So I modified my code based on these examples:
- Optimization of Ordinary Differential Equations · SciMLSensitivity.jl
- Parameter Estimation on Highly Stiff Systems · SciMLSensitivity.jl
But when I run it, it throws an error (see code and complete traceback at the bottom of the post). My guess is this section is the most relevant:
warning: Linking two modules of different target triples: 'bcloader' is 'x86_64-w64-windows-gnu' whereas 'text' is 'x86_64-w64-mingw32'
warning: Linking two modules of different target triples: 'bcloader' is 'x86_64-w64-windows-gnu' whereas 'text' is 'x86_64-w64-mingw32'
warning: Linking two modules of different target triples: 'bcloader' is 'x86_64-w64-windows-gnu' whereas 'text' is 'x86_64-w64-mingw32'
┌ Warning: Using fallback BLAS replacements, performance may be degraded
└ @ Enzyme.Compiler C:\Users\Jon\.julia\packages\GPUCompiler\jVY4I\src\utils.jl:35
ERROR: LoadError: Compiling Tuple{Type{Dict}, Base.Generator{Base.Iterators.Enumerate{Vector{Symbol}}, SciMLBase.var"#516#517"}}: try/catch is not supported.
Refer to the Zygote documentation for fixes.
https://fluxml.ai/Zygote.jl/latest/limitations
My code doesn’t use any try/catch statements, so I think I need to resolve the two modules having different target triples? I’m not sure what that means. Do you have any advice?
Code
using CSV
using DataFrames
using DifferentialEquations
using DiffEqParamEstim
using Optimization
using OptimizationOptimJL
using LinearAlgebra
using OptimizationPolyalgorithms
using SciMLSensitivity
"""ODE representing steady-state, isothermal, isobaric 1D PFR"""
function pfr_ode!(dζ_dz, ζ, logk, z, v_mat, Fj0)
# Calculate rate constants
k = 10.0.^logk;
# Calculate molar flow rate
Fj = Fj0 .+ ζ * v_mat;
# Calculate mole fractions
xj = Fj / sum(Fj);
# Calculate derivatives
dζ_dz[1] = k[1] * xj[1] * xj[2];
dζ_dz[2] = k[2] * (xj[1]^2.0);
return nothing;
end
"""Custom loss function for pfr_ode by calculating L2 norm of Fj"""
function pfr_loss_func(p, prob, z_vec, Fj_obs, v_mat, Fj0)
sol = DifferentialEquations.solve(prob, Tsit5(), p=p, saveat=z_vec)
tot_loss = 0.0;
if (sol.retcode != :Success)
tot_loss = Inf;
else
# Calculate molar flow rates
ζ_df = DataFrame(sol);
rename!(ζ_df, ["z", "ζ1", "ζ2"]);
ζ = Matrix(ζ_df[:, ["ζ1", "ζ2"]]);
Fj = repeat(Fj0, size(ζ)[1]) .+ ζ * v_mat;
tot_loss = LinearAlgebra.norm(Fj .- Fj_obs, 2);
end
return tot_loss;
end
"""Callback function to observe training"""
function callback(p, l, pred)
println("Loss: $l");
println("Parameters: $p");
println("-")
return false;
end
function main()
# Read CSV file for response variables
Fj_obs_df = CSV.read("./pfr_results.csv", DataFrame);
z_vec = convert(Array, Fj_obs_df[:, "z"]);
Fj_obs = Matrix(Fj_obs_df[:, r"F_"]);
ζ0 = [0. 0.]; # Initial extent of reaction in mol/s. (The initial condition)
zspan = (0.0,1.0); # Dimensionless axial position
species_names = ["A" "B" "C" "D"];
# Experimental settings
Fj0 = [10. 20. 0. 0.]; # Feed molar flow rate (mol/s)
# Stoichiometric matrix
# A B C D
v_mat = [-1. -1. 1. 0.; # A + B -> C
-2. 0. 0. 1]; # 2A -> D
logk0 = [1.5, 1.5]; # Initial parameter guesses. True logk0 is [1., 2.]
