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: 209839032

10 files changed, 51 insertions, 51 deletions

diff --git a/tensorflow/contrib/training/python/training/batch_sequences_with_states_test.py b/tensorflow/contrib/training/python/training/batch_sequences_with_states_test.py
index 81278ea82c..afeef978f3 100644
--- a/tensorflow/contrib/training/python/training/batch_sequences_with_states_test.py
+++ b/tensorflow/contrib/training/python/training/batch_sequences_with_states_test.py
@@ -108,7 +108,7 @@ class BatchSequencesWithStatesTest(test.TestCase):
                   expected_seq4_batch1, expected_seq4_batch2,
                   key=None, make_keys_unique=False):
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       next_batch = sqss.batch_sequences_with_states(
           input_key=key if key is not None else self.key,
           input_sequences=self.sequences,
@@ -332,7 +332,7 @@ class BatchSequencesWithStatesTest(test.TestCase):
         "seq4": self.sequences["seq4"],
     }
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       with self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
                                    ".*should be a multiple of: 3, but saw "
                                    "value: 4. Consider setting pad=True."):
diff --git a/tensorflow/contrib/training/python/training/bucket_ops_test.py b/tensorflow/contrib/training/python/training/bucket_ops_test.py
index 504f1fcd41..b259e0ee83 100644
--- a/tensorflow/contrib/training/python/training/bucket_ops_test.py
+++ b/tensorflow/contrib/training/python/training/bucket_ops_test.py
@@ -112,7 +112,7 @@ class BucketTest(test.TestCase):
     self.assertAllEqual(
         [[32], [32, None], [32, 3], [None, None]],
         [out.get_shape().as_list() for out in bucketed_dynamic[1]])
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       for v in range(32):
         self.enqueue_inputs(sess, {
             self.scalar_int_feed: v,
@@ -162,7 +162,7 @@ class BucketTest(test.TestCase):
     self.assertAllEqual(
         [[None], [None, None], [None, 3], [None, None]],
         [out.get_shape().as_list() for out in bucketed_dynamic[1]])
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       for v in range(15):
         self.enqueue_inputs(sess, {
             self.scalar_int_feed: v,
@@ -204,7 +204,7 @@ class BucketTest(test.TestCase):
     self.assertAllEqual(
         [[32], [32, None], [32, 3], [None, None]],
         [out.get_shape().as_list() for out in bucketed_dynamic[1]])
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       for v in range(64):
         self.enqueue_inputs(sess, {
             self.scalar_int_feed: v,
@@ -286,7 +286,7 @@ class BucketTest(test.TestCase):
     self.assertAllEqual(
         [[32], [32, None], [32, 3]],
         [out.get_shape().as_list() for out in bucketed_dynamic[1]])
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       for v in range(128):
         self.enqueue_inputs(sess, {
             self.scalar_int_feed: v,
@@ -405,7 +405,7 @@ class BucketBySequenceLengthTest(test.TestCase):
               num_pairs_to_enqueue - (batch_size - 1) * num_buckets,
               num_pairs_dequeued)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       coord = coordinator.Coordinator()
 
       # Feed the inputs, then close the input thread.
diff --git a/tensorflow/contrib/training/python/training/evaluation_test.py b/tensorflow/contrib/training/python/training/evaluation_test.py
index c36d00e842..ec47fe5d97 100644
--- a/tensorflow/contrib/training/python/training/evaluation_test.py
+++ b/tensorflow/contrib/training/python/training/evaluation_test.py
@@ -67,7 +67,7 @@ class CheckpointIteratorTest(test.TestCase):
     global_step = variables.get_or_create_global_step()
     saver = saver_lib.Saver()  # Saves the global step.
 
-    with self.test_session() as session:
+    with self.cached_session() as session:
       session.run(variables_lib.global_variables_initializer())
       save_path = os.path.join(checkpoint_dir, 'model.ckpt')
       saver.save(session, save_path, global_step=global_step)
diff --git a/tensorflow/contrib/training/python/training/resample_test.py b/tensorflow/contrib/training/python/training/resample_test.py
index 774241a816..8665a24883 100644
--- a/tensorflow/contrib/training/python/training/resample_test.py
+++ b/tensorflow/contrib/training/python/training/resample_test.py
@@ -44,7 +44,7 @@ class ResampleTest(test.TestCase):
         ([3], [0, 0, 0]),
         ([0, 1, 2, 3], [1, 2, 2, 3, 3, 3]),
     ]
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       for inputs, expected in cases:
         array_inputs = numpy.array(inputs, dtype=numpy.int32)
         actual = sess.run(resample._repeat_range(array_inputs))
@@ -65,7 +65,7 @@ class ResampleTest(test.TestCase):
 
     init = control_flow_ops.group(variables.local_variables_initializer(),
                                   variables.global_variables_initializer())
-    with self.test_session() as s:
+    with self.cached_session() as s:
       s.run(init)  # initialize
 
