diff options
24 files changed, 150 insertions, 150 deletions
diff --git a/tensorflow/contrib/slim/python/slim/data/dataset_data_provider_test.py b/tensorflow/contrib/slim/python/slim/data/dataset_data_provider_test.py index 1bb6fbc570..795de6a408 100644 --- a/tensorflow/contrib/slim/python/slim/data/dataset_data_provider_test.py +++ b/tensorflow/contrib/slim/python/slim/data/dataset_data_provider_test.py @@ -88,7 +88,7 @@ class DatasetDataProviderTest(test.TestCase): height = 300 width = 280 - with self.test_session(): + with self.cached_session(): test_dataset = _create_tfrecord_dataset(dataset_dir) provider = dataset_data_provider.DatasetDataProvider(test_dataset) key, image, label = provider.get(['record_key', 'image', 'label']) @@ -111,7 +111,7 @@ class DatasetDataProviderTest(test.TestCase): height = 300 width = 280 - with self.test_session(): + with self.cached_session(): provider = dataset_data_provider.DatasetDataProvider( _create_tfrecord_dataset(dataset_dir)) [image] = provider.get(['image']) @@ -128,7 +128,7 @@ class DatasetDataProviderTest(test.TestCase): dataset_dir = tempfile.mkdtemp(prefix=os.path.join(self.get_temp_dir(), 'tfrecord_dataset')) - with self.test_session(): + with self.cached_session(): with self.assertRaises(ValueError): dataset_data_provider.DatasetDataProvider( _create_tfrecord_dataset(dataset_dir), record_key='image') diff --git a/tensorflow/contrib/slim/python/slim/data/parallel_reader_test.py b/tensorflow/contrib/slim/python/slim/data/parallel_reader_test.py index ea8cc0ff61..c457d44e07 100644 --- a/tensorflow/contrib/slim/python/slim/data/parallel_reader_test.py +++ b/tensorflow/contrib/slim/python/slim/data/parallel_reader_test.py @@ -39,7 +39,7 @@ class ParallelReaderTest(test.TestCase): ops.reset_default_graph() def _verify_all_data_sources_read(self, shared_queue): - with self.test_session(): + with self.cached_session(): tfrecord_paths = test_utils.create_tfrecord_files( self.get_temp_dir(), num_files=3) @@ -76,7 +76,7 @@ class ParallelReaderTest(test.TestCase): self.assertEquals(count0 + count1 + count2, num_reads) def _verify_read_up_to_out(self, shared_queue): - with self.test_session(): + with self.cached_session(): num_files = 3 num_records_per_file = 7 tfrecord_paths = test_utils.create_tfrecord_files( @@ -161,7 +161,7 @@ class ParallelReadTest(test.TestCase): ops.reset_default_graph() def testTFRecordReader(self): - with self.test_session(): + with self.cached_session(): self._tfrecord_paths = test_utils.create_tfrecord_files( self.get_temp_dir(), num_files=3) @@ -188,7 +188,7 @@ class SinglePassReadTest(test.TestCase): ops.reset_default_graph() def testOutOfRangeError(self): - with self.test_session(): + with self.cached_session(): [tfrecord_path] = test_utils.create_tfrecord_files( self.get_temp_dir(), num_files=1) @@ -196,7 +196,7 @@ class SinglePassReadTest(test.TestCase): tfrecord_path, reader_class=io_ops.TFRecordReader) init_op = variables.local_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: sess.run(init_op) with queues.QueueRunners(sess): num_reads = 11 @@ -205,7 +205,7 @@ class SinglePassReadTest(test.TestCase): sess.run([key, value]) def testTFRecordReader(self): - with self.test_session(): + with self.cached_session(): [tfrecord_path] = test_utils.create_tfrecord_files( self.get_temp_dir(), num_files=1) @@ -213,7 +213,7 @@ class SinglePassReadTest(test.TestCase): tfrecord_path, reader_class=io_ops.TFRecordReader) init_op = variables.local_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: sess.run(init_op) with queues.QueueRunners(sess): flowers = 0 diff --git a/tensorflow/contrib/slim/python/slim/data/prefetch_queue_test.py b/tensorflow/contrib/slim/python/slim/data/prefetch_queue_test.py index 6c3e57c47d..7caa42dcb9 100644 --- a/tensorflow/contrib/slim/python/slim/data/prefetch_queue_test.py +++ b/tensorflow/contrib/slim/python/slim/data/prefetch_queue_test.py @@ -37,7 +37,7 @@ from tensorflow.python.training import queue_runner_impl class PrefetchQueueTest(test.TestCase): def testOneThread(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 image_size = 32 num_batches = 5 @@ -74,7 +74,7 @@ class PrefetchQueueTest(test.TestCase): thread.join() def testMultiThread(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 image_size = 32 num_batches = 5 @@ -114,7 +114,7 @@ class PrefetchQueueTest(test.TestCase): thread.join() def testMultipleDequeue(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 image_size = 32 num_batches = 4 @@ -162,7 +162,7 @@ class PrefetchQueueTest(test.TestCase): prefetch_queue.prefetch_queue([variable_tensor]) def testDynamicPad(self): - with self.test_session() as sess: + with self.cached_session() as sess: # Create 3 tensors of variable but compatible shapes. var_shape = [None, 2] p1 = constant_op.constant([[1, 2], [3, 4]]) diff --git a/tensorflow/contrib/slim/python/slim/data/tfexample_decoder_test.py b/tensorflow/contrib/slim/python/slim/data/tfexample_decoder_test.py index 826242c9d7..3114949b82 100644 --- a/tensorflow/contrib/slim/python/slim/data/tfexample_decoder_test.py +++ b/tensorflow/contrib/slim/python/slim/data/tfexample_decoder_test.py @@ -45,7 +45,7 @@ class TFExampleDecoderTest(test.TestCase): int64_list=feature_pb2.Int64List(value=ndarray.flatten().tolist())) def _EncodedBytesFeature(self, tf_encoded): - with self.test_session(): + with self.cached_session(): encoded = tf_encoded.eval() def BytesList(value): @@ -133,7 +133,7 @@ class TFExampleDecoderTest(test.TestCase): tf_image = self.DecodeExample(serialized_example, item_handler, image_format) - with self.test_session(): + with self.cached_session(): decoded_image = tf_image.eval() # We need to recast them here to avoid some issues with uint8. @@ -265,7 +265,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'labels': @@ -296,7 +296,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'array': parsing_ops.FixedLenFeature(np_array.shape, dtypes.float32) @@ -319,7 +319,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'array': parsing_ops.FixedLenFeature(np_array.shape, dtypes.int64) @@ -342,7 +342,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'labels': parsing_ops.VarLenFeature(dtype=dtypes.int64), @@ -366,7 +366,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'labels': @@ -390,7 +390,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'labels': parsing_ops.VarLenFeature(dtype=dtypes.int64), @@ -423,7 +423,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'image': parsing_ops.VarLenFeature(dtype=dtypes.float32), @@ -468,7 +468,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'image': parsing_ops.VarLenFeature(dtype=dtypes.float32), @@ -505,7 +505,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'indices': parsing_ops.VarLenFeature(dtype=dtypes.int64), @@ -536,7 +536,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'indices': parsing_ops.VarLenFeature(dtype=dtypes.int64), @@ -567,7 +567,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'indices': parsing_ops.VarLenFeature(dtype=dtypes.int64), @@ -598,7 +598,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { 'indices': parsing_ops.VarLenFeature(dtype=dtypes.int64), @@ -625,7 +625,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { @@ -657,7 +657,7 @@ class TFExampleDecoderTest(test.TestCase): serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { @@ -692,7 +692,7 @@ class TFExampleDecoderTest(test.TestCase): image, serialized_example = self.GenerateImage( image_format=image_encoding, image_shape=image_shape) - with self.test_session(): + with self.cached_session(): def ConditionalDecoding(keys_to_tensors): """See base class.""" @@ -759,7 +759,7 @@ class TFExampleDecoderTest(test.TestCase): })) serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { @@ -800,7 +800,7 @@ class TFExampleDecoderTest(test.TestCase): })) serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) keys_to_features = { @@ -837,7 +837,7 @@ class TFExampleDecoderTest(test.TestCase): image, _ = self.GenerateImage( image_format=image_format, image_shape=image_shape) tf_encoded = self._Encoder(image, image_format) - with self.test_session(): + with self.cached_session(): tf_string = tf_encoded.eval() example = example_pb2.Example( @@ -852,7 +852,7 @@ class TFExampleDecoderTest(test.TestCase): })) serialized_example = example.SerializeToString() - with self.test_session(): + with self.cached_session(): serialized_example = array_ops.reshape(serialized_example, shape=[]) decoder = tfexample_decoder.TFExampleDecoder( @@ -885,7 +885,7 @@ class TFExampleDecoderTest(test.TestCase): table = lookup_ops.index_table_from_tensor( constant_op.constant(['dog', 'guinea pig', 'cat'])) - with self.test_session() as sess: + with self.cached_session() as sess: sess.run(lookup_ops.tables_initializer()) serialized_example = array_ops.reshape(serialized_example, shape=[]) @@ -943,7 +943,7 @@ class TFExampleDecoderTest(test.TestCase): decoder = tfexample_decoder.TFExampleDecoder(keys_to_features, items_to_handlers) obtained_class_ids_each_example = [] - with self.test_session() as sess: + with self.cached_session() as sess: sess.run(lookup_ops.tables_initializer()) for example in [example1, example2, example3]: serialized_example = array_ops.reshape( diff --git a/tensorflow/contrib/solvers/python/kernel_tests/lanczos_test.py b/tensorflow/contrib/solvers/python/kernel_tests/lanczos_test.py index 4707dc2229..8fcd7aeef6 100644 --- a/tensorflow/contrib/solvers/python/kernel_tests/lanczos_test.py +++ b/tensorflow/contrib/solvers/python/kernel_tests/lanczos_test.py @@ -47,7 +47,7 @@ def _get_lanczos_tests(dtype_, use_static_shape_, shape_, orthogonalize_, low=-1.0, high=1.0, size=np.prod(shape_)).reshape(shape_).astype(dtype_) tol = 1e-12 if dtype_ == np.float64 else 1e-5 - with self.test_session() as sess: + with self.cached_session() as sess: if use_static_shape_: a = constant_op.constant(a_np) else: diff --git a/tensorflow/contrib/solvers/python/kernel_tests/least_squares_test.py b/tensorflow/contrib/solvers/python/kernel_tests/least_squares_test.py index a73642716b..2a9100903a 100644 --- a/tensorflow/contrib/solvers/python/kernel_tests/least_squares_test.py +++ b/tensorflow/contrib/solvers/python/kernel_tests/least_squares_test.py @@ -47,7 +47,7 @@ def _get_least_squares_tests(dtype_, use_static_shape_, shape_): low=-1.0, high=1.0, size=shape_[0]).astype(dtype_) tol = 1e-12 if dtype_ == np.float64 else 1e-6 max_iter = 20 - with self.test_session() as sess: + with self.cached_session() as sess: if use_static_shape_: a = constant_op.constant(a_np) rhs = constant_op.constant(rhs_np) diff --git a/tensorflow/contrib/solvers/python/kernel_tests/linear_equations_test.py b/tensorflow/contrib/solvers/python/kernel_tests/linear_equations_test.py index a1282847be..a0e6eb87bc 100644 --- a/tensorflow/contrib/solvers/python/kernel_tests/linear_equations_test.py +++ b/tensorflow/contrib/solvers/python/kernel_tests/linear_equations_test.py @@ -54,7 +54,7 @@ def _get_linear_equations_tests(dtype_, use_static_shape_, shape_): x_np = np.zeros_like(rhs_np) tol = 1e-6 if dtype_ == np.float64 else 1e-3 max_iter = 20 - with self.test_session() as sess: + with self.cached_session() as sess: if use_static_shape_: a = constant_op.constant(a_np) rhs = constant_op.constant(rhs_np) diff --git a/tensorflow/contrib/solvers/python/kernel_tests/util_test.py b/tensorflow/contrib/solvers/python/kernel_tests/util_test.py index 5d7534657b..57b4996689 100644 --- a/tensorflow/contrib/solvers/python/kernel_tests/util_test.py +++ b/tensorflow/contrib/solvers/python/kernel_tests/util_test.py @@ -33,7 +33,7 @@ class UtilTest(test.TestCase): a_np = np.array([[1., 2.], [3., 4.], [5., 6.]], dtype=dtype) x_np = np.array([[2.], [-3.]], dtype=dtype) y_np = np.array([[2], [-3.], [5.]], dtype=dtype) - with self.test_session() as sess: + with self.cached_session() as sess: if use_static_shape_: a = constant_op.constant(a_np, dtype=dtype) x = constant_op.constant(x_np, dtype=dtype) @@ -68,7 +68,7 @@ class UtilTest(test.TestCase): a_np = np.array([[1., 2.], [3., 4.], [5., 6.]], dtype=dtype) x_np = np.array([[2.], [-3.]], dtype=dtype) y_np = np.array([[2], [-3.], [5.]], dtype=dtype) - with self.test_session() as sess: + with self.cached_session() as sess: if use_static_shape_: a = constant_op.constant(a_np, dtype=dtype) x = constant_op.constant(x_np, dtype=dtype) @@ -101,7 +101,7 @@ class