The Continuous Normalizing Flows example throws exception #953
Description
Hello,
I tried the continuous normalizing flows example in the documentation, although the code kept running, it threw exceptions at
res1 = Optimization.solve(
optprob, OptimizationOptimisers.Adam(0.01); maxiters = 20, callback = cb)and
res2 = Optimization.solve(optprob2, Optim.LBFGS(); allow_f_increases=false, callback=cb)Error & Stacktrace
Complete error message
┌ Error: Exception while generating log record in module Main at /home/lancexwq/Dropbox (ASU)/Code/Julia/CNF/example.jl:21
│ exception =
│ type OptimizationState has no field layer_1
│ Stacktrace:
│ [1] getproperty
│ @ ./Base.jl:37 [inlined]
│ [2] macro expansion
│ @ ~/.julia/packages/Lux/VkHFW/src/layers/containers.jl:0 [inlined]
│ [3] applychain(layers::@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, x::SubArray{Float32, 2, Matrix{Float32}, Tuple{UnitRange{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, ps::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, st::@NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}})
Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, x::SubArray{Float32, 2, Matrix{Float32}, Tuple{UnitRange{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, ps::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, st::@NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}})
│ @ Lux ~/.julia/packages/Lux/VkHFW/src/layers/containers.jl:482
│ [4] (::Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing})(x::SubArray{Float32, 2, Matrix{Float32}, Tuple{UnitRange{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, ps::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, st::@NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}})
│ @ Lux ~/.julia/packages/Lux/VkHFW/src/layers/containers.jl:480
│ [5] apply(model::Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, x::SubArray{Float32, 2, Matrix{Float32}, Tuple{UnitRange{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, ps::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, st::@NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}})
│ @ LuxCore ~/.julia/packages/LuxCore/IBKvY/src/LuxCore.jl:155
│ [6] (::StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}})(x::SubArray{Float32, 2, Matrix{Float32}, Tuple{UnitRange{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, p::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}})
│ @ Lux ~/.julia/packages/Lux/VkHFW/src/helpers/stateful.jl:119
│ [7] __ffjord(model::StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}}, u::Matrix{Float32}, p::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, ad::AutoZygote, regularize::Bool, monte_carlo::Bool)
│ @ DiffEqFlux ~/.julia/packages/DiffEqFlux/u9oZE/src/ffjord.jl:83
│ [8] (::DiffEqFlux.var"#ffjord#11"{FFJORD{Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, AutoZygote, Tuple{Int64}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @Kwargs{}}, StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}}, Bool, Bool})(u::Matrix{Float32}, p::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, t::Float32)
│ @ DiffEqFlux ~/.julia/packages/DiffEqFlux/u9oZE/src/ffjord.jl:137
│ [9] (::ODEFunction{false, SciMLBase.AutoSpecialize, DiffEqFlux.var"#ffjord#11"{FFJORD{Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, AutoZygote, Tuple{Int64}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @Kwargs{}}, StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}}, Bool, Bool}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing})(::Matrix{Float32}, ::Vararg{Any})
│ @ SciMLBase ~/.julia/packages/SciMLBase/PTTHz/src/scimlfunctions.jl:2336
