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Issues Reported by JET #353

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prbzrg opened this issue Nov 29, 2023 · 2 comments
Open

Issues Reported by JET #353

prbzrg opened this issue Nov 29, 2023 · 2 comments
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enhancement New feature or request help wanted Extra attention is needed upstream

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prbzrg commented Nov 29, 2023 

  ┌ loss(icnf::RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, mode::TrainMode, xs::Matrix{Float32}, ps::ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, st::NamedTuple{(), Tuple{}}) @ ContinuousNormalizingFlows /home/runner/work/ContinuousNormalizingFlows.jl/ContinuousNormalizingFlows.jl/src/rnode.jl:280
  │┌ inference(icnf::RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, mode::TrainMode, xs::Matrix{Float32}, ps::ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, st::NamedTuple{(), Tuple{}}) @ ContinuousNormalizingFlows /home/runner/work/ContinuousNormalizingFlows.jl/ContinuousNormalizingFlows.jl/src/base_icnf.jl:123
  ││┌ inference_sol(icnf::RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, mode::TrainMode, prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}) @ ContinuousNormalizingFlows /home/runner/work/ContinuousNormalizingFlows.jl/ContinuousNormalizingFlows.jl/src/base.jl:129
  │││┌ kwcall(::NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, ::typeof(CommonSolve.solve), ::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}) @ DiffEqBase /home/runner/.julia/packages/DiffEqBase/SlYdg/src/solve.jl:923
  ││││┌ solve(::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}; sensealg::SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, u0::Nothing, p::Nothing, wrap::Val{true}, kwargs::Base.Pairs{Symbol, Any, NTuple{6, Symbol}, NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}}) @ DiffEqBase /home/runner/.julia/packages/DiffEqBase/SlYdg/src/solve.jl:933
  │││││┌ kwcall(::NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}, ::typeof(DiffEqBase.solve_up), ::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, ::SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, ::Matrix{Float32}, ::ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}) @ DiffEqBase /home/runner/.julia/packages/DiffEqBase/SlYdg/src/solve.jl:996
  ││││││┌ solve_up(::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, ::SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, ::Matrix{Float32}, ::ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}; kwargs::Base.Pairs{Symbol, Any, NTuple{6, Symbol}, NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}}) @ DiffEqBase /home/runner/.julia/packages/DiffEqBase/SlYdg/src/solve.jl:1010
  │││││││┌ kwcall(::NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}, ::typeof(DiffEqBase.solve_call), _prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, args::OrdinaryDiffEq.VCABM) @ DiffEqBase /home/runner/.julia/packages/DiffEqBase/SlYdg/src/solve.jl:527
  ││││││││┌ solve_call(_prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, args::OrdinaryDiffEq.VCABM; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::Base.Pairs{Symbol, Any, NTuple{6, Symbol}, NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}}) @ DiffEqBase /home/runner/.julia/packages/DiffEqBase/SlYdg/src/solve.jl:561
  │││││││││┌ kwcall(::NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}, ::typeof(SciMLBase.__solve), ::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, ::OrdinaryDiffEq.VCABM) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/solve.jl:1
  ││││││││││┌ __solve(::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, ::OrdinaryDiffEq.VCABM; kwargs::Base.Pairs{Symbol, Any, NTuple{6, Symbol}, NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}}) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/solve.jl:5
  │││││││││││┌ kwcall(::NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}, ::typeof(SciMLBase.__init), prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, alg::OrdinaryDiffEq.VCABM) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/solve.jl:10
  ││││││││││││┌ kwcall(::NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}, ::typeof(SciMLBase.__init), prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, alg::OrdinaryDiffEq.VCABM, timeseries_init::Tuple{}) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/solve.jl:10
  │││││││││││││┌ kwcall(::NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}, ::typeof(SciMLBase.__init), prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, alg::OrdinaryDiffEq.VCABM, timeseries_init::Tuple{}, ts_init::Tuple{}) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/solve.jl:10
