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Functions2,023 in github.com/THUDM/HGB

⨍ Functions 2,023◇ Types & classes 293
↓ 1 callersMethodaggregate
(self, entities, relations)
Recom/KGNN-LS/src/model.py:286
↓ 1 callersMethodaggregate_all
(self, triple_list_batch, triple_index)
NC/HetGNN/code/tools.py:302
↓ 1 callersMethodaggregate_all
(self, triple_list_batch, triple_index)
NC/benchmark/methods/HetGNN/code/DBLP/tools.py:307
↓ 1 callersMethodaggregate_all
(self, triple_list_batch, triple_pair)
NC/benchmark/methods/HetGNN/code/ACM/tools.py:158
↓ 1 callersMethodaggregate_all
(self, triple_list_batch, triple_pair)
NC/benchmark/methods/HetGNN/code/IMDB/tools.py:160
↓ 1 callersMethodaggregate_all
(self, triple_list_batch, triple_index)
LP/HetGNN/code/tools.py:302
↓ 1 callersMethodaggregate_all
(self, triple_list_batch, triple_pair)
LP/benchmark/methods/HetGNN/tools.py:161
↓ 1 callersFunctionaverage_precision
Score is average precision (area under PR curve) Relevance is binary (nonzero is relevant). Returns: Average precision
Recom/baseline/Model/utility/metrics.py:21
↓ 1 callersFunctionaverage_precision
Score is average precision (area under PR curve) Relevance is binary (nonzero is relevant). Returns: Average precision
Recom/KGAT/Model/utility/metrics.py:21
↓ 1 callersFunctionbaseline_model
(input_adj_train, input_features_train, input_adj_val, input_features_val)
TC/HGAT/model/code/train.py:272
↓ 1 callersFunctionbaseline_model
(hg, args, edge_type_count, feature_dims)
TC/HGAT/model/code/base.py:274
↓ 1 callersFunctionbuild_entity_feature_with_description
(datapath, stopwords=list())
TC/HGAT/build_features.py:27
↓ 1 callersMethodbuild_hidden_layer
(self, idx)
NC/RGCN/model.py:131
↓ 1 callersMethodbuild_hidden_layer
(self, idx)
NC/benchmark/methods/RGCN/model.py:41
↓ 1 callersMethodbuild_hidden_layer
(self, idx)
LP/RGCN/model.py:132
↓ 1 callersMethodbuild_hidden_layer
(self, idx)
LP/RGCN-WN18/code/model.py:40
↓ 1 callersMethodbuild_hidden_layer
(self, idx)
LP/benchmark/methods/RGCN/model.py:40
↓ 1 callersMethodbuild_input_layer
(self)
NC/RGCN/model.py:128
↓ 1 callersMethodbuild_input_layer
(self)
NC/benchmark/methods/RGCN/model.py:38
↓ 1 callersMethodbuild_input_layer
(self)
LP/RGCN/model.py:129
↓ 1 callersMethodbuild_input_layer
(self)
LP/RGCN-WN18/code/model.py:37
↓ 1 callersMethodbuild_input_layer
(self)
LP/benchmark/methods/RGCN/model.py:37
↓ 1 callersMethodbuild_model
(self)
NC/RGCN/model.py:113
↓ 1 callersMethodbuild_model
(self)
NC/benchmark/methods/RGCN/model.py:25
↓ 1 callersMethodbuild_model
(self)
LP/RGCN/model.py:114
↓ 1 callersMethodbuild_model
(self)
LP/RGCN-WN18/code/model.py:24
↓ 1 callersMethodbuild_model
(self)
LP/benchmark/methods/RGCN/model.py:24
↓ 1 callersMethodbuild_output_layer
(self)
NC/RGCN/model.py:134
↓ 1 callersMethodbuild_output_layer
(self)
NC/benchmark/methods/RGCN/model.py:44
↓ 1 callersMethodbuild_output_layer
(self)
LP/RGCN/model.py:135
↓ 1 callersMethodbuild_output_layer
(self)
LP/RGCN-WN18/code/model.py:43
↓ 1 callersMethodbuild_output_layer
(self)
LP/benchmark/methods/RGCN/model.py:43
↓ 1 callersFunctionbuild_relation_adj
build a AIFB-relation graph adjacency based on random walk from the original graph
NC/benchmark/methods/RSHN/build_coarsened_line_graph/relation_graph.py:8
↓ 1 callersFunctionbuild_relation_adj
build a AIFB-relation graph adjacency based on random walk from the original graph
