https://github.com/beliavsky/optimization-codes-by-chatgpt

numerical optimization subroutines in Fortran generated by ChatGPT-4
https://github.com/beliavsky/optimization-codes-by-chatgpt

chatgpt chatgpt4 conjugate-gradient conjugate-gradient-descent fortran gradient-descent hooke-jeeves nelder-mead numerical-optimization simulated-annealing unconstrained-optimization

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numerical optimization subroutines in Fortran generated by ChatGPT-4

• Host: GitHub
• URL: https://github.com/beliavsky/optimization-codes-by-chatgpt
• Owner: Beliavsky
• Created: 2023-05-19T18:54:49.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-06-07T14:03:05.000Z (over 1 year ago)
• Last Synced: 2024-01-29T14:45:06.350Z (11 months ago)
• Topics: chatgpt, chatgpt4, conjugate-gradient, conjugate-gradient-descent, fortran, gradient-descent, hooke-jeeves, nelder-mead, numerical-optimization, simulated-annealing, unconstrained-optimization
• Language: Fortran
• Homepage:
• Size: 46.9 KB
• Stars: 5
• Watchers: 1
• Forks: 0
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

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README

        
# Optimization Codes by ChatGPT

The prompts given to ChatGPT-4 are shown in the codes. Sometimes cleanup was required. This is an experiment in code generation by ChatGPT -- the codes should not be relied upon.

Compile with 

`gfortran optim_util.f90 hooke_jeeves.f90 simulated_annealing.f90 adam.f90 nelder_mead.f90 conjugate_gradient_min.f90 bfgs_min.f90 luus_jaakola.f90 gradient_descent.f90 xminimize.f90`

Works with gfortran 12.0.1 20220213 and ifort version 2021.6.0.

## Some ChatGPT-4 quirks

* When ChatGPT-4 generates code, it often forgets the `import` statement that is needed in the interface below.

```Fortran

    interface

        function funk(x)

            import :: dp

            real(kind=dp), dimension(:), intent(in) :: x

            real(kind=dp) :: funk

        end function funk

    end interface`

```

* It can produce code with `implicit none` and undeclared variables that does not compile. It tends to declare a variable `i` as integer even in a procedure that does not use the variable `i`.

* When ChatGPT-4 translated some algorithms from the literature with `g*g'` or equivalently `g*transpose(g)`, it erroneously translated this to `g**2` in Fortran instead of `sum(g**2)`.

* ChatGPT-4 sometimes forgets that the `random_number()` intrinsic is a subroutine, not a function, so that you cannot write 

```

x = random_number()

```

* ChatGPT-4 sometimes declares as `intent(in)` an argument that needs to be `intent(in out)`, since its initial value in changed in the procedure.

* ChatGPT-4 can incorrectly use a procedure argument in what is supposed to be a constant expression, as in

```Fortran

module sv_mod

use kind_mod, only: dp

use random_mod, only: random_normal

implicit none

contains

subroutine ret(n, kappa, theta, eta, y, x)

integer      , intent(in)    :: n

real(kind=dp), intent(in)    :: kappa, theta, eta

real(kind=dp), intent(out)   :: y(n), x(n)

! for line below, gfortran says 'Error: Parameter 'n' at (1) has not been declared or is a variable, which does not reduce to a constant expression'

real(kind=dp)                :: dt = 1.0_dp / n 

integer                      :: i

real(kind=dp)                :: dW, dV

y(1) = theta

do i=2,n

   dW = sqrt(dt) * random_normal()

   dV = sqrt(dt) * random_normal()

   y(i) = y(i-1) + kappa * (theta - y(i-1)) * dt + eta * sqrt(max(0.0_dp, y(i-1))) * dV

   x(i) = exp(y(i-1)) * dW

end do

end subroutine ret

end module sv_mod

```