UtilTest(test.TestCase): self._testIdentityOperator(False) def testL2Norm(self): - with self.test_session(): + with self.cached_session(): x_np = np.array([[2], [-3.], [5.]]) x_norm_np = np.linalg.norm(x_np) x_normalized_np = x_np / x_norm_np diff --git a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/filtering_postprocessor_test.py b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/filtering_postprocessor_test.py index 53d7340e85..a77c507d9b 100644 --- a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/filtering_postprocessor_test.py +++ b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/filtering_postprocessor_test.py @@ -61,7 +61,7 @@ class FilteringStepPostprocessorTest(test.TestCase): expected_state = [[[80.], [20.]], [1., 6.], [-1, -2]] - with self.test_session(): + with self.cached_session(): for interpolated, expected in zip(interpolated_state, expected_state): self.assertAllClose(expected, interpolated.eval()) self.assertGreater(0., updated_outputs["anomaly_score"][0].eval()) diff --git a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/kalman_filter_test.py b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/kalman_filter_test.py index 57f29f3c7f..f636126a33 100644 --- a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/kalman_filter_test.py +++ b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/kalman_filter_test.py @@ -98,7 +98,7 @@ class MultivariateTests(test.TestCase): observation_model=observation_model, predicted_observations=(observed_mean, observed_var), observation_noise=observation_noise_covariance) - with self.test_session() as session: + with self.cached_session() as session: evaled_state = numpy.array([[1., 1., 1., 1.]]) evaled_state_var = numpy.eye(4)[None] for i in range(500): @@ -136,7 +136,7 @@ class KalmanFilterNonBatchTest(test.TestCase): def test_observed_from_state(self): """Compare observation mean and noise to hand-computed values.""" - with self.test_session(): + with self.cached_session(): state = constant_op.constant([[2., 1.]]) state_var = constant_op.constant([[[4., 0.], [0., 3.]]]) observed_mean, observed_var = self.kalman_filter.observed_from_state( @@ -171,7 +171,7 @@ class KalmanFilterNonBatchTest(test.TestCase): observation_model=observation_model, predicted_observations=predicted_observations, observation_noise=observation_noise)) - with self.test_session() as session: + with self.cached_session() as session: evaled_state, evaled_state_var = session.run([state, state_var]) for _ in range(300): evaled_state, evaled_state_var = session.run( @@ -231,7 +231,7 @@ class KalmanFilterNonBatchTest(test.TestCase): def test_predict_state_mean(self): """Compare state mean transitions with simple hand-computed values.""" - with self.test_session(): + with self.cached_session(): state = constant_op.constant([[4., 2.]]) state = self.kalman_filter.predict_state_mean( state, self.transition_fn([1])) @@ -245,7 +245,7 @@ class KalmanFilterNonBatchTest(test.TestCase): def test_predict_state_var(self): """Compare a variance transition with simple hand-computed values.""" - with self.test_session(): + with self.cached_session(): state_var = constant_op.constant([[[1., 0.], [0., 2.]]]) state_var = self.kalman_filter.predict_state_var( state_var, self.transition_fn([1]), self.power_sum_fn([1])) @@ -259,7 +259,7 @@ class KalmanFilterNonBatchTest(test.TestCase): Tests that correct values have high probability and incorrect values have low probability when there is low uncertainty. """ - with self.test_session(): + with self.cached_session(): state = constant_op.constant([[4., 2.]]) state_var = constant_op.constant([[[0.0001, 0.], [0., 0.0001]]]) observation = constant_op.constant([[ @@ -289,7 +289,7 @@ class KalmanFilterNonBatchTest(test.TestCase): self.assertGreater(first_log_prob.eval()[0], numpy.log(0.99)) def test_predict_n_ahead_mean(self): - with self.test_session(): + with self.cached_session(): original_state = constant_op.constant([[4., 2.]]) n = 5 iterative_state = original_state @@ -304,7 +304,7 @@ class KalmanFilterNonBatchTest(test.TestCase): self.transition_fn([1])) def test_predict_n_ahead_var(self): - with self.test_session(): + with self.cached_session(): original_var = constant_op.constant([[[2., 3.], [4., 5.]]]) n = 5 iterative_var = original_var @@ -330,7 +330,7 @@ class KalmanFilterBatchTest(test.TestCase): Tests that correct values have high probability and incorrect values have low probability when there is low uncertainty. """ - with self.test_session(): + with self.cached_session(): state = constant_op.constant([[4., 2.], [5., 3.], [6., 4.]]) state_var = constant_op.constant(3 * [[[0.0001, 0.], [0., 0.0001]]]) observation = constant_op.constant([ @@ -378,7 +378,7 @@ class KalmanFilterBatchTest(test.TestCase): self.assertLess(third_log_prob.sum(), numpy.log(0.01)) def test_predict_n_ahead_mean(self): - with self.test_session(): + with self.cached_session(): kf = kalman_filter.KalmanFilter() transition_fn, _ = _powers_and_sums_from_transition_matrix( state_transition=STATE_TRANSITION, @@ -396,7 +396,7 @@ class KalmanFilterBatchTest(test.TestCase): self.assertAllClose(state2.eval()[2], batch_eval[2]) def test_predict_n_ahead_var(self): - with self.test_session(): + with self.cached_session(): kf = kalman_filter.KalmanFilter() transition_fn, power_sum_fn = _powers_and_sums_from_transition_matrix( state_transition=STATE_TRANSITION, diff --git a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/state_space_model_test.py b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/state_space_model_test.py index c2eaa78493..80126ac786 100644 --- a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/state_space_model_test.py +++ b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/state_space_model_test.py @@ -96,7 +96,7 @@ class ConstructionTests(test.TestCase): }, mode=estimator_lib.ModeKeys.TRAIN) initializer = variables.global_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: sess.run([initializer]) outputs.loss.eval() @@ -114,7 +114,7 @@ class ConstructionTests(test.TestCase): }, mode=estimator_lib.ModeKeys.TRAIN) initializer = variables.global_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: sess.run([initializer]) outputs.loss.eval() @@ -144,7 +144,7 @@ class GapTests(test.TestCase): state=math_utils.replicate_state( start_state=random_model.get_start_state(), batch_size=array_ops.shape(times)[0])) - 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) @@ -250,7 +250,7 @@ class StateSpaceEquivalenceTests(test.TestCase): self.assertAllClose(combined_value, split_predict[prediction_key]) def _equivalent_to_single_model_test_template(self, model_generator): - with self.test_session() as session: + with self.cached_session() as session: random_model = RandomStateSpaceModel( state_dimension=5, state_noise_dimension=4, @@ -374,7 +374,7 @@ class PredictionTests(test.TestCase): math_utils.replicate_state( start_state=random_model.get_start_state(), batch_size=1) }) - with self.test_session(): + with self.cached_session(): variables.global_variables_initializer().run() predicted_mean = prediction_dict["mean"].eval() predicted_covariance = prediction_dict["covariance"].eval() @@ -404,7 +404,7 @@ class PredictionTests(test.TestCase): feature_keys.PredictionFeatures.TIMES: [[5, 7, 8]], feature_keys.PredictionFeatures.STATE_TUPLE: model_outputs.end_state }) - with self.test_session(): + with self.cached_session(): variables.global_variables_initializer().run() predicted_mean = predictions["mean"].eval() predicted_covariance = predictions["covariance"].eval() @@ -428,7 +428,7 @@ class ExogenousTests(test.TestCase): state=[ array_ops.ones(shape=[1, 5]), original_covariance[None], [0] ]) - with self.test_session() as session: + with self.cached_session() as session: variables.global_variables_initializer().run() evaled_new_covariance, evaled_original_covariance = session.run( [new_covariance[0], original_covariance]) @@ -454,7 +454,7 @@ class ExogenousTests(test.TestCase): -array_ops.ones(shape=[1, 5], dtype=dtype), original_covariance[None], [0] ]) - with self.test_session() as session: + with self.cached_session() as session: variables.global_variables_initializer().run() evaled_new_covariance, evaled_original_covariance = session.run( [new_covariance[0], original_covariance]) @@ -519,7 +519,7 @@ class PosteriorTests(test.TestCase): model=stub_model, data=data, true_parameters=true_params) def test_exact_posterior_recovery_no_transition_noise(self): - with self.test_session() as session: + with self.cached_session() as session: stub_model, data, true_params = self._get_single_model() input_fn = input_pipeline.WholeDatasetInputFn( input_pipeline.NumpyReader(data)) @@ -559,7 +559,7 @@ class PosteriorTests(test.TestCase): posterior_times) def test_chained_exact_posterior_recovery_no_transition_noise(self): - with self.test_session() as session: + with self.cached_session() as session: stub_model, data, true_params = self._get_single_model() chunk_size = 10 input_fn = test_utils.AllWindowInputFn( @@ -748,7 +748,7 @@ class MultivariateTests(test.TestCase): }, mode=estimator_lib.ModeKeys.TRAIN) initializer = variables.global_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: sess.run([initializer]) outputs.loss.eval() diff --git a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/varma_test.py b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/varma_test.py index 84885d5c9a..e8875f4eb9 100644 --- a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/varma_test.py +++ b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/varma_test.py @@ -46,7 +46,7 @@ class MakeModelTest(test.TestCase): }, mode=estimator_lib.ModeKeys.TRAIN) initializer = variables.global_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: sess.run([initializer]) outputs.loss.eval() @@ -65,7 +65,7 @@ class MakeModelTest(test.TestCase): }, mode=estimator_lib.ModeKeys.TRAIN) initializer = variables.global_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: sess.run([initializer]) outputs.loss.eval() @@ -85,7 +85,7 @@ class MakeModelTest(test.TestCase): TrainEvalFeatures.VALUES: constant_op.constant([[[1.], [2.]]])}, mode=estimator_lib.ModeKeys.TRAIN) initializer = variables.global_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: sess.run([initializer]) outputs.loss.eval() diff --git a/tensorflow/examples/speech_commands/freeze_test.py b/tensorflow/examples/speech_commands/freeze_test.py index c8de6c2152..0c7ca9bc01 100644 --- a/tensorflow/examples/speech_commands/freeze_test.py +++ b/tensorflow/examples/speech_commands/freeze_test.py @@ -25,7 +25,7 @@ from tensorflow.python.platform import test class FreezeTest(test.TestCase): def testCreateInferenceGraphWithMfcc(self): - with self.test_session() as sess: + with self.cached_session() as sess: freeze.create_inference_graph( wanted_words='a,b,c,d', sample_rate=16000, @@ -44,7 +44,7 @@ class FreezeTest(test.TestCase): self.assertEqual(1, ops.count('Mfcc')) def testCreateInferenceGraphWithoutMfcc(self): - with self.test_session() as sess: + with self.cached_session() as sess: freeze.create_inference_graph( wanted_words='a,b,c,d', sample_rate=16000, @@ -63,7 +63,7 @@ class FreezeTest(test.TestCase): self.assertEqual(0, ops.count('Mfcc')) def testFeatureBinCount(self): - with self.test_session() as sess: + with self.cached_session() as sess: freeze.create_inference_graph( wanted_words='a,b,c,d', sample_rate=16000, diff --git a/tensorflow/examples/speech_commands/input_data_test.py b/tensorflow/examples/speech_commands/input_data_test.py index 2e551be9a2..aa4e807779 100644 --- a/tensorflow/examples/speech_commands/input_data_test.py +++ b/tensorflow/examples/speech_commands/input_data_test.py @@ -32,7 +32,7 @@ from tensorflow.python.platform import test class InputDataTest(test.TestCase): def _getWavData(self): - with self.test_session() as sess: + with self.cached_session() as sess: sample_data = tf.zeros([32000, 2]) wav_encoder = contrib_audio.encode_wav(sample_data, 16000) wav_data = sess.run(wav_encoder) @@ -75,7 +75,7 @@ class InputDataTest(test.TestCase): self._saveTestWavFile(file_path, wav_data) model_settings = models.prepare_model_settings( 4, 16000, 1000, window_length_ms, 20, 40, preprocess) - with self.test_session() as sess: + with self.cached_session() as sess: audio_processor = input_data.AudioProcessor( "", wav_dir, 10, 10, ["a", "b"], 10, 10, model_settings, tmp_dir) result_data, result_labels = audio_processor.get_data( diff --git a/tensorflow/examples/speech_commands/label_wav_test.py b/tensorflow/examples/speech_commands/label_wav_test.py index 80ca774706..f0af2a4798 100644 --- a/tensorflow/examples/speech_commands/label_wav_test.py +++ b/tensorflow/examples/speech_commands/label_wav_test.py @@ -30,7 +30,7 @@ from tensorflow.python.platform import test class LabelWavTest(test.TestCase): def _getWavData(self): - with self.test_session() as sess: + with self.cached_session() as sess: sample_data = tf.zeros([1000, 2]) wav_encoder = contrib_audio.encode_wav(sample_data, 16000) wav_data = sess.run(wav_encoder) diff --git a/tensorflow/examples/speech_commands/models_test.py b/tensorflow/examples/speech_commands/models_test.py index 0c373967ed..04478c0962 100644 --- a/tensorflow/examples/speech_commands/models_test.py +++ b/tensorflow/examples/speech_commands/models_test.py @@ -49,7 +49,7 @@ class ModelsTest(test.TestCase): def testCreateModelConvTraining(self): model_settings = self._modelSettings() - with self.test_session() as sess: + with self.cached_session() as sess: fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]]) logits, dropout_prob = models.create_model(fingerprint_input, model_settings, "conv", True) @@ -60,7 +60,7 @@ class ModelsTest(test.TestCase): def testCreateModelConvInference(self): model_settings = self._modelSettings() - with self.test_session() as sess: + with self.cached_session() as sess: fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]]) logits = models.create_model(fingerprint_input, model_settings, "conv", False) @@ -69,7 +69,7 @@ class ModelsTest(test.TestCase): def testCreateModelLowLatencyConvTraining(self): model_settings = self._modelSettings() - with self.test_session() as sess: + with self.cached_session() as sess: fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]]) logits, dropout_prob = models.create_model( fingerprint_input, model_settings, "low_latency_conv", True) @@ -80,7 +80,7 @@ class ModelsTest(test.TestCase): def testCreateModelFullyConnectedTraining(self): model_settings = self._modelSettings() - with self.test_session() as sess: + with self.cached_session() as sess: fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]]) logits, dropout_prob = models.create_model( fingerprint_input, model_settings, "single_fc", True) @@ -91,7 +91,7 @@ class ModelsTest(test.TestCase): def testCreateModelBadArchitecture(self): model_settings = self._modelSettings() - with self.test_session(): + with self.cached_session(): fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]]) with self.assertRaises(Exception) as e: models.create_model(fingerprint_input, model_settings, @@ -100,7 +100,7 @@ class ModelsTest(test.TestCase): def testCreateModelTinyConvTraining(self): model_settings = self._modelSettings() - with self.test_session() as sess: + with self.cached_session() as sess: fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]]) logits, dropout_prob = models.create_model( fingerprint_input, model_settings, "tiny_conv", True) diff --git a/tensorflow/python/keras/backend_test.py b/tensorflow/python/keras/backend_test.py index 266af56611..2f271c4f50 100644 --- a/tensorflow/python/keras/backend_test.py +++ b/tensorflow/python/keras/backend_test.py @@ -279,7 +279,7 @@ class BackendUtilsTest(test.TestCase): keras.backend.get_session().run(fetches=[x, y]), [30., 40.]) def test_function_tf_run_options_with_run_metadata(self): - with self.test_session(): + with self.cached_session(): x_placeholder = keras.backend.placeholder(shape=()) y_placeholder = keras.backend.placeholder(shape=()) diff --git a/tensorflow/python/keras/callbacks_test.py b/tensorflow/python/keras/callbacks_test.py index 7675a6586f..b6fae19823 100644 --- a/tensorflow/python/keras/callbacks_test.py +++ b/tensorflow/python/keras/callbacks_test.py @@ -63,7 +63,7 @@ class KerasCallbacksTest(test.TestCase): if h5py is None: return # Skip test if models cannot be saved. - with self.test_session(): + with self.cached_session(): np.random.seed(1337) temp_dir = self.get_temp_dir() @@ -226,7 +226,7 @@ class KerasCallbacksTest(test.TestCase): mode='unknown') def test_EarlyStopping(self): - with self.test_session(): + with self.cached_session(): np.random.seed(123) (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data( train_samples=TRAIN_SAMPLES, @@ -265,7 +265,7 @@ class KerasCallbacksTest(test.TestCase): verbose=0) def test_EarlyStopping_reuse(self): - with self.test_session(): + with self.cached_session(): np.random.seed(1337) patience = 3 data = np.random.random((100, 1)) @@ -287,7 +287,7 @@ class KerasCallbacksTest(test.TestCase): assert len(hist.epoch) >= patience def test_EarlyStopping_with_baseline(self): - with self.test_session(): + with self.cached_session(): np.random.seed(1337) baseline = 0.5 (data, labels), _ = testing_utils.get_test_data( @@ -321,7 +321,7 @@ class KerasCallbacksTest(test.TestCase): monitor.on_epoch_end(0, logs={'loss': 0.}) def test_LearningRateScheduler(self): - with self.test_session(): + with self.cached_session(): np.random.seed(1337) (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data( train_samples=TRAIN_SAMPLES, @@ -368,7 +368,7 @@ class KerasCallbacksTest(test.TestCase): model.optimizer.lr)) - 0.01 / 4) < keras.backend.epsilon() def test_ReduceLROnPlateau(self): - with self.test_session(): + with self.cached_session(): np.random.seed(1337) (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data( train_samples=TRAIN_SAMPLES, @@ -470,7 +470,7 @@ class KerasCallbacksTest(test.TestCase): self.assertEqual(reduce_on_plateau.min_delta, 1e-13) def test_CSVLogger(self): - with self.test_session(): + with self.cached_session(): np.random.seed(1337) temp_dir = self.get_temp_dir() self.addCleanup(shutil.rmtree, temp_dir, ignore_errors=True) @@ -549,7 +549,7 @@ class KerasCallbacksTest(test.TestCase): tmpdir = self.get_temp_dir() self.addCleanup(shutil.rmtree, tmpdir, ignore_errors=True) - with self.test_session(): + with self.cached_session(): fp = os.path.join(tmpdir, 'test.csv') (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data( train_samples=TRAIN_SAMPLES, @@ -601,7 +601,7 @@ class