ForwardDiff and FunctionWrappers

ChrisRackauckas · December 2, 2022, 9:57am

Easiest thing: set autodiff=false in the solver. It doesn’t make the hugest difference to performance anyways.

More time consuming: using FunctionWrappersWrappers.jl like how DiffEqBase does to support all of the Dual combinations.

github.com

SciML/DiffEqBase.jl/blob/v6.109.0/src/norecompile.jl#L3-L73


      
          const dualT = ForwardDiff.Dual{ForwardDiff.Tag{OrdinaryDiffEqTag, Float64}, Float64, 1}
          
          
dualgen(::Type{T}) where {T} = ForwardDiff.Dual{ForwardDiff.Tag{OrdinaryDiffEqTag, T}, T, 1}
          
          
const NORECOMPILE_IIP_SUPPORTED_ARGS = (Tuple{Vector{Float64}, Vector{Float64},
                                                        Vector{Float64}, Float64},
                                                  Tuple{Vector{Float64}, Vector{Float64},
                                                        SciMLBase.NullParameters, Float64})
          
          
const oop_arglists = (Tuple{Vector{Float64}, Vector{Float64}, Float64},
                                Tuple{Vector{Float64}, SciMLBase.NullParameters, Float64},
                                Tuple{Vector{Float64}, Vector{Float64}, dualT},
                                Tuple{Vector{dualT}, Vector{Float64}, Float64},
                                Tuple{Vector{dualT}, SciMLBase.NullParameters, Float64},
                                Tuple{Vector{Float64}, SciMLBase.NullParameters, dualT})
          
          
const NORECOMPILE_OOP_SUPPORTED_ARGS = (Tuple{Vector{Float64},
                                                        Vector{Float64}, Float64},
                                                  Tuple{Vector{Float64},
                                                        SciMLBase.NullParameters, Float64})

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ForwardDiff and FunctionWrappers

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