diff --git a/src/layers/stateless.jl b/src/layers/stateless.jl
index b8ce3c7d..5f9c1090 100644
--- a/src/layers/stateless.jl
+++ b/src/layers/stateless.jl
@@ -1,3 +1,4 @@
+using CuArrays
 using NNlib: logsoftmax, logσ
 
 # Cost functions
@@ -35,6 +36,9 @@ Return `-y*log(ŷ + ϵ) - (1-y)*log(1-ŷ + ϵ)`. The ϵ term provides numerica
 """
 binarycrossentropy(ŷ, y; ϵ=eps(ŷ)) = -y*log(ŷ + ϵ) - (1 - y)*log(1 - ŷ + ϵ)
 
+# Re-definition to fix interaction with CuArrays.
+CuArrays.@cufunc binarycrossentropy(ŷ, y; ϵ=eps(ŷ)) = -y*log(ŷ + ϵ) - (1 - y)*log(1 - ŷ + ϵ)
+
 """
     logitbinarycrossentropy(logŷ, y)
 
diff --git a/test/cuda/cuda.jl b/test/cuda/cuda.jl
index d2907995..ddd92e1e 100644
--- a/test/cuda/cuda.jl
+++ b/test/cuda/cuda.jl
@@ -31,6 +31,10 @@ cx = gpu(x)
 @test Flux.crossentropy(x,x, weight=1.0) ≈ Flux.crossentropy(cx,cx, weight=1.0)
 @test Flux.crossentropy(x,x, weight=[1.0;2.0;3.0]) ≈ Flux.crossentropy(cx,cx, weight=cu([1.0;2.0;3.0]))
 
+x = σ.([-1.1491, 0.8619, 0.3127])
+y = [1, 1, 0.]
+@test Flux.binarycrossentropy.(x,y) ≈ Flux.binarycrossentropy.(cu(x),cu(y))
+
 xs = rand(5, 5)
 ys = Flux.onehotbatch(1:5,1:5)
 @test collect(cu(xs) .+ cu(ys)) ≈ collect(xs .+ ys)