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: 212336321

2 files changed, 21 insertions, 21 deletions

diff --git a/tensorflow/contrib/boosted_trees/lib/learner/batch/categorical_split_handler_test.py b/tensorflow/contrib/boosted_trees/lib/learner/batch/categorical_split_handler_test.py
index d9f03c3840..94ea7bc2eb 100644
--- a/tensorflow/contrib/boosted_trees/lib/learner/batch/categorical_split_handler_test.py
+++ b/tensorflow/contrib/boosted_trees/lib/learner/batch/categorical_split_handler_test.py
@@ -47,7 +47,7 @@ def get_empty_tensors(gradient_shape, hessian_shape):
 class EqualitySplitHandlerTest(test_util.TensorFlowTestCase):
 
   def testGenerateFeatureSplitCandidates(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Feature ID     |
       # i0      |  (0.2, 0.12)  | 0         | 1,2            |
@@ -281,7 +281,7 @@ class EqualitySplitHandlerTest(test_util.TensorFlowTestCase):
         gains[0], 0.00001)
 
   def testGenerateFeatureSplitCandidatesSumReduction(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Feature ID     |
       # i0      |  (0.2, 0.12)  | 0         | 1,2            |
@@ -404,7 +404,7 @@ class EqualitySplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertEqual(1, split_node.feature_id)
 
   def testGenerateFeatureSplitCandidatesMulticlass(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # Batch size is 4, 2 gradients per each instance.
       gradients = array_ops.constant(
           [[0.2, 0.1], [-0.5, 0.2], [1.2, 3.4], [4.0, -3.5]], shape=[4, 2])
@@ -482,7 +482,7 @@ class EqualitySplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertEqual(1, split_node.feature_id)
 
   def testEmpty(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       gradients = array_ops.constant([0.2, -0.5, 1.2, 4.0])
       hessians = array_ops.constant([0.12, 0.07, 0.2, 0.13])
       partition_ids = [0, 0, 0, 1]
@@ -530,7 +530,7 @@ class EqualitySplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertEqual(len(splits), 0)
 
   def testInactive(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       gradients = array_ops.constant([0.2, -0.5, 1.2, 4.0])
       hessians = array_ops.constant([0.12, 0.07, 0.2, 0.13])
       partition_ids = [0, 0, 0, 1]
diff --git a/tensorflow/contrib/boosted_trees/lib/learner/batch/ordinal_split_handler_test.py b/tensorflow/contrib/boosted_trees/lib/learner/batch/ordinal_split_handler_test.py
index 5532bd026a..74b0ea6989 100644
--- a/tensorflow/contrib/boosted_trees/lib/learner/batch/ordinal_split_handler_test.py
+++ b/tensorflow/contrib/boosted_trees/lib/learner/batch/ordinal_split_handler_test.py
@@ -50,7 +50,7 @@ def get_empty_tensors(gradient_shape, hessian_shape):
 class DenseSplitHandlerTest(test_util.TensorFlowTestCase):
 
   def testGenerateFeatureSplitCandidates(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Dense Quantile |
       # i0      |  (0.2, 0.12)  | 0         | 1              |
@@ -183,7 +183,7 @@ class DenseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertAllClose(0.52, split_node.threshold, 0.00001)
 
   def testObliviousFeatureSplitGeneration(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Dense Quantile |
       # i0      |  (0.2, 0.12)  | 1         | 3              |
@@ -320,7 +320,7 @@ class DenseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertEqual(2, oblivious_split_info.children_parent_id[1])
 
   def testGenerateFeatureSplitCandidatesLossUsesSumReduction(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Dense Quantile |
       # i0      |  (0.2, 0.12)  | 0         | 1              |
@@ -458,7 +458,7 @@ class DenseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertAllClose(0.52, split_node.threshold, 0.00001)
 
   def testGenerateFeatureSplitCandidatesMulticlassFullHessian(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       dense_column = array_ops.constant([0.52, 0.52, 0.3, 0.52])
       # Batch size is 4, 2 gradients per each instance.
       gradients = array_ops.constant(
@@ -546,7 +546,7 @@ class DenseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertAllClose(0.3, split_node.threshold, 1e-6)
 
