input: Write a function to optimize a given multivariate function using the scipy.optimize module. The function should take the multivariate function and an initial guess as inputs, and return the optimal solution as an array.
  assert optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1])==[0, 0]
  assert optimize_function(lambda x: (x[0] - 2)**2 + (x[1] - 3)**2, [0, 0])==[2, 3]
  assert optimize_function(lambda x: (x[0]**2)/3 + 3*x[1]**2, [4, 1])==[0, 0]
  assert optimize_function(lambda x: x[0]**4 + x[1]**4, [-1, -1])==[0, 0]
  assert optimize_function(lambda x: abs(x[0]) + abs(x[1]), [2, 2])==[0, 0]
output: def optimize_function(func, initial_guess):
      from scipy.optimize import minimize
      result = minimize(func, initial_guess)
      return result.x