│ [10] initialize!(integrator::OrdinaryDiffEqCore.ODEIntegrator{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, false, Matrix{Float32}, Nothing, Float32, Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, Float32, Float32, Float32, Float32, Vector{Matrix{Float32}}, ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, Nothing, ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, ODEFunction{false, SciMLBase.AutoSpecialize, DiffEqFlux.var"#ffjord#11"{FFJORD{Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, AutoZygote, Tuple{Int64}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @Kwargs{}}, StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}}, Bool, Bool}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, OrdinaryDiffEqCore.InterpolationData{ODEFunction{false, SciMLBase.AutoSpecialize, DiffEqFlux.var"#ffjord#11"{FFJORD{Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, AutoZygote, Tuple{Int64}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @Kwargs{}}, StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}}, Bool, Bool}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, Nothing, OrdinaryDiffEqTsit5.Tsit5ConstantCache, Nothing}, SciMLBase.DEStats, Nothing, Nothing, Nothing}, ODEFunction{false, SciMLBase.AutoSpecialize, DiffEqFlux.var"#ffjord#11"{FFJORD{Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, AutoZygote, Tuple{Int64}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @Kwargs{}}, StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}}, Bool, Bool}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, OrdinaryDiffEqTsit5.Tsit5ConstantCache, OrdinaryDiffEqCore.DEOptions{Float32, Float32, Float32, Float32, PIController{Rational{Int64}}, typeof(DiffEqBase.ODE_DEFAULT_NORM), typeof(LinearAlgebra.opnorm), Bool, CallbackSet{Tuple{}, Tuple{}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), DataStructures.BinaryHeap{Float32, DataStructures.FasterForward}, DataStructures.BinaryHeap{Float32, DataStructures.FasterForward}, Nothing, Nothing, Int64, Tuple{}, Tuple{}, Tuple{}}, Matrix{Float32}, Float32, Nothing, OrdinaryDiffEqCore.DefaultInit, Nothing}, cache::OrdinaryDiffEqTsit5.Tsit5ConstantCache)
│ @ OrdinaryDiffEqTsit5 ~/.julia/packages/OrdinaryDiffEqTsit5/DHYtz/src/tsit_perform_step.jl:111
│ [11] __init(prob::ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, ODEFunction{false, SciMLBase.AutoSpecialize, DiffEqFlux.var"#ffjord#11"{FFJORD{Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, AutoZygote, Tuple{Int64}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @Kwargs{}}, StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}}, Bool, Bool}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, alg::Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{Val{true}}; saveat::Tuple{}, tstops::Tuple{}, d_discontinuities::Tuple{}, save_idxs::Nothing, save_everystep::Bool, save_on::Bool, save_start::Bool, save_end::Bool, callback::Nothing, dense::Bool, calck::Bool, dt::Float32, dtmin::Float32, dtmax::Float32, force_dtmin::Bool, adaptive::Bool, gamma::Rational{Int64}, abstol::Nothing, reltol::Nothing, qmin::Rational{Int64}, qmax::Int64, qsteady_min::Int64, qsteady_max::Int64, beta1::Nothing, beta2::Nothing, qoldinit::Rational{Int64}, controller::Nothing, fullnormalize::Bool, failfactor::Int64, maxiters::Int64, internalnorm::typeof(DiffEqBase.ODE_DEFAULT_NORM), internalopnorm::typeof(LinearAlgebra.opnorm), isoutofdomain::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), unstable_check::typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), verbose::Bool, timeseries_errors::Bool, dense_errors::Bool, advance_to_tstop::Bool, stop_at_next_tstop::Bool, initialize_save::Bool, progress::Bool, progress_steps::Int64, progress_name::String, progress_message::typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), progress_id::Symbol, userdata::Nothing, allow_extrapolation::Bool, initialize_integrator::Bool, alias_u0::Bool, alias_du0::Bool, initializealg::OrdinaryDiffEqCore.DefaultInit, kwargs::@Kwargs{})
