Bound tests

test/conv.jl

@@ -878,6 +878,8 @@ end
   gradtest((y, w) -> sum(∇depthwiseconv_data(y, w, dcdims)), y, w)
 end
 
+@static if Test_Enzyme
+
 @testset "EnzymeRules: conv! spatial_rank=$spatial_rank" for spatial_rank in (1, 2, 3)
   x = rand(rng, repeat([5], spatial_rank)..., 3, 2)
   w = rand(rng, repeat([3], spatial_rank)..., 3, 3)
@@ -899,7 +901,6 @@ end
   end
 end
 
-
 @testset "EnzymeRules: depthwiseconv! spatial_rank=$spatial_rank" for spatial_rank in (1, 2, 3)
   x = rand(rng, repeat([5], spatial_rank)..., 3, 2)
   w = rand(rng, repeat([3], spatial_rank)..., 3, 3)
@@ -919,4 +920,6 @@ end
 
     EnzymeTestUtils.test_reverse(curconv!, Tret, (dst, Tdst), (x, Tx), (w, Tw), (cdims, EnzymeCore.Const))
   end
+end
+
 end

test/dropout.jl

@@ -76,6 +76,8 @@ using Zygote, StableRNGs, ChainRulesCore, Enzyme
     @test_throws ArgumentError dropout!(y1, x1, 3)
 end
 
+@static if Test_Enzyme
+
 @testset "EnzymeRules: dropout " begin
     rng = Random.default_rng()
 
@@ -99,4 +101,6 @@ end
     val = convert(Float32, 1/(1-p))
 
     @test dx1[tape[1]] ≈ (val * dout)[tape[1]]
+end
+
 end

test/gather.jl

@@ -154,6 +154,7 @@ function gather_testsuite(Backend)
             gradtest_fn((s, i) -> gather(s, i), src, idx)
     end
 
+    @static if Test_Enzyme
 
     @testset "EnzymeRules: gather! gradient for scalar index" begin
         src = device(Float64[3, 4, 5, 6, 7])
@@ -172,6 +173,8 @@ function gather_testsuite(Backend)
         end
     end
 
+    end
+
     @testset "gather gradient for tuple index" begin
         src = device(Float64[
             3 5 7

test/pooling.jl

@@ -968,6 +968,7 @@ end
   gradtest(x -> sum(meanpool(x, k)), x)
 end
 
+@static if Test_Enzyme
 
 @testset "EnzymeRules: pooling! $pool spatial_rank=$spatial_rank " for spatial_rank in (1, 2),
                                                                                 (pool, pool!) in ((maxpool, maxpool!), (meanpool, meanpool!))
@@ -985,4 +986,6 @@ end
     EnzymeTestUtils.test_reverse(pool!, Tret, (y, Tdst), (x, Tsrc), (pdims, EnzymeCore.Const))
   end
 
+end
+
 end

test/runtests.jl

@@ -13,6 +13,8 @@ using Adapt
 using KernelAbstractions
 import ReverseDiff as RD        # used in `pooling.jl`
 
+const Test_Enzyme = VERSION <= v"1.10" && !Sys.iswindows()
+
 DocMeta.setdocmeta!(NNlib, :DocTestSetup, :(using NNlib, UnicodePlots); recursive=true)
 
 # ENV["NNLIB_TEST_CUDA"] = "true" # uncomment to run CUDA tests

test/scatter.jl

@@ -208,6 +208,8 @@ function scatter_testsuite(Backend)
             end
         end
 
+        @static if Test_Enzyme
+
         @testset "EnzymeRules" begin
             idx = device([2, 2, 3, 4, 4])
             src = device(ones(T, 3, 5))
@@ -226,5 +228,7 @@ function scatter_testsuite(Backend)
                 end
             end
         end
+
+        end
     end
 end