# A type error of Turing
**URL:** https://discourse.julialang.org/t/a-type-error-of-turing/129279
**Category:** New to Julia
**Tags:** turing
**Created:** [May 23, 2025, 2:47pm UTC](https://discourse.julialang.org/t/a-type-error-of-turing/129279 "2025-05-23T14:47:47Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@Cyan](https://discourse.julialang.org/u/Cyan)
#### Post date: [May 23, 2025, 2:47pm UTC](https://discourse.julialang.org/t/a-type-error-of-turing/129279/1 "2025-05-23T14:47:47Z")
I want to use Turing to fit parameters from my costume function like
```julia
function sersic2d(x, y; I_e::Float64=1.0, r_e::Float64=1.0, n::Float64=1.0, x0::Float64=1.0, y0::Float64=1.0)
r = sqrt.((x .- x0) .^ 2 .+ (y .- y0) .^ 2)
return I_e .* exp.(-b_n(n) .* ((r ./ r_e) .^ (1 / n) .- 1))
end
```
But I got error of
```julia
MethodError: no method matching sersic2d(::Matrix{Float64}, ::Matrix{Float64}, ::Float64, ::Float64, ::Float64, ::Float64, ::Float64)
Closest candidates are:
sersic2d(::Any, ::Any; I_e, r_e, n, x0, y0)
@ Main ~/Documents/VScodeProjects/Jens/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X44sZmlsZQ==.jl:12
```
It seems the type of parameter in my function doesn’t match the function. How can I fix it?
Plus, it turns out
```julia
TypeError: in keyword argument I_e, expected Float64, got a value of type ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 6}
```
After I change ‘,’ to ‘;’ to separate keyword arguments.
---
### Author:  [@gdalle](https://discourse.julialang.org/u/gdalle)
#### Post date: [May 23, 2025, 2:57pm UTC](https://discourse.julialang.org/t/a-type-error-of-turing/129279/2 "2025-05-23T14:57:19Z")
It seems you called `sersic2d` by passing everything as a positional argument, instead of only the first two? Perhaps you forgot the semicolon `;` that is meant to separate keyword arguments?
---
### Author:  [@Cyan](https://discourse.julialang.org/u/Cyan)
#### Post date: [May 23, 2025, 3:01pm UTC](https://discourse.julialang.org/t/a-type-error-of-turing/129279/3 "2025-05-23T15:01:49Z")
Thanks, it works, but it turns out to be another error
```julia
TypeError: in keyword argument I_e, expected Float64, got a value of type ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 6}
```
---
### Author:  [@Eliassj](https://discourse.julialang.org/u/Eliassj)
#### Post date: [May 23, 2025, 4:23pm UTC](https://discourse.julialang.org/t/a-type-error-of-turing/129279/4 "2025-05-23T16:23:27Z")
In order for ForwardDiff.jl to work it passes a special number (`Dual`) through your function. So if you restrict your function to only accept `Float64` it won’t work with the `Dual` type that ForwardDiff passes to it. To solve this you could:
1. Remove the types from the function signature entirely
2. Relax the type assertions to `<:Real`
3. Use a different autodiff backend such as Mooncake.jl
I would recommend doing #1 unless the types are actually used for dispatch.
Limitations of ForwardDiff: [Limitations of ForwardDiff · ForwardDiff](https://juliadiff.org/ForwardDiff.jl/release-0.10/user/limitations.html)
How to switch autodiff backend in Turing: [Automatic Differentiation – Turing.jl](https://turinglang.org/docs/usage/automatic-differentiation/)
Julia docs on when to use types in functions: [Functions · The Julia Language](https://docs.julialang.org/en/v1/manual/functions/#Argument-type-declarations)