diff options
| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2018-09-10 14:36:35 -0700 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-09-10 14:53:04 -0700 |
| commit | f1cc58bb4144de61a693076d8ff8a26b2644ebbb (patch) | |
| tree | a8c68e517f1819cc84d06981d69fb6162f670987 /tensorflow/python/training | |
| parent | 890e16594a005fe703a5556530b0dc3e6527fa47 (diff) | |
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: 212336352
Diffstat (limited to 'tensorflow/python/training')
25 files changed, 259 insertions, 259 deletions
diff --git a/tensorflow/python/training/adadelta_test.py b/tensorflow/python/training/adadelta_test.py index 2678016d24..a14ac895ac 100644 --- a/tensorflow/python/training/adadelta_test.py +++ b/tensorflow/python/training/adadelta_test.py @@ -155,7 +155,7 @@ class AdadeltaOptimizerTest(test.TestCase): rtol=1e-5) def testBasic(self): - with self.test_session(): + with self.cached_session(): self.doTestBasic(use_resource=False) @test_util.run_in_graph_and_eager_modes(reset_test=True) @@ -168,7 +168,7 @@ class AdadeltaOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) diff --git a/tensorflow/python/training/adagrad_da_test.py b/tensorflow/python/training/adagrad_da_test.py index c3a242a75e..00801be3b4 100644 --- a/tensorflow/python/training/adagrad_da_test.py +++ b/tensorflow/python/training/adagrad_da_test.py @@ -34,7 +34,7 @@ class AdagradDAOptimizerTest(test.TestCase): def doTestAdagradDAwithoutRegularizationBasic1(self, use_resource=False): for dtype in [dtypes.float64, dtypes.float32]: - with self.test_session() as sess: + with self.cached_session() as sess: global_step = variables.Variable(0, dtype=dtypes.int64) if use_resource: var0 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype) @@ -81,7 +81,7 @@ class AdagradDAOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariable(self): for dtype in [dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) global_step = resource_variable_ops.ResourceVariable( 0, dtype=dtypes.int64) @@ -101,7 +101,7 @@ class AdagradDAOptimizerTest(test.TestCase): def testAdagradDAwithoutRegularizationBasic2(self): for dtype in [dtypes.float64, dtypes.float32]: - with self.test_session() as sess: + with self.cached_session() as sess: global_step = variables.Variable(0, dtype=dtypes.int64) var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([4.0, 3.0], dtype=dtype) @@ -133,7 +133,7 @@ class AdagradDAOptimizerTest(test.TestCase): def testAdagradDAWithL1(self): for dtype in [dtypes.float64, dtypes.float32]: - with self.test_session() as sess: + with self.cached_session() as sess: global_step = variables.Variable(0, dtype=dtypes.int64) var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([4.0, 3.0], dtype=dtype) @@ -165,7 +165,7 @@ class AdagradDAOptimizerTest(test.TestCase): def testAdagradDAWithL1_L2(self): for dtype in [dtypes.float64, dtypes.float32]: - with self.test_session() as sess: + with self.cached_session() as sess: global_step = variables.Variable(0, dtype=dtypes.int64) var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([4.0, 3.0], dtype=dtype) diff --git a/tensorflow/python/training/adagrad_test.py b/tensorflow/python/training/adagrad_test.py index 4e634fff84..7caf01f64d 100644 --- a/tensorflow/python/training/adagrad_test.py +++ b/tensorflow/python/training/adagrad_test.py @@ -98,7 +98,7 @@ class AdagradOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable( [[1.0, 2.0], [3.0, 4.0]], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) @@ -117,7 +117,7 @@ class AdagradOptimizerTest(test.TestCase): def testTensorLearningRate(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -141,7 +141,7 @@ class AdagradOptimizerTest(test.TestCase): def testSparseBasic(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([[1.0], [2.0]], dtype=dtype) var1 = variables.Variable([[3.0], [4.0]], dtype=dtype) grads0 = ops.IndexedSlices( @@ -172,7 +172,7 @@ class AdagradOptimizerTest(test.TestCase): def testSparseRepeatedIndices(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): repeated_index_update_var = variables.Variable( [[1.0], [2.0]], dtype=dtype) aggregated_update_var = variables.Variable( @@ -202,7 +202,7 @@ class AdagradOptimizerTest(test.TestCase): def testSparseRepeatedIndicesResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var_repeated = resource_variable_ops.ResourceVariable( [1.0, 2.0], dtype=dtype) loss_repeated = math_ops.reduce_sum( @@ -226,7 +226,7 @@ class AdagradOptimizerTest(test.TestCase): def testSparseStability(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): shape = [1, 6] var0 = variables.Variable( [[ @@ -262,7 +262,7 @@ class AdagradOptimizerTest(test.TestCase): def testSharing(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -295,7 +295,7 @@ class AdagradOptimizerTest(test.TestCase): np.array([2.715679168701172, 3.715679168701172]), var1.eval()) def testDynamicShapeVariable_Ok(self): - with self.test_session(): + with self.cached_session(): v = variable_scope.get_variable("v", initializer=constant_op.constant(1.), validate_shape=False) self.assertFalse(v.shape.is_fully_defined()) diff --git a/tensorflow/python/training/adam_test.py b/tensorflow/python/training/adam_test.py index 778c672077..48db6e3733 100644 --- a/tensorflow/python/training/adam_test.py +++ b/tensorflow/python/training/adam_test.py @@ -56,7 +56,7 @@ class AdamOptimizerTest(test.TestCase): def doTestSparse(self, use_resource=False): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): # Initialize variables for numpy implementation. m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0 var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype) @@ -122,7 +122,7 @@ class AdamOptimizerTest(test.TestCase): def testSparseRepeatedIndices(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): repeated_index_update_var = variables.Variable( [[1.0], [2.0]], dtype=dtype) aggregated_update_var = variables.Variable( @@ -224,7 +224,7 @@ class AdamOptimizerTest(test.TestCase): opt.get_slot(var=var0, name="m").name) def testBasic(self): - with self.test_session(): + with self.cached_session(): self.doTestBasic(use_resource=False) @test_util.run_in_graph_and_eager_modes(reset_test=True) @@ -237,7 +237,7 @@ class AdamOptimizerTest(test.TestCase): def testTensorLearningRate(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): # Initialize variables for numpy implementation. m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0 var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype) @@ -274,7 +274,7 @@ class AdamOptimizerTest(test.TestCase): def testSharing(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): # Initialize variables for numpy implementation. m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0 var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype) diff --git a/tensorflow/python/training/basic_session_run_hooks_test.py b/tensorflow/python/training/basic_session_run_hooks_test.py index fe8a3e9062..2d469634e0 100644 --- a/tensorflow/python/training/basic_session_run_hooks_test.py +++ b/tensorflow/python/training/basic_session_run_hooks_test.py @@ -1145,7 +1145,7 @@ class SummarySaverHookTest(test.TestCase): summary_writer=self.summary_writer, summary_op=self.summary_op) - with self.test_session() as sess: + with self.cached_session() as sess: hook.begin() sess.run(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) @@ -1177,7 +1177,7 @@ class SummarySaverHookTest(test.TestCase): summary_writer=self.summary_writer, summary_op=[self.summary_op, self.summary_op2]) - with self.test_session() as sess: + with self.cached_session() as sess: hook.begin() sess.run(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) @@ -1205,7 +1205,7 @@ class SummarySaverHookTest(test.TestCase): summary_writer=self.summary_writer, summary_op=self.summary_op) - with self.test_session() as sess: + with self.cached_session() as sess: hook.begin() sess.run(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) @@ -1240,7 +1240,7 @@ class SummarySaverHookTest(test.TestCase): summary_writer=self.summary_writer, summary_op=self.summary_op) - with self.test_session() as sess: + with self.cached_session() as sess: hook.begin() sess.run(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) @@ -1388,7 +1388,7 @@ class ResourceSummarySaverHookTest(test.TestCase): summary_writer=self.summary_writer, summary_op=self.summary_op) - with self.test_session() as sess: + with self.cached_session() as sess: hook.begin() sess.run(variables_lib.global_variables_initializer()) mon_sess = monitored_session._HookedSession(sess, [hook]) diff --git a/tensorflow/python/training/checkpoint_management_test.py b/tensorflow/python/training/checkpoint_management_test.py index 8ef5048299..3a061bcb35 100644 --- a/tensorflow/python/training/checkpoint_management_test.py +++ b/tensorflow/python/training/checkpoint_management_test.py @@ -73,7 +73,7 @@ class LatestCheckpointWithRelativePaths(test.TestCase): # Collides with the default name of the checkpoint state file. filepath = os.path.join(traindir, "checkpoint") - with self.test_session() as sess: + with self.cached_session() as sess: unused_a = variables.Variable(0.0) # So that Saver saves something. variables.global_variables_initializer().run() @@ -113,7 +113,7 @@ class LatestCheckpointWithRelativePaths(test.TestCase): filename = "snapshot" filepath = os.path.join(traindir, filename) - with self.test_session() as sess: + with self.cached_session() as sess: # Build a simple graph. v0 = variables.Variable(0.0) inc = v0.assign_add(1.0) @@ -128,7 +128,7 @@ class LatestCheckpointWithRelativePaths(test.TestCase): inc.eval() save.save(sess, filepath, global_step=2) - with self.test_session() as sess: + with self.cached_session() as sess: # Build a new graph with different initialization. v0 = variables.Variable(-1.0) diff --git a/tensorflow/python/training/checkpoint_ops_test.py b/tensorflow/python/training/checkpoint_ops_test.py index 00611de862..dde8431497 100644 --- a/tensorflow/python/training/checkpoint_ops_test.py +++ b/tensorflow/python/training/checkpoint_ops_test.py @@ -43,7 +43,7 @@ class LoadAndRemapWrappersTest(test.TestCase): # 0., 1., ..., 79. reshaped into [5, 16]. initializer = init_ops.constant_initializer( np.reshape(np.linspace(0.0, 79, 5 * 16), (5, 16))) - with self.test_session() as sess: + with self.cached_session() as sess: with variable_scope.variable_scope('some_scope'): variable_scope.get_variable(name='embeddings', shape=[5, 