# ForwardDiff - MethodError: no method matching extract\_jacobian

**URL:** <https://discourse.julialang.org/t/forwarddiff-methoderror-no-method-matching-extract-jacobian/124724>\
**Category:** General Usage\
**Tags:** forwarddiff, julia\
**Created:** [January 13, 2025, 1:06pm UTC](https://discourse.julialang.org/t/forwarddiff-methoderror-no-method-matching-extract-jacobian/124724 "2025-01-13T13:06:48Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![Adrien\_Vet](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/adrien_vet/32/214670_2.png) [@Adrien\_Vet](https://discourse.julialang.org/u/Adrien_Vet)\
**Post date:** [January 13, 2025, 1:06pm UTC](https://discourse.julialang.org/t/forwarddiff-methoderror-no-method-matching-extract-jacobian/124724/1 "2025-01-13T13:06:48Z")

</div>

Hello everyone,

I’m struggling with the differentiation of some functions using the `ForwardDiff` package. Here is a reproducible example :

```julia
using StaticArrays
using ForwardDiff

function f_test(x)
       return exp(x[1])*sin(x[2])
end

y = SVector(0.0, 0.0) # or a random SVector

ForwardDiff.jacobian(f_test, y)

```

Unfortunately I get this error:

```julia
ERROR: MethodError: no method matching extract_jacobian(::Type{ForwardDiff.Tag{…}}, ::ForwardDiff.Dual{ForwardDiff.Tag{…}, Float64, 2}, ::SVector{2, Float64})

Closest candidates are:
  extract_jacobian(::Type{T}, ::StaticArray, ::S) where {T, S<:StaticArray}
   @ ForwardDiffStaticArraysExt C:\Users\Adrien VET\.julia\packages\ForwardDiff\UBbGT\ext\ForwardDiffStaticArraysExt.jl:74
  extract_jacobian(::Type{T}, ::AbstractArray, ::StaticArray) where T
   @ ForwardDiffStaticArraysExt C:\Users\Adrien VET\.julia\packages\ForwardDiff\UBbGT\ext\ForwardDiffStaticArraysExt.jl:84

Stacktrace:
 [1] vector_mode_jacobian
   @ C:\Users\Adrien VET\.julia\packages\ForwardDiff\UBbGT\ext\ForwardDiffStaticArraysExt.jl:91 [inlined]
 [2] jacobian(f::typeof(f_test), x::SVector{2, Float64})
   @ ForwardDiffStaticArraysExt C:\Users\Adrien VET\.julia\packages\ForwardDiff\UBbGT\ext\ForwardDiffStaticArraysExt.jl:66
 [3] top-level scope
   @ REPL[99]:1
Some type information was truncated. Use `show(err)` to see complete types.

```

I don’t get why I have this error. I see in the docstring that the function to differentiate has to take an `AbstractArray` and output an `AbstractArray` ; and every `SVector` is indeed an `AbstractArray`…

---

<div class="post-metadata">

**Author:** ![Adrien\_Vet](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/adrien_vet/32/214670_2.png) [@Adrien\_Vet](https://discourse.julialang.org/u/Adrien_Vet)\
**Post date:** [January 13, 2025, 1:12pm UTC](https://discourse.julialang.org/t/forwarddiff-methoderror-no-method-matching-extract-jacobian/124724/2 "2025-01-13T13:12:48Z")

</div>

Alright, quick response lol. I just figured out my problem by reading this post again. The output HAS to be an abstract vector, and my function output was a Float which is NOT an abstract vector.

To fix the problem you have to output something like `(SVector(exp(x[1])*sin(x[2])))` which is a `1-element SVector{1, Float64}`.

This topic can be closed

---

<div class="post-metadata">

**Author:** ![eldee](https://avatars.discourse-cdn.com/v4/letter/e/b5a626/32.png) [@eldee](https://discourse.julialang.org/u/eldee)\
**Post date:** [January 13, 2025, 6:10pm UTC](https://discourse.julialang.org/t/forwarddiff-methoderror-no-method-matching-extract-jacobian/124724/3 "2025-01-13T18:10:44Z")

</div>

Alternatively (as also hinted to in `?ForwardDiff.jacobian`), you can get the 1 \times n Jacobian of a scalar-valued function `f` at an n-D point `x` via `ForwardDiff.gradient(f, x)`, though the Jacobian will then be represented as a length-`n` `Vector`. If you want `size(...) == (1, n)`, you can always just transpose it.

```julia
using StaticArrays
using ForwardDiff

function f_test(x)
       return exp(x[1])*sin(x[2])
end

y = SVector(0.0, 0.0) # or a random SVector

ForwardDiff.gradient(f_test, y)'
# 1×2 adjoint(::SVector{2, Float64}) with eltype Float64 with indices SOneTo(1)×SOneTo(2):
# 0.0 1.0

```

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<div class="post-metadata">

**Author:** ![mcabbott](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mcabbott/32/6603_2.png) [@mcabbott](https://discourse.julialang.org/u/mcabbott)\
**Post date:** [January 13, 2025, 6:18pm UTC](https://discourse.julialang.org/t/forwarddiff-methoderror-no-method-matching-extract-jacobian/124724/4 "2025-01-13T18:18:33Z")

</div>

ForwardDiff will usually friendly errors when you use the wrong function:

```julia
julia> ForwardDiff.jacobian(f_test, [0.0, 0.0])
ERROR: DimensionMismatch: jacobian(f, x) expects that f(x) is an array. Perhaps you meant gradient(f, x)?
...

julia> ForwardDiff.gradient(f_test, [0.0, 0.0])
2-element Vector{Float64}:
 0.0
 1.0

```

The fact that you get an internal error instead with StaticArrays is arguably a bug, perhaps make an issue?