NC/RSHN/build_coarsened_line_graph/relation_graph.py:8
↓ 1 callersFunctionbuild_text_feature
(datapath, DATASETS, rho=0.3, lp=0.5, stopwords=list())
TC/HGAT/build_features.py:71
↓ 1 callersFunctionbuild_topic_feature_sklearn
(datapath, DATASETS, TopicNum=20, stopwords=list(), train=False)
TC/HGAT/build_features.py:151
↓ 1 callersFunctionbuild_x
()
NC/RSHN/model/RSHN.py:37
↓ 1 callersFunctionbuild_x
()
NC/RSHN/model/RSHN_gnn.py:44
↓ 1 callersFunctioncalc_filtered_mrr
(embedding, w, train_triplets, valid_triplets, test_triplets, hits=[])
LP/RGCN/utils.py:326
↓ 1 callersFunctioncalc_raw_mrr
(embedding, w, test_triplets, hits=[], eval_bz=100)
LP/RGCN/utils.py:218
↓ 1 callersMethodcalc_score
(self, embedding, triplets)
LP/RGCN/link_predict.py:59
↓ 1 callersMethodcalc_score
(self, embedding, triplets)
LP/RGCN-WN18/code/model.py:78
↓ 1 callersFunctionchange_to_homo
(input_adj_train, input_features_train, input_adj_val, input_features_val)
TC/HGAT/model/code/train.py:230
↓ 1 callersFunctionchange_to_homo
(input_adj_train, input_features_train)
TC/HGAT/model/code/base.py:238
↓ 1 callersFunctioncomp_deg_norm
(g)
LP/RGCN/utils.py:131
↓ 1 callersMethodcompute_sample_p
(self)
NC/HetGNN/code/data_generator.py:394
↓ 1 callersMethodcompute_sample_p
(self)
NC/benchmark/methods/HetGNN/code/DBLP/data_generator.py:217
↓ 1 callersMethodcompute_sample_p
(self)
NC/benchmark/methods/HetGNN/code/ACM/data_generator.py:133
↓ 1 callersMethodcompute_sample_p
(self)
NC/benchmark/methods/HetGNN/code/IMDB/data_generator.py:150
↓ 1 callersMethodcompute_sample_p
(self)
LP/HetGNN/code/data_generator.py:394
↓ 1 callersMethodcompute_sample_p
(self)
LP/benchmark/methods/HetGNN/data_generator.py:147
↓ 1 callersFunctionconstruct_adj
(args, kg, entity_num)
Recom/KGCN/src/data_loader.py:90
↓ 1 callersFunctionconstruct_adj
(args, kg, entity_num)
Recom/KGNN-LS/src/data_loader.py:88
↓ 1 callersFunctionconstruct_kg
(kg_np)
Recom/KGCN/src/data_loader.py:73
↓ 1 callersFunctionconstruct_kg
(kg_np)
Recom/KGNN-LS/src/data_loader.py:71
↓ 1 callersFunctioncontains_isolated_nodes
(edge_index, num_nodes=None)
NC/benchmark/methods/RSHN/torch_geometric/utils/isolated.py:7
↓ 1 callersFunctioncontains_isolated_nodes
(edge_index, num_nodes=None)
NC/RSHN/torch_geometric/utils/isolated.py:7
↓ 1 callersFunctioncontains_self_loops
(edge_index)
NC/benchmark/methods/RSHN/torch_geometric/utils/loop.py:6
↓ 1 callersFunctioncontains_self_loops
(edge_index)
NC/RSHN/torch_geometric/utils/loop.py:6
↓ 1 callersFunctionconvert_kg
()
Recom/KGCN/src/preprocess.py:75
↓ 1 callersFunctionconvert_kg
()
Recom/KGNN-LS/src/preprocess.py:75
↓ 1 callersFunctionconvert_rating
()
Recom/KGCN/src/preprocess.py:21
↓ 1 callersFunctionconvert_rating
()
Recom/KGNN-LS/src/preprocess.py:21
↓ 1 callersMethodcreate_sparsity_split
(self)
Recom/baseline/Model/utility/load_data.py:158
↓ 1 callersMethodcreate_sparsity_split
(self)
Recom/KGAT/Model/utility/load_data.py:162
↓ 1 callersFunctiondataset_split
(rating_np, args)
Recom/KGCN/src/data_loader.py:31
↓ 1 callersFunctiondataset_split
(rating_np, args)
Recom/KGNN-LS/src/data_loader.py:31
↓ 1 callersMethodde_dismult
(self, x, edge_index)
LP/GATNE/src/homGNN.py:171
↓ 1 callersMethodde_dismult
(self, x, edge_index)
LP/GATNE/src/homGNN.py:222
↓ 1 callersFunctiondegree
Computes the degree of a given index tensor. Args: index (LongTensor): Source or target indices of edges. num_nodes (int, optiona