KerasCallbacksTest(test.TestCase): assert 'nan' in values[-1], 'The last epoch was not logged.' def test_TerminateOnNaN(self): - with self.test_session(): + with self.cached_session(): np.random.seed(1337) (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data( train_samples=TRAIN_SAMPLES, @@ -666,7 +666,7 @@ class KerasCallbacksTest(test.TestCase): i %= max_batch_index # case: Sequential - with self.test_session(): + with self.cached_session(): model = keras.models.Sequential() model.add( keras.layers.Dense( @@ -743,7 +743,7 @@ class KerasCallbacksTest(test.TestCase): tmpdir = self.get_temp_dir() self.addCleanup(shutil.rmtree, tmpdir, ignore_errors=True) - with self.test_session(): + with self.cached_session(): filepath = os.path.join(tmpdir, 'logs') (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data( @@ -815,7 +815,7 @@ class KerasCallbacksTest(test.TestCase): tmpdir = self.get_temp_dir() self.addCleanup(shutil.rmtree, tmpdir, ignore_errors=True) - with self.test_session(): + with self.cached_session(): filepath = os.path.join(tmpdir, 'logs') (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data( @@ -925,7 +925,7 @@ class KerasCallbacksTest(test.TestCase): y_test = keras.utils.to_categorical(y_test) y_train = keras.utils.to_categorical(y_train) - with self.test_session(): + with self.cached_session(): model = keras.models.Sequential() model.add( keras.layers.Dense( @@ -969,7 +969,7 @@ class KerasCallbacksTest(test.TestCase): while True: yield x, y - with self.test_session(): + with self.cached_session(): model = testing_utils.get_small_sequential_mlp( num_hidden=10, num_classes=10, input_dim=100) model.compile( @@ -1011,7 +1011,7 @@ class KerasCallbacksTest(test.TestCase): os.name == 'nt', 'use_multiprocessing=True does not work on windows properly.') def test_LambdaCallback(self): - with self.test_session(): + with self.cached_session(): np.random.seed(1337) (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data( train_samples=TRAIN_SAMPLES, @@ -1055,7 +1055,7 @@ class KerasCallbacksTest(test.TestCase): assert not t.is_alive() def test_TensorBoard_with_ReduceLROnPlateau(self): - with self.test_session(): + with self.cached_session(): temp_dir = self.get_temp_dir() self.addCleanup(shutil.rmtree, temp_dir, ignore_errors=True) @@ -1194,7 +1194,7 @@ class KerasCallbacksTest(test.TestCase): def test_RemoteMonitorWithJsonPayload(self): if requests is None: self.skipTest('`requests` required to run this test') - with self.test_session(): + with self.cached_session(): (x_train, y_train), (x_test, y_test) = testing_utils.get_test_data( train_samples=TRAIN_SAMPLES, test_samples=TEST_SAMPLES, diff --git a/tensorflow/python/keras/model_subclassing_test.py b/tensorflow/python/keras/model_subclassing_test.py index 71c1987cee..3a1b00041f 100644 --- a/tensorflow/python/keras/model_subclassing_test.py +++ b/tensorflow/python/keras/model_subclassing_test.py @@ -463,7 +463,7 @@ class ModelSubclassingTest(test.TestCase): num_samples = 10 input_dim = 50 - with self.test_session(): + with self.cached_session(): model = SimpleTestModel(num_classes=num_classes, use_dp=True, use_bn=True) @@ -481,7 +481,7 @@ class ModelSubclassingTest(test.TestCase): num_samples = 10 input_dim = 50 - with self.test_session(): + with self.cached_session(): model = MultiIOTestModel(num_classes=num_classes, use_dp=True, use_bn=True) @@ -501,7 +501,7 @@ class ModelSubclassingTest(test.TestCase): num_samples = 10 input_dim = 50 - with self.test_session(): + with self.cached_session(): model = SimpleTestModel(num_classes=num_classes, use_dp=True, use_bn=True) model.compile(loss='mse', optimizer=RMSPropOptimizer(learning_rate=0.001)) @@ -521,7 +521,7 @@ class ModelSubclassingTest(test.TestCase): num_samples = 1000 input_dim = 50 - with self.test_session(): + with self.cached_session(): model = MultiIOTestModel(num_classes=num_classes, use_dp=True, use_bn=True) @@ -610,7 +610,7 @@ class ModelSubclassingTest(test.TestCase): def call(self, x): return self.bn(self.fc(x)) - with self.test_session(): + with self.cached_session(): model = TestModel1() x = array_ops.ones(shape=[100, 784], dtype='float32') @@ -631,7 +631,7 @@ class ModelSubclassingTest(test.TestCase): def call(self, x): return self.bn(self.fc(x)) - with self.test_session(): + with self.cached_session(): model = TestModel2() x = array_ops.ones(shape=[100, 784], dtype='float32') @@ -655,7 +655,7 @@ class ModelSubclassingTest(test.TestCase): def call(self, x): return self.bn(self.fc(x)) - with self.test_session(): + with self.cached_session(): model = TestModel3() x = array_ops.ones(shape=[100, 784], dtype='float32') diff --git a/tensorflow/python/keras/optimizers_test.py b/tensorflow/python/keras/optimizers_test.py index 9a68fc0e35..8d7493462e 100644 --- a/tensorflow/python/keras/optimizers_test.py +++ b/tensorflow/python/keras/optimizers_test.py @@ -85,23 +85,23 @@ def _test_optimizer(optimizer, target=0.75): class KerasOptimizersTest(test.TestCase): def test_sgd(self): - with self.test_session(): + with self.cached_session(): _test_optimizer(keras.optimizers.SGD(lr=0.01, momentum=0.9, nesterov=True)) def test_rmsprop(self): - with self.test_session(): + with self.cached_session(): _test_optimizer(keras.optimizers.RMSprop()) _test_optimizer(keras.optimizers.RMSprop(decay=1e-3)) def test_adagrad(self): - with self.test_session(): + with self.cached_session(): _test_optimizer(keras.optimizers.Adagrad()) _test_optimizer(keras.optimizers.Adagrad(decay=1e-3)) def test_adadelta(self): - with self.test_session(): + with self.cached_session(): _test_optimizer(keras.optimizers.Adadelta(), target=0.6) # Accuracy seems dependent on the initialization. Even adding tf.Print # nodes in the graph seemed to affect the initialization seed, and hence @@ -109,28 +109,28 @@ class KerasOptimizersTest(test.TestCase): _test_optimizer(keras.optimizers.Adadelta(decay=1e-3), target=0.4) def test_adam(self): - with self.test_session(): + with self.cached_session(): _test_optimizer(keras.optimizers.Adam()) _test_optimizer(keras.optimizers.Adam(decay=1e-3)) _test_optimizer(keras.optimizers.Adam(amsgrad=True)) def test_adamax(self): - with self.test_session(): + with