diff --git a/tensorflow/contrib/layers/python/layers/feature_column_test.py b/tensorflow/contrib/layers/python/layers/feature_column_test.py
index 67c2d3c6525210afc4753910512c9dc9a3e6657c..2e8bf9ffef298bc91025cd4db766b06d2f495d3f 100644
--- a/tensorflow/contrib/layers/python/layers/feature_column_test.py
+++ b/tensorflow/contrib/layers/python/layers/feature_column_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
 
 import itertools
 import os
+import tempfile
 
 import numpy as np
 import tensorflow as tf
@@ -609,7 +610,10 @@ class FeatureColumnTest(tf.test.TestCase):
             {embedding_col: input_tensor}, [embedding_col])
 
     save = tf.train.Saver()
-    checkpoint_path = os.path.join(self.get_temp_dir(), "model.ckpt")
+    ckpt_dir_prefix = os.path.join(
+        self.get_temp_dir(), "init_embedding_col_w_from_ckpt")
+    ckpt_dir = tempfile.mkdtemp(prefix=ckpt_dir_prefix)
+    checkpoint_path = os.path.join(ckpt_dir, "model.ckpt")
 
     with self.test_session() as sess:
       sess.run(tf.initialize_all_variables())
@@ -670,7 +674,10 @@ class FeatureColumnTest(tf.test.TestCase):
           assign_op = tf.assign(weight[0], weight[0] + 0.5)
 
     save = tf.train.Saver()
-    checkpoint_path = os.path.join(self.get_temp_dir(), "model.ckpt")
+    ckpt_dir_prefix = os.path.join(
+        self.get_temp_dir(), "init_crossed_col_w_from_ckpt")
+    ckpt_dir = tempfile.mkdtemp(prefix=ckpt_dir_prefix)
+    checkpoint_path = os.path.join(ckpt_dir, "model.ckpt")
 
     with self.test_session() as sess:
       sess.run(tf.initialize_all_variables())
diff --git a/tensorflow/contrib/lookup/lookup_ops_test.py b/tensorflow/contrib/lookup/lookup_ops_test.py
index 803cc3eb1ef5f0b11320a538bfdbdaf0e6be936a..d2d722214064d45165e0a28ce9832a102aa9c83c 100644
--- a/tensorflow/contrib/lookup/lookup_ops_test.py
+++ b/tensorflow/contrib/lookup/lookup_ops_test.py
@@ -18,6 +18,7 @@ from __future__ import division
 from __future__ import print_function
 
 import os
+import tempfile
 import numpy as np
 import six
 import tensorflow as tf
@@ -296,7 +297,8 @@ class MutableHashTableOpTest(tf.test.TestCase):
       self.assertAllEqual([0, 1, 2], sorted_values)
 
   def testSaveRestore(self):
-    save_path = os.path.join(self.get_temp_dir(), "hash")
+    save_dir = os.path.join(self.get_temp_dir(), "save_restore")
+    save_path = os.path.join(tempfile.mkdtemp(prefix=save_dir), "hash")
 
     with self.test_session(graph=tf.Graph()) as sess:
       v0 = tf.Variable(10.0, name="v0")
@@ -867,7 +869,8 @@ class MutableDenseHashTableOpTest(tf.test.TestCase):
                            [100, 0], [100, 0], [100, 0]], pairs)
 
   def testSaveRestore(self):
-    save_path = os.path.join(self.get_temp_dir(), "hash")
+    save_dir = os.path.join(self.get_temp_dir(), "save_restore")
+    save_path = os.path.join(tempfile.mkdtemp(prefix=save_dir), "hash")
 
     with self.test_session(graph=tf.Graph()) as sess:
       default_value = -1
@@ -922,7 +925,8 @@ class MutableDenseHashTableOpTest(tf.test.TestCase):
       self.assertAllEqual([-1, 0, 1, 2, -1], output.eval())
 
   def testVectorSaveRestore(self):
-    save_path = os.path.join(self.get_temp_dir(), "hash")
+    save_dir = os.path.join(self.get_temp_dir(), "vector_save_restore")
+    save_path = os.path.join(tempfile.mkdtemp(prefix=save_dir), "hash")
 
     with self.test_session(graph=tf.Graph()) as sess:
       empty_key = tf.constant([11, 13], tf.int64)
diff --git a/tensorflow/contrib/opt/python/training/moving_average_optimizer_test.py b/tensorflow/contrib/opt/python/training/moving_average_optimizer_test.py
index 4c24276cdd5e09ba830e9b49bf7479affc90ae0a..02ce9ff24fb1530ff726f045ed35f2a8450efc85 100644
--- a/tensorflow/contrib/opt/python/training/moving_average_optimizer_test.py
+++ b/tensorflow/contrib/opt/python/training/moving_average_optimizer_test.py
@@ -18,6 +18,7 @@ from __future__ import division
 from __future__ import print_function
 
 import os.path
+import tempfile
 
 import six
 import tensorflow as tf
@@ -40,7 +41,9 @@ class MovingAverageOptimizerTest(tf.test.TestCase):
               tf.train.GradientDescentOptimizer(learning_rate=2.0),
               average_decay=0.5,
               sequential_update=sequential_update)
-          save_path = os.path.join(self.get_temp_dir(), 'model')
+          save_dir = tempfile.mkdtemp(
+              prefix=os.path.join(self.get_temp_dir(), 'run_1'))
+          save_path = os.path.join(save_dir, 'model')
           update = opt.apply_gradients(
               list(six.moves.zip([grads0, grads1], [var0, var1])))
           train_saver = opt.swapping_saver()