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Functions28 in github.com/PetarV-/DGI

↓ 2 callersFunctionsparse_to_tuple
Convert sparse matrix to tuple representation.
utils/process.py:144
↓ 2 callersFunctionto_tuple
(mx)
utils/process.py:147
↓ 1 callersMethodembed
(self, seq, adj, sparse, msk)
models/dgi.py:28
↓ 1 callersFunctionnormalize_adj
Symmetrically normalize adjacency matrix.
utils/process.py:189
↓ 1 callersFunctionparse_index_file
Parse index file.
utils/process.py:92
↓ 1 callersMethodweights_init
(self, m)
layers/gcn.py:19
↓ 1 callersMethodweights_init
(self, m)
layers/discriminator.py:12
↓ 1 callersMethodweights_init
(self, m)
models/logreg.py:13
Method__init__
(self, in_ft, out_ft, act, bias=True)
layers/gcn.py:5
Method__init__
(self)
layers/readout.py:7
Method__init__
(self, n_h)
layers/discriminator.py:5
Method__init__
(self, n_in, n_h, activation)
models/dgi.py:6
Method__init__
(self, ft_in, nb_classes)
models/logreg.py:6
Functionadj_to_bias
(adj, sizes, nhood=1)
utils/process.py:74
Methodforward
(self, seq, adj, sparse=False)
layers/gcn.py:26
Methodforward
(self, seq, msk)
layers/readout.py:10
Methodforward
(self, c, h_pl, h_mi, s_bias1=None, s_bias2=None)
layers/discriminator.py:18
Methodforward
(self, seq1, seq2, adj, sparse, msk, samp_bias1, samp_bias2)
models/dgi.py:15
Methodforward
(self, seq)
models/logreg.py:19
Functionload_data
Load data.
utils/process.py:105
Functionmicro_f1
(logits, labels)
utils/process.py:48
Functionparse_skipgram
(fname)
utils/process.py:10
Functionpreprocess_adj
Preprocessing of adjacency matrix for simple GCN model and conversion to tuple representation.
utils/process.py:199
Functionpreprocess_features
Row-normalize feature matrix and convert to tuple representation
utils/process.py:180
Functionprocess_tu
(data, nb_nodes)
utils/process.py:27
Functionsample_mask
Create mask.
utils/process.py:99
Functionsparse_mx_to_torch_sparse_tensor
Convert a scipy sparse matrix to a torch sparse tensor.
utils/process.py:204
Functionstandardize_data
Standardize feature matrix and convert to tuple representation
utils/process.py:168