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Warning: Instability detected. Aborting
└ @ SciMLBase /Users/nghianguyen/.julia/packages/SciMLBase/QzHjf/src/integrator_interface.jl:491
MethodError: no method matching _forward(::Vector{Float64})
Stacktrace:
[1] track(::Vector{Float64}; kw::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ Tracker ~/.julia/packages/Tracker/9xWLl/src/Tracker.jl:58
[2] track(::Vector{Float64})
@ Tracker ~/.julia/packages/Tracker/9xWLl/src/Tracker.jl:58
[3] promote_u0(u0::Vector{Float64}, p::TrackedArray{…,Vector{Float32}}, t0::Float64)
@ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/tS9ay/src/tracker.jl:33
[4] get_concrete_problem(prob::DAEProblem{TrackedArray{…,Vector{Float64}}, Vector{Float64}, Tuple{Float64, Float64}, false, TrackedArray{…,Vector{Float32}}, DAEFunction{false, SciMLSensitivity.var"#297#304"{DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, isadapt::Bool; kwargs::Base.Pairs{Symbol, Tracker.TrackedVector{T, A} where {T, A<:AbstractVector{T}}, Tuple{Symbol, Symbol}, NamedTuple{(:u0, :p), Tuple{TrackedArray{…,Vector{Float64}}, TrackedArray{…,Vector{Float32}}}}})
@ DiffEqBase ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:882
[5] solve_up(prob::DAEProblem{TrackedArray{…,Vector{Float64}}, Vector{Float64}, Tuple{Float64, Float64}, false, TrackedArray{…,Vector{Float32}}, DAEFunction{false, SciMLSensitivity.var"#297#304"{DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, sensealg::SensitivityADPassThrough, u0::TrackedArray{…,Vector{Float64}}, p::TrackedArray{…,Vector{Float32}}, args::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ DiffEqBase ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:781
[6] solve_up(prob::DAEProblem{TrackedArray{…,Vector{Float64}}, Vector{Float64}, Tuple{Float64, Float64}, false, TrackedArray{…,Vector{Float32}}, DAEFunction{false, SciMLSensitivity.var"#297#304"{DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, sensealg::SensitivityADPassThrough, u0::TrackedArray{…,Vector{Float64}}, p::TrackedArray{…,Vector{Float32}}, args::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing})
@ DiffEqBase ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:768
[7] solve(prob::DAEProblem{TrackedArray{…,Vector{Float64}}, Vector{Float64}, Tuple{Float64, Float64}, false, TrackedArray{…,Vector{Float32}}, DAEFunction{false, SciMLSensitivity.var"#297#304"{DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, args::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}; sensealg::SensitivityADPassThrough, u0::Nothing, p::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ DiffEqBase ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:763
[8] (::SciMLSensitivity.var"#tracker_adjoint_forwardpass#303"{Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}, TrackerAdjoint, Tuple{}})(_u0::TrackedArray{…,Vector{Float64}}, _p::TrackedArray{…,Vector{Float32}})
@ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/tS9ay/src/concrete_solve.jl:833
[9] (::Tracker.var"#20#22"{SciMLSensitivity.var"#tracker_adjoint_forwardpass#303"{Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}, TrackerAdjoint, Tuple{}}, Tuple{TrackedArray{…,Vector{Float64}}, TrackedArray{…,Vector{Float32}}}})()
@ Tracker ~/.julia/packages/Tracker/9xWLl/src/back.jl:148
[10] forward(f::Tracker.var"#20#22"{SciMLSensitivity.var"#tracker_adjoint_forwardpass#303"{Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}, TrackerAdjoint, Tuple{}}, Tuple{TrackedArray{…,Vector{Float64}}, TrackedArray{…,Vector{Float32}}}}, ps::Tracker.Params)
@ Tracker ~/.julia/packages/Tracker/9xWLl/src/back.jl:135
[11] forward(::Function, ::Vector{Float64}, ::Vector{Float32})
@ Tracker ~/.julia/packages/Tracker/9xWLl/src/back.jl:148
[12] _concrete_solve_adjoint(::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, ::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}, ::TrackerAdjoint, ::Vector{Float64}, ::Vector{Float32}, ::SciMLBase.ChainRulesOriginator; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/tS9ay/src/concrete_solve.jl:849
