devmotion · Oct 23, 2026 · Oct 22, 2026 · Oct 22, 2026 · Oct 23, 2026 · Oct 23, 2026
diff --git a/.github/workflows/Downgrade.yml b/.github/workflows/Downgrade.yml
@@ -45,9 +45,6 @@ jobs:
           coverage: true
           allow_reresolve: false
           force_latest_compatible_version: false
-        env:
-          # `julia-downgrade-compat` promotes weakdeps to deps, so extensions always load
-          DOWNGRADE_TEST: "true"
       - uses: julia-actions/julia-processcoverage@v1
       - uses: codecov/codecov-action@v7
         with:

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -48,8 +48,6 @@ jobs:
       - uses: julia-actions/cache@v3
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
-        env:
-          JULIA_NUM_THREADS: 4
       - uses: julia-actions/julia-processcoverage@v1
       - uses: codecov/codecov-action@v7
         with:

diff --git a/test/ChainRulesTests.jl b/test/ChainRulesTests.jl
@@ -1,5 +1,3 @@
-module ChainRulesTest
-
 using LinearAlgebra
 using ChainRulesCore
 using DiffResults
@@ -283,5 +281,3 @@ module IsolatedModuleForTestingScoping
 
     end # end of SubModule
 end # end of IsolatedModuleForTestingScoping
-
-end
diff --git a/test/MacrosTests.jl b/test/MacrosTests.jl
@@ -1,5 +1,3 @@
-module MacrosTests
-
 using ReverseDiff, ForwardDiff, Test, StaticArrays
 using ForwardDiff: Dual, Partials, partials
 
@@ -344,5 +342,3 @@ using ReverseDiff: @grad, TrackedReal, TrackedVector, TrackedMatrix, TrackedArra
     @test g1 == g2
     @test custom_grad_called
 end
-
-end # module
diff --git a/test/PrecisionTests.jl b/test/PrecisionTests.jl
@@ -1,5 +1,3 @@
-module PrecisionTests
-
 using ReverseDiff, Test, LinearAlgebra, Statistics
 
 include("utils.jl")
@@ -53,5 +51,3 @@ for (n, d) in ((1.0e-200, 1.0e-200), (1.0e200, 1.0e200))
         @test ReverseDiff.gradient(f, [d]) ≈ [∂] rtol = 8 * eps(Float64)
     end
 end
-
-end # module
diff --git a/test/Project.toml b/test/Project.toml
@@ -9,6 +9,7 @@ IrrationalConstants = "92d709cd-6900-40b7-9082-c6be49f344b6"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogExpFunctions = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
 NaNMath = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
+ParallelTestRunner = "d3525ed8-44d0-4b2c-a655-542cee43accc"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
@@ -27,6 +28,7 @@ IrrationalConstants = "0.2"
 LinearAlgebra = "1"
 LogExpFunctions = "1"
 NaNMath = "1"
+ParallelTestRunner = "2.0.1"
 Random = "1"
 SpecialFunctions = "2"
 StaticArrays = "1.6.4"

diff --git a/test/TapeTests.jl b/test/TapeTests.jl
@@ -1,5 +1,3 @@
-module TapeTests
-
 using ReverseDiff, Test
 using ReverseDiff: SpecialInstruction, ScalarInstruction, NULL_TAPE
 
