bla.txt

julia> jprod_rev(F, rand(5), rand(5))
ERROR: DimensionMismatch("arrays could not be broadcast to a common size; got a dimension with lengths 5 and 6")
Stacktrace:
  [1] _bcs1
    @ ./broadcast.jl:501 [inlined]
  [2] _bcs
    @ ./broadcast.jl:495 [inlined]
  [3] broadcast_shape(::Tuple{Base.OneTo{Int64}}, ::Tuple{Base.OneTo{Int64}})
    @ Base.Broadcast ./broadcast.jl:489
  [4] combine_axes
    @ ./broadcast.jl:484 [inlined]
  [5] _axes
    @ ./broadcast.jl:209 [inlined]
  [6] axes
    @ ./broadcast.jl:207 [inlined]
  [7] copy
    @ ./broadcast.jl:1095 [inlined]
  [8] materialize
    @ ./broadcast.jl:883 [inlined]
  [9] special_reverse_exec!(instruction::ReverseDiff.SpecialInstruction{typeof(DiffEqBase.solve_up), Tuple{ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, ReverseDiff.TrackedArray{Float64, Int64, 1, Vector{Float64}, Vector{Int64}}, ODEFunction{true, typeof(ODE), UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Nothing, Vector{Float64}, ReverseDiff.TrackedArray{Float64, Int64, 1, Vector{Float64}, Vector{Int64}}, Vern9}, ReverseDiff.TrackedArray{Float64, Float64, 2, Matrix{Float64}, Matrix{Float64}}, Tuple{DiffEqSensitivity.var"#forward_sensitivity_backpass#231"{0, Float64, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, typeof(ODE), UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Vern9, ForwardDiffSensitivity{0, nothing}, Vector{Float64}, Vector{Float64}, Tuple{}, UnitRange{Int64}}, DiffEqBase.var"##solve_up#257#222"{DiffEqBase.var"##solve_up#257#221#223"}, NamedTuple{(:saveat,), Tuple{Float64}}}})
    @ DiffEqBase ~/.julia/packages/ReverseDiff/E4Tzn/src/macros.jl:218
 [10] reverse_exec!(instruction::ReverseDiff.SpecialInstruction{typeof(DiffEqBase.solve_up), Tuple{ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, ReverseDiff.TrackedArray{Float64, Int64, 1, Vector{Float64}, Vector{Int64}}, ODEFunction{true, typeof(ODE), UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Nothing, Vector{Float64}, ReverseDiff.TrackedArray{Float64, Int64, 1, Vector{Float64}, Vector{Int64}}, Vern9}, ReverseDiff.TrackedArray{Float64, Float64, 2, Matrix{Float64}, Matrix{Float64}}, Tuple{DiffEqSensitivity.var"#forward_sensitivity_backpass#231"{0, Float64, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, typeof(ODE), UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Vern9, ForwardDiffSensitivity{0, nothing}, Vector{Float64}, Vector{Float64}, Tuple{}, UnitRange{Int64}}, DiffEqBase.var"##solve_up#257#222"{DiffEqBase.var"##solve_up#257#221#223"}, NamedTuple{(:saveat,), Tuple{Float64}}}})
    @ ReverseDiff ~/.julia/packages/ReverseDiff/E4Tzn/src/tape.jl:93
 [11] reverse_pass!(tape::Vector{ReverseDiff.AbstractInstruction})
    @ ReverseDiff ~/.julia/packages/ReverseDiff/E4Tzn/src/tape.jl:87
 [12] reverse_pass!
    @ ~/.julia/packages/ReverseDiff/E4Tzn/src/api/tape.jl:36 [inlined]
 [13] seeded_reverse_pass!(result::Matrix{Int64}, output::ReverseDiff.TrackedArray{Float64, Float64, 1, Vector{Float64}, Vector{Float64}}, input::ReverseDiff.TrackedArray{Int64, Int64, 1, Vector{Int64}, Vector{Int64}}, tape::ReverseDiff.JacobianTape{var"#17#18"{typeof(F), Vector{Float64}, Vector{Float64}}, ReverseDiff.TrackedArray{Int64, Int64, 1, Vector{Int64}, Vector{Int64}}, ReverseDiff.TrackedArray{Float64, Float64, 1, Vector{Float64}, Vector{Float64}}})
    @ ReverseDiff ~/.julia/packages/ReverseDiff/E4Tzn/src/api/utils.jl:51
 [14] seeded_reverse_pass!
    @ ~/.julia/packages/ReverseDiff/E4Tzn/src/api/tape.jl:47 [inlined]
 [15] jacobian!
    @ ~/.julia/packages/ReverseDiff/E4Tzn/src/api/jacobians.jl:122 [inlined]
 [16] jacobian!(tape::ReverseDiff.JacobianTape{var"#17#18"{typeof(F), Vector{Float64}, Vector{Float64}}, ReverseDiff.TrackedArray{Int64, Int64, 1, Vector{Int64}, Vector{Int64}}, ReverseDiff.TrackedArray{Float64, Float64, 1, Vector{Float64}, Vector{Float64}}}, input::Vector{Int64})
    @ ReverseDiff ~/.julia/packages/ReverseDiff/E4Tzn/src/api/jacobians.jl:106
 [17] jacobian(f::Function, input::Vector{Int64}, cfg::ReverseDiff.JacobianConfig{ReverseDiff.TrackedArray{Int64, Int64, 1, Vector{Int64}, Vector{Int64}}, Nothing})
    @ ReverseDiff ~/.julia/packages/ReverseDiff/E4Tzn/src/api/jacobians.jl:25
 [18] jacobian
    @ ~/.julia/packages/ReverseDiff/E4Tzn/src/api/jacobians.jl:23 [inlined]
 [19] jprod_rev(f::typeof(F), x::Vector{Float64}, u::Vector{Float64})
    @ Main ./REPL[15]:1
 [20] top-level scope
    @ REPL[16]:1