# 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