@@ -62,5 +60,3 @@ for Instr in (SpecialInstruction, ScalarInstruction)
     @test length(NULL_TAPE) == 0
     @test repr(MIME"text/plain"(), NULL_TAPE) == "0-element InstructionTape"
 end
-
-end # module
diff --git a/test/ThreadsTests.jl b/test/ThreadsTests.jl
@@ -0,0 +1,32 @@
+using ReverseDiff, Test
+
+# Run on a multithreaded worker, see `test_worker` in runtests.jl
+@test Threads.nthreads() > 1
+
+@testset "recording from multiple threads (#218)" begin
+    function g(x, i)
+        acc = zero(eltype(x))
+        for _ in 1:100
+            acc += (i * x[1] - x[2])^2
+        end
+        return acc + sum(abs2, i .* x)
+    end
+    function f(x)
+        s = Vector{Any}(undef, 64)
+        @sync for i in eachindex(s)
+            Threads.@spawn s[i] = g(x, i)
+        end
+        return sum(s)
+    end
+    f_serial(x) = sum(i -> g(x, i), 1:64)
+
+    x = [1.0, 2.0]
+    ∇f = ReverseDiff.gradient(f_serial, x)
+    for _ in 1:20
+        @test ReverseDiff.gradient(f, x) ≈ ∇f
+    end
+
+    # tape replay
+    tape = ReverseDiff.compile(ReverseDiff.GradientTape(f, x))
+    @test ReverseDiff.gradient!(similar(x), tape, x) ≈ ∇f
+end
diff --git a/test/TrackedTests.jl b/test/TrackedTests.jl
@@ -1,5 +1,3 @@
-module TrackedTests
-
 using ReverseDiff, Test
 using ReverseDiff: TrackedReal, TrackedArray
 
@@ -652,6 +650,7 @@ instr = first(recorded)
 @test instr.cache === nothing
 
 for T in (UInt, Int)
+    local ta_sub, idx, recorded, instr
     ta_sub = ta[:, T(1):T(2)]
     idx = ReverseDiff.index_iterable(axes(ta), (:, T(1):T(2)))
     @test collect(idx) == [(i, j) for i in 1:3, j in 1:2]
@@ -897,5 +896,3 @@ end
 @test occursin(r"^TrackedReal<\w{3}>\(1\.0, 0\.0, ---, ---\)$", repr(TrackedReal(1.0, 0.0)))
 ta = TrackedArray([1.0, 2.0], [0.0, 3.0], InstructionTape())
 @test occursin(r"^TrackedReal<\w{3}>\(2\.0, 3\.0, \w{3}, 2, \w{3}\)$", repr(ta[2]))
-
-end
diff --git a/test/api/ConfigTests.jl b/test/api/ConfigTests.jl
@@ -1,5 +1,3 @@
-module ConfigTests
-
 using ReverseDiff, Test
 
 include(joinpath(dirname(@__FILE__), "../utils.jl"))
@@ -75,5 +73,3 @@ cfg = HessianConfig(DiffResults.HessianResult(y), x, gtp, jtp)
 # These two act weird: work locally but fail in test mode
 #@test issimilar(cfg.gradient_config, GradientConfig(track(x, Int), gtp))
 #@test issimilar(cfg.jacobian_config, JacobianConfig(y, x, jtp))
-
-end # module
diff --git a/test/api/GradientTests.jl b/test/api/GradientTests.jl
@@ -1,5 +1,3 @@
-module GradientTests
-
 using DiffTests, ForwardDiff, ReverseDiff, StaticArrays, Test, LinearAlgebra
 
 include(joinpath(dirname(@__FILE__), "../utils.jl"))
@@ -489,33 +487,3 @@ end
     # a `Float64` buffer throws instead of zeroing the gradient
     @test_throws ArgumentError ReverseDiff.gradient(W -> loss(zeros(3, 5), W, H), W)
 end
-
-@testset "recording from multiple threads (#218)" begin
-    function g(x, i)
-        acc = zero(eltype(x))
-        for _ in 1:100
-            acc += (i * x[1] - x[2])^2
-        end
-        return acc + sum(abs2, i .* x)
-    end
-    function f(x)
-        s = Vector{Any}(undef, 64)
-        @sync for i in eachindex(s)
-            Threads.@spawn s[i] = g(x, i)
-        end
-        return sum(s)
-    end
-    f_serial(x) = sum(i -> g(x, i), 1:64)
-
-    x = [1.0, 2.0]
-    ∇f = ReverseDiff.gradient(f_serial, x)
-    for _ in 1:20
-        @test ReverseDiff.gradient(f, x) ≈ ∇f
-    end
-
-    # tape replay
-    tape = ReverseDiff.compile(ReverseDiff.GradientTape(f, x))
-    @test ReverseDiff.gradient!(similar(x), tape, x) ≈ ∇f
-end
-
-end # module
diff --git a/test/api/HessianTests.jl b/test/api/HessianTests.jl
@@ -1,5 +1,3 @@
-module HessianTests
-
 using DiffTests, ForwardDiff, ReverseDiff, StaticArrays, Test
 
