ParallelMALASampler + DynamicPPL + Enzyme errors

[penelopeysm]

Following up from #20 (comment).

I think both errors look most likely to be genuine Enzyme bugs (there's a possibility it could be a DI thing but I don't suspect that at first glance). I'm not super surprised, we've never really tested anything beyond just gradients so there are definitely more bugs out there to be squished :-)

With Enzyme bugs traditionally what I've done is to try to minimise them to strip away all the extra bits. For example, I'm fairly sure this can probably be stripped down to something that calls hvp on a function that calls logpdf(dist, x). I'd be happy to help with that (at some point in time).

Setup

I'm running this with the code currently on #20 (my fork), but I get the same results with current main (ed83efc).

(jl) pkg> st
Status `~/jl/Project.toml`
  [31c24e10] Distributions v0.25.125
  [366bfd00] DynamicPPL v0.41.7
  [1a970f40] ParallelMCMC v0.0.2 `ParallelMCMC.jl`

(jl) pkg> st --manifest
Status `~/jl/Manifest.toml`
  [47edcb42] ADTypes v1.22.0
  [621f4979] AbstractFFTs v1.5.0
  [80f14c24] AbstractMCMC v5.15.1
  [7a57a42e] AbstractPPL v0.14.2
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.44
  [79e6a3ab] Adapt v4.5.2
  [66dad0bd] AliasTables v1.1.3
  [dce04be8] ArgCheck v2.5.0
  [a9b6321e] Atomix v1.1.3
  [13072b0f] AxisAlgorithms v1.1.0
  [39de3d68] AxisArrays v0.4.8
  [ab4f0b2a] BFloat16s v0.6.1
  [198e06fe] BangBang v0.4.9
  [76274a88] Bijectors v0.15.24
  [fa961155] CEnum v0.5.0
⌃ [052768ef] CUDA v5.11.2
  [1af6417a] CUDA_Runtime_Discovery v2.0.0
  [d360d2e6] ChainRulesCore v1.26.1
  [0ca39b1e] Chairmarks v1.3.1
  [9e997f8a] ChangesOfVariables v0.1.10
  [38540f10] CommonSolve v0.2.6
  [34da2185] Compat v4.18.1
  [a33af91c] CompositionsBase v0.1.2
  [88cd18e8] ConsoleProgressMonitor v0.1.2
  [187b0558] ConstructionBase v1.6.0
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.19.4
  [e2d170a0] DataValueInterfaces v1.0.0
  [b429d917] DensityInterface v0.4.0
  [a0c0ee7d] DifferentiationInterface v0.7.17
  [31c24e10] Distributions v0.25.125
  [ffbed154] DocStringExtensions v0.9.5
  [366bfd00] DynamicPPL v0.41.7
  [7da242da] Enzyme v0.13.140
  [f151be2c] EnzymeCore v0.8.20
  [e2ba6199] ExprTools v0.1.10
  [b86e33f2] FFTA v0.3.1
  [1a297f60] FillArrays v1.16.0
  [d9f16b24] Functors v0.5.2
  [0c68f7d7] GPUArrays v11.5.3
  [46192b85] GPUArraysCore v0.2.0
  [61eb1bfa] GPUCompiler v1.9.1
  [096a3bc2] GPUToolbox v1.1.1
  [076d061b] HashArrayMappedTries v0.2.0
  [34004b35] HypergeometricFunctions v0.3.28
  [22cec73e] InitialValues v0.3.1
  [18e54dd8] IntegerMathUtils v0.1.3
  [a98d9a8b] Interpolations v0.16.2
  [8197267c] IntervalSets v0.7.14
  [3587e190] InverseFunctions v0.1.17
  [41ab1584] InvertedIndices v1.3.1
  [92d709cd] IrrationalConstants v0.2.6
  [c8e1da08] IterTools v1.10.0
  [82899510] IteratorInterfaceExtensions v1.0.0
  [692b3bcd] JLLWrappers v1.7.1
  [682c06a0] JSON v1.5.2
  [63c18a36] KernelAbstractions v0.9.41
  [5ab0869b] KernelDensity v0.6.11
  [929cbde3] LLVM v9.7.1
  [8b046642] LLVMLoopInfo v1.0.0
  [b964fa9f] LaTeXStrings v1.4.0
  [1d6d02ad] LeftChildRightSiblingTrees v0.2.1
  [6fdf6af0] LogDensityProblems v2.2.0
  [2ab3a3ac] LogExpFunctions v0.3.29
  [e6f89c97] LoggingExtras v1.2.0
  [c7f686f2] MCMCChains v7.7.0
  [be115224] MCMCDiagnosticTools v0.3.17
  [e80e1ace] MLJModelInterface v1.12.1
  [1914dd2f] MacroTools v0.5.16
  [dbb5928d] MappedArrays v0.4.3
  [e1d29d7a] Missings v1.2.0
  [46d2c3a1] MuladdMacro v0.2.4
  [5da4648a] NVTX v1.0.3
  [c020b1a1] NaturalSort v1.0.0
  [d8793406] ObjectFile v0.5.0
  [6fe1bfb0] OffsetArrays v1.17.0
  [bac558e1] OrderedCollections v1.8.1
  [90014a1f] PDMats v0.11.37
  [1a970f40] ParallelMCMC v0.0.2 `ParallelMCMC.jl`
  [69de0a69] Parsers v2.8.4
  [569bd051] PartitionedDistributions v0.0.1
⌅ [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.5.2
  [08abe8d2] PrettyTables v3.3.2
  [27ebfcd6] Primes v0.5.7
  [33c8b6b6] ProgressLogging v0.1.6
  [92933f4c] ProgressMeter v1.11.0
  [43287f4e] PtrArrays v1.4.0
  [1fd47b50] QuadGK v2.11.3
  [74087812] Random123 v1.7.1
  [e6cf234a] RandomNumbers v1.6.0
  [b3c3ace0] RangeArrays v0.3.2
  [c84ed2f1] Ratios v0.4.5
  [3cdcf5f2] RecipesBase v1.3.4
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.1
  [79098fc4] Rmath v0.9.0
  [f2b01f46] Roots v3.0.0
  [30f210dd] ScientificTypesBase v3.1.0
  [7e506255] ScopedValues v1.6.2
  [6c6a2e73] Scratch v1.3.0
  [a2af1166] SortingAlgorithms v1.2.2
  [276daf66] SpecialFunctions v2.7.2
  [90137ffa] StaticArrays v1.9.18
  [1e83bf80] StaticArraysCore v1.4.4
  [64bff920] StatisticalTraits v3.5.0
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.8.0
  [2913bbd2] StatsBase v0.34.10
  [4c63d2b9] StatsFuns v1.5.2
  [892a3eda] StringManipulation v0.4.4
  [53d494c1] StructIO v0.3.1
  [ec057cc2] StructUtils v2.8.1
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.1
  [5d786b92] TerminalLoggers v0.1.7
  [e689c965] Tracy v0.1.6
  [013be700] UnsafeAtomics v0.3.1
  [efce3f68] WoodburyMatrices v1.1.0
  [d1e2174e] CUDA_Compiler_jll v0.4.3+0
  [4ee394cb] CUDA_Driver_jll v13.2.1+0
  [76a88914] CUDA_Runtime_jll v0.21.0+1
  [7cc45869] Enzyme_jll v0.0.258+0
  [9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0
  [dad2f222] LLVMExtra_jll v0.0.42+0
  [ad6e5548] LibTracyClient_jll v0.13.1+0
  [e98f9f5b] NVTX_jll v3.2.2+0
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [f50d1b31] Rmath_jll v0.5.1+0
  [1e29f10c] demumble_jll v1.3.0+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
  [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
  [3fa0cd96] REPL 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
  [f489334b] StyledStrings v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [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
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`

