input: Write a function to optimize a given multivariate function using the scipy.optimize module. The function should take a function and an initial guess as input, and return the optimized values of the variables.
  
  assert optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1]) == [-9.14904225e-09, -9.14904225e-09]
  assert optimize_function(lambda x: (x[0]-2)**2 + (x[1]+3)**2, [0, 0]) == [2.00000005, -3.00000008]
  assert optimize_function(lambda x: x[0]*x[1], [1, 1]) == [1.13700267e-08, 1.13700267e-08]
  assert optimize_function(lambda x: (x[0]-3)**2 + (x[1]-4)**2, [5, 5]) == [3.00000001, 4.00000002]
  assert optimize_function(lambda x: x[0]**4 + x[1]**4, [1, 1]) == [0, 0]
output: def optimize_function(func, initial_guess):
      from scipy.optimize import minimize
      result = minimize(func, initial_guess)
      return result.x