input: Write a python function to optimize a given function using scipy's minimize method.
  assert np.isclose(optimize_function(5*x + 3*y, [0, 0])[0], 0.0)
  assert np.isclose(optimize_function(5*x + 3*y, [0, 0])[1], 0.0)
  assert np.isclose(optimize_function(2*x + 4*y, [1, 1])[0], 1.0)
  assert np.isclose(optimize_function(2*x + 4*y, [1, 1])[1], 1.0)
output: import numpy as np
  from scipy.optimize import minimize
  from sympy import symbols, lambdify
  
  def optimize_function(expr, initial_guess):
      x, y = symbols('x y')
      func = lambdify((x, y), expr, 'numpy')
      
      def objective(vars):
          return func(vars[0], vars[1])
      
      result = minimize(objective, initial_guess)
      return result.x