       # outputs
@@ -112,7 +112,7 @@ class ResampleTest(test.TestCase):
     init = control_flow_ops.group(variables.local_variables_initializer(),
                                   variables.global_variables_initializer())
     expected_sum_op = math_ops.reduce_sum(vals)
-    with self.test_session() as s:
+    with self.cached_session() as s:
       s.run(init)
       expected_sum = n * s.run(expected_sum_op)
 
@@ -147,7 +147,7 @@ class ResampleTest(test.TestCase):
 
     resampled = resample.resample_at_rate([vals], rates)
 
-    with self.test_session() as s:
+    with self.cached_session() as s:
       rs, = s.run(resampled, {
           vals: list(range(count)),
           rates: numpy.zeros(
diff --git a/tensorflow/contrib/training/python/training/sampling_ops_test.py b/tensorflow/contrib/training/python/training/sampling_ops_test.py
index bf7fb4fd48..1aeff7dc80 100644
--- a/tensorflow/contrib/training/python/training/sampling_ops_test.py
+++ b/tensorflow/contrib/training/python/training/sampling_ops_test.py
@@ -146,7 +146,7 @@ class StratifiedSampleTest(test.TestCase):
 
     for illegal_label in illegal_labels:
       # Run session that should fail.
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         with self.assertRaises(errors_impl.InvalidArgumentError):
           sess.run([val_tf, lbl_tf],
                    feed_dict={label_ph: illegal_label,
@@ -154,7 +154,7 @@ class StratifiedSampleTest(test.TestCase):
 
     for illegal_prob in illegal_probs:
       # Run session that should fail.
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         with self.assertRaises(errors_impl.InvalidArgumentError):
           sess.run([prob_tf],
                    feed_dict={label_ph: valid_labels,
@@ -172,7 +172,7 @@ class StratifiedSampleTest(test.TestCase):
     summary_op = logging_ops.merge_summary(
         ops.get_collection(ops.GraphKeys.SUMMARIES))
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       coord = coordinator.Coordinator()
       threads = queue_runner_impl.start_queue_runners(coord=coord)
 
@@ -197,7 +197,7 @@ class StratifiedSampleTest(test.TestCase):
         batch_size,
         init_probs=[0, .3, 0, .7, 0],
         enqueue_many=True)
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       coord = coordinator.Coordinator()
       threads = queue_runner_impl.start_queue_runners(coord=coord)
 
@@ -228,7 +228,7 @@ class StratifiedSampleTest(test.TestCase):
 
     # Run graph to make sure there are no shape-related runtime errors.
     for vals, labels in legal_input_pairs:
-      with self.test_session() as sess:
+      with self.cached_session() as sess:
         sess.run([val_tf, labels_tf],
                  feed_dict={vals_ph: vals,
                             labels_ph: labels})
@@ -253,7 +253,7 @@ class StratifiedSampleTest(test.TestCase):
     self.assertEqual(len(val_list), len(val_input_batch))
     self.assertTrue(isinstance(lbls, ops.Tensor))
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       coord = coordinator.Coordinator()
       threads = queue_runner_impl.start_queue_runners(coord=coord)
 
@@ -283,7 +283,7 @@ class StratifiedSampleTest(test.TestCase):
     # Run session and keep track of how frequently the labels and values appear.
     data_l = []
     label_l = []
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # Need to initialize variables that keep running total of classes seen.
       variables.global_variables_initializer().run()
 
@@ -374,7 +374,7 @@ class RejectionSampleTest(test.TestCase):
         'rejection_sample/prob_with_checks:0')
 
     # Run session that should fail.
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       for illegal_prob in [-0.1, 1.1]:
         with self.assertRaises(errors_impl.InvalidArgumentError):
           sess.run(prob_tensor, feed_dict={prob_ph: illegal_prob})
@@ -393,7 +393,7 @@ class RejectionSampleTest(test.TestCase):
     sample = sampling_ops.rejection_sample(tensor_list, accept_prob_fn,
                                            batch_size)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       coord = coordinator.Coordinator()
       threads = queue_runner_impl.start_queue_runners(coord=coord)
 
diff --git a/tensorflow/contrib/training/python/training/sampling_ops_threading_test.py b/tensorflow/contrib/training/python/training/sampling_ops_threading_test.py
index ca78c0029e..73ad859ab3 100644
--- a/tensorflow/contrib/training/python/training/sampling_ops_threading_test.py
+++ b/tensorflow/contrib/training/python/training/sampling_ops_threading_test.py
@@ -59,7 +59,7 @@ class SamplingOpsThreadingTest(test.TestCase):
     out_tensor = queue.dequeue()
 
