search

SciML / SciMLSensitivity.jl

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
https://docs.sciml.ai/SciMLSensitivity/stable/
Other
333 stars 71 forks source link

Gradient returns error when using `ComplexF64` ODE and a custom `struct` for parameters #1146

Open albertomercurio opened 2 weeks ago

albertomercurio commented 2 weeks ago

Describe the bug 🐞

The calculation of the gradient on a ODE of Float64 type works when using params as both Vector or a custom struct (using SciMLStructures.jl). However, it fails when I simply change the type of the ODE to ComplexF64.

It seems that, in the CompleF64 case, it converts the parameters to a Vector. But they are a custom struct, so p.p1 doesn't work.

It works when using a Vector instead of a custom struct.

Expected behavior

Returning the correct gradient as in the Float64 or as in the ComplexF64 case with Vector parameters.

Minimal Reproducible Example 👇

using OrdinaryDiffEq
using Zygote
using SciMLSensitivity

Definition of the custom struct

struct MyParameters{T}
  params::T
end

Base.length(p::MyParameters) = length(p.params)

function Base.getproperty(obj::MyParameters, field::Symbol)
  if field ∈ fieldnames(typeof(obj))
      getfield(obj, field)
  elseif field ∈ fieldnames(typeof(obj.params))
      getfield(obj.params, field)
  else
      throw(KeyError("Field $field not found in MyParameters or params."))
  end
end

import SciMLStructures: isscimlstructure, ismutablescimlstructure, hasportion, canonicalize, replace, Tunable

isscimlstructure(::MyParameters) = true

ismutablescimlstructure(::MyParameters) = false

hasportion(::Tunable, ::MyParameters) = true

function canonicalize(::Tunable, p::MyParameters)
  buffer = isempty(p.params) ? Float64[] : collect(values(p.params)) 

  repack = let p = p
    function repack(newbuffer)
      replace(Tunable(), p, newbuffer)
    end
  end

  return buffer, repack, false
end

function replace(::Tunable, p::MyParameters, newbuffer)
  @assert length(newbuffer) == length(p.params)
  new_params = NamedTuple{keys(p.params)}(Tuple(newbuffer))
  return MyParameters(new_params)
end

ODE Problem

const T = ComplexF64

function lotka_volterra(u, p, t)
  dx = p.p1 * u[1] - p.p2 * u[1] * u[2]
  dy = -p.p3 * u[2] + p.p4 * u[1] * u[2]

  return [dx, dy]
end

function my_f(p)
  u0 = T[1.0, 1.0]
  param = MyParameters((p1 = p[1], p2 = p[2], p3 = p[3], p4 = p[4],))
  prob = ODEProblem{false}(lotka_volterra, u0, (0.0, 10.0), param)
  sol = solve(prob, Tsit5(), reltol = 1e-6, abstol = 1e-6)
  return sum(real, sol.u[end])
end

p = rand(4)
my_f(p) # OK

Gradient Calculation (fails)

Zygote.gradient(my_f, p)

