input: Write a function to optimize a given multivariate function using the scipy.optimize.minimize function. The function should take a multivariate function and an initial guess for the optimization 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, 0.0]
  assert list(optimize_function(lambda x: (x[0] - 1) ** 2 + (x[1] - 2) ** 2, [0, 0]))==[1.0, 2.0]
  assert list(optimize_function(lambda x: x[0] ** 2 + 4 * x[0] * x[1] + x[1] ** 2, [0.5, 0.5]))==[-1.0, -1.0]
output: def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x