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Functions2,023 in github.com/THUDM/HGB

⨍ Functions 2,023◇ Types & classes 293
↓ 379 callersMethodwrite
(self, message)
TC/HGAT/model/code/print_log.py:12
↓ 304 callersMethodto
(self, device, *keys)
NC/RSHN/torch_geometric/data/data.py:116
↓ 259 callersMethodsplit
(self, index)
NC/RSHN/torch_geometric/data/in_memory_dataset.py:74
↓ 169 callersMethodkeys
(self)
NC/RSHN/torch_geometric/data/data.py:39
↓ 155 callersMethodto
(self, device, *keys)
NC/benchmark/methods/RSHN/torch_geometric/data/data.py:116
↓ 105 callersMethodeval
(self, sess, feed_dict)
Recom/KGAT/Model/CKE.py:178
↓ 97 callersMethodtrain
(self, sess, feed_dict)
Recom/KGAT/Model/CKE.py:175
↓ 86 callersMethodcuda
(self, *keys)
NC/RSHN/torch_geometric/data/data.py:124
↓ 78 callersMethodsplit
(self, index)
NC/benchmark/methods/RSHN/torch_geometric/data/in_memory_dataset.py:74
↓ 46 callersMethodkeys
(self)
NC/benchmark/methods/RSHN/torch_geometric/data/data.py:39
↓ 46 callersMethodshuffle
(self)
NC/RSHN/torch_geometric/data/in_memory_dataset.py:60
↓ 36 callersFunctionearly_stopping
(log_value, best_value, stopping_step, expected_order='acc', flag_step=100)
Recom/KGAT/Model/utility/helper.py:38
↓ 34 callersFunctionf1_score
r"""Computes the :math:`F_1` score: :math:`2 \cdot \frac{\mathrm{precision} \cdot \mathrm{recall}} {\mathrm{precision}+\mathrm{recall}}`.
NC/GTN/utils.py:133
↓ 33 callersFunctionmodel
(cluster_id_num)
NC/HetGNN/code/node_clustering_model.py:25
↓ 33 callersMethodnode_het_agg
(self, id_batch, node_type)
NC/HetGNN/code/tools.py:141
↓ 33 callersMethodnode_het_agg
(self, id_batch, node_type)
LP/HetGNN/code/tools.py:141
↓ 31 callersFunctioninitializer
(init_G, init_node_type)
LP/GATNE/src/walk.py:28
↓ 28 callersMethodupdate
(self, aggr_out)
NC/GTN/gcn.py:108
↓ 27 callersMethodget
(self, idx)
NC/RSHN/torch_geometric/data/dataset.py:42
↓ 26 callersMethodstep
(self, loss, acc, model)
NC/benchmark/methods/HAN/utils.py:362
↓ 25 callersMethodupdate
(self, aggr_out)
NC/benchmark/methods/GTN/gcn.py:108
↓ 23 callersFunctionf1_score
r"""Computes the :math:`F_1` score: :math:`2 \cdot \frac{\mathrm{precision} \cdot \mathrm{recall}} {\mathrm{precision}+\mathrm{recall}}`.
NC/benchmark/methods/GTN/utils.py:133
↓ 21 callersMethodevaluate
:param edge_list: shape(2, edge_num) :param confidence: shape(edge_num,) :param labels: shape(edge_num,) :return: dic
LP/benchmark/methods/HGT/data_loader.py:208
↓ 21 callersFunctionget_adjlist_pkl
(dl, meta, type_id=0, return_dic=True, symmetric=False, return_tmp=False)
LP/benchmark/methods/MAGNN/utils/data.py:35
↓ 18 callersMethodstep
(self, loss, acc, model)
NC/HAN/utils.py:242
↓ 17 callersMethodshuffle
(self)
NC/benchmark/methods/RSHN/torch_geometric/data/in_memory_dataset.py:60
↓ 16 callersFunctionget_adjlist_pkl
(dl, meta, type_id=0, return_dic=True, symmetric=False)
NC/benchmark/methods/MAGNN/utils/data.py:35
↓ 15 callersFunctionLOSS
(x, y)
NC/benchmark/methods/RSHN/RSHN.py:274
↓ 15 callersMethodstep
(self, loss, model)
LP/benchmark/methods/GNN/utils.py:127
↓ 14 callersMethodevaluate
(self, pred)
NC/benchmark/methods/HGT/data_loader.py:133
↓ 13 callersMethodnum_iterations
(self)
NC/benchmark/methods/MAGNN/utils/tools.py:232