julia> versioninfo()
Julia Version 1.11.9
Commit 53a02c0720c (2026-02-06 00:27 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: macOS (arm64-apple-darwin24.0.0)
  CPU: 10 × Apple M1 Pro
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, apple-m1)
Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores)

Normal works

using DynamicPPL, Distributions, ParallelMCMC, LinearAlgebra

sampler = ParallelMALASampler(0.1)

@model f1() = x ~ Normal()
sample(DensityModel(f1()), sampler, 500)

MvNormal fails

@model f2() = x ~ MvNormal(zeros(2), I)
sample(DensityModel(f2()), sampler, 500)

#=
ERROR: AssertionError: ety == eltype(vt)
Stacktrace:
  [1] sret_ty(fn::LLVM.Function, idx::Int64)
    @ Enzyme ~/.julia/packages/Enzyme/9OkvN/src/utils.jl:575
  [2] removeDeadArgs!(mod::LLVM.Module, tm::LLVM.TargetMachine, post_gc_fixup::Bool)
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/llvm/transforms.jl:2667
  [3] optimize!(mod::LLVM.Module, tm::LLVM.TargetMachine)
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler/optimize.jl:200
  [4] compile_unhooked(output::Symbol, job::GPUCompiler.CompilerJob{…})
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:5493
  [5] #compile#163
    @ ~/.julia/packages/GPUCompiler/Yuvf5/src/driver.jl:67 [inlined]
  [6] compile
    @ ~/.julia/packages/GPUCompiler/Yuvf5/src/driver.jl:55 [inlined]
  [7] _thunk(job::GPUCompiler.CompilerJob{…}, postopt::Bool)
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:6776
  [8] _thunk
    @ ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:6774 [inlined]
  [9] cached_compilation
    @ ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:6832 [inlined]
 [10] thunkbase(mi::Core.MethodInstance, World::UInt64, FA::Type{…}, A::Type{…}, TT::Type, Mode::Enzyme.API.CDerivativeMode, width::Int64, ModifiedBetween::NTuple{…} where N, ReturnPrimal::Bool, ShadowInit::Bool, ABI::Type, ErrIfFuncWritten::Bool, RuntimeActivity::Bool, StrongZero::Bool, edges::Vector{…})
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:6948
 [11] thunk_generator(world::UInt64, source::Union{…}, FA::Type, A::Type, TT::Type, Mode::Enzyme.API.CDerivativeMode, Width::Int64, ModifiedBetween::NTuple{…} where N, ReturnPrimal::Bool, ShadowInit::Bool, ABI::Type, ErrIfFuncWritten::Bool, RuntimeActivity::Bool, StrongZero::Bool, self::Any, fakeworld::Any, fa::Type, a::Type, tt::Type, mode::Type, width::Type, modifiedbetween::Type, returnprimal::Type, shadowinit::Type, abi::Type, erriffuncwritten::Type, runtimeactivity::Type, strongzero::Type)
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:7092
 [12] autodiff
    @ ~/.julia/packages/Enzyme/9OkvN/src/Enzyme.jl:665 [inlined]
 [13] autodiff
    @ ~/.julia/packages/Enzyme/9OkvN/src/Enzyme.jl:569 [inlined]
 [14] pushforward(::typeof(DifferentiationInterface.shuffled_gradient), ::DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{…}, ::ADTypes.AutoEnzyme{…}, ::Vector{…}, ::Tuple{…}, ::DifferentiationInterface.FunctionContext{…}, ::DifferentiationInterface.Constant{…}, ::DifferentiationInterface.Constant{…})
    @ DifferentiationInterfaceEnzymeExt ~/.julia/packages/DifferentiationInterface/IS0Dg/ext/DifferentiationInterfaceEnzymeExt/forward_onearg.jl:76
 [15] hvp
    @ ~/.julia/packages/DifferentiationInterface/IS0Dg/src/second_order/hvp.jl:331 [inlined]
 [16] _logdensity_hvp_prepared
    @ ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:166 [inlined]
 [17] #12
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:396 [inlined]
 [18] mala_step_taped_and_jvp!(x_next::Vector{…}, jvp_out::Vector{…}, ws::ParallelMCMC.MALA.MALAWorkspace{…}, logp::ParallelMCMC.LogDensityProblemPrimal{…}, gradlogp::ParallelMCMC.LogDensityProblemGradient{…}, x::Vector{…}, ε::Float64, ξ::SubArray{…}, u::Float64, v::Vector{…}, hvp_fn::ParallelMCMC.var"#12#18"{…}; cholM::Nothing)
    @ ParallelMCMC.MALA ~/jl/ParallelMCMC.jl/src/MALA/MALA.jl:766
 [19] mala_step_taped_and_jvp!
    @ ~/jl/ParallelMCMC.jl/src/MALA/MALA.jl:730 [inlined]
 [20] #mala_step_taped_and_jvp#27
    @ ~/jl/ParallelMCMC.jl/src/MALA/MALA.jl:809 [inlined]
 [21] mala_step_taped_and_jvp
    @ ~/jl/ParallelMCMC.jl/src/MALA/MALA.jl:795 [inlined]
 [22] #15
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:411 [inlined]
 [23] deer_update!(ws::ParallelMCMC.DEER.DEERWorkspace{…}, S_out::Matrix{…}, rec::ParallelMCMC.DEER.TapedRecursion{…}, s0_in::Vector{…}, S_in::Matrix{…}; jacobian::Symbol, damping::Float64, probes::Int64, rng::Random.TaskLocalRNG)
    @ ParallelMCMC.DEER ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:336
 [24] deer_update!
    @ ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:275 [inlined]
 [25] solve(rec::ParallelMCMC.DEER.TapedRecursion{…}, s0_in::Vector{…}; init::Nothing, tol_abs::Float64, tol_rel::Float64, maxiter::Int64, jacobian::Symbol, damping::Float64, probes::Int64, rng::Random.TaskLocalRNG, return_info::Bool, workspace::ParallelMCMC.DEER.DEERWorkspace{…}, copy_result::Bool)
    @ ParallelMCMC.DEER ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:455
 [26] solve
    @ ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:406 [inlined]
 [27] #_deer_solve_new_tape#24
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:512 [inlined]
 [28] macro expansion
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:671 [inlined]
 [29] (::ParallelMCMC.var"#33#34"{…})()
    @ ParallelMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
 [30] with_logstate(f::ParallelMCMC.var"#33#34"{…}, logstate::Base.CoreLogging.LogState)
    @ Base.CoreLogging ./logging/logging.jl:526
 [31] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{…}})
    @ Base.CoreLogging ./logging/logging.jl:637
 [32] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
    @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
 [33] macro expansion
    @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
 [34] _sample_parallel_mala_blocks(rng::Random.TaskLocalRNG, model::DensityModel{…}, sampler::ParallelMALASampler{…}, N::Int64; initial_params::Nothing, progress::Bool, progressname::String)
    @ ParallelMCMC ~/jl/ParallelMCMC.jl/src/interface.jl:667
 [35] _sample_parallel_mala_blocks
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:645 [inlined]
 [36] #mcmcsample#36
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:778 [inlined]
 [37] mcmcsample
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:720 [inlined]
 [38] #sample#21
    @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:61 [inlined]
 [39] sample
    @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:54 [inlined]
 [40] #sample#20
    @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:23 [inlined]
 [41] sample(model_or_logdensity::DensityModel{…}, sampler::ParallelMALASampler{…}, N_or_isdone::Int64)
    @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:20
 [42] top-level scope
    @ REPL[20]:1
Some type information was truncated. Use `show(err)` to see complete types.
=#

