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Functions241 in github.com/JhuoW/ERIC

⨍ Functions 241◇ Types & classes 32

↓ 1 callersMethodinit_parameters

Initializing weights.

model/layers.py:75

↓ 1 callersMethodinit_parameters

model/layers.py:134

↓ 1 callersMethodinit_parameters

model/layers.py:185

↓ 1 callersMethodinput_dim

DataHelper/simgnn_utils.py:150

↓ 1 callersFunctionlast_len

length of last line

utils/logger.py:20

↓ 1 callersFunctionlen_ignore_n

len(s) ignoring \\n

utils/logger.py:9

↓ 1 callersFunctionload

DataHelper/simgnn_utils.py:266

↓ 1 callersMethodload_custom_data

(self, config, args)

DataHelper/DatasetLocal.py:132

↓ 1 callersFunctionload_model_all

(dataset, model, loss_func, model_paths, T)

utils/utils.py:308

↓ 1 callersFunctionlog_sum_exp

Log sum exp function Args: x: Input. axis: Axis over which to perform sum. Returns: torch.Tensor: log sum exp

utils/misc.py:8

↓ 1 callersMethodm_n

DataHelper/simgnn_utils.py:371

↓ 1 callersFunctionmain

(args, config, logger: Logger, run_id: int, dataset: DatasetLocal)

↓ 1 callersFunctionmy_clock

basically time.clock()

utils/logger.py:5

↓ 1 callersFunctionplot_embeddings_for_each_query

(embs, ids, plt_cnt,ground_truth_nged, sort_id_mat_normed, extra_dir, plot_

↓ 1 callersMethodpre_process

(self , content)

utils/logger.py:63

↓ 1 callersFunctionprint_config

utils/utils.py:118

↓ 1 callersFunctionprint_evaluation

Printing the error rates.

↓ 1 callersFunctionprint_evaluation

Printing the error rates.

test_linux.py:112

↓ 1 callersFunctionprint_evaluation

Printing the error rates.

test_imdb.py:113

↓ 1 callersFunctionranking

(qid, gid, sort_id_mat_normed, ground_truth_nged, one_based=True)

↓ 1 callersMethodranking

:param qid: query id (0-indexed). :param gid: database graph id (0-indexed) (NOT g.graph['gid']). :param norm: :param

DataHelper/simgnn_utils.py:432

↓ 1 callersFunctionsave_best_val_model

(config, dataset_name, model, PATH_MODEL)

utils/utils.py:240

↓ 1 callersFunctionsave_best_val_model_all

current_metric: [rho, tau, p10, p20]

utils/utils.py:269

↓ 1 callersFunctionsave_model

(config, dataset_name, model)

utils/utils.py:223

↓ 1 callersFunctionsave_pkl

DataHelper/simgnn_utils.py:323

↓ 1 callersMethodscale_init

model/GSC.py:139

↓ 1 callersFunctionset_random_seed

utils/random_seeder.py:5

↓ 1 callersFunctionset_save_paths_for_vis

(info_dict, extra_dir, fn, plt_cnt)

↓ 1 callersMethodsetup_layers

Creating the layers.

model/SImGNN.py:35

↓ 1 callersMethodsetup_layers

model/GSC.py:26

↓ 1 callersMethodsetup_layers

model/Base/GSC_custom.py:18

↓ 1 callersMethodsetup_score_layer

model/GSC.py:117

↓ 1 callersMethodsetup_score_layer

model/Base/GSC_custom.py:100

↓ 1 callersMethodsetup_weights

Defining weights.

model/layers.py:67

↓ 1 callersMethodsetup_weights

model/layers.py:115

↓ 1 callersMethodsetup_weights

model/layers.py:173

↓ 1 callersFunctionsorted_nicely

DataHelper/simgnn_utils.py:225

↓ 1 callersFunctiontry_int

DataHelper/simgnn_utils.py:226

↓ 1 callersFunctionunnormalized_dist_sim

↓ 1 callersFunctionvis_small

(q=None, gs=None, info_dict=None, types = None)

utils/vis.py:35

(self , mode = [print] , log_path = None , append = ["clock"] , line_length = 90)

utils/logger.py:29

(self, args, config, logger)

training_procedure/__init__.py:11

(self, nfeat, nhid, nclass, num_layers = 2 ,use_bn=True)

model/layers.py:9

(self, n_in, n_hid, n_out, num_layers = 2 ,use_bn=True, act = 'relu')

model/layers.py:32

:param args: Arguments object.

