added sageconv lux (#500)

GNNLux/src/GNNLux.jl

@@ -35,7 +35,7 @@ export AGNNConv,
  MEGNetConv,
  NNConv,
  ResGatedGraphConv,
- # SAGEConv,
+ SAGEConv,
  SGConv
  # TAGConv,
  # TransformerConv

GNNLux/src/layers/conv.jl

@@ -844,3 +844,51 @@ function Base.show(io::IO, l::ResGatedGraphConv)
  l.use_bias || print(io, ", use_bias=false")
  print(io, ")")
 end
+
+@concrete struct SAGEConv <: GNNLayer
+ in_dims::Int
+ out_dims::Int
+ use_bias::Bool
+ init_weight
+ init_bias
+ σ
+ aggr
+end
+
+function SAGEConv(ch::Pair{Int, Int}, σ = identity; 
+ aggr = mean,
+ init_weight = glorot_uniform,
+ init_bias = zeros32, 
+ use_bias::Bool = true)
+ in_dims, out_dims = ch
+ σ = NNlib.fast_act(σ)
+ return SAGEConv(in_dims, out_dims, use_bias, init_weight, init_bias, σ, aggr)
+end
+
+function LuxCore.initialparameters(rng::AbstractRNG, l::SAGEConv)
+ weight = l.init_weight(rng, l.out_dims, 2 * l.in_dims)
+ if l.use_bias
+ bias = l.init_bias(rng, l.out_dims)
+ return (; weight, bias)
+ else
+ return (; weight)
+ end
+end
+
+LuxCore.parameterlength(l::SAGEConv) = l.use_bias ? l.out_dims * 2 * l.in_dims + l.out_dims : 
+ l.out_dims * 2 * l.in_dims
+LuxCore.outputsize(d::SAGEConv) = (d.out_dims,)
+
+function Base.show(io::IO, l::SAGEConv)
+ print(io, "SAGEConv(", l.in_dims, " => ", l.out_dims)
+ (l.σ == identity) || print(io, ", ", l.σ)
+ (l.aggr == mean) || print(io, ", aggr=", l.aggr)
+ l.use_bias || print(io, ", use_bias=false") 
+ print(io, ")")
+end
+
+function (l::SAGEConv)(g, x, ps, st)
+ m = (; ps.weight, bias = _getbias(ps), 
+ l.σ, l.aggr)
+ return GNNlib.sage_conv(m, g, x), st
+end

GNNLux/test/layers/conv_tests.jl

@@ -134,4 +134,9 @@
  l = ResGatedGraphConv(in_dims => out_dims, tanh)
  test_lux_layer(rng, l, g, x, outputsize=(out_dims,))
  end
+
+ @testset "SAGEConv" begin
+ l = SAGEConv(in_dims => out_dims, tanh)
+ test_lux_layer(rng, l, g, x, outputsize=(out_dims,))
+ end
 end