Error when differentiating a linear problem with Enzyme.jl

[albertomercurio]

Describe the bug 🐞

I get an error when differentiating a linear problem with Enzyme.jl. I can fix the error using the set_runtime_activity option, but I'm wondering why this is happening and if this can be fixed.

I don't know whether to put this issue here or in Enzyme.jl. Tell me if the other case is better.

Expected behavior

A correct computation of the gradient.

Minimal Reproducible Example 👇

using LinearAlgebra
using SparseArrays
using LinearSolve
using Zygote
using Enzyme
using BenchmarkTools

# %%

const N = 100
const A = sprand(N, N, 1/N)
const B = sprand(N, N, 1/N)
const x = rand(N)

function test(p)
    C = p[1] * A' * A + p[2] * B' * B + I

    prob = LinearProblem(C, x)
    sol = solve(prob, KrylovJL_GMRES())
    return sum(abs2, sol.u .- x)
end

# %%

test([1.0, 2.2])

# %%

Zygote.gradient(test, [1.0, 2.2]) # Works

# %%

Enzyme.gradient(Reverse, test, [1.0, 2.2]) # Doesn't work

Error & Stacktrace ⚠️

ERROR: Constant memory is stored (or returned) to a differentiable variable.
As a result, Enzyme cannot provably ensure correctness and throws this error.
This might be due to the use of a constant variable as temporary storage for active memory (https://enzyme.mit.edu/julia/stable/faq/#Runtime-Activity).
If Enzyme should be able to prove this use non-differentable, open an issue!
To work around this issue, either:
 a) rewrite this variable to not be conditionally active (fastest, but requires a code change), or
 b) set the Enzyme mode to turn on runtime activity (e.g. autodiff(set_runtime_activity(Reverse), ...) ). This will maintain correctness, but may slightly reduce performance.
Mismatched activity for:   store {} addrspace(10)* addrspacecast ({}* inttoptr (i64 4521255888 to {}*) to {} addrspace(10)*), {} addrspace(10)** %.fca.1.gep, align 8, !dbg !1206, !noalias !1212 const val: {} addrspace(10)* addrspacecast ({}* inttoptr (i64 4521255888 to {}*) to {} addrspace(10)*)

...

Environment (please complete the following information):

• Output of using Pkg; Pkg.status()

Status `~/GitHub/Research/Undef/Autodiff QuantumToolbox/Project.toml`
  [6e4b80f9] BenchmarkTools v1.6.0
  [a0c0ee7d] DifferentiationInterface v0.7.7
  [7da242da] Enzyme v0.13.72
  [26cc04aa] FiniteDifferences v0.12.32
  [f6369f11] ForwardDiff v1.1.0
  [b27dd330] GTPSA v1.4.7
  [7ed4a6bd] LinearSolve v3.38.0
  [1dea7af3] OrdinaryDiffEq v6.102.0
  [6c2fb7c5] QuantumToolbox v0.34.1
  [c0aeaf25] SciMLOperators v1.7.1
  [1ed8b502] SciMLSensitivity v7.89.0
  [e88e6eb3] Zygote v0.7.10

• Output of using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)