 include(joinpath(dirname(@__FILE__), "../utils.jl"))
@@ -130,5 +128,3 @@ f251(x) = sum(abs2, x)
         @test DiffResults.hessian(result) == hess
     end
 end
-
-end # module
diff --git a/test/api/JacobianTests.jl b/test/api/JacobianTests.jl
@@ -1,5 +1,3 @@
-module JacobianTests
-
 using DiffTests, ForwardDiff, ReverseDiff, StaticArrays, Test
 
 include(joinpath(dirname(@__FILE__), "../utils.jl"))
@@ -269,57 +267,6 @@ for f in DiffTests.BINARY_MATRIX_TO_MATRIX_FUNCS
     test_binary_jacobian(f, rand(5, 5), rand(5, 5))
 end
 
-for f in (DiffTests.ARRAY_TO_ARRAY_FUNCS..., DiffTests.MATRIX_TO_MATRIX_FUNCS...)
-    test_println("ARRAY_TO_ARRAY_FUNCS + MATRIX_TO_MATRIX_FUNCS", f)
-
-    x = rand(5, 5)
-    test = ForwardDiff.jacobian(y -> ForwardDiff.jacobian(f, y), x)
-
-    # without JacobianTape
-
-    J = ReverseDiff.jacobian(y -> ReverseDiff.jacobian(f, y), x)
-    test_approx(J, test)
-
-    # with JacobianTape
-
-    tp = ReverseDiff.JacobianTape(y -> ReverseDiff.jacobian(f, y), rand(eltype(x), size(x)))
-    J = ReverseDiff.jacobian!(tp, x)
-    test_approx(J, test)
-end
-
-for f in DiffTests.BINARY_MATRIX_TO_MATRIX_FUNCS
-    test_println("BINARY_MATRIX_TO_MATRIX_FUNCS", f)
-
-    a, b = rand(5, 5), rand(5, 5)
-
-    test_val = f(a, b)
-    test_a = ForwardDiff.jacobian(y -> ForwardDiff.jacobian(x -> f(x, b), y), a)
-    test_b = ForwardDiff.jacobian(y -> ForwardDiff.jacobian(x -> f(a, x), y), b)
-
-    # without JacobianTape
-
-    Ja = ReverseDiff.jacobian(y -> ReverseDiff.jacobian(x -> f(x, b), y), a)
-    Jb = ReverseDiff.jacobian(y -> ReverseDiff.jacobian(x -> f(a, x), y), b)
-    test_approx(Ja, test_a)
-    test_approx(Jb, test_b)
-
-    # with JacobianTape
-
-    ra = ReverseDiff.JacobianTape(y -> ReverseDiff.jacobian(x -> f(x, b), y), rand(eltype(a), size(a)))
-    rb = ReverseDiff.JacobianTape(y -> ReverseDiff.jacobian(x -> f(a, x), y), rand(eltype(b), size(b)))
-    Ja = ReverseDiff.jacobian!(ra, a)
-    Jb = ReverseDiff.jacobian!(rb, b)
-    test_approx(Ja, test_a)
-    test_approx(Jb, test_b)
-
-    # The below will fail until support for the Jacobian of
-    # functions with multiple output arrays is implemented
-
-    # Ja, Jb = ReverseDiff.jacobian((x, y) -> ReverseDiff.jacobian(f, (x, y)), (a, b))
-    # test_approx(Ja test_a)
-    # test_approx(Jb test_b)
-end
-
 ############################################################################################
 