  ││││││││││││││┌ kwcall(::NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}, ::typeof(SciMLBase.__init), prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, alg::OrdinaryDiffEq.VCABM, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/solve.jl:10
  │││││││││││││││┌ kwcall(::NamedTuple{(:alg_hints, :save_everystep, :alg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, Float32, Float32, Int32}}, ::typeof(SciMLBase.__init), prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, alg::OrdinaryDiffEq.VCABM, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{Val{true}}) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/solve.jl:10
  ││││││││││││││││┌ __init(prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, alg::OrdinaryDiffEq.VCABM, 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::Nothing, callback::Nothing, dense::Bool, calck::Bool, dt::Float32, dtmin::Nothing, dtmax::Float32, force_dtmin::Bool, adaptive::Bool, gamma::Rational{Int64}, abstol::Float32, reltol::Float32, 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::Int32, 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::OrdinaryDiffEq.DefaultInit, kwargs::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:alg_hints, :alg), Tuple{Vector{Symbol}, OrdinaryDiffEq.VCABM}}}) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/solve.jl:492
  │││││││││││││││││┌ initialize_dae!(integrator::OrdinaryDiffEq.ODEIntegrator{OrdinaryDiffEq.VCABM, false, Matrix{Float32}, Nothing, Float32, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, Float32, Float32, Float32, Float32, Vector{Matrix{Float32}}, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}, OrdinaryDiffEq.DEOptions{Float32, Float32, Float32, Float32, OrdinaryDiffEq.IController, typeof(DiffEqBase.ODE_DEFAULT_NORM), typeof(LinearAlgebra.opnorm), Nothing, SciMLBase.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, Int32, Tuple{}, Tuple{}, Tuple{}}, Matrix{Float32}, Float32, Nothing, OrdinaryDiffEq.DefaultInit}) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/initialize_dae.jl:49
  ││││││││││││││││││┌ initialize_dae!(integrator::OrdinaryDiffEq.ODEIntegrator{OrdinaryDiffEq.VCABM, false, Matrix{Float32}, Nothing, Float32, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, Float32, Float32, Float32, Float32, Vector{Matrix{Float32}}, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}, OrdinaryDiffEq.DEOptions{Float32, Float32, Float32, Float32, OrdinaryDiffEq.IController, typeof(DiffEqBase.ODE_DEFAULT_NORM), typeof(LinearAlgebra.opnorm), Nothing, SciMLBase.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, Int32, Tuple{}, Tuple{}, Tuple{}}, Matrix{Float32}, Float32, Nothing, OrdinaryDiffEq.DefaultInit}, initializealg::OrdinaryDiffEq.DefaultInit) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/initialize_dae.jl:49
  │││││││││││││││││││┌ _initialize_dae!(integrator::OrdinaryDiffEq.ODEIntegrator{OrdinaryDiffEq.VCABM, false, Matrix{Float32}, Nothing, Float32, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, Float32, Float32, Float32, Float32, Vector{Matrix{Float32}}, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}, OrdinaryDiffEq.DEOptions{Float32, Float32, Float32, Float32, OrdinaryDiffEq.IController, typeof(DiffEqBase.ODE_DEFAULT_NORM), typeof(LinearAlgebra.opnorm), Nothing, SciMLBase.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, Int32, Tuple{}, Tuple{}, Tuple{}}, Matrix{Float32}, Float32, Nothing, OrdinaryDiffEq.DefaultInit}, prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, alg::OrdinaryDiffEq.DefaultInit, x::Val{false}) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/initialize_dae.jl:64
  ││││││││││││││││││││┌ _initialize_dae!(integrator::OrdinaryDiffEq.ODEIntegrator{OrdinaryDiffEq.VCABM, false, Matrix{Float32}, Nothing, Float32, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, Float32, Float32, Float32, Float32, Vector{Matrix{Float32}}, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}, OrdinaryDiffEq.DEOptions{Float32, Float32, Float32, Float32, OrdinaryDiffEq.IController, typeof(DiffEqBase.ODE_DEFAULT_NORM), typeof(LinearAlgebra.opnorm), Nothing, SciMLBase.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, Int32, Tuple{}, Tuple{}, Tuple{}}, Matrix{Float32}, Float32, Nothing, OrdinaryDiffEq.DefaultInit}, prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, alg::OrdinaryDiffEq.BrownFullBasicInit{Float32, Nothing}, isinplace::Val{false}) @ OrdinaryDiffEq /home/runner/.julia/packages/OrdinaryDiffEq/wz2EI/src/initialize_dae.jl:466
  │││││││││││││││││││││ no matching method found `eachcol(::LinearAlgebra.UniformScaling{Bool})`: OrdinaryDiffEq.eachcol(M)
  ││││││││││││││││││││└────────────────────
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prbzrg commented Nov 29, 2023 

