Add support for using non-AbstractArrays with OrdinaryDiffEq and Zygote #1092

apkille · 2024-08-16T17:49:57Z

Continuing my quest to open up SciML to custom non-AbstractArray types :). See SciML/StochasticDiffEq.jl#579 and SciML/OrdinaryDiffEq.jl#2368 for more reference.

ChrisRackauckas · 2024-08-17T13:22:45Z

These changes don't look too unreasonble. However, we already support non-AbstractArrays? For parameters we support SciMLStructure types and Functors. If you define the custom type as a SciMLStructure with the right canonicialization dispatch does it just work?

apkille · 2024-08-17T16:18:36Z

@ChrisRackauckas Defining the SciMLStructure interface for my custom type as follows:

isscimlstructure(::CustomArray) = true
hasportion(::Tunable, ::CustomArray) = true
hasportion(::Constants, ::CustomArray) = false
hasportion(::Caches, ::CustomArray) = false
hasportion(::Discrete, ::CustomArray) = false

canonicalize(::Tunable, x::CustomArray) = vec(x.x), ArrayRepack(x.x), true

and running the test on master gives the following error:

ERROR: MethodError: no method matching vec(::ChainRulesCore.Tangent{Any, @NamedTuple{x::Vector{Float64}}})

Closest candidates are:
  vec(::StaticArraysCore.SizedArray{S, T, N, M} where {T, N, M}) where S
   @ StaticArrays ~/.julia/packages/StaticArrays/MSJcA/src/SizedArray.jl:171
  vec(::LazyArrays.ApplyArray{T, 2, typeof(hcat)} where T)
   @ LazyArrays ~/.julia/packages/LazyArrays/jaUBE/src/lazyconcat.jl:408
  vec(::Distributions.Distribution{<:Distributions.ArrayLikeVariate})
   @ Distributions ~/.julia/packages/Distributions/ji8PW/src/reshaped.jl:143
  ...

Stacktrace:
  [1] (::SciMLSensitivity.var"#332#341"{Vector{Any}, CustomArray{Float64, 1}})(i::Int64)
    @ SciMLSensitivity ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/concrete_solve.jl:1089
  [2] _mapreduce(f::SciMLSensitivity.var"#332#341"{…}, op::typeof(Base.add_sum), ::IndexLinear, A::Base.OneTo{…})
    @ Base ./reduce.jl:440
  [3] _mapreduce_dim(f::Function, op::Function, ::Base._InitialValue, A::Base.OneTo{Int64}, ::Colon)
    @ Base ./reducedim.jl:365
  [4] mapreduce
    @ ./reducedim.jl:357 [inlined]
  [5] _sum
    @ ./reducedim.jl:1015 [inlined]
  [6] sum(f::Function, a::Base.OneTo{Int64})
    @ Base ./reducedim.jl:1011
  [7] (::SciMLSensitivity.var"#330#339"{…})()
    @ SciMLSensitivity ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/concrete_solve.jl:1074
  [8] unthunk
    @ ~/.julia/packages/ChainRulesCore/I1EbV/src/tangent_types/thunks.jl:204 [inlined]
  [9] wrap_chainrules_output
    @ ~/.julia/packages/Zygote/nsBv0/src/compiler/chainrules.jl:110 [inlined]
 [10] map
    @ ./tuple.jl:293 [inlined]
 [11] map (repeats 3 times)
    @ ./tuple.jl:294 [inlined]
 [12] wrap_chainrules_output
    @ ~/.julia/packages/Zygote/nsBv0/src/compiler/chainrules.jl:111 [inlined]
 [13] ZBack
    @ ~/.julia/packages/Zygote/nsBv0/src/compiler/chainrules.jl:211 [inlined]
 [14] (::Zygote.var"#kw_zpullback#53"{SciMLSensitivity.var"#forward_sensitivity_backpass#335"{…}})(dy::Vector{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/chainrules.jl:237
 [15] #291
    @ ~/.julia/packages/Zygote/nsBv0/src/lib/lib.jl:206 [inlined]
 [16] (::Zygote.var"#2169#back#293"{Zygote.var"#291#292"{Tuple{…}, Zygote.var"#kw_zpullback#53"{…}}})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [17] #solve#51
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:1003 [inlined]
 [18] (::Zygote.Pullback{Tuple{…}, Any})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface2.jl:0
 [19] #291
    @ ~/.julia/packages/Zygote/nsBv0/src/lib/lib.jl:206 [inlined]
 [20] (::Zygote.var"#2169#back#293"{Zygote.var"#291#292"{Tuple{…}, Zygote.Pullback{…}}})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [21] solve
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:993 [inlined]
 [22] (::Zygote.Pullback{Tuple{…}, Any})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface2.jl:0
 [23] cost
    @ ~/Documents/Julia Packages/SciML/zcratch/sciml_structure.jl:103 [inlined]
 [24] (::Zygote.Pullback{Tuple{…}, Tuple{…}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface2.jl:0
 [25] (::Zygote.var"#75#76"{Zygote.Pullback{Tuple{…}, Tuple{…}}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface.jl:91
 [26] gradient(f::Function, args::Vector{Float64})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface.jl:148
 [27] (::var"#38#42"{var"#cost#39"{Tsit5{…}}})()
    @ Main ~/.julia/juliaup/julia-1.10.4+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Test/src/Test.jl:898
 [28] (::Base.RedirectStdStream)(thunk::var"#38#42"{var"#cost#39"{Tsit5{…}}}, stream::IOStream)
    @ Base ./stream.jl:1429
 [29] #37
    @ ~/.julia/juliaup/julia-1.10.4+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Test/src/Test.jl:897 [inlined]
 [30] open(::var"#37#41"{var"#cost#39"{Tsit5{…}}}, ::String, ::Vararg{String}; kwargs::@Kwargs{})
    @ Base ./io.jl:396
 [31] open(::Function, ::String, ::String)
    @ Base ./io.jl:393
 [32] macro expansion
    @ ~/.julia/juliaup/julia-1.10.4+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Test/src/Test.jl:896 [inlined]
 [33] top-level scope
    @ ~/Documents/Julia Packages/SciML/zcratch/sciml_structure.jl:106
Some type information was truncated. Use `show(err)` to see complete types.