Dirichlet fails with a different error

@model f3() = x ~ Dirichlet(ones(3))
sample(DensityModel(f3()), sampler, 500)

#=
ERROR: BoundsError: attempt to access 1-element Vector{LLVM.LLVMType} at index [2]
Stacktrace:
  [1] throw_boundserror(A::Vector{LLVM.LLVMType}, I::Tuple{Int64})
    @ Base ./essentials.jl:14
  [2] getindex
    @ ./essentials.jl:916 [inlined]
  [3] handle_param(args::Vector{…}, codegen_types::Vector{…}, source_typ::Type, rooted_typ::Union{…}, source_i::Int64, orig_i::Int64, arg_jl_i::Int64, codegen_i::Int64, last_cc::GPUCompiler.ArgumentCC, parmsRemoved::Vector{…})
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/typeutils/jltypes.jl:180
  [4] classify_arguments(source_sig::Type, codegen_ft::LLVM.FunctionType, has_sret::Bool, has_returnroots::Bool, has_swiftself::Bool, parmsRemoved::Vector{…}, mi::Core.MethodInstance, world::UInt64)
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/typeutils/jltypes.jl:303
  [5] set_module_types!(interp::Enzyme.Compiler.Interpreter.EnzymeInterpreter{…}, mod::LLVM.Module, primalf::LLVM.Function, job::GPUCompiler.CompilerJob{…}, edges::Vector{…}, run_enzyme::Bool, mode::Enzyme.API.CDerivativeMode)
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:1153
  [6] compile_unhooked(output::Symbol, job::GPUCompiler.CompilerJob{…})
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:5344
  [7] #compile#163
    @ ~/.julia/packages/GPUCompiler/Yuvf5/src/driver.jl:67 [inlined]
  [8] compile
    @ ~/.julia/packages/GPUCompiler/Yuvf5/src/driver.jl:55 [inlined]
  [9] _thunk(job::GPUCompiler.CompilerJob{…}, postopt::Bool)
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:6776
 [10] _thunk
    @ ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:6774 [inlined]
 [11] cached_compilation
    @ ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:6832 [inlined]
 [12] thunkbase(mi::Core.MethodInstance, World::UInt64, FA::Type{…}, A::Type{…}, TT::Type, Mode::Enzyme.API.CDerivativeMode, width::Int64, ModifiedBetween::NTuple{…} where N, ReturnPrimal::Bool, ShadowInit::Bool, ABI::Type, ErrIfFuncWritten::Bool, RuntimeActivity::Bool, StrongZero::Bool, edges::Vector{…})
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:6948
 [13] thunk_generator(world::UInt64, source::Union{…}, FA::Type, A::Type, TT::Type, Mode::Enzyme.API.CDerivativeMode, Width::Int64, ModifiedBetween::NTuple{…} where N, ReturnPrimal::Bool, ShadowInit::Bool, ABI::Type, ErrIfFuncWritten::Bool, RuntimeActivity::Bool, StrongZero::Bool, self::Any, fakeworld::Any, fa::Type, a::Type, tt::Type, mode::Type, width::Type, modifiedbetween::Type, returnprimal::Type, shadowinit::Type, abi::Type, erriffuncwritten::Type, runtimeactivity::Type, strongzero::Type)
    @ Enzyme.Compiler ~/.julia/packages/Enzyme/9OkvN/src/compiler.jl:7092
 [14] autodiff
    @ ~/.julia/packages/Enzyme/9OkvN/src/Enzyme.jl:665 [inlined]
 [15] autodiff
    @ ~/.julia/packages/Enzyme/9OkvN/src/Enzyme.jl:569 [inlined]
 [16] pushforward(::typeof(DifferentiationInterface.shuffled_gradient), ::DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{…}, ::ADTypes.AutoEnzyme{…}, ::Vector{…}, ::Tuple{…}, ::DifferentiationInterface.FunctionContext{…}, ::DifferentiationInterface.Constant{…}, ::DifferentiationInterface.Constant{…})
    @ DifferentiationInterfaceEnzymeExt ~/.julia/packages/DifferentiationInterface/IS0Dg/ext/DifferentiationInterfaceEnzymeExt/forward_onearg.jl:76
 [17] hvp
    @ ~/.julia/packages/DifferentiationInterface/IS0Dg/src/second_order/hvp.jl:331 [inlined]
 [18] _logdensity_hvp_prepared
    @ ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:166 [inlined]
 [19] #12
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:396 [inlined]
