/HGB

⨍ Functions 2,023◇ Types & classes 293
↓ 4 callersFunctionremove_self_loops
(edge_index, edge_attr=None)
NC/benchmark/methods/RSHN/torch_geometric/utils/loop.py:12
↓ 4 callersFunctionwrite_log
(log_file, log_msg)
NC/benchmark/scripts/NC_F1.py:92
↓ 4 callersFunctionwrite_log
(log_file, log_msg)
LP/benchmark/scripts/LP_AUC_MRR.py:120
↓ 4 callersFunctionwrite_node
(dic, mat, feat, type_id)
NC/GTN/get_acm_data.py:133
↓ 3 callersMethod__init__
(self, g, in_dims, num_hidden, num_classes
NC/benchmark/methods/HGT/GNN.py:133
↓ 3 callersMethod__init__
(self, g, in_dims, num_hidden, num_classes
NC/benchmark/methods/baseline/GNN.py:136
↓ 3 callersMethod__init__
(self, meta_paths, in_size, hidden_size, out_size, num_heads, dropout)
NC/benchmark/methods/HAN/model_hetero_multi.py:94
↓ 3 callersMethod__init__
(self, meta_paths, in_size, hidden_size, out_size, num_heads, dropout)
NC/benchmark/methods/HAN/model_hetero.py:94
↓ 3 callersMethod__init__
(self)
LP/HetGNN/code/homoGNN.py:42
↓ 3 callersMethod__init__
(self)
LP/benchmark/methods/HGT/model.py:21
↓ 3 callersMethod__init__
(self)
LP/benchmark/methods/GNN/GNN.py:25
↓ 3 callersMethod__init__
(self, g, in_feats, n_hidden, n_classes,
TC/HGAT/model/code/models.py:55
↓ 3 callersMethod__init__
(self, g, in_dims, num_hidden, num_classes
TC/HGAT/model/code/baseline/GNN.py:136
↓ 3 callersMethod__init__
(self, batch_size, dim, dropout, act, name)
Recom/KGCN/src/aggregators.py:17
↓ 3 callersMethod_call
(self, inputs)
Recom/KGNN-LS/src/gcn/layers.py:36
↓ 3 callersMethod_extract_sp_info
(self, sp_feats)
Recom/KGAT/Model/utility/loader_nfm.py:76
↓ 3 callersMethod_get_bi_pooling_predictions
(self, feats)
Recom/KGAT/Model/NFM.py:134
↓ 3 callersMethod_mix_neighbor_vectors
(self, neighbor_vectors, neighbor_relations, user_embeddings)
Recom/KGCN/src/aggregators.py:40
↓ 3 callersMethod_mix_neighbor_vectors
(self, neighbor_vectors, neighbor_relations, user_embeddings)
Recom/KGNN-LS/src/aggregators.py:41
↓ 3 callersMethodapply
(self, func, *keys)
NC/benchmark/methods/RSHN/torch_geometric/data/data.py:107
↓ 3 callersMethodapply
(self, func, *keys)
NC/RSHN/torch_geometric/data/data.py:107
↓ 3 callersMethodcalc_score
(self, embedding, triplets)
LP/RGCN-WN18/code/link_predict.py:41
↓ 3 callersMethodcalc_score
(self, embedding, triplets)
LP/benchmark/methods/RGCN/link_predict.py:46
↓ 3 callersFunctioncnt_nodes
(g)
TC/HGAT/build_data.py:29
↓ 3 callersMethodcontiguous
(self, *keys)
NC/benchmark/methods/RSHN/torch_geometric/data/data.py:112
↓ 3 callersMethodcontiguous
(self, *keys)
NC/RSHN/torch_geometric/data/data.py:112
↓ 3 callersFunctionctr_eval
(sess, model, data, batch_size)
Recom/KGCN/src/train.py:92
↓ 3 callersFunctionctr_eval
(sess, model, data, batch_size)
Recom/KGNN-LS/src/train.py:108
↓ 3 callersMethodcuda
(self, *keys)
NC/benchmark/methods/RSHN/torch_geometric/data/data.py:124
↓ 3 callersMethodcumsum
(self, key, item)
NC/benchmark/methods/RSHN/torch_geometric/data/batch.py:39
↓ 3 callersMethodcumsum
(self, key, item)
NC/RSHN/torch_geometric/data/batch.py:39
↓ 3 callersMethoddfs
(self, now, meta, meta_dict)
NC/benchmark/scripts/data_loader.py:113
