rm CUDA & GPU test

Author: prbzrg

test/Project.toml

@@ -1,46 +1,38 @@
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
-CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 ComputationalResources = "ed09eef8-17a6-5b46-8889-db040fac31e3"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DifferentiationInterface = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
-GPUArraysCore = "46192b85-c4d5-4398-a991-12ede77f4527"
 JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
-LuxCUDA = "d0bbae9a-e099-4d5b-a835-1c6931763bda"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 TerminalLoggers = "5d786b92-1e48-4d6f-9151-6b4477ca9bed"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
-cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [compat]
 ADTypes = "1"
 Aqua = "0.8"
-CUDA = "5"
 ComponentArrays = "0.15"
 ComputationalResources = "0.3"
 DataFrames = "1"
 DifferentiationInterface = "0.6"
 Distances = "0.10"
 Distributions = "0.25"
 Enzyme = "0.13"
-GPUArraysCore = "0.1, 0.2"
 JET = "0.9"
 Lux = "1"
-LuxCUDA = "0.3"
 MLJBase = "1"
 SciMLBase = "2"
 StableRNGs = "1"
 TerminalLoggers = "0.1"
 Zygote = "0.6, 0.7"
-cuDNN = "1"
 julia = "1.10"

test/call_tests.jl

@@ -62,9 +62,6 @@ Test.@testset "Call Tests" begin
     ]
     data_types = Type{<:AbstractFloat}[Float32]
     resources = ComputationalResources.AbstractResource[ComputationalResources.CPU1()]
-    if CUDA.has_cuda_gpu() && USE_GPU
-        push!(resources, ComputationalResources.CUDALibs())
-    end
 
     Test.@testset "$resource | $data_type | $compute_mode | inplace = $inplace | aug & steer = $aug_steer | nvars = $nvars | $omode | $mt" for resource in
                                                                                                                                                resources,

test/fit_tests.jl

@@ -59,9 +59,6 @@ Test.@testset "Fit Tests" begin
     ]
     data_types = Type{<:AbstractFloat}[Float32]
     resources = ComputationalResources.AbstractResource[ComputationalResources.CPU1()]
-    if CUDA.has_cuda_gpu() && USE_GPU
-        push!(resources, ComputationalResources.CUDALibs())
-    end
 
     Test.@testset "$resource | $data_type | $compute_mode | $adtype | inplace = $inplace | aug & steer = $aug_steer | nvars = $nvars | $mt" for resource in
                                                                                                                                                 resources,

test/runtests.jl

@@ -2,18 +2,14 @@ import ADTypes,
     Aqua,
     ComponentArrays,
     ComputationalResources,
-    CUDA,
-    cuDNN,
     DataFrames,
     DifferentiationInterface,
     Distances,
     Distributions,
     Enzyme,
-    GPUArraysCore,
     JET,
     Logging,
     Lux,
-    LuxCUDA,
     MLJBase,
     SciMLBase,
     StableRNGs,
@@ -23,7 +19,6 @@ import ADTypes,
     ContinuousNormalizingFlows
 
 GROUP = get(ENV, "GROUP", "All")
-USE_GPU = get(ENV, "USE_GPU", "Yes") == "Yes"
 
 if (GROUP == "All")
     GC.enable_logging(true)
@@ -35,9 +30,7 @@ end
 Test.@testset "Overall" begin
     if GROUP == "All" ||
        GROUP in ["RNODE", "FFJORD", "Planar", "CondRNODE", "CondFFJORD", "CondPlanar"]
-        GPUArraysCore.allowscalar() do
-            include("smoke_tests.jl")
-        end
+        include("smoke_tests.jl")
     end
 
     if GROUP == "All" || GROUP == "Quality"