│ @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/55UVY/src/solve.jl:525
│ [12] __init (repeats 5 times)
│ @ ~/.julia/packages/OrdinaryDiffEqCore/55UVY/src/solve.jl:11 [inlined]
│ [13] #__solve#75
│ @ ~/.julia/packages/OrdinaryDiffEqCore/55UVY/src/solve.jl:6 [inlined]
│ [14] __solve
│ @ ~/.julia/packages/OrdinaryDiffEqCore/55UVY/src/solve.jl:1 [inlined]
│ [15] solve_call(_prob::ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, ODEFunction{false, SciMLBase.AutoSpecialize, DiffEqFlux.var"#ffjord#11"{FFJORD{Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, AutoZygote, Tuple{Int64}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @Kwargs{}}, StatefulLuxLayer{Static.True, Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, @NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}}, Bool, Bool}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, args::Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::@Kwargs{save_everystep::Bool, save_start::Bool, save_end::Bool})
│ @ DiffEqBase ~/.julia/packages/DiffEqBase/uqSeD/src/solve.jl:612
│ [16] solve_call
│ @ ~/.julia/packages/DiffEqBase/uqSeD/src/solve.jl:569 [inlined]
│ [17] #solve_up#53
│ @ ~/.julia/packages/DiffEqBase/uqSeD/src/solve.jl:1092 [inlined]
│ [18] solve_up
│ @ ~/.julia/packages/DiffEqBase/uqSeD/src/solve.jl:1078 [inlined]
│ [19] #solve#51
│ @ ~/.julia/packages/DiffEqBase/uqSeD/src/solve.jl:1015 [inlined]
│ [20] solve
│ @ ~/.julia/packages/DiffEqBase/uqSeD/src/solve.jl:1005 [inlined]
│ [21] __forward_ffjord(n::FFJORD{Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, AutoZygote, Tuple{Int64}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @Kwargs{}}, x::Matrix{Float32}, ps::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, st::@NamedTuple{model::@NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}, regularize::Bool, monte_carlo::Bool})
│ @ DiffEqFlux ~/.julia/packages/DiffEqFlux/u9oZE/src/ffjord.jl:143
│ [22] FFJORD
│ @ ~/.julia/packages/DiffEqFlux/u9oZE/src/ffjord.jl:128 [inlined]
│ [23] apply
│ @ ~/.julia/packages/LuxCore/IBKvY/src/LuxCore.jl:155 [inlined]
│ [24] (::StatefulLuxLayer{Static.True, FFJORD{Chain{@NamedTuple{layer_1::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}, layer_2::Dense{typeof(tanh), Int64, Int64, Nothing, Nothing, Static.True}}, Nothing}, Nothing, AutoZygote, Tuple{Int64}, Tuple{Float32, Float32}, Tuple{Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}}, @Kwargs{}}, Nothing, @NamedTuple{model::@NamedTuple{layer_1::@NamedTuple{}, layer_2::@NamedTuple{}}, regularize::Bool, monte_carlo::Bool}})(x::Matrix{Float32}, p::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}})
│ @ Lux ~/.julia/packages/Lux/VkHFW/src/helpers/stateful.jl:119
│ [25] loss(θ::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}})
│ @ Main ~/Dropbox (ASU)/Code/Julia/CNF/example.jl:16
│ [26] macro expansion
│ @ ./logging.jl:373 [inlined]
│ [27] cb(p::Optimization.OptimizationState{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Float32, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, Nothing, Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}}, l::Float32)
│ @ Main ~/Dropbox (ASU)/Code/Julia/CNF/example.jl:21
│ [28] macro expansion