  [47edcb42] ADTypes v1.17.0
  [621f4979] AbstractFFTs v1.5.0
  [7d9f7c33] Accessors v0.1.42
  [79e6a3ab] Adapt v4.3.0
  [66dad0bd] AliasTables v1.1.3
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.20.0
  [4c555306] ArrayLayouts v1.11.2
  [a9b6321e] Atomix v1.1.2
  [6e4b80f9] BenchmarkTools v1.6.0
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [70df07ce] BracketingNonlinearSolve v1.3.0
  [fa961155] CEnum v0.5.0
  [2a0fbf3d] CPUSummary v0.2.7
  [7057c7e9] Cassette v0.3.14
  [082447d4] ChainRules v1.72.5
  [d360d2e6] ChainRulesCore v1.26.0
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.1
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.18.0
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [187b0558] ConstructionBase v1.6.0
  [adafc99b] CpuId v0.3.1
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
⌅ [864edb3b] DataStructures v0.18.22
  [e2d170a0] DataValueInterfaces v1.0.0
  [2b5f629d] DiffEqBase v6.186.0
  [459566f4] DiffEqCallbacks v4.9.0
  [77a26b50] DiffEqNoiseProcess v5.24.1
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [a0c0ee7d] DifferentiationInterface v0.7.7
  [b4f34e82] Distances v0.10.12
  [31c24e10] Distributions v0.25.120
  [ffbed154] DocStringExtensions v0.9.5
  [4e289a0a] EnumX v1.0.5
  [7da242da] Enzyme v0.13.72
  [f151be2c] EnzymeCore v0.8.12
  [7d51a73a] ExplicitImports v1.13.2
  [d4d017d3] ExponentialUtilities v1.27.0
  [e2ba6199] ExprTools v0.1.10
  [55351af7] ExproniconLite v0.10.14
  [7a1cc6ca] FFTW v1.9.0
  [7034ab61] FastBroadcast v0.3.5
  [9aa1b823] FastClosures v0.3.2
  [442a2c76] FastGaussQuadrature v1.0.2
  [a4df4552] FastPower v1.1.3
  [1a297f60] FillArrays v1.13.0
  [6a86dc24] FiniteDiff v2.28.1
  [26cc04aa] FiniteDifferences v0.12.32
  [f6369f11] ForwardDiff v1.1.0
  [f62d2435] FunctionProperties v0.1.2
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v0.1.3
  [d9f16b24] Functors v0.5.2
  [46192b85] GPUArraysCore v0.2.0
  [61eb1bfa] GPUCompiler v1.6.1
  [b27dd330] GTPSA v1.4.7
  [c145ed77] GenericSchur v0.5.5
  [86223c79] Graphs v1.13.1
  [076d061b] HashArrayMappedTries v0.2.0
  [34004b35] HypergeometricFunctions v0.3.28
  [7869d1d1] IRTools v0.4.15
  [615f187c] IfElse v0.1.1
  [40713840] IncompleteLU v0.2.1
  [d25df0c9] Inflate v0.1.5
  [3587e190] InverseFunctions v0.1.17
  [92d709cd] IrrationalConstants v0.2.4
  [82899510] IteratorInterfaceExtensions v1.0.0
  [692b3bcd] JLLWrappers v1.7.1
  [682c06a0] JSON v0.21.4
  [ae98c720] Jieko v0.2.1
  [ccbc3e58] JumpProcesses v9.17.0
  [63c18a36] KernelAbstractions v0.9.38
  [ba0b0d4f] Krylov v0.10.1
  [929cbde3] LLVM v9.4.2
  [b964fa9f] LaTeXStrings v1.4.0
  [10f19ff3] LayoutPointers v0.1.17
  [5078a376] LazyArrays v2.6.2
  [2d8b4e74] LevyArea v1.0.0
  [87fe0de2] LineSearch v0.1.4
