code: def test_flatten_dict():
      val = {
          "k": npr.random((4, 4)),
          "k2": npr.random((3, 3)),
          "k3": 3.0,
          "k4": [1.0, 4.0, 7.0, 9.0],
      }
  
      vect, unflatten = flatten(val)
      val_recovered = unflatten(vect)
      vect_2, _ = flatten(val_recovered)
      assert np.all(vect == vect_2)
  
file_path: autograd/tests/test_misc.py
imports: import autograd.numpy
  import autograd.numpy.random
  from autograd.test_util import scalar_close
  from autograd import make_vjp, grad
  from autograd.tracer import primitive
  from autograd.misc import const_graph, flatten
label_desc: Use image node_id 5 for calling a global function with example usage: test_flatten_dict() without return types