 [20] mala_step_taped_and_jvp!(x_next::Vector{…}, jvp_out::Vector{…}, ws::ParallelMCMC.MALA.MALAWorkspace{…}, logp::ParallelMCMC.LogDensityProblemPrimal{…}, gradlogp::ParallelMCMC.LogDensityProblemGradient{…}, x::Vector{…}, ε::Float64, ξ::SubArray{…}, u::Float64, v::Vector{…}, hvp_fn::ParallelMCMC.var"#12#18"{…}; cholM::Nothing)
    @ ParallelMCMC.MALA ~/jl/ParallelMCMC.jl/src/MALA/MALA.jl:766
 [21] mala_step_taped_and_jvp!
    @ ~/jl/ParallelMCMC.jl/src/MALA/MALA.jl:730 [inlined]
 [22] #mala_step_taped_and_jvp#27
    @ ~/jl/ParallelMCMC.jl/src/MALA/MALA.jl:809 [inlined]
 [23] mala_step_taped_and_jvp
    @ ~/jl/ParallelMCMC.jl/src/MALA/MALA.jl:795 [inlined]
 [24] #15
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:411 [inlined]
 [25] deer_update!(ws::ParallelMCMC.DEER.DEERWorkspace{…}, S_out::Matrix{…}, rec::ParallelMCMC.DEER.TapedRecursion{…}, s0_in::Vector{…}, S_in::Matrix{…}; jacobian::Symbol, damping::Float64, probes::Int64, rng::Random.TaskLocalRNG)
    @ ParallelMCMC.DEER ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:336
 [26] deer_update!
    @ ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:275 [inlined]
 [27] solve(rec::ParallelMCMC.DEER.TapedRecursion{…}, s0_in::Vector{…}; init::Nothing, tol_abs::Float64, tol_rel::Float64, maxiter::Int64, jacobian::Symbol, damping::Float64, probes::Int64, rng::Random.TaskLocalRNG, return_info::Bool, workspace::ParallelMCMC.DEER.DEERWorkspace{…}, copy_result::Bool)
    @ ParallelMCMC.DEER ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:455
 [28] solve
    @ ~/jl/ParallelMCMC.jl/src/DEER/DEER.jl:406 [inlined]
 [29] #_deer_solve_new_tape#24
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:512 [inlined]
 [30] macro expansion
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:671 [inlined]
 [31] (::ParallelMCMC.var"#33#34"{…})()
    @ ParallelMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
 [32] with_logstate(f::ParallelMCMC.var"#33#34"{…}, logstate::Base.CoreLogging.LogState)
    @ Base.CoreLogging ./logging/logging.jl:526
 [33] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{…}})
    @ Base.CoreLogging ./logging/logging.jl:637
 [34] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
    @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
 [35] macro expansion
    @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
 [36] _sample_parallel_mala_blocks(rng::Random.TaskLocalRNG, model::DensityModel{…}, sampler::ParallelMALASampler{…}, N::Int64; initial_params::Nothing, progress::Bool, progressname::String)
    @ ParallelMCMC ~/jl/ParallelMCMC.jl/src/interface.jl:667
 [37] _sample_parallel_mala_blocks
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:645 [inlined]
 [38] #mcmcsample#36
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:778 [inlined]
 [39] mcmcsample
    @ ~/jl/ParallelMCMC.jl/src/interface.jl:720 [inlined]
 [40] #sample#21
    @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:61 [inlined]
 [41] sample
    @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:54 [inlined]
 [42] #sample#20
    @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:23 [inlined]
 [43] sample(model_or_logdensity::DensityModel{…}, sampler::ParallelMALASampler{…}, N_or_isdone::Int64)
    @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:20
 [44] top-level scope
    @ REPL[28]:1
Some type information was truncated. Use `show(err)` to see complete types.
=#

[rsenne]

AH the Normal model working makes sense. This was my test run i was able to get working which I naively assumed was evidence i fixed it completely. Thank you this is very helpful!

[penelopeysm]

You don't need to do this, but in case it's of interest, I made a specific Claude skill for minimising AD bugs (or at least attempting to do so). https://github.com/TuringLang/DynamicPPL.jl/tree/main/.claude/skills/minimize-ad-bug It really guzzles tokens like nobody's business so I've not used it too much, but I've set it on the MvNormal case so maybe it'll come up with something.