Error & Stacktrace ⚠️

ERROR: type Array has no field p1
Stacktrace:
  [1] adjoint
    @ ~/.julia/packages/Zygote/NRp5C/src/lib/lib.jl:229 [inlined]
  [2] _pullback
    @ ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:67 [inlined]
  [3] lotka_volterra
    @ ~/GitHub/Research/Undef/Autodiff QuantumToolbox/autodiff.jl:140 [inlined]
  [4] _pullback(::Zygote.Context{false}, ::typeof(lotka_volterra), ::Vector{ComplexF64}, ::Vector{Float64}, ::Float64)
    @ Zygote ~/.julia/packages/Zygote/NRp5C/src/compiler/interface2.jl:0
  [5] _apply(::Function, ::Vararg{Any})
    @ Core ./boot.jl:946
  [6] adjoint
    @ ~/.julia/packages/Zygote/NRp5C/src/lib/lib.jl:203 [inlined]
  [7] _pullback
    @ ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:67 [inlined]
  [8] ODEFunction
    @ ~/.julia/packages/SciMLBase/t7Xn0/src/scimlfunctions.jl:2362 [inlined]
  [9] _pullback(::Zygote.Context{…}, ::ODEFunction{…}, ::Vector{…}, ::Vector{…}, ::Float64)
    @ Zygote ~/.julia/packages/Zygote/NRp5C/src/compiler/interface2.jl:0
 [10] #262
    @ ~/.julia/packages/SciMLSensitivity/ME3jV/src/gauss_adjoint.jl:486 [inlined]
 [11] _pullback(ctx::Zygote.Context{…}, f::SciMLSensitivity.var"#262#263"{…}, args::Vector{…})
    @ Zygote ~/.julia/packages/Zygote/NRp5C/src/compiler/interface2.jl:0
 [12] pullback
    @ ~/.julia/packages/Zygote/NRp5C/src/compiler/interface.jl:90 [inlined]
 [13] pullback
    @ ~/.julia/packages/Zygote/NRp5C/src/compiler/interface.jl:88 [inlined]
 [14] vec_pjac!(out::Vector{…}, λ::Vector{…}, y::Vector{…}, t::Float64, S::SciMLSensitivity.GaussIntegrand{…})
    @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/ME3jV/src/gauss_adjoint.jl:485
 [15] GaussIntegrand
    @ ~/.julia/packages/SciMLSensitivity/ME3jV/src/gauss_adjoint.jl:517 [inlined]
 [16] (::SciMLSensitivity.var"#265#266"{…})(out::Vector{…}, u::Vector{…}, t::Float64, integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/ME3jV/src/gauss_adjoint.jl:558
 [17] (::DiffEqCallbacks.SavingIntegrandSumAffect{…})(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ DiffEqCallbacks ~/.julia/packages/DiffEqCallbacks/00gNi/src/integrating_sum.jl:50
 [18] apply_discrete_callback!
    @ ~/.julia/packages/DiffEqBase/frOsk/src/callbacks.jl:615 [inlined]
 [19] apply_discrete_callback!
    @ ~/.julia/packages/DiffEqBase/frOsk/src/callbacks.jl:631 [inlined]
 [20] handle_callbacks!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/integrators/integrator_utils.jl:355
 [21] _loopfooter!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/integrators/integrator_utils.jl:243
 [22] loopfooter!
    @ ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/integrators/integrator_utils.jl:207 [inlined]
 [23] solve!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/solve.jl:579
 [24] #__solve#75
    @ ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/solve.jl:7 [inlined]
 [25] __solve
    @ ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/solve.jl:1 [inlined]
