input: Write a function to optimize a given multivariate function using the scipy.optimize module. The function should take as input a callable function and an initial guess for the variables, and return the optimized values of the variables.
  assert list(optimize_function(lambda x: (x[0] - 2)**2 + (x[1] - 3)**2, [0, 0]))==[2.0, 3.0]
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1]))==[0.0, 0.0]
  assert list(optimize_function(lambda x: (x[0] - 1)**2 + (x[1] + 2)**2, [-1, 2]))==[1.0, -2.0]
output: def optimize_function(func, initial_guess):
      from scipy.optimize import minimize
      result = minimize(func, initial_guess)
      return result.x