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Functions29 in github.com/PetarV-/GAT

↓ 3 callersFunctionsample_mask
Create mask.
utils/process.py:39
↓ 2 callersMethodinference
(inputs, nb_classes, nb_nodes, training, attn_drop, ffd_drop, bias_mat, hid_units, n_heads, activa
models/gat.py:8
↓ 2 callersMethodmasked_accuracy
Accuracy with masking.
models/base_gattn.py:57
↓ 2 callersMethodmasked_softmax_cross_entropy
Softmax cross-entropy loss with masking.
models/base_gattn.py:39
↓ 2 callersFunctionsparse_to_tuple
Convert sparse matrix to tuple representation.
utils/process.py:125
↓ 2 callersFunctionto_tuple
(mx)
utils/process.py:127
↓ 2 callersMethodtraining
(loss, lr, l2_coef)
models/base_gattn.py:10
↓ 1 callersFunctiondfs_split
(adj)
utils/process_ppi.py:20
↓ 1 callersFunctionfind_split
(adj, mapping, ds_label)
utils/process_ppi.py:46
↓ 1 callersFunctionnormalize_adj
Symmetrically normalize adjacency matrix.
utils/process.py:164
↓ 1 callersFunctionparse_index_file
Parse index file.
utils/process.py:32
↓ 1 callersFunctionrun_dfs
(adj, msk, u, ind, nb_nodes)
utils/process_ppi.py:11
↓ 1 callersFunctiontest
(adj, mapping)
utils/process_ppi.py:34
Functionadj_to_bias
(adj, sizes, nhood=1)
utils/process.py:14
Functionattn_head
(seq, out_sz, bias_mat, activation, in_drop=0.0, coef_drop=0.0, residual=False)
utils/layers.py:6
Methodconfmat
(logits, labels)
models/base_gattn.py:31
Methodinference
(inputs, nb_classes, nb_nodes, training, attn_drop, ffd_drop, bias_mat, hid_units, n_heads, activa
models/sp_gat.py:8
Functionload_data
Load data.
utils/process.py:45
Functionload_random_data
(size)
utils/process.py:98
Methodloss
(logits, labels, nb_classes, class_weights)
models/base_gattn.py:4
Methodmasked_sigmoid_cross_entropy
Softmax cross-entropy loss with masking.
models/base_gattn.py:47
Methodmicro_f1
Accuracy with masking.
models/base_gattn.py:66
Functionpreprocess_adj
Preprocessing of adjacency matrix for simple GCN model and conversion to tuple representation.
utils/process.py:174
Functionpreprocess_adj_bias
(adj)
utils/process.py:179
Functionpreprocess_features
Row-normalize feature matrix and convert to tuple representation
utils/process.py:155
Methodpreshape
(logits, labels, nb_classes)
models/base_gattn.py:24
Functionprocess_p2p
()
utils/process_ppi.py:85
Functionsp_attn_head
(seq, out_sz, adj_mat, activation, nb_nodes, in_drop=0.0, coef_drop=0.0, residual=False)
utils/layers.py:38
Functionstandardize_data
Standardize feature matrix and convert to tuple representation
utils/process.py:143