Merge changes from github.

PiperOrigin-RevId: 201011811

1 files changed, 20 insertions, 1 deletions

diff --git a/tensorflow/python/ops/variable_scope.py b/tensorflow/python/ops/variable_scope.py
index f49e2d314d..47414c28af 100644
--- a/tensorflow/python/ops/variable_scope.py
+++ b/tensorflow/python/ops/variable_scope.py
@@ -1786,6 +1786,23 @@ class variable_scope(object):
           assert v.name == "foo/bar/v:0"
   ```
 
+  Simple example of how to reenter a premade variable scope safely:
+
+  ```python
+  with tf.variable_scope("foo") as vs:
+    pass
+
+  # Re-enter the variable scope.
+  with tf.variable_scope(vs,
+                         auxiliary_name_scope=False) as vs1:
+    # Restore the original name_scope.
+    with tf.name_scope(vs1.original_name_scope):
+        v = tf.get_variable("v", [1])
+        assert v.name == "foo/v:0"
+        c = tf.constant([1], name="c")
+        assert c.name == "foo/c:0"
+  ```
+
   Basic example of sharing a variable AUTO_REUSE:
 
   ```python
@@ -1924,7 +1941,9 @@ class variable_scope(object):
         (which must have the same shape). Constraints are not safe to
         use when doing asynchronous distributed training.
       auxiliary_name_scope: If `True`, we create an auxiliary name scope with
-        the scope. If `False`, we don't touch name scope.
+        the scope. If `False`, we don't create it. Note that the argument is
+        not inherited, and it only takes effect for once when creating. You
+        should only use it for re-entering a premade variable scope.
 
     Returns:
       A scope that can be captured and reused.