input: Write a function to optimize a given multivariate function using the Scipy library's minimize function. The function should take a target function and an initial guess as input and return the optimized values of the variables.
  
  import scipy.optimize as opt 
    
  def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x
  
  # Test cases
  def test_function(x): 
      return x[0]**2 + x[1]**2 + x[2]**3 
  
  assert optimize_function(test_function, [1, 1, 1]).all() == [0, 0, 0].all()
  assert optimize_function(test_function, [-1, -1, -1]).all() == [0, 0, 0].all()
  assert optimize_function(test_function, [2, 3, 4]).all() == [0, 0, 0].all()
  assert optimize_function(test_function, [-2, -3, -4]).all() == [0, 0, 0].all()
  
output: 
  def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x
  