 [26] solve_call(_prob::ODEProblem{…}, args::Tsit5{…}; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:612
 [27] solve_call
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:569 [inlined]
 [28] #solve_up#53
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1092 [inlined]
 [29] solve_up
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1078 [inlined]
 [30] #solve#51
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1015 [inlined]
 [31] _adjoint_sensitivities(sol::ODESolution{…}, sensealg::GaussAdjoint{…}, alg::Tsit5{…}; t::Vector{…}, dgdu_discrete::Function, dgdp_discrete::Nothing, dgdu_continuous::Nothing, dgdp_continuous::Nothing, g::Nothing, abstol::Float64, reltol::Float64, checkpoints::Vector{…}, corfunc_analytical::Bool, callback::Nothing, kwargs::@Kwargs{…})
    @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/ME3jV/src/gauss_adjoint.jl:578
 [32] _adjoint_sensitivities
    @ ~/.julia/packages/SciMLSensitivity/ME3jV/src/gauss_adjoint.jl:531 [inlined]
 [33] #adjoint_sensitivities#63
    @ ~/.julia/packages/SciMLSensitivity/ME3jV/src/sensitivity_interface.jl:401 [inlined]
 [34] (::SciMLSensitivity.var"#adjoint_sensitivity_backpass#315"{…})(Δ::ODESolution{…})
    @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/ME3jV/src/concrete_solve.jl:627
 [35] ZBack
    @ ~/.julia/packages/Zygote/NRp5C/src/compiler/chainrules.jl:212 [inlined]
 [36] (::Zygote.var"#kw_zpullback#56"{…})(dy::ODESolution{…})
    @ Zygote ~/.julia/packages/Zygote/NRp5C/src/compiler/chainrules.jl:238
 [37] #294
    @ ~/.julia/packages/Zygote/NRp5C/src/lib/lib.jl:206 [inlined]
 [38] (::Zygote.var"#2169#back#296"{…})(Δ::ODESolution{…})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [39] #solve#51
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1015 [inlined]
 [40] (::Zygote.Pullback{…})(Δ::ODESolution{…})
    @ Zygote ~/.julia/packages/Zygote/NRp5C/src/compiler/interface2.jl:0
 [41] #294
    @ ~/.julia/packages/Zygote/NRp5C/src/lib/lib.jl:206 [inlined]
 [42] (::Zygote.var"#2169#back#296"{…})(Δ::ODESolution{…})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [43] solve
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1005 [inlined]
 [44] (::Zygote.Pullback{…})(Δ::ODESolution{…})
    @ Zygote ~/.julia/packages/Zygote/NRp5C/src/compiler/interface2.jl:0
 [45] my_f
    @ ~/GitHub/Research/Undef/Autodiff QuantumToolbox/autodiff.jl:158 [inlined]
 [46] (::Zygote.Pullback{Tuple{…}, Tuple{…}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/NRp5C/src/compiler/interface2.jl:0
 [47] (::Zygote.var"#78#79"{Zygote.Pullback{Tuple{…}, Tuple{…}}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/NRp5C/src/compiler/interface.jl:91
 [48] gradient(f::Function, args::Vector{Float64})
    @ Zygote ~/.julia/packages/Zygote/NRp5C/src/compiler/interface.jl:148
 [49] top-level scope
    @ ~/GitHub/Research/Undef/Autodiff QuantumToolbox/autodiff.jl:167
Some type information was truncated. Use `show(err)` to see complete types.