self.cached_session(): _test_optimizer(keras.optimizers.Adamax()) _test_optimizer(keras.optimizers.Adamax(decay=1e-3)) def test_nadam(self): - with self.test_session(): + with self.cached_session(): _test_optimizer(keras.optimizers.Nadam()) def test_clipnorm(self): - with self.test_session(): + with self.cached_session(): _test_optimizer(keras.optimizers.SGD(lr=0.01, momentum=0.9, clipnorm=0.5)) def test_clipvalue(self): - with self.test_session(): + with self.cached_session(): _test_optimizer(keras.optimizers.SGD(lr=0.01, momentum=0.9, clipvalue=0.5)) @@ -158,7 +158,7 @@ class KerasOptimizersTest(test.TestCase): @test_util.run_in_graph_and_eager_modes def test_tfoptimizer_iterations(self): - with self.test_session(): + with self.cached_session(): optimizer = keras.optimizers.TFOptimizer(AdamOptimizer(0.01)) model = keras.models.Sequential() model.add(keras.layers.Dense( diff --git a/tensorflow/python/kernel_tests/boosted_trees/prediction_ops_test.py b/tensorflow/python/kernel_tests/boosted_trees/prediction_ops_test.py index 4e31b1ea2a..dee96102fb 100644 --- a/tensorflow/python/kernel_tests/boosted_trees/prediction_ops_test.py +++ b/tensorflow/python/kernel_tests/boosted_trees/prediction_ops_test.py @@ -30,7 +30,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase): def testCachedPredictionOnEmptyEnsemble(self): """Tests that prediction on a dummy ensemble does not fail.""" - with self.test_session() as session: + with self.cached_session() as session: # Create a dummy ensemble. tree_ensemble = boosted_trees_ops.TreeEnsemble( 'ensemble', serialized_proto='') @@ -63,7 +63,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase): def testNoCachedPredictionButTreeExists(self): """Tests that predictions are updated once trees are added.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -129,7 +129,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase): def testCachedPredictionIsCurrent(self): """Tests that prediction based on previous node in the tree works.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -201,7 +201,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase): def testCachedPredictionFromTheSameTree(self): """Tests that prediction based on previous node in the tree works.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -315,7 +315,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase): def testCachedPredictionFromPreviousTree(self): """Tests the predictions work when we have cache from previous trees.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -447,7 +447,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase): def testCachedPredictionFromTheSameTreeWithPostPrunedNodes(self): """Tests that prediction based on previous node in the tree works.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -577,7 +577,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase): def testCachedPredictionFromThePreviousTreeWithPostPrunedNodes(self): """Tests that prediction based on previous node in the tree works.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -722,7 +722,7 @@ class TrainingPredictionOpsTest(test_util.TensorFlowTestCase): def testCachedPredictionTheWholeTreeWasPruned(self): """Tests that prediction based on previous node in the tree works.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -794,7 +794,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase): def testPredictionOnEmptyEnsemble(self): """Tests that prediction on a empty ensemble does not fail.""" - with self.test_session() as session: + with self.cached_session() as session: # Create an empty ensemble. tree_ensemble = boosted_trees_ops.TreeEnsemble( 'ensemble', serialized_proto='') @@ -816,7 +816,7 @@ class PredictionOpsTest(test_util.TensorFlowTestCase): def testPredictionMultipleTree(self): """Tests the predictions work when we have multiple trees.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -930,7 +930,7 @@ class FeatureContribsOpsTest(test_util.TensorFlowTestCase): def testContribsMultipleTree(self): """Tests that the contribs work when we have multiple trees.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge( """ diff --git a/tensorflow/python/kernel_tests/boosted_trees/resource_ops_test.py b/tensorflow/python/kernel_tests/boosted_trees/resource_ops_test.py index d5f0c22d6e..65bb9ab55f 100644 --- a/tensorflow/python/kernel_tests/boosted_trees/resource_ops_test.py +++ b/tensorflow/python/kernel_tests/boosted_trees/resource_ops_test.py @@ -31,7 +31,7 @@ class ResourceOpsTest(test_util.TensorFlowTestCase): """Tests resource_ops.""" def testCreate(self): - with self.test_session(): + with self.cached_session(): ensemble = boosted_trees_ops.TreeEnsemble('ensemble') resources.initialize_resources(resources.shared_resources()).run() stamp_token = ensemble.get_stamp_token() @@ -44,7 +44,7 @@ class ResourceOpsTest(test_util.TensorFlowTestCase): self.assertAllEqual([0, 1], nodes_range.eval()) def testCreateWithProto(self): - with self.test_session(): + with self.cached_session(): ensemble_proto = boosted_trees_pb2.TreeEnsemble() text_format.Merge( """ @@ -161,7 +161,7 @@ class ResourceOpsTest(test_util.TensorFlowTestCase): self.assertAllEqual([16, 19], nodes_range.eval()) def testSerializeDeserialize(self): - with self.test_session(): + with self.cached_session(): # Initialize. ensemble = boosted_trees_ops.TreeEnsemble('ensemble', stamp_token=5) resources.initialize_resources(resources.shared_resources()).run() diff --git a/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py b/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py index 568e695fd5..09e9cfa3af 100644 --- a/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py +++ b/tensorflow/python/kernel_tests/boosted_trees/stats_ops_test.py @@ -30,7 +30,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): def testCalculateBestGainsWithoutRegularization(self): """Testing Gain calculation without any regularization.""" - with self.test_session() as sess: + with self.cached_session() as sess: max_splits = 7 node_id_range = [1, 3] # node 1 through 2 will be processed. stats_summary_list = [ @@ -78,7 +78,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): def testCalculateBestGainsWithL2(self): """Testing Gain calculation with L2.""" - with