↓ 3 callersMethoddfs
(self, now, meta, meta_dict)
NC/benchmark/methods/HGT/data_loader.py:92
↓ 3 callersMethoddfs
(self, now, meta, meta_dict)
NC/benchmark/methods/HetSANN/HetSANN_MRV/scripts/data_loader.py:92
↓ 3 callersMethoddfs
(self, now, meta, meta_dict)
NC/benchmark/methods/RGCN/scripts/data_loader.py:41
↓ 3 callersMethoddfs
(self, now, meta, meta_dict)
LP/RGCN-WN18/code/scripts/data_loader.py:120
↓ 3 callersMethoddfs
(self, now, meta, meta_dict)
LP/benchmark/scripts/data_loader.py:166
↓ 3 callersMethoddfs
(self, now, meta, meta_dict)
LP/benchmark/methods/HGT/data_loader.py:146
↓ 3 callersFunctionevaluate
(model, true_edges, false_edges, dl)
LP/benchmark/methods/GATNE/utils.py:270
↓ 3 callersFunctionevaluate_results_nc
(embeddings, labels, num_classes)
NC/MAGNN/utils/tools.py:51
↓ 3 callersMethodgen_file_for_evaluate
:param edge_list: shape(2, edge_num) :param confidence: shape(edge_num,) :param edge_type: shape(1) :param file_path:
LP/benchmark/scripts/data_loader.py:227
↓ 3 callersFunctiongen_hom_data
(data_name, dataset_type='train')
LP/GATNE/src/gen_hom_data.py:20
↓ 3 callersMethodget_data
(self, name='train')
LP/RGCN/HomGNN.py:50
↓ 3 callersMethodget_edge_type
(self, info)
LP/benchmark/methods/HGT/data_loader.py:243
↓ 3 callersMethodget_initializer
()
Recom/KGCN/src/model.py:41
↓ 3 callersMethodget_node_type
(self, node_id)
NC/benchmark/scripts/data_loader.py:225
↓ 3 callersMethodget_test_neigh
(self)
LP/RGCN-WN18/code/scripts/data_loader.py:296
↓ 3 callersMethodget_train_neg
(self, edge_types=[])
LP/RGCN-WN18/code/scripts/data_loader.py:263
↓ 3 callersMethodget_valid_neg
(self, edge_types=[])
LP/RGCN-WN18/code/scripts/data_loader.py:278
↓ 3 callersMethodl2_norm
(self, x)
LP/benchmark/methods/baseline/GNN.py:75
↓ 3 callersFunctionload_data
(prefix='DBLP')
NC/benchmark/methods/baseline/utils/data.py:7
↓ 3 callersFunctionload_data
(prefix='DBLP')
TC/HGAT/model/code/baseline/utils/data.py:7
↓ 3 callersFunctionmakedirs
(path)
NC/benchmark/methods/RSHN/torch_geometric/data/makedirs.py:6
↓ 3 callersFunctionmakedirs
(path)
NC/RSHN/torch_geometric/data/makedirs.py:6
↓ 3 callersFunctionmakedirs
(dirs: list)
TC/HGAT/model/code/utils.py:248
↓ 3 callersFunctionmaybe_log
(path, log=True)
NC/benchmark/methods/RSHN/torch_geometric/data/extract.py:10
↓ 3 callersFunctionmaybe_log
(path, log=True)
NC/RSHN/torch_geometric/data/extract.py:10
↓ 3 callersMethodnode_neigh_agg
(self, id_batch, node_type)
NC/HetGNN/code/tools.py:115
↓ 3 callersMethodnode_neigh_agg
(self, id_batch, node_type)
LP/HetGNN/code/tools.py:115
↓ 3 callersFunctionparse_minibatch
(adjlists, edge_metapath_indices_list, idx_batch, device, samples=None)
NC/MAGNN/utils/tools.py:104
↓ 3 callersFunctionparse_minibatch
(adjlists, edge_metapath_indices_list, idx_batch, device, samples=None)
LP/benchmark/methods/MAGNN/utils/tools.py:104
↓ 3 callersFunctionparse_minibatch
(adjlists, edge_metapath_indices_list, idx_batch, device, samples=None)
LP/benchmark/methods/MAGNN_ini/utils/tools.py:104
↓ 3 callersFunctionsample
(datapath, DATASETS, resample = False, trainNumPerClass=20)
TC/HGAT/utils.py:10
↓ 3 callersFunctionsample_mask
Create mask.