     # Run the multi-threaded session.
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       # Need to initialize variables that keep running total of classes seen.
       variables.global_variables_initializer().run()
 
diff --git a/tensorflow/contrib/training/python/training/sequence_queueing_state_saver_test.py b/tensorflow/contrib/training/python/training/sequence_queueing_state_saver_test.py
index 7aebd9d9fe..8932b905c9 100644
--- a/tensorflow/contrib/training/python/training/sequence_queueing_state_saver_test.py
+++ b/tensorflow/contrib/training/python/training/sequence_queueing_state_saver_test.py
@@ -36,7 +36,7 @@ from tensorflow.python.platform import test
 class SequenceQueueingStateSaverTest(test.TestCase):
 
   def testSequenceInputWrapper(self):
-    with self.test_session():
+    with self.cached_session():
       length = 3
       key = "key"
       padded_length = 4
@@ -54,7 +54,7 @@ class SequenceQueueingStateSaverTest(test.TestCase):
       self.assertTrue(isinstance(input_wrapper.context["context1"], ops.Tensor))
 
   def testStateSaverWithTwoSimpleSteps(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       batch_size_value = 2
       batch_size = constant_op.constant(batch_size_value)
       num_unroll = 2
@@ -159,7 +159,7 @@ class SequenceQueueingStateSaverTest(test.TestCase):
       self.assertEqual(0, state_saver.barrier.ready_size().eval())
 
   def testStateSaverFailsIfPaddedLengthIsNotMultipleOfNumUnroll(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       batch_size = constant_op.constant(32)
       num_unroll = 17
       bad_padded_length = 3
@@ -194,7 +194,7 @@ class SequenceQueueingStateSaverTest(test.TestCase):
                  })
 
   def _testStateSaverFailsIfCapacityTooSmall(self, batch_size):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       num_unroll = 2
       length = array_ops.placeholder(dtypes.int32)
       key = array_ops.placeholder(dtypes.string)
@@ -243,7 +243,7 @@ class SequenceQueueingStateSaverTest(test.TestCase):
       self._testStateSaverFailsIfCapacityTooSmall(batch_size)
 
   def testStateSaverFailsIfInconsistentPaddedLength(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       batch_size = constant_op.constant(32)
       num_unroll = 17
       length = array_ops.placeholder(dtypes.int32)
@@ -282,7 +282,7 @@ class SequenceQueueingStateSaverTest(test.TestCase):
 
   def testStateSaverFailsIfInconsistentWriteState(self):
     # TODO(b/26910386): Identify why this infrequently causes timeouts.
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       batch_size = constant_op.constant(1)
       num_unroll = 17
       length = array_ops.placeholder(dtypes.int32)
@@ -326,7 +326,7 @@ class SequenceQueueingStateSaverTest(test.TestCase):
   def testStateSaverWithManyInputsReadWriteThread(self):
     batch_size_value = 32
     num_proc_threads = 100
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       batch_size = constant_op.constant(batch_size_value)
       num_unroll = 17
       length = array_ops.placeholder(dtypes.int32)
@@ -490,7 +490,7 @@ class SequenceQueueingStateSaverTest(test.TestCase):
       self.assertGreater(processed_count[0], 2 * 20 * batch_size_value)
 
   def testStateSaverProcessesExamplesInOrder(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       batch_size_value = 32
       batch_size = constant_op.constant(batch_size_value)
       num_unroll = 17
@@ -563,7 +563,7 @@ class SequenceQueueingStateSaverTest(test.TestCase):
       self.assertEqual(get_ready_size.eval(), 0)
 
