fix documentation and test

Author: juanmigutierrez

GNNLux/src/layers/temporalconv.jl

@@ -93,7 +93,7 @@ rng = Random.default_rng()
 g = rand_graph(rng, 5, 10)
 x = rand(rng, Float32, 2, 5)
 
-# create TGCN layer with default activation (sigmoid)
+# create TGCN layer 
 tgcn = TGCN(2 => 6)
 
 # create TGCN layer with custom activation

GNNLux/test/layers/temporalconv.jl

@@ -10,16 +10,16 @@
     tx = [x for _ in 1:5]
 
     @testset "TGCN" begin
-        # Test with default activation (relu)
+        # Test with default activation (sigmoid)
         l = TGCN(3=>3)
         ps = LuxCore.initialparameters(rng, l)
         st = LuxCore.initialstates(rng, l)
         y1, _ = l(g, x, ps, st)
         loss = (x, ps) -> sum(first(l(g, x, ps, st)))
         test_gradients(loss, x, ps; atol=1.0f-2, rtol=1.0f-2, skip_backends=[AutoReverseDiff(), AutoTracker(), AutoForwardDiff(), AutoEnzyme()])
 
-        # Test with custom activation (sigmoid)
-        l_relu = TGCN(3=>3, act = sigmoid)
+        # Test with custom activation (relu)
+        l_relu = TGCN(3=>3, act = relu)
         ps_relu = LuxCore.initialparameters(rng, l_relu)
         st_relu = LuxCore.initialstates(rng, l_relu)
         y2, _ = l_relu(g, x, ps_relu, st_relu)

GraphNeuralNetworks/src/layers/temporalconv.jl

@@ -869,12 +869,12 @@ See [`GNNRecurrence`](@ref) for more details.
 
 # Additional Parameters
 
-- `gate_activation`: Activation function for the gate mechanisms. Default `sigmoid`.
+- `act`: Activation function for the GCNConv layers. Default `relu`.
 
 # Examples
 
 ```jldoctest
-julia> using Flux  # Ensure relu is available
+julia> using Flux  # Ensure activation functions are available
 
 julia> num_nodes, num_edges = 5, 10;