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authorGravatar TensorFlower Gardener <gardener@tensorflow.org>2018-08-08 19:31:21 -0700
committerGravatar TensorFlower Gardener <gardener@tensorflow.org>2018-08-08 19:31:21 -0700
commitacb75f221312fc82c1a2a5a642bd6b02dd87ee5f (patch)
tree5be40aa0bc535aa30a512514f3c7316b2b682172
parentf3a52fea81868e49e2ebf0e7d6ba6dda5081b1a3 (diff)
parent163aae337c875efce2518c3cd0fecb61968fe408 (diff)
Merge pull request #20876 from elielhojman:master
PiperOrigin-RevId: 207984120
-rw-r--r--tensorflow/python/data/ops/iterator_ops.py4
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/python/data/ops/iterator_ops.py b/tensorflow/python/data/ops/iterator_ops.py
index 83c541c2f7..f2dfea69a8 100644
--- a/tensorflow/python/data/ops/iterator_ops.py
+++ b/tensorflow/python/data/ops/iterator_ops.py
@@ -221,8 +221,8 @@ class Iterator(checkpointable.CheckpointableBase):
This method allows you to define a "feedable" iterator where you can choose
between concrete iterators by feeding a value in a @{tf.Session.run} call.
- In that case, `string_handle` would a @{tf.placeholder}, and you would feed
- it with the value of @{tf.data.Iterator.string_handle} in each step.
+ In that case, `string_handle` would be a @{tf.placeholder}, and you would
+ feed it with the value of @{tf.data.Iterator.string_handle} in each step.
For example, if you had two iterators that marked the current position in
a training dataset and a test dataset, you could choose which to use in