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ChrisRackauckas-ClaudeChrisRackauckasclaudeChrisRackauckas-Claude
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Canonical CI: grouped-tests.yml + root test/test_groups.toml (#217)
* Canonical CI: grouped-tests.yml + root test/test_groups.toml Convert the root test workflow (Tests.yml, name: CI) to the canonical SciML/.github grouped-tests.yml@v1 thin caller, with the group x version matrix declared once in test/test_groups.toml at the repo root. - .github/workflows/Tests.yml: replace the hand-maintained group({CPU,QA}) x version({lts,1}) matrix job (which called the legacy per-job tests.yml@v1) with a thin caller to grouped-tests.yml@v1. on: and concurrency: preserved verbatim; filename + name: kept. - test/test_groups.toml (new, root): [Core] and [QA], each on [lts, 1]. Reproduces the old matrix with the functional CPU group renamed to the canonical Core (QA unchanged). Linux-only, no os axis. - test/qa/Project.toml (new): isolated QA env (Aqua, ExplicitImports, Documenter + the doctest/ExplicitImports support deps) with DeepEquilibriumNetworks via [sources] path = "../.." and julia = "1.10". - test/qa/qa.jl: the QA checks, moved verbatim from test/qa_tests.jl (no checks added, removed, or excluded). - test/runtests.jl: GROUP == "QA" now activates test/qa, develops the package, instantiates, then includes qa/qa.jl. Functional tests run under GROUP Core (CPU and ALL still accepted for back-compat). - test/shared_testsetup.jl: treat BACKEND_GROUP "core" as CPU so the renamed Core group selects the CPU device. Project.toml already satisfies the benign-metadata checks: [compat] julia = "1.10" (LTS floor) and every [extras] dep has a [compat] entry. Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com> Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Fold GPU.yml CUDA tests into the [GPU] test group The bespoke .github/workflows/GPU.yml ran the functional suite on the self-hosted CUDA runner with BACKEND_GROUP=CUDA. That is now a [GPU] group in test/test_groups.toml (versions ["1"], runner [self-hosted, Linux, X64, gpu], timeout 240) executed by the grouped-tests.yml@v1 caller, with runtests.jl setting BACKEND_GROUP=CUDA for GROUP=GPU. The workflow's gpu-docs job was a duplicate of the centralized documentation.yml already on main, so GPU.yml is deleted outright. Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com> Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Adopt SciMLTesting v1.2 folder-based run_tests (on top of grouped-tests conversion) DEQ's GROUP semantics are backend/capability-based, not folder-partitioned: the GPU group runs the *same* Core test files (utils_tests.jl + layers_tests.jl) with shared_testsetup.jl's backend switched to CUDA via BACKEND_GROUP, so it cannot be expressed as a separate folder of files. Use explicit-args run_tests (v1.2): core = the two top-level Core files (each in its own @safetestset), GPU group = same body with BACKEND_GROUP=CUDA, QA = test/qa sub-env. Curated all=["Core"] so the self-hosted GPU lane and QA stay out of the aggregate. Drop Pkg from the test deps (only the old harness used it; SciMLTesting handles activate/develop now) and add SciMLTesting + SafeTestsets to the QA sub-env. test_groups.toml unchanged. Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com> Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: ChrisRackauckas-Claude <accounts@chrisrackauckas.com> Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Co-authored-by: ChrisRackauckas-Claude <claude@chrisrackauckas.com>
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‎.github/workflows/GPU.yml‎

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‎.github/workflows/Tests.yml‎

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jobs:
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tests:
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name: "Tests"
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strategy:
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fail-fast: false
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matrix:
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group:
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- CPU
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- QA
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version:
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- 'lts'
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- '1'
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uses: "SciML/.github/.github/workflows/tests.yml@v1"
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with:
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julia-version: "${{ matrix.version }}"
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group: "${{ matrix.group }}"
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uses: "SciML/.github/.github/workflows/grouped-tests.yml@v1"
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secrets: "inherit"