model/layers.py:58

:param args: Arguments object.

model/layers.py:105

(self, config, filters)

model/layers.py:165

:param args: Arguments object. :param number_of_labels: Number of node labels.

model/SImGNN.py:16

(self, n_in, n_hid, n_out, num_layers = 2 ,use_bn=True)

model/MLP.py:31

(self, config, embedding_dim)

model/GSC.py:269

(self,config, hid_channels, in_channels, out_channels)

model/Base/GAT.py:6

(self, config, in_dim)

model/Base/GSC_custom.py:195

(self,config, hidden_channels, num_features, num_classes)

model/Base/GCN.py:12

(self, dName=None, dDescription=None)

DataHelper/DatasetLocal.py:21

(self, dName=None, dDescription=None)

DataHelper/dataset_helper.py:23

DataHelper/simgnn_utils.py:17

(self, save_folder, train_or_test)

DataHelper/simgnn_utils.py:54

(self, save_folder, train_or_test)

DataHelper/simgnn_utils.py:87

(self, data_save_folder, data_set_name, validation_ratio, node_feat_name, node_encoder_name)

DataHelper/simgnn_utils.py:114

(self, gs, node_feat_name)

DataHelper/simgnn_utils.py:187

(self, _, node_feat_name=None, node_encoder_name='constant_1_2')

DataHelper/simgnn_utils.py:210

(self, root_folder, data_name)

DataHelper/simgnn_utils.py:335

(self, dataset, model, result_folder, dist_mat, row_graphs, col_graphs, scale)

DataHelper/simgnn_utils.py:498

(self, ged_main_dir, config)

DataHelper/CustomDataset.py:15

Functionaccuracy

(output, labels)

utils/utils.py:78

Functionalphanum_key

DataHelper/simgnn_utils.py:232

Methodclassification_mat

(self, thresh_pos, thresh_neg, thresh_pos_sim, thresh_neg_sim, norm)

DataHelper/simgnn_utils.py:459

Functioncomputing_precision_ks

(trues, predictions, ks, inclusive=True, rm=0)

DataHelper/simgnn_utils.py:293

Functioncopy_unnormalized_sim_mat

(sim_mat, testing_graphs, trainval_graphs)

Methoddist_metric

DataHelper/simgnn_utils.py:613

Methoddist_or_sim

DataHelper/simgnn_utils.py:374

Methoddist_or_sim

DataHelper/simgnn_utils.py:529

:param qid: query id (0-indexed). :param gid: database graph id (0-indexed) (NOT g.graph['gid']). :param norm: :retur

DataHelper/simgnn_utils.py:386

(self, qid, gid, norm)

DataHelper/simgnn_utils.py:532

Methoddist_sim_mat

DataHelper/simgnn_utils.py:526

Functiondraw_emb_hist_heat

(args, testing_graphs, trainval_graphs, model: GSC, extra_dir=None, plot_max_num=np.inf)

Functiondraw_ranking

(args, testing_graphs, trainval_graphs, pred_mat , pred_mat_unexp, existing_mappings = None, plot_gids=False,

Functionedge_index_to_torch_sparse_tensor

(edge_index, edge_weight = None)

utils/utils.py:135

DataHelper/simgnn_utils.py:196

DataHelper/simgnn_utils.py:217

Functionevaluate

(self, testing_graphs, training_graphs, model, loss_func, dataset: DatasetLocal, validation = False)

training_procedure/evaluate.py:29

Functionevaluate

(testing_graphs, training_graphs, model, dataset: DatasetLocal, config)

Methodextract_test_matrices

DataHelper/CustomDataset.py:41

Functionformat_ds

model/layers.py:27

model/layers.py:49

Making a forward propagation pass to create a graph level representation. :param x: Result of the GNN. :param size: Dimension

model/layers.py:81

(self, x, batch, size=None)

model/layers.py:137

(self, embedding_1, embedding_2)

model/layers.py:191

model/layers.py:224

Forward pass with graphs. :param data: Data dictionary. :return score: Similarity score.

model/SImGNN.py:149

model/MLP.py:26

model/MLP.py:48

model/GSC.py:182

(self, batch_1, batch_2, z1, z2, g1 = None, g2 = None)

model/GSC.py:290

(self, x, edge_index)

model/Base/GAT.py:13

model/Base/GSC_custom.py:131

(self, score_vec)

model/Base/GSC_custom.py:199

(self, x, edge_index)

model/Base/GCN.py:25

Methodgenerate_all_val_gs

DataHelper/DatasetLocal.py:209

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