anyeltypedual(::Type{Union{}}) is ambiguous

[daviehh]

Describe the bug 🐞
Regression: 6.146.0 works fine, v6.146.1 errors:

When the parameter p of ode solver contains the soltion to another ode, with the #999 it now errors w/

anyeltypedual(::Type{Union{}}) is ambiguous

Expected behavior

Allow p to contain ode solutions

Minimal Reproducible Example 👇

using OrdinaryDiffEq

f(u,p,t) = 1.01*u
u0=1/2
tspan = (0.0,1.0)
prob = ODEProblem(f,u0,tspan)
sol = solve(prob,Tsit5(),reltol=1e-8,abstol=1e-8)

OrdinaryDiffEq.DiffEqBase.anyeltypedual((;x=sol))

Error & Stacktrace ⚠️

ERROR: MethodError: anyeltypedual(::Type{Union{}}) is ambiguous.

Candidates:
  anyeltypedual(::Type{T}) where T<:ForwardDiff.Dual
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:130
  anyeltypedual(::Type{T}) where T<:(Tuple{Vararg{T, N}} where {N, T})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:144
  anyeltypedual(x::Type{T}) where T<:ForwardDiff.AbstractConfig
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:117
  anyeltypedual(::Type{T}) where T<:Union{Set, AbstractArray}
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:131

Possible fix, define
  anyeltypedual(::Type{Union{}})

Stacktrace:
  [1] (::Base.MappingRF{typeof(DiffEqBase.anyeltypedual), Base.BottomRF{typeof(DiffEqBase.promote_dual)}})(acc::Type, x::Type)
    @ Base ./reduce.jl:100
  [2] _foldl_impl(op::Base.MappingRF{typeof(DiffEqBase.anyeltypedual), Base.BottomRF{typeof(DiffEqBase.promote_dual)}}, init::Type, itr::Core.SimpleVector)
    @ Base ./reduce.jl:62
  [3] foldl_impl
    @ Base ./reduce.jl:48 [inlined]
  [4] mapfoldl_impl
    @ Base ./reduce.jl:44 [inlined]
  [5] mapfoldl
    @ Base ./reduce.jl:175 [inlined]
  [6] mapreduce
    @ Base ./reduce.jl:307 [inlined]
  [7] __anyeltypedual(::Type{@Kwargs{}})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:126
  [8] anyeltypedual(::Type{@Kwargs{}}, ::Type{Val{0}})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:129
  [9] anyeltypedual(::Type{@Kwargs{}})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:129
 [10] (::Base.MappingRF{typeof(DiffEqBase.anyeltypedual), Base.BottomRF{typeof(DiffEqBase.promote_dual)}})(acc::Type, x::Type)
    @ Base ./reduce.jl:100
 [11] _foldl_impl(op::Base.MappingRF{typeof(DiffEqBase.anyeltypedual), Base.BottomRF{typeof(DiffEqBase.promote_dual)}}, init::Type, itr::Core.SimpleVector)
    @ Base ./reduce.jl:62
 [12] foldl_impl
    @ Base ./reduce.jl:48 [inlined]
 [13] mapfoldl_impl
    @ Base ./reduce.jl:44 [inlined]
 [14] mapfoldl
    @ Base ./reduce.jl:175 [inlined]
 [15] mapreduce
    @ Base ./reduce.jl:307 [inlined]
 [16] __anyeltypedual(::Type{ODEProblem{Float64, Tuple{…}, false, SciMLBase.NullParameters, ODEFunction{…}, @Kwargs{}, SciMLBase.StandardODEProblem}})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:126
 [17] anyeltypedual(::Type{ODEProblem{Float64, Tuple{…}, false, SciMLBase.NullParameters, ODEFunction{…}, @Kwargs{}, SciMLBase.StandardODEProblem}}, ::Type{Val{1}})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:129
 [18] (::DiffEqBase.var"#69#70"{Int64})(x::Type)
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:102
 [19] (::Base.MappingRF{DiffEqBase.var"#69#70"{Int64}, Base.BottomRF{typeof(DiffEqBase.promote_dual)}})(acc::Type, x::Type)
    @ Base ./reduce.jl:100
 [20] _foldl_impl(op::Base.MappingRF{DiffEqBase.var"#69#70"{Int64}, Base.BottomRF{typeof(DiffEqBase.promote_dual)}}, init::Type, itr::Core.SimpleVector)
    @ Base ./reduce.jl:62
 [21] foldl_impl
    @ Base ./reduce.jl:48 [inlined]
 [22] mapfoldl_impl
    @ Base ./reduce.jl:44 [inlined]
 [23] mapfoldl
    @ Base ./reduce.jl:175 [inlined]
 [24] mapreduce
    @ Base ./reduce.jl:307 [inlined]
 [25] diffeqmapreduce(f::DiffEqBase.var"#69#70"{Int64}, op::typeof(DiffEqBase.promote_dual), x::Core.SimpleVector)
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:55
 [26] #s87#68
    @ ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:102 [inlined]
 [27] var"#s87#68"(counter::Any, ::Any, x::Any, ::Any)
    @ DiffEqBase ./none:0
 [28] (::Core.GeneratedFunctionStub)(::UInt64, ::LineNumberNode, ::Any, ::Vararg{Any})
    @ Core ./boot.jl:602
 [29] anyeltypedual
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:95 [inlined]
 [30] map
    @ Base ./tuple.jl:291 [inlined]
 [31] diffeqmapreduce
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:50 [inlined]
 [32] anyeltypedual
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:210 [inlined]
 [33] anyeltypedual(x::@NamedTuple{x::ODESolution{Float64, 1, Vector{…}, Nothing, Nothing, Vector{…}, Vector{…}, ODEProblem{…}, Tsit5{…}, OrdinaryDiffEq.InterpolationData{…}, SciMLBase.DEStats, Nothing}})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/UoaYd/src/forwarddiff.jl:210
 [34] top-level scope
    @ REPL[7]:1
Some type information was truncated. Use `show(err)` to see complete types.

Environment (please complete the following information):

• Output of using Pkg; Pkg.status()

[1dea7af3] OrdinaryDiffEq v6.70.1

• Output of versioninfo()

Julia Version 1.10.0
Commit 3120989f39b (2023-12-25 18:01 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: macOS (arm64-apple-darwin22.4.0)
  CPU: 10 × Apple M1 Pro
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, apple-m1)
  Threads: 11 on 8 virtual cores

Additional context

Add any other context about the problem here.

[daviehh]

also, mwe with ode.jl only:

using OrdinaryDiffEq

f(u,p,t) = 1.01*u
u0=1/2
tspan = (0.0,1.0)
prob = ODEProblem(f,u0,tspan)
sol = solve(prob,Tsit5(),reltol=1e-8,abstol=1e-8)

prob2 = ODEProblem((du,u,p,t) -> du[1]=1, [0.0], (0,10), (;x=sol))
solve(prob2, Tsit5())