devmotion/stacktrace.txt

## stacktrace.txt
┌ Warning: dt(2.220446049250313e-16) <= dtmin(2.220446049250313e-16) at t=4.2228999661198057e-16. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /home/david/.julia/packages/SciMLBase/koNdH/src/integrator_interface.jl:366
Sampling 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| Time: 0:00:09
ERROR: DimensionMismatch("arrays could not be broadcast to a common size; got a dimension with lengths 120 and 6120")
Stacktrace:
  [1] _bcs1
    @ ./broadcast.jl:516 [inlined]
  [2] _bcs
    @ ./broadcast.jl:510 [inlined]
  [3] broadcast_shape
    @ ./broadcast.jl:504 [inlined]
  [4] combine_axes
    @ ./broadcast.jl:499 [inlined]
  [5] instantiate
    @ ./broadcast.jl:281 [inlined]
  [6] materialize
    @ ./broadcast.jl:860 [inlined]
  [7] dot_observe(dists::Vector{Normal{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}}, value::Vector{Float64}, vi::DynamicPPL.ThreadSafeVarInfo{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}}}, ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}, Vector{Base.RefValue{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}}})
    @ DynamicPPL ~/.julia/dev/DynamicPPL/src/context_implementations.jl:622
  [8] dot_observe
    @ ~/.julia/dev/Turing/src/inference/hmc.jl:525 [inlined]
  [9] dot_tilde_observe
    @ ~/.julia/dev/DynamicPPL/src/context_implementations.jl:563 [inlined]
 [10] dot_tilde_observe
    @ ~/.julia/dev/DynamicPPL/src/context_implementations.jl:561 [inlined]
 [11] dot_tilde_observe
    @ ~/.julia/dev/DynamicPPL/src/context_implementations.jl:556 [inlined]
 [12] dot_tilde_observe!!
    @ ~/.julia/dev/DynamicPPL/src/context_implementations.jl:604 [inlined]
 [13] dot_tilde_observe!!
    @ ~/.julia/dev/DynamicPPL/src/context_implementations.jl:592 [inlined]
 [14] macro expansion
    @ ~/.julia/dev/DynamicPPL/src/compiler.jl:531 [inlined]
 [15] fit_cucker_smaile(__model__::DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, __varinfo__::DynamicPPL.ThreadSafeVarInfo{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}}}, ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}, Vector{Base.RefValue{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}}}, __context__::DynamicPPL.SamplingContext{DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext, Random._GLOBAL_RNG}, data::Vector{Float64}, cucker_smaile_problem::ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, problem_p::Tuple{Int64, Float64, Float64}, global_p::Tuple{RK4, Float64})
    @ Main ./REPL[10]:11
 [16] macro expansion
    @ ~/.julia/dev/DynamicPPL/src/model.jl:493 [inlined]
 [17] _evaluate!!
    @ ~/.julia/dev/DynamicPPL/src/model.jl:476 [inlined]
 [18] evaluate_threadsafe!!
    @ ~/.julia/dev/DynamicPPL/src/model.jl:467 [inlined]
 [19] evaluate!!
    @ ~/.julia/dev/DynamicPPL/src/model.jl:402 [inlined]
 [20] evaluate!!
    @ ~/.julia/dev/DynamicPPL/src/model.jl:415 [inlined]
 [21] evaluate!!
    @ ~/.julia/dev/DynamicPPL/src/model.jl:423 [inlined]
 [22] (::Turing.LogDensityFunction{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext})(θ::Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}})
    @ Turing ~/.julia/dev/Turing/src/Turing.jl:37
 [23] vector_mode_dual_eval!
    @ ~/.julia/packages/ForwardDiff/wAaVJ/src/apiutils.jl:37 [inlined]
 [24] vector_mode_gradient!(result::DiffResults.MutableDiffResult{1, Float64, Tuple{Vector{Float64}}}, f::Turing.LogDensityFunction{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, x::Vector{Float64}, cfg::ForwardDiff.GradientConfig{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}})
    @ ForwardDiff ~/.julia/packages/ForwardDiff/wAaVJ/src/gradient.jl:113
 [25] gradient!
