input: Write a function to optimize a given multivariate function using the scipy.optimize module. The function should take a function to be optimized and an initial guess as arguments, and return the optimized parameters. 
  assert optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1])==[0, 0]
  assert optimize_function(lambda x: (x[0]-2)**2 + (x[1]-3)**4, [5, 5])==[2, 3]
  assert optimize_function(lambda x: (x[0]-1)**2 + (x[1]+2)**2, [0, 0])==[1, -2]
  assert optimize_function(lambda x: (x[0]-4)**2 + (x[1]-4)**2, [4, 4])==[4, 4]
  assert optimize_function(lambda x: (x[0]-3)**2 + (x[1]-1)**2, [3, 2])==[3, 1]
output: 
  import scipy.optimize as opt
  
  def optimize_function(func, initial_guess):
      result = opt.minimize(func, initial_guess)
      return result.x
  