[13] _concrete_solve_adjoint(::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, ::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}, ::TrackerAdjoint, ::Vector{Float64}, ::Vector{Float32}, ::SciMLBase.ChainRulesOriginator)
@ SciMLSensitivity ~/.julia/packages/SciMLSensitivity/tS9ay/src/concrete_solve.jl:754
[14] _solve_adjoint(prob::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, sensealg::TrackerAdjoint, u0::Vector{Float64}, p::Vector{Float32}, originator::SciMLBase.ChainRulesOriginator, args::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}; merge_callbacks::Bool, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ DiffEqBase ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:1159
[15] _solve_adjoint(prob::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, sensealg::TrackerAdjoint, u0::Vector{Float64}, p::Vector{Float32}, originator::SciMLBase.ChainRulesOriginator, args::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing})
@ DiffEqBase ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:1130
[16] rrule(::typeof(DiffEqBase.solve_up), prob::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, sensealg::TrackerAdjoint, u0::Vector{Float64}, p::Vector{Float32}, args::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ DiffEqBase ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:1112
[17] rrule(::typeof(DiffEqBase.solve_up), prob::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, sensealg::TrackerAdjoint, u0::Vector{Float64}, p::Vector{Float32}, args::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing})
@ DiffEqBase ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:1112
[18] rrule(::Zygote.ZygoteRuleConfig{Zygote.Context}, ::Function, ::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, ::TrackerAdjoint, ::Vector{Float64}, ::Vector{Float32}, ::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing})
@ ChainRulesCore ~/.julia/packages/ChainRulesCore/ctmSK/src/rules.jl:134
[19] chain_rrule
@ ~/.julia/packages/Zygote/IoW2g/src/compiler/chainrules.jl:217 [inlined]
[20] macro expansion
@ ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0 [inlined]
[21] _pullback(::Zygote.Context, ::typeof(DiffEqBase.solve_up), ::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, ::TrackerAdjoint, ::Vector{Float64}, ::Vector{Float32}, ::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:9
[22] _apply(::Function, ::Vararg{Any})
@ Core ./boot.jl:814
[23] adjoint
@ ~/.julia/packages/Zygote/IoW2g/src/lib/lib.jl:204 [inlined]
[24] _pullback
@ ~/.julia/packages/ZygoteRules/AIbCs/src/adjoint.jl:65 [inlined]
[25] _pullback
@ ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:763 [inlined]
[26] _pullback(::Zygote.Context, ::DiffEqBase.var"##solve#33", ::TrackerAdjoint, ::Nothing, ::Nothing, ::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, ::typeof(solve), ::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, ::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0
[27] _apply(::Function, ::Vararg{Any})
@ Core ./boot.jl:814
[28] adjoint
@ ~/.julia/packages/Zygote/IoW2g/src/lib/lib.jl:204 [inlined]
[29] _pullback
@ ~/.julia/packages/ZygoteRules/AIbCs/src/adjoint.jl:65 [inlined]
[30] _pullback
@ ~/.julia/packages/DiffEqBase/HDcso/src/solve.jl:758 [inlined]
[31] _pullback(::Zygote.Context, ::CommonSolve.var"#solve##kw", ::NamedTuple{(:sensealg,), Tuple{TrackerAdjoint}}, ::typeof(solve), ::DAEProblem{Vector{Float64}, Vector{Float64}, Tuple{Float64, Float64}, false, Vector{Float32}, DAEFunction{false, var"#f#160"{MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Vector{Bool}}, ::DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0
[32] _apply(::Function, ::Vararg{Any})
@ Core ./boot.jl:814
[33] adjoint
@ ~/.julia/packages/Zygote/IoW2g/src/lib/lib.jl:204 [inlined]
[34] _pullback
@ ~/.julia/packages/ZygoteRules/AIbCs/src/adjoint.jl:65 [inlined]
[35] _pullback
@ ./In[30]:52 [inlined]
