I’m testing out the ForwardDiff package for the first time, but unfortunately I’m getting a “No Method Matching” error that I can’t figure out. I was successful in making the following test example by mimicking the one in the documentation (https://github.com/JuliaDiff/ForwardDiff.jl):

```
f(x::Vector) = 4*(x[1])^2 + 2*(x[2])^3
x = [2.0,3.0]
grad(y) = ForwardDiff.gradient(f, y)
println(grad(x))
```

which gave [16.0, 54.0], as expected. However, when I tried this on a more complicated objective function called `objective`

, I got the following error:

```
MethodError: no method matching Float64(::ForwardDiff.Dual{ForwardDiff.Tag{var"#objective#282"{typeof(One_Age_Model_1eta),typeof(f_ICs),typeof(norm1),DataFrame,Array{String,1},Array{String,1},Array{Float64,1},Array{Union{Missing, Float64},1},Array{Union{Missing, Float64},1},Array{Float64,1},Array{Float64,1},Array{Int64,1},Array{Int64,1},Array{Int64,1},Array{Int64,1},Int64,Int64,Int64},Float64},Float64,10})
Closest candidates are:
Float64(::Real, !Matched::RoundingMode) where T<:AbstractFloat at rounding.jl:200
Float64(::T) where T<:Number at boot.jl:716
Float64(!Matched::Irrational{:ℯ}) at irrationals.jl:189
```

The objective function is fairly long, so I’ll just give an outline of my code:

```
function objective(x::Vector)
#The vector x contains a bunch of parameters which are used
#to solve an ODE system. (There are also a bunch of other objects
#needed to evaluate the function which are defined just before the
#function definition.)
#The ODE solution is compared against some data, and a residual
#vector is calculated by comparing the observed data with the
#ODE solution at a set of discrete points.
#The function returns an L^2 norm of the residual vector.
return norm
end
#Defining a gradient function
grad(y) = ForwardDiff.gradient(objective,y)
#Calling the gradient function gives the error shown earlier:
println(grad(x0))
```

Here, `x0`

is the input vector I’m using to test. I’ve confirmed that the objective function is working, and `objective(x0)`

gives the expected output. So where am I going wrong here? Any help would be greatly appreciated.