dgl.readout

Graph Readout

sum_nodes(graph, feat[, weight, ntype]) Syntax sugar for dgl.readout_nodes(graph, feat, weight, ntype=ntype, op='sum').
sum_edges(graph, feat[, weight, etype]) Syntax sugar for dgl.readout_edges(graph, feat, weight, etype=etype, op='sum').
mean_nodes(graph, feat[, weight, ntype]) Syntax sugar for dgl.readout_nodes(graph, feat, weight, ntype=ntype, op='mean').
mean_edges(graph, feat[, weight, etype]) Syntax sugar for dgl.readout_edges(graph, feat, weight, etype=etype, op='mean').
max_nodes(graph, feat[, weight, ntype]) Syntax sugar for dgl.readout_nodes(graph, feat, weight, ntype=ntype, op='max').
max_edges(graph, feat[, weight, etype]) Syntax sugar for dgl.readout_edges(graph, feat, weight, etype=etype, op='max').
topk_nodes(graph, feat, k, *[, descending, …]) Perform a graph-wise top-k on node features feat in graph by feature at index sortby.
topk_edges(graph, feat, k, *[, descending, …]) Perform a graph-wise top-k on node features feat in graph by feature at index sortby.
softmax_nodes(graph, feat, *[, ntype]) Perform graph-wise softmax on the node features.
softmax_edges(graph, feat, *[, etype]) Perform graph-wise softmax on the edge features.
broadcast_nodes(graph, graph_feat, *[, ntype]) Generate a node feature equal to the graph-level feature graph_feat.
broadcast_edges(graph, graph_feat, *[, etype]) Generate an edge feature equal to the graph-level feature graph_feat.