From a2b9788ce440c350d4e3fef53fe0c51ba1c10c1a Mon Sep 17 00:00:00 2001
From: Frank Li <lif@google.com>
Date: Wed, 29 Jun 2016 16:30:37 -0800
Subject: [PATCH] Ensure ExponentialMovingAverage returns correct average_name
when used in scope Fixes #2740 Change: 126251978
---
tensorflow/python/training/moving_averages.py | 5 ++-
.../python/training/moving_averages_test.py | 31 +++++++++++++++++++
.../python/training/slot_creator_test.py | 8 +++++
3 files changed, 43 insertions(+), 1 deletion(-)
diff --git a/tensorflow/python/training/moving_averages.py b/tensorflow/python/training/moving_averages.py
index 9cc1d917ab1..4bbb89ff897 100644
--- a/tensorflow/python/training/moving_averages.py
+++ b/tensorflow/python/training/moving_averages.py
@@ -339,7 +339,10 @@ class ExponentialMovingAverage(object):
by the `ExponentialMovingAverage class` to hold the moving average of
`var`.
"""
- return var.op.name + "/" + self._name
+ if var in self._averages:
+ return self._averages[var].op.name
+ return ops.get_default_graph().unique_name(
+ var.op.name + "/" + self._name, mark_as_used=False)
def variables_to_restore(self, moving_avg_variables=None):
"""Returns a map of names to `Variables` to restore.
diff --git a/tensorflow/python/training/moving_averages_test.py b/tensorflow/python/training/moving_averages_test.py
index 437f2170fb3..413c38e601a 100644
--- a/tensorflow/python/training/moving_averages_test.py
+++ b/tensorflow/python/training/moving_averages_test.py
@@ -208,6 +208,37 @@ class ExponentialMovingAverageTest(tf.test.TestCase):
self.assertEqual(ema.average_name(v1), ema.average(v1).op.name)
self.assertEqual(ema.average_name(tensor2), ema.average(tensor2).op.name)
+ def testAverageVariablesNamesRespectScope(self):
+ # See discussion on #2740.
+ with self.test_session():
+ with tf.variable_scope("scope1"):
+ v0 = tf.Variable(10.0, name="v0")
+ v1 = tf.Variable(30.0, name="v1")
+ # Add a non-trainable variable.
+ v2 = tf.Variable(20.0, name="v2", trainable=False)
+ tensor2 = v0 + v1
+ with tf.variable_scope("scope2"):
+ ema = tf.train.ExponentialMovingAverage(0.25, name="foo_avg")
+ self.assertEqual("scope2/scope1/v0/foo_avg", ema.average_name(v0))
+ self.assertEqual("scope2/scope1/v1/foo_avg", ema.average_name(v1))
+ self.assertEqual("scope2/scope1/add/foo_avg", ema.average_name(tensor2))
+ ema.apply([v0, v1, tensor2])
+ vars_to_restore = ema.variables_to_restore()
+ # vars_to_restore should contain the following:
+ # {scope2/scope1/v0/foo_avg : v0,
+ # scope2/scope1/v1/foo_avg : v1,
+ # scope2/scope1/add/foo_avg : add/foo_avg
+ # scope1/v2 : v2}
+ self.assertEqual(sorted(vars_to_restore.keys()),
+ sorted([ema.average_name(v0),
+ ema.average_name(v1),
+ ema.average_name(tensor2),
+ v2.op.name]))
+ self.assertEqual(ema.average_name(v0), ema.average(v0).op.name)
+ self.assertEqual(ema.average_name(v1), ema.average(v1).op.name)
+ self.assertEqual(ema.average_name(tensor2),
+ ema.average(tensor2).op.name)
+
def testSubsetAverageVariablesNames(self):
with self.test_session():
v0 = tf.Variable(10.0, name="v0")
diff --git a/tensorflow/python/training/slot_creator_test.py b/tensorflow/python/training/slot_creator_test.py
index 8a11e44d1e6..4e2b980751d 100644
--- a/tensorflow/python/training/slot_creator_test.py
+++ b/tensorflow/python/training/slot_creator_test.py
@@ -73,5 +73,13 @@ class SlotCreatorTest(tf.test.TestCase):
self.assertEqual(slot.dtype.base_dtype, tf.float32)
self.assertAllEqual(slot.eval(), [0.0, 0.0])
+ def testCreateSlotFromVariableRespectsScope(self):
+ # See discussion on #2740.
+ with self.test_session():
+ with tf.variable_scope("scope"):
+ v = tf.Variable([1.0, 2.5], name="var")
+ slot = slot_creator.create_slot(v, v.initialized_value(), name="slot")
+ self.assertEqual(slot.op.name, "scope/scope/var/slot")
+
if __name__ == "__main__":
tf.test.main()