Although I'm not sure if I'm doing this correctly, as the docs and tests for SciMLStructures are lacking examples. If it somehow does work, I'm happy to write up a docs example for a simple custom type, as this would save me a ton of work.

ChrisRackauckas · 2024-08-20T11:23:26Z

Try setting it to GaussAdjoint?

For forward mode, #1085 should've just handled this yesterday. Give master a try?

apkille · 2024-08-22T21:47:37Z

@ChrisRackauckas still getting an error. On master, running

isscimlstructure(::CustomArray) = true
hasportion(::Tunable, ::CustomArray) = true
hasportion(::Constants, ::CustomArray) = false
hasportion(::Caches, ::CustomArray) = false
hasportion(::Discrete, ::CustomArray) = false

canonicalize(::Tunable, x::CustomArray) = vec(x.x), ArrayRepack(x.x), true

ca0 = CustomArray(ones(2))
tspan = (0.0, 1.0)
par = [rand(), rand()]

algs = [Tsit5(), BS3(), Vern9(), DP5()]

for alg in algs
    function cost(ca0, p)
        prob = ODEProblem((du, u, p, t) -> (du[1] = p[1]*u[1] + p[2]*u[2]; du[2] = p[2]*u[1]), ca0, tspan, p)
        sol = solve(prob, alg; sensealg = GaussAdjoint(), save_everystep = false)
        return 1 - norm(sol[end])^2
    end
    @test_nowarn Zygote.gradient(cost, ca0, par)
end

gives

ERROR: MethodError: no method matching ForwardDiff.JacobianConfig(::SciMLBase.ParamJacobianWrapper{…}, ::CustomArray{…}, ::Vector{…}, ::ForwardDiff.Chunk{…})

Closest candidates are:
  ForwardDiff.JacobianConfig(::F, ::AbstractArray{Y}, ::AbstractArray{X}, ::ForwardDiff.Chunk{N}) where {F, Y, X, N}
   @ ForwardDiff ~/.julia/packages/ForwardDiff/PcZ48/src/config.jl:179
  ForwardDiff.JacobianConfig(::F, ::AbstractArray{Y}, ::AbstractArray{X}, ::ForwardDiff.Chunk{N}, ::T) where {F, Y, X, N, T}
   @ ForwardDiff ~/.julia/packages/ForwardDiff/PcZ48/src/config.jl:179
  ForwardDiff.JacobianConfig(::F, ::AbstractArray{V}, ::ForwardDiff.Chunk{N}, ::T) where {F, V, N, T}
   @ ForwardDiff ~/.julia/packages/ForwardDiff/PcZ48/src/config.jl:154
  ...