  [d3d80556] LineSearches v7.4.0
  [7ed4a6bd] LinearSolve v3.38.0
  [2ab3a3ac] LogExpFunctions v0.3.29
  [1914dd2f] MacroTools v0.5.16
  [d125e4d3] ManualMemory v0.1.8
  [bb5d69b7] MaybeInplace v0.1.4
  [e1d29d7a] Missings v1.2.0
  [2e0e35c7] Moshi v0.3.7
  [46d2c3a1] MuladdMacro v0.2.4
  [d41bc354] NLSolversBase v7.10.0
  [2774e3e8] NLsolve v4.5.1
  [872c559c] NNlib v0.9.31
  [77ba4419] NaNMath v1.1.3
  [8913a72c] NonlinearSolve v4.10.0
  [be0214bd] NonlinearSolveBase v1.14.0
  [5959db7a] NonlinearSolveFirstOrder v1.7.0
  [9a2c21bd] NonlinearSolveQuasiNewton v1.8.0
  [26075421] NonlinearSolveSpectralMethods v1.3.0
  [d8793406] ObjectFile v0.5.0
  [429524aa] Optim v1.13.2
  [3bd65402] Optimisers v0.4.6
  [bac558e1] OrderedCollections v1.8.1
  [1dea7af3] OrdinaryDiffEq v6.102.0
  [89bda076] OrdinaryDiffEqAdamsBashforthMoulton v1.5.0
  [6ad6398a] OrdinaryDiffEqBDF v1.10.1
  [bbf590c4] OrdinaryDiffEqCore v1.30.0
  [50262376] OrdinaryDiffEqDefault v1.8.0
  [4302a76b] OrdinaryDiffEqDifferentiation v1.14.0
  [9286f039] OrdinaryDiffEqExplicitRK v1.4.0
  [e0540318] OrdinaryDiffEqExponentialRK v1.8.0
  [becaefa8] OrdinaryDiffEqExtrapolation v1.8.0
  [5960d6e9] OrdinaryDiffEqFIRK v1.16.0
  [101fe9f7] OrdinaryDiffEqFeagin v1.4.0
  [d3585ca7] OrdinaryDiffEqFunctionMap v1.5.0
  [d28bc4f8] OrdinaryDiffEqHighOrderRK v1.5.0
  [9f002381] OrdinaryDiffEqIMEXMultistep v1.7.0
  [521117fe] OrdinaryDiffEqLinear v1.6.0
  [1344f307] OrdinaryDiffEqLowOrderRK v1.6.0
  [b0944070] OrdinaryDiffEqLowStorageRK v1.6.0
  [127b3ac7] OrdinaryDiffEqNonlinearSolve v1.14.1
  [c9986a66] OrdinaryDiffEqNordsieck v1.4.0
  [5dd0a6cf] OrdinaryDiffEqPDIRK v1.6.0
  [5b33eab2] OrdinaryDiffEqPRK v1.4.0
  [04162be5] OrdinaryDiffEqQPRK v1.4.0
  [af6ede74] OrdinaryDiffEqRKN v1.5.0
  [43230ef6] OrdinaryDiffEqRosenbrock v1.17.0
  [2d112036] OrdinaryDiffEqSDIRK v1.7.0
  [669c94d9] OrdinaryDiffEqSSPRK v1.6.0
  [e3e12d00] OrdinaryDiffEqStabilizedIRK v1.6.0
  [358294b1] OrdinaryDiffEqStabilizedRK v1.4.0
  [fa646aed] OrdinaryDiffEqSymplecticRK v1.7.0
  [b1df2697] OrdinaryDiffEqTsit5 v1.5.0
  [79d7bb75] OrdinaryDiffEqVerner v1.6.0
  [90014a1f] PDMats v0.11.35
  [d96e819e] Parameters v0.12.3
  [69de0a69] Parsers v2.8.3
  [e409e4f3] PoissonRandom v0.4.6
  [f517fe37] Polyester v0.7.18
  [1d0040c9] PolyesterWeave v0.2.2
  [85a6dd25] PositiveFactorizations v0.2.4
  [d236fae5] PreallocationTools v0.4.33
⌅ [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.5.0
⌅ [08abe8d2] PrettyTables v2.4.0
  [43287f4e] PtrArrays v1.3.0
  [1fd47b50] QuadGK v2.11.2
  [6c2fb7c5] QuantumToolbox v0.34.1
  [74087812] Random123 v1.7.1
  [e6cf234a] RandomNumbers v1.6.0
  [c1ae055f] RealDot v0.1.0
  [3cdcf5f2] RecipesBase v1.3.4
  [731186ca] RecursiveArrayTools v3.37.1
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.1
