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June 21, 2022 09:21
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Stacktrace for https://discourse.julialang.org/t/first-function-call-produced-nans-when-using-nuts-but-not-mh/83024?u=devmotion with https://github.com/TuringLang/Turing.jl/pull/1841
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| ┌ 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 |
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