# Assigning variables that will be known when doing parameter estimation
pfr_ode1!(dζ_dz, ζ, logk, z) = pfr_ode!(dζ_dz, ζ, logk, z, v_mat, Fj0);
# Define the ODE
prob = DifferentialEquations.ODEProblem(pfr_ode1!, ζ0, zspan, logk0);
# Assign values to loss function
pfr_loss_func1(p) = pfr_loss_func(p, prob, z_vec, Fj_obs, v_mat, Fj0);
# Optimize parameters
adtype = Optimization.AutoZygote();
optf = Optimization.OptimizationFunction((x,p)->pfr_loss_func1(x), adtype);
optprob = Optimization.OptimizationProblem(optf, logk0)
result_ode = Optimization.solve(optprob,
OptimizationPolyalgorithms.PolyOpt(),
callback=callback,
maxiters=100);
return nothing;
end
main();
Julia Version and Installed Packages
julia> VERSION
v"1.8.0"
julia> Pkg.status()
Status `C:\Users\Jon\.julia\environments\v1.8\Project.toml`
[336ed68f] CSV v0.10.4
[a93c6f00] DataFrames v1.3.4
[1130ab10] DiffEqParamEstim v1.26.0
[0c46a032] DifferentialEquations v7.2.0
[7f7a1694] Optimization v3.8.2
[36348300] OptimizationOptimJL v0.1.2
[500b13db] OptimizationPolyalgorithms v0.1.0
[91a5bcdd] Plots v1.31.7
[1ed8b502] SciMLSensitivity v7.6.1
[37e2e46d] LinearAlgebra
Full Traceback
PS C:\Users\Jon\Downloads\toy_julia_model\toy_julia_model> julia .\PfrParamEstMWE.jl
warning: Linking two modules of different target triples: 'bcloader' is 'x86_64-w64-windows-gnu' whereas 'text' is 'x86_64-w64-mingw32'
warning: Linking two modules of different target triples: 'bcloader' is 'x86_64-w64-windows-gnu' whereas 'text' is 'x86_64-w64-mingw32'
warning: Linking two modules of different target triples: 'bcloader' is 'x86_64-w64-windows-gnu' whereas 'text' is 'x86_64-w64-mingw32'
┌ Warning: Using fallback BLAS replacements, performance may be degraded
└ @ Enzyme.Compiler C:\Users\Jon\.julia\packages\GPUCompiler\jVY4I\src\utils.jl:35
ERROR: LoadError: Compiling Tuple{Type{Dict}, Base.Generator{Base.Iterators.Enumerate{Vector{Symbol}}, SciMLBase.var"#516#517"}}: try/catch is not supported.
Refer to the Zygote documentation for fixes.
https://fluxml.ai/Zygote.jl/latest/limitations
Stacktrace:
[1] error(s::String)
@ Base .\error.jl:35
[2] instrument(ir::IRTools.Inner.IR)
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\reverse.jl:121
[3] #Primal#23
@ C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\reverse.jl:205 [inlined]
[4] Zygote.Adjoint(ir::IRTools.Inner.IR; varargs::Nothing, normalise::Bool)
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\reverse.jl:330
[5] _generate_pullback_via_decomposition(T::Type)
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\emit.jl:101
[6] #s2772#1066
@ C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:28 [inlined]
[7] var"#s2772#1066"(::Any, ctx::Any, f::Any, args::Any)
@ Zygote .\none:0
[8] (::Core.GeneratedFunctionStub)(::Any, ::Vararg{Any})
@ Core .\boot.jl:582
[9] _pullback
@ C:\Users\Jon\.julia\packages\SciMLBase\DPsGA\src\tabletraits.jl:13 [inlined]
[10] _pullback(::Zygote.Context{false}, ::Type{SciMLBase.AbstractTimeseriesSolutionRows}, ::Vector{Symbol}, ::Vector{Type}, ::Vector{Float64}, ::Vector{Matrix{Float64}})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[11] _pullback
@ C:\Users\Jon\.julia\packages\SciMLBase\DPsGA\src\tabletraits.jl:40 [inlined]
[12] _pullback(ctx::Zygote.Context{false}, f::typeof(Tables.rows), args::ODESolution{Float64, 3, Vector{Matrix{Float64}}, Nothing, Nothing, Vector{Float64}, Vector{Vector{Matrix{Float64}}}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}, OrdinaryDiffEq.InterpolationData{ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float64}}, Vector{Float64}, Vector{Vector{Matrix{Float64}}}, OrdinaryDiffEq.Tsit5Cache{Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, OrdinaryDiffEq.Tsit5ConstantCache{Float64, Float64}, typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}}, DiffEqBase.DEStats})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[13] _pullback
@ C:\Users\Jon\.julia\packages\SciMLBase\DPsGA\src\tabletraits.jl:2 [inlined]
