Move from deprecated self.test_session() to self.cached_session().

self.test_session() has been deprecated in 9962eb5e84b15e309410071b06c2ed2d6148ed44 as its name confuses readers of the test. Moving to cached_session() instead which is more explicit about:
* the fact that the session may be reused.
* the session is not closed even when doing a "with self.test_session()" statement.

PiperOrigin-RevId: 209703613

21 files changed, 98 insertions, 98 deletions

diff --git a/tensorflow/contrib/autograph/converters/builtin_functions_test.py b/tensorflow/contrib/autograph/converters/builtin_functions_test.py
index d5c3e2c250..d0a0cbbeb6 100644
--- a/tensorflow/contrib/autograph/converters/builtin_functions_test.py
+++ b/tensorflow/contrib/autograph/converters/builtin_functions_test.py
@@ -36,7 +36,7 @@ class BuiltinFunctionsTest(converter_testing.TestCase):
 
     with self.converted(test_fn, builtin_functions, {'len': len},
                         array_ops.shape) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         ops = result.test_fn(constant_op.constant([0, 0, 0]))
         self.assertEqual(sess.run(ops), 3)
 
@@ -49,7 +49,7 @@ class BuiltinFunctionsTest(converter_testing.TestCase):
       return print(a)
 
     with self.converted(test_fn, builtin_functions, {'print': print}) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         with self.assertPrints('a\n'):
           sess.run(result.test_fn('a'))
 
@@ -62,7 +62,7 @@ class BuiltinFunctionsTest(converter_testing.TestCase):
       return print(a, b, c)
 
     with self.converted(test_fn, builtin_functions, {'print': print}) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         with self.assertPrints('a 1 [2, 3]\n'):
           sess.run(
               result.test_fn(
diff --git a/tensorflow/contrib/autograph/converters/call_trees_test.py b/tensorflow/contrib/autograph/converters/call_trees_test.py
index 8cdba659ee..ca4d1f2932 100644
--- a/tensorflow/contrib/autograph/converters/call_trees_test.py
+++ b/tensorflow/contrib/autograph/converters/call_trees_test.py
@@ -91,7 +91,7 @@ class CallTreesTest(converter_testing.TestCase):
       setattr(a, 'foo', 'bar')
 
     with self.converted(test_fn, call_trees, {'setattr': setattr}) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
 
         class Dummy(object):
           pass
@@ -110,7 +110,7 @@ class CallTreesTest(converter_testing.TestCase):
 
     with self.converted(test_fn, call_trees, {'np': np},
                         dtypes.int64) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         self.assertTrue(isinstance(result.test_fn(), ops.Tensor))
         self.assertIn(sess.run(result.test_fn()), (0, 1, 2))
 
@@ -129,7 +129,7 @@ class CallTreesTest(converter_testing.TestCase):
     node = call_trees.transform(node, ctx)
 
     with self.compiled(node, ns) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         result_tensor = result.test_fn(constant_op.constant(1))
         self.assertEquals(sess.run(result_tensor), 3)
 
diff --git a/tensorflow/contrib/autograph/converters/control_flow_test.py b/tensorflow/contrib/autograph/converters/control_flow_test.py
index ade3501426..6cb907f69a 100644
--- a/tensorflow/contrib/autograph/converters/control_flow_test.py
+++ b/tensorflow/contrib/autograph/converters/control_flow_test.py
@@ -33,7 +33,7 @@ class ControlFlowTest(converter_testing.TestCase):
       inputs = (inputs,)
     with self.converted(test_fn, control_flow, {},
                         constant_op.constant) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         self.assertEqual(sess.run(result.test_fn(*inputs)), expected)
 
   def test_while_basic(self):
@@ -89,7 +89,7 @@ class ControlFlowTest(converter_testing.TestCase):
       return obj
 
     with self.converted(test_fn, control_flow, {}) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         res_obj = result.test_fn(constant_op.constant(1), TestClass(0, 0))
         self.assertEqual(sess.run((res_obj.a, res_obj.b)), (-1, 0))
         res_obj = result.test_fn(constant_op.constant(-1), TestClass(0, 0))
diff --git a/tensorflow/contrib/autograph/converters/lists_test.py b/tensorflow/contrib/autograph/converters/lists_test.py
index 996e99ee61..c5e2dcf75e 100644
--- a/tensorflow/contrib/autograph/converters/lists_test.py
+++ b/tensorflow/contrib/autograph/converters/lists_test.py
@@ -65,7 +65,7 @@ class ListTest(converter_testing.TestCase):
 
     ns = {'special_functions': special_functions}
     with self.converted(test_fn, lists, ns) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         tl = result.test_fn()
         r = list_ops.tensor_list_stack(tl, dtypes.int32)
         self.assertAllEqual(sess.run(r), [1, 2, 3])
@@ -88,7 +88,7 @@ class ListTest(converter_testing.TestCase):
     node = lists.transform(node, ctx)
 
     with self.compiled(node, ns, dtypes.int32) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         ts, tl = result.test_fn()
         r = list_ops.tensor_list_stack(tl, dtypes.int32)
         self.assertAllEqual(sess.run(r), [1, 2])
@@ -122,7 +122,7 @@ class ListTest(converter_testing.TestCase):
     node = lists.transform(node, ctx)
 
     with self.compiled(node, {}, array_ops.stack, dtypes.int32) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         self.assertAllEqual(sess.run(result.test_fn()), [1, 2, 3])
 