Environment (please complete the following information):

Status `~/GitHub/Research/Undef/Autodiff QuantumToolbox/Project.toml`
  [6e4b80f9] BenchmarkTools v1.5.0
  [b0b7db55] ComponentArrays v0.15.17
  [7da242da] Enzyme v0.13.14
  [1dea7af3] OrdinaryDiffEq v6.89.0
  [6c2fb7c5] QuantumToolbox v0.21.1 `~/.julia/dev/QuantumToolbox`
  [1ed8b502] SciMLSensitivity v7.71.1
  [53ae85a6] SciMLStructures v1.5.0
  [e88e6eb3] Zygote v0.6.72
Status `~/GitHub/Research/Undef/Autodiff QuantumToolbox/Manifest.toml`
  [47edcb42] ADTypes v1.9.0
  [621f4979] AbstractFFTs v1.5.0
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.38
  [79e6a3ab] Adapt v4.1.1
  [66dad0bd] AliasTables v1.1.3
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.17.0
  [4c555306] ArrayLayouts v1.10.4
  [a9b6321e] Atomix v0.1.0
  [6e4b80f9] BenchmarkTools v1.5.0
  [e2ed5e7c] Bijections v0.1.9
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [fa961155] CEnum v0.5.0
  [2a0fbf3d] CPUSummary v0.2.6
  [7057c7e9] Cassette v0.3.14
  [082447d4] ChainRules v1.71.0
  [d360d2e6] ChainRulesCore v1.25.0
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [861a8166] Combinatorics v1.0.2
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.1
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.16.0
  [b0b7db55] ComponentArrays v0.15.17
  [b152e2b5] CompositeTypes v0.1.4
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [187b0558] ConstructionBase v1.5.8
  [adafc99b] CpuId v0.3.1
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.18.20
  [e2d170a0] DataValueInterfaces v1.0.0
  [2b5f629d] DiffEqBase v6.158.3
  [459566f4] DiffEqCallbacks v4.1.0
  [77a26b50] DiffEqNoiseProcess v5.23.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [a0c0ee7d] DifferentiationInterface v0.6.22
  [b4f34e82] Distances v0.10.12
  [31c24e10] Distributions v0.25.113
  [ffbed154] DocStringExtensions v0.9.3
  [5b8099bc] DomainSets v0.7.14
  [7c1d4256] DynamicPolynomials v0.6.0
  [4e289a0a] EnumX v1.0.4
  [7da242da] Enzyme v0.13.14
  [f151be2c] EnzymeCore v0.8.5
  [d4d017d3] ExponentialUtilities v1.26.1
  [e2ba6199] ExprTools v0.1.10
⌅ [6b7a57c9] Expronicon v0.8.5
  [7a1cc6ca] FFTW v1.8.0
  [7034ab61] FastBroadcast v0.3.5
  [9aa1b823] FastClosures v0.3.2
  [29a986be] FastLapackInterface v2.0.4
  [a4df4552] FastPower v1.1.1
  [1a297f60] FillArrays v1.13.0
  [6a86dc24] FiniteDiff v2.26.0
  [1fa38f19] Format v1.3.7
  [f6369f11] ForwardDiff v0.10.38
  [f62d2435] FunctionProperties v0.1.2
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v0.1.3
⌅ [d9f16b24] Functors v0.4.12
⌅ [0c68f7d7] GPUArrays v10.3.1
⌅ [46192b85] GPUArraysCore v0.1.6
  [61eb1bfa] GPUCompiler v1.0.1
  [14197337] GenericLinearAlgebra v0.3.14
  [c145ed77] GenericSchur v0.5.4
  [86223c79] Graphs v1.12.0
  [3e5b6fbb] HostCPUFeatures v0.1.17
  [34004b35] HypergeometricFunctions v0.3.24
  [7869d1d1] IRTools v0.4.14
  [615f187c] IfElse v0.1.1
  [40713840] IncompleteLU v0.2.1
  [d25df0c9] Inflate v0.1.5
  [18e54dd8] IntegerMathUtils v0.1.2
  [8197267c] IntervalSets v0.7.10
  [3587e190] InverseFunctions v0.1.17
  [92d709cd] IrrationalConstants v0.2.2
  [82899510] IteratorInterfaceExtensions v1.0.0
  [692b3bcd] JLLWrappers v1.6.1
