GCNNormΒΆ
-
class
dgl.transforms.
GCNNorm
(eweight_name='w')[source]ΒΆ Bases:
dgl.transforms.module.BaseTransform
Apply symmetric adjacency normalization to an input graph and save the result edge weights, as described in Semi-Supervised Classification with Graph Convolutional Networks.
For a heterogeneous graph, this only applies to symmetric canonical edge types, whose source and destination node types are identical.
- Parameters
eweight_name (str, optional) β
edata
name to retrieve and store edge weights. The edge weights are optional.
Example
Case1: Transform an unweighted graph
Case2: Transform a weighted graph