ERROR: MethodError: no method matching -(::NTuple{29,Float64})

[shalinkpatel]

I am attempting to use DiffEqFlux for the first time and keep running into the error in the subject. Below is my code (I put in the VSCode screenshot so the data shapes are clear). I was wondering if I could get any help. I am a little new to the area and I might be doing something that's painfully wrong so please let me know.

Stacktrace:

Closest candidates are:
  -(::Any, ::ChainRulesCore.DoesNotExist) at /Users/shalinpatel/.julia/packages/ChainRulesCore/7m6Ti/src/differential_arithmetic.jl:25
  -(::Any, ::ChainRulesCore.Zero) at /Users/shalinpatel/.julia/packages/ChainRulesCore/7m6Ti/src/differential_arithmetic.jl:58
  -(::Any, ::VectorizationBase.Static{N}) where N at /Users/shalinpatel/.julia/packages/VectorizationBase/whL6J/src/static.jl:140
  ...
Stacktrace:
 [1] _broadcast_getindex_evalf at ./broadcast.jl:648 [inlined]
 [2] _broadcast_getindex at ./broadcast.jl:621 [inlined]
 [3] getindex at ./broadcast.jl:575 [inlined]
 [4] copy at ./broadcast.jl:876 [inlined]
 [5] materialize at ./broadcast.jl:837 [inlined]
 [6] broadcast_preserving_zero_d at ./broadcast.jl:826 [inlined]
 [7] -(::Array{Any,1}) at ./arraymath.jl:30
 [8] (::DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon})(::SubArray{Float32,1,Array{Float32,1},Tuple{UnitRange{Int64}},true}, ::Array{Float64,2}, ::Array{Float32,1}, ::Float64, ::Int64) at /Users/shalinpatel/.julia/packages/DiffEqSensitivity/tGdHI/src/local_sensitivity/concrete_solve.jl:119
 [9] (::DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}})(::OrdinaryDiffEq.ODEIntegrator{Tsit5,true,Array{Float32,1},Nothing,Float64,Array{Float32,1},Float64,Float64,Float64,Array{Array{Float32,1},1},ODESolution{Float32,2,Array{Array{Float32,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float32,1},1},1},ODEProblem{Array{Float32,1},Tuple{Float64,Float64},true,Array{Float32,1},ODEFunction{true,DiffEqSensitivity.ODEInterpolatingAdjointSensitivityFunction{DiffEqSensitivity.AdjointDiffCache{Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool}},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats},Nothing,ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Symbol,CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#35#40"{Bool,DiffEqCallbacks.var"#37#42"{Bool},DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},Base.RefValue{Union{Nothing, Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}},Tuple{Symbol},NamedTuple{(:callback,),Tuple{CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#35#40"{Bool,DiffEqCallbacks.var"#37#42"{Bool},DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},Base.RefValue{Union{Nothing, Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}}}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,DiffEqSensitivity.ODEInterpolatingAdjointSensitivityFunction{DiffEqSensitivity.AdjointDiffCache{Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool}},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats},Nothing,ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float32,1},1},Array{Float64,1},Array{Array{Array{Float32,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float32,1},Array{Float32,1},Array{Float32,1},OrdinaryDiffEq.Tsit5ConstantCache{Float32,Float64}}},DiffEqBase.DEStats},ODEFunction{true,DiffEqSensitivity.ODEInterpolatingAdjointSensitivityFunction{DiffEqSensitivity.AdjointDiffCache{Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool}},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats},Nothing,ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},OrdinaryDiffEq.Tsit5Cache{Array{Float32,1},Array{Float32,1},Array{Float32,1},OrdinaryDiffEq.Tsit5ConstantCache{Float32,Float64}},OrdinaryDiffEq.DEOptions{Float64,Float64,Float64,Float64,typeof(DiffEqBase.ODE_DEFAULT_NORM),typeof(LinearAlgebra.opnorm),CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#35#40"{Bool,DiffEqCallbacks.var"#37#42"{Bool},DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},Base.RefValue{Union{Nothing, Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}},typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN),typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE),typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK),DataStructures.BinaryHeap{Float64,DataStructures.LessThan},DataStructures.BinaryHeap{Float64,DataStructures.LessThan},Nothing,Nothing,Int64,Array{Float64,1},Array{Float64,1},Tuple{}},Array{Float32,1},Float32,Nothing,OrdinaryDiffEq.DefaultInit}) at /Users/shalinpatel/.julia/packages/DiffEqSensitivity/tGdHI/src/local_sensitivity/adjoint_common.jl:286
