message: Fix non-deterministic doctest.
  The doctest relied on the order of keys in a dictionary, which isn't always the same.
diff: @@ -1532,23 +1532,26 @@ class DatasetV2(tracking_base.Trackable, composite_tensor.CompositeTensor):
  >>> def g(x):
  ... return tf.constant(37.0), tf.constant(["Foo", "Bar", "Baz"])
  >>> result = dataset.map(g)
  - >>> result
  - <MapDataset shapes: ((), (3,)), types: (tf.float32, tf.string)>
  + >>> result.element_spec
  + (TensorSpec(shape=(), dtype=tf.float32, name=None), TensorSpec(shape=(3,), \
  +dtype=tf.string, name=None))
  >>> # Python primitives, lists, and NumPy arrays are implicitly converted to
  >>> # `tf.Tensor`.
  >>> def h(x):
  ... return 37.0, ["Foo", "Bar"], np.array([1.0, 2.0], dtype=np.float64)
  >>> result = dataset.map(h)
  - >>> result
  - <MapDataset shapes: ((), (2,), (2,)), \
  -types: (tf.float32, tf.string, tf.float64)>
  + >>> result.element_spec
  + (TensorSpec(shape=(), dtype=tf.float32, name=None), TensorSpec(shape=(2,), \
  +dtype=tf.string, name=None), TensorSpec(shape=(2,), dtype=tf.float64, \
  +name=None))
  >>> # `map_func` can return nested structures.
  >>> def i(x):
  - ... return {"a": 37.0, "b": [42, 16]}, "foo"
  + ... return (37.0, [42, 16]), "foo"
  >>> result = dataset.map(i)
  - >>> result
  - <MapDataset shapes: ({a: (), b: (2,)}, ()), \
  -types: ({a: tf.float32, b: tf.int32}, tf.string)>
  + >>> result.element_spec
  + ((TensorSpec(shape=(), dtype=tf.float32, name=None),
  + TensorSpec(shape=(2,), dtype=tf.int32, name=None)),
  + TensorSpec(shape=(), dtype=tf.string, name=None))
  `map_func` can accept as arguments and return any type of dataset element.
  