input: Write a function to optimize a given multivariate function using the `scipy.optimize` module. The function should take a multivariate function and an initial guess as input, and return the optimized parameters.
  assert (optimize_function(lambda x: x[0]**2 + x[1]**4, [1, 1]) == [0, 0]).all()
  assert (optimize_function(lambda x: x[0]**4 + x[1]**2, [2, 2]) == [0, 0]).all()
  assert (optimize_function(lambda x: x[0] + x[1], [10, 5]) != [0, 0]).all()
  assert (optimize_function(lambda x: x[0]**2 + x[1]**2, [4, 4]) == [0, 0]).all()
  assert (optimize_function(lambda x: x[0] + x[1]**2, [1, 1]) == [1, 0]).all()
output: 
  import scipy.optimize as opt
  
  def optimize_function(func, initial_guess):
      result = opt.minimize(func, initial_guess)
      return result.x
  