   def testStateSaverCanHandleVariableBatchsize(self):
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       batch_size = array_ops.placeholder(dtypes.int32)
       num_unroll = 17
       length = array_ops.placeholder(dtypes.int32)
diff --git a/tensorflow/contrib/training/python/training/sgdr_learning_rate_decay_test.py b/tensorflow/contrib/training/python/training/sgdr_learning_rate_decay_test.py
index 4a46e9a49e..3269d5fef2 100644
--- a/tensorflow/contrib/training/python/training/sgdr_learning_rate_decay_test.py
+++ b/tensorflow/contrib/training/python/training/sgdr_learning_rate_decay_test.py
@@ -62,7 +62,7 @@ class SGDRDecayTest(test_util.TensorFlowTestCase):
   def get_sgdr_values(self, lr, initial_period_steps, t_mul, iters):
     """Get an array with learning rate values from the consecutive steps
     using current tensorflow implementation."""
-    with self.test_session():
+    with self.cached_session():
       step = placeholder(dtypes.int32)
 
       decay = sgdr_decay(lr, step, initial_period_steps, t_mul)
@@ -76,7 +76,7 @@ class SGDRDecayTest(test_util.TensorFlowTestCase):
     """Compare values generated by tensorflow implementation to the values
     generated by the original implementation
     (https://github.com/loshchil/SGDR/blob/master/SGDR_WRNs.py)."""
-    with self.test_session():
+    with self.cached_session():
       lr = 10.0
       init_steps = 2
       t_mul = 3
@@ -92,7 +92,7 @@ class SGDRDecayTest(test_util.TensorFlowTestCase):
   def testMDecay(self):
     """Test m_mul argument. Check values for learning rate at the beginning
     of the first, second, third and fourth period. """
-    with self.test_session():
+    with self.cached_session():
       step = placeholder(dtypes.int32)
 
       lr = 0.1
@@ -121,7 +121,7 @@ class SGDRDecayTest(test_util.TensorFlowTestCase):
   def testCos(self):
     """Check learning rate values at the beginning, in the middle
     and at the end of the period."""
-    with self.test_session():
+    with self.cached_session():
       step = placeholder(dtypes.int32)
       lr = 0.2
       t_e = 1000
diff --git a/tensorflow/contrib/training/python/training/tensor_queue_dataset_test.py b/tensorflow/contrib/training/python/training/tensor_queue_dataset_test.py
index df0a186f4f..d9b0511a98 100644
--- a/tensorflow/contrib/training/python/training/tensor_queue_dataset_test.py
+++ b/tensorflow/contrib/training/python/training/tensor_queue_dataset_test.py
@@ -79,7 +79,7 @@ class PrependFromQueueAndPaddedBatchDatasetTest(test.TestCase):
     iterator = dataset.make_one_shot_iterator()
     queue_handle, value = iterator.get_next()
     enqueue_negative = tqd.enqueue_in_queue_dataset(queue_handle, -value)
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       self.assertAllEqual([[0, 0, 0]], sess.run(value))
       value_1, _ = sess.run([value, enqueue_negative])
       self.assertAllEqual([[1, 0, 0]], value_1)
@@ -101,7 +101,7 @@ class PrependFromQueueAndPaddedBatchDatasetTest(test.TestCase):
     iterator = dataset.make_one_shot_iterator()
     queue_handle, value = iterator.get_next()
     enqueue_negative = tqd.enqueue_in_queue_dataset(queue_handle, -value)
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       self.assertEqual([0], sess.run(value))
       value_1, _ = sess.run([value, enqueue_negative])
       self.assertEqual([1], value_1)
@@ -126,7 +126,7 @@ class PrependFromQueueAndPaddedBatchDatasetTest(test.TestCase):
     enqueue_zeroth = tqd.enqueue_in_queue_dataset([queue_handle[0]],
                                                   array_ops.expand_dims(
                                                       value[0], axis=0))
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       value_0, _ = sess.run([value, enqueue_negative])
       self.assertAllEqual([0, 1], value_0)
       value_1, _ = sess.run([value, enqueue_zeroth])
@@ -147,7 +147,7 @@ class PrependFromQueueAndPaddedBatchDatasetTest(test.TestCase):
         tqd.enqueue_in_queue_dataset(queue_handle, value + 100 + i)
         for i in range(1000)
     ]
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       value_0, _ = sess.run((value, enqueue_many_more))
       self.assertEqual([0], value_0)
       rest = []
@@ -174,7 +174,7 @@ class PrependFromQueueAndPaddedBatchDatasetTest(test.TestCase):
     iterator = dataset.make_one_shot_iterator()
     queue_handle, value = iterator.get_next()
     enqueue = tqd.enqueue_in_queue_dataset(queue_handle, value + 1)
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       i = 0
       while i < 4:
         received, _ = sess.run((value, enqueue))
@@ -199,7 +199,7 @@ class PrependFromQueueAndPaddedBatchDatasetTest(test.TestCase):
             batch_size=1, padded_shapes=[2]))
     iterator = dataset.make_one_shot_iterator()
     _, value = iterator.get_next()
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       with self.assertRaisesOpError(
           r"Incompatible input shapes at component 0 between "
           r"input dataset this dataset: \[3\] vs. \[2\]"):
@@ -224,7 +224,7 @@ class PrependFromQueueAndPaddedBatchDatasetTest(test.TestCase):
                                                      np.array(
                                                          [[1]], dtype=np.int32))
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       with self.assertRaisesOpError(
           "mismatched number of tensors.  Queue expects 1 tensors but "
           "tried to insert 2"):
@@ -274,7 +274,7 @@ class PrependFromQueueAndPaddedBatchDatasetTest(test.TestCase):
     with ops.control_dependencies([enqueue_rest_op]):
       calc = array_ops.identity(value_head)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       self.assertAllEqual([[0, 0], [2, 2], [4, 4]], sess.run(calc))
       self.assertAllEqual([[4, 4], [6, 6]], sess.run(calc))
       self.assertAllEqual([[6, 6]], sess.run(calc))
@@ -304,7 +304,7 @@ class PrependFromQueueAndPaddedBatchDatasetTest(test.TestCase):
     iterator = dataset.make_one_shot_iterator()
     _, (unused_count, padded_value) = iterator.get_next()
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       self.assertAllEqual([[-1, -1, -1, -1], [2, 2, -1, -1], [4, 4, 4, 4]],
                           sess.run(padded_value))
       self.assertAllEqual([[6] * 6], sess.run(padded_value))
diff --git a/tensorflow/contrib/training/python/training/training_test.py b/tensorflow/contrib/training/python/training/training_test.py
index 94cf7788b2..3b524ac8c7 100644
--- a/tensorflow/contrib/training/python/training/training_test.py
+++ b/tensorflow/contrib/training/python/training/training_test.py
@@ -62,7 +62,7 @@ class ClipGradsTest(test.TestCase):
     clipped_gradients_to_variables = training.clip_gradient_norms(
         gradients_to_variables, 3.0)
 
