Add an API for third order tensor products

[amontoison]

It will be great to have a few routines to compute tensor products.
We can do that with Enzyme.jl and add a backend for it in ADNLPModels.jl.

[tmigot]

I have the code, for third order products so I can upload it and see how can improve it :).

[tmigot]

@amontoison Do you have a link to what Enzyme is doing for this?

[amontoison]

@wsmoses and @michel2323 can probably better explain than me.
The first step is to add it in the API on Enzyme.jl,
I discussed about it with Michel this morning.
I hope that we can discuss about that all together next week during AD2024.

[amontoison]

We discussed about the API for n-th order tensor products with @michel2323 and we think that this API could be relevant:

"""
    tensor_projection(nlp, n, x, directions, args...)

Computes the projection of the n-th derivative of `nlp` at `x` along the specified directions.

# Arguments

- `nlp`: An NLPModel.
- `n::Int`: The order of the derivative to compute.
- `x::AbstractVector`: The point at which the derivative is evaluated.
- `directions::Tuple{Int, Vararg{Int}}`: A tuple of indices specifying the derivative directions 
  (e.g., `(1, 2)` for a tensor projection along the first and second axes).
- `args...`: A list of vectors, one for each direction specified in `directions`.

# Output

The projection of the n-th derivative of `nlp` at `x` along the specified directions.
"""
function tensor_projection end