[penelopeysm]

Boiled it down to this: EnzymeAD/Enzyme.jl#3067 It may well be that there's more than one error present but we won't know until this one is fixed

[gdalle]

As always, happy to help with DI errors, real or imagined ;)

[rsenne]

Hi @penelopeysm that's great you found the bug so quickly--did your Claude plugin do that? How hard do you think that would be to fix? I'd be interested in taking a crack at it later this week

and thanks @gdalle I'll never say no to your help :) DI is great by the way, first time I've had the chance to use it. Will probably port it over to my other projects at some point

[penelopeysm]

I think it was about 50% Claude and 50% me haha. As for how hard to fix, I have no idea as I've never looked into Enzyme's actual codebase!

[wsmoses]

I can't presently reproduce any of the errors above (with latest enzyme, which did introduce potentially relevant fixes).

Can you confirm what still does or doesn't work and open issues?

[rsenne]

Hi @wsmoses -- sorry for the late reply. Using the latest version of Enzyme resolved the MvNormal example on my end, however, when attempting the Dirichlet example I am met with what seems to be the same error as @penelopeysm.

ERROR: LoadError: BoundsError: attempt to access 1-element Vector{LLVM.LLVMType} at index [2]
Stacktrace:
  [1] throw_boundserror(A::Vector{LLVM.LLVMType}, I::Tuple{Int64})
    @ Base ./essentials.jl:15
  [2] getindex
    @ ./essentials.jl:919 [inlined]
  [3] handle_param(args::Vector{Any}, codegen_types::Vector{LLVM.LLVMType}, source_typ::Type, rooted_typ::Union{Nothing, Type}, source_i::Int64, orig_i::Int64, arg_jl_i::Int64, codegen_i::Int64, last_cc::GPUCompiler.ArgumentCC, parmsRemoved::Vector{UInt64})
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/typeutils/jltypes.jl:180
  [4] classify_arguments(source_sig::Type, codegen_ft::LLVM.FunctionType, has_sret::Bool, has_returnroots::Bool, has_swiftself::Bool, parmsRemoved::Vector{UInt64}, mi::Core.MethodInstance, world::UInt64)
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/typeutils/jltypes.jl:303
  [5] set_module_types!(interp::Enzyme.Compiler.Interpreter.EnzymeInterpreter{Nothing}, mod::LLVM.Module, primalf::LLVM.Function, job::GPUCompiler.CompilerJob{Enzyme.Compiler.EnzymeTarget{GPUCompiler.NativeCompilerTarget}, Enzyme.Compiler.EnzymeCompilerParams{Enzyme.Compiler.PrimalCompilerParams}}, edges::Vector{Any}, run_enzyme::Bool, mode::Enzyme.API.CDerivativeMode)
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:1156
  [6] compile_unhooked(output::Symbol, job::GPUCompiler.CompilerJob{Enzyme.Compiler.EnzymeTarget{GPUCompiler.NativeCompilerTarget}, Enzyme.Compiler.EnzymeCompilerParams{Enzyme.Compiler.PrimalCompilerParams}})
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:5401
  [7] #compile#94
    @ /projectnb/ssmsvi/rsenne/.julia/packages/GPUCompiler/KwfWk/src/driver.jl:67 [inlined]
  [8] compile
    @ /projectnb/ssmsvi/rsenne/.julia/packages/GPUCompiler/KwfWk/src/driver.jl:55 [inlined]
  [9] _thunk(job::GPUCompiler.CompilerJob{Enzyme.Compiler.EnzymeTarget{GPUCompiler.NativeCompilerTarget}, Enzyme.Compiler.EnzymeCompilerParams{Enzyme.Compiler.PrimalCompilerParams}}, postopt::Bool)
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:6853
 [10] _thunk
    @ /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:6851 [inlined]
 [11] cached_compilation
    @ /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:6921 [inlined]
 [12] thunkbase(mi::Core.MethodInstance, World::UInt64, FA::Type{<:EnzymeCore.Annotation}, A::Type{<:EnzymeCore.Annotation}, TT::Type, Mode::Enzyme.API.CDerivativeMode, width::Int64, ModifiedBetween::NTuple{N, Bool} where N, ReturnPrimal::Bool, ShadowInit::Bool, ABI::Type, ErrIfFuncWritten::Bool, RuntimeActivity::Bool, StrongZero::Bool, edges::Vector{Any})
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:7037
 [13] thunk_generator(world::UInt64, source::Union{LineNumberNode, Method}, FA::Type, A::Type, TT::Type, Mode::Enzyme.API.CDerivativeMode, Width::Int64, ModifiedBetween::NTuple{N, Bool} where N, ReturnPrimal::Bool, ShadowInit::Bool, ABI::Type, ErrIfFuncWritten::Bool, RuntimeActivity::Bool, StrongZero::Bool, self::Any, fakeworld::Any, fa::Type, a::Type, tt::Type, mode::Type, width::Type, modifiedbetween::Type, returnprimal::Type, shadowinit::Type, abi::Type, erriffuncwritten::Type, runtimeactivity::Type, strongzero::Type)
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:7181
 [14] autodiff
    @ /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/Enzyme.jl:673 [inlined]
 [15] autodiff
    @ /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/Enzyme.jl:577 [inlined]
 [16] pushforward(::typeof(DifferentiationInterface.shuffled_gradient), ::DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, ::ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ::Vector{Float64}, ::Tuple{Vector{Float64}}, ::DifferentiationInterface.FunctionContext{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ::DifferentiationInterface.Constant{ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ::DifferentiationInterface.Constant{DifferentiationInterface.Rewrap{0, Tuple{}}})
    @ DifferentiationInterfaceEnzymeExt /projectnb/ssmsvi/rsenne/.julia/packages/DifferentiationInterface/f85Vv/ext/DifferentiationInterfaceEnzymeExt/forward_onearg.jl:76
 [17] hvp
    @ /projectnb/ssmsvi/rsenne/.julia/packages/DifferentiationInterface/f85Vv/src/second_order/hvp.jl:331 [inlined]
 [18] _logdensity_hvp_prepared
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:166 [inlined]
 [19] #18
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:385 [inlined]
 [20] mala_step_taped_and_jvp!(x_next::Vector{Float64}, jvp_out::Vector{Float64}, ws::ParallelMCMC.MALA.MALAWorkspace{Vector{Float64}}, logp::ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, gradlogp::ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, x::Vector{Float64}, ε::Float64, ξ::SubArray{Float64, 1, Matrix{Float64}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}, u::Float64, v::Vector{Float64}, hvp_fn::ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}; cholM::Nothing)
    @ ParallelMCMC.MALA /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/MALA/MALA.jl:766
