diff --git a/test/Project.toml b/test/Project.toml index 1a4936a4..fed824b2 100644 --- a/test/Project.toml +++ b/test/Project.toml @@ -1,7 +1,6 @@ [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" @@ -9,23 +8,19 @@ 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" @@ -33,14 +28,11 @@ 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" diff --git a/test/call_tests.jl b/test/call_tests.jl index de93924e..2cc61cc2 100644 --- a/test/call_tests.jl +++ b/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 | $mt" for resource in resources, diff --git a/test/fit_tests.jl b/test/fit_tests.jl index 8f8b1488..79188a95 100644 --- a/test/fit_tests.jl +++ b/test/fit_tests.jl @@ -59,9 +59,6 @@ Test.@testset "Fit Tests" begin ] data_types = Type{<:AbstractFloat}[Float32] resources = ComputationalResources.AbstractResource[ComputationalResources.CPU1()] - if CUDA.has_cuda_gpu() && USE_GPU - push!(resources, ComputationalResources.CUDALibs()) - end Test.@testset "$resource | $data_type | $compute_mode | $adtype | inplace = $inplace | aug & steer = $aug_steer | nvars = $nvars | $mt" for resource in resources, diff --git a/test/runtests.jl b/test/runtests.jl index 6f983bf4..402ce93a 100644 --- a/test/runtests.jl +++ b/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"