 [10] (::DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, 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Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}},typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN),typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE),typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK),DataStructures.BinaryHeap{Float64,DataStructures.LessThan},DataStructures.BinaryHeap{Float64,DataStructures.LessThan},Nothing,Nothing,Int64,Array{Float64,1},Array{Float64,1},Tuple{}},Array{Float32,1},Float32,Nothing,OrdinaryDiffEq.DefaultInit}) at /Users/shalinpatel/.julia/packages/DiffEqCallbacks/b4ahb/src/iterative_and_periodic.jl:45
 [12] initialize! at /Users/shalinpatel/.julia/packages/DiffEqBase/T5smF/src/callbacks.jl:325 [inlined]
 [13] initialize! at /Users/shalinpatel/.julia/packages/DiffEqBase/T5smF/src/callbacks.jl:315 [inlined]
 [14] initialize_callbacks!(::OrdinaryDiffEq.ODEIntegrator{Tsit5,true,Array{Float32,1},Nothing,Float64,Array{Float32,1},Float64,Float64,Float64,Array{Array{Float32,1},1},ODESolution{Float32,2,Array{Array{Float32,1},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float32,1},1},1},ODEProblem{Array{Float32,1},Tuple{Float64,Float64},true,Array{Float32,1},ODEFunction{true,DiffEqSensitivity.ODEInterpolatingAdjointSensitivityFunction{DiffEqSensitivity.AdjointDiffCache{Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool}},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats},Nothing,ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Symbol,CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, 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Float64}}}}}}}}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{true,DiffEqSensitivity.ODEInterpolatingAdjointSensitivityFunction{DiffEqSensitivity.AdjointDiffCache{Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool}},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats},Nothing,ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float32,1},1},Array{Float64,1},Array{Array{Array{Float32,1},1},1},OrdinaryDiffEq.Tsit5Cache{Array{Float32,1},Array{Float32,1},Array{Float32,1},OrdinaryDiffEq.Tsit5ConstantCache{Float32,Float64}}},DiffEqBase.DEStats},ODEFunction{true,DiffEqSensitivity.ODEInterpolatingAdjointSensitivityFunction{DiffEqSensitivity.AdjointDiffCache{Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool}},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats},Nothing,ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},OrdinaryDiffEq.Tsit5Cache{Array{Float32,1},Array{Float32,1},Array{Float32,1},OrdinaryDiffEq.Tsit5ConstantCache{Float32,Float64}},OrdinaryDiffEq.DEOptions{Float64,Float64,Float64,Float64,typeof(DiffEqBase.ODE_DEFAULT_NORM),typeof(LinearAlgebra.opnorm),CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#35#40"{Bool,DiffEqCallbacks.var"#37#42"{Bool},DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},Base.RefValue{Union{Nothing, Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}},typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN),typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE),typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK),DataStructures.BinaryHeap{Float64,DataStructures.LessThan},DataStructures.BinaryHeap{Float64,DataStructures.LessThan},Nothing,Nothing,Int64,Array{Float64,1},Array{Float64,1},Tuple{}},Array{Float32,1},Float32,Nothing,OrdinaryDiffEq.DefaultInit}, ::Bool) at /Users/shalinpatel/.julia/packages/OrdinaryDiffEq/yn1YB/src/solve.jl:521