Stacktrace:
  [1] build_param_jac_config(alg::GaussAdjoint{…}, pf::Function, u::CustomArray{…}, p::Vector{…})
    @ SciMLSensitivity ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/derivative_wrappers.jl:1063
  [2] SciMLSensitivity.GaussIntegrand(sol::ODESolution{…}, sensealg::GaussAdjoint{…}, checkpoints::Vector{…}, dgdp::Nothing)
    @ SciMLSensitivity ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/gauss_adjoint.jl:440
  [3] _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 ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/gauss_adjoint.jl:558
  [4] adjoint_sensitivities(sol::ODESolution{…}, args::Tsit5{…}; sensealg::GaussAdjoint{…}, verbose::Bool, kwargs::@Kwargs{…})
    @ SciMLSensitivity ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/sensitivity_interface.jl:397
  [5] (::SciMLSensitivity.var"#adjoint_sensitivity_backpass#310"{…})(Δ::Vector{…})
    @ SciMLSensitivity ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/concrete_solve.jl:633
  [6] ZBack
    @ ~/.julia/packages/Zygote/nsBv0/src/compiler/chainrules.jl:211 [inlined]
  [7] (::Zygote.var"#kw_zpullback#53"{SciMLSensitivity.var"#adjoint_sensitivity_backpass#310"{…}})(dy::Vector{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/chainrules.jl:237
  [8] #291
    @ ~/.julia/packages/Zygote/nsBv0/src/lib/lib.jl:206 [inlined]
  [9] (::Zygote.var"#2169#back#293"{Zygote.var"#291#292"{Tuple{…}, Zygote.var"#kw_zpullback#53"{…}}})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [10] #solve#51
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:1003 [inlined]
 [11] (::Zygote.Pullback{Tuple{…}, Any})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface2.jl:0
 [12] #291
    @ ~/.julia/packages/Zygote/nsBv0/src/lib/lib.jl:206 [inlined]
 [13] (::Zygote.var"#2169#back#293"{Zygote.var"#291#292"{Tuple{…}, Zygote.Pullback{…}}})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [14] solve
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:993 [inlined]
 [15] (::Zygote.Pullback{Tuple{…}, Any})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface2.jl:0
 [16] cost
    @ ~/Documents/Julia Packages/SciML/zcratch/sciml_structure.jl:103 [inlined]
 [17] (::Zygote.Pullback{Tuple{…}, Tuple{…}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface2.jl:0
 [18] (::Zygote.var"#75#76"{Zygote.Pullback{Tuple{…}, Tuple{…}}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface.jl:91
 [19] gradient(::Function, ::CustomArray{Float64, 1}, ::Vararg{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface.jl:148
 [20] (::var"#10#14"{var"#cost#11"{Tsit5{…}}})()
    @ Main ~/.julia/juliaup/julia-1.10.4+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Test/src/Test.jl:898
 [21] (::Base.RedirectStdStream)(thunk::var"#10#14"{var"#cost#11"{Tsit5{…}}}, stream::IOStream)
    @ Base ./stream.jl:1429
 [22] #9
    @ ~/.julia/juliaup/julia-1.10.4+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Test/src/Test.jl:897 [inlined]
 [23] open(::var"#9#13"{var"#cost#11"{Tsit5{…}}}, ::String, ::Vararg{String}; kwargs::@Kwargs{})
    @ Base ./io.jl:396
 [24] open(::Function, ::String, ::String)
    @ Base ./io.jl:393
 [25] macro expansion
    @ ~/.julia/juliaup/julia-1.10.4+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Test/src/Test.jl:896 [inlined]
 [26] top-level scope
    @ ~/Documents/Julia Packages/SciML/zcratch/sciml_structure.jl:106