‎Project.toml‎

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NonlinearSolveBase = "1.5, 2"
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OrdinaryDiffEq = "6.74, 7"
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OrdinaryDiffEqAdamsBashforthMoulton = "1, 2"
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Pkg = "1.10"
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PrecompileTools = "1.2.1"
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Random = "1.10"
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SciMLBase = "2, 3.3"
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SciMLSensitivity = "7.43"
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SciMLTesting = "1"
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StableRNGs = "1"
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Static = "1"
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SteadyStateDiffEq = "2.5.0"
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NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
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OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
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OrdinaryDiffEqAdamsBashforthMoulton = "89bda076-bce5-4f1c-845f-551c83cdda9a"
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Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
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SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
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SciMLTesting = "09d9d899-5365-40a9-917a-5f67fddea283"
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StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
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[targets]
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test = ["Aqua", "Documenter", "ExplicitImports", "ForwardDiff", "Functors", "GPUArraysCore", "InteractiveUtils", "LuxTestUtils", "MLDataDevices", "NLsolve", "NonlinearSolve", "OrdinaryDiffEq", "OrdinaryDiffEqAdamsBashforthMoulton", "Pkg", "SafeTestsets", "SciMLSensitivity", "StableRNGs", "Test", "Zygote"]
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test = ["Aqua", "Documenter", "ExplicitImports", "ForwardDiff", "Functors", "GPUArraysCore", "InteractiveUtils", "LuxTestUtils", "MLDataDevices", "NLsolve", "NonlinearSolve", "OrdinaryDiffEq", "OrdinaryDiffEqAdamsBashforthMoulton", "SafeTestsets", "SciMLSensitivity", "SciMLTesting", "StableRNGs", "Test", "Zygote"]

‎test/qa/Project.toml‎

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[deps]
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Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
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DeepEquilibriumNetworks = "6748aba7-0e9b-415e-a410-ae3cc0ecb334"
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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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ExplicitImports = "7d51a73a-1435-4ff3-83d9-f097790105c7"
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Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
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NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
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OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
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Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
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SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
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SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
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SciMLTesting = "09d9d899-5365-40a9-917a-5f67fddea283"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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[sources]
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DeepEquilibriumNetworks = {path = "../.."}
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[compat]
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Aqua = "0.8"
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Documenter = "1"
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ExplicitImports = "1"
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Lux = "1"
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NonlinearSolve = "4"
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OrdinaryDiffEq = "6.74, 7"
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Random = "1.10"
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SciMLSensitivity = "7.43"
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SciMLTesting = "1"
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Test = "1.10"
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julia = "1.10"

test/qa_tests.jl renamed to test/qa/qa.jl

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‎test/runtests.jl‎

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using Pkg
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using SafeTestsets, Test
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using SciMLTesting
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using SafeTestsets
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const GROUP = uppercase(get(ENV, "GROUP", "CPU"))
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@info "Running tests for GROUP: $GROUP"
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@time begin
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if GROUP == "CPU" || GROUP == "ALL"
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@time @safetestset "Utils Tests" include("utils_tests.jl")
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@time @safetestset "Layers Tests" include("layers_tests.jl")
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end
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if GROUP == "QA"
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@time @safetestset "Quality Assurance Tests" include("qa_tests.jl")
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end
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# DEQ's GROUP semantics are backend/capability-based, not folder-partitioned: the
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# GPU group runs the *same* Core test files (utils_tests.jl + layers_tests.jl)
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# with shared_testsetup.jl's backend switched to CUDA via BACKEND_GROUP, so it
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# cannot be expressed as a separate folder of files. Hence explicit-args run_tests.
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function core_body()
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@safetestset "Utils Tests" include("utils_tests.jl")
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@safetestset "Layers Tests" include("layers_tests.jl")
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end
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run_tests(;
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core = core_body,
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groups = Dict(
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# GPU is the self-hosted CUDA runner lane: the same Core suite with the
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# backend switched to CUDA.
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"GPU" => () -> begin
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ENV["BACKEND_GROUP"] = "CUDA"
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core_body()
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end,
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),
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qa = (; env = joinpath(@__DIR__, "qa"), body = joinpath(@__DIR__, "qa", "qa.jl")),
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# Curated "All": run only Core. GPU (self-hosted CUDA lane) and QA stay
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# selectable by name but out of the aggregate.
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all = ["Core"],
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)

‎test/shared_testsetup.jl‎

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GPUArraysCore.allowscalar(false)
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cpu_testing() = BACKEND_GROUP == "all" || BACKEND_GROUP == "cpu"
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cpu_testing() = BACKEND_GROUP == "all" || BACKEND_GROUP == "cpu" || BACKEND_GROUP == "core"
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function cuda_testing()
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return (BACKEND_GROUP == "all" || BACKEND_GROUP == "cuda") &&
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MLDataDevices.functional(CUDADevice)

‎test/test_groups.toml‎

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[Core]
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versions = ["lts", "1"]
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[QA]
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versions = ["lts", "1"]
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[GPU]
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versions = ["1"]
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runner = ["self-hosted", "Linux", "X64", "gpu"]
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timeout = 240

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