↓ 12 callersFunctionmodel
(cluster_id_num)
LP/HetGNN/code/node_clustering_model.py:25
↓ 12 callersMethodnext
(self)
NC/benchmark/methods/MAGNN/utils/tools.py:226
↓ 12 callersMethodnorm
(self, H, add=False)
NC/GTN/model.py:52
↓ 12 callersMethodstep
(self, auc, model)
LP/GATNE/src/homGNN.py:84
↓ 11 callersMethodnode_het_agg
(self, id_batch, node_type)
NC/benchmark/methods/HetGNN/code/DBLP/tools.py:148
↓ 11 callersMethodnum_iterations
(self)
LP/MAGNN/utils/tools.py:233
↓ 10 callersFunctionf1_score
(pred, target, num_classes)
NC/benchmark/methods/RSHN/torch_geometric/utils/metric.py:62
↓ 10 callersMethodget_test_neigh
(self)
LP/benchmark/methods/HGT/data_loader.py:313
↓ 10 callersFunctionmaybe_num_nodes
(edge_index, num_nodes=None)
NC/benchmark/methods/RSHN/torch_geometric/utils/num_nodes.py:1
↓ 10 callersFunctionmaybe_num_nodes
(edge_index, num_nodes=None)
NC/RSHN/torch_geometric/utils/num_nodes.py:1
↓ 10 callersFunctionmodel
()
NC/benchmark/methods/HetGNN/code/ACM/do_class.py:62
↓ 9 callersFunction_write_log
(f, write_str)
NC/benchmark/methods/HGT/gpu_memory_log.py:31
↓ 9 callersMethoddecode
(self, x, edge_index)
LP/GATNE/src/homGNN.py:162
↓ 9 callersMethodget_test_neigh_w_random
(self)
LP/benchmark/methods/HGT/data_loader.py:384
↓ 9 callersFunctionparse_minibatch
(adjlists, edge_metapath_indices_list, idx_batch, device, samples=None)
NC/benchmark/methods/MAGNN/utils/tools.py:104
↓ 8 callersMethoddecode
(self, x, edge_index)
LP/GATNE/src/homGNN.py:213
↓ 8 callersMethodget
(self, idx)
NC/benchmark/methods/RSHN/torch_geometric/data/dataset.py:42
↓ 8 callersMethodnum_iterations
(self)
LP/benchmark/methods/MAGNN_ini/utils/tools.py:232
↓ 8 callersFunctionwrite_link
(A, fr, to, name, type_id)
NC/GTN/get_acm_data.py:115
↓ 7 callersMethodevaluate
:param edge_list: shape(2, edge_num) :param confidence: shape(edge_num,) :param labels: shape(edge_num,) :return: dic
LP/benchmark/scripts/LP_AUC_MRR.py:71
↓ 7 callersMethodget_train_neg
(self, edge_types=[])
LP/benchmark/methods/HGT/data_loader.py:282
↓ 7 callersMethodget_valid_neg
(self, edge_types=[])
LP/benchmark/methods/HGT/data_loader.py:296
↓ 7 callersMethodnext
(self)
LP/benchmark/methods/MAGNN_ini/utils/tools.py:226
↓ 7 callersMethodnum_iterations
(self)
NC/MAGNN/utils/tools.py:232
↓ 7 callersMethodnum_iterations
(self)
LP/benchmark/methods/MAGNN/utils/tools.py:232
↓ 7 callersFunctionparse_minibatch_LastFM
(adjlists_ua, edge_metapath_indices_list_ua, user_artist_batch, device, samples=None, use_masks=None, offset=N
LP/benchmark/methods/MAGNN_ini/utils/tools.py:184
↓ 6 callersMethodcat_dim
(self, key, item)
NC/benchmark/methods/RSHN/torch_geometric/data/data.py:61
↓ 6 callersMethodcat_dim
(self, key, item)
NC/RSHN/torch_geometric/data/data.py:61
↓ 6 callersMethodencode
(self, data)
LP/RGCN/GNN.py:91
↓ 6 callersMethodforward
(self, A, X, target_x, target)
NC/benchmark/methods/GTN/model.py:68
↓ 6 callersMethodforward
(self, inputs)
NC/GTN/GNN.py:43
↓ 6 callersFunctionget_binary_mask
(total_size, indices)
NC/HAN/utils.py:114
↓ 6 callersMethodget_initializer
()
Recom/KGNN-LS/src/model.py:40
↓ 6 callersMethodget_sub_graph
node_types_tokeep is a list or set of node types that you want to keep in the sub-graph We only support whole type sub-graph for now.
