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: 209701635

3 files changed, 15 insertions, 15 deletions

diff --git a/tensorflow/contrib/seq2seq/python/kernel_tests/attention_wrapper_test.py b/tensorflow/contrib/seq2seq/python/kernel_tests/attention_wrapper_test.py
index cd162bae25..f2c43f30d4 100644
--- a/tensorflow/contrib/seq2seq/python/kernel_tests/attention_wrapper_test.py
+++ b/tensorflow/contrib/seq2seq/python/kernel_tests/attention_wrapper_test.py
@@ -512,7 +512,7 @@ class AttentionWrapperTest(test.TestCase):
 
     for axis in [0, 1]:
       for exclusive in [True, False]:
-        with self.test_session():
+        with self.cached_session():
           # Compute cumprod with regular tf.cumprod
           cumprod_output = math_ops.cumprod(
               test_input, axis=axis, exclusive=exclusive).eval()
@@ -548,7 +548,7 @@ class AttentionWrapperTest(test.TestCase):
         for p, a in zip(p_choose_i, previous_attention)])
 
     # Compute output with TensorFlow function, for both calculation types
-    with self.test_session():
+    with self.cached_session():
       recursive_output = wrapper.monotonic_attention(
           p_choose_i, previous_attention, 'recursive').eval()
 
@@ -569,7 +569,7 @@ class AttentionWrapperTest(test.TestCase):
         for p, a in zip(p_choose_i, previous_attention)])
 
     # Compute output with TensorFlow function, for both calculation types
-    with self.test_session():
+    with self.cached_session():
       parallel_output = wrapper.monotonic_attention(
           p_choose_i, previous_attention, 'parallel').eval()
 
@@ -594,7 +594,7 @@ class AttentionWrapperTest(test.TestCase):
         for p, a in zip(p_choose_i, previous_attention)])
 
     # Compute output with TensorFlow function, for both calculation types
-    with self.test_session():
+    with self.cached_session():
       hard_output = wrapper.monotonic_attention(
           # TensorFlow is unhappy when these are not wrapped as tf.constant
           constant_op.constant(p_choose_i),
@@ -634,7 +634,7 @@ class AttentionWrapperTest(test.TestCase):
     recursive_output = [np.array([1] + [0]*(p_choose_i.shape[1] - 1),
                                  np.float32)]
     # Compute output with TensorFlow function, for both calculation types
-    with self.test_session():
+    with self.cached_session():
       for j in range(p_choose_i.shape[0]):
         # Compute attention distribution for this output time step
         recursive_output.append(wrapper.monotonic_attention(
diff --git a/tensorflow/contrib/seq2seq/python/kernel_tests/beam_search_decoder_test.py b/tensorflow/contrib/seq2seq/python/kernel_tests/beam_search_decoder_test.py
index 4073b390fc..f5b6b1bde9 100644
--- a/tensorflow/contrib/seq2seq/python/kernel_tests/beam_search_decoder_test.py
+++ b/tensorflow/contrib/seq2seq/python/kernel_tests/beam_search_decoder_test.py
@@ -66,7 +66,7 @@ class TestGatherTree(test.TestCase):
         max_sequence_lengths=max_sequence_lengths,
         end_token=11)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       res_ = sess.run(res)
 
     self.assertAllEqual(expected_result, res_)
@@ -115,7 +115,7 @@ class TestGatherTree(test.TestCase):
     sorted_array = beam_search_decoder.gather_tree_from_array(
         array, parent_ids, sequence_length)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       sorted_array = sess.run(sorted_array)
       expected_array = sess.run(expected_array)
       self.assertAllEqual(expected_array, sorted_array)
@@ -170,7 +170,7 @@ class TestGatherTree(test.TestCase):
     sorted_array = beam_search_decoder.gather_tree_from_array(
         array, parent_ids, sequence_length)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       sorted_array, expected_array = sess.run([sorted_array, expected_array])
       self.assertAllEqual(expected_array, sorted_array)
 
@@ -186,7 +186,7 @@ class TestArrayShapeChecks(test.TestCase):
     batch_size = array_ops.constant(batch_size)
     check_op = beam_search_decoder._check_batch_beam(t, batch_size, beam_width)  # pylint: disable=protected-access
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       if is_valid:
         sess.run(check_op)
       else:
@@ -220,7 +220,7 @@ class TestEosMasking(test.TestCase):
     masked = beam_search_decoder._mask_probs(probs, eos_token,
                                              previously_finished)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       probs = sess.run(probs)
       masked = sess.run(masked)
 
@@ -283,7 +283,7 @@ class TestBeamStep(test.TestCase):
         end_token=self.end_token,
         length_penalty_weight=self.length_penalty_weight)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       outputs_, next_state_, state_, log_probs_ = sess.run(
           [outputs, next_beam_state, beam_state, log_probs])
 
@@ -338,7 +338,7 @@ class TestBeamStep(test.TestCase):
         end_token=self.end_token,
         length_penalty_weight=self.length_penalty_weight)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       outputs_, next_state_, state_, log_probs_ = sess.run(
           [outputs, next_beam_state, beam_state, log_probs])
 
@@ -436,7 +436,7 @@ class TestLargeBeamStep(test.TestCase):
         end_token=self.end_token,
         length_penalty_weight=self.length_penalty_weight)
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       outputs_, next_state_, _, _ = sess.run(
           [outputs, next_beam_state, beam_state, log_probs])
 
@@ -471,7 +471,7 @@ class BeamSearchDecoderTest(test.TestCase):
     output_layer = layers_core.Dense(vocab_size, use_bias=True, activation=None)
     beam_width = 3
 
-    with self.test_session() as sess:
+    with self.cached_session() as sess:
       batch_size_tensor = constant_op.constant(batch_size)
       embedding = np.random.randn(vocab_size, embedding_dim).astype(np.float32)
       cell = rnn_cell.LSTMCell(cell_depth)
diff --git a/tensorflow/contrib/seq2seq/python/kernel_tests/beam_search_ops_test.py b/tensorflow/contrib/seq2seq/python/kernel_tests/beam_search_ops_test.py
index 277c5b6ef7..9662a5780a 100644
--- a/tensorflow/contrib/seq2seq/python/kernel_tests/beam_search_ops_test.py
+++ b/tensorflow/contrib/seq2seq/python/kernel_tests/beam_search_ops_test.py
@@ -67,7 +67,7 @@ class GatherTreeTest(test.TestCase):
           parent_ids=parent_ids,
           max_sequence_lengths=max_sequence_lengths,
           end_token=end_token)
-    with self.test_session():
+    with self.cached_session():
       with self.assertRaisesOpError(
           r"parent id -1 at \(batch, time, beam\) == \(0, 0, 1\)"):
         _ = beams.eval()