What am I doing wrong withe this gradient computation?

``` f(x,y)=y*x^2 FiniteDiff.finite_difference_gradient(f,[1.,1.]) ROR: MethodError: no method matching ^(::Vector{Float64}, ::Int64) Closest candidates are: ^(::Union{AbstractChar, AbstractString}, ::Integer) @ Base strings/basic.jl:733 ^(::LinearAlgebra.Hermitian, ::Integer) @ LinearAlgebra ~/.julia/juliaup/julia-1.9.0+0.x64.linux.gnu/share/julia/stdlib/v1.9/LinearAlgebra/src/symmetric.jl:697 ^(::LinearAlgebra.Hermitian{T, S} where S<:(AbstractMatrix{<:T}), ::Real) where T @ LinearAlgebra ~/.julia/juliaup/julia-1.9.0+0.x64.linux.gnu/share/julia/stdlib/v1.9/LinearAlgebra/src/symmetric.jl:708 ... Stacktrace: [1] literal_pow @ ./intfuncs.jl:338 [inlined] [2] f(x::Vector{Float64}) @ Main ./REPL[13]:1 [3] finite_difference_gradient!(df::Vector{Float64}, f::typeof(f), x::Vector{Float64}, cache::FiniteDiff.GradientCache{Nothing, Nothing, Nothing, Vector{Float64}, Val{:central}(), Float64, Val{true}()}; relstep::Float64, absstep::Float64, dir::Bool) @ FiniteDiff ~/.julia/packages/FiniteDiff/grio1/src/gradients.jl:318 [4] finite_difference_gradient(f::typeof(f), x::Vector{Float64}, fdtype::Val{:central}, returntype::Type, inplace::Val{true}, fx::Nothing, c1::Nothing, c2::Nothing; relstep::Float64, absstep::Float64, dir::Bool) @ FiniteDiff ~/.julia/packages/FiniteDiff/grio1/src/gradients.jl:133 [5] finite_difference_gradient(f::Function, x::Vector{Float64}, fdtype::Val{:central}, returntype::Type, inplace::Val{true}, fx::Nothing, c1::Nothing, c2::Nothing) @ FiniteDiff ~/.julia/packages/FiniteDiff/grio1/src/gradients.jl:99 [6] finite_difference_gradient(f::Function, x::Vector{Float64}) @ FiniteDiff ~/.julia/packages/FiniteDiff/grio1/src/gradients.jl:99 [7] top-level scope @ REPL[116]:1 ``` I also tried with `FiniteDiff.finite_difference_gradient(f,1.,1.)` Thank you very much