  [ae5879a3] ResettableStacks v1.1.1
  [37e2e3b7] ReverseDiff v1.16.1
  [708f8203] Richardson v1.4.2
  [79098fc4] Rmath v0.8.0
  [7e49a35a] RuntimeGeneratedFunctions v0.5.15
  [94e857df] SIMDTypes v0.1.0
  [0bca4576] SciMLBase v2.115.0
  [19f34311] SciMLJacobianOperators v0.1.8
  [c0aeaf25] SciMLOperators v1.7.1
  [1ed8b502] SciMLSensitivity v7.89.0
  [53ae85a6] SciMLStructures v1.7.0
  [7e506255] ScopedValues v1.5.0
  [6c6a2e73] Scratch v1.3.0
  [efcf1570] Setfield v1.1.2
  [727e6d20] SimpleNonlinearSolve v2.7.0
  [699a6c99] SimpleTraits v0.9.5
  [ce78b400] SimpleUnPack v1.1.0
  [a2af1166] SortingAlgorithms v1.2.2
  [dc90abb0] SparseInverseSubset v0.1.2
  [0a514795] SparseMatrixColorings v0.4.21
  [276daf66] SpecialFunctions v2.5.1
  [aedffcd0] Static v1.2.0
  [0d7ed370] StaticArrayInterface v1.8.0
  [90137ffa] StaticArrays v1.9.15
  [1e83bf80] StaticArraysCore v1.4.3
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.7.1
  [2913bbd2] StatsBase v0.34.6
  [4c63d2b9] StatsFuns v1.5.0
  [789caeaf] StochasticDiffEq v6.81.0
  [7792a7ef] StrideArraysCore v0.5.8
  [892a3eda] StringManipulation v0.4.1
  [09ab397b] StructArrays v0.7.1
  [53d494c1] StructIO v0.3.1
  [2efcf032] SymbolicIndexingInterface v0.3.43
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.1
  [8290d209] ThreadingUtilities v0.5.5
  [a759f4b9] TimerOutputs v0.5.29
  [9f7883ad] Tracker v0.2.38
  [e689c965] Tracy v0.1.5
  [781d530d] TruncatedStacktraces v1.4.0
  [3a884ed6] UnPack v1.0.2
  [013be700] UnsafeAtomics v0.3.0
  [e88e6eb3] Zygote v0.7.10
  [700de1a5] ZygoteRules v0.2.7
  [7cc45869] Enzyme_jll v0.0.195+0
  [f5851436] FFTW_jll v3.3.11+0
  [a4739e29] GTPSA_jll v1.6.1+0
  [1d5cc7b8] IntelOpenMP_jll v2025.2.0+0
  [dad2f222] LLVMExtra_jll v0.0.37+2
  [ad6e5548] LibTracyClient_jll v0.9.1+6
  [856f044c] MKL_jll v2025.2.0+0
  [656ef2d0] OpenBLAS32_jll v0.3.29+0
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [f50d1b31] Rmath_jll v0.5.1+0
  [1317d2d5] oneTBB_jll v2022.0.0+0
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching v1.11.0
  [9fa8497b] Future v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [4af54fe1] LazyArtifacts v1.11.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.11.0
  [de0858da] Printf v1.11.0
  [9abbd945] Profile v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [1a1011a3] SharedArrays v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.1.1+0
  [deac9b47] LibCURL_jll v8.6.0+0
  [e37daf67] LibGit2_jll v1.7.2+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.6+0
  [14a3606d] MozillaCACerts_jll v2023.12.12
  [4536629a] OpenBLAS_jll v0.3.27+1
  [05823500] OpenLibm_jll v0.8.5+0
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.59.0+0
  [3f19e933] p7zip_jll v17.4.0+2

