Graph network block

Graph network (GN) is a more generic model for graph neural network. It describes an update order: edge, node and then global. There are three corresponding update functions for edge, node and then global, respectively. Three update functions return their default values as follow:

update_edge(gn, e, vi, vj, u) = e
update_vertex(gn, ē, vi, u) = vi
update_global(gn, ē, v̄, u) = u

Information propagation between different levels are achieved by aggregate functions. Three aggregate functions aggregate_neighbors, aggregate_edges and aggregate_vertices are defined to aggregate states.

GN block is realized into a abstract type GraphNet. User can make a subtype of GraphNet to customize GN block. Thus, a GN block is defined as a layer in GNN. MessagePassing is a subtype of GraphNet.

Update functions

update_edge acts as the first update function to apply to edge states. It takes edge state e, node i state vi, node j state vj and global state u. It is expected to return a feature vector for new edge state. update_vertex updates nodes state by taking aggregated edge state ē, node i state vi and global state u. It is expected to return a feature vector for new node state. update_global updates global state with aggregated information from edge and node. It takes aggregated edge state ē, aggregated node state v̄ and global state u. It is expected to return a feature vector for new global state. User can define their own behavior by overriding update functions.

Aggregate functions

An aggregate function aggregate_neighbors aggregates edge states for edges incident to some node i into node-level information. Aggregate function aggregate_edges aggregates all edge states into global-level information. The last aggregate function aggregate_vertices aggregates all vertex states into global-level information. It is available for assigning aggregate function by assigning aggregate operations to propagate function.

propagate(gn, fg::FeaturedGraph, naggr=nothing, eaggr=nothing, vaggr=nothing)

naggr, eaggr and vaggr are arguments for aggregate_neighbors, aggregate_edges and aggregate_vertices, respectively. Available aggregate functions are assigned by following symbols to them: :add, :sub, :mul, :div, :max, :min and :mean.