[14] _pullback(ctx::Zygote.Context{false}, f::typeof(Tables.columns), args::ODESolution{Float64, 3, Vector{Matrix{Float64}}, Nothing, Nothing, Vector{Float64}, Vector{Vector{Matrix{Float64}}}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}, OrdinaryDiffEq.InterpolationData{ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float64}}, Vector{Float64}, Vector{Vector{Matrix{Float64}}}, OrdinaryDiffEq.Tsit5Cache{Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, OrdinaryDiffEq.Tsit5ConstantCache{Float64, Float64}, typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}}, DiffEqBase.DEStats})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[15] _pullback
@ C:\Users\Jon\.julia\packages\DataFrames\zqFGs\src\other\tables.jl:58 [inlined]
[16] _pullback(::Zygote.Context{false}, ::DataFrames.var"##DataFrame#796", ::Nothing, ::Type{DataFrame}, ::ODESolution{Float64, 3, Vector{Matrix{Float64}}, Nothing, Nothing, Vector{Float64}, Vector{Vector{Matrix{Float64}}}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}, OrdinaryDiffEq.InterpolationData{ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float64}}, Vector{Float64}, Vector{Vector{Matrix{Float64}}}, OrdinaryDiffEq.Tsit5Cache{Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, OrdinaryDiffEq.Tsit5ConstantCache{Float64, Float64}, typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}}, DiffEqBase.DEStats})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[17] _pullback
@ C:\Users\Jon\.julia\packages\DataFrames\zqFGs\src\other\tables.jl:48 [inlined]
[18] _pullback(ctx::Zygote.Context{false}, f::Type{DataFrame}, args::ODESolution{Float64, 3, Vector{Matrix{Float64}}, Nothing, Nothing, Vector{Float64}, Vector{Vector{Matrix{Float64}}}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}, OrdinaryDiffEq.InterpolationData{ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float64}}, Vector{Float64}, Vector{Vector{Matrix{Float64}}}, OrdinaryDiffEq.Tsit5Cache{Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, OrdinaryDiffEq.Tsit5ConstantCache{Float64, Float64}, typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}}, DiffEqBase.DEStats})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[19] _pullback
@ C:\Users\Jon\Downloads\toy_julia_model\toy_julia_model\PfrParamEstMWE.jl:34 [inlined]
[20] _pullback(::Zygote.Context{false}, ::typeof(pfr_loss_func), ::Vector{Float64}, ::ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, ::Vector{Float64}, ::Matrix{Float64}, ::Matrix{Float64}, ::Matrix{Float64})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[21] _pullback
@ C:\Users\Jon\Downloads\toy_julia_model\toy_julia_model\PfrParamEstMWE.jl:79 [inlined]
[22] _pullback
@ C:\Users\Jon\Downloads\toy_julia_model\toy_julia_model\PfrParamEstMWE.jl:83 [inlined]
[23] _pullback(::Zygote.Context{false}, ::var"#1#4"{var"#pfr_loss_func1#3"{ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, Vector{Float64}}}, ::Vector{Float64}, ::SciMLBase.NullParameters)
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[24] _apply(::Function, ::Vararg{Any})
@ Core .\boot.jl:816
[25] adjoint
@ C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\lib\lib.jl:203 [inlined]
[26] _pullback
@ C:\Users\Jon\.julia\packages\ZygoteRules\AIbCs\src\adjoint.jl:65 [inlined]
[27] _pullback
@ C:\Users\Jon\.julia\packages\SciMLBase\DPsGA\src\scimlfunctions.jl:3024 [inlined]
[28] _pullback(::Zygote.Context{false}, ::OptimizationFunction{true, Optimization.AutoZygote, var"#1#4"{var"#pfr_loss_func1#3"{ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, Vector{Float64}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, ::Vector{Float64}, ::SciMLBase.NullParameters)
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[29] _apply(::Function, ::Vararg{Any})
@ Core .\boot.jl:816
[30] adjoint
@ C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\lib\lib.jl:203 [inlined]
[31] _pullback
@ C:\Users\Jon\.julia\packages\ZygoteRules\AIbCs\src\adjoint.jl:65 [inlined]
