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

7 files changed, 40 insertions, 40 deletions

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])