   # TODO(mdan): Add a test with tf.stack with axis kwarg.
diff --git a/tensorflow/contrib/autograph/converters/logical_expressions_test.py b/tensorflow/contrib/autograph/converters/logical_expressions_test.py
index ca07de5e8a..8f9eee7081 100644
--- a/tensorflow/contrib/autograph/converters/logical_expressions_test.py
+++ b/tensorflow/contrib/autograph/converters/logical_expressions_test.py
@@ -33,7 +33,7 @@ class GradientsFunctionTest(converter_testing.TestCase):
 
     with self.converted(test_fn, logical_expressions, {},
                         math_ops.equal) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         self.assertTrue(sess.run(result.test_fn(1, 1)))
         self.assertFalse(sess.run(result.test_fn(1, 2)))
 
@@ -44,7 +44,7 @@ class GradientsFunctionTest(converter_testing.TestCase):
 
     with self.converted(test_fn, logical_expressions, {}, math_ops.logical_or,
                         math_ops.logical_and) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         self.assertTrue(sess.run(result.test_fn(True, False, True)))
 
 
diff --git a/tensorflow/contrib/autograph/converters/side_effect_guards_test.py b/tensorflow/contrib/autograph/converters/side_effect_guards_test.py
index bee512abbc..5fe5114d4b 100644
--- a/tensorflow/contrib/autograph/converters/side_effect_guards_test.py
+++ b/tensorflow/contrib/autograph/converters/side_effect_guards_test.py
@@ -46,7 +46,7 @@ class SideEffectGuardsTest(converter_testing.TestCase):
     self.assertEqual(len(node.body), 1)
 
     with self.compiled(node, {}, state_ops.assign) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         v = variable_scope.get_variable('test', initializer=2)
         sess.run(v.initializer)
         sess.run(result.test_fn(v))
@@ -67,7 +67,7 @@ class SideEffectGuardsTest(converter_testing.TestCase):
     self.assertEqual(len(node.body), 1)
 
     with self.compiled(node, {}, state_ops.assign) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         v = variable_scope.get_variable('test', initializer=2)
         sess.run(v.initializer)
         sess.run(result.test_fn(v))
@@ -87,7 +87,7 @@ class SideEffectGuardsTest(converter_testing.TestCase):
     self.assertEqual(len(node.body), 1)
 
     with self.compiled(node, {}, control_flow_ops.Assert) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         with self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
                                      'expected in throw'):
           sess.run(result.test_fn(constant_op.constant(-1)))
@@ -107,7 +107,7 @@ class SideEffectGuardsTest(converter_testing.TestCase):
     self.assertEqual(len(node.body), 1)
 
     with self.compiled(node, {}, state_ops.assign_add) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         v = variable_scope.get_variable('test', initializer=2)
         sess.run(v.initializer)
         sess.run(result.test_fn(v))
@@ -128,7 +128,7 @@ class SideEffectGuardsTest(converter_testing.TestCase):
     self.assertEqual(len(node.body[0].body), 1)
 
     with self.compiled(node, {}, state_ops.assign, ops.name_scope) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         v = variable_scope.get_variable('test', initializer=2)
         sess.run(v.initializer)
         sess.run(result.test_fn(v))
@@ -151,7 +151,7 @@ class SideEffectGuardsTest(converter_testing.TestCase):
 
     with self.compiled(node, {}, state_ops.assign,
                        state_ops.assign_add) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         v = variable_scope.get_variable('test', initializer=2)
         sess.run(v.initializer)
         sess.run(result.test_fn(v))
diff --git a/tensorflow/contrib/autograph/converters/slices_test.py b/tensorflow/contrib/autograph/converters/slices_test.py
index c822d53a4a..d74b2e025e 100644
--- a/tensorflow/contrib/autograph/converters/slices_test.py
+++ b/tensorflow/contrib/autograph/converters/slices_test.py
@@ -45,7 +45,7 @@ class SliceTest(converter_testing.TestCase):
     node = slices.transform(node, ctx)
 
     with self.compiled(node, {}, dtypes.int32) as result:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         tl = list_ops.tensor_list_from_tensor(
             [1, 2], element_shape=constant_op.constant([], dtype=dtypes.int32))
         y = result.test_fn(tl)
diff --git a/tensorflow/contrib/image/python/kernel_tests/dense_image_warp_test.py b/tensorflow/contrib/image/python/kernel_tests/dense_image_warp_test.py
index a58b6a247e..24b790977d 100644
--- a/tensorflow/contrib/image/python/kernel_tests/dense_image_warp_test.py
+++ b/tensorflow/contrib/image/python/kernel_tests/dense_image_warp_test.py
@@ -50,7 +50,7 @@ class DenseImageWarpTest(test_util.TensorFlowTestCase):
 
     interp = dense_image_warp._interpolate_bilinear(grid, query_points)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       predicted = sess.run(interp)
       self.assertAllClose(expected_results, predicted)
 
