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 inputs, 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 all(abs(optimize_function(lambda x: (x[0] - 3)**2 + (x[1] + 2)**2, [0, 0]) - [3, -2]) < 1e-6)
  assert all(abs(optimize_function(lambda x: (x[0] + 1)**4 + (x[1] - 2)**4, [0, 0]) - [-1, 2]) < 1e-6)
  assert all(abs(optimize_function(lambda x: x[0]**2 + x[1]**2, [5, 5]) - [0, 0]) < 1e-6)
  assert all(abs(optimize_function(lambda x: (x[0] - 1)**2 + (x[1] - 4)**2, [-5, 5]) - [1, 4]) < 1e-6)
output: def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x