NC/benchmark/methods/HetSANN/HetSANN_MRV/utils/process.py:49
↓ 3 callersMethodstep
(self, loss, acc, model)
NC/HetGNN/code/homoGNN.py:28
↓ 3 callersFunctiontest
(model, data, test_mask, labels)
NC/HetGNN/code/homoGNN.py:342
↓ 3 callersFunctiontest
(sess, model, users_to_test, drop_flag=False, batch_test_flag=False)
Recom/KGAT/Model/utility/batch_test.py:148
↓ 3 callersFunctionuniform
(size, tensor)
NC/benchmark/methods/RSHN/torch_geometric/nn/inits.py:4
↓ 3 callersFunctionuniform
(size, tensor)
NC/RSHN/torch_geometric/nn/inits.py:4
↓ 2 callersMethod__init__
(self, in_dim, num_hidden, num_classes, nu
NC/RGCN/model.py:9
↓ 2 callersMethod__init__
(self, num_edge, num_channels, w_in, w_out, num_class, num_nodes, num_layers)
NC/benchmark/methods/GTN/model_sparse.py:18
↓ 2 callersMethod__init__
(self, num_edge, num_channels, w_ins, w_out, num_class,num_layers,norm)
NC/benchmark/methods/GTN/model.py:12
↓ 2 callersMethod__init__
(self, meta_paths, in_size, hidden_size, out_size, num_heads, dropout)
NC/HAN/model_hetero.py:91
↓ 2 callersMethod__init__
(self, num_meta_paths, in_size, hidden_size, out_size, num_heads, dropout)
NC/HAN/model.py:69
↓ 2 callersMethod__init__
(self, num_edge, num_channels, w_in, w_out, num_class, num_nodes, num_layers)
NC/GTN/model_sparse.py:18
↓ 2 callersMethod__init__
(self, num_edge, num_channels, w_in, w_out, num_class,num_layers,norm)
NC/GTN/model.py:12
↓ 2 callersMethod__init__
(self, g, num_layers, in_dim, num_hidden,
LP/MAGNN/GNN.py:11
↓ 2 callersMethod__init__
(self)
LP/benchmark/methods/baseline/GNN.py:23
↓ 2 callersMethod__init__
(self, in_feats, hid_feats, out_feats, n_layers=2, dropout=0.5)
LP/GATNE/src/homGNN.py:138
↓ 2 callersMethod_call
(self, inputs)
Recom/KGCN/src/gcn/layers.py:35
↓ 2 callersFunction_get_tensors
()
NC/benchmark/methods/HGT/gpu_memory_log.py:22
↓ 2 callersMethod_load_ratings
(self, file_name)
Recom/baseline/Model/utility/load_data.py:42
↓ 2 callersMethod_load_ratings
(self, file_name)
Recom/KGAT/Model/utility/load_data.py:42
↓ 2 callersFunction_reset
(item)
NC/benchmark/methods/RSHN/torch_geometric/nn/inits.py:27
↓ 2 callersFunction_reset
(item)
NC/benchmark/methods/GTN/inits.py:33
↓ 2 callersFunction_reset
(item)
NC/RSHN/torch_geometric/nn/inits.py:27
↓ 2 callersFunction_reset
(item)
NC/GTN/inits.py:33
↓ 2 callersMethoda_content_agg
(self, id_batch)
NC/HetGNN/code/tools.py:60
↓ 2 callersMethoda_content_agg
(self, id_batch)
NC/benchmark/methods/HetGNN/code/DBLP/tools.py:70
↓ 2 callersMethoda_content_agg
(self, id_batch)
LP/HetGNN/code/tools.py:60
↓ 2 callersFunctionadd_self_loops
(edge_index, num_nodes=None)
NC/benchmark/methods/RSHN/torch_geometric/utils/loop.py:22
↓ 2 callersFunctionadd_self_loops
(edge_index, num_nodes=None)
NC/RSHN/torch_geometric/utils/loop.py:22
↓ 2 callersFunctionauc
(ground_truth, prediction)
Recom/KGAT/Model/utility/metrics.py:99
↓ 2 callersFunctionbuild_graph_from_triplets
Create a DGL graph. The graph is bidirectional because RGCN authors use reversed relations. This function also generates edge type an
LP/RGCN/utils.py:139
↓ 2 callersMethodcollate
(self, data_list)
NC/benchmark/methods/RSHN/torch_geometric/data/in_memory_dataset.py:80
↓ 2 callersMethodcollate
(self, data_list)
NC/RSHN/torch_geometric/data/in_memory_dataset.py:80
↓ 2 callersMethodconteng_agg
(self, id_batch, node_type)
NC/benchmark/methods/HetGNN/code/ACM/tools.py:66
↓ 2 callersMethodconteng_agg
(self, id_batch, node_type)
NC/benchmark/methods/HetGNN/code/IMDB/tools.py:66
↓ 2 callersMethodconteng_agg
(self, id_batch, node_type)
LP/benchmark/methods/HetGNN/tools.py:65
↓ 2 callersFunctiondcg_at_k
Score is discounted cumulative gain (dcg) Relevance is positive real values. Can use binary as the previous methods. Returns: Dis
Recom/baseline/Model/utility/metrics.py:43
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