 [15] __init(::ODEProblem{Array{Float32,1},Tuple{Float64,Float64},true,Array{Float32,1},ODEFunction{true,DiffEqSensitivity.ODEInterpolatingAdjointSensitivityFunction{DiffEqSensitivity.AdjointDiffCache{Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool}},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats},Nothing,ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Symbol,CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#35#40"{Bool,DiffEqCallbacks.var"#37#42"{Bool},DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},Base.RefValue{Union{Nothing, Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}},Tuple{Symbol},NamedTuple{(:callback,),Tuple{CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#35#40"{Bool,DiffEqCallbacks.var"#37#42"{Bool},DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},Base.RefValue{Union{Nothing, Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}}}}},DiffEqBase.StandardODEProblem}, ::Tsit5, ::Tuple{}, ::Tuple{}, ::Tuple{}, ::Type{Val{true}}; saveat::Array{Float64,1}, tstops::Array{Float64,1}, d_discontinuities::Tuple{}, save_idxs::Nothing, save_everystep::Bool, save_on::Bool, save_start::Bool, save_end::Bool, callback::CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#35#40"{Bool,DiffEqCallbacks.var"#37#42"{Bool},DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},Base.RefValue{Union{Nothing, Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}}, dense::Bool, calck::Bool, dt::Float64, dtmin::Nothing, dtmax::Float64, force_dtmin::Bool, adaptive::Bool, gamma::Rational{Int64}, abstol::Float64, reltol::Float64, qmin::Rational{Int64}, qmax::Int64, qsteady_min::Int64, qsteady_max::Int64, qoldinit::Rational{Int64}, fullnormalize::Bool, failfactor::Int64, beta1::Nothing, beta2::Nothing, maxiters::Int64, internalnorm::typeof(DiffEqBase.ODE_DEFAULT_NORM), internalopnorm::typeof(LinearAlgebra.opnorm), isoutofdomain::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), unstable_check::typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), verbose::Bool, timeseries_errors::Bool, dense_errors::Bool, advance_to_tstop::Bool, stop_at_next_tstop::Bool, initialize_save::Bool, progress::Bool, progress_steps::Int64, progress_name::String, progress_message::typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), userdata::Nothing, allow_extrapolation::Bool, initialize_integrator::Bool, alias_u0::Bool, alias_du0::Bool, initializealg::OrdinaryDiffEq.DefaultInit, kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at /Users/shalinpatel/.julia/packages/OrdinaryDiffEq/yn1YB/src/solve.jl:403
 [16] #__solve#382 at /Users/shalinpatel/.julia/packages/OrdinaryDiffEq/yn1YB/src/solve.jl:4 [inlined]
 [17] solve_call(::ODEProblem{Array{Float32,1},Tuple{Float64,Float64},true,Array{Float32,1},ODEFunction{true,DiffEqSensitivity.ODEInterpolatingAdjointSensitivityFunction{DiffEqSensitivity.AdjointDiffCache{Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool}},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats},Nothing,ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Symbol,CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#35#40"{Bool,DiffEqCallbacks.var"#37#42"{Bool},DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},Base.RefValue{Union{Nothing, Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}},Tuple{Symbol},NamedTuple{(:callback,),Tuple{CallbackSet{Tuple{},Tuple{DiscreteCallback{DiffEqCallbacks.var"#33#38"{Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}},DiffEqCallbacks.var"#35#40"{Bool,DiffEqCallbacks.var"#37#42"{Bool},DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},Base.RefValue{Union{Nothing, Float64}},DiffEqCallbacks.var"#34#39"{DiffEqSensitivity.var"#94#96"{Base.RefValue{Int64},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}},DiffEqSensitivity.var"#95#97"{DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon},DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Base.OneTo{Int64},UnitRange{Int64},LinearAlgebra.UniformScaling{Bool},Bool,Nothing,Nothing,Nothing,Nothing,Bool,Array{Float32,1},StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}},Array{Float64,2},Base.RefValue{Int64},Int64,LinearAlgebra.UniformScaling{Bool}},Base.RefValue{Union{Nothing, Float64}}}}}}}}}},DiffEqBase.StandardODEProblem}, ::Tsit5; merge_callbacks::Bool, kwargs::Base.Iterators.Pairs{Symbol,Any,NTuple{6,Symbol},NamedTuple{(:save_everystep, :save_start, :saveat, :tstops, :abstol, :reltol),Tuple{Bool,Bool,Array{Float64,1},Array{Float64,1},Float64,Float64}}}) at /Users/shalinpatel/.julia/packages/DiffEqBase/T5smF/src/solve.jl:92