  [682c06a0] JSON v0.21.4
  [ccbc3e58] JumpProcesses v9.14.0
  [ef3ab10e] KLU v0.6.0
  [63c18a36] KernelAbstractions v0.9.29
  [ba0b0d4f] Krylov v0.9.8
  [929cbde3] LLVM v9.1.3
  [b964fa9f] LaTeXStrings v1.4.0
  [23fbe1c1] Latexify v0.16.5
  [10f19ff3] LayoutPointers v0.1.17
  [5078a376] LazyArrays v2.2.1
  [2d8b4e74] LevyArea v1.0.0
  [87fe0de2] LineSearch v0.1.4
  [d3d80556] LineSearches v7.3.0
  [7ed4a6bd] LinearSolve v2.36.2
  [2ab3a3ac] LogExpFunctions v0.3.28
  [bdcacae8] LoopVectorization v0.12.171
  [d8e11817] MLStyle v0.4.17
  [1914dd2f] MacroTools v0.5.13
  [d125e4d3] ManualMemory v0.1.8
  [bb5d69b7] MaybeInplace v0.1.4
  [e1d29d7a] Missings v1.2.0
  [46d2c3a1] MuladdMacro v0.2.4
  [102ac46a] MultivariatePolynomials v0.5.7
  [d8a4904e] MutableArithmetics v1.5.2
  [d41bc354] NLSolversBase v7.8.3
  [2774e3e8] NLsolve v4.5.1
  [872c559c] NNlib v0.9.24
  [77ba4419] NaNMath v1.0.2
⌅ [8913a72c] NonlinearSolve v3.15.1
  [d8793406] ObjectFile v0.4.2
  [6fe1bfb0] OffsetArrays v1.14.1
  [429524aa] Optim v1.9.4
⌃ [3bd65402] Optimisers v0.3.4
  [bac558e1] OrderedCollections v1.6.3
  [1dea7af3] OrdinaryDiffEq v6.89.0
  [89bda076] OrdinaryDiffEqAdamsBashforthMoulton v1.1.0
  [6ad6398a] OrdinaryDiffEqBDF v1.1.2
  [bbf590c4] OrdinaryDiffEqCore v1.10.0
  [50262376] OrdinaryDiffEqDefault v1.1.0
  [4302a76b] OrdinaryDiffEqDifferentiation v1.1.0
  [9286f039] OrdinaryDiffEqExplicitRK v1.1.0
  [e0540318] OrdinaryDiffEqExponentialRK v1.1.0
  [becaefa8] OrdinaryDiffEqExtrapolation v1.2.1
  [5960d6e9] OrdinaryDiffEqFIRK v1.2.0
  [101fe9f7] OrdinaryDiffEqFeagin v1.1.0
  [d3585ca7] OrdinaryDiffEqFunctionMap v1.1.1
  [d28bc4f8] OrdinaryDiffEqHighOrderRK v1.1.0
  [9f002381] OrdinaryDiffEqIMEXMultistep v1.1.0
  [521117fe] OrdinaryDiffEqLinear v1.1.0
  [1344f307] OrdinaryDiffEqLowOrderRK v1.2.0
  [b0944070] OrdinaryDiffEqLowStorageRK v1.2.1
  [127b3ac7] OrdinaryDiffEqNonlinearSolve v1.2.2
  [c9986a66] OrdinaryDiffEqNordsieck v1.1.0
  [5dd0a6cf] OrdinaryDiffEqPDIRK v1.1.0
  [5b33eab2] OrdinaryDiffEqPRK v1.1.0
  [04162be5] OrdinaryDiffEqQPRK v1.1.0
  [af6ede74] OrdinaryDiffEqRKN v1.1.0
  [43230ef6] OrdinaryDiffEqRosenbrock v1.2.0
  [2d112036] OrdinaryDiffEqSDIRK v1.1.0
  [669c94d9] OrdinaryDiffEqSSPRK v1.2.0
  [e3e12d00] OrdinaryDiffEqStabilizedIRK v1.1.0
  [358294b1] OrdinaryDiffEqStabilizedRK v1.1.0
  [fa646aed] OrdinaryDiffEqSymplecticRK v1.1.0
  [b1df2697] OrdinaryDiffEqTsit5 v1.1.0
  [79d7bb75] OrdinaryDiffEqVerner v1.1.1
  [90014a1f] PDMats v0.11.31
  [65ce6f38] PackageExtensionCompat v1.0.2
  [d96e819e] Parameters v0.12.3
  [69de0a69] Parsers v2.8.1
  [e409e4f3] PoissonRandom v0.4.4
  [f517fe37] Polyester v0.7.16
  [1d0040c9] PolyesterWeave v0.2.2
  [f27b6e38] Polynomials v4.0.11
  [85a6dd25] PositiveFactorizations v0.2.4
  [d236fae5] PreallocationTools v0.4.24
  [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [27ebfcd6] Primes v0.5.6
  [43287f4e] PtrArrays v1.2.1
  [1fd47b50] QuadGK v2.11.1
  [6c2fb7c5] QuantumToolbox v0.21.1 `~/.julia/dev/QuantumToolbox`
  [74087812] Random123 v1.7.0
  [e6cf234a] RandomNumbers v1.6.0
  [c1ae055f] RealDot v0.1.0
  [3cdcf5f2] RecipesBase v1.3.4
  [731186ca] RecursiveArrayTools v3.27.3
  [f2c3362d] RecursiveFactorization v0.2.23