[36] _pullback(::Zygote.Context, ::MyNeuralDAE{Vector{Float32}, Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, var"#164#165", Matrix{Float64}, Optimisers.Restructure{Chain{Tuple{var"#162#163", Dense{typeof(tanh), Matrix{Float32}, Vector{Float32}}, Dense{typeof(identity), Matrix{Float32}, Vector{Float32}}}}, NamedTuple{(:layers,), Tuple{Tuple{Tuple{}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}, NamedTuple{(:weight, :bias, :σ), Tuple{Int64, Int64, Tuple{}}}}}}}, Tuple{Float64, Float64}, Vector{Bool}, Tuple{DImplicitEuler{0, true, Nothing, NLNewton{Rational{Int64}, Rational{Int64}, Rational{Int64}}, typeof(OrdinaryDiffEq.DEFAULT_PRECS), Val{:forward}, true, nothing}}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::Vector{Float64}, ::Vector{Float64}, ::Vector{Float32})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0
[37] _pullback
@ ./In[30]:83 [inlined]
[38] _pullback(ctx::Zygote.Context, f::typeof(predict_n_dae), args::Vector{Float32})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0
[39] _pullback
@ ./In[30]:87 [inlined]
[40] _pullback(ctx::Zygote.Context, f::typeof(loss), args::Vector{Float32})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0
[41] _pullback
@ ./In[30]:104 [inlined]
[42] _pullback(::Zygote.Context, ::var"#166#167", ::Vector{Float32}, ::SciMLBase.NullParameters)
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0
[43] _apply
@ ./boot.jl:814 [inlined]
[44] adjoint
@ ~/.julia/packages/Zygote/IoW2g/src/lib/lib.jl:204 [inlined]
[45] _pullback
@ ~/.julia/packages/ZygoteRules/AIbCs/src/adjoint.jl:65 [inlined]
[46] _pullback
@ ~/.julia/packages/SciMLBase/QzHjf/src/scimlfunctions.jl:2885 [inlined]
[47] _pullback(::Zygote.Context, ::OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, ::Vector{Float32}, ::SciMLBase.NullParameters)
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0
[48] _apply(::Function, ::Vararg{Any})
@ Core ./boot.jl:814
[49] adjoint
@ ~/.julia/packages/Zygote/IoW2g/src/lib/lib.jl:204 [inlined]
[50] _pullback
@ ~/.julia/packages/ZygoteRules/AIbCs/src/adjoint.jl:65 [inlined]
[51] _pullback
@ ~/.julia/packages/Optimization/VVccM/src/function/zygote.jl:30 [inlined]
[52] _pullback(ctx::Zygote.Context, f::Optimization.var"#124#134"{OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}, args::Vector{Float32})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0
[53] _apply(::Function, ::Vararg{Any})
@ Core ./boot.jl:814
[54] adjoint
@ ~/.julia/packages/Zygote/IoW2g/src/lib/lib.jl:204 [inlined]
[55] _pullback
@ ~/.julia/packages/ZygoteRules/AIbCs/src/adjoint.jl:65 [inlined]
[56] _pullback
@ ~/.julia/packages/Optimization/VVccM/src/function/zygote.jl:32 [inlined]
[57] _pullback(ctx::Zygote.Context, f::Optimization.var"#127#137"{Tuple{}, Optimization.var"#124#134"{OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}}, args::Vector{Float32})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface2.jl:0
[58] _pullback(f::Function, args::Vector{Float32})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface.jl:34
[59] pullback(f::Function, args::Vector{Float32})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface.jl:40
[60] gradient(f::Function, args::Vector{Float32})
@ Zygote ~/.julia/packages/Zygote/IoW2g/src/compiler/interface.jl:75
[61] (::Optimization.var"#125#135"{Optimization.var"#124#134"{OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}})(::Vector{Float32}, ::Vector{Float32})
@ Optimization ~/.julia/packages/Optimization/VVccM/src/function/zygote.jl:32
[62] (::OptimizationOptimJL.var"#5#13"{OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float32}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, OptimizationOptimJL.var"#4#12"{OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float32}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, OptimizationFunction{false, Optimization.AutoZygote, OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.var"#125#135"{Optimization.var"#124#134"{OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}}, Optimization.var"#128#138"{Optimization.var"#124#134"{OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}}, Optimization.var"#133#143", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}}, OptimizationFunction{false, Optimization.AutoZygote, OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.var"#125#135"{Optimization.var"#124#134"{OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}}, Optimization.var"#128#138"{Optimization.var"#124#134"{OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, SciMLBase.NullParameters}}, Optimization.var"#133#143", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}})(G::Vector{Float32}, θ::Vector{Float32})