caused by: AssertionError: sensealg isa QuadratureAdjoint
Stacktrace:
  [1] (::SciMLSensitivity.ReverseLossCallback{…})(integrator::OrdinaryDiffEq.ODEIntegrator{…})
    @ SciMLSensitivity ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/adjoint_common.jl:563
  [2] (::DiffEqCallbacks.var"#112#116"{…})(c::DiscreteCallback{…}, u::CustomArray{…}, t::Float64, integrator::OrdinaryDiffEq.ODEIntegrator{…})
    @ DiffEqCallbacks ~/.julia/packages/DiffEqCallbacks/kbsPG/src/preset_time.jl:75
  [3] initialize!
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/callbacks.jl:18 [inlined]
  [4] initialize!
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/callbacks.jl:14 [inlined]
  [5] initialize!
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/callbacks.jl:7 [inlined]
  [6] initialize_callbacks!(integrator::OrdinaryDiffEq.ODEIntegrator{…}, initialize_save::Bool)
    @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/s27pa/src/solve.jl:667
  [7] __init(prob::ODEProblem{…}, alg::Tsit5{…}, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{…}; saveat::Vector{…}, tstops::Vector{…}, d_discontinuities::Tuple{}, save_idxs::Nothing, save_everystep::Bool, save_on::Bool, save_start::Bool, save_end::Bool, callback::CallbackSet{…}, dense::Bool, calck::Bool, dt::Float64, dtmin::Float64, dtmax::Float64, force_dtmin::Bool, adaptive::Bool, gamma::Rational{…}, abstol::Float64, reltol::Float64, qmin::Rational{…}, qmax::Int64, qsteady_min::Int64, qsteady_max::Int64, beta1::Nothing, beta2::Nothing, qoldinit::Rational{…}, controller::Nothing, fullnormalize::Bool, failfactor::Int64, maxiters::Int64, internalnorm::typeof(DiffEqBase.ODE_DEFAULT_NORM), internalopnorm::typeof(opnorm), isoutofdomain::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), unstable_check::typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), verbose::Bool, timeseries_errors::Bool, dense_errors::Bool, advance_to_tstop::Bool, stop_at_next_tstop::Bool, initialize_save::Bool, progress::Bool, progress_steps::Int64, progress_name::String, progress_message::typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), progress_id::Symbol, userdata::Nothing, allow_extrapolation::Bool, initialize_integrator::Bool, alias_u0::Bool, alias_du0::Bool, initializealg::OrdinaryDiffEq.DefaultInit, kwargs::@Kwargs{})
    @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/s27pa/src/solve.jl:523
  [8] __init (repeats 5 times)
    @ ~/.julia/packages/OrdinaryDiffEq/s27pa/src/solve.jl:11 [inlined]
  [9] #__solve#433
    @ ~/.julia/packages/OrdinaryDiffEq/s27pa/src/solve.jl:6 [inlined]
 [10] __solve
    @ ~/.julia/packages/OrdinaryDiffEq/s27pa/src/solve.jl:1 [inlined]
 [11] solve_call(_prob::ODEProblem{…}, args::Tsit5{…}; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:612
 [12] solve_call
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:569 [inlined]
 [13] #solve_up#53
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:1080 [inlined]
 [14] solve_up
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:1066 [inlined]
 [15] #solve#51
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:1003 [inlined]
 [16] _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 ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/gauss_adjoint.jl:580
 [17] _adjoint_sensitivities
    @ ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/gauss_adjoint.jl:533 [inlined]
 [18] adjoint_sensitivities(sol::ODESolution{…}, args::Tsit5{…}; sensealg::GaussAdjoint{…}, verbose::Bool, kwargs::@Kwargs{…})
    @ SciMLSensitivity ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/sensitivity_interface.jl:393
 [19] (::SciMLSensitivity.var"#adjoint_sensitivity_backpass#310"{…})(Δ::Vector{…})
    @ SciMLSensitivity ~/Documents/Julia Packages/SciML/SciMLSensitivity.jl/src/concrete_solve.jl:633
 [20] ZBack
    @ ~/.julia/packages/Zygote/nsBv0/src/compiler/chainrules.jl:211 [inlined]
 [21] (::Zygote.var"#kw_zpullback#53"{SciMLSensitivity.var"#adjoint_sensitivity_backpass#310"{…}})(dy::Vector{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/chainrules.jl:237
 [22] #291
    @ ~/.julia/packages/Zygote/nsBv0/src/lib/lib.jl:206 [inlined]
 [23] (::Zygote.var"#2169#back#293"{Zygote.var"#291#292"{Tuple{…}, Zygote.var"#kw_zpullback#53"{…}}})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [24] #solve#51
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:1003 [inlined]
 [25] (::Zygote.Pullback{Tuple{…}, Any})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface2.jl:0
 [26] #291
    @ ~/.julia/packages/Zygote/nsBv0/src/lib/lib.jl:206 [inlined]
 [27] (::Zygote.var"#2169#back#293"{Zygote.var"#291#292"{Tuple{…}, Zygote.Pullback{…}}})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/ZygoteRules/M4xmc/src/adjoint.jl:72
 [28] solve
    @ ~/.julia/packages/DiffEqBase/V6SCE/src/solve.jl:993 [inlined]
 [29] (::Zygote.Pullback{Tuple{…}, Any})(Δ::Vector{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface2.jl:0
 [30] cost
    @ ~/Documents/Julia Packages/SciML/zcratch/sciml_structure.jl:103 [inlined]
 [31] (::Zygote.Pullback{Tuple{…}, Tuple{…}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface2.jl:0
 [32] (::Zygote.var"#75#76"{Zygote.Pullback{Tuple{…}, Tuple{…}}})(Δ::Float64)
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface.jl:91
 [33] gradient(::Function, ::CustomArray{Float64, 1}, ::Vararg{Any})
    @ Zygote ~/.julia/packages/Zygote/nsBv0/src/compiler/interface.jl:148
 [34] (::var"#10#14"{var"#cost#11"{Tsit5{…}}})()
    @ Main ~/.julia/juliaup/julia-1.10.4+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Test/src/Test.jl:898
 [35] (::Base.RedirectStdStream)(thunk::var"#10#14"{var"#cost#11"{Tsit5{…}}}, stream::IOStream)
    @ Base ./stream.jl:1429
 [36] #9
    @ ~/.julia/juliaup/julia-1.10.4+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Test/src/Test.jl:897 [inlined]
 [37] open(::var"#9#13"{var"#cost#11"{Tsit5{…}}}, ::String, ::Vararg{String}; kwargs::@Kwargs{})
    @ Base ./io.jl:396
 [38] open(::Function, ::String, ::String)
    @ Base ./io.jl:393
 [39] macro expansion
    @ ~/.julia/juliaup/julia-1.10.4+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Test/src/Test.jl:896 [inlined]
 [40] top-level scope
    @ ~/Documents/Julia Packages/SciML/zcratch/sciml_structure.jl:106
Some type information was truncated. Use `show(err)` to see complete types.