 [21] mala_step_taped_and_jvp!
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/MALA/MALA.jl:730 [inlined]
 [22] #mala_step_taped_and_jvp#24
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/MALA/MALA.jl:809 [inlined]
 [23] mala_step_taped_and_jvp
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/MALA/MALA.jl:795 [inlined]
 [24] #24
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:400 [inlined]
 [25] deer_update!(ws::ParallelMCMC.DEER.DEERWorkspace{Matrix{Float64}, Vector{Float64}, ParallelMCMC.DEER.DEERScan.AffineScanWorkspace{Matrix{Float64}}, Nothing, Nothing}, S_out::Matrix{Float64}, rec::ParallelMCMC.DEER.TapedRecursion{ParallelMCMC.var"#20#21"{Nothing, Float64, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.var"#22#23"{Nothing, Float64, ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.var"#24#25"{Nothing, Float64, ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, Nothing, ParallelMCMC.MALATapeElement{Float64, SubArray{Float64, 1, Matrix{Float64}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}}}, s0_in::Vector{Float64}, S_in::Matrix{Float64}; jacobian::Symbol, damping::Float64, probes::Int64, rng::Random.TaskLocalRNG)
    @ ParallelMCMC.DEER /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:336
 [26] deer_update!
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:275 [inlined]
 [27] solve(rec::ParallelMCMC.DEER.TapedRecursion{ParallelMCMC.var"#20#21"{Nothing, Float64, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.var"#22#23"{Nothing, Float64, ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.var"#24#25"{Nothing, Float64, ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, Nothing, ParallelMCMC.MALATapeElement{Float64, SubArray{Float64, 1, Matrix{Float64}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}}}, s0_in::Vector{Float64}; init::Nothing, tol_abs::Float64, tol_rel::Float64, maxiter::Int64, jacobian::Symbol, damping::Float64, probes::Int64, rng::Random.TaskLocalRNG, return_info::Bool, workspace::ParallelMCMC.DEER.DEERWorkspace{Matrix{Float64}, Vector{Float64}, ParallelMCMC.DEER.DEERScan.AffineScanWorkspace{Matrix{Float64}}, Nothing, Nothing}, copy_result::Bool)
    @ ParallelMCMC.DEER /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:455
 [28] solve
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:406 [inlined]
 [29] #_deer_solve_new_tape#30
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:501 [inlined]
 [30] macro expansion
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:660 [inlined]
 [31] (::ParallelMCMC.var"#39#40"{AbstractMCMC.CreateNewProgressBar{String}, Random.TaskLocalRNG, DensityModel{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing, Nothing, Nothing}, ParallelMALASampler{Float64, Nothing, ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}}, Int64, Float64, Vector{AbstractVector}, Vector{AbstractMatrix}})()
    @ ParallelMCMC /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
 [32] with_logstate(f::ParallelMCMC.var"#39#40"{AbstractMCMC.CreateNewProgressBar{String}, Random.TaskLocalRNG, DensityModel{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing, Nothing, Nothing}, ParallelMALASampler{Float64, Nothing, ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}}, Int64, Float64, Vector{AbstractVector}, Vector{AbstractMatrix}}, logstate::Base.CoreLogging.LogState)
    @ Base.CoreLogging ./logging/logging.jl:542
 [33] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
    @ Base.CoreLogging ./logging/logging.jl:653
 [34] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
    @ AbstractMCMC /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
 [35] macro expansion
    @ /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
 [36] _sample_parallel_mala_blocks(rng::Random.TaskLocalRNG, model::DensityModel{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing, Nothing, Nothing}, sampler::ParallelMALASampler{Float64, Nothing, ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}}, N::Int64; initial_params::Nothing, progress::Bool, progressname::String)
    @ ParallelMCMC /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:656
 [37] _sample_parallel_mala_blocks
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:634 [inlined]
 [38] #mcmcsample#42
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:767 [inlined]
 [39] mcmcsample
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:709 [inlined]
 [40] #sample#20
    @ /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:61 [inlined]
 [41] sample
    @ /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:54 [inlined]
 [42] #sample#19
    @ /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:23 [inlined]
 [43] sample(model_or_logdensity::DensityModel{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing, Nothing, Nothing}, sampler::ParallelMALASampler{Float64, Nothing, ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}}, N_or_isdone::Int64)
    @ AbstractMCMC /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:20
 [44] top-level scope
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/scripts/enzyme_test.jl:11
 [45] include(mod::Module, _path::String)
    @ Base ./Base.jl:306
 [46] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:317
 [47] _start()
    @ Base ./client.jl:550
in expression starting at /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/scripts/enzyme_test.jl:11
[rsenne@scc-501 ParallelMCMC.jl]$ julia --project=scripts scripts/enzyme_test.jl
[rsenne@scc-501 ParallelMCMC.jl]$ julia --project=scripts scripts/enzyme_test.jl
┌ Warning: TODO: Removed parameter with rooting cannot be known without calling convention. This is a bug which requires a fix in Julia (1.12+) itself
└ @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/typeutils/jltypes.jl:311
┌ Warning: TODO: Removed parameter with rooting cannot be known without calling convention. This is a bug which requires a fix in Julia (1.12+) itself
└ @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/typeutils/jltypes.jl:311
┌ Warning: TODO: Removed parameter with rooting cannot be known without calling convention. This is a bug which requires a fix in Julia (1.12+) itself
└ @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/typeutils/jltypes.jl:311