NC/benchmark/methods/RSHN/torch_geometric/utils/degree.py:6
↓ 1 callersFunctiondegree
Computes the degree of a given index tensor. Args: index (LongTensor): Source or target indices of edges. num_nodes (int, optiona
NC/RSHN/torch_geometric/utils/degree.py:6
↓ 1 callersMethoddownload
(self)
NC/benchmark/methods/RSHN/torch_geometric/data/dataset.py:30
↓ 1 callersMethoddownload
(self)
NC/RSHN/torch_geometric/data/dataset.py:30
↓ 1 callersFunctiondownload_and_extract
(path)
NC/benchmark/scripts/data_loader.py:15
↓ 1 callersFunctiondownload_and_extract
(path)
LP/benchmark/scripts/data_loader.py:15
↓ 1 callersFunctiondownload_url
(url, folder, log=True)
NC/benchmark/methods/RSHN/torch_geometric/data/download.py:9
↓ 1 callersFunctiondownload_url
(url, folder, log=True)
NC/RSHN/torch_geometric/data/download.py:9
↓ 1 callersFunctionearly_stopping
(log_value, best_value, stopping_step, expected_order='acc', flag_step=100)
Recom/baseline/Model/utility/helper.py:38
↓ 1 callersMethodedge_softmax
(self, g)
NC/MAGNN/model/base_MAGNN.py:66
↓ 1 callersMethodedge_softmax
(self, g)
NC/benchmark/methods/MAGNN/model/base_MAGNN.py:66
↓ 1 callersMethodedge_softmax
(self, g)
LP/MAGNN/model/base_MAGNN.py:66
↓ 1 callersMethodedge_softmax
(self, g)
LP/benchmark/methods/MAGNN/model/base_MAGNN.py:66
↓ 1 callersMethodedge_softmax
(self, g)
LP/benchmark/methods/MAGNN_ini/model/base_MAGNN.py:66
↓ 1 callersFunctionencode_onehot
(labels)
TC/HGAT/model/code/utils.py:140
↓ 1 callersMethodeval
(self, sess, feed_dict)
Recom/KGCN/src/model.py:194
↓ 1 callersMethodeval
(self, sess, feed_dict)
Recom/KGNN-LS/src/model.py:192
↓ 1 callersMethodevaluate
(self, pred)
NC/benchmark/scripts/data_loader.py:182
↓ 1 callersMethodevaluate_AUC_MRR
(self)
LP/benchmark/scripts/LP_AUC_MRR.py:49
↓ 1 callersMethodevaluate_F1
(self,pred_label)
NC/benchmark/scripts/NC_F1.py:57
↓ 1 callersFunctionevaluate_results_nc
(embeddings, labels, num_classes)
NC/benchmark/methods/MAGNN/utils/tools.py:51
↓ 1 callersFunctionextract_tar
(path, folder, mode='r:gz', log=True)
NC/benchmark/methods/RSHN/torch_geometric/data/extract.py:15
↓ 1 callersFunctionextract_tar
(path, folder, mode='r:gz', log=True)
NC/RSHN/torch_geometric/data/extract.py:15
↓ 1 callersFunctionextract_zip
(zip_path, extract_path)
NC/benchmark/scripts/NC_F1.py:87
↓ 1 callersFunctionextract_zip
(zip_path, extract_path)
LP/benchmark/scripts/LP_AUC_MRR.py:115
↓ 1 callersFunctionfalse_negative
(pred, target, num_classes)
NC/benchmark/methods/RSHN/torch_geometric/utils/metric.py:34
↓ 1 callersFunctionfalse_negative
r"""Computes the number of false negative predictions. Args: pred (Tensor): The predictions. target (Tensor): The targets.
NC/benchmark/methods/GTN/utils.py:73
↓ 1 callersFunctionfalse_negative
(pred, target, num_classes)
NC/RSHN/torch_geometric/utils/metric.py:34
↓ 1 callersFunctionfalse_negative
r"""Computes the number of false negative predictions. Args: pred (Tensor): The predictions. target (Tensor): The targets.
NC/GTN/utils.py:73
↓ 1 callersFunctionfalse_positive
(pred, target, num_classes)
NC/benchmark/methods/RSHN/torch_geometric/utils/metric.py:26
↓ 1 callersFunctionfalse_positive
r"""Computes the number of false positive predictions. Args: pred (Tensor): The predictions. target (Tensor): The targets.
NC/benchmark/methods/GTN/utils.py:55
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