16], initializer=initializer) @@ -114,7 +114,7 @@ class LoadAndRemapWrappersTest(test.TestCase): ], axis=1) - with self.test_session(): + with self.cached_session(): self.assertAllClose(expected_remapped_matrix, remapped_matrix.eval()) def test_load_and_remap_output_layer_weight_initializer_linear(self): @@ -150,7 +150,7 @@ class LoadAndRemapWrappersTest(test.TestCase): initializer=loading_initializer, partitioner=partitioned_variables.fixed_size_partitioner(2)) - with self.test_session(): + with self.cached_session(): variables.global_variables_initializer().run() self.assertAllClose(expected_remapped_matrix, remapped_matrix.as_tensor().eval()) @@ -184,7 +184,7 @@ class LoadAndRemapWrappersTest(test.TestCase): initializer=loading_initializer, partitioner=partitioned_variables.fixed_size_partitioner(2)) - with self.test_session(): + with self.cached_session(): variables.global_variables_initializer().run() self.assertAllClose(expected_remapped_matrix, remapped_matrix.as_tensor().eval()) @@ -222,7 +222,7 @@ class LoadAndRemapWrappersTest(test.TestCase): initializer=loading_initializer, partitioner=partitioned_variables.fixed_size_partitioner(2)) - with self.test_session(): + with self.cached_session(): variables.global_variables_initializer().run() self.assertAllClose(expected_remapped_matrix, remapped_matrix.as_tensor().eval()) @@ -258,7 +258,7 @@ class LoadAndRemapWrappersTest(test.TestCase): initializer=loading_initializer, partitioner=partitioned_variables.fixed_size_partitioner(2)) - with self.test_session(): + with self.cached_session(): variables.global_variables_initializer().run() self.assertAllClose(expected_remapped_matrix, remapped_matrix.as_tensor().eval()) @@ -292,7 +292,7 @@ class LoadAndRemapWrappersTest(test.TestCase): initializer=embedding_loading_initializer, partitioner=partitioned_variables.fixed_size_partitioner(2)) - with self.test_session(): + with self.cached_session(): variables.global_variables_initializer().run() self.assertAllClose(expected_remapped_embeddings, remapped_embeddings.as_tensor().eval()) @@ -338,7 +338,7 @@ class LoadAndRemapWrappersTest(test.TestCase): initializer=embedding_loading_initializer, partitioner=partitioned_variables.fixed_size_partitioner(2)) - with self.test_session(): + with self.cached_session(): variables.global_variables_initializer().run() self.assertAllClose(expected_remapped_embeddings, remapped_embeddings.as_tensor().eval()) @@ -376,7 +376,7 @@ class LoadAndRemapWrappersTest(test.TestCase): initializer=embedding_loading_initializer, partitioner=partitioned_variables.fixed_size_partitioner(2)) - with self.test_session(): + with self.cached_session(): variables.global_variables_initializer().run() self.assertAllClose(expected_remapped_embeddings, remapped_embeddings.as_tensor().eval()) diff --git a/tensorflow/python/training/checkpoint_utils_test.py b/tensorflow/python/training/checkpoint_utils_test.py index 1aab16338a..61dcbdb2b8 100644 --- a/tensorflow/python/training/checkpoint_utils_test.py +++ b/tensorflow/python/training/checkpoint_utils_test.py @@ -84,7 +84,7 @@ class CheckpointsTest(test.TestCase): def testNoTensor(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: _, _, _, _ = _create_checkpoints(session, checkpoint_dir) with self.assertRaises(errors_impl.OpError): self.assertAllEqual( @@ -92,7 +92,7 @@ class CheckpointsTest(test.TestCase): def testGetTensor(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: v1, v2, v3, v4 = _create_checkpoints(session, checkpoint_dir) self.assertAllEqual( checkpoint_utils.load_variable(checkpoint_dir, "var1"), v1) @@ -105,7 +105,7 @@ class CheckpointsTest(test.TestCase): def testGetAllVariables(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: _create_checkpoints(session, checkpoint_dir) self.assertEqual( checkpoint_utils.list_variables(checkpoint_dir), @@ -114,7 +114,7 @@ class CheckpointsTest(test.TestCase): def testInitFromCheckpoint(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: v1, v2, v3, v4 = _create_checkpoints(session, checkpoint_dir) # New graph and session. @@ -148,7 +148,7 @@ class CheckpointsTest(test.TestCase): def testInitialValueComesFromCheckpoint(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: v1, _, _, _ = _create_checkpoints(session, checkpoint_dir) # New graph and session. @@ -178,7 +178,7 @@ class CheckpointsTest(test.TestCase): def testInitWithScopeDoesNotCaptureSuffixes(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: _, _, _, v4 = _create_checkpoints(session, checkpoint_dir) with ops.Graph().as_default() as g: @@ -197,7 +197,7 @@ class CheckpointsTest(test.TestCase): def testRestoreRunsOnSameDevice(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: _create_checkpoints(session, checkpoint_dir) with ops.Graph().as_default(): @@ -213,7 +213,7 @@ class CheckpointsTest(test.TestCase): def testInitFromRootCheckpoint(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: v1, v2, v3, v4 = _create_checkpoints(session, checkpoint_dir) # New graph and session. @@ -237,7 +237,7 @@ class CheckpointsTest(test.TestCase): def testInitToRootCheckpoint(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: v1, v2, v3, v4 = _create_checkpoints(session, checkpoint_dir) # New graph and session. @@ -260,7 +260,7 @@ class CheckpointsTest(test.TestCase): def testInitFromPartitionVar(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: v1 = _create_partition_checkpoints(session, checkpoint_dir) # New graph and session. @@ -322,7 +322,7 @@ class CheckpointsTest(test.TestCase): def testInitFromCheckpointMissing(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: _, _, _, _ = _create_checkpoints(session, checkpoint_dir) # New graph and session. @@ -367,7 +367,7 @@ class CheckpointsTest(test.TestCase): def testNoAdditionalReadOpsForResourceVariables(self): checkpoint_dir = self.get_temp_dir() - with self.test_session() as session: + with self.cached_session() as session: v1, _, _, _ = _create_checkpoints(session, checkpoint_dir) # New graph and session. diff --git a/tensorflow/python/training/ftrl_test.py b/tensorflow/python/training/ftrl_test.py index 76ca5b45c9..09d6fe36d3 100644 --- a/tensorflow/python/training/ftrl_test.py +++ b/tensorflow/python/training/ftrl_test.py @@ -37,7 +37,7 @@ class FtrlOptimizerTest(test.TestCase): def doTestFtrlwithoutRegularization(self, use_resource=False): for dtype in [dtypes.half, dtypes.float32]: - with self.test_session() as sess: + with self.cached_session() as sess: if use_resource: var0 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype) var1 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype) @@ -76,7 +76,7 @@ class FtrlOptimizerTest(test.TestCase): def testFtrlwithoutRegularization2(self): for dtype in [dtypes.half, dtypes.float32]: - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([4.0, 3.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.2], dtype=dtype) @@ -105,7 +105,7 @@ class FtrlOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) @@ -121,7 +121,7 @@ class FtrlOptimizerTest(test.TestCase): def testFtrlWithL1(self): for dtype in [dtypes.half, dtypes.float32]: - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([4.0, 3.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.2], dtype=dtype) @@ -150,7 +150,7 @@ class FtrlOptimizerTest(test.TestCase): def testFtrlWithL1_L2(self): for dtype in [dtypes.half, dtypes.float32]: - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([4.0, 3.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.2], dtype=dtype) @@ -186,7 +186,7 @@ class FtrlOptimizerTest(test.TestCase): weights will tend to have smaller magnitudes with this parameter set. """ for dtype in [dtypes.half, dtypes.float32]: - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([4.0, 3.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.2], dtype=dtype) @@ -335,7 +335,7 @@ class FtrlOptimizerTest(test.TestCase): # FTRL-Proximal performs same updates as Adagrad or GradientDescent. def testEquivAdagradwithoutRegularization(self): for dtype in [dtypes.half, dtypes.float32]: - with self.test_session(): + with self.cached_session(): val0, val1 = self.applyOptimizer( ftrl.FtrlOptimizer( 3.0, @@ -346,7 +346,7 @@ class FtrlOptimizerTest(test.TestCase): l2_regularization_strength=0.0), dtype) - with self.test_session(): + with self.cached_session(): val2, val3 = self.applyOptimizer( adagrad.AdagradOptimizer(3.0, initial_accumulator_value=0.1), dtype) @@ -355,7 +355,7 @@ class FtrlOptimizerTest(test.TestCase): def testEquivSparseAdagradwithoutRegularization(self): for dtype in [dtypes.half, dtypes.float32]: - with self.test_session(): + with self.cached_session(): val0, val1 = self.applyOptimizer( ftrl.FtrlOptimizer( 3.0, @@ -367,7 +367,7 @@ class FtrlOptimizerTest(test.TestCase): dtype, is_sparse=True) - with self.test_session(): + with self.cached_session(): val2, val3 = self.applyOptimizer( adagrad.AdagradOptimizer(3.0, initial_accumulator_value=0.1), dtype, @@ -378,7 +378,7 @@ class FtrlOptimizerTest(test.TestCase): def testEquivSparseGradientDescentwithoutRegularization(self): for dtype in [dtypes.half, dtypes.float32]: - with self.test_session(): + with self.cached_session(): val0, val1 = self.applyOptimizer( ftrl.FtrlOptimizer( 3.0, @@ -390,7 +390,7 @@ class FtrlOptimizerTest(test.TestCase): dtype, is_sparse=True) - with self.test_session(): + with self.cached_session(): val2, val3 = self.applyOptimizer( gradient_descent.GradientDescentOptimizer(3.0), dtype, @@ -401,7 +401,7 @@ class FtrlOptimizerTest(test.TestCase): def testEquivGradientDescentwithoutRegularization(self): for dtype in [dtypes.half, dtypes.float32]: - with self.test_session(): + with self.cached_session(): val0, val1 = self.applyOptimizer( ftrl.FtrlOptimizer( 3.0, @@ -412,7 +412,7 @@ class FtrlOptimizerTest(test.TestCase): l2_regularization_strength=0.0), dtype) - with self.test_session(): + with self.cached_session(): val2, val3 = self.applyOptimizer( gradient_descent.GradientDescentOptimizer(3.0), dtype) diff --git a/tensorflow/python/training/gradient_descent_test.py b/tensorflow/python/training/gradient_descent_test.py index b304e92421..56d82a5b88 100644 --- a/tensorflow/python/training/gradient_descent_test.py +++ b/tensorflow/python/training/gradient_descent_test.py @@ -37,7 +37,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testBasic(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -60,7 +60,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testBasicResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype) var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -85,7 +85,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testBasicCallableParams(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype) var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -111,7 +111,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testMinimizeResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) var1 = resource_variable_ops.ResourceVariable([3.0], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) @@ -137,7 +137,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) var1 = resource_variable_ops.ResourceVariable([3.0], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) @@ -164,7 +164,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testTensorLearningRate(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -186,7 +186,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testGradWrtRef(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): opt = gradient_descent.GradientDescentOptimizer(3.0) values = [1.0, 3.0] vars_ = [variables.Variable([v], dtype=dtype) for v in values] @@ -197,7 +197,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testWithGlobalStep(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): global_step = variables.Variable(0, trainable=False) var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) @@ -220,7 +220,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testSparseBasic(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([[1.0], [2.0]], dtype=dtype) var1 = variables.Variable([[3.0], [4.0]], dtype=dtype) grads0 = ops.IndexedSlices( diff --git a/tensorflow/python/training/input_test.py b/tensorflow/python/training/input_test.py index 1b1e89cb26..a9b05dcc73 100644 --- a/tensorflow/python/training/input_test.py +++ b/tensorflow/python/training/input_test.py @@ -51,7 +51,7 @@ class MatchFilenamesOnceTest(test_lib.TestCase): for name in additional: open(name, "w").write("Some contents") filenames = list(set(filenames + additional)) - with self.test_session(): + with self.cached_session(): star = inp.match_filenames_once(os.path.join(self.get_temp_dir(), "*")) question = inp.match_filenames_once( os.path.join(self.get_temp_dir(), "match_filenames.?")) @@ -66,7 +66,7 @@ class MatchFilenamesOnceTest(test_lib.TestCase): class LimitEpochsTest(test_lib.TestCase): def testNoLimit(self): - with self.test_session(): + with self.cached_session(): seven = constant_op.constant(7) seven_forever = inp.limit_epochs(seven) variables.local_variables_initializer().run() @@ -74,7 +74,7 @@ class LimitEpochsTest(test_lib.TestCase): self.assertEqual(7, seven_forever.eval()) def testLimit(self): - with self.test_session(): + with self.cached_session(): love_me = constant_op.constant("Love Me") love_me_two_times = inp.limit_epochs(love_me, num_epochs=2) variables.global_variables_initializer().run() @@ -88,7 +88,7 @@ class LimitEpochsTest(test_lib.TestCase): class InputProducerTest(test_lib.TestCase): def testNoShuffle(self): - with self.test_session(): + with self.cached_session(): input_tensor = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]] @@ -111,7 +111,7 @@ class InputProducerTest(test_lib.TestCase): thread.join() def testNoShapeInference(self): - with self.test_session(): + with self.cached_session(): # Disable shape inference for the input. input_value = [[1, 2, 3, 4], [5, 6, 7, 8], @@ -144,7 +144,7 @@ class InputProducerTest(test_lib.TestCase): class StringInputProducerTest(test_lib.TestCase): def testNoShuffle(self): - with self.test_session(): + with self.cached_session(): strings = [b"to", b"be", b"or", b"not", b"to", b"be"] num_epochs = 3 queue = inp.string_input_producer( @@ -166,7 +166,7 @@ class StringInputProducerTest(test_lib.TestCase): thread.join() def testShuffle(self): - with self.test_session(): + with self.cached_session(): strings = [b"a", b"b", b"c"] num_epochs = 600 queue = inp.string_input_producer( @@ -206,7 +206,7 @@ class StringInputProducerTest(test_lib.TestCase): def testNullStringPython(self): # Graph-construction time check for empty string list: - with self.test_session(): + with self.cached_session(): with self.assertRaises(ValueError): _ = inp.string_input_producer([]) @@ -214,7 +214,7 @@ class StringInputProducerTest(test_lib.TestCase): # Runtime check for empty string list. This is slightly oblique: # The queue runner should die with an assertion error on the null # input tensor, causing the dequeue to fail with an OutOfRangeError. - with self.test_session(): + with self.cached_session(): coord = coordinator.Coordinator() queue = inp.string_input_producer( constant_op.constant( @@ -230,7 +230,7 @@ class StringInputProducerTest(test_lib.TestCase): thread.join() def testSharedName(self): - with self.test_session(): + with self.cached_session(): strings = [b"to", b"be", b"or", b"not", b"to", b"be"] queue = inp.string_input_producer( strings, shared_name="SHARED_NAME_XYZ", name="Q") @@ -238,7 +238,7 @@ class StringInputProducerTest(test_lib.TestCase): queue.queue_ref.op.node_def.attr["shared_name"]) def testConstructionRace(self): - with self.test_session() as sess: + with self.cached_session() as sess: strings = [b"to", b"be", b"or", b"not", b"to", b"be"] queue = inp.string_input_producer(strings, shuffle=False) coord = coordinator.Coordinator() @@ -260,7 +260,7 @@ class StringInputProducerTest(test_lib.TestCase): class RangeInputProducerTest(test_lib.TestCase): def testNoShuffle(self): - with self.test_session(): + with self.cached_session(): num_epochs = 3 range_size = 5 queue = inp.range_input_producer( @@ -282,7 +282,7 @@ class RangeInputProducerTest(test_lib.TestCase): thread.join() def testShuffle(self): - with self.test_session(): + with self.cached_session(): num_epochs = 200 range_size = 2 queue = inp.range_input_producer( @@ -321,7 +321,7 @@ class RangeInputProducerTest(test_lib.TestCase): thread.join() def testSharedName(self): - with self.test_session(): + with self.cached_session(): range_size = 5 queue = inp.range_input_producer( range_size, shared_name="SHARED_NAME_XYZ", name="Q") @@ -332,7 +332,7 @@ class RangeInputProducerTest(test_lib.TestCase): class SliceInputProducerTest(test_lib.TestCase): def testNoShuffle(self): - with self.test_session() as sess: + with self.cached_session() as sess: num_epochs = 3 source_strings = [b"Alpha", b"Beta", b"Delta", b"Gamma"] source_ints = [2, 3, 5, 7] @@ -356,7 +356,7 @@ class SliceInputProducerTest(test_lib.TestCase): thread.join() def testShuffle(self): - with self.test_session() as sess: + with self.cached_session() as sess: num_epochs = 1200 source_strings = ["A", "B", "D", "G"] source_ints = [7, 3, 5, 2] @@ -400,7 +400,7 @@ class SliceInputProducerTest(test_lib.TestCase): thread.join() def testSharedName(self): - with self.test_session(): + with self.cached_session(): source_strings = ["A", "B", "D", "G"] source_ints = [7, 3, 5, 2] slices = inp.slice_input_producer( @@ -440,7 +440,7 @@ class DictHelperTest(test_lib.TestCase): class BatchTest(test_lib.TestCase): def _testOneThreadHelper(self, use_dict): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -500,7 +500,7 @@ class BatchTest(test_lib.TestCase): def testUint32DataTypes(self): values = constant_op.constant([0, 1, 2, 3, 4, 5], dtype=dtypes.uint32) batched = inp.batch([values], batch_size=2) - with self.test_session() as sess: + with self.cached_session() as sess: coord = coordinator.Coordinator() threads = queue_runner_impl.start_queue_runners(sess=sess, coord=coord) sess.run(batched) @@ -511,7 +511,7 @@ class BatchTest(test_lib.TestCase): def testUint64DataTypes(self): values = constant_op.constant([0, 1, 2, 3, 4, 5], dtype=dtypes.uint64) batched = inp.batch([values], batch_size=2) - with self.test_session() as sess: + with self.cached_session() as sess: coord = coordinator.Coordinator() threads = queue_runner_impl.start_queue_runners(sess=sess, coord=coord) sess.run(batched) @@ -520,7 +520,7 @@ class BatchTest(test_lib.TestCase): thread.join() def testOneThreadDynamicPad(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -550,7 +550,7 @@ class BatchTest(test_lib.TestCase): thread.join() def testOneThreadEnqueueMany(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -585,7 +585,7 @@ class BatchTest(test_lib.TestCase): thread.join() def testManyThreads(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -625,7 +625,7 @@ class BatchTest(test_lib.TestCase): thread.join() def testOneThreadSmallerBatch(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 extra_elements = 5 @@ -682,7 +682,7 @@ class BatchTest(test_lib.TestCase): thread.join() def testManyThreadsSmallerBatch(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 extra_elements = 5 @@ -737,7 +737,7 @@ class BatchTest(test_lib.TestCase): thread.join() def testSharedName(self): - with self.test_session(): + with self.cached_session(): batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -754,7 +754,7 @@ class BatchTest(test_lib.TestCase): batched[0].op.inputs[0].op.node_def.attr["shared_name"]) def testCannotInferRankError(self): - with self.test_session(): + with self.cached_session(): x = array_ops.placeholder(dtype=dtypes.int64) with self.assertRaisesRegexp(ValueError, "Cannot infer Tensor's rank"): inp.batch([x], batch_size=2) @@ -797,7 +797,7 @@ class BatchTest(test_lib.TestCase): def _testKeepInputHelper(self, num_threads, enqueue_many, keep_input_vector=False): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 5 num_batches = 4 examples = variables.Variable(0) @@ -934,7 +934,7 @@ class BatchTest(test_lib.TestCase): batched = inp.maybe_batch( [sparse_t], keep_input=keep, batch_size=1, enqueue_many=True) - with self.test_session(): + with self.cached_session(): coord = coordinator.Coordinator() threads = queue_runner_impl.start_queue_runners(coord=coord) @@ -952,7 +952,7 @@ class BatchTest(test_lib.TestCase): class BatchJoinTest(test_lib.TestCase): def _testTwoThreadsHelper(self, use_dict): - with self.test_session() as sess: + with self.cached_session() as sess: # Two threads, the first generates (0..69, "a"). num_a = 70 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -1069,7 +1069,7 @@ class BatchJoinTest(test_lib.TestCase): batch_size=8) def DISABLED_testTwoThreadsDynamicPad(self): - with self.test_session() as sess: + with self.cached_session() as sess: # Two