@ OptimizationOptimJL ~/.julia/packages/OptimizationOptimJL/iyLQi/src/OptimizationOptimJL.jl:106
[63] value_gradient!!(obj::TwiceDifferentiable{Float32, Vector{Float32}, Matrix{Float32}, Vector{Float32}}, x::Vector{Float32})
@ NLSolversBase ~/.julia/packages/NLSolversBase/cfJrN/src/interface.jl:82
[64] initial_state(method::BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Float64, Flat}, options::Optim.Options{Float64, OptimizationOptimJL.var"#_cb#11"{OptimizationOptimJL.var"#9#17", BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Float64, Flat}, Base.Iterators.Cycle{Tuple{Optimization.NullData}}}}, d::TwiceDifferentiable{Float32, Vector{Float32}, Matrix{Float32}, Vector{Float32}}, initial_x::Vector{Float32})
@ Optim ~/.julia/packages/Optim/rpjtl/src/multivariate/solvers/first_order/bfgs.jl:94
[65] optimize(d::TwiceDifferentiable{Float32, Vector{Float32}, Matrix{Float32}, Vector{Float32}}, initial_x::Vector{Float32}, method::BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Float64, Flat}, options::Optim.Options{Float64, OptimizationOptimJL.var"#_cb#11"{OptimizationOptimJL.var"#9#17", BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Float64, Flat}, Base.Iterators.Cycle{Tuple{Optimization.NullData}}}})
@ Optim ~/.julia/packages/Optim/rpjtl/src/multivariate/optimize/optimize.jl:36
[66] ___solve(prob::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float32}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, opt::BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Float64, Flat}, data::Base.Iterators.Cycle{Tuple{Optimization.NullData}}; callback::Function, maxiters::Nothing, maxtime::Nothing, abstol::Nothing, reltol::Nothing, progress::Bool, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ OptimizationOptimJL ~/.julia/packages/OptimizationOptimJL/iyLQi/src/OptimizationOptimJL.jl:143
[67] ___solve
@ ~/.julia/packages/OptimizationOptimJL/iyLQi/src/OptimizationOptimJL.jl:69 [inlined]
[68] #__solve#2
@ ~/.julia/packages/OptimizationOptimJL/iyLQi/src/OptimizationOptimJL.jl:56 [inlined]
[69] __solve (repeats 2 times)
@ ~/.julia/packages/OptimizationOptimJL/iyLQi/src/OptimizationOptimJL.jl:44 [inlined]
[70] #solve#514
@ ~/.julia/packages/SciMLBase/QzHjf/src/solve.jl:71 [inlined]
[71] solve(::OptimizationProblem{true, OptimizationFunction{true, Optimization.AutoZygote, var"#166#167", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Float32}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Float64, Flat})
@ SciMLBase ~/.julia/packages/SciMLBase/QzHjf/src/solve.jl:71
[72] top-level scope
@ In[30]:106
[73] eval
@ ./boot.jl:373 [inlined]
┌ Error: Error showing method candidates, aborted
│ exception = (ErrorException("could not determine location of method definition"), Union{Ptr{Nothing}, Base.InterpreterIP}[Ptr{Nothing} @0x0000000126b31a1e, Ptr{Nothing} @0x00000001e87ce5d7, Ptr{Nothing} @0x00000001e87d0e76, Ptr{Nothing} @0x00000001e87d1a09, Ptr{Nothing} @0x00000001e87d1b5a, Ptr{Nothing} @0x00000001e87d1bc0, Ptr{Nothing} @0x000000010bcfcf50, Ptr{Nothing} @0x000000010bd09d3a, Ptr{Nothing} @0x00000001e87cbeb1, Ptr{Nothing} @0x00000001e87cbf30, Ptr{Nothing} @0x000000010bcfcf50, Ptr{Nothing} @0x000000010bd09b0b, Ptr{Nothing} @0x00000001e87cbc83, Ptr{Nothing} @0x000000010bcfcf50, Ptr{Nothing} @0x000000010bd09b0b, Ptr{Nothing} @0x00000001e87cbb00, Ptr{Nothing} @0x000000010bcfcf50, Ptr{Nothing} @0x000000010d9ca031, Ptr{Nothing} @0x000000010d9ca394, Ptr{Nothing} @0x000000010d9ca3fb, Ptr{Nothing} @0x000000010bcfcf50, Ptr{Nothing} @0x00000001e71e81ae, Ptr{Nothing} @0x000000010bcfcf50, Ptr{Nothing} @0x000000010bd09d3a, Ptr{Nothing} @0x000000010d985ca0, Ptr{Nothing} @0x000000010d98639c, Ptr{Nothing} @0x000000010d9863af, Ptr{Nothing} @0x000000010bcfcf50, Ptr{Nothing} @0x000000010bd1ac8f])
└ @ Base errorshow.jl:320