cl/upsample

Author: CarloLucibello

Project.toml

@@ -7,7 +7,6 @@ ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
-StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
@@ -17,11 +16,13 @@ julia = "1.3"
 
 [extras]
 ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"
+CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["ChainRulesTestUtils", "FiniteDifferences", "Random", "StableRNGs", "Test", "Zygote"]
+test = ["ChainRulesTestUtils", "CUDA", "FiniteDifferences", 
+        "Random", "StableRNGs", "Test", "Zygote"]

test/runtests.jl

@@ -6,6 +6,8 @@ using FiniteDifferences: FiniteDifferenceMethod, central_fdm
 import Zygote
 using Zygote: gradient
 using StableRNGs
+using CUDA
+CUDA.allowscalar(false)
 
 const rng = StableRNG(123)
 

test/upsample.jl

@@ -1,6 +1,3 @@
-using CUDA
-CUDA.allowscalar(false)
-
 @testset "bilinear_upsample 2d" begin
     x = reshape(Float32[1. 2.; 3. 4.], (2,2,1,1))
     y_true =   [1//1  5//4    7//4    2//1;
@@ -17,14 +14,15 @@ CUDA.allowscalar(false)
 
     gradtest(x->bilinear_upsample(x, (3, 2)), x, atol=1e-4)
 
-    # CUDA compatibility
-    y = bilinear_upsample(x |> cu, (3, 2))
-    @test y isa CuArray 
-    @test Array(y) ≈ y_true
-    g_gpu = Zygote.gradient(x -> sum(sin.(bilinear_upsample(x, (3, 2))))
-                            , x |> cu)[1]
-    @test g_gpu isa CuArray
-    g_cpu = Zygote.gradient(x -> sum(sin.(bilinear_upsample(x, (3, 2))))
-                            , x)[1]
-    @test Array(g_cpu) ≈ g_cpu  atol=1e-4
+    if CUDA.has_cuda()
+        y = bilinear_upsample(x |> cu, (3, 2))
+        @test y isa CuArray 
+        @test Array(y) ≈ y_true
+        g_gpu = Zygote.gradient(x -> sum(sin.(bilinear_upsample(x, (3, 2))))
+                                , x |> cu)[1]
+        @test g_gpu isa CuArray
+        g_cpu = Zygote.gradient(x -> sum(sin.(bilinear_upsample(x, (3, 2))))
+                                , x)[1]
+        @test Array(g_cpu) ≈ g_cpu  atol=1e-4
+    end
 end