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-rw-r--r--tensorflow/contrib/boosted_trees/python/kernel_tests/prediction_ops_test.py44
1 files changed, 22 insertions, 22 deletions
diff --git a/tensorflow/contrib/boosted_trees/python/kernel_tests/prediction_ops_test.py b/tensorflow/contrib/boosted_trees/python/kernel_tests/prediction_ops_test.py
index bef42fdf7f..4278a30ba9 100644
--- a/tensorflow/contrib/boosted_trees/python/kernel_tests/prediction_ops_test.py
+++ b/tensorflow/contrib/boosted_trees/python/kernel_tests/prediction_ops_test.py
@@ -201,7 +201,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
reduce_dim=reduce_dim)
def testEmptyEnsemble(self):
- with self.test_session():
+ with self.cached_session():
# Empty tree ensenble.
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
@@ -224,7 +224,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual([[], []], dropout_info.eval())
def testBiasEnsembleSingleClass(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
tree = tree_ensemble_config.trees.add()
tree_ensemble_config.tree_metadata.add().is_finalized = True
@@ -252,7 +252,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual([[], []], dropout_info.eval())
def testBiasEnsembleMultiClass(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
tree = tree_ensemble_config.trees.add()
tree_ensemble_config.tree_metadata.add().is_finalized = True
@@ -282,7 +282,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual([[], []], dropout_info.eval())
def testFullEnsembleSingleClass(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Bias tree.
tree1 = tree_ensemble_config.trees.add()
@@ -378,7 +378,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual([[], []], dropout_info.eval())
def testFullEnsembleWithMultidimensionalSparseSingleClass(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Bias tree.
tree1 = tree_ensemble_config.trees.add()
@@ -466,7 +466,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual([[], []], dropout_info.eval())
def testExcludeNonFinalTree(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Bias tree.
tree1 = tree_ensemble_config.trees.add()
@@ -513,7 +513,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual([[], []], dropout_info.eval())
def testIncludeNonFinalTree(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Bias tree.
tree1 = tree_ensemble_config.trees.add()
@@ -564,7 +564,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
def testMetadataMissing(self):
# Sometimes we want to do prediction on trees that are not added to ensemble
# (for example in
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Bias tree.
tree1 = tree_ensemble_config.trees.add()
@@ -612,7 +612,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
# For TREE_PER_CLASS strategy, predictions size is num_classes-1
def testFullEnsembleMultiClassTreePerClassStrategy(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Bias tree only for second class.
tree1 = tree_ensemble_config.trees.add()
@@ -663,7 +663,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
# This test is when leafs have SPARSE weights stored (class id and
# contribution).
def testFullEnsembleMultiNotClassTreePerClassStrategySparseVector(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Bias tree only for second class.
tree1 = tree_ensemble_config.trees.add()
@@ -713,7 +713,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
# will have the size of the number of classes.
# This test is when leafs have DENSE weights stored (weight for each class)
def testFullEnsembleMultiNotClassTreePerClassStrategyDenseVector(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Bias tree only for second class.
tree1 = tree_ensemble_config.trees.add()
@@ -760,7 +760,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual([[], []], dropout_info.eval())
def testDropout(self):
- with self.test_session():
+ with self.cached_session():
# Empty tree ensenble.
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Add 1000 trees with some weights.
@@ -823,7 +823,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
# This is for normal non-batch mode where ensemble does not contain the tree
# that is being built currently.
num_trees = 10
- with self.test_session():
+ with self.cached_session():
# Empty tree ensemble.
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Add 10 trees with some weights.
@@ -891,7 +891,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
# This is batch mode where ensemble already contains the tree that we are
# building. This tree should never be dropped.
num_trees = 10
- with self.test_session():
+ with self.cached_session():
# Empty tree ensemble.
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Add 10 trees with some weights.
@@ -959,7 +959,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
dropout_info_center[0][num_dropped_center - 1])
def testDropoutSeed(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Add 10 trees with some weights.
for i in range(0, 999):
@@ -1032,7 +1032,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
len(dropout_info_4.eval()[0]) + 1, len(dropout_info_1.eval()[0]))
def testDropOutZeroProb(self):
- with self.test_session():
+ with self.cached_session():
# Empty tree ensemble.
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Add 1000 trees with some weights.
@@ -1075,7 +1075,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose(result.eval(), result_no_dropout.eval())
def testAveragingAllTrees(self):
- with self.test_session():
+ with self.cached_session():
# Empty tree ensemble.
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
adjusted_tree_ensemble_config = (
@@ -1139,7 +1139,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(dropout_info.eval(), pattern_dropout_info.eval())
def testAveragingSomeTrees(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
adjusted_tree_ensemble_config = (
tree_config_pb2.DecisionTreeEnsembleConfig())
@@ -1220,7 +1220,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual(dropout_info_2.eval(), pattern_dropout_info.eval())
def testAverageMoreThanNumTreesExist(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
adjusted_tree_ensemble_config = (
tree_config_pb2.DecisionTreeEnsembleConfig())
@@ -1309,7 +1309,7 @@ class PartitionExamplesOpsTest(test_util.TensorFlowTestCase):
self._sparse_int_shape1 = np.array([2, 2])
def testEnsembleEmpty(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
tree_ensemble_handle = model_ops.tree_ensemble_variable(
@@ -1329,7 +1329,7 @@ class PartitionExamplesOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual([0, 0], result.eval())
def testTreeNonFinalized(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Depth 3 tree.
tree1 = tree_ensemble_config.trees.add()
@@ -1364,7 +1364,7 @@ class PartitionExamplesOpsTest(test_util.TensorFlowTestCase):
self.assertAllEqual([5, 3], result.eval())
def testTreeFinalized(self):
- with self.test_session():
+ with self.cached_session():
tree_ensemble_config = tree_config_pb2.DecisionTreeEnsembleConfig()
# Depth 3 tree.
tree1 = tree_ensemble_config.trees.add()
generated by cgit v1.2.3 (git 2.39.1) at 2024-06-26 16:25:39 +0000