Merge branch 'nn-lux' of https://github.com/rbSparky/GraphNeuralNetwo…

…rks.jl into nn-lux

GNNLux/src/layers/conv.jl

@@ -656,7 +656,7 @@ function NNConv(ch::Pair{Int, Int}, nn, σ = identity;
     return NNConv(nn, aggr, in_dims, out_dims, use_bias, add_self_loops, use_edge_weight, init_weight, init_bias, σ)
 end
 
-function (l::GCNConv)(g, x, edge_weight, ps, st)
+function (l::NNConv)(g, x, edge_weight, ps, st)
     nn = StatefulLuxLayer{true}(l.nn, ps, st)
 
     # what would be the order of args here?
@@ -680,8 +680,7 @@ end
 LuxCore.parameterlength(l::NNConv) = l.use_bias ? l.in_dims * l.out_dims + l.out_dims : l.in_dims * l.out_dims # nn wont affect this right?
 LuxCore.outputsize(d::NNConv) = (d.out_dims,)
 
-
-function Base.show(io::IO, l::NNConv)
+function Base.show(io::IO, l::GINConv)
     print(io, "NNConv($(l.nn)")
     print(io, ", $(l.ϵ)")
     l.σ == identity || print(io, ", ", l.σ)