│ @ ~/.julia/packages/OptimizationOptimisers/Geiis/src/OptimizationOptimisers.jl:100 [inlined]
│ [29] macro expansion
│ @ ~/.julia/packages/Optimization/DFBOb/src/utils.jl:32 [inlined]
│ [30] __solve(cache::OptimizationCache{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, var"#11#12", OptimizationBase.var"#grad#16"{SciMLBase.NullParameters, OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, var"#11#12", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoForwardDiff{nothing, Nothing}}, OptimizationBase.var"#fg!#18"{SciMLBase.NullParameters, OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, var"#11#12", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoForwardDiff{nothing, Nothing}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, OptimizationBase.ReInitCache{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, SciMLBase.NullParameters}, Nothing, Nothing, Nothing, Nothing, Nothing, Optimisers.Adam, Bool, typeof(cb), Nothing})
│ @ OptimizationOptimisers ~/.julia/packages/OptimizationOptimisers/Geiis/src/OptimizationOptimisers.jl:80
│ [31] solve!(cache::OptimizationCache{OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, var"#11#12", OptimizationBase.var"#grad#16"{SciMLBase.NullParameters, OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, var"#11#12", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoForwardDiff{nothing, Nothing}}, OptimizationBase.var"#fg!#18"{SciMLBase.NullParameters, OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, var"#11#12", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, AutoForwardDiff{nothing, Nothing}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, OptimizationBase.ReInitCache{ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, SciMLBase.NullParameters}, Nothing, Nothing, Nothing, Nothing, Nothing, Optimisers.Adam, Bool, typeof(cb), Nothing})
│ @ SciMLBase ~/.julia/packages/SciMLBase/PTTHz/src/solve.jl:186
│ [32] solve(::OptimizationProblem{true, OptimizationFunction{true, AutoForwardDiff{nothing, Nothing}, var"#11#12", Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, ComponentVector{Float32, Vector{Float32}, Tuple{Axis{(layer_1 = ViewAxis(1:6, Axis(weight = ViewAxis(1:3, ShapedAxis((3, 1))), bias = 4:6)), layer_2 = ViewAxis(7:10, Axis(weight = ViewAxis(1:3, ShapedAxis((1, 3))), bias = 4:4)))}}}, SciMLBase.NullParameters, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, @Kwargs{}}, ::Optimisers.Adam; kwargs::@Kwargs{maxiters::Int64, callback::typeof(cb)})
│ @ SciMLBase ~/.julia/packages/SciMLBase/PTTHz/src/solve.jl:94
│ [33] top-level scope
│ @ ~/Dropbox (ASU)/Code/Julia/CNF/example.jl:29
│ [34] eval
│ @ ./boot.jl:385 [inlined]
│ [35] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)
│ @ Base ./loading.jl:2076
│ [36] invokelatest(::Any, ::Any, ::Vararg{Any}; kwargs::@Kwargs{})
│ @ Base ./essentials.jl:892
│ [37] invokelatest(::Any, ::Any, ::Vararg{Any})
│ @ Base ./essentials.jl:889
│ [38] inlineeval(m::Module, code::String, code_line::Int64, code_column::Int64, file::String; softscope::Bool)
│ @ VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.124.2/scripts/packages/VSCodeServer/src/eval.jl:271
│ [39] (::VSCodeServer.var"#69#74"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
│ @ VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.124.2/scripts/packages/VSCodeServer/src/eval.jl:181
│ [40] withpath(f::VSCodeServer.var"#69#74"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams}, path::String)
│ @ VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.124.2/scripts/packages/VSCodeServer/src/repl.jl:276
│ [41] (::VSCodeServer.var"#68#73"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