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.0
  [ae5879a3] ResettableStacks v1.1.1
  [37e2e3b7] ReverseDiff v1.15.3
  [79098fc4] Rmath v0.8.0
  [47965b36] RootedTrees v2.23.1
  [7e49a35a] RuntimeGeneratedFunctions v0.5.13
  [94e857df] SIMDTypes v0.1.0
  [476501e8] SLEEFPirates v0.6.43
  [0bca4576] SciMLBase v2.59.1
  [19f34311] SciMLJacobianOperators v0.1.1
  [c0aeaf25] SciMLOperators v0.3.12
  [1ed8b502] SciMLSensitivity v7.71.1
  [53ae85a6] SciMLStructures v1.5.0
  [6c6a2e73] Scratch v1.2.1
  [efcf1570] Setfield v1.1.1
⌅ [727e6d20] SimpleNonlinearSolve v1.12.3
  [699a6c99] SimpleTraits v0.9.4
  [ce78b400] SimpleUnPack v1.1.0
  [a2af1166] SortingAlgorithms v1.2.1
  [9f842d2f] SparseConnectivityTracer v0.6.8
  [47a9eef4] SparseDiffTools v2.23.0
  [dc90abb0] SparseInverseSubset v0.1.2
  [0a514795] SparseMatrixColorings v0.4.9
  [e56a9233] Sparspak v0.3.9
  [276daf66] SpecialFunctions v2.4.0
  [aedffcd0] Static v1.1.1
  [0d7ed370] StaticArrayInterface v1.8.0
  [90137ffa] StaticArrays v1.9.8
  [1e83bf80] StaticArraysCore v1.4.3
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.7.0
  [2913bbd2] StatsBase v0.34.3
  [4c63d2b9] StatsFuns v1.3.2
  [789caeaf] StochasticDiffEq v6.70.0
  [7792a7ef] StrideArraysCore v0.5.7
  [09ab397b] StructArrays v0.6.18
  [53d494c1] StructIO v0.3.1
  [2efcf032] SymbolicIndexingInterface v0.3.34
  [19f23fe9] SymbolicLimits v0.2.2
  [d1185830] SymbolicUtils v3.7.2
  [0c5d862f] Symbolics v6.18.3
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.0
  [8ea1fca8] TermInterface v2.0.0
  [8290d209] ThreadingUtilities v0.5.2
  [a759f4b9] TimerOutputs v0.5.25
  [9f7883ad] Tracker v0.2.37
  [d5829a12] TriangularSolve v0.2.1
  [781d530d] TruncatedStacktraces v1.4.0
  [3a884ed6] UnPack v1.0.2
  [a7c27f48] Unityper v0.1.6
  [013be700] UnsafeAtomics v0.2.1
  [d80eeb9a] UnsafeAtomicsLLVM v0.2.1
  [3d5dd08c] VectorizationBase v0.21.71
  [19fa3120] VertexSafeGraphs v0.2.0
  [e88e6eb3] Zygote v0.6.72
  [700de1a5] ZygoteRules v0.2.5
  [7cc45869] Enzyme_jll v0.0.163+0
  [f5851436] FFTW_jll v3.3.10+1
  [1d5cc7b8] IntelOpenMP_jll v2024.2.1+0
  [dad2f222] LLVMExtra_jll v0.0.34+0
  [856f044c] MKL_jll v2024.2.0+0
  [efe28fd5] OpenSpecFun_jll v0.5.5+0
  [f50d1b31] Rmath_jll v0.5.1+0
  [1317d2d5] oneTBB_jll v2021.12.0+0
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching v1.11.0
  [9fa8497b] Future v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [4af54fe1] LazyArtifacts v1.11.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.11.0
  [de0858da] Printf v1.11.0
  [9abbd945] Profile v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [1a1011a3] SharedArrays v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [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 v0.8.1+2
  [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
Julia Version 1.11.1
Commit 8f5b7ca12ad (2024-10-16 10:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 32 × 13th Gen Intel(R) Core(TM) i9-13900KF
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, alderlake)
Threads: 16 default, 0 interactive, 8 GC (on 32 virtual cores)
Environment:
  JULIA_EDITOR = code
  JULIA_NUM_THREADS = 16
DhairyaLGandhi commented 1 week ago