    @ ~/.julia/packages/ForwardDiff/wAaVJ/src/gradient.jl:37 [inlined]
 [26] gradient!(result::DiffResults.MutableDiffResult{1, Float64, Tuple{Vector{Float64}}}, f::Turing.LogDensityFunction{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, x::Vector{Float64}, cfg::ForwardDiff.GradientConfig{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 3}}})
    @ ForwardDiff ~/.julia/packages/ForwardDiff/wAaVJ/src/gradient.jl:35
 [27] gradient_logp(ad::Turing.Essential.ForwardDiffAD{0, true}, θ::Vector{Float64}, vi::DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, model::DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, sampler::DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, context::DynamicPPL.DefaultContext)
    @ Turing.Essential ~/.julia/dev/Turing/src/essential/ad.jl:130
 [28] gradient_logp (repeats 2 times)
    @ ~/.julia/dev/Turing/src/essential/ad.jl:88 [inlined]
 [29] ∂logπ∂θ
    @ ~/.julia/dev/Turing/src/inference/hmc.jl:433 [inlined]
 [30] ∂H∂θ
    @ ~/.julia/packages/AdvancedHMC/51xgc/src/hamiltonian.jl:31 [inlined]
 [31] macro expansion
    @ ~/.julia/packages/UnPack/EkESO/src/UnPack.jl:100 [inlined]
 [32] step(lf::AdvancedHMC.Leapfrog{Float64}, h::AdvancedHMC.Hamiltonian{AdvancedHMC.DiagEuclideanMetric{Float64, Vector{Float64}}, Turing.Inference.var"#logπ#54"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}}, Turing.Inference.var"#∂logπ∂θ#53"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}}}, z::AdvancedHMC.PhasePoint{Vector{Float64}, AdvancedHMC.DualValue{Float64, Vector{Float64}}}, n_steps::Int64; fwd::Bool, full_trajectory::Val{false})
    @ AdvancedHMC ~/.julia/packages/AdvancedHMC/51xgc/src/integrator.jl:88
 [33] step (repeats 2 times)
    @ ~/.julia/packages/AdvancedHMC/51xgc/src/integrator.jl:66 [inlined]
 [34] A
    @ ~/.julia/packages/AdvancedHMC/51xgc/src/trajectory.jl:692 [inlined]
 [35] find_good_stepsize(rng::Random._GLOBAL_RNG, h::AdvancedHMC.Hamiltonian{AdvancedHMC.DiagEuclideanMetric{Float64, Vector{Float64}}, Turing.Inference.var"#logπ#54"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}}, Turing.Inference.var"#∂logπ∂θ#53"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}}}, θ::Vector{Float64}; max_n_iters::Int64)
    @ AdvancedHMC ~/.julia/packages/AdvancedHMC/51xgc/src/trajectory.jl:714
 [36] #find_good_stepsize#19
    @ ~/.julia/packages/AdvancedHMC/51xgc/src/trajectory.jl:770 [inlined]
 [37] find_good_stepsize
    @ ~/.julia/packages/AdvancedHMC/51xgc/src/trajectory.jl:770 [inlined]
 [38] initialstep(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, spl::DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, vi::DynamicPPL.TypedVarInfo{NamedTuple{(:β, :K, :var), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Setfield.IdentityLens}, Int64}, Vector{Uniform{Float64}}, Vector{AbstractPPL.VarName{:β, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:K, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:K, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:var, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:var, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}; init_params::Nothing, nadapts::Int64, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ Turing.Inference ~/.julia/dev/Turing/src/inference/hmc.jl:187
 [39] step(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, spl::DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}; resume_from::Nothing, init_params::Nothing, kwargs::Base.Pairs{Symbol, Int64, Tuple{Symbol}, NamedTuple{(:nadapts,), Tuple{Int64}}})
    @ DynamicPPL ~/.julia/dev/DynamicPPL/src/sampler.jl:104
 [40] macro expansion
    @ ~/.julia/packages/AbstractMCMC/fnRmh/src/sample.jl:120 [inlined]
 [41] macro expansion
    @ ~/.julia/packages/ProgressLogging/6KXlp/src/ProgressLogging.jl:328 [inlined]
 [42] macro expansion
    @ ~/.julia/packages/AbstractMCMC/fnRmh/src/logging.jl:9 [inlined]
 [43] mcmcsample(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, sampler::DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, discard_initial::Int64, thinning::Int64, chain_type::Type, kwargs::Base.Pairs{Symbol, Int64, Tuple{Symbol}, NamedTuple{(:nadapts,), Tuple{Int64}}})
    @ AbstractMCMC ~/.julia/packages/AbstractMCMC/fnRmh/src/sample.jl:111
 [44] sample(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, sampler::DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, N::Int64; chain_type::Type, resume_from::Nothing, progress::Bool, nadapts::Int64, discard_adapt::Bool, discard_initial::Int64, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ Turing.Inference ~/.julia/dev/Turing/src/inference/hmc.jl:133
 [45] sample
    @ ~/.julia/dev/Turing/src/inference/hmc.jl:116 [inlined]
 [46] #sample#2
    @ ~/.julia/dev/Turing/src/inference/Inference.jl:145 [inlined]
 [47] sample
    @ ~/.julia/dev/Turing/src/inference/Inference.jl:145 [inlined]
 [48] #sample#1
    @ ~/.julia/dev/Turing/src/inference/Inference.jl:135 [inlined]
 [49] sample(model::DynamicPPL.Model{typeof(fit_cucker_smaile), (:data, :cucker_smaile_problem, :problem_p, :global_p), (), (), Tuple{Vector{Float64}, ODEProblem{Matrix{Float64}, Tuple{Float64, Float64}, true, Tuple{Int64, Float64, Float64}, ODEFunction{true, typeof(cuckersmale!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Int64, Float64, Float64}, Tuple{RK4, Float64}}, Tuple{}, DynamicPPL.DefaultContext}, alg::NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}, N::Int64)
    @ Turing.Inference ~/.julia/dev/Turing/src/inference/Inference.jl:135
 [50] main()
    @ Main ./REPL[11]:20