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: 212348850

5 files changed, 20 insertions, 19 deletions

diff --git a/tensorflow/contrib/timeseries/python/timeseries/head_test.py b/tensorflow/contrib/timeseries/python/timeseries/head_test.py
index e65e7b74d4..647455ae42 100644
--- a/tensorflow/contrib/timeseries/python/timeseries/head_test.py
+++ b/tensorflow/contrib/timeseries/python/timeseries/head_test.py
@@ -122,7 +122,7 @@ class EvaluationMetricsTests(test.TestCase):
           metric[1] for metric in outputs.eval_metric_ops.values()]
       loss_mean, loss_update = metrics.mean(outputs.loss)
       metric_update_ops.append(loss_update)
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         coordinator = coordinator_lib.Coordinator()
         queue_runner_impl.start_queue_runners(sess, coord=coordinator)
         variables.local_variables_initializer().run()
diff --git a/tensorflow/contrib/timeseries/python/timeseries/input_pipeline_test.py b/tensorflow/contrib/timeseries/python/timeseries/input_pipeline_test.py
index 703537abf0..f92148b788 100644
--- a/tensorflow/contrib/timeseries/python/timeseries/input_pipeline_test.py
+++ b/tensorflow/contrib/timeseries/python/timeseries/input_pipeline_test.py
@@ -88,7 +88,7 @@ class RandomWindowInputFnTests(test.TestCase):
         window_size=window_size, batch_size=batch_size)
     result, _ = input_fn()
     init_op = variables.local_variables_initializer()
-    with self.test_session() as session:
+    with self.cached_session() as session:
       coordinator = coordinator_lib.Coordinator()
       queue_runner_impl.start_queue_runners(session, coord=coordinator)
       session.run(init_op)
@@ -261,7 +261,7 @@ class WholeDatasetInputFnTests(test.TestCase):
   def _whole_dataset_input_fn_test_template(
       self, time_series_reader, num_features, num_samples):
     result, _ = input_pipeline.WholeDatasetInputFn(time_series_reader)()
-    with self.test_session() as session:
+    with self.cached_session() as session:
       session.run(variables.local_variables_initializer())
       coordinator = coordinator_lib.Coordinator()
       queue_runner_impl.start_queue_runners(session, coord=coordinator)
@@ -340,7 +340,7 @@ class AllWindowInputFnTests(test.TestCase):
         window_size=window_size)
     features, _ = input_fn()
     init_op = variables.local_variables_initializer()
-    with self.test_session() as session:
+    with self.cached_session() as session:
       coordinator = coordinator_lib.Coordinator()
       queue_runner_impl.start_queue_runners(session, coord=coordinator)
       session.run(init_op)
diff --git a/tensorflow/contrib/timeseries/python/timeseries/math_utils_test.py b/tensorflow/contrib/timeseries/python/timeseries/math_utils_test.py
index 02d2524b66..c0de42b15b 100644
--- a/tensorflow/contrib/timeseries/python/timeseries/math_utils_test.py
+++ b/tensorflow/contrib/timeseries/python/timeseries/math_utils_test.py
@@ -55,7 +55,7 @@ class MathUtilsTest(test.TestCase):
       running_sum = running_sum + current_contribution
       # pylint: enable=g-no-augmented-assignment
       transition_power = numpy.dot(transition, transition_power)
-    with self.test_session():
+    with self.cached_session():
       self.assertAllClose(result,
                           math_utils.power_sums_tensor(
                               array_size, transition, addition).eval())
@@ -66,7 +66,7 @@ class MathUtilsTest(test.TestCase):
     result = []
     for i in range(powers.shape[0]):
       result.append(numpy.linalg.matrix_power(matrix, powers[i]))
-    with self.test_session():
+    with self.cached_session():
       self.assertAllClose(result,
                           math_utils.matrix_to_powers(matrix, powers).eval(),
                           rtol=1e-5,
@@ -78,7 +78,7 @@ class MathUtilsTest(test.TestCase):
     result = []
     for i in range(batch.shape[0]):
       result.append(numpy.linalg.matrix_power(batch[i], powers[i]))
-    with self.test_session():
+    with self.cached_session():
       # TODO(allenl): Numerical errors seem to be creeping in. Maybe it can be
       # made slightly more stable?
       self.assertAllClose(result,
@@ -91,7 +91,7 @@ class MathUtilsTest(test.TestCase):
     left_transpose = numpy.transpose(left, [0, 2, 1])
     right = numpy.random.normal(size=[2, 3]).astype(numpy.float32)
     expected_result = numpy.dot(left, right)
-    with self.test_session():
+    with self.cached_session():
       self.assertAllClose(expected_result,
                           math_utils.batch_times_matrix(
                               left, right).eval())
@@ -114,7 +114,7 @@ class MathUtilsTest(test.TestCase):
     right_transpose = numpy.transpose(right, [0, 2, 1])
     expected_result = numpy.transpose(numpy.dot(right_transpose, left.T),
                                       [0, 2, 1])
-    with self.test_session():
+    with self.cached_session():
       self.assertAllClose(expected_result,
                           math_utils.matrix_times_batch(
                               left, right).eval())
@@ -132,7 +132,7 @@ class MathUtilsTest(test.TestCase):
                               adj_x=True, adj_y=True).eval())
 