apkille · 2024-08-22T21:49:58Z

Maybe the discussion for using SciMLStructures with SciMLSensitivity should be moved to another issue. This PR only deals with using non-AbstractArrays directly with Zygote and SciMLSensitivity.

apkille · 2024-08-25T15:47:44Z

@ChrisRackauckas pinging in case you missed my above comment

ChrisRackauckas · 2024-09-02T02:53:01Z

Rebase this PR onto the latest master. If all went well then this shouldn't need the code changes, just the tests.

apkille · 2024-09-02T09:46:33Z

@ChrisRackauckas the tests work with two small changes in concrete_solve.jl.

apkille added 2 commits September 2, 2024 05:06

add support for non-AbstractArrays

e4e4f9f

rm gauss_adjoint.jl changes

5824180

apkille force-pushed the ca branch from f41b34d to 5824180 Compare September 2, 2024 09:42

ChrisRackauckas approved these changes Sep 2, 2024

View reviewed changes

ChrisRackauckas merged commit 552d22b into SciML:master Sep 2, 2024
13 of 16 checks passed

apkille deleted the ca branch September 2, 2024 14:49

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Add support for using non-AbstractArrays with OrdinaryDiffEq and Zygote #1092

Add support for using non-AbstractArrays with OrdinaryDiffEq and Zygote #1092

apkille commented Aug 16, 2024

ChrisRackauckas commented Aug 17, 2024

apkille commented Aug 17, 2024

ChrisRackauckas commented Aug 20, 2024

apkille commented Aug 22, 2024

apkille commented Aug 22, 2024

apkille commented Aug 25, 2024

ChrisRackauckas commented Sep 2, 2024

apkille commented Sep 2, 2024 •

edited

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Add support for using non-AbstractArrays with OrdinaryDiffEq and Zygote #1092

Add support for using non-AbstractArrays with OrdinaryDiffEq and Zygote #1092

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apkille commented Aug 16, 2024

ChrisRackauckas commented Aug 17, 2024

apkille commented Aug 17, 2024

ChrisRackauckas commented Aug 20, 2024

apkille commented Aug 22, 2024

apkille commented Aug 22, 2024

apkille commented Aug 25, 2024

ChrisRackauckas commented Sep 2, 2024

apkille commented Sep 2, 2024 • edited Loading

apkille commented Sep 2, 2024 •

edited

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