diff --git a/tensorflow/python/kernel_tests/random/random_ops_test.py b/tensorflow/python/kernel_tests/random/random_ops_test.py
index e4b5c3832a2..0ef6a95cfc9 100644
--- a/tensorflow/python/kernel_tests/random/random_ops_test.py
+++ b/tensorflow/python/kernel_tests/random/random_ops_test.py
@@ -24,13 +24,42 @@ from six.moves import xrange  # pylint: disable=redefined-builtin
 from tensorflow.python.eager import context
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import random_seed
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import random_ops
 from tensorflow.python.ops import variables
 from tensorflow.python.platform import test
 
 
-class RandomNormalTest(test.TestCase):
+class RandomOpTestCommon(test.TestCase):
+
+  # Checks that executing the same rng_func multiple times rarely produces the
+  # same result.
+  def _testSingleSessionNotConstant(self,
+                                    rng_func,
+                                    num,
+                                    dtype,
+                                    min_or_mean,
+                                    max_or_stddev,
+                                    use_gpu,
+                                    op_seed=None,
+                                    graph_seed=None):
+    with self.test_session(use_gpu=use_gpu, graph=ops.Graph()) as sess:
+      if graph_seed is not None:
+        random_seed.set_random_seed(graph_seed)
+      x = rng_func([num], min_or_mean, max_or_stddev, dtype=dtype, seed=op_seed)
+
+      y = sess.run(x)
+      z = sess.run(x)
+      w = sess.run(x)
+
+      # We use exact equality here. If the random-number generator is producing
+      # the same output, all three outputs will be bitwise identical.
+      self.assertTrue((not np.array_equal(y, z)) or
+                      (not np.array_equal(z, w)) or (not np.array_equal(y, w)))
+
+
+class RandomNormalTest(RandomOpTestCommon):
 
   def _Sampler(self, num, mu, sigma, dtype, use_gpu, seed=None):
 
@@ -90,6 +119,36 @@ class RandomNormalTest(test.TestCase):
         diff = rnd2 - rnd1
         self.assertTrue(np.linalg.norm(diff.eval()) > 0.1)
 
+  def testSingleSessionNotConstant(self):
+    for use_gpu in [False, True]:
+      for dt in dtypes.float16, dtypes.float32, dtypes.float64:
+        self._testSingleSessionNotConstant(
+            random_ops.random_normal, 100, dt, 0.0, 1.0, use_gpu=use_gpu)
+
+  def testSingleSessionOpSeedNotConstant(self):
+    for use_gpu in [False, True]:
+      for dt in dtypes.float16, dtypes.float32, dtypes.float64:
+        self._testSingleSessionNotConstant(
+            random_ops.random_normal,
+            100,
+            dt,
+            0.0,
+            1.0,
+            use_gpu=use_gpu,
+            op_seed=1345)
+
+  def testSingleSessionGraphSeedNotConstant(self):
+    for use_gpu in [False, True]:
+      for dt in dtypes.float16, dtypes.float32, dtypes.float64:
+        self._testSingleSessionNotConstant(
+            random_ops.random_normal,
+            100,
+            dt,
+            0.0,
+            1.0,
+            use_gpu=use_gpu,
+            graph_seed=965)
+
 
 class TruncatedNormalTest(test.TestCase):
 
@@ -187,7 +246,7 @@ class TruncatedNormalTest(test.TestCase):
       self.assertAllEqual(rnd1, rnd2)
 
 
-class RandomUniformTest(test.TestCase):
+class RandomUniformTest(RandomOpTestCommon):
 
   def _Sampler(self, num, minv, maxv, dtype, use_gpu, seed=None):
 
@@ -291,6 +350,39 @@ class RandomUniformTest(test.TestCase):
         diff = (rnd2 - rnd1).eval()
         self.assertTrue(np.linalg.norm(diff) > 0.1)
 
+  def testSingleSessionNotConstant(self):
+    for use_gpu in [False, True]:
+      for dt in (dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int32,
+                 dtypes.int64):
+        self._testSingleSessionNotConstant(
+            random_ops.random_uniform, 100, dt, 0, 17, use_gpu=use_gpu)
+
+  def testSingleSessionOpSeedNotConstant(self):
+    for use_gpu in [False, True]:
+      for dt in (dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int32,
+                 dtypes.int64):
+        self._testSingleSessionNotConstant(
+            random_ops.random_uniform,
+            100,
+            dt,
+            10,
+            20,
+            use_gpu=use_gpu,
+            op_seed=1345)
+
+  def testSingleSessionGraphSeedNotConstant(self):
+    for use_gpu in [False, True]:
+      for dt in (dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int32,
+                 dtypes.int64):
+        self._testSingleSessionNotConstant(
+            random_ops.random_uniform,
+            100,
+            dt,
+            20,
+            200,
+            use_gpu=use_gpu,
+            graph_seed=965)
+
 
 class RandomShapeTest(test.TestCase):