message: Moved example and changed wording
diff: @@ -1009,11 +1009,8 @@ class Dataset(object):
  def flat_map(self, map_func):
  """Maps `map_func` across this dataset and flattens the result.
  - `tf.data.Dataset.interleave()` is a generalization of `flat_map`, since
  - `flat_map` produces a similar outputs as `tf.data.Dataset.interleave(cycle_length=1)`
  -
  Use `flat_map` if you want to make sure, that the order of your dataset stays the same.
  - For example, to implement unbatch:
  + For example, to flatten a dataset of batches into a dataset of their elements:
  ```python
  # NOTE: The following examples use `{ ... }` to represent the
  @@ -1023,6 +1020,10 @@ class Dataset(object):
  a.flat_map(lambda x: Dataset.from_tensor_slices(x)) ==
  {[1,2,3,4,5,6,7,8,9,10]}
  ```
  +
  + `tf.data.Dataset.interleave()` is a generalization of `flat_map`, since
  + `flat_map` produces the same output as `tf.data.Dataset.interleave(cycle_length=1)`
  +
  Args:
  map_func: A function mapping a nested structure of tensors (having shapes
  and types defined by `self.output_shapes` and `self.output_types`) to a
  