threads, the first generates (0..69, ["a"] * 1..70). num_a = 70 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -1144,7 +1144,7 @@ class BatchJoinTest(test_lib.TestCase): thread.join() def DISABLED_testTwoThreadsSmallerBatch(self): - with self.test_session() as sess: + with self.cached_session() as sess: extra_elements = 2 # Two threads, the first generates (0..69, "a"). num_a = 70 + extra_elements @@ -1243,7 +1243,7 @@ class BatchJoinTest(test_lib.TestCase): thread.join() def DISABLED_testTwoThreadsDynamicPadSmallerBatch(self): - with self.test_session() as sess: + with self.cached_session() as sess: extra_elements = 2 # Two threads, the first generates (0..69, ["a"] * 1..70). num_a = 70 + extra_elements @@ -1338,7 +1338,7 @@ class BatchJoinTest(test_lib.TestCase): thread.join() def testSharedName(self): - with self.test_session(): + with self.cached_session(): batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -1360,7 +1360,7 @@ class BatchJoinTest(test_lib.TestCase): batched[0].op.inputs[0].op.node_def.attr["shared_name"]) def testCannotInferRankError(self): - with self.test_session(): + with self.cached_session(): x = array_ops.placeholder(dtype=dtypes.int64) with self.assertRaisesRegexp(ValueError, "Cannot infer Tensor's rank"): inp.batch_join([[x]], batch_size=2) @@ -1371,7 +1371,7 @@ class BatchJoinTest(test_lib.TestCase): def _testKeepInputHelper(self, num_threads, enqueue_many, keep_input_vector=False): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 5 num_batches = 4 examples = variables.Variable(0) @@ -1511,7 +1511,7 @@ class BatchJoinTest(test_lib.TestCase): batched = inp.maybe_batch_join( [[sparse]], keep_input=keep, batch_size=1, enqueue_many=True) - with self.test_session(): + with self.cached_session(): coord = coordinator.Coordinator() threads = queue_runner_impl.start_queue_runners(coord=coord) @@ -1529,7 +1529,7 @@ class BatchJoinTest(test_lib.TestCase): class ShuffleBatchTest(test_lib.TestCase): def _testOneThreadHelper(self, use_dict): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -1594,7 +1594,7 @@ class ShuffleBatchTest(test_lib.TestCase): self._testOneThreadHelper(use_dict=True) def testOneThreadSmallerBatch(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 extra_elements = 5 @@ -1650,7 +1650,7 @@ class ShuffleBatchTest(test_lib.TestCase): thread.join() def testManyThreads(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -1697,7 +1697,7 @@ class ShuffleBatchTest(test_lib.TestCase): thread.join() def testManyThreadsSmallerBatch(self): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 10 num_batches = 3 extra_elements = 5 @@ -1755,7 +1755,7 @@ class ShuffleBatchTest(test_lib.TestCase): thread.join() def testSharedName(self): - with self.test_session(): + with self.cached_session(): batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -1775,7 +1775,7 @@ class ShuffleBatchTest(test_lib.TestCase): def _testKeepInputHelper(self, num_threads, enqueue_many, keep_input_vector=False): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 5 num_batches = 4 examples = variables.Variable(0) @@ -1906,7 +1906,7 @@ class ShuffleBatchTest(test_lib.TestCase): class ShuffleBatchJoinTest(test_lib.TestCase): def _testTwoThreadsHelper(self, use_dict): - with self.test_session() as sess: + with self.cached_session() as sess: # Two threads, the first generates (0..24, "a"). num_a = 25 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -2017,7 +2017,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase): self._testTwoThreadsHelper(use_dict=True) def testTwoThreadsSmallerBatch(self): - with self.test_session() as sess: + with self.cached_session() as sess: # Two threads, the first generates (0..26, "a"). extra_elements = 2 num_a = 25 + extra_elements @@ -2137,7 +2137,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase): seed=223607) def testSharedName(self): - with self.test_session(): + with self.cached_session(): batch_size = 10 num_batches = 3 zero64 = constant_op.constant(0, dtype=dtypes.int64) @@ -2162,7 +2162,7 @@ class ShuffleBatchJoinTest(test_lib.TestCase): def _testKeepInputHelper(self, num_threads, enqueue_many, keep_input_vector=False): - with self.test_session() as sess: + with self.cached_session() as sess: batch_size = 5 num_batches = 4 examples = variables.Variable(0) diff --git a/tensorflow/python/training/learning_rate_decay_test.py b/tensorflow/python/training/learning_rate_decay_test.py index 4f3cf01822..5a9215730e 100644 --- a/tensorflow/python/training/learning_rate_decay_test.py +++ b/tensorflow/python/training/learning_rate_decay_test.py @@ -62,7 +62,7 @@ class LRDecayTest(test_util.TensorFlowTestCase): self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6) def testVariables(self): - with self.test_session(): + with self.cached_session(): step = variables.Variable(1) assign_1 = step.assign(1) assign_2 = step.assign(2) diff --git a/tensorflow/python/training/momentum_test.py b/tensorflow/python/training/momentum_test.py index f7e78071d8..8a21c39d32 100644 --- a/tensorflow/python/training/momentum_test.py +++ b/tensorflow/python/training/momentum_test.py @@ -123,7 +123,7 @@ class MomentumOptimizerTest(test.TestCase): ]), self.evaluate(var1)) def testBasic(self): - with self.test_session(): + with self.cached_session(): self.doTestBasic(use_resource=False) @test_util.run_in_graph_and_eager_modes(reset_test=True) @@ -162,7 +162,7 @@ class MomentumOptimizerTest(test.TestCase): def testNesterovMomentum(self): for dtype in [dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype) @@ -188,7 +188,7 @@ class MomentumOptimizerTest(test.TestCase): def testSparseNesterovMomentum(self): for dtype in [dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype) var1_np = np.array([3.0, 4.0], dtype=dtype.as_numpy_dtype) accum0_np = np.array([0.0, 0.0], dtype=dtype.as_numpy_dtype) @@ -282,7 +282,7 @@ class MomentumOptimizerTest(test.TestCase): def testTensorLearningRateAndMomentum(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -435,7 +435,7 @@ class MomentumOptimizerTest(test.TestCase): return db_grad, db_out def testLikeDistBeliefMom01(self): - with self.test_session(): + with self.cached_session(): db_grad, db_out = self._dbParamsMom01() num_samples = len(db_grad) var0 = variables.Variable([0.0] * num_samples) @@ -449,7 +449,7 @@ class MomentumOptimizerTest(test.TestCase): def testSparse(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable(array_ops.zeros([4, 2], dtype=dtype)) var1 = variables.Variable(constant_op.constant(1.0, dtype, [4, 2])) grads0 = ops.IndexedSlices( @@ -518,7 +518,7 @@ class MomentumOptimizerTest(test.TestCase): def testSharing(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) diff --git a/tensorflow/python/training/monitored_session_test.py b/tensorflow/python/training/monitored_session_test.py index ff586b6c03..2d7799d66a 100644 --- a/tensorflow/python/training/monitored_session_test.py +++ b/tensorflow/python/training/monitored_session_test.py @@ -80,7 +80,7 @@ class ScaffoldTest(test.TestCase): self.assertTrue(isinstance(scaffold.ready_for_local_init_op, ops.Tensor)) self.assertTrue(isinstance(scaffold.local_init_op, ops.Operation)) self.assertTrue(isinstance(scaffold.saver, saver_lib.Saver)) - with self.test_session() as sess: + with self.cached_session() as sess: self.assertItemsEqual([b'my_var', b'my_local_var'], sess.run(scaffold.ready_op)) self.assertItemsEqual([b'my_var'], @@ -513,21 +513,21 @@ class WrappedSessionTest(test.TestCase): """_WrappedSession tests.""" def test_properties(self): - with self.test_session() as sess: + with self.cached_session() as sess: constant_op.constant(0.0) wrapped_sess = monitored_session._WrappedSession(sess) self.assertEquals(sess.graph, wrapped_sess.graph) self.assertEquals(sess.sess_str, wrapped_sess.sess_str) def test_should_stop_on_close(self): - with self.test_session() as sess: + with self.cached_session() as sess: wrapped_sess = monitored_session._WrappedSession(sess) self.assertFalse(wrapped_sess.should_stop()) wrapped_sess.close() self.assertTrue(wrapped_sess.should_stop()) def test_should_stop_uses_check_stop(self): - with self.test_session() as sess: + with self.cached_session() as sess: wrapped_sess = StopAtNSession(sess, 3) self.assertFalse(wrapped_sess.should_stop()) self.assertFalse(wrapped_sess.should_stop()) @@ -535,7 +535,7 @@ class WrappedSessionTest(test.TestCase): self.assertTrue(wrapped_sess.should_stop()) def test_should_stop_delegates_to_wrapped_session(self): - with self.test_session() as sess: + with self.cached_session() as sess: wrapped_sess0 = StopAtNSession(sess, 4) wrapped_sess1 = monitored_session._WrappedSession(wrapped_sess0) self.assertFalse(wrapped_sess1.should_stop()) @@ -545,7 +545,7 @@ class WrappedSessionTest(test.TestCase): self.assertTrue(wrapped_sess1.should_stop()) def test_close_twice(self): - with self.test_session() as sess: + with self.cached_session() as sess: wrapped_sess = monitored_session._WrappedSession(sess) wrapped_sess.close() self.assertTrue(wrapped_sess.should_stop()) @@ -553,7 +553,7 @@ class WrappedSessionTest(test.TestCase): self.assertTrue(wrapped_sess.should_stop()) def test_run(self): - with self.test_session() as sess: + with self.cached_session() as sess: c = constant_op.constant(0) v = array_ops.identity(c) self.assertEqual(42, sess.run(v, feed_dict={c: 42})) @@ -570,7 +570,7 @@ class CoordinatedSessionTest(test.TestCase): """_CoordinatedSession tests.""" def test_properties(self): - with self.test_session() as sess: + with self.cached_session() as sess: constant_op.constant(0.0) coord = coordinator.Coordinator() coord_sess = monitored_session._CoordinatedSession(sess, coord) @@ -578,7 +578,7 @@ class CoordinatedSessionTest(test.TestCase): self.assertEquals(sess.sess_str, coord_sess.sess_str) def test_run(self): - with self.test_session() as sess: + with self.cached_session() as sess: c = constant_op.constant(0) v = array_ops.identity(c) coord = coordinator.Coordinator() @@ -586,7 +586,7 @@ class CoordinatedSessionTest(test.TestCase): self.assertEqual(42, coord_sess.run(v, feed_dict={c: 42})) def test_should_stop_on_close(self): - with self.test_session() as sess: + with self.cached_session() as sess: coord = coordinator.Coordinator() coord_sess = monitored_session._CoordinatedSession(sess, coord) self.assertFalse(coord_sess.should_stop()) @@ -594,7 +594,7 @@ class CoordinatedSessionTest(test.TestCase): self.assertTrue(coord_sess.should_stop()) def