Moved example and changed wording

1 files changed, 5 insertions, 4 deletions

diff --git a/tensorflow/python/data/ops/dataset_ops.py b/tensorflow/python/data/ops/dataset_ops.py
index 2fc41a3b98..1b9ea2ed08 100644
--- a/tensorflow/python/data/ops/dataset_ops.py
+++ b/tensorflow/python/data/ops/dataset_ops.py
@@ -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