 [18] #solve_up#461 at /Users/shalinpatel/.julia/packages/DiffEqBase/T5smF/src/solve.jl:114 [inlined]
 [19] #solve#460 at /Users/shalinpatel/.julia/packages/DiffEqBase/T5smF/src/solve.jl:102 [inlined]
 [20] _adjoint_sensitivities(::ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats}, ::DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool}, ::Tsit5, ::DiffEqSensitivity.var"#df#134"{Array{Any,1},Array{Float64,2},Colon}, ::StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}, ::Nothing; abstol::Float64, reltol::Float64, checkpoints::Array{Float64,1}, kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at /Users/shalinpatel/.julia/packages/DiffEqSensitivity/tGdHI/src/local_sensitivity/sensitivity_interface.jl:22
 [21] _adjoint_sensitivities(::ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats}, ::DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool}, ::Tsit5, ::Function, ::StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}, ::Nothing) at /Users/shalinpatel/.julia/packages/DiffEqSensitivity/tGdHI/src/local_sensitivity/sensitivity_interface.jl:13 (repeats 2 times)
 [22] adjoint_sensitivities(::ODESolution{Float64,3,Array{Array{Float64,2},1},Nothing,Nothing,Array{Float64,1},Array{Array{Array{Float64,2},1},1},ODEProblem{Array{Float64,2},Tuple{Float64,Float64},false,Array{Float32,1},ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}},DiffEqBase.StandardODEProblem},Tsit5,OrdinaryDiffEq.InterpolationData{ODEFunction{false,DiffEqFlux.var"#dudt_#104"{NeuralODE{FastChain{Tuple{var"#9#10",FastDense{typeof(tanh),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}},FastDense{typeof(identity),DiffEqFlux.var"#initial_params#89"{typeof(Flux.glorot_uniform),typeof(Flux.zeros),Int64,Int64}}}},Array{Float32,1},Nothing,Tuple{Float64,Float64},Tuple{Tsit5},Base.Iterators.Pairs{Symbol,Float64,Tuple{Symbol},NamedTuple{(:saveat,),Tuple{Float64}}}}},LinearAlgebra.UniformScaling{Bool},Nothing,typeof(DiffEqFlux.basic_tgrad),Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing},Array{Array{Float64,2},1},Array{Float64,1},Array{Array{Array{Float64,2},1},1},OrdinaryDiffEq.Tsit5ConstantCache{Float64,Float64}},DiffEqBase.DEStats}, ::Tsit5, ::Vararg{Any,N} where N; sensealg::DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool}, kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at /Users/shalinpatel/.julia/packages/DiffEqSensitivity/tGdHI/src/local_sensitivity/sensitivity_interface.jl:6
 [23] (::DiffEqSensitivity.var"#adjoint_sensitivity_backpass#133"{Tsit5,DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},Array{Float32,1},Tuple{},Colon})(::Array{Any,1}) at /Users/shalinpatel/.julia/packages/DiffEqSensitivity/tGdHI/src/local_sensitivity/concrete_solve.jl:127
 [24] #694#back at /Users/shalinpatel/.julia/packages/ZygoteRules/6nssF/src/adjoint.jl:55 [inlined]
 [25] #179 at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/lib/lib.jl:178 [inlined]
 [26] (::Zygote.var"#1732#back#181"{Zygote.var"#179#180"{DiffEqBase.var"#694#back#474"{DiffEqSensitivity.var"#adjoint_sensitivity_backpass#133"{Tsit5,DiffEqSensitivity.InterpolatingAdjoint{0,true,Val{:central},DiffEqSensitivity.ZygoteVJP,Bool},Array{Float64,2},Array{Float32,1},Tuple{},Colon}},Tuple{NTuple{6,Nothing},Tuple{Nothing}}}})(::Array{Any,1}) at /Users/shalinpatel/.julia/packages/ZygoteRules/6nssF/src/adjoint.jl:49
 [27] #solve#460 at /Users/shalinpatel/.julia/packages/DiffEqBase/T5smF/src/solve.jl:102 [inlined]
 [28] (::typeof(∂(#solve#460)))(::Array{Any,1}) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/compiler/interface2.jl:0
 [29] (::Zygote.var"#179#180"{typeof(∂(#solve#460)),Tuple{NTuple{6,Nothing},Tuple{Nothing}}})(::Array{Any,1}) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/lib/lib.jl:178
 [30] (::Zygote.var"#1732#back#181"{Zygote.var"#179#180"{typeof(∂(#solve#460)),Tuple{NTuple{6,Nothing},Tuple{Nothing}}}})(::Array{Any,1}) at /Users/shalinpatel/.julia/packages/ZygoteRules/6nssF/src/adjoint.jl:49
