remove cast rrule not needed anymore (#135)

Author: CarloLucibello

src/utils.jl

@@ -99,17 +99,3 @@ function broadcast_edges(g::GNNGraph, x)
     gi = graph_indicator(g, edges=true)
     return gather(x, gi)
 end
-
-# More generic version of
-# https://github.com/JuliaDiff/ChainRules.jl/pull/586
-# This applies to all arrays
-# Withouth this, gradient of T.(A) for A dense gpu matrix errors.
-function ChainRulesCore.rrule(::typeof(Broadcast.broadcasted), T::Type{<:Number}, x::AbstractArray)
-    proj = ProjectTo(x)
-
-    function broadcasted_cast(Δ)
-        return NoTangent(), NoTangent(), proj(Δ)         
-    end
-
-    return T.(x), broadcasted_cast
-end

test/runtests.jl

@@ -41,10 +41,10 @@ tests = [
 
 !CUDA.functional() && @warn("CUDA unavailable, not testing GPU support")
 
-@testset "GraphNeuralNetworks: graph format $graph_type" for graph_type in (:dense, :coo, :sparse) 
+@testset "GraphNeuralNetworks: graph format $graph_type" for graph_type in (:coo, :dense, :sparse) 
     global GRAPH_T = graph_type
     global TEST_GPU = CUDA.functional() && (GRAPH_T != :sparse)
-    
+
     for t in tests
         startswith(t, "examples") && GRAPH_T == :dense && continue     # not testing :dense since causes OutOfMememory on github's CI
         include("$t.jl")