[GNNLux] Adding MegNetConv Layer

GNNLux/src/GNNLux.jl

@@ -1,6 +1,7 @@
 module GNNLux
 using ConcreteStructs: @concrete
 using NNlib: NNlib, sigmoid, relu, swish
+using Statistics: mean
 using LuxCore: LuxCore, AbstractExplicitLayer, AbstractExplicitContainerLayer, parameterlength, statelength, outputsize, 
               initialparameters, initialstates, parameterlength, statelength
 using Lux: Lux, Chain, Dense, GRUCell,
@@ -30,7 +31,7 @@ export AGNNConv,
        GINConv,
        # GMMConv,
        GraphConv,
-       # MEGNetConv,
+       MEGNetConv,
        # NNConv,
        # ResGatedGraphConv,
        # SAGEConv,

GNNLux/src/layers/conv.jl

@@ -628,3 +628,45 @@ function Base.show(io::IO, l::GINConv)
     print(io, ", $(l.ϵ)")
     print(io, ")")
 end
+
+@concrete struct MEGNetConv{TE, TV, A} <: GNNContainerLayer{(:ϕe, :ϕv)}
+    in_dims::Int
+    out_dims::Int
+    ϕe::TE
+    ϕv::TV
+    aggr::A
+end
+
+function MEGNetConv(in_dims::Int, out_dims::Int, ϕe::TE, ϕv::TV; aggr::A = mean) where {TE, TV, A}
+    return MEGNetConv{TE, TV, A}(in_dims, out_dims, ϕe, ϕv, aggr)
+end
+
+function MEGNetConv(ch::Pair{Int, Int}; aggr = mean)
+    nin, nout = ch
+    ϕe = Chain(Dense(3nin, nout, relu),
+               Dense(nout, nout))
+
+    ϕv = Chain(Dense(nin + nout, nout, relu),
+               Dense(nout, nout))
+
+    return MEGNetConv(nin, nout, ϕe, ϕv, aggr=aggr)
+end
+
+function (l::MEGNetConv)(g, x, e, ps, st)
+    ϕe = StatefulLuxLayer{true}(l.ϕe, ps.ϕe, _getstate(st, :ϕe))
+    ϕv = StatefulLuxLayer{true}(l.ϕv, ps.ϕv, _getstate(st, :ϕv))    
+    m = (; ϕe, ϕv, aggr=l.aggr)
+    return GNNlib.megnet_conv(m, g, x, e), st
+end
+
+
+LuxCore.outputsize(l::MEGNetConv) = (l.out_dims,)
+
+(l::MEGNetConv)(g, x, ps, st) = l(g, x, nothing, ps, st)
+
+function Base.show(io::IO, l::MEGNetConv)
+    nin = l.in_dims
+    nout = l.out_dims
+    print(io, "MEGNetConv(", nin, " => ", nout)
+    print(io, ")")
+end

GNNLux/test/layers/conv_tests.jl

@@ -93,4 +93,17 @@
         l = GINConv(nn, 0.5)
         test_lux_layer(rng, l, g, x, sizey=(out_dims,g.num_nodes), container=true)
     end
+
+    @testset "MEGNetConv" begin
+        l = MEGNetConv(in_dims => out_dims)
+
+        ps = LuxCore.initialparameters(rng, l)
+        st = LuxCore.initialstates(rng, l)
+
+        e = randn(rng, Float32, in_dims, g.num_edges) 
+        (x_new, e_new), st_new = l(g, x, e, ps, st)   
+
+        @test size(x_new) == (out_dims, g.num_nodes)
+        @test size(e_new) == (out_dims, g.num_edges)
+    end
 end

GNNlib/src/layers/conv.jl

@@ -721,4 +721,4 @@ function d_conv(l, g::GNNGraph, x::AbstractMatrix)
         T1_out = T2_out
     end
     return h .+ l.bias
-end
+end