self.test_session() as sess: + with self.cached_session() as sess: max_splits = 7 node_id_range = [1, 3] # node 1 through 2 will be processed. stats_summary_list = [ @@ -126,7 +126,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): def testCalculateBestGainsWithL1(self): """Testing Gain calculation with L1.""" - with self.test_session() as sess: + with self.cached_session() as sess: max_splits = 7 node_id_range = [1, 3] # node 1 through 2 will be processed. stats_summary_list = [ @@ -177,7 +177,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): def testCalculateBestGainsWithTreeComplexity(self): """Testing Gain calculation with L2.""" - with self.test_session() as sess: + with self.cached_session() as sess: max_splits = 7 node_id_range = [1, 3] # node 1 through 2 will be processed. stats_summary_list = [ @@ -229,7 +229,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): def testCalculateBestGainsWithMinNodeWeight(self): """Testing Gain calculation without any regularization.""" - with self.test_session() as sess: + with self.cached_session() as sess: max_splits = 7 node_id_range = [1, 3] # node 1 through 2 will be processed. stats_summary_list = [ @@ -276,7 +276,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): def testCalculateBestGainsWithMinNodeWeightNoSplitOnFeturePossible(self): """Testing Gain calculation without any regularization.""" - with self.test_session() as sess: + with self.cached_session() as sess: max_splits = 7 node_id_range = [1, 3] # node 1 through 2 will be processed. stats_summary_list = [ @@ -329,7 +329,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): def testMakeStatsSummarySimple(self): """Simple test for MakeStatsSummary.""" - with self.test_session(): + with self.cached_session(): self.assertAllClose([[[[1., 5.], [2., 6.]], [[3., 7.], [4., 8.]]]], boosted_trees_ops.make_stats_summary( node_ids=[0, 0, 1, 1], @@ -341,7 +341,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): def testMakeStatsSummaryAccumulate(self): """Tests that Summary actually accumulates.""" - with self.test_session(): + with self.cached_session(): max_splits = 3 num_buckets = 4 node_ids = [1, 1, 2, 2, 1, 1, 2, 0] @@ -363,7 +363,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): def testMakeStatsSummaryMultipleFeatures(self): """Tests that MakeStatsSummary works for multiple features.""" - with self.test_session(): + with self.cached_session(): max_splits = 3 num_buckets = 4 node_ids = [1, 1, 2, 2, 1, 1, 2, 0] @@ -392,7 +392,7 @@ class StatsOpsTest(test_util.TensorFlowTestCase): result.eval()) def _verify_precision(self, length): - with self.test_session(): + with self.cached_session(): max_splits = 1 num_buckets = 1 node_ids = array_ops.fill([length], 0) diff --git a/tensorflow/python/kernel_tests/boosted_trees/training_ops_test.py b/tensorflow/python/kernel_tests/boosted_trees/training_ops_test.py index d55240297a..ea022820e4 100644 --- a/tensorflow/python/kernel_tests/boosted_trees/training_ops_test.py +++ b/tensorflow/python/kernel_tests/boosted_trees/training_ops_test.py @@ -32,7 +32,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testGrowWithEmptyEnsemble(self): """Test growing an empty ensemble.""" - with self.test_session() as session: + with self.cached_session() as session: # Create empty ensemble. tree_ensemble = boosted_trees_ops.TreeEnsemble('ensemble') tree_ensemble_handle = tree_ensemble.resource_handle @@ -141,7 +141,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testBiasCenteringOnEmptyEnsemble(self): """Test growing with bias centering on an empty ensemble.""" - with self.test_session() as session: + with self.cached_session() as session: # Create empty ensemble. tree_ensemble = boosted_trees_ops.TreeEnsemble('ensemble') tree_ensemble_handle = tree_ensemble.resource_handle @@ -184,7 +184,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testGrowExistingEnsembleTreeNotFinalized(self): """Test growing an existing ensemble with the last tree not finalized.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -368,7 +368,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testGrowExistingEnsembleTreeFinalized(self): """Test growing an existing ensemble with the last tree finalized.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -517,7 +517,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testPrePruning(self): """Test growing an existing ensemble with pre-pruning.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge(""" trees { @@ -673,7 +673,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testMetadataWhenCantSplitDueToEmptySplits(self): """Test that the metadata is updated even though we can't split.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge( """ @@ -784,7 +784,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testMetadataWhenCantSplitDuePrePruning(self): """Test metadata is updated correctly when no split due to prepruning.""" - with self.test_session() as session: + with self.cached_session() as session: tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() text_format.Merge( """ @@ -919,7 +919,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testPostPruningOfSomeNodes(self): """Test growing an ensemble with post-pruning.""" - with self.test_session() as session: + with self.cached_session() as session: # Create empty ensemble. tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() tree_ensemble = boosted_trees_ops.TreeEnsemble( @@ -1253,7 +1253,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testPostPruningOfAllNodes(self): """Test growing an ensemble with post-pruning, with all nodes are pruned.""" - with self.test_session() as session: + with self.cached_session() as session: # Create empty ensemble. # Create empty ensemble. tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() @@ -1436,7 +1436,7 @@ class UpdateTreeEnsembleOpTest(test_util.TensorFlowTestCase): def testPostPruningChangesNothing(self): """Test growing an ensemble with post-pruning with all gains >0.""" - with self.test_session() as session: + with self.cached_session() as session: # Create empty ensemble. tree_ensemble_config = boosted_trees_pb2.TreeEnsemble() tree_ensemble = boosted_trees_ops.TreeEnsemble( |