test_should_stop_on_coord_stop(self): - with self.test_session() as sess: + with self.cached_session() as sess: coord = coordinator.Coordinator() coord_sess = monitored_session._CoordinatedSession(sess, coord) self.assertFalse(coord_sess.should_stop()) @@ -602,7 +602,7 @@ class CoordinatedSessionTest(test.TestCase): self.assertTrue(coord_sess.should_stop()) def test_dont_request_stop_on_exception_in_main_thread(self): - with self.test_session() as sess: + with self.cached_session() as sess: c = constant_op.constant(0) v = array_ops.identity(c) coord = coordinator.Coordinator() @@ -616,7 +616,7 @@ class CoordinatedSessionTest(test.TestCase): self.assertFalse(coord_sess.should_stop()) def test_stop_threads_on_close_after_exception(self): - with self.test_session() as sess: + with self.cached_session() as sess: c = constant_op.constant(0) v = array_ops.identity(c) coord = coordinator.Coordinator() @@ -646,7 +646,7 @@ class CoordinatedSessionTest(test.TestCase): self.assertTrue(coord_sess.should_stop()) def test_stop_threads_on_close(self): - with self.test_session() as sess: + with self.cached_session() as sess: coord = coordinator.Coordinator() threads = [ threading.Thread( @@ -664,7 +664,7 @@ class CoordinatedSessionTest(test.TestCase): def test_propagates_exception_trace(self): assertion = control_flow_ops.Assert(False, ['This should fail.']) - with self.test_session() as sess: + with self.cached_session() as sess: coord = coordinator.Coordinator(clean_stop_exception_types=()) coord_sess = monitored_session._CoordinatedSession(sess, coord) try: @@ -810,7 +810,7 @@ class RecoverableSessionTest(test.TestCase): return self._sess def test_properties(self): - with self.test_session() as sess: + with self.cached_session() as sess: constant_op.constant(0.0) recoverable_sess = monitored_session._RecoverableSession( self._SessionReturner(sess)) @@ -818,7 +818,7 @@ class RecoverableSessionTest(test.TestCase): self.assertEquals(sess.sess_str, recoverable_sess.sess_str) def test_run(self): - with self.test_session() as sess: + with self.cached_session() as sess: c = constant_op.constant(0) v = array_ops.identity(c) recoverable_sess = monitored_session._RecoverableSession( @@ -826,7 +826,7 @@ class RecoverableSessionTest(test.TestCase): self.assertEqual(51, recoverable_sess.run(v, feed_dict={c: 51})) def test_recovery(self): - with self.test_session() as sess: + with self.cached_session() as sess: class StackSessionCreator(object): @@ -872,7 +872,7 @@ class RecoverableSessionTest(test.TestCase): recoverable_sess.run(v, feed_dict={c: -12}) def test_recovery_from_coordinator_exception(self): - with self.test_session() as test_session: + with self.cached_session() as test_session: session_creator = CountingSessionCreator(test_session) session = monitored_session.MonitoredSession( session_creator, @@ -897,7 +897,7 @@ class RecoverableSessionTest(test.TestCase): self.assertEqual(2, session_creator.number_of_sessions_created) def test_recovery_from_non_preemption_in_coordinator(self): - with self.test_session() as test_session: + with self.cached_session() as test_session: session_creator = CountingSessionCreator(test_session) hook = StopCoordinatorWithException( calls_before_stopping=2, @@ -926,7 +926,7 @@ class RecoverableSessionTest(test.TestCase): session.close() def test_recovery_from_session_getting_stuck(self): - with self.test_session() as test_session: + with self.cached_session() as test_session: session_creator = CountingSessionCreator(test_session) session = monitored_session.MonitoredSession( session_creator, @@ -950,7 +950,7 @@ class RecoverableSessionTest(test.TestCase): self.assertEqual(2, session_creator.number_of_sessions_created) def test_step_fn_recovery_from_coordinator_exception_when_run_hooks(self): - with self.test_session() as test_session: + with self.cached_session() as test_session: session_creator = CountingSessionCreator(test_session) session = monitored_session.MonitoredSession( session_creator, @@ -980,7 +980,7 @@ class RecoverableSessionTest(test.TestCase): self.assertEqual(2, session_creator.number_of_sessions_created) def test_recovery_from_non_preemption_in_coordinator_when_run_hooks(self): - with self.test_session() as test_session: + with self.cached_session() as test_session: session_creator = CountingSessionCreator(test_session) hook = StopCoordinatorWithException( calls_before_stopping=2, @@ -1014,7 +1014,7 @@ class RecoverableSessionTest(test.TestCase): session.close() def test_recovery_from_session_getting_stuck_when_run_hooks(self): - with self.test_session() as test_session: + with self.cached_session() as test_session: session_creator = CountingSessionCreator(test_session) session = monitored_session.MonitoredSession( session_creator, @@ -1058,7 +1058,7 @@ class RecoverableSessionTest(test.TestCase): return session def test_step_fn_recovery_from_coordinator_exception_with_raw_session(self): - with self.test_session() as test_session: + with self.cached_session() as test_session: session_creator = CountingSessionCreator(test_session) session = self.create_raw_session_with_failing_coordinator( session_creator, @@ -1090,7 +1090,7 @@ class RecoverableSessionTest(test.TestCase): self.assertEqual(2, session_creator.number_of_sessions_created) def test_recovery_from_non_preemption_in_coordinator_with_raw_session(self): - with self.test_session() as test_session: + with self.cached_session() as test_session: session_creator = CountingSessionCreator(test_session) session = self.create_raw_session_with_failing_coordinator( session_creator, @@ -1127,7 +1127,7 @@ class RecoverableSessionTest(test.TestCase): session.close() def test_recovery_from_session_getting_stuck_with_raw_session(self): - with self.test_session() as test_session: + with self.cached_session() as test_session: session_creator = CountingSessionCreator(test_session) session = self.create_raw_session_with_failing_coordinator( session_creator, @@ -2047,7 +2047,7 @@ class MonitoredSessionTest(test.TestCase): return value - with self.test_session() as test_session: + with self.cached_session() as test_session: with monitored_session.MonitoredSession( CountingSessionCreator(test_session)) as session: session.run(variables.global_variables_initializer()) @@ -2110,7 +2110,7 @@ class MonitoredSessionTest(test.TestCase): step_context.session.run(graph_side_effect) return step_context.run_with_hooks(fetches=v, feed_dict={c: 1.3}) - with self.test_session() as test_session: + with self.cached_session() as test_session: with monitored_session.MonitoredSession( CountingSessionCreator(test_session), hooks=[Hook(self)]) as session: diff --git a/tensorflow/python/training/moving_averages_test.py b/tensorflow/python/training/moving_averages_test.py index fdb8d795c3..93991d0e14 100644 --- a/tensorflow/python/training/moving_averages_test.py +++ b/tensorflow/python/training/moving_averages_test.py @@ -35,7 +35,7 @@ from tensorflow.python.training import saver as saver_lib class MovingAveragesTest(test.TestCase): def testAssignMovingAverageWithoutZeroDebias(self): - with self.test_session(): + with self.cached_session(): var = variables.Variable([10.0, 11.0]) val = constant_op.constant([1.0, 2.0], dtypes.float32) decay = 0.25 @@ -49,7 +49,7 @@ class MovingAveragesTest(test.TestCase): var.eval()) def testAssignMovingAverage(self): - with self.test_session(): + with self.cached_session(): var = variables.Variable([0.0, 0.0]) val = constant_op.constant([1.0, 2.0], dtypes.float32) decay = 0.25 @@ -86,7 +86,7 @@ class MovingAveragesTest(test.TestCase): moving_averages.assign_moving_average(var, 0.0, 0.99) def testWeightedMovingAverage(self): - with self.test_session() as sess: + with self.cached_session() as sess: decay = 0.5 weight = array_ops.placeholder(dtypes.float32, []) val = array_ops.placeholder(dtypes.float32, []) @@ -187,53 +187,53 @@ class ExponentialMovingAverageTest(test.TestCase): self.assertAllClose(expected, avg2.eval()) def testAverageVariablesNoNumUpdates_Scalar(self): - with self.test_session(): + with self.cached_session(): ema = moving_averages.ExponentialMovingAverage(0.25) self._CheckDecay(ema, actual_decay=0.25, dim=1) def testAverageVariablesNoNumUpdates_Scalar_Debias(self): - with self.test_session(): + with self.cached_session(): ema = moving_averages.ExponentialMovingAverage(0.25, zero_debias=True) self._CheckDecay(ema, actual_decay=0.25, dim=1) def testAverageVariablesNoNumUpdates_Vector(self): - with self.test_session(): + with self.cached_session(): ema = moving_averages.ExponentialMovingAverage(0.25) self._CheckDecay(ema, actual_decay=0.25, dim=5) def testAverageVariablesNoNumUpdates_Vector_Debias(self): - with self.test_session(): + with self.cached_session(): ema = moving_averages.ExponentialMovingAverage(0.25, zero_debias=True) self._CheckDecay(ema, actual_decay=0.25, dim=5) def testAverageVariablesNumUpdates_Scalar(self): - with self.test_session(): + with self.cached_session(): # With num_updates 1, the decay applied is 0.1818 ema = moving_averages.ExponentialMovingAverage(0.25, num_updates=1) self._CheckDecay(ema, actual_decay=0.181818, dim=1) def testAverageVariablesNumUpdates_Scalar_Debias(self): - with self.test_session(): + with self.cached_session(): # With num_updates 1, the decay applied is 0.1818 ema = moving_averages.ExponentialMovingAverage( 0.25, num_updates=1, zero_debias=True) self._CheckDecay(ema, actual_decay=0.181818, dim=1) def testAverageVariablesNumUpdates_Vector(self): - with self.test_session(): + with self.cached_session(): # With num_updates 1, the decay applied is 0.1818 ema = moving_averages.ExponentialMovingAverage(0.25, num_updates=1) self._CheckDecay(ema, actual_decay=0.181818, dim=5) def testAverageVariablesNumUpdates_Vector_Debias(self): - with self.test_session(): + with self.cached_session(): # With num_updates 1, the decay applied is 0.1818 ema = moving_averages.ExponentialMovingAverage( 0.25, num_updates=1, zero_debias=True) self._CheckDecay(ema, actual_decay=0.181818, dim=5) def testAverageVariablesWithControlDeps(self): - with self.test_session() as sess: + with self.cached_session() as sess: v0 = variables.Variable(0, name="v0") add_to_v0 = v0.assign_add(1) v1 = variables.Variable([10.0], name="v1") @@ -276,7 +276,7 @@ class ExponentialMovingAverageTest(test.TestCase): self.assertAllEqual(self.evaluate(ema.average(v1)), 3.5) def averageVariablesNamesHelper(self, zero_debias): - with