│ @ VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.124.2/scripts/packages/VSCodeServer/src/eval.jl:179
│ [42] hideprompt(f::VSCodeServer.var"#68#73"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})
│ @ VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.124.2/scripts/packages/VSCodeServer/src/repl.jl:38
│ [43] (::VSCodeServer.var"#67#72"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
│ @ VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.124.2/scripts/packages/VSCodeServer/src/eval.jl:150
│ [44] with_logstate(f::Function, logstate::Any)
│ @ Base.CoreLogging ./logging.jl:515
│ [45] with_logger
│ @ ./logging.jl:627 [inlined]
│ [46] (::VSCodeServer.var"#66#71"{VSCodeServer.ReplRunCodeRequestParams})()
│ @ VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.124.2/scripts/packages/VSCodeServer/src/eval.jl:263
│ [47] #invokelatest#2
│ @ ./essentials.jl:892 [inlined]
│ [48] invokelatest(::Any)
│ @ Base ./essentials.jl:889
│ [49] (::VSCodeServer.var"#64#65")()
│ @ VSCodeServer ~/.vscode/extensions/julialang.language-julia-1.124.2/scripts/packages/VSCodeServer/src/eval.jl:34
└ @ Main ~/Dropbox (ASU)/Code/Julia/CNF/example.jl:21Environment:
Project
Status `~/ASU Dropbox/Xu Weiqing/Code/Julia/CNF/Project.toml`
[b0b7db55] ComponentArrays v0.15.17
[aae7a2af] DiffEqFlux v4.0.0
[31c24e10] Distributions v0.25.112
[d0bbae9a] LuxCUDA v0.3.3
[7f7a1694] Optimization v4.0.3
[36348300] OptimizationOptimJL v0.4.1
[42dfb2eb] OptimizationOptimisers v0.3.3
[1dea7af3] OrdinaryDiffEq v6.89.0
[9a3f8284] RandomManifest
Status `~/ASU Dropbox/Xu Weiqing/Code/Julia/CNF/Manifest.toml`
[47edcb42] ADTypes v1.9.0
[621f4979] AbstractFFTs v1.5.0
[1520ce14] AbstractTrees v0.4.5
[7d9f7c33] Accessors v0.1.38
[79e6a3ab] Adapt v4.0.4
[66dad0bd] AliasTables v1.1.3
[dce04be8] ArgCheck v2.3.0
[ec485272] ArnoldiMethod v0.4.0
[4fba245c] ArrayInterface v7.16.0
[4c555306] ArrayLayouts v1.10.3
[a9b6321e] Atomix v0.1.0
[ab4f0b2a] BFloat16s v0.5.0
[62783981] BitTwiddlingConvenienceFunctions v0.1.6
[4544d5e4] Boltz v1.0.1
[fa961155] CEnum v0.5.0
[2a0fbf3d] CPUSummary v0.2.6
[052768ef] CUDA v5.5.2
[1af6417a] CUDA_Runtime_Discovery v0.3.5
[7057c7e9] Cassette v0.3.13
[082447d4] ChainRules v1.71.0
[d360d2e6] ChainRulesCore v1.25.0
[fb6a15b2] CloseOpenIntervals v0.1.13
[3da002f7] ColorTypes v0.11.5
[5ae59095] Colors v0.12.11
[38540f10] CommonSolve v0.2.4
[bbf7d656] CommonSubexpressions v0.3.1
[f70d9fcc] CommonWorldInvalidations v1.0.0
[34da2185] Compat v4.16.0
[b0b7db55] ComponentArrays v0.15.17
[a33af91c] CompositionsBase v0.1.2
[2569d6c7] ConcreteStructs v0.2.3
[88cd18e8] ConsoleProgressMonitor v0.1.2
[187b0558] ConstructionBase v1.5.8
[adafc99b] CpuId v0.3.1
[a8cc5b0e] Crayons v4.1.1
[9a962f9c] DataAPI v1.16.0
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[864edb3b] DataStructures v0.18.20
[e2d170a0] DataValueInterfaces v1.0.0
[2b5f629d] DiffEqBase v6.157.0
⌅ [459566f4] DiffEqCallbacks v3.9.1
[aae7a2af] DiffEqFlux v4.0.0
[77a26b50] DiffEqNoiseProcess v5.23.0
[163ba53b] DiffResults v1.1.0
[b552c78f] DiffRules v1.15.1
[a0c0ee7d] DifferentiationInterface v0.6.6
[8d63f2c5] DispatchDoctor v0.4.15
[31c24e10] Distributions v0.25.112
[ffbed154] DocStringExtensions v0.9.3
[da5c29d0] EllipsisNotation v1.8.0
[4e289a0a] EnumX v1.0.4
[7da242da] Enzyme v0.13.7
[f151be2c] EnzymeCore v0.8.4
[d4d017d3] ExponentialUtilities v1.26.1
[e2ba6199] ExprTools v0.1.10
⌅ [6b7a57c9] Expronicon v0.8.5
[7034ab61] FastBroadcast v0.3.5
[9aa1b823] FastClosures v0.3.2
[29a986be] FastLapackInterface v2.0.4
[1a297f60] FillArrays v1.13.0
[6a86dc24] FiniteDiff v2.26.0
[53c48c17] FixedPointNumbers v0.8.5
[f6369f11] ForwardDiff v0.10.36
