message: [tf.data] Document how lists are treated as tensors instead of nested structure.
diff: @@ -152,14 +152,18 @@ class DatasetV2(tracking_base.Trackable, composite_tensor.CompositeTensor):
  Elements may be nested structures containing multiple components. For
  example, the element `(1, (3, "apple"))` has one tuple nested in another
  tuple. The components are `1`, `3`, and `"apple"`.
  +
  **Component**: The leaf in the nested structure of an element.
  Supported types:
  Elements can be nested structures of tuples, named tuples, and dictionaries.
  - Element components can be of any type representable by `tf.TypeSpec`,
  - including `tf.Tensor`, `tf.data.Dataset`, `tf.sparse.SparseTensor`,
  - `tf.RaggedTensor`, and `tf.TensorArray`.
  + Note that Python lists are *not* treated as nested structures of components.
  + Instead, lists are converted to tensors and treated as components. For
  + example, the element `(1, [1, 2, 3])` has only two components; the tensor `1`
  + and the tensor `[1, 2, 3]`. Element components can be of any type
  + representable by `tf.TypeSpec`, including `tf.Tensor`, `tf.data.Dataset`,
  + `tf.sparse.SparseTensor`, `tf.RaggedTensor`, and `tf.TensorArray`.
  >>> a = 1 # Integer element
  >>> b = 2.0 # Float element
  