  ││┌ inference_sol(icnf::RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, mode::TrainMode, prob::SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}) @ ContinuousNormalizingFlows /home/runner/work/ContinuousNormalizingFlows.jl/ContinuousNormalizingFlows.jl/src/base.jl:133
  │││┌ -(A::Vector{Float32}, B::SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}) @ Base ./arraymath.jl:8
  ││││┌ broadcast_preserving_zero_d(::typeof(-), ::Vector{Float32}, ::SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}) @ Base.Broadcast ./broadcast.jl:862
  │││││┌ materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, typeof(-), Tuple{Vector{Float32}, SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}}}) @ Base.Broadcast ./broadcast.jl:873
  ││││││┌ copy(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, typeof(-), Tuple{Vector{Float32}, SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}}}) @ Base.Broadcast ./broadcast.jl:898
  │││││││┌ copyto!(dest::Vector{Float32}, bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, typeof(-), Tuple{Vector{Float32}, SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}}}) @ Base.Broadcast ./broadcast.jl:926
  ││││││││┌ copyto!(dest::Vector{Float32}, bc::Base.Broadcast.Broadcasted{Nothing, Tuple{Base.OneTo{Int64}}, typeof(-), Tuple{Vector{Float32}, SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}}}) @ Base.Broadcast ./broadcast.jl:970
  │││││││││┌ preprocess(dest::Vector{Float32}, bc::Base.Broadcast.Broadcasted{Nothing, Tuple{Base.OneTo{Int64}}, typeof(-), Tuple{Vector{Float32}, SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}}}) @ Base.Broadcast ./broadcast.jl:953
  ││││││││││┌ preprocess_args(dest::Vector{Float32}, args::Tuple{Vector{Float32}, SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}}) @ Base.Broadcast ./broadcast.jl:956
  │││││││││││┌ preprocess_args(dest::Vector{Float32}, args::Tuple{SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}}) @ Base.Broadcast ./broadcast.jl:957
  ││││││││││││┌ preprocess(dest::Vector{Float32}, x::SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}) @ Base.Broadcast ./broadcast.jl:954
  │││││││││││││┌ broadcast_unalias(dest::Vector{Float32}, src::SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}) @ Base.Broadcast ./broadcast.jl:947
  ││││││││││││││┌ unalias(dest::Vector{Float32}, A::SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}) @ Base ./abstractarray.jl:1482
  │││││││││││││││┌ unaliascopy(A::SubArray{Float32, 1, SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}, Int64}, false}) @ Base ./subarray.jl:105
  ││││││││││││││││┌ unaliascopy(A::SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}) @ Base ./abstractarray.jl:1499
  │││││││││││││││││┌ copy(VA::SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}) @ RecursiveArrayTools /home/runner/.julia/packages/RecursiveArrayTools/X30HP/src/vector_of_array.jl:351
  ││││││││││││││││││┌ getproperty(x::SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, s::Symbol) @ SciMLBase /home/runner/.julia/packages/SciMLBase/xja2M/src/solutions/ode_solutions.jl:125
  │││││││││││││││││││ type ODESolution has no field sc: SciMLBase.getfield(x::SciMLBase.ODESolution{Float32, 3, Vector{Matrix{Float32}}, Nothing, Nothing, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, SciMLBase.ODEProblem{Matrix{Float32}, Tuple{Float32, Float32}, false, ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(weight = ViewAxis(1:49, ShapedAxis((7, 7), NamedTuple())), bias = ViewAxis(50:56, ShapedAxis((7, 1), NamedTuple())))}}}, SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.VCABM, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{false, SciMLBase.FullSpecialize, ContinuousNormalizingFlows.var"#11#14"{RNODE{Float32, ZygoteMatrixMode, false, false, false, Lux.Dense{true, typeof(NNlib.tanh_fast), typeof(WeightInitializers.glorot_uniform), typeof(WeightInitializers.zeros32)}, Int64, ComputationalResources.CPU1{Nothing}, Distributions.MvNormal{Float32, PDMats.ScalMat{Float32}, FillArrays.Zeros{Float32, 1, Tuple{Base.OneTo{Int64}}}}, Tuple{Float32, Float32}, Distributions.Uniform{Float32}, AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, ADTypes.AutoZygote, NamedTuple{(:alg_hints, :save_everystep, :alg, :sensealg, :reltol, :abstol, :maxiters), Tuple{Vector{Symbol}, Bool, OrdinaryDiffEq.VCABM, SciMLSensitivity.InterpolatingAdjoint{0, true, Val{:central}, SciMLSensitivity.ZygoteVJP}, Float32, Float32, Int32}}, Random.TaskLocalRNG}, TrainMode, Matrix{Float32}, NamedTuple{(), Tuple{}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Vector{Matrix{Float32}}, Vector{Float32}, Vector{Vector{Matrix{Float32}}}, OrdinaryDiffEq.VCABMConstantCache{Vector{Float32}, Vector{Matrix{Float32}}, Matrix{Float32}, Float32, Vector{Float32}}}, SciMLBase.DEStats, Nothing}, s::Symbol)
  ││││││││││││││││││└────────────────────

@prbzrg prbzrg added enhancement New feature or request help wanted Extra attention is needed upstream labels Nov 29, 2023
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prbzrg commented Nov 29, 2023

Ref
https://github.com/impICNF/ContinuousNormalizingFlows.jl/actions/runs/6992289140/job/19023743559#step:5:1757

This was referenced Nov 29, 2023
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