Functions — github.com/HanGuangXin/Result-Visualization-of-Graph-Convolutional-Networks-in-PyTorch

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Functions19 in github.com/HanGuangXin/Result-Visualization-of-Graph-Convolutional-Networks-in-PyTorch

⨍ Functions 19 ◇ Types & classes 2

↓ 5 callersFunctionnormalize

Row-normalize sparse matrix

pygcn/utils.py:94

↓ 4 callersFunctionVisualization

(vis, result, labels,title)

pygcn/train.py:97

↓ 4 callersFunctiont_SNE

(output, dimention)

pygcn/train.py:89

↓ 3 callersFunctionaccuracy

(output, labels)

pygcn/utils.py:104

↓ 2 callersFunctionencode_onehot

(labels)

pygcn/utils.py:6

↓ 2 callersFunctionsparse_mx_to_torch_sparse_tensor

Convert a scipy sparse matrix to a torch sparse tensor.

pygcn/utils.py:111

↓ 1 callersFunctionencode_onehot

(labels)

pygcn/test.py:5

↓ 1 callersFunctionget_data

()

pygcn/MNIST_with_t-SNE.py:11

↓ 1 callersFunctionload_data

Load citation network dataset (cora only for now)

pygcn/utils.py:22

↓ 1 callersFunctionplot_embedding

(data, label, title)

pygcn/MNIST_with_t-SNE.py:19

↓ 1 callersMethodreset_parameters

(self)

pygcn/layers.py:26

↓ 1 callersFunctionshow_Hyperparameter

(args)

pygcn/train.py:31

↓ 1 callersFunctiontest

()

pygcn/train.py:78

↓ 1 callersFunctiontrain

(epoch)

pygcn/train.py:37

Method__init__

(self, in_features, out_features, bias=True)

pygcn/layers.py:14

Method__init__

(self, nfeat, nhid, nclass, dropout)