ERROR: LoadError: BoundsError: attempt to access 1-element Vector{LLVM.LLVMType} at index [2]
Stacktrace:
  [1] throw_boundserror(A::Vector{LLVM.LLVMType}, I::Tuple{Int64})
    @ Base ./essentials.jl:15
  [2] getindex
    @ ./essentials.jl:919 [inlined]
  [3] handle_param(args::Vector{Any}, codegen_types::Vector{LLVM.LLVMType}, source_typ::Type, rooted_typ::Union{Nothing, Type}, source_i::Int64, orig_i::Int64, arg_jl_i::Int64, codegen_i::Int64, last_cc::GPUCompiler.ArgumentCC, parmsRemoved::Vector{UInt64})
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/typeutils/jltypes.jl:180
  [4] classify_arguments(source_sig::Type, codegen_ft::LLVM.FunctionType, has_sret::Bool, has_returnroots::Bool, has_swiftself::Bool, parmsRemoved::Vector{UInt64}, mi::Core.MethodInstance, world::UInt64)
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/typeutils/jltypes.jl:303
  [5] set_module_types!(interp::Enzyme.Compiler.Interpreter.EnzymeInterpreter{Nothing}, mod::LLVM.Module, primalf::LLVM.Function, job::GPUCompiler.CompilerJob{Enzyme.Compiler.EnzymeTarget{GPUCompiler.NativeCompilerTarget}, Enzyme.Compiler.EnzymeCompilerParams{Enzyme.Compiler.PrimalCompilerParams}}, edges::Vector{Any}, run_enzyme::Bool, mode::Enzyme.API.CDerivativeMode)
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:1156
  [6] compile_unhooked(output::Symbol, job::GPUCompiler.CompilerJob{Enzyme.Compiler.EnzymeTarget{GPUCompiler.NativeCompilerTarget}, Enzyme.Compiler.EnzymeCompilerParams{Enzyme.Compiler.PrimalCompilerParams}})
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:5401
  [7] #compile#94
    @ /projectnb/ssmsvi/rsenne/.julia/packages/GPUCompiler/KwfWk/src/driver.jl:67 [inlined]
  [8] compile
    @ /projectnb/ssmsvi/rsenne/.julia/packages/GPUCompiler/KwfWk/src/driver.jl:55 [inlined]
  [9] _thunk(job::GPUCompiler.CompilerJob{Enzyme.Compiler.EnzymeTarget{GPUCompiler.NativeCompilerTarget}, Enzyme.Compiler.EnzymeCompilerParams{Enzyme.Compiler.PrimalCompilerParams}}, postopt::Bool)
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:6853
 [10] _thunk
    @ /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:6851 [inlined]
 [11] cached_compilation
    @ /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:6921 [inlined]
 [12] thunkbase(mi::Core.MethodInstance, World::UInt64, FA::Type{<:EnzymeCore.Annotation}, A::Type{<:EnzymeCore.Annotation}, TT::Type, Mode::Enzyme.API.CDerivativeMode, width::Int64, ModifiedBetween::NTuple{N, Bool} where N, ReturnPrimal::Bool, ShadowInit::Bool, ABI::Type, ErrIfFuncWritten::Bool, RuntimeActivity::Bool, StrongZero::Bool, edges::Vector{Any})
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:7037
 [13] thunk_generator(world::UInt64, source::Union{LineNumberNode, Method}, FA::Type, A::Type, TT::Type, Mode::Enzyme.API.CDerivativeMode, Width::Int64, ModifiedBetween::NTuple{N, Bool} where N, ReturnPrimal::Bool, ShadowInit::Bool, ABI::Type, ErrIfFuncWritten::Bool, RuntimeActivity::Bool, StrongZero::Bool, self::Any, fakeworld::Any, fa::Type, a::Type, tt::Type, mode::Type, width::Type, modifiedbetween::Type, returnprimal::Type, shadowinit::Type, abi::Type, erriffuncwritten::Type, runtimeactivity::Type, strongzero::Type)
    @ Enzyme.Compiler /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/compiler.jl:7181
 [14] autodiff
    @ /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/Enzyme.jl:673 [inlined]
 [15] autodiff
    @ /projectnb/ssmsvi/rsenne/.julia/packages/Enzyme/995Eg/src/Enzyme.jl:577 [inlined]
 [16] pushforward(::typeof(DifferentiationInterface.shuffled_gradient), ::DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, ::ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ::Vector{Float64}, ::Tuple{Vector{Float64}}, ::DifferentiationInterface.FunctionContext{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ::DifferentiationInterface.Constant{ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ::DifferentiationInterface.Constant{DifferentiationInterface.Rewrap{0, Tuple{}}})
    @ DifferentiationInterfaceEnzymeExt /projectnb/ssmsvi/rsenne/.julia/packages/DifferentiationInterface/f85Vv/ext/DifferentiationInterfaceEnzymeExt/forward_onearg.jl:76
 [17] hvp
    @ /projectnb/ssmsvi/rsenne/.julia/packages/DifferentiationInterface/f85Vv/src/second_order/hvp.jl:331 [inlined]
 [18] _logdensity_hvp_prepared
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:166 [inlined]
 [19] #18
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:385 [inlined]
 [20] mala_step_taped_and_jvp!(x_next::Vector{Float64}, jvp_out::Vector{Float64}, ws::ParallelMCMC.MALA.MALAWorkspace{Vector{Float64}}, logp::ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, gradlogp::ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, x::Vector{Float64}, ε::Float64, ξ::SubArray{Float64, 1, Matrix{Float64}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}, u::Float64, v::Vector{Float64}, hvp_fn::ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}; cholM::Nothing)
    @ ParallelMCMC.MALA /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/MALA/MALA.jl:766
 [21] mala_step_taped_and_jvp!
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/MALA/MALA.jl:730 [inlined]
 [22] #mala_step_taped_and_jvp#24
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/MALA/MALA.jl:809 [inlined]
 [23] mala_step_taped_and_jvp
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/MALA/MALA.jl:795 [inlined]
 [24] #24
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:400 [inlined]
 [25] deer_update!(ws::ParallelMCMC.DEER.DEERWorkspace{Matrix{Float64}, Vector{Float64}, ParallelMCMC.DEER.DEERScan.AffineScanWorkspace{Matrix{Float64}}, Nothing, Nothing}, S_out::Matrix{Float64}, rec::ParallelMCMC.DEER.TapedRecursion{ParallelMCMC.var"#20#21"{Nothing, Float64, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.var"#22#23"{Nothing, Float64, ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.var"#24#25"{Nothing, Float64, ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, Nothing, ParallelMCMC.MALATapeElement{Float64, SubArray{Float64, 1, Matrix{Float64}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}}}, s0_in::Vector{Float64}, S_in::Matrix{Float64}; jacobian::Symbol, damping::Float64, probes::Int64, rng::Random.TaskLocalRNG)