There are a couple compounding factors at play here. First its inconsistently defined. f is written expecting parameters of type MyParameters whereas what is passed is a vector. There's no conversion happening either because a vector is treated as a SciMLStructure by itself.

Second is that when we were working on #1135 we were missing https://github.com/JuliaArrays/ArrayInterface.jl/pull/456.

Third is that the way MyParameters stores its parameters vs the adjoint we get is inconsistent. MyParameters stores it as a Tuple whereas we get a vector back when calculating the parameter jacobian.

should also be solved by #1147

albertomercurio commented 1 week ago

Hi @DhairyaLGandhi,

I tried with the branch of #1147, and I get a different error instead

p = rand(T, 4)

Zygote.gradient(my_f, p)
ERROR: MethodError: no method matching recursive_copyto!(::Vector{ComplexF64}, ::NTuple{4, ComplexF64})
The function `recursive_copyto!` exists, but no method is defined for this combination of argument types.

Closest candidates are:
  recursive_copyto!(::Tuple, ::Tuple)
   @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/qX1o7/src/parameters_handling.jl:11
  recursive_copyto!(::AbstractArray, ::AbstractArray)
   @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/qX1o7/src/parameters_handling.jl:9
  recursive_copyto!(::Any, ::Nothing)
   @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/qX1o7/src/parameters_handling.jl:16
  ...

