input: Write a function to optimize a given multivariate function using the scipy.optimize library. The function should take two arguments: the first argument is the function to be optimized, and the second argument is the initial guess for the optimization. The function should return the optimal values of the function.
  import scipy.optimize as opt 
    
  def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x
  
  assert optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1])==[0, 0]
  assert optimize_function(lambda x: x[0]**2 - x[1]**2, [3, 4])==[0, 0]
  assert optimize_function(lambda x: x[0]**2 + x[1]**2 - 2*x[1] + 5, [-1, -1])==[0, 1]
  assert optimize_function(lambda x: x[0]**3 + x[1]**3 - 6*x[0]*x[1], [2, 2])==[0, 0]
  assert optimize_function(lambda x: x[0] + x[1], [-5, -5])==[-5, -5]
output: def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x