input: Write a function to optimize a given multivariate function using the scipy.optimize library. The function should take a multivariate 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
  
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1]))==[0, 0]
  assert list(optimize_function(lambda x: (x[0]-2)**2 + (x[1]+3)**2, [0, 0]))==[2, -3]
  assert list(optimize_function(lambda x: x[0]**2 - 4*x[0] + x[1]**2 - 4*x[1], [0, 0]))==[2, 2]
  assert list(optimize_function(lambda x: (x[0]-1)**2 + (x[1]-1)**2, [0, 0]))==[1, 1]
output: def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x