• Output of versioninfo()

Julia Version 1.11.6
Commit 9615af0f269 (2025-07-09 12:58 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: macOS (arm64-apple-darwin24.0.0)
  CPU: 8 × Apple M3
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, apple-m2)
Threads: 4 default, 0 interactive, 2 GC (on 4 virtual cores)
Environment:
  JULIA_EDITOR = code
  JULIA_VSCODE_REPL = 1

[AbdAlazezAhmed]

I just ran into a similar issue doing funny stuff with Ferrite. Using set_runtime_activity doesn't seem to resolve the issue:

function just_solve(lambda, solver)
   
  A = zeros(100,100)
  b = ones(100)
  for i in 1:size(A,1)
    A[i, i] += lambda
  end
  leadprob = LinearSolve.LinearProblem(
        A, b
  )
  lincache = init(leadprob, solver)
  LinearSolve.solve!(lincache)
  sum(lincache.u)
end
  grad = Enzyme.gradient(Reverse|>set_runtime_activity, just_solve, 0.3, Const(KrylovJL_CG()))

error:

ERROR: LoadError: Enzyme execution failed.
Enzyme: Augmented forward pass custom rule Tuple{EnzymeCore.EnzymeRules.RevConfigWidth{1, true, false, (false, true), true, false}, Const{typeof(solve!)}, Type{Const{SciMLBase.LinearSolution{Float64, 1, Vector{Float64}, Float64, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, LinearSolve.LinearCache{Matrix{Float64}, Vector{Float64}, Vector{Float64}, SciMLBase.NullParameters, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, Krylov.CgSolver{Float64, Float64, Vector{Float64}}, IdentityOperator, IdentityOperator, Float64, Bool, LinearSolveAdjoint{Missing}}, Krylov.SimpleStats{Float64}}}}, Duplicated{LinearSolve.LinearCache{Matrix{Float64}, Vector{Float64}, Vector{Float64}, SciMLBase.NullParameters, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, Krylov.CgSolver{Float64, Float64, Vector{Float64}}, IdentityOperator, IdentityOperator, Float64, Bool, LinearSolveAdjoint{Missing}}}} return type mismatch, expected EnzymeCore.EnzymeRules.AugmentedReturn{SciMLBase.LinearSolution{Float64, 1, Vector{Float64}, Float64, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, LinearSolve.LinearCache{Matrix{Float64}, Vector{Float64}, Vector{Float64}, SciMLBase.NullParameters, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, Krylov.CgSolver{Float64, Float64, Vector{Float64}}, IdentityOperator, IdentityOperator, Float64, Bool, LinearSolveAdjoint{Missing}}, Krylov.SimpleStats{Float64}}, Nothing, Any} found EnzymeCore.EnzymeRules.AugmentedReturn{SciMLBase.LinearSolution{Float64, 1, Vector{Float64}, Float64, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, LinearSolve.LinearCache{Matrix{Float64}, Vector{Float64}, Vector{Float64}, SciMLBase.NullParameters, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, Krylov.CgSolver{Float64, Float64, Vector{Float64}}, IdentityOperator, IdentityOperator, Float64, Bool, LinearSolveAdjoint{Missing}}, Krylov.SimpleStats{Float64}}, SciMLBase.LinearSolution{Float64, 1, Vector{Float64}, Float64, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, LinearSolve.LinearCache{Matrix{Float64}, Vector{Float64}, Vector{Float64}, SciMLBase.NullParameters, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, Krylov.CgSolver{Float64, Float64, Vector{Float64}}, IdentityOperator, IdentityOperator, Float64, Bool, LinearSolveAdjoint{Missing}}, Krylov.SimpleStats{Float64}}, Tuple{Vector{Float64}, Vector{Float64}, LinearSolve.LinearCache{Matrix{Float64}, Vector{Float64}, Vector{Float64}, SciMLBase.NullParameters, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, Krylov.CgSolver{Float64, Float64, Vector{Float64}}, IdentityOperator, IdentityOperator, Float64, Bool, LinearSolveAdjoint{Missing}}, Tuple{Matrix{Float64}}, Tuple{Vector{Float64}}}}

Stacktrace:
  [1] just_solve
    @ ~/Schreibtisch/repr/enzyme_slow.jl:109 [inlined]
  [2] just_solve
    @ ~/Schreibtisch/repr/enzyme_slow.jl:0 [inlined]
  [3] diffejulia_just_solve_62101_inner_83wrap
    @ ~/Schreibtisch/repr/enzyme_slow.jl:0
  [4] macro expansion
    @ ~/.julia/packages/Enzyme/4HcV9/src/compiler.jl:5613 [inlined]
  [5] enzyme_call
    @ ~/.julia/packages/Enzyme/4HcV9/src/compiler.jl:5147 [inlined]
  [6] CombinedAdjointThunk
    @ ~/.julia/packages/Enzyme/4HcV9/src/compiler.jl:5022 [inlined]
  [7] autodiff
    @ ~/.julia/packages/Enzyme/4HcV9/src/Enzyme.jl:517 [inlined]
  [8] autodiff
    @ ~/.julia/packages/Enzyme/4HcV9/src/Enzyme.jl:538 [inlined]
  [9] macro expansion
    @ ~/.julia/packages/Enzyme/4HcV9/src/sugar.jl:275 [inlined]
 [10] gradient(rm::ReverseMode{false, true, false, FFIABI, false, false}, f::typeof(just_solve), x::Float64, args::Const{KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, @Kwargs{}}})
    @ Enzyme ~/.julia/packages/Enzyme/4HcV9/src/sugar.jl:262
 [11] top-level scope
    @ ~/Schreibtisch/repr/enzyme_slow.jl