[f62d2435] FunctionProperties v0.1.2
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[3e5b6fbb] HostCPUFeatures v0.1.17
[0e44f5e4] Hwloc v3.3.0
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[ba0b0d4f] Krylov v0.9.6
[5be7bae1] LBFGSB v0.4.1
[929cbde3] LLVM v9.1.2
[8b046642] LLVMLoopInfo v1.0.0
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[e6f89c97] LoggingExtras v1.0.3
[bdcacae8] LoopVectorization v0.12.171
[30fc2ffe] LossFunctions v0.11.2
[b2108857] Lux v1.1.0
[d0bbae9a] LuxCUDA v0.3.3
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[82251201] LuxLib v1.3.2
[7e8f7934] MLDataDevices v1.2.0
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[1914dd2f] MacroTools v0.5.13
[d125e4d3] ManualMemory v0.1.8
[bb5d69b7] MaybeInplace v0.1.4
[e1d29d7a] Missings v1.2.0
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[d41bc354] NLSolversBase v7.8.3
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[77ba4419] NaNMath v1.0.2
[8913a72c] NonlinearSolve v3.15.1
[d8793406] ObjectFile v0.4.2
[6fd5a793] Octavian v0.3.28
[6fe1bfb0] OffsetArrays v1.14.1
[429524aa] Optim v1.9.4
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[7f7a1694] Optimization v4.0.3
[bca83a33] OptimizationBase v2.3.0
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[42dfb2eb] OptimizationOptimisers v0.3.3
[bac558e1] OrderedCollections v1.6.3
[1dea7af3] OrdinaryDiffEq v6.89.0
[89bda076] OrdinaryDiffEqAdamsBashforthMoulton v1.1.0
[6ad6398a] OrdinaryDiffEqBDF v1.1.2
[bbf590c4] OrdinaryDiffEqCore v1.6.0
[50262376] OrdinaryDiffEqDefault v1.1.0
[4302a76b] OrdinaryDiffEqDifferentiation v1.1.0
[9286f039] OrdinaryDiffEqExplicitRK v1.1.0
[e0540318] OrdinaryDiffEqExponentialRK v1.1.0
[becaefa8] OrdinaryDiffEqExtrapolation v1.1.0
[5960d6e9] OrdinaryDiffEqFIRK v1.1.1
[101fe9f7] OrdinaryDiffEqFeagin v1.1.0
[d3585ca7] OrdinaryDiffEqFunctionMap v1.1.1
[d28bc4f8] OrdinaryDiffEqHighOrderRK v1.1.0
[9f002381] OrdinaryDiffEqIMEXMultistep v1.1.0
[521117fe] OrdinaryDiffEqLinear v1.1.0
[1344f307] OrdinaryDiffEqLowOrderRK v1.2.0
[b0944070] OrdinaryDiffEqLowStorageRK v1.2.1
[127b3ac7] OrdinaryDiffEqNonlinearSolve v1.2.1
[c9986a66] OrdinaryDiffEqNordsieck v1.1.0
[5dd0a6cf] OrdinaryDiffEqPDIRK v1.1.0
[5b33eab2] OrdinaryDiffEqPRK v1.1.0
[04162be5] OrdinaryDiffEqQPRK v1.1.0
[af6ede74] OrdinaryDiffEqRKN v1.1.0
[43230ef6] OrdinaryDiffEqRosenbrock v1.2.0
[2d112036] OrdinaryDiffEqSDIRK v1.1.0
[669c94d9] OrdinaryDiffEqSSPRK v1.2.0
[e3e12d00] OrdinaryDiffEqStabilizedIRK v1.1.0
[358294b1] OrdinaryDiffEqStabilizedRK v1.1.0
[fa646aed] OrdinaryDiffEqSymplecticRK v1.1.0
[b1df2697] OrdinaryDiffEqTsit5 v1.1.0
[79d7bb75] OrdinaryDiffEqVerner v1.1.1
[90014a1f] PDMats v0.11.31
[65ce6f38] PackageExtensionCompat v1.0.2
[d96e819e] Parameters v0.12.3
[e409e4f3] PoissonRandom v0.4.4
[f517fe37] Polyester v0.7.16
[1d0040c9] PolyesterWeave v0.2.2
[2dfb63ee] PooledArrays v1.4.3
[85a6dd25] PositiveFactorizations v0.2.4
[d236fae5] PreallocationTools v0.4.24
[aea7be01] PrecompileTools v1.2.1
[21216c6a] Preferences v1.4.3
[08abe8d2] PrettyTables v2.4.0
[33c8b6b6] ProgressLogging v0.1.4
[92933f4c] ProgressMeter v1.10.2
[43287f4e] PtrArrays v1.2.1
[1fd47b50] QuadGK v2.11.1
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[e6cf234a] RandomNumbers v1.6.0
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[f2c3362d] RecursiveFactorization v0.2.23
[189a3867] Reexport v1.2.2
[ae029012] Requires v1.3.0
[ae5879a3] ResettableStacks v1.1.1
[37e2e3b7] ReverseDiff v1.15.3
[79098fc4] Rmath v0.8.0
[7e49a35a] RuntimeGeneratedFunctions v0.5.13
[94e857df] SIMDTypes v0.1.0
[476501e8] SLEEFPirates v0.6.43
[0bca4576] SciMLBase v2.56.0
[19f34311] SciMLJacobianOperators v0.1.0