    @ ParallelMCMC.DEER /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:336
 [26] deer_update!
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:275 [inlined]
 [27] solve(rec::ParallelMCMC.DEER.TapedRecursion{ParallelMCMC.var"#20#21"{Nothing, Float64, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.var"#22#23"{Nothing, Float64, ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.var"#24#25"{Nothing, Float64, ParallelMCMC.var"#18#19"{DifferentiationInterface.ForwardOverAnythingHVPPrep{Nothing, Vector{Float64}, Tuple{}, Tuple{}, DifferentiationInterfaceEnzymeExt.EnzymeOneArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}, DifferentiationInterfaceEnzymeExt.EnzymeTwoArgPushforwardPrep{Nothing, Nothing, Tuple{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing}}}, DifferentiationInterface.SecondOrder{ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Const}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}}, Nothing, ParallelMCMC.MALATapeElement{Float64, SubArray{Float64, 1, Matrix{Float64}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}}}, s0_in::Vector{Float64}; init::Nothing, tol_abs::Float64, tol_rel::Float64, maxiter::Int64, jacobian::Symbol, damping::Float64, probes::Int64, rng::Random.TaskLocalRNG, return_info::Bool, workspace::ParallelMCMC.DEER.DEERWorkspace{Matrix{Float64}, Vector{Float64}, ParallelMCMC.DEER.DEERScan.AffineScanWorkspace{Matrix{Float64}}, Nothing, Nothing}, copy_result::Bool)
    @ ParallelMCMC.DEER /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:455
 [28] solve
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/DEER/DEER.jl:406 [inlined]
 [29] #_deer_solve_new_tape#30
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:501 [inlined]
 [30] macro expansion
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:660 [inlined]
 [31] (::ParallelMCMC.var"#39#40"{AbstractMCMC.CreateNewProgressBar{String}, Random.TaskLocalRNG, DensityModel{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing, Nothing, Nothing}, ParallelMALASampler{Float64, Nothing, ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}}, Int64, Float64, Vector{AbstractVector}, Vector{AbstractMatrix}})()
    @ ParallelMCMC /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
 [32] with_logstate(f::ParallelMCMC.var"#39#40"{AbstractMCMC.CreateNewProgressBar{String}, Random.TaskLocalRNG, DensityModel{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing, Nothing, Nothing}, ParallelMALASampler{Float64, Nothing, ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}}, Int64, Float64, Vector{AbstractVector}, Vector{AbstractMatrix}}, logstate::Base.CoreLogging.LogState)
    @ Base.CoreLogging ./logging/logging.jl:542
 [33] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
    @ Base.CoreLogging ./logging/logging.jl:653
 [34] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
    @ AbstractMCMC /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
 [35] macro expansion
    @ /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
 [36] _sample_parallel_mala_blocks(rng::Random.TaskLocalRNG, model::DensityModel{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing, Nothing, Nothing}, sampler::ParallelMALASampler{Float64, Nothing, ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}}, N::Int64; initial_params::Nothing, progress::Bool, progressname::String)
    @ ParallelMCMC /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:656
 [37] _sample_parallel_mala_blocks
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:634 [inlined]
 [38] #mcmcsample#42
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:767 [inlined]
 [39] mcmcsample
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/src/interface.jl:709 [inlined]
 [40] #sample#20
    @ /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:61 [inlined]
 [41] sample
    @ /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:54 [inlined]
 [42] #sample#19
    @ /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:23 [inlined]
 [43] sample(model_or_logdensity::DensityModel{ParallelMCMC.LogDensityProblemPrimal{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, ParallelMCMC.LogDensityProblemGradient{LogDensityFunction{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}, ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, LinkAll, typeof(getlogjoint_internal), VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}, DifferentiationInterfaceEnzymeExt.EnzymeGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoEnzyme{EnzymeCore.ReverseMode{false, true, false, EnzymeCore.FFIABI, false, false}, EnzymeCore.Duplicated}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{Model{typeof(f3), (), (), (), Tuple{}, Tuple{}, DefaultContext, false}}, DifferentiationInterface.Constant{typeof(getlogjoint_internal)}, DifferentiationInterface.Constant{VarNamedTuple{(:x,), Tuple{RangeAndTransform{DynamicLink}}}}, DifferentiationInterface.Constant{LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}}}}, Nothing, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::LogPriorAccumulator{Float64}, LogJacobian::LogJacobianAccumulator{Float64}, LogLikelihood::LogLikelihoodAccumulator{Float64}}}, false}}, Nothing, Nothing, Nothing, Nothing}, sampler::ParallelMALASampler{Float64, Nothing, ADTypes.AutoEnzyme{EnzymeCore.ForwardMode{false, EnzymeCore.FFIABI, false, false, false}, EnzymeCore.Duplicated}}, N_or_isdone::Int64)
    @ AbstractMCMC /projectnb/ssmsvi/rsenne/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:20
 [44] top-level scope
    @ /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/scripts/enzyme_test.jl:11
 [45] include(mod::Module, _path::String)
    @ Base ./Base.jl:306
 [46] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:317
 [47] _start()
    @ Base ./client.jl:550
in expression starting at /projectnb/ssmsvi/rsenne/ParallelMCMC.jl/scripts/enzyme_test.jl:11

Using the following script which i adapted from above:

using DynamicPPL, Distributions, ParallelMCMC, LinearAlgebra

sampler = ParallelMALASampler(0.1)

# problematic model 1
@model f2() = x ~ MvNormal(zeros(2), I)
sample(DensityModel(f2()), sampler, 500)

# problematic model 2
@model f3() = x ~ Dirichlet(ones(3))
sample(DensityModel(f3()), sampler, 500)