   def test_make_diagonal_undefined_shapes(self):
-    with self.test_session():
+    with self.cached_session():
       completely_undefined = array_ops.placeholder(dtype=dtypes.float32)
       partly_undefined = array_ops.placeholder(
           shape=[None, None], dtype=dtypes.float32)
@@ -152,7 +152,7 @@ class MathUtilsTest(test.TestCase):
                                  [5., 6.]]}))
 
   def test_make_diagonal_mostly_defined_shapes(self):
-    with self.test_session():
+    with self.cached_session():
       mostly_defined = array_ops.placeholder(
           shape=[None, 2], dtype=dtypes.float32)
       blocked = math_utils.block_diagonal([[[2.]],
@@ -192,7 +192,7 @@ class TestMakeToeplitzMatrix(test.TestCase):
 
   def _test_make_toeplitz_matrix(self, inputs, output_expected):
     output_tf = math_utils.make_toeplitz_matrix(inputs)
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       output_tf_np = sess.run(output_tf)
     self.assertAllClose(output_tf_np, output_expected)
 
@@ -201,13 +201,13 @@ class TestMakeCovarianceMatrix(test.TestCase):
 
   def test_zero_size_matrix(self):
     raw = numpy.zeros([0, 0])
-    with self.test_session():
+    with self.cached_session():
       constructed = math_utils.sign_magnitude_positive_definite(raw=raw).eval()
     self.assertEqual((0, 0), constructed.shape)
 
   def test_sign_magnitude_positive_definite(self):
     for dtype in [dtypes.float32, dtypes.float64]:
-      with self.test_session():
+      with self.cached_session():
         matrix_tensor = math_utils.sign_magnitude_positive_definite(
             raw=constant_op.constant([[-1., -2.], [3., 4.]], dtype=dtype),
             off_diagonal_scale=constant_op.constant(-1., dtype=dtype),
@@ -230,7 +230,8 @@ class TestLookupTable(test.TestCase):
         name="test_lookup")
     def stack_tensor(base_tensor):
       return array_ops.stack([base_tensor + 1, base_tensor + 2])
-    with self.test_session() as session:
+
+    with self.cached_session() as session:
       ((float_output, double_output), int_output) = session.run(
           hash_table.lookup([2, 1, 0]))
       def expected_output_before_insert(base_tensor):
diff --git a/tensorflow/contrib/timeseries/python/timeseries/model_utils_test.py b/tensorflow/contrib/timeseries/python/timeseries/model_utils_test.py
index cfd31cc70d..a049dbe773 100644
--- a/tensorflow/contrib/timeseries/python/timeseries/model_utils_test.py
+++ b/tensorflow/contrib/timeseries/python/timeseries/model_utils_test.py
@@ -29,7 +29,7 @@ class ModelUtilsTest(test.TestCase):
   def test_parameter_switching(self):
     parameter = array_ops.constant(5)
     overridden_parameter = array_ops.constant(3)
-    with self.test_session():
+    with self.cached_session():
       getter = model_utils.parameter_switch({overridden_parameter: 4})
       self.assertEqual(5, getter(parameter))
       self.assertEqual(4, getter(overridden_parameter))
diff --git a/tensorflow/contrib/timeseries/python/timeseries/state_management_test.py b/tensorflow/contrib/timeseries/python/timeseries/state_management_test.py
index 5f7e3da2db..42ba6e1c25 100644
--- a/tensorflow/contrib/timeseries/python/timeseries/state_management_test.py
+++ b/tensorflow/contrib/timeseries/python/timeseries/state_management_test.py
@@ -127,7 +127,7 @@ class ChainingStateManagerTest(test.TestCase):
     chainer.initialize_graph(model=stub_model)
     model_outputs = chainer.define_loss(
         model=stub_model, features=features, mode=estimator_lib.ModeKeys.TRAIN)
-    with self.test_session() as session:
+    with self.cached_session() as session:
       variables.global_variables_initializer().run()
       coordinator = coordinator_lib.Coordinator()
       queue_runner_impl.start_queue_runners(session, coord=coordinator)
@@ -178,7 +178,7 @@ class ChainingStateManagerTest(test.TestCase):
     result_model_outputs = chainer.define_loss(
         model=stub_model, features=result_input_fn()[0],
         mode=estimator_lib.ModeKeys.TRAIN)
-    with self.test_session() as session:
+    with self.cached_session() as session:
       variables.global_variables_initializer().run()
       coordinator = coordinator_lib.Coordinator()
       queue_runner_impl.start_queue_runners(session, coord=coordinator)
@@ -221,7 +221,7 @@ class ChainingStateManagerTest(test.TestCase):
     chainer.initialize_graph(model=stub_model)
     model_outputs = chainer.define_loss(
         model=stub_model, features=features, mode=estimator_lib.ModeKeys.TRAIN)
-    with self.test_session() as session:
+    with self.cached_session() as session:
       variables.global_variables_initializer().run()
       coordinator = coordinator_lib.Coordinator()
       queue_runner_impl.start_queue_runners(session, coord=coordinator)