-    with self.test_session() as session:
+    with self.cached_session() as session:
       session.run(variables_lib2.global_variables_initializer())
       self.assertAlmostEqual(4.0, gradients_to_variables[0][0].eval())
       self.assertAlmostEqual(3.0, clipped_gradients_to_variables[0][0].eval())
@@ -75,7 +75,7 @@ class ClipGradsTest(test.TestCase):
     clipped_gradients_to_variables = training.clip_gradient_norms_fn(3.0)(
         gradients_to_variables)
 
-    with self.test_session() as session:
+    with self.cached_session() as session:
       session.run(variables_lib2.global_variables_initializer())
       self.assertAlmostEqual(4.0, gradients_to_variables[0][0].eval())
       self.assertAlmostEqual(3.0, clipped_gradients_to_variables[0][0].eval())
@@ -122,7 +122,7 @@ class CreateTrainOpTest(test.TestCase):
       moving_variance = variables_lib.get_variables_by_name('moving_variance')[
           0]
 
-      with self.test_session() as session:
+      with self.cached_session() as session:
         # Initialize all variables
         session.run(variables_lib2.global_variables_initializer())
         mean, variance = session.run([moving_mean, moving_variance])
@@ -155,7 +155,7 @@ class CreateTrainOpTest(test.TestCase):
       moving_variance = variables_lib.get_variables_by_name('moving_variance')[
           0]
 
-      with self.test_session() as session:
+      with self.cached_session() as session:
         # Initialize all variables
         session.run(variables_lib2.global_variables_initializer())
         mean, variance = session.run([moving_mean, moving_variance])
@@ -186,7 +186,7 @@ class CreateTrainOpTest(test.TestCase):
 
       global_step = variables_lib.get_or_create_global_step()
 
-      with self.test_session() as session:
+      with self.cached_session() as session:
         # Initialize all variables
         session.run(variables_lib2.global_variables_initializer())
 
@@ -209,7 +209,7 @@ class CreateTrainOpTest(test.TestCase):
 
       global_step = variables_lib.get_or_create_global_step()
 
-      with self.test_session() as session:
+      with self.cached_session() as session:
         # Initialize all variables
         session.run(variables_lib2.global_variables_initializer())
 
@@ -535,7 +535,7 @@ class TrainTest(test.TestCase):
       train_biases = training.create_train_op(
           total_loss, optimizer, variables_to_train=[biases])
 
-      with self.test_session() as session:
+      with self.cached_session() as session:
         # Initialize the variables.
         session.run(variables_lib2.global_variables_initializer())