 [31] (::typeof(∂(solve##kw)))(::Array{Any,1}) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/compiler/interface2.jl:0
 [32] (::Zygote.var"#179#180"{typeof(∂(solve##kw)),Tuple{Tuple{Nothing,Nothing,Nothing},Tuple{Nothing}}})(::Array{Any,1}) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/lib/lib.jl:178
 [33] #1732#back at /Users/shalinpatel/.julia/packages/ZygoteRules/6nssF/src/adjoint.jl:49 [inlined]
 [34] NeuralODE at /Users/shalinpatel/.julia/packages/DiffEqFlux/FZMwP/src/neural_de.jl:77 [inlined]
 [35] (::typeof(∂(λ)))(::Array{Any,1}) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/compiler/interface2.jl:0
 [36] #13 at /Volumes/GoogleDrive/My Drive/Brown/Research/Stocks_DL/scripts/n_ode.jl:25 [inlined]
 [37] (::typeof(∂(λ)))(::Array{Float64,1}) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/compiler/interface2.jl:0
 [38] #589 at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/lib/array.jl:192 [inlined]
 [39] #3 at ./generator.jl:36 [inlined]
 [40] iterate at ./generator.jl:47 [inlined]
 [41] collect(::Base.Generator{Base.Iterators.Zip{Tuple{Array{typeof(∂(λ)),1},NTuple{1258,Array{Float64,1}}}},Base.var"#3#4"{Zygote.var"#589#593"}}) at ./array.jl:686
 [42] map at ./abstractarray.jl:2248 [inlined]
 [43] (::Zygote.var"#588#592"{Array{typeof(∂(λ)),1}})(::NTuple{1258,Array{Float64,1}}) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/lib/array.jl:192
 [44] (::Zygote.var"#2665#back#594"{Zygote.var"#588#592"{Array{typeof(∂(λ)),1}}})(::NTuple{1258,Array{Float64,1}}) at /Users/shalinpatel/.julia/packages/ZygoteRules/6nssF/src/adjoint.jl:49
 [45] predict at /Volumes/GoogleDrive/My Drive/Brown/Research/Stocks_DL/scripts/n_ode.jl:25 [inlined]
 [46] (::typeof(∂(predict)))(::Array{Float64,2}) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/compiler/interface2.jl:0
 [47] loss at /Volumes/GoogleDrive/My Drive/Brown/Research/Stocks_DL/scripts/n_ode.jl:29 [inlined]
 [48] #179 at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/lib/lib.jl:178 [inlined]
 [49] (::Zygote.var"#1732#back#181"{Zygote.var"#179#180"{typeof(∂(loss)),Tuple{Tuple{Nothing},Tuple{}}}})(::Tuple{Float64,Nothing}) at /Users/shalinpatel/.julia/packages/ZygoteRules/6nssF/src/adjoint.jl:49
 [50] #33 at /Users/shalinpatel/.julia/packages/DiffEqFlux/FZMwP/src/train.jl:99 [inlined]
 [51] (::typeof(∂(λ)))(::Float64) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/compiler/interface2.jl:0
 [52] (::Zygote.var"#54#55"{Zygote.Params,Zygote.Context,typeof(∂(λ))})(::Float64) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/compiler/interface.jl:177
 [53] gradient(::Function, ::Zygote.Params) at /Users/shalinpatel/.julia/packages/Zygote/seGHk/src/compiler/interface.jl:54
 [54] macro expansion at /Users/shalinpatel/.julia/packages/DiffEqFlux/FZMwP/src/train.jl:98 [inlined]
 [55] macro expansion at /Users/shalinpatel/.julia/packages/ProgressLogging/BBN0b/src/ProgressLogging.jl:328 [inlined]
 [56] (::DiffEqFlux.var"#32#37"{DiffEqFlux.var"#36#41",Int64,Bool,Bool,typeof(loss),Array{Float32,1},Zygote.Params})() at /Users/shalinpatel/.julia/packages/DiffEqFlux/FZMwP/src/train.jl:43
 [57] with_logstate(::Function, ::Any) at ./logging.jl:408
 [58] with_logger at ./logging.jl:514 [inlined]
 [59] maybe_with_logger(::DiffEqFlux.var"#32#37"{DiffEqFlux.var"#36#41",Int64,Bool,Bool,typeof(loss),Array{Float32,1},Zygote.Params}, ::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger,DiffEqBase.var"#10#12"},LoggingExtras.EarlyFilteredLogger{Logging.ConsoleLogger,DiffEqBase.var"#11#13"}}}) at /Users/shalinpatel/.julia/packages/DiffEqBase/T5smF/src/utils.jl:259
 [60] sciml_train(::Function, ::Array{Float32,1}, ::ADAM, ::Base.Iterators.Cycle{Tuple{DiffEqFlux.NullData}}; cb::Function, maxiters::Int64, progress::Bool, save_best::Bool) at /Users/shalinpatel/.julia/packages/DiffEqFlux/FZMwP/src/train.jl:42
 [61] top-level scope at /Volumes/GoogleDrive/My Drive/Brown/Research/Stocks_DL/scripts/n_ode.jl:35
in expression starting at /Volumes/GoogleDrive/My Drive/Brown/Research/Stocks_DL/scripts/n_ode.jl:35