[c0aeaf25] SciMLOperators v0.3.10
[1ed8b502] SciMLSensitivity v7.68.0
[53ae85a6] SciMLStructures v1.5.0
[6c6a2e73] Scratch v1.2.1
[91c51154] SentinelArrays v1.4.5
[efcf1570] Setfield v1.1.1
[727e6d20] SimpleNonlinearSolve v1.12.3
[699a6c99] SimpleTraits v0.9.4
[ce78b400] SimpleUnPack v1.1.0
[a2af1166] SortingAlgorithms v1.2.1
[9f842d2f] SparseConnectivityTracer v0.6.6
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[dc90abb0] SparseInverseSubset v0.1.2
[0a514795] SparseMatrixColorings v0.4.6
[e56a9233] Sparspak v0.3.9
[276daf66] SpecialFunctions v2.4.0
[aedffcd0] Static v1.1.1
[0d7ed370] StaticArrayInterface v1.8.0
[90137ffa] StaticArrays v1.9.7
[1e83bf80] StaticArraysCore v1.4.3
[82ae8749] StatsAPI v1.7.0
[2913bbd2] StatsBase v0.34.3
[4c63d2b9] StatsFuns v1.3.2
[7792a7ef] StrideArraysCore v0.5.7
[892a3eda] StringManipulation v0.4.0
[09ab397b] StructArrays v0.6.18
[53d494c1] StructIO v0.3.1
[2efcf032] SymbolicIndexingInterface v0.3.31
[3783bdb8] TableTraits v1.0.1
[bd369af6] Tables v1.12.0
[5d786b92] TerminalLoggers v0.1.7
[8290d209] ThreadingUtilities v0.5.2
[a759f4b9] TimerOutputs v0.5.24
[9f7883ad] Tracker v0.2.35
[d5829a12] TriangularSolve v0.2.1
[410a4b4d] Tricks v0.1.9
[781d530d] TruncatedStacktraces v1.4.0
[3a884ed6] UnPack v1.0.2
[013be700] UnsafeAtomics v0.2.1
[d80eeb9a] UnsafeAtomicsLLVM v0.2.1
[3d5dd08c] VectorizationBase v0.21.70
[19fa3120] VertexSafeGraphs v0.2.0
[d49dbf32] WeightInitializers v1.0.3
[e88e6eb3] Zygote v0.6.71
[700de1a5] ZygoteRules v0.2.5
[02a925ec] cuDNN v1.4.0
[4ee394cb] CUDA_Driver_jll v0.10.3+0
[76a88914] CUDA_Runtime_jll v0.15.3+0
[62b44479] CUDNN_jll v9.4.0+0
[7cc45869] Enzyme_jll v0.0.153+0
[e33a78d0] Hwloc_jll v2.11.2+0
[1d5cc7b8] IntelOpenMP_jll v2024.2.1+0
[9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0
[dad2f222] LLVMExtra_jll v0.0.34+0
[81d17ec3] L_BFGS_B_jll v3.0.1+0
[856f044c] MKL_jll v2024.2.0+0
[e98f9f5b] NVTX_jll v3.1.0+2
[efe28fd5] OpenSpecFun_jll v0.5.5+0
[f50d1b31] Rmath_jll v0.5.1+0
[1e29f10c] demumble_jll v1.3.0+0
[1317d2d5] oneTBB_jll v2021.12.0+0
[0dad84c5] ArgTools v1.1.1
[56f22d72] Artifacts
[2a0f44e3] Base64
[ade2ca70] Dates
[8ba89e20] Distributed
[f43a241f] Downloads v1.6.0
[7b1f6079] FileWatching
[9fa8497b] Future
[b77e0a4c] InteractiveUtils
[4af54fe1] LazyArtifacts
[b27032c2] LibCURL v0.6.4
[76f85450] LibGit2
[8f399da3] Libdl
[37e2e46d] LinearAlgebra
[56ddb016] Logging
[d6f4376e] Markdown
[a63ad114] Mmap
[ca575930] NetworkOptions v1.2.0
[44cfe95a] Pkg v1.10.0
[de0858da] Printf
[3fa0cd96] REPL
[9a3f8284] Random
[ea8e919c] SHA v0.7.0
[9e88b42a] Serialization
[1a1011a3] SharedArrays
[6462fe0b] Sockets
[2f01184e] SparseArrays v1.10.0
[10745b16] Statistics v1.10.0
[4607b0f0] SuiteSparse
[fa267f1f] TOML v1.0.3
[a4e569a6] Tar v1.10.0
[8dfed614] Test
[cf7118a7] UUIDs
[4ec0a83e] Unicode
[e66e0078] CompilerSupportLibraries_jll v1.1.1+0
[deac9b47] LibCURL_jll v8.4.0+0
[e37daf67] LibGit2_jll v1.6.4+0
[29816b5a] LibSSH2_jll v1.11.0+1
[c8ffd9c3] MbedTLS_jll v2.28.2+1
[14a3606d] MozillaCACerts_jll v2023.1.10
[4536629a] OpenBLAS_jll v0.3.23+4
[05823500] OpenLibm_jll v0.8.1+2
[bea87d4a] SuiteSparse_jll v7.2.1+1
[83775a58] Zlib_jll v1.2.13+1
[8e850b90] libblastrampoline_jll v5.11.0+0
[8e850ede] nghttp2_jll v1.52.0+1
[3f19e933] p7zip_jll v17.4.0+2
Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`versioninfo
Julia Version 1.10.5
Commit 6f3fdf7b362 (2024-08-27 14:19 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: 8 × Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-15.0.7 (ORCJIT, skylake)
Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores)
Environment:
JULIA_EDITOR = code
JULIA_NUM_THREADS = 1