NC/benchmark/methods/HGT/data_loader.py:15
↓ 6 callersMethodget_train_valid_pos
(self, train_ratio=0.9)
LP/benchmark/methods/HGT/data_loader.py:24
↓ 6 callersMethodnext
(self)
NC/MAGNN/utils/tools.py:226
↓ 6 callersMethodnext
(self)
LP/MAGNN/utils/tools.py:227
↓ 6 callersMethodnext
(self)
LP/benchmark/methods/MAGNN/utils/tools.py:226
↓ 6 callersFunctionparse_minibatch_LastFM
(adjlists_ua, edge_metapath_indices_list_ua, user_artist_batch, device, samples=None, use_masks=None, offset=N
NC/MAGNN/utils/tools.py:184
↓ 6 callersFunctionparse_minibatch_LastFM
(adjlists_ua, edge_metapath_indices_list_ua, user_artist_batch, device, samples=None, use_masks=None, offset=N
NC/benchmark/methods/MAGNN/utils/tools.py:184
↓ 6 callersFunctionparse_minibatch_LastFM
(adjlists_ua, edge_metapath_indices_list_ua, user_artist_batch, device, samples=None, use_masks=None, offset=N
LP/MAGNN/utils/tools.py:184
↓ 6 callersFunctionremove_self_loops
(edge_index, edge_attr=None)
NC/RSHN/torch_geometric/utils/loop.py:12
↓ 6 callersFunctiontest_func
(test_user_artist)
LP/benchmark/methods/MAGNN_ini/test_LastFM.py:54
↓ 5 callersMethod__init__
(self)
LP/RGCN-WN18/code/model.py:122
↓ 5 callersMethod__init__
(self, in_features, idx, hidden_dim)
TC/HGAT/model/code/layers.py:106
↓ 5 callersMethodencode
(self, data)
LP/GATNE/src/homGNN.py:153
↓ 5 callersFunctionensureDir
(dir_path)
Recom/KGAT/Model/utility/helper.py:15
↓ 5 callersFunctionevaluate
(preds_list, y_list)
TC/HGAT/model/code/train.py:113
↓ 5 callersFunctionload_data
(prefix='DBLP')
LP/RGCN-WN18/code/utils.py:58
↓ 5 callersMethodnorm
(self, H, add=False)
NC/benchmark/methods/GTN/model.py:54
↓ 5 callersFunctionparse_minibatch_LastFM
(adjlists_ua, edge_metapath_indices_list_ua, user_artist_batch, device, samples=None, use_masks=None, offset=N
LP/benchmark/methods/MAGNN/utils/tools.py:184
↓ 4 callersMethod__init__
(self)
LP/RGCN/GNN.py:25
↓ 4 callersMethod__init__
(self, in_feats, hid_feats, n_layers=2, dropout=0.5, rel_num=1)
LP/RGCN/model.py:28
↓ 4 callersMethod__init__
(self, batch_size, dim, dropout, act, name)
Recom/KGNN-LS/src/aggregators.py:17
↓ 4 callersMethod_generate_train_cf_batch
(self)
Recom/KGAT/Model/utility/load_data.py:101
↓ 4 callersMethod_split_A_hat
(self, X)
Recom/KGAT/Model/KGAT.py:440
↓ 4 callersMethodencode
(self, g, x)
LP/RGCN-WN18/code/model.py:194
↓ 4 callersMethodencode
(self, data)
LP/benchmark/methods/GNN/GNN.py:54
↓ 4 callersFunctionevaluate
(model, true_edges, false_edges)
LP/GATNE/src/utils.py:261
↓ 4 callersFunctionevaluate
(preds_list, y_list)
TC/HGAT/model/code/base.py:111
↓ 4 callersMethodevaluate
:param edge_list: shape(2, edge_num) :param confidence: shape(edge_num,) :param labels: shape(edge_num,) :return: dic
LP/RGCN-WN18/code/scripts/data_loader.py:187
↓ 4 callersMethodgen_file_for_evaluate
(self, test_idx, label, file_name, mode='bi')
NC/benchmark/scripts/data_loader.py:165
↓ 4 callersMethodget_node_type
(self, node_id)
LP/RGCN-WN18/code/scripts/data_loader.py:218
↓ 4 callersFunctionload_testing_data
(f_name)
LP/GATNE/src/utils.py:103
↓ 4 callersMethodloss
(logits, labels, nb_classes, class_weights)
NC/benchmark/methods/HetSANN/HetSANN_MRV/models/base_gattn.py:7
↓ 4 callersMethodnode_het_agg
(self, id_batch, node_type)
NC/benchmark/methods/HetGNN/code/ACM/tools.py:86
↓ 4 callersMethodnode_het_agg
(self, id_batch, node_type)
NC/benchmark/methods/HetGNN/code/IMDB/tools.py:86
↓ 4 callersMethodnode_het_agg
(self, id_batch, node_type)
LP/benchmark/methods/HetGNN/tools.py:89
↓ 4 callersMethodnode_neigh_agg
(self, id_batch, node_type)
NC/benchmark/methods/HetGNN/code/DBLP/tools.py:119
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