@@ -64,7 +64,7 @@ class DenseImageWarpTest(test_util.TensorFlowTestCase):
     interp = dense_image_warp._interpolate_bilinear(
         grid, query_points, indexing='xy')
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       predicted = sess.run(interp)
       self.assertAllClose(expected_results, predicted)
 
@@ -78,7 +78,7 @@ class DenseImageWarpTest(test_util.TensorFlowTestCase):
 
     interp = dense_image_warp._interpolate_bilinear(grid, query_points)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       predicted = sess.run(interp)
       self.assertAllClose(expected_results, predicted)
 
@@ -160,7 +160,7 @@ class DenseImageWarpTest(test_util.TensorFlowTestCase):
                                                         flow_type)
     interp = dense_image_warp.dense_image_warp(image, flows)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       rand_image, rand_flows = self.get_random_image_and_flows(
           shape, image_type, flow_type)
       rand_flows *= 0
@@ -191,7 +191,7 @@ class DenseImageWarpTest(test_util.TensorFlowTestCase):
                                                         flow_type)
     interp = dense_image_warp.dense_image_warp(image, flows)
     low_precision = image_type == 'float16' or flow_type == 'float16'
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       rand_image, rand_flows = self.get_random_image_and_flows(
           shape, image_type, flow_type)
 
@@ -249,7 +249,7 @@ class DenseImageWarpTest(test_util.TensorFlowTestCase):
     opt_func = optimizer.apply_gradients(zip(grad, [flows]))
     init_op = variables.global_variables_initializer()
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       sess.run(init_op)
       for _ in range(10):
         sess.run(opt_func)
diff --git a/tensorflow/contrib/image/python/kernel_tests/distort_image_ops_test.py b/tensorflow/contrib/image/python/kernel_tests/distort_image_ops_test.py
index a495b58b7f..ac8573445c 100644
--- a/tensorflow/contrib/image/python/kernel_tests/distort_image_ops_test.py
+++ b/tensorflow/contrib/image/python/kernel_tests/distort_image_ops_test.py
@@ -217,7 +217,7 @@ class AdjustSaturationInYiqTest(test_util.TensorFlowTestCase):
         'gb_same',
         'rgb_same',
     ]
-    with self.test_session():
+    with self.cached_session():
       for x_shape in x_shapes:
         for test_style in test_styles:
           x_np = np.random.rand(*x_shape) * 255.
diff --git a/tensorflow/contrib/image/python/kernel_tests/image_ops_test.py b/tensorflow/contrib/image/python/kernel_tests/image_ops_test.py
index f588eae923..70339d7612 100644
--- a/tensorflow/contrib/image/python/kernel_tests/image_ops_test.py
+++ b/tensorflow/contrib/image/python/kernel_tests/image_ops_test.py
@@ -39,7 +39,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
 
   def test_zeros(self):
     for dtype in _DTYPES:
-      with self.test_session():
+      with self.cached_session():
         for shape in [(5, 5), (24, 24), (2, 24, 24, 3)]:
           for angle in [0, 1, np.pi / 2.0]:
             image = array_ops.zeros(shape, dtype)
@@ -49,7 +49,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
 
   def test_rotate_even(self):
     for dtype in _DTYPES:
-      with self.test_session():
+      with self.cached_session():
         image = array_ops.reshape(
             math_ops.cast(math_ops.range(36), dtype), (6, 6))
         image_rep = array_ops.tile(image[None, :, :, None], [3, 1, 1, 1])
@@ -71,7 +71,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
 
   def test_rotate_odd(self):
     for dtype in _DTYPES:
-      with self.test_session():
+      with self.cached_session():
         image = array_ops.reshape(
             math_ops.cast(math_ops.range(25), dtype), (5, 5))
         image_rep = array_ops.tile(image[None, :, :, None], [3, 1, 1, 1])
@@ -91,7 +91,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
 
   def test_translate(self):
     for dtype in _DTYPES:
-      with self.test_session():
+      with self.cached_session():
         image = constant_op.constant(
             [[1, 0, 1, 0],
              [0, 1, 0, 1],
@@ -107,7 +107,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
 
   def test_compose(self):
     for dtype in _DTYPES:
-      with self.test_session():
+      with self.cached_session():
         image = constant_op.constant(
             [[1, 1, 1, 0],
              [1, 0, 0, 0],
@@ -131,7 +131,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
 