   def testGenerateFeatureSplitCandidatesMulticlassDiagonalHessian(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       dense_column = array_ops.constant([0.52, 0.52, 0.3, 0.52])
       # Batch size is 4, 2 gradients per each instance.
       gradients = array_ops.constant(
@@ -633,7 +633,7 @@ class DenseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertAllClose(0.3, split_node.threshold, 1e-6)
 
   def testGenerateFeatureSplitCandidatesInactive(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Dense Quantile |
       # i0      |  (0.2, 0.12)  | 0         | 1              |
@@ -708,7 +708,7 @@ class DenseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertEqual(len(splits), 0)
 
   def testGenerateFeatureSplitCandidatesWithTreeComplexity(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Dense Quantile |
       # i0      |  (0.2, 0.12)  | 0         | 1              |
@@ -842,7 +842,7 @@ class DenseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertAllClose(0.52, split_node.threshold, 0.00001)
 
   def testGenerateFeatureSplitCandidatesWithMinNodeWeight(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Dense Quantile |
       # i0      |  (0.2, 0.12)  | 0         | 1              |
@@ -951,7 +951,7 @@ class DenseSplitHandlerTest(test_util.TensorFlowTestCase):
 class SparseSplitHandlerTest(test_util.TensorFlowTestCase):
 
   def testGenerateFeatureSplitCandidates(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Sparse Quantile |
       # i0      |  (0.2, 0.12)  | 0         | 1               |
@@ -1074,7 +1074,7 @@ class SparseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertAllClose(0.52, split_node.split.threshold)
 
   def testGenerateFeatureSplitCandidatesLossUsesSumReduction(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Sparse Quantile |
       # i0      |  (0.2, 0.12)  | 0         | 1               |
@@ -1207,7 +1207,7 @@ class SparseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertAllClose(0.52, split_node.split.threshold)
 
   def testGenerateFeatureSplitCandidatesMulticlassFullHessian(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # Batch is 4, 2 classes
       gradients = array_ops.constant([[0.2, 1.4], [-0.5, 0.1], [1.2, 3],
                                       [4.0, -3]])
@@ -1302,7 +1302,7 @@ class SparseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertAllClose(0.52, split_node.split.threshold)
 
   def testGenerateFeatureSplitCandidatesMulticlassDiagonalHessian(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # Batch is 4, 2 classes
       gradients = array_ops.constant([[0.2, 1.4], [-0.5, 0.1], [1.2, 3],
                                       [4.0, -3]])
@@ -1397,7 +1397,7 @@ class SparseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertAllClose(0.52, split_node.split.threshold)
 
   def testGenerateFeatureSplitCandidatesInactive(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # The data looks like the following:
       # Example |  Gradients    | Partition | Sparse Quantile |
       # i0      |  (0.2, 0.12)  | 0         | 1               |
@@ -1475,7 +1475,7 @@ class SparseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertEqual(len(splits), 0)
 
   def testEmpty(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       indices = array_ops.constant([], dtype=dtypes.int64, shape=[0, 2])
       # No values in this feature column in this mini-batch.
       values = array_ops.constant([], dtype=dtypes.float32)
@@ -1545,7 +1545,7 @@ class SparseSplitHandlerTest(test_util.TensorFlowTestCase):
 
   def testEmptyBuckets(self):
     """Test that reproduces the case when quantile buckets were empty."""
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       sparse_column = array_ops.sparse_placeholder(dtypes.float32)
 
       # We have two batches - at first, a sparse feature is empty.
@@ -1638,7 +1638,7 @@ class SparseSplitHandlerTest(test_util.TensorFlowTestCase):
     self.assertEqual(len(splits), 0)
 
   def testDegenerativeCase(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # One data example only, one leaf and thus one quantile bucket.The same
       # situation is when all examples have the same values. This case was
       # causing before a failure.