SortPooling

class dgl.nn.mxnet.glob.SortPooling(k)[source]

Bases: mxnet.gluon.block.Block

Pooling layer from An End-to-End Deep Learning Architecture for Graph Classification

Parameters

k (int) – The number of nodes to hold for each graph.

forward(graph, feat)[source]

Compute sort pooling.

Parameters

  • graph (DGLGraph) – The graph.

  • feat (mxnet.NDArray) – The input node feature with shape \((N, D)\) where \(N\) is the number of nodes in the graph.

Returns

The output feature with shape \((B, k * D)\), where \(B\) refers to the batch size.

Return type

mxnet.NDArray