[32] _pullback
@ C:\Users\Jon\.julia\packages\Optimization\6nIwk\src\function\zygote.jl:30 [inlined]
[33] _pullback(ctx::Zygote.Context{false}, f::Optimization.var"#136#146"{OptimizationFunction{true, Optimization.AutoZygote, var"#1#4"{var"#pfr_loss_func1#3"{ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, Vector{Float64}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}, args::Vector{Float64})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[34] _apply(::Function, ::Vararg{Any})
@ Core .\boot.jl:816
[35] adjoint
@ C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\lib\lib.jl:203 [inlined]
[36] _pullback
@ C:\Users\Jon\.julia\packages\ZygoteRules\AIbCs\src\adjoint.jl:65 [inlined]
[37] _pullback
@ C:\Users\Jon\.julia\packages\Optimization\6nIwk\src\function\zygote.jl:32 [inlined]
[38] _pullback(ctx::Zygote.Context{false}, f::Optimization.var"#139#149"{Tuple{}, Optimization.var"#136#146"{OptimizationFunction{true, Optimization.AutoZygote, var"#1#4"{var"#pfr_loss_func1#3"{ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, Vector{Float64}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}}, args::Vector{Float64})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface2.jl:0
[39] pullback(f::Function, cx::Zygote.Context{false}, args::Vector{Float64})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface.jl:44
[40] pullback
@ C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface.jl:42 [inlined]
[41] gradient(f::Function, args::Vector{Float64})
@ Zygote C:\Users\Jon\.julia\packages\Zygote\qGFGD\src\compiler\interface.jl:96
[42] (::Optimization.var"#137#147"{Optimization.var"#136#146"{OptimizationFunction{true, Optimization.AutoZygote, var"#1#4"{var"#pfr_loss_func1#3"{ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, Vector{Float64}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}})(::Vector{Float64}, ::Vector{Float64})
@ Optimization C:\Users\Jon\.julia\packages\Optimization\6nIwk\src\function\zygote.jl:32
[43] macro expansion
@ C:\Users\Jon\.julia\packages\OptimizationOptimisers\XLPqT\src\OptimizationOptimisers.jl:35 [inlined]
[44] macro expansion
@ C:\Users\Jon\.julia\packages\Optimization\6nIwk\src\utils.jl:35 [inlined]
[45] __solve(prob::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoZygote, var"#1#4"{var"#pfr_loss_func1#3"{ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, Vector{Float64}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, opt::Optimisers.Adam{Float64}, data::Base.Iterators.Cycle{Tuple{Optimization.NullData}}; maxiters::Int64, callback::Function, progress::Bool, save_best::Bool, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ OptimizationOptimisers C:\Users\Jon\.julia\packages\OptimizationOptimisers\XLPqT\src\OptimizationOptimisers.jl:33
[46] #solve#509
@ C:\Users\Jon\.julia\packages\SciMLBase\DPsGA\src\solve.jl:71 [inlined]
[47] __solve(::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoZygote, var"#1#4"{var"#pfr_loss_func1#3"{ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, var"#pfr_ode1!#2"{Matrix{Float64}, Matrix{Float64}}, UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Matrix{Float64}, Matrix{Float64}, Vector{Float64}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float64}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::PolyOpt; maxiters::Int64, kwargs::Base.Pairs{Symbol, typeof(callback), Tuple{Symbol}, NamedTuple{(:callback,), Tuple{typeof(callback)}}})
@ OptimizationPolyalgorithms C:\Users\Jon\.julia\packages\OptimizationPolyalgorithms\5gDHf\src\OptimizationPolyalgorithms.jl:25
[48] #solve#509
@ C:\Users\Jon\.julia\packages\SciMLBase\DPsGA\src\solve.jl:71 [inlined]
[49] main()
@ Main C:\Users\Jon\Downloads\toy_julia_model\toy_julia_model\PfrParamEstMWE.jl:86
[50] top-level scope
@ C:\Users\Jon\Downloads\toy_julia_model\toy_julia_model\PfrParamEstMWE.jl:93
in expression starting at C:\Users\Jon\Downloads\toy_julia_model\toy_julia_model\PfrParamEstMWE.jl:93