code: def time_grad_flatten():
      val = {
          "k": npr.random((4, 4)),
          "k2": npr.random((3, 3)),
          "k3": 3.0,
          "k4": [1.0, 4.0, 7.0, 9.0],
          "k5": np.array([4.0, 5.0, 6.0]),
          "k6": np.array([[7.0, 8.0], [9.0, 10.0]]),
      }
  
      vect, unflatten = flatten(val)
  
      def fun(vec):
          v = unflatten(vec)
          return np.sum(v["k5"]) + np.sum(v["k6"])
  
      grad(fun)(vect)
  
imports: import autograd.numpy.random
  import autograd.numpy
  from autograd import grad
label_desc: Use image node_id 2 for calling a global function with example usage: time_grad_flatten() and returns: unknown