   def test_extreme_projective_transform(self):
     for dtype in _DTYPES:
-      with self.test_session():
+      with self.cached_session():
         image = constant_op.constant(
             [[1, 0, 1, 0],
              [0, 1, 0, 1],
@@ -147,7 +147,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
                              [0, 0, 0, 0]])
 
   def test_bilinear(self):
-    with self.test_session():
+    with self.cached_session():
       image = constant_op.constant(
           [[0, 0, 0, 0, 0],
            [0, 1, 1, 1, 0],
@@ -176,7 +176,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
            [0, 0, 1, 0, 0]])
 
   def test_bilinear_uint8(self):
-    with self.test_session():
+    with self.cached_session():
       image = constant_op.constant(
           np.asarray(
               [[0.0, 0.0, 0.0, 0.0, 0.0],
@@ -209,7 +209,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
     self.assertAllEqual([3, 5], result.get_shape())
 
   def _test_grad(self, shape_to_test):
-    with self.test_session():
+    with self.cached_session():
       test_image_shape = shape_to_test
       test_image = np.random.randn(*test_image_shape)
       test_image_tensor = constant_op.constant(
@@ -228,7 +228,7 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
       self.assertLess(left_err, 1e-10)
 
   def _test_grad_different_shape(self, input_shape, output_shape):
-    with self.test_session():
+    with self.cached_session():
       test_image_shape = input_shape
       test_image = np.random.randn(*test_image_shape)
       test_image_tensor = constant_op.constant(
@@ -276,7 +276,7 @@ class BipartiteMatchTest(test_util.TensorFlowTestCase):
     expected_col_to_row_match_np = np.array(expected_col_to_row_match,
                                             dtype=np.int32)
 
-    with self.test_session():
+    with self.cached_session():
       distance_mat_tf = constant_op.constant(distance_mat_np,
                                              shape=distance_mat_shape)
       location_to_prior, prior_to_location = image_ops.bipartite_match(
diff --git a/tensorflow/contrib/image/python/kernel_tests/interpolate_spline_test.py b/tensorflow/contrib/image/python/kernel_tests/interpolate_spline_test.py
index 3054128979..d58a654292 100644
--- a/tensorflow/contrib/image/python/kernel_tests/interpolate_spline_test.py
+++ b/tensorflow/contrib/image/python/kernel_tests/interpolate_spline_test.py
@@ -165,7 +165,7 @@ class InterpolateSplineTest(test_util.TensorFlowTestCase):
     with ops.name_scope('interpolator'):
       interpolator = interpolate_spline.interpolate_spline(
           train_points, train_values, query_points, interpolation_order)
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         fetches = [query_points, train_points, train_values, interpolator]
         query_points_, train_points_, train_values_, interp_ = sess.run(fetches)
 
@@ -205,7 +205,7 @@ class InterpolateSplineTest(test_util.TensorFlowTestCase):
 
         target_interpolation = tp.HARDCODED_QUERY_VALUES[(order, reg_weight)]
         target_interpolation = np.array(target_interpolation)
-        with self.test_session() as sess:
+        with self.cached_session() as sess:
           interp_val = sess.run(interpolator)
           self.assertAllClose(interp_val[0, :, 0], target_interpolation)
 
@@ -223,7 +223,7 @@ class InterpolateSplineTest(test_util.TensorFlowTestCase):
 
         target_interpolation = tp.HARDCODED_QUERY_VALUES[(order, reg_weight)]
         target_interpolation = np.array(target_interpolation)
-        with self.test_session() as sess:
+        with self.cached_session() as sess:
           interp_val = sess.run(interpolator)
           self.assertAllClose(interp_val[0, :, 0], target_interpolation)
 
@@ -253,7 +253,7 @@ class InterpolateSplineTest(test_util.TensorFlowTestCase):
 
     target_interpolation = tp.HARDCODED_QUERY_VALUES[(order, reg_weight)]
     target_interpolation = np.array(target_interpolation)
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
 
       (train_points_value, train_values_value, query_points_value) = sess.run(
           [train_points, train_values, query_points])
@@ -330,7 +330,7 @@ class InterpolateSplineTest(test_util.TensorFlowTestCase):
       opt_func = optimizer.apply_gradients(zip(grad, [train_points]))
       init_op = variables.global_variables_initializer()
 
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         sess.run(init_op)
         for _ in range(100):
           sess.run([loss, opt_func])
diff --git a/tensorflow/contrib/image/python/kernel_tests/segmentation_test.py b/tensorflow/contrib/image/python/kernel_tests/segmentation_test.py
index 48066cbace..3d39165ede 100644
--- a/tensorflow/contrib/image/python/kernel_tests/segmentation_test.py
+++ b/tensorflow/contrib/image/python/kernel_tests/segmentation_test.py
@@ -59,19 +59,19 @@ class SegmentationTest(test_util.TensorFlowTestCase):
          [7, 0, 8, 0, 0, 0, 9, 0, 0],
          [0, 0, 0, 0, 10, 0, 0, 0, 0],
          [0, 0, 11, 0, 0, 0, 0, 0, 0]])  # pyformat: disable
-    with self.test_session():
+    with self.cached_session():
       self.assertAllEqual(image_ops.connected_components(arr).eval(), expected)
 
