consider using identity for deepcopy of RGF

**Is your feature request related to a problem? Please describe.** I use Symbolics to generate code for some components in simulation. Sometimes, it is desired to copy those components. However it is still important to check, whether different components have the same functional behavior, i.e. are derived from the same models. This works with "normal" julia functions: ```julia f = function(du, u) du[1] = u[1]^2 du[2] = u[2]^2 end f2 = deepcopy(f) f == f2 # true f === f2 # true ``` However, the `==` and `===` property is lost on RGFs: ```julia using Symbolics @variables x y formulas = [x^2, y^2] _, f_rgf = build_function(formulas, [x, y]; expression=Val{false}) f_rgf2 = deepcopy(f_rgf) f_rgf == f_rgf2 # false f_rgf === f_rgf2 # false ``` **Describe the solution you’d like** I think it would be possible to define `deepcopy_internal` as stated in the [`deepcopy` docstring](https://docs.julialang.org/en/v1/base/base/#Base.deepcopy) to avoid this: ```julia using Symbolics.RuntimeGeneratedFunctions: RuntimeGeneratedFunction Base.deepcopy_internal(f::RuntimeGeneratedFunction, stackdict::IdDict) = f ``` This definition aligns the behavior of RGFs with "normal" functions. **Additional context** **DISCLAIMER:** I don't know the inner workings of RGF. Somebody who knows would need to chime in on that. Is the current behavior actually desired and important? If so, feel free to just close this issue :)