 f251(x) = x .^ 2
@@ -348,5 +295,3 @@ end
     # an element that is not a number has no single derivative to seed
     @test_throws ArgumentError ReverseDiff.jacobian(x -> [x, x], [1.0, 2.0])
 end
-
-end # module
diff --git a/test/api/NestedJacobianTests.jl b/test/api/NestedJacobianTests.jl
@@ -0,0 +1,54 @@
+using DiffTests, ForwardDiff, ReverseDiff, Test
+
+include("../utils.jl")
+
+for f in (DiffTests.ARRAY_TO_ARRAY_FUNCS..., DiffTests.MATRIX_TO_MATRIX_FUNCS...)
+    test_println("ARRAY_TO_ARRAY_FUNCS + MATRIX_TO_MATRIX_FUNCS", f)
+
+    x = rand(5, 5)
+    test = ForwardDiff.jacobian(y -> ForwardDiff.jacobian(f, y), x)
+
+    # without JacobianTape
+
+    J = ReverseDiff.jacobian(y -> ReverseDiff.jacobian(f, y), x)
+    test_approx(J, test)
+
+    # with JacobianTape
+
+    tp = ReverseDiff.JacobianTape(y -> ReverseDiff.jacobian(f, y), rand(eltype(x), size(x)))
+    J = ReverseDiff.jacobian!(tp, x)
+    test_approx(J, test)
+end
+
+for f in DiffTests.BINARY_MATRIX_TO_MATRIX_FUNCS
+    test_println("BINARY_MATRIX_TO_MATRIX_FUNCS", f)
+
+    a, b = rand(5, 5), rand(5, 5)
+
+    test_val = f(a, b)
+    test_a = ForwardDiff.jacobian(y -> ForwardDiff.jacobian(x -> f(x, b), y), a)
+    test_b = ForwardDiff.jacobian(y -> ForwardDiff.jacobian(x -> f(a, x), y), b)
+
+    # without JacobianTape
+
+    Ja = ReverseDiff.jacobian(y -> ReverseDiff.jacobian(x -> f(x, b), y), a)
+    Jb = ReverseDiff.jacobian(y -> ReverseDiff.jacobian(x -> f(a, x), y), b)
+    test_approx(Ja, test_a)
+    test_approx(Jb, test_b)
+
+    # with JacobianTape
+
+    ra = ReverseDiff.JacobianTape(y -> ReverseDiff.jacobian(x -> f(x, b), y), rand(eltype(a), size(a)))
+    rb = ReverseDiff.JacobianTape(y -> ReverseDiff.jacobian(x -> f(a, x), y), rand(eltype(b), size(b)))
+    Ja = ReverseDiff.jacobian!(ra, a)
+    Jb = ReverseDiff.jacobian!(rb, b)
+    test_approx(Ja, test_a)
+    test_approx(Jb, test_b)
+
+    # The below will fail until support for the Jacobian of
+    # functions with multiple output arrays is implemented
+
+    # Ja, Jb = ReverseDiff.jacobian((x, y) -> ReverseDiff.jacobian(f, (x, y)), (a, b))
+    # test_approx(Ja test_a)
+    # test_approx(Jb test_b)
+end
diff --git a/test/compat/CompatTests.jl b/test/compat/CompatTests.jl
@@ -1,5 +1,3 @@
-module CompatTests
-
 using FillArrays, ReverseDiff, Test
 
 @test ReverseDiff.gradient(fill(2.0, 3)) do x
@@ -9,5 +7,3 @@ end == fill(4.0, 3)
 @test ReverseDiff.gradient(fill(2.0, 3)) do x
     sum(abs2.(x .- (1:3)))
 end == [2, 0, -2]
-
-end
diff --git a/test/derivatives/BroadcastTests.jl b/test/derivatives/BroadcastTests.jl
@@ -1,5 +1,3 @@
-module BroadcastTests
-
 using ReverseDiff
 
 using ForwardDiff
@@ -686,5 +684,3 @@ end
     @test ReverseDiff.gradient!(tape3, x) == 2 .* x
     @test ReverseDiff.gradient!(ReverseDiff.compile(tape3), x) == 2 .* x
 end
-
-end # module
diff --git a/test/derivatives/ElementwiseBinaryTests1.jl b/test/derivatives/ElementwiseBinaryTests1.jl
@@ -0,0 +1,5 @@
+include("elementwise_utils.jl")
+
+for (M, fsym) in binary_diffrules()[1:2:end]
+    test_binary(M, fsym)
+end
diff --git a/test/derivatives/ElementwiseBinaryTests2.jl b/test/derivatives/ElementwiseBinaryTests2.jl
@@ -0,0 +1,5 @@
+include("elementwise_utils.jl")
+
+for (M, fsym) in binary_diffrules()[2:2:end]
+    test_binary(M, fsym)
+end