   def testSimple(self):
     arr = [[0, 1, 0], [1, 1, 1], [0, 1, 0]]
-    with self.test_session():
+    with self.cached_session():
       # Single component with id 1.
       self.assertAllEqual(
           image_ops.connected_components(math_ops.cast(
               arr, dtypes.bool)).eval(), arr)
 
   def testSnake(self):
-    with self.test_session():
+    with self.cached_session():
       # Single component with id 1.
       self.assertAllEqual(
           image_ops.connected_components(math_ops.cast(
@@ -80,7 +80,7 @@ class SegmentationTest(test_util.TensorFlowTestCase):
   def testSnake_disconnected(self):
     for i in range(SNAKE.shape[0]):
       for j in range(SNAKE.shape[1]):
-        with self.test_session():
+        with self.cached_session():
           # If we disconnect any part of the snake except for the endpoints,
           # there will be 2 components.
           if SNAKE[i, j] and (i, j) not in [(1, 1), (6, 3)]:
@@ -121,27 +121,27 @@ class SegmentationTest(test_util.TensorFlowTestCase):
                  [0, 6, 6, 0],
                  [8, 0, 6, 0],
                  [0, 0, 6, 6]]]  # pyformat: disable
-    with self.test_session():
+    with self.cached_session():
       self.assertAllEqual(
           image_ops.connected_components(math_ops.cast(
               images, dtypes.bool)).eval(), expected)
 
   def testZeros(self):
-    with self.test_session():
+    with self.cached_session():
       self.assertAllEqual(
           image_ops.connected_components(
               array_ops.zeros((100, 20, 50), dtypes.bool)).eval(),
           np.zeros((100, 20, 50)))
 
   def testOnes(self):
-    with self.test_session():
+    with self.cached_session():
       self.assertAllEqual(
           image_ops.connected_components(
               array_ops.ones((100, 20, 50), dtypes.bool)).eval(),
           np.tile(np.arange(100)[:, None, None] + 1, [1, 20, 50]))
 
   def testOnes_small(self):
-    with self.test_session():
+    with self.cached_session():
       self.assertAllEqual(
           image_ops.connected_components(array_ops.ones((3, 5),
                                                         dtypes.bool)).eval(),
@@ -153,7 +153,7 @@ class SegmentationTest(test_util.TensorFlowTestCase):
     expected = connected_components_reference_implementation(images)
     if expected is None:
       return
-    with self.test_session():
+    with self.cached_session():
       self.assertAllEqual(
           image_ops.connected_components(images).eval(), expected)
 
diff --git a/tensorflow/contrib/image/python/kernel_tests/single_image_random_dot_stereograms_ops_test.py b/tensorflow/contrib/image/python/kernel_tests/single_image_random_dot_stereograms_ops_test.py
index 3f4029e558..e5980c53b2 100644
--- a/tensorflow/contrib/image/python/kernel_tests/single_image_random_dot_stereograms_ops_test.py
+++ b/tensorflow/contrib/image/python/kernel_tests/single_image_random_dot_stereograms_ops_test.py
@@ -47,7 +47,7 @@ class SingleImageRandomDotStereogramsTest(test_util.TensorFlowTestCase):
         normalize=True)
     shape_1 = sirds_1.get_shape().as_list()
     self.assertEqual(shape_1, [768, 1024, 1])
-    with self.test_session():
+    with self.cached_session():
       r_tf_1 = sirds_1.eval()
       self.assertAllEqual(shape_1, r_tf_1.shape)
 
@@ -59,7 +59,7 @@ class SingleImageRandomDotStereogramsTest(test_util.TensorFlowTestCase):
         normalize=True)
     shape_2 = sirds_2.get_shape().as_list()
     self.assertEqual(shape_2, [768, 1024, 3])
-    with self.test_session():
+    with self.cached_session():
       r_tf_2 = sirds_2.eval()
       self.assertAllEqual(shape_2, r_tf_2.shape)
 
@@ -73,7 +73,7 @@ class SingleImageRandomDotStereogramsTest(test_util.TensorFlowTestCase):
         output_image_shape=[1200, 800, 1])
     shape_3 = sirds_3.get_shape().as_list()
     self.assertEqual(shape_3, [800, 1200, 1])
-    with self.test_session():
+    with self.cached_session():
       r_tf_3 = sirds_3.eval()
       self.assertAllEqual(shape_3, r_tf_3.shape)
 
diff --git a/tensorflow/contrib/image/python/kernel_tests/sparse_image_warp_test.py b/tensorflow/contrib/image/python/kernel_tests/sparse_image_warp_test.py
index 0135c66e29..ce9e34df73 100644
--- a/tensorflow/contrib/image/python/kernel_tests/sparse_image_warp_test.py
+++ b/tensorflow/contrib/image/python/kernel_tests/sparse_image_warp_test.py
@@ -107,7 +107,7 @@ class SparseImageWarpTest(test_util.TensorFlowTestCase):
         regularization_weight=regularization,
         num_boundary_points=num_boundary_points)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       warped_image, input_image, _ = sess.run(
           [warped_image_op, input_image_op, flow_field])
 