self.test_session(): + with self.cached_session(): v0 = variables.Variable(10.0, name="v0") v1 = variables.Variable(30.0, name="v1") # Add a non-trainable variable. @@ -320,7 +320,7 @@ class ExponentialMovingAverageTest(test.TestCase): def averageVariablesNamesRespectScopeHelper(self, zero_debias): # See discussion on #2740. - with self.test_session(): + with self.cached_session(): with variable_scope.variable_scope("scope1"): v0 = variables.Variable(10.0, name="v0") v1 = variables.Variable(30.0, name="v1") @@ -367,7 +367,7 @@ class ExponentialMovingAverageTest(test.TestCase): self.averageVariablesNamesRespectScopeHelper(zero_debias=False) def testSubsetAverageVariablesNames(self): - with self.test_session(): + with self.cached_session(): v0 = variables.Variable(10.0, name="v0") v1 = variables.Variable(30.0, name="v1") # Add a non-trainable variable. diff --git a/tensorflow/python/training/optimizer_test.py b/tensorflow/python/training/optimizer_test.py index dfe9176bea..7a7d01d50e 100644 --- a/tensorflow/python/training/optimizer_test.py +++ b/tensorflow/python/training/optimizer_test.py @@ -64,7 +64,7 @@ class OptimizerTest(test.TestCase): def testAggregationMethod(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) cost = 5 * var0 + 3 * var1 @@ -89,7 +89,7 @@ class OptimizerTest(test.TestCase): def testPrecomputedGradient(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) cost = 5 * var0 + 3 * var1 @@ -231,7 +231,7 @@ class OptimizerTest(test.TestCase): sgd_op.apply_gradients(grads_and_vars) def testTrainOp(self): - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0]) var1 = variables.Variable([3.0, 4.0]) cost = 5 * var0 + 3 * var1 @@ -244,7 +244,7 @@ class OptimizerTest(test.TestCase): def testConstraint(self): constraint_01 = lambda x: clip_ops.clip_by_value(x, -0.1, 0.) constraint_0 = lambda x: clip_ops.clip_by_value(x, 0., 1.) - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], constraint=constraint_01) var1 = variables.Variable([3.0, 4.0], diff --git a/tensorflow/python/training/proximal_adagrad_test.py b/tensorflow/python/training/proximal_adagrad_test.py index 430c16b351..74e06a5e2e 100644 --- a/tensorflow/python/training/proximal_adagrad_test.py +++ b/tensorflow/python/training/proximal_adagrad_test.py @@ -35,7 +35,7 @@ from tensorflow.python.training import proximal_adagrad class ProximalAdagradOptimizerTest(test.TestCase): def doTestProximalAdagradwithoutRegularization(self, use_resource=False): - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([0.0, 0.0]) var1 = variables.Variable([0.0, 0.0]) grads0 = constant_op.constant([0.1, 0.2]) @@ -71,7 +71,7 @@ class ProximalAdagradOptimizerTest(test.TestCase): self.doTestProximalAdagradwithoutRegularization(use_resource=True) def testProximalAdagradwithoutRegularization2(self): - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([1.0, 2.0]) var1 = variables.Variable([4.0, 3.0]) grads0 = constant_op.constant([0.1, 0.2]) @@ -98,7 +98,7 @@ class ProximalAdagradOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariable(self): for dtype in [dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) @@ -114,7 +114,7 @@ class ProximalAdagradOptimizerTest(test.TestCase): [[0, 1]], var0.eval(), atol=0.01) def testProximalAdagradWithL1(self): - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([1.0, 2.0]) var1 = variables.Variable([4.0, 3.0]) grads0 = constant_op.constant([0.1, 0.2]) @@ -140,7 +140,7 @@ class ProximalAdagradOptimizerTest(test.TestCase): self.assertAllClose(np.array([2.959304, 1.029232]), v1_val) def testProximalAdagradWithL1_L2(self): - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([1.0, 2.0]) var1 = variables.Variable([4.0, 3.0]) grads0 = constant_op.constant([0.1, 0.2]) @@ -206,7 +206,7 @@ class ProximalAdagradOptimizerTest(test.TestCase): return v0_val, v1_val def testEquivAdagradwithoutRegularization(self): - with self.test_session(): + with self.cached_session(): val0, val1 = self.applyOptimizer( proximal_adagrad.ProximalAdagradOptimizer( 3.0, @@ -214,7 +214,7 @@ class ProximalAdagradOptimizerTest(test.TestCase): l1_regularization_strength=0.0, l2_regularization_strength=0.0)) - with self.test_session(): + with self.cached_session(): val2, val3 = self.applyOptimizer( adagrad.AdagradOptimizer( 3.0, initial_accumulator_value=0.1)) @@ -223,7 +223,7 @@ class ProximalAdagradOptimizerTest(test.TestCase): self.assertAllClose(val1, val3) def testEquivSparseAdagradwithoutRegularization(self): - with self.test_session(): + with self.cached_session(): val0, val1 = self.applyOptimizer( proximal_adagrad.ProximalAdagradOptimizer( 3.0, @@ -232,7 +232,7 @@ class ProximalAdagradOptimizerTest(test.TestCase): l2_regularization_strength=0.0), is_sparse=True) - with self.test_session(): + with self.cached_session(): val2, val3 = self.applyOptimizer( adagrad.AdagradOptimizer( 3.0, initial_accumulator_value=0.1), diff --git a/tensorflow/python/training/proximal_gradient_descent_test.py b/tensorflow/python/training/proximal_gradient_descent_test.py index 4e4812fe60..f77f68b234 100644 --- a/tensorflow/python/training/proximal_gradient_descent_test.py +++ b/tensorflow/python/training/proximal_gradient_descent_test.py @@ -36,7 +36,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase): def doTestProximalGradientDescentwithoutRegularization( self, use_resource=False): - with self.test_session() as sess: + with self.cached_session() as sess: if use_resource: var0 = resource_variable_ops.ResourceVariable([0.0, 0.0]) var1 = resource_variable_ops.ResourceVariable([0.0, 0.0]) @@ -69,7 +69,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase): self.doTestProximalGradientDescentwithoutRegularization(use_resource=True) def testProximalGradientDescentwithoutRegularization2(self): - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([1.0, 2.0]) var1 = variables.Variable([4.0, 3.0]) grads0 = constant_op.constant([0.1, 0.2]) @@ -94,7 +94,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariable(self): for dtype in [dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) @@ -111,7 +111,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase): [[-111, -138]], var0.eval(), atol=0.01) def testProximalGradientDescentWithL1_L2(self): - with self.test_session() as sess: + with self.cached_session() as sess: var0 = variables.Variable([1.0, 2.0]) var1 = variables.Variable([4.0, 3.0]) grads0 = constant_op.constant([0.1, 0.2]) @@ -174,7 +174,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase): return v0_val, v1_val def testEquivSparseGradientDescentwithoutRegularization(self): - with self.test_session(): + with self.cached_session(): val0, val1 = self.applyOptimizer( proximal_gradient_descent.ProximalGradientDescentOptimizer( 3.0, @@ -182,7 +182,7 @@ class ProximalGradientDescentOptimizerTest(test.TestCase): l2_regularization_strength=0.0), is_sparse=True) - with self.test_session(): + with self.cached_session(): val2, val3 = self.applyOptimizer( gradient_descent.GradientDescentOptimizer(3.0), is_sparse=True) @@ -190,14 +190,14 @@ class ProximalGradientDescentOptimizerTest(test.TestCase): self.assertAllClose(val1, val3) def testEquivGradientDescentwithoutRegularization(self): - with self.test_session(): + with self.cached_session(): val0, val1 = self.applyOptimizer( proximal_gradient_descent.ProximalGradientDescentOptimizer( 3.0, l1_regularization_strength=0.0, l2_regularization_strength=0.0)) - with self.test_session(): + with self.cached_session(): val2, val3 = self.applyOptimizer( gradient_descent.GradientDescentOptimizer(3.0)) diff --git a/tensorflow/python/training/queue_runner_test.py b/tensorflow/python/training/queue_runner_test.py index 900f9706ac..9b9e28af2b 100644 --- a/tensorflow/python/training/queue_runner_test.py +++ b/tensorflow/python/training/queue_runner_test.py @@ -41,7 +41,7 @@ _MockOp = collections.namedtuple("MockOp", ["name"]) class QueueRunnerTest(test.TestCase): def testBasic(self): - with self.test_session() as sess: + with self.cached_session() as sess: # CountUpTo will raise OUT_OF_RANGE when it reaches the count. zero64 = constant_op.constant(0, dtype=dtypes.int64) var = variables.Variable(zero64) @@ -61,7 +61,7 @@ class QueueRunnerTest(test.TestCase): self.assertEqual(3, var.eval()) def testTwoOps(self): - with self.test_session() as sess: + with self.cached_session() as sess: # CountUpTo will raise OUT_OF_RANGE when it reaches the count. zero64 = constant_op.constant(0, dtype=dtypes.int64) var0 = variables.Variable(zero64) @@ -84,7 +84,7 @@ class QueueRunnerTest(test.TestCase): self.assertEqual(30, var1.eval()) def testExceptionsCaptured(self): - with self.test_session() as sess: + with self.cached_session() as sess: queue = data_flow_ops.FIFOQueue(10, dtypes.float32) qr = queue_runner_impl.QueueRunner(queue, [_MockOp("i fail"), _MockOp("so fail")]) @@ -100,7 +100,7 @@ class QueueRunnerTest(test.TestCase): self.assertTrue("Operation not in the graph" in str(exceptions[1])) def testRealDequeueEnqueue(self): - with self.test_session() as sess: + with self.cached_session() as sess: q0 = data_flow_ops.FIFOQueue(3, dtypes.float32) enqueue0 = q0.enqueue((10.0,)) close0 = q0.close() @@ -128,7 +128,7 @@ class QueueRunnerTest(test.TestCase): dequeue1.eval() def testRespectCoordShouldStop(self): - with self.test_session() as sess: + with self.cached_session() as sess: # CountUpTo will raise OUT_OF_RANGE when it reaches the count. zero64 = constant_op.constant(0, dtype=dtypes.int64) var = variables.Variable(zero64) @@ -152,7 +152,7 @@ class QueueRunnerTest(test.TestCase): self.assertEqual(0, var.eval()) def testRequestStopOnException(self): - with self.test_session() as sess: + with self.cached_session() as sess: queue = data_flow_ops.FIFOQueue(10, dtypes.float32) qr = queue_runner_impl.QueueRunner(queue, [_MockOp("not an op")]) coord = coordinator.Coordinator() @@ -164,7 +164,7 @@ class QueueRunnerTest(test.TestCase): coord.join() def testGracePeriod(self): - with self.test_session() as sess: + with self.cached_session() as sess: # The enqueue will quickly block. queue = data_flow_ops.FIFOQueue(2, dtypes.float32) enqueue = queue.enqueue((10.0,)) @@ -181,7 +181,7 @@ class QueueRunnerTest(test.TestCase): coord.join(stop_grace_period_secs=1.0) def testMultipleSessions(self): - with self.test_session() as sess: + with self.cached_session() as sess: with session.Session() as other_sess: zero64 = constant_op.constant(0, dtype=dtypes.int64) var = variables.Variable(zero64) @@ -196,7 +196,7 @@ class QueueRunnerTest(test.TestCase): self.assertEqual(len(threads), len(other_threads)) def testIgnoreMultiStarts(self): - with self.test_session() as sess: + with self.cached_session() as sess: # CountUpTo will raise OUT_OF_RANGE when it reaches the count. zero64 = constant_op.constant(0, dtype=dtypes.int64) var = variables.Variable(zero64) @@ -212,7 +212,7 @@ class QueueRunnerTest(test.TestCase): self.assertEqual([], new_threads) def testThreads(self): - with self.test_session() as sess: + with self.cached_session() as sess: # CountUpTo will raise OUT_OF_RANGE when it reaches the count. zero64 = constant_op.constant(0, dtype=dtypes.int64) var = variables.Variable(zero64) @@ -256,7 +256,7 @@ class QueueRunnerTest(test.TestCase): init_op = variables.global_variables_initializer() qr = queue_runner_impl.QueueRunner(queue, [count_up_to]) queue_runner_impl.add_queue_runner(qr) - with self.test_session() as sess: + with self.cached_session() as sess: init_op.run() threads = queue_runner_impl.start_queue_runners(sess) for t in threads: @@ -273,7 +273,7 @@ class QueueRunnerTest(test.TestCase): init_op = variables.global_variables_initializer() qr = queue_runner_impl.QueueRunner(queue, [count_up_to]) queue_runner_impl.add_queue_runner(qr) - with self.test_session(): + with self.cached_session(): init_op.run() with self.assertRaisesRegexp(TypeError, "tf.Session"): queue_runner_impl.start_queue_runners("NotASession") @@ -286,7 +286,7 @@ class QueueRunnerTest(test.TestCase): init_op = variables.global_variables_initializer() qr = queue_runner_impl.QueueRunner(queue, [count_up_to]) queue_runner_impl.add_queue_runner(qr) - with self.test_session(): + with self.cached_session(): init_op.run() threads = queue_runner_impl.start_queue_runners( monitored_session.MonitoredSession()) diff --git a/tensorflow/python/training/rmsprop_test.py b/tensorflow/python/training/rmsprop_test.py index 6043327384..4f5f96e2b4 100644 --- a/tensorflow/python/training/rmsprop_test.py +++ b/tensorflow/python/training/rmsprop_test.py @@ -165,7 +165,7 @@ class RMSPropOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariable(self): for dtype in [dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) @@ -187,7 +187,7 @@ class RMSPropOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariableCentered(self): for dtype in [dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) diff --git a/tensorflow/python/training/saver_test.py b/tensorflow/python/training/saver_test.py index f5b2a22327..0ac84813c8 100644 --- a/tensorflow/python/training/saver_test.py +++ b/tensorflow/python/training/saver_test.py @@ -324,7 +324,7 @@ class SaverTest(test.TestCase): save_relative_paths=True) init_all_op = [variables.global_variables_initializer(), v2_init] - with self.test_session() as sess: + with self.cached_session() as sess: # Initialize all variables sess.run(init_all_op) @@ -349,7 +349,7 @@ class SaverTest(test.TestCase): # Start a second session. In that session the parameter nodes # have not been initialized either. - with self.test_session() as sess: + with self.cached_session() as sess: v0 = variables.Variable(-1.0, name="v0") v1 = variables.Variable(-1.0, name="v1") v2 = saver_test_utils.CheckpointedOp(name="v2") @@ -373,7 +373,7 @@ class SaverTest(test.TestCase): v0 = variables.Variable(0, name="v0") filename = b"somerandomfilename" save = saver_module.Saver({"v0": v0}, filename=filename) - with self.test_session() as sess: + with self.cached_session() as sess: tensor = sess.graph.get_tensor_by_name( save.saver_def.filename_tensor_name) self.assertEqual(sess.run(tensor), filename) @@ -381,7 +381,7 @@ class SaverTest(test.TestCase): def testInvalidPath(self): v0 = variables.Variable(0, name="v0") for ver in (saver_pb2.SaverDef.V1, saver_pb2.SaverDef.V2): - with self.test_session() as sess: + with self.cached_session() as sess: save = saver_module.Saver({"v0": v0}, write_version=ver) with self.assertRaisesRegexp( ValueError, "The passed save_path is not a valid checkpoint:"): @@ -390,7 +390,7 @@ class SaverTest(test.TestCase): def testInt64(self): save_path = os.path.join(self.get_temp_dir(), "int64") - with self.test_session() as sess: + with self.cached_session() as sess: # Build a graph with 1 node, and save and restore for them. v = variables.Variable(np.int64(15), name="v") save = saver_module.Saver({"v": v}, restore_sequentially=True) @@ -401,7 +401,7 @@ class SaverTest(test.TestCase): self.assertTrue(isinstance(val, six.string_types)) self.assertEqual(save_path, val) - with self.test_session() as sess: + with self.cached_session() as sess: v = variables.Variable(np.int64(-1), name="v") save = saver_module.Saver({"v": v}) @@ -559,12 +559,12 @@ class SaverTest(test.TestCase): def testAllowEmpty(self): save_path = os.path.join(self.get_temp_dir(), "allow_empty") - with self.test_session() as sess: + with self.cached_session() as sess: _ = constant_op.constant(1) save = saver_module.Saver(allow_empty=True) val = save.save(sess, save_path) self.assertIsNone(val) - with self.test_session() as sess: + with self.cached_session() as sess: save = saver_module.Saver(allow_empty=True) save.restore(sess, save_path) @@ -740,7 +740,7 @@ class SaverTest(test.TestCase): # save succeeds or fails is implementation dependent. Therefore we allow # both cases. try: - with self.test_session() as sess: + with self.cached_session() as sess: # Initialize all variables sess.run(init_all_op) @@ -751,7 +751,7 @@ class SaverTest(test.TestCase): # Save the graph. save.save(sess, save_path) - with self.test_session() as sess: + with self.cached_session() as sess: # Restore the saved values in the parameter nodes. save.restore(sess, save_path) # Check that the parameter nodes have been restored. @@ -775,7 +775,7 @@ class SaverTest(test.TestCase): save = saver_module.Saver({"v0": v0, "v1": v1}, restore_sequentially=True) init_all_op = variables.global_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: # Initialize all variables sess.run(init_all_op) @@ -983,7 +983,7 @@ class SaveRestoreShardedTest(test.TestCase): os.path.join(self.get_temp_dir(), "sharded_basics")) def testSaverDef(self): - with self.test_session(): + with self.cached_session(): v0 = variables.Variable(123, name="v0") save = saver_module.Saver({"v0": v0}, sharded=True) sd = save.as_saver_def() @@ -1209,7 +1209,7 @@ class MaxToKeepTest(test.TestCase): def testNonSharded(self): save_dir = self._get_test_dir("max_to_keep_non_sharded") - with self.test_session() as sess: + with self.cached_session() as sess: v = variables.Variable(10.0, name="v") save = saver_module.Saver({"v": v}, max_to_keep=2) variables.global_variables_initializer().run() @@ -1447,7 +1447,7 @@ class MaxToKeepTest(test.TestCase): save_dir = self._get_test_dir("no_max_to_keep") save_dir2 = self._get_test_dir("max_to_keep_0") - with self.test_session() as sess: + with self.cached_session() as sess: v = variables.Variable(10.0, name="v") variables.global_variables_initializer().run() @@ -1474,7 +1474,7 @@ class MaxToKeepTest(test.TestCase): def testNoMetaGraph(self): save_dir = self._get_test_dir("no_meta_graph") - with self.test_session() as sess: + with self.cached_session() as sess: v = variables.Variable(10.0, name="v") save = saver_module.Saver({"v": v}) variables.global_variables_initializer().run() @@ -1497,7 +1497,7 @@ class KeepCheckpointEveryNHoursTest(test.TestCase): def testNonSharded(self, mock_time): save_dir = self._get_test_dir("keep_checkpoint_every_n_hours") - with self.test_session() as sess: + with self.cached_session() as sess: v = variable_scope.variable([10.0], name="v") # Run the initializer NOW to avoid the 0.5s overhead of the first Run() # call, which throws the test timing off in fastbuild mode. @@ -1630,7 +1630,7 @@ class MetaGraphTest(test.TestCase): def testAddCollectionDef(self): test_dir = self._get_test_dir("good_collection") filename = os.path.join(test_dir, "metafile") - with self.test_session(): + with self.cached_session(): # Creates a graph. v0 = variables.Variable(1.0, name="v0") control_flow_ops.cond( @@ -1685,7 +1685,7 @@ class MetaGraphTest(test.TestCase): self, meta_graph_def, new_meta_graph_def) def testAddCollectionDefFails(self): - with self.test_session(): + with self.cached_session(): # Creates a graph. v0 = variables.Variable(10.0, name="v0") # Creates a saver. @@ -1870,7 +1870,7 @@ class MetaGraphTest(test.TestCase): def testSliceVariable(self): test_dir = self._get_test_dir("slice_saver") filename = os.path.join(test_dir, "metafile") - with self.test_session(): + with self.cached_session(): v1 = variables.Variable([20.0], name="v1") v2 = variables.Variable([20.0], name="v2") v2._set_save_slice_info( @@ -1946,7 +1946,7 @@ class MetaGraphTest(test.TestCase): ops_lib.add_to_collection("logits", logits) init_all_op = variables.global_variables_initializer() - with self.test_session() as sess: + with self.cached_session() as sess: # Initializes all the variables. sess.run(init_all_op) # Runs to logit. @@ -2120,7 +2120,7 @@ class MetaGraphTest(test.TestCase): # pylint: enable=g-long-lambda def testStrippedOpListDef(self): - with self.test_session(): + with self.cached_session(): # Creates a graph. v0 = variables.Variable(0.0) var = variables.Variable(10.0) @@ -2160,7 +2160,7 @@ class MetaGraphTest(test.TestCase): # With strip_default_attrs enabled, attributes "T" (float32) and "Tout" # (complex64) in the "Complex" op must be removed. - with self.test_session(): + with self.cached_session(): real_num = variables.Variable(1.0, dtype=dtypes.float32, name="real") imag_num = variables.Variable(2.0, dtype=dtypes.float32, name="imag") math_ops.complex(real_num, imag_num, name="complex") @@ -2397,7 +2397,7 @@ class CheckpointReaderTest(test.TestCase): }, write_version=self._WRITE_VERSION) save_path = os.path.join(self.get_temp_dir(), "ckpt_for_debug_string" + str(self._WRITE_VERSION)) - with self.test_session() as sess: + with self.cached_session() as sess: sess.run(init_all_op) # Saves a checkpoint. save.save(sess, save_path) @@ -2853,7 +2853,7 @@ class CheckpointableCompatibilityTests(test.TestCase): saver = saver_module.Saver(var_list=[v]) test_dir = self.get_temp_dir() prefix = os.path.join(test_dir, "ckpt") - with self.test_session() as sess: + with self.cached_session() as sess: self.evaluate(v.non_dep_variable.assign(42.)) save_path = saver.save(sess, prefix) self.evaluate(v.non_dep_variable.assign(43.)) @@ -2867,7 +2867,7 @@ class CheckpointableCompatibilityTests(test.TestCase): test_dir = self.get_temp_dir() prefix = os.path.join(test_dir, "ckpt") self.evaluate(v.non_dep_variable.assign(42.)) - with self.test_session() as sess: + with self.cached_session() as sess: save_path = saver.save(sess, prefix) self.evaluate(v.non_dep_variable.assign(43.)) self.evaluate(v.mirrored.assign(44.)) @@ -2900,7 +2900,7 @@ class CheckpointableCompatibilityTests(test.TestCase): saver = saver_module.Saver(var_list=[v]) test_dir = self.get_temp_dir() prefix = os.path.join(test_dir, "ckpt") - with self.test_session() as sess: + with self.cached_session() as sess: save_path = saver.save(sess, prefix) self.assertEqual(1, v.eval_count) saver.restore(sess, save_path) @@ -2957,7 +2957,7 @@ class CheckpointableCompatibilityTests(test.TestCase): b = resource_variable_ops.ResourceVariable(1., name="b") a_saver = saver_module.Saver([a]) b_saver = saver_module.Saver([b]) - with self.test_session() as sess: + with self.cached_session() as sess: sess.run(a.initializer) save_path = a_saver.save(sess=sess, save_path=checkpoint_prefix) with self.assertRaisesRegexp( diff --git a/tensorflow/python/training/session_manager_test.py b/tensorflow/python/training/session_manager_test.py index d7e6dac95b..f1d18f7704 100644 --- a/tensorflow/python/training/session_manager_test.py +++ b/tensorflow/python/training/session_manager_test.py @@ -98,7 +98,7 @@ class SessionManagerTest(test.TestCase): os.rename(checkpoint_dir, checkpoint_dir2) gfile.MakeDirs(checkpoint_dir) v = variables.Variable([6.0, 7.0, 8.0], name="v") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) session_manager.SessionManager( ready_op=variables.report_uninitialized_variables()) @@ -236,7 +236,7 @@ class SessionManagerTest(test.TestCase): trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES], name="w") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) self.assertEqual(False, variables.is_variable_initialized(w).eval()) sm2 = session_manager.SessionManager( @@ -294,7 +294,7 @@ class SessionManagerTest(test.TestCase): trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES], name="w") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) self.assertEqual(False, variables.is_variable_initialized(w).eval()) sm2 = session_manager.SessionManager( @@ -326,7 +326,7 @@ class SessionManagerTest(test.TestCase): trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES], name="w") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(w).eval()) sm2 = session_manager.SessionManager( ready_op=variables.report_uninitialized_variables(), @@ -362,7 +362,7 @@ class SessionManagerTest(test.TestCase): trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES], name="w") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) self.assertEqual(False, variables.is_variable_initialized(w).eval()) sm2 = session_manager.SessionManager( @@ -467,7 +467,7 @@ class SessionManagerTest(test.TestCase): trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES], name="x") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) self.assertEqual(False, variables.is_variable_initialized(w).eval()) self.assertEqual(False, variables.is_variable_initialized(x).eval()) @@ -519,7 +519,7 @@ class SessionManagerTest(test.TestCase): collections=[ops.GraphKeys.LOCAL_VARIABLES], name="x_res") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) self.assertEqual(False, variables.is_variable_initialized(w).eval()) self.assertEqual(False, variables.is_variable_initialized(x).eval()) @@ -566,7 +566,7 @@ class SessionManagerTest(test.TestCase): with ops.Graph().as_default(): i = control_flow_ops.while_loop(lambda i: i < 1, lambda i: i + 1, [0]) v = variables.Variable(array_ops.identity(i), name="v") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) sm = session_manager.SessionManager( ready_op=variables.report_uninitialized_variables()) @@ -585,7 +585,7 @@ class SessionManagerTest(test.TestCase): trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES], name="w") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) self.assertEqual(False, variables.is_variable_initialized(w).eval()) sm2 = session_manager.SessionManager( @@ -602,7 +602,7 @@ class SessionManagerTest(test.TestCase): trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES], name="w") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) self.assertEqual(False, variables.is_variable_initialized(w).eval()) sm2 = session_manager.SessionManager( @@ -619,7 +619,7 @@ class SessionManagerTest(test.TestCase): trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES], name="w") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) self.assertEqual(False, variables.is_variable_initialized(w).eval()) sm2 = session_manager.SessionManager( @@ -640,7 +640,7 @@ class SessionManagerTest(test.TestCase): trainable=False, collections=[ops.GraphKeys.LOCAL_VARIABLES], name="w") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) self.assertEqual(False, variables.is_variable_initialized(w).eval()) sm2 = session_manager.SessionManager( @@ -714,7 +714,7 @@ class ObsoleteSessionManagerTest(test.TestCase): os.rename(checkpoint_dir, checkpoint_dir2) gfile.MakeDirs(checkpoint_dir) v = variables.Variable([6.0, 7.0, 8.0], name="v") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) session_manager.SessionManager( ready_op=variables.assert_variables_initialized()) @@ -769,7 +769,7 @@ class ObsoleteSessionManagerTest(test.TestCase): # Create a new Graph and SessionManager and recover. with ops.Graph().as_default(): v = variables.Variable(2, name="v") - with self.test_session(): + with self.cached_session(): self.assertEqual(False, variables.is_variable_initialized(v).eval()) sm2 = session_manager.SessionManager( ready_op=variables.assert_variables_initialized()) diff --git a/tensorflow/python/training/slot_creator_test.py b/tensorflow/python/training/slot_creator_test.py index 08a3c8dc53..6d6364169f 100644 --- a/tensorflow/python/training/slot_creator_test.py +++ b/tensorflow/python/training/slot_creator_test.py @@ -32,7 +32,7 @@ from tensorflow.python.training import slot_creator class SlotCreatorTest(test.TestCase): def testCreateSlotFromVariable(self): - with self.test_session(): + with self.cached_session(): v = variables.Variable([1.0, 2.5], name="var") slot = slot_creator.create_slot(v, v.initialized_value(), name="slot") @@ -44,7 +44,7 @@ class SlotCreatorTest(test.TestCase): self.assertAllEqual([1.0, 2.5], slot.eval()) def testCreateSlotFromTensor(self): - with self.test_session(): + with self.cached_session(): v = constant_op.constant([1.0, 2.5], name="const") slot = slot_creator.create_slot(v, v * 2, name="slot") @@ -56,7 +56,7 @@ class SlotCreatorTest(test.TestCase): self.assertAllEqual([2.0, 5.0], slot.eval()) def testCreateZerosSlotFromVariable(self): - with self.test_session(): + with self.cached_session(): v = variables.Variable([1.0, 2.5], name="var") with ops.control_dependencies(None): slot = slot_creator.create_zeros_slot( @@ -70,7 +70,7 @@ class SlotCreatorTest(test.TestCase): self.assertAllEqual([0.0, 0.0], slot.eval()) def testCreateZerosSlotFromDynamicShapedVariable(self): - with self.test_session(): + with self.cached_session(): dyn_shape = constant_op.constant([2], dtype=dtypes.int32) dyn_shape = array_ops.placeholder_with_default(dyn_shape, shape=[None]) @@ -91,7 +91,7 @@ class SlotCreatorTest(test.TestCase): self.assertAllEqual([0.0, 0.0], slot.eval()) def testCreateZerosSlotFromTensor(self): - with self.test_session(): + with self.cached_session(): v = constant_op.constant([1.0, 2.5], name="const") with ops.control_dependencies(None): slot = slot_creator.create_zeros_slot(v, name="slot") @@ -104,7 +104,7 @@ class SlotCreatorTest(test.TestCase): self.assertAllEqual([0.0, 0.0], slot.eval()) def testCreateZerosSlotFromDynamicShapedTensor(self): - with self.test_session(): + with self.cached_session(): v = random_ops.random_uniform([2], dtype=dtypes.float64) v = array_ops.placeholder_with_default(v, shape=[None], name="const") with ops.control_dependencies(None): @@ -120,7 +120,7 @@ class SlotCreatorTest(test.TestCase): def testCreateSlotFromVariableRespectsScope(self): # See discussion on #2740. - with self.test_session(): + with self.cached_session(): with variable_scope.variable_scope("scope"): v = variables.Variable([1.0, 2.5], name="var") slot = slot_creator.create_slot(v, v.initialized_value(), name="slot") diff --git a/tensorflow/python/training/supervisor_test.py b/tensorflow/python/training/supervisor_test.py index 71ed88093a..caf6eba3e0 100644 --- a/tensorflow/python/training/supervisor_test.py +++ b/tensorflow/python/training/supervisor_test.py @@ -795,7 +795,7 @@ class SupervisorTest(test.TestCase): self.assertRaises(StopIteration, lambda: next(rr)) # There should be a checkpoint file with the variable "foo" - with ops.Graph().as_default(), self.test_session() as sess: + with ops.Graph().as_default(), self.cached_session() as sess: v = variables.Variable([10.10], name="foo") sav = saver_lib.Saver([v]) sav.restore(sess, save_path) @@ -859,14 +859,14 @@ class SupervisorTest(test.TestCase): self.assertEquals(event_pb2.SessionLog.STOP, ev.session_log.status) self.assertRaises(StopIteration, lambda: next(rr)) # There should be a checkpoint file with the variable "foo" - with ops.Graph().as_default(), self.test_session() as sess: + with ops.Graph().as_default(), self.cached_session() as sess: v = variables.Variable([-12], name="global_step") sav = saver_lib.Saver([v]) sav.restore(sess, save_path) self.assertEqual(123, v.eval()[0]) def testNoQueueRunners(self): - with ops.Graph().as_default(), self.test_session() as sess: + with ops.Graph().as_default(), self.cached_session() as sess: sv = supervisor.Supervisor(logdir=self._test_dir("no_queue_runners")) self.assertEqual(0, len(sv.start_queue_runners(sess))) sv.stop() diff --git a/tensorflow/python/training/warm_starting_util_test.py b/tensorflow/python/training/warm_starting_util_test.py index 3ee0f6aaa2..6c860cd452 100644 --- a/tensorflow/python/training/warm_starting_util_test.py +++ b/tensorflow/python/training/warm_starting_util_test.py @@ -1133,7 +1133,7 @@ class WarmStartingUtilTest(test.TestCase): # Unused variable names raises ValueError. with ops.Graph().as_default(): - with self.test_session() as sess: + with self.cached_session() as sess: x = variable_scope.get_variable( "x", shape=[4, 1], |