message: Update of flat_map
  Rework based on Marks review
diff: @@ -1009,16 +1009,18 @@ class Dataset(object):
  def flat_map(self, map_func):
  """Maps `map_func` across this dataset and flattens the result.
  - Will produce similar results to `tf.data.Dataset.interleave(cycle_length=1)`.
  + `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:
  + For example, to implement unbatch:
  ```python
  # NOTE: The following examples use `{ ... }` to represent the
  # contents of a dataset. '[...]' represents a tensor.
  a = {[1,2,3,4,5], [6,7,8,9], [10]}
  - a.flat_map(lambda x: Dataset.from_tensors(x)) ==
  + a.flat_map(lambda x: Dataset.from_tensor_slices(x)) ==
  {[1,2,3,4,5,6,7,8,9,10]}
  ```
  Args:
  