@@ -149,7 +149,7 @@ class SparseImageWarpTest(test_util.TensorFlowTestCase):
         interpolation_order=order,
         num_boundary_points=num_boundary_points)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       warped_image, input_image, flow = sess.run(
           [warped_image_op, input_image_op, flow_field])
       # Check that it moved the pixel correctly.
@@ -176,7 +176,7 @@ class SparseImageWarpTest(test_util.TensorFlowTestCase):
     test_data_dir = test.test_src_dir_path('contrib/image/python/'
                                            'kernel_tests/test_data/')
     input_file = test_data_dir + 'Yellow_Smiley_Face.png'
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       input_image = self.load_image(input_file, sess)
     control_points = np.asarray([[64, 59], [180 - 64, 59], [39, 111],
                                  [180 - 39, 111], [90, 143], [58, 134],
@@ -199,7 +199,7 @@ class SparseImageWarpTest(test_util.TensorFlowTestCase):
             control_points_op + control_point_displacements_op,
             interpolation_order=interpolation_order,
             num_boundary_points=num_boundary_points)
-        with self.test_session() as sess:
+        with self.cached_session() as sess:
           warped_image = sess.run(warp_op)
           out_image = np.uint8(warped_image[0, :, :, :] * 255)
           target_file = (
@@ -244,7 +244,7 @@ class SparseImageWarpTest(test_util.TensorFlowTestCase):
     opt_func = optimizer.apply_gradients(zip(grad, [image]))
     init_op = variables.global_variables_initializer()
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       sess.run(init_op)
       for _ in range(5):
         sess.run([loss, opt_func])
diff --git a/tensorflow/contrib/optimizer_v2/adadelta_test.py b/tensorflow/contrib/optimizer_v2/adadelta_test.py
index 31cfec0d50..4c94b66679 100644
--- a/tensorflow/contrib/optimizer_v2/adadelta_test.py
+++ b/tensorflow/contrib/optimizer_v2/adadelta_test.py
@@ -37,7 +37,7 @@ class AdadeltaOptimizerTest(test.TestCase):
     for dtype in [dtypes.half, dtypes.float32]:
       for grad in [0.2, 0.1, 0.01]:
         for lr in [1.0, 0.5, 0.1]:
-          with self.test_session():
+          with self.cached_session():
             var0_init = [1.0, 2.0]
             var1_init = [3.0, 4.0]
             if use_resource:
@@ -146,7 +146,7 @@ class AdadeltaOptimizerTest(test.TestCase):
 
   def testMinimizeSparseResourceVariable(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
         x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
         pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
diff --git a/tensorflow/contrib/optimizer_v2/adagrad_test.py b/tensorflow/contrib/optimizer_v2/adagrad_test.py
index 18191c3ef2..debaaaeeba 100644
--- a/tensorflow/contrib/optimizer_v2/adagrad_test.py
+++ b/tensorflow/contrib/optimizer_v2/adagrad_test.py
@@ -36,7 +36,7 @@ class AdagradOptimizerTest(test.TestCase):
 
   def doTestBasic(self, use_locking=False, use_resource=False):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         if use_resource:
           var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
           var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
@@ -73,7 +73,7 @@ class AdagradOptimizerTest(test.TestCase):
 
   def testMinimizeSparseResourceVariable(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = resource_variable_ops.ResourceVariable(
             [[1.0, 2.0], [3.0, 4.0]], dtype=dtype)
         x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
@@ -92,7 +92,7 @@ class AdagradOptimizerTest(test.TestCase):
 
   def testTensorLearningRate(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
         grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@@ -116,7 +116,7 @@ class AdagradOptimizerTest(test.TestCase):
 
   def testSparseBasic(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([[1.0], [2.0]], dtype=dtype)
         var1 = variables.Variable([[3.0], [4.0]], dtype=dtype)
         grads0 = ops.IndexedSlices(
@@ -147,7 +147,7 @@ class AdagradOptimizerTest(test.TestCase):
 
   def testSparseRepeatedIndices(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         repeated_index_update_var = variables.Variable(
             [[1.0], [2.0]], dtype=dtype)
         aggregated_update_var = variables.Variable(
@@ -177,7 +177,7 @@ class AdagradOptimizerTest(test.TestCase):
 
   def testSparseRepeatedIndicesResourceVariable(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var_repeated = resource_variable_ops.ResourceVariable(
             [1.0, 2.0], dtype=dtype)
         loss_repeated = math_ops.reduce_sum(
@@ -201,7 +201,7 @@ class AdagradOptimizerTest(test.TestCase):
 