Edit: rememebering

LinearSolve.jl/ext/LinearSolveEnzymeExt.jl

Line 226 in 2f41c8e

error("Adjoint case currently not handled. Instead of using `solve!(cache); s1 = copy(cache.u) ...`, use `sol = solve!(cache); s1 = copy(sol.u)`.")

function just_solve(lambda)
  solver = KrylovJL_CG()
  A = zeros(100,100)
  b = ones(100)
  for i in 1:size(A,1)
    A[i, i] += lambda
  end
  leadprob = LinearSolve.LinearProblem(
        A, b
  )
  lincache = init(leadprob, solver)
  sol = LinearSolve.solve!(lincache)
  sum(copy(sol.u))
end
grad = Enzyme.gradient(Reverse|>set_runtime_activity, just_solve, 0.3)

Error:

ERROR: LoadError: Enzyme execution failed.
Enzyme: Return type SciMLBase.LinearSolution{Float64, 1, Vector{Float64}, Float64, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, LinearSolve.LinearCache{Matrix{Float64}, Vector{Float64}, Vector{Float64}, SciMLBase.NullParameters, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, Krylov.CgSolver{Float64, Float64, Vector{Float64}}, IdentityOperator, IdentityOperator, Float64, Bool, LinearSolveAdjoint{Missing}}, Krylov.SimpleStats{Float64}} has mixed internal activity types in evaluation of custom rule for MethodInstance for CommonSolve.solve!(::LinearSolve.LinearCache{Matrix{Float64}, Vector{Float64}, Vector{Float64}, SciMLBase.NullParameters, KrylovJL{typeof(Krylov.cg!), Int64, Nothing, Tuple{}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}}, Krylov.CgSolver{Float64, Float64, Vector{Float64}}, IdentityOperator, IdentityOperator, Float64, Bool, LinearSolveAdjoint{Missing}}). See https://enzyme.mit.edu/julia/stable/faq/#Mixed-activity for more information

Stacktrace:
  [1] just_solve
    @ ~/Schreibtisch/repr/enzyme_slow.jl:109 [inlined]
  [2] diffejulia_just_solve_62116wrap
    @ ~/Schreibtisch/repr/enzyme_slow.jl:0
  [3] macro expansion
    @ ~/.julia/packages/Enzyme/4HcV9/src/compiler.jl:5613 [inlined]
  [4] enzyme_call
    @ ~/.julia/packages/Enzyme/4HcV9/src/compiler.jl:5147 [inlined]
  [5] CombinedAdjointThunk
    @ ~/.julia/packages/Enzyme/4HcV9/src/compiler.jl:5022 [inlined]
  [6] autodiff
    @ ~/.julia/packages/Enzyme/4HcV9/src/Enzyme.jl:517 [inlined]
  [7] autodiff
    @ ~/.julia/packages/Enzyme/4HcV9/src/Enzyme.jl:538 [inlined]
  [8] macro expansion
    @ ~/.julia/packages/Enzyme/4HcV9/src/sugar.jl:331 [inlined]
  [9] gradient(::ReverseMode{false, true, false, FFIABI, false, false}, ::typeof(just_solve), ::Float64)
    @ Enzyme ~/.julia/packages/Enzyme/4HcV9/src/sugar.jl:262
 [10] top-level scope

Edit once again: MB I was trying with V2