The heterogeneous convolution wrapper torch_geometric.nn.conv.HeteroConv allows to define custom heterogeneous message and update functions to build arbitrary MP-GNNs for heterogeneous graphs from scratch.While the automatic converter to_hetero() uses the same operator for all edge types, the wrapper allows to define different operators for different edge types.Here, HeteroConv takes a dictionary of submodules as input, one for each edge type in the graph data.The following example shows how to apply it.
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