   def testSparseStability(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         shape = [1, 6]
         var0 = variables.Variable(
             [[
@@ -237,7 +237,7 @@ class AdagradOptimizerTest(test.TestCase):
 
   def testSharing(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
         grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@@ -270,7 +270,7 @@ class AdagradOptimizerTest(test.TestCase):
             np.array([2.715679168701172, 3.715679168701172]), var1.eval())
 
   def testDynamicShapeVariable_Ok(self):
-    with self.test_session():
+    with self.cached_session():
       v = variable_scope.get_variable("v", initializer=constant_op.constant(1.),
                                       validate_shape=False)
       self.assertFalse(v.shape.is_fully_defined())
diff --git a/tensorflow/contrib/optimizer_v2/adam_test.py b/tensorflow/contrib/optimizer_v2/adam_test.py
index 1f079d9afc..b1ad0ade42 100644
--- a/tensorflow/contrib/optimizer_v2/adam_test.py
+++ b/tensorflow/contrib/optimizer_v2/adam_test.py
@@ -56,7 +56,7 @@ class AdamOptimizerTest(test.TestCase):
 
   def doTestSparse(self, use_resource=False):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         # Initialize variables for numpy implementation.
         m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0
         var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype)
@@ -122,7 +122,7 @@ class AdamOptimizerTest(test.TestCase):
 
   def testSparseRepeatedIndices(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         repeated_index_update_var = variables.Variable(
             [[1.0], [2.0]], dtype=dtype)
         aggregated_update_var = variables.Variable(
@@ -215,7 +215,7 @@ class AdamOptimizerTest(test.TestCase):
                              opt.get_slot(var=var0, name="m").name)
 
   def testBasic(self):
-    with self.test_session():
+    with self.cached_session():
       self.doTestBasic(use_resource=False)
 
   @test_util.run_in_graph_and_eager_modes(reset_test=True)
@@ -224,7 +224,7 @@ class AdamOptimizerTest(test.TestCase):
 
   def testTensorLearningRate(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         # Initialize variables for numpy implementation.
         m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0
         var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype)
@@ -261,7 +261,7 @@ class AdamOptimizerTest(test.TestCase):
 
   def testSharing(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         # Initialize variables for numpy implementation.
         m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0
         var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype)
diff --git a/tensorflow/contrib/optimizer_v2/gradient_descent_test.py b/tensorflow/contrib/optimizer_v2/gradient_descent_test.py
index ad9aef804f..4a77bce478 100644
--- a/tensorflow/contrib/optimizer_v2/gradient_descent_test.py
+++ b/tensorflow/contrib/optimizer_v2/gradient_descent_test.py
@@ -34,7 +34,7 @@ class GradientDescentOptimizerTest(test.TestCase):
 
   def testBasic(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
         grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@@ -57,7 +57,7 @@ class GradientDescentOptimizerTest(test.TestCase):
 
   def testBasicResourceVariable(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
         var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
         grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@@ -82,7 +82,7 @@ class GradientDescentOptimizerTest(test.TestCase):
 
   def testMinimizeResourceVariable(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
         var1 = resource_variable_ops.ResourceVariable([3.0], dtype=dtype)
         x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
@@ -108,7 +108,7 @@ class GradientDescentOptimizerTest(test.TestCase):
 
   def testMinimizeSparseResourceVariable(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
         var1 = resource_variable_ops.ResourceVariable([3.0], dtype=dtype)
         x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
@@ -135,7 +135,7 @@ class GradientDescentOptimizerTest(test.TestCase):
 
   def testTensorLearningRate(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
         grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@@ -157,7 +157,7 @@ class GradientDescentOptimizerTest(test.TestCase):
 
   def testGradWrtRef(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         opt = gradient_descent.GradientDescentOptimizer(3.0)
         values = [1.0, 3.0]
         vars_ = [variables.Variable([v], dtype=dtype) for v in values]
@@ -168,7 +168,7 @@ class GradientDescentOptimizerTest(test.TestCase):
 
   def testWithGlobalStep(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         global_step = variables.Variable(0, trainable=False)
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
@@ -191,7 +191,7 @@ class GradientDescentOptimizerTest(test.TestCase):
 
   def testSparseBasic(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([[1.0], [2.0]], dtype=dtype)
         var1 = variables.Variable([[3.0], [4.0]], dtype=dtype)
         grads0 = ops.IndexedSlices(
diff --git a/tensorflow/contrib/optimizer_v2/momentum_test.py b/tensorflow/contrib/optimizer_v2/momentum_test.py
index 24cdab4626..e69f12839e 100644
--- a/tensorflow/contrib/optimizer_v2/momentum_test.py
+++ b/tensorflow/contrib/optimizer_v2/momentum_test.py
@@ -123,7 +123,7 @@ class MomentumOptimizerTest(test.TestCase):
           ]), self.evaluate(var1))
 
   def testBasic(self):
-    with self.test_session():
+    with self.cached_session():
       self.doTestBasic(use_resource=False)
 