[ChrisRackauckas]

I'm not sure what you are trying to do with that predict function. The ways you're using ... are very unnecessary. Did you mean

reduce(hcat,[n_ode(x,p)[end] for x in X])

?

[shalinkpatel]

Probably. I wanted to create something that predicts one timestep into the future but I have 1258 timesteps that I can train on. So for each of these points in time I wanted to get a prediction for one step into the future and then train on the loss between these values and the actual values that were recorded. So predict collates the results of this into a 29x1258 Matrix as there are 29 different series I am training this against.

[ChrisRackauckas]

Then just do Array(sol) and save the time series?

[shalinkpatel]

Maybe this doesn't make sense, but I want to reset the initial conditions each time-step. So at time 0 I use the i.c. as the system state at time 0 and predict for time 1. For time 1 I want to use the actual values at time 1 as the i.c. and predict for time 2 and so on.

[shalinkpatel]

I guess this doesn't make much sense I and I should predict on the whole time series.

[ChrisRackauckas]

actual values, as in from the dataset?

[shalinkpatel]

Yes. But in either case, would I not end up with a 29 x 1258 matrix as the output of the system? Is the issue here that Zygote can't differentiate through the ...?

[ChrisRackauckas]

Then reduce(hcat,[n_ode(x,p)[end] for x in X]) is exactly what you want.

[shalinkpatel]

Got it thanks! Appreciate it.

[ChrisRackauckas]

No problem. It should just work, and be a lot faster since splatting can be slow.

[shalinkpatel]

Yea works like a charm now.