Stacktrace:
  [1] vec_pjac!(out::Vector{…}, λ::Vector{…}, y::Vector{…}, t::Float64, S::SciMLSensitivity.GaussIntegrand{…})
    @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/qX1o7/src/gauss_adjoint.jl:492
  [2] GaussIntegrand
    @ ~/.julia/packages/SciMLSensitivity/qX1o7/src/gauss_adjoint.jl:517 [inlined]
  [3] (::SciMLSensitivity.var"#265#266"{…})(out::Vector{…}, u::Vector{…}, t::Float64, integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/qX1o7/src/gauss_adjoint.jl:558
  [4] (::DiffEqCallbacks.SavingIntegrandSumAffect{…})(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ DiffEqCallbacks ~/.julia/packages/DiffEqCallbacks/00gNi/src/integrating_sum.jl:50
  [5] apply_discrete_callback!
    @ ~/.julia/packages/DiffEqBase/frOsk/src/callbacks.jl:615 [inlined]
  [6] apply_discrete_callback!
    @ ~/.julia/packages/DiffEqBase/frOsk/src/callbacks.jl:631 [inlined]
  [7] handle_callbacks!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/integrators/integrator_utils.jl:355
  [8] _loopfooter!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/integrators/integrator_utils.jl:243
  [9] loopfooter!
    @ ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/integrators/integrator_utils.jl:207 [inlined]
 [10] solve!(integrator::OrdinaryDiffEqCore.ODEIntegrator{…})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/solve.jl:579
 [11] #__solve#75
    @ ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/solve.jl:7 [inlined]
 [12] __solve
    @ ~/.julia/packages/OrdinaryDiffEqCore/2K6jv/src/solve.jl:1 [inlined]
 [13] solve_call(_prob::ODEProblem{…}, args::Tsit5{…}; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:612
 [14] solve_call
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:569 [inlined]
 [15] #solve_up#53
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1092 [inlined]
 [16] solve_up
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1078 [inlined]
 [17] #solve#51
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1015 [inlined]
 [18] _adjoint_sensitivities(sol::ODESolution{…}, sensealg::GaussAdjoint{…}, alg::Tsit5{…}; t::Vector{…}, dgdu_discrete::Function, dgdp_discrete::Nothing, dgdu_continuous::Nothing, dgdp_continuous::Nothing, g::Nothing, abstol::Float64, reltol::Float64, checkpoints::Vector{…}, corfunc_analytical::Bool, callback::Nothing, kwargs::@Kwargs{…})
    @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/qX1o7/src/gauss_adjoint.jl:578
 [19] _adjoint_sensitivities
    @ ~/.julia/packages/SciMLSensitivity/qX1o7/src/gauss_adjoint.jl:531 [inlined]
 [20] #adjoint_sensitivities#63
    @ ~/.julia/packages/SciMLSensitivity/qX1o7/src/sensitivity_interface.jl:401 [inlined]
 [21] (::SciMLSensitivity.var"#adjoint_sensitivity_backpass#315"{…})(Δ::ODESolution{…})
    @ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/qX1o7/src/concrete_solve.jl:627
 [22] ZBack
    @ ~/.julia/packages/Zygote/nyzjS/src/compiler/chainrules.jl:212 [inlined]
 [23] (::Zygote.var"#kw_zpullback#56"{…})(dy::ODESolution{…})
    @ Zygote ~/.julia/packages/Zygote/nyzjS/src/compiler/chainrules.jl:238
 [24] #294
    @ ~/.julia/packages/Zygote/nyzjS/src/lib/lib.jl:206 [inlined]
 [25] (::Zygote.var"#2169#back#296"{…})(Δ::ODESolution{…})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [26] #solve#51
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1015 [inlined]
 [27] (::Zygote.Pullback{…})(Δ::ODESolution{…})
    @ Zygote ~/.julia/packages/Zygote/nyzjS/src/compiler/interface2.jl:0
 [28] #294
    @ ~/.julia/packages/Zygote/nyzjS/src/lib/lib.jl:206 [inlined]
 [29] (::Zygote.var"#2169#back#296"{…})(Δ::ODESolution{…})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [30] solve
    @ ~/.julia/packages/DiffEqBase/frOsk/src/solve.jl:1005 [inlined]
 [31] (::Zygote.Pullback{…})(Δ::ODESolution{…})
    @ Zygote ~/.julia/packages/Zygote/nyzjS/src/compiler/interface2.jl:0
 [32] my_f
    @ ~/GitHub/Research/Undef/Autodiff QuantumToolbox/autodiff.jl:158 [inlined]
 [33] (::Zygote.Pullback{Tuple{…}, Tuple{…}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/nyzjS/src/compiler/interface2.jl:0
 [34] (::Zygote.var"#78#79"{Zygote.Pullback{Tuple{…}, Tuple{…}}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/nyzjS/src/compiler/interface.jl:91
 [35] gradient(f::Function, args::Vector{ComplexF64})
    @ Zygote ~/.julia/packages/Zygote/nyzjS/src/compiler/interface.jl:148
 [36] top-level scope
    @ ~/GitHub/Research/Undef/Autodiff QuantumToolbox/autodiff.jl:167
Some type information was truncated. Use `show(err)` to see complete types.

It's very strange because canonicalize returns a Vector for the buffer.

DhairyaLGandhi commented 1 week ago

Yes, that's the third point from my comment. The adjoint is a Tuple since that's how the struct is stored in memory. We can add a dispatch to recursive_copyto but I worry that it's slightly ambiguous. I'll check out if there are any corner cases worth worrying about.

albertomercurio commented 1 week ago

Ok. But still I don't understand why the Float64 case works.

albertomercurio commented 1 week ago

I don't know if #1149 is also related to this, where I get a null-gradient when using complex ComponentArray rather than float .