   @test_util.run_in_graph_and_eager_modes(reset_test=True)
@@ -162,7 +162,7 @@ class MomentumOptimizerTest(test.TestCase):
 
   def testNesterovMomentum(self):
     for dtype in [dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
         var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype)
@@ -188,7 +188,7 @@ class MomentumOptimizerTest(test.TestCase):
 
   def testSparseNesterovMomentum(self):
     for dtype in [dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype)
         var1_np = np.array([3.0, 4.0], dtype=dtype.as_numpy_dtype)
         accum0_np = np.array([0.0, 0.0], dtype=dtype.as_numpy_dtype)
@@ -282,7 +282,7 @@ class MomentumOptimizerTest(test.TestCase):
 
   def testTensorLearningRateAndMomentum(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
         grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@@ -435,7 +435,7 @@ class MomentumOptimizerTest(test.TestCase):
     return db_grad, db_out
 
   def testLikeDistBeliefMom01(self):
-    with self.test_session():
+    with self.cached_session():
       db_grad, db_out = self._dbParamsMom01()
       num_samples = len(db_grad)
       var0 = variables.Variable([0.0] * num_samples)
@@ -449,7 +449,7 @@ class MomentumOptimizerTest(test.TestCase):
 
   def testSparse(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable(array_ops.zeros([4, 2], dtype=dtype))
         var1 = variables.Variable(constant_op.constant(1.0, dtype, [4, 2]))
         grads0 = ops.IndexedSlices(
@@ -518,7 +518,7 @@ class MomentumOptimizerTest(test.TestCase):
 
   def testSharing(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
         grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
diff --git a/tensorflow/contrib/optimizer_v2/optimizer_v2_test.py b/tensorflow/contrib/optimizer_v2/optimizer_v2_test.py
index a44bfd1bfd..dd7f2f4405 100644
--- a/tensorflow/contrib/optimizer_v2/optimizer_v2_test.py
+++ b/tensorflow/contrib/optimizer_v2/optimizer_v2_test.py
@@ -61,7 +61,7 @@ class OptimizerTest(test.TestCase):
 
   def testAggregationMethod(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
         cost = 5 * var0 + 3 * var1
@@ -86,7 +86,7 @@ class OptimizerTest(test.TestCase):
 
   def testPrecomputedGradient(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         var0 = variables.Variable([1.0, 2.0], dtype=dtype)
         var1 = variables.Variable([3.0, 4.0], dtype=dtype)
         cost = 5 * var0 + 3 * var1
@@ -212,7 +212,7 @@ class OptimizerTest(test.TestCase):
       sgd_op.apply_gradients(grads_and_vars)
 
   def testTrainOp(self):
-    with self.test_session():
+    with self.cached_session():
       var0 = variables.Variable([1.0, 2.0])
       var1 = variables.Variable([3.0, 4.0])
       cost = 5 * var0 + 3 * var1
@@ -225,7 +225,7 @@ class OptimizerTest(test.TestCase):
   def testConstraint(self):
     constraint_01 = lambda x: clip_ops.clip_by_value(x, -0.1, 0.)
     constraint_0 = lambda x: clip_ops.clip_by_value(x, 0., 1.)
-    with self.test_session():
+    with self.cached_session():
       var0 = variables.Variable([1.0, 2.0],
                                 constraint=constraint_01)
       var1 = variables.Variable([3.0, 4.0],
@@ -247,7 +247,7 @@ class OptimizerTest(test.TestCase):
       self.assertAllClose([0., 0.], var1.eval())
 
   def testStopGradients(self):
-    with self.test_session():
+    with self.cached_session():
       var0 = variables.Variable([1.0, 2.0], name='var0')
       var1 = variables.Variable([3.0, 4.0], name='var1')
       var0_id = array_ops.identity(var0)
diff --git a/tensorflow/contrib/optimizer_v2/rmsprop_test.py b/tensorflow/contrib/optimizer_v2/rmsprop_test.py
index 628d0418dd..44301ffe9e 100644
--- a/tensorflow/contrib/optimizer_v2/rmsprop_test.py
+++ b/tensorflow/contrib/optimizer_v2/rmsprop_test.py
@@ -162,7 +162,7 @@ class RMSPropOptimizerTest(test.TestCase, parameterized.TestCase):
 
   @parameterized.parameters([dtypes.float32, dtypes.float64])
   def testMinimizeSparseResourceVariable(self, dtype):
-    with self.test_session():
+    with self.cached_session():
       var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
       x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
       pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
@@ -184,7 +184,7 @@ class RMSPropOptimizerTest(test.TestCase, parameterized.TestCase):
 
   @parameterized.parameters([dtypes.float32, dtypes.float64])
   def testMinimizeSparseResourceVariableCentered(self, dtype):
-    with self.test_session():
+    with self.cached_session():
       var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
       x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
       pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)