From 496023e9dc84a076caeb2e5e8e13b6a3d819ad6d Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Tue, 21 Aug 2018 19:24:19 -0700 Subject: Move from deprecated self.test_session() to self.cached_session(). self.test_session() has been deprecated in 9962eb5e84b15e309410071b06c2ed2d6148ed44 as its name confuses readers of the test. Moving to cached_session() instead which is more explicit about: * the fact that the session may be reused. * the session is not closed even when doing a "with self.test_session()" statement. PiperOrigin-RevId: 209701635 --- tensorflow/python/layers/convolutional_test.py | 8 ++++---- tensorflow/python/layers/core_test.py | 23 ++++++++++++----------- tensorflow/python/layers/normalization_test.py | 24 ++++++++++++------------ 3 files changed, 28 insertions(+), 27 deletions(-) (limited to 'tensorflow/python/layers') diff --git a/tensorflow/python/layers/convolutional_test.py b/tensorflow/python/layers/convolutional_test.py index 625320b48b..d61d3b6dba 100644 --- a/tensorflow/python/layers/convolutional_test.py +++ b/tensorflow/python/layers/convolutional_test.py @@ -264,7 +264,7 @@ class ConvTest(test.TestCase): self.assertEqual(len(variables.trainable_variables()), 2) def testFunctionalConv2DInitializerFromScope(self): - with self.test_session() as sess: + with self.cached_session() as sess: with variable_scope.variable_scope( 'scope', initializer=init_ops.ones_initializer()): height, width = 7, 9 @@ -647,7 +647,7 @@ class SeparableConv2DTest(test.TestCase): self.assertEqual(len(variables.trainable_variables()), 3) def testFunctionalConv2DInitializerFromScope(self): - with self.test_session() as sess: + with self.cached_session() as sess: with variable_scope.variable_scope( 'scope', initializer=init_ops.ones_initializer()): height, width = 7, 9 @@ -882,7 +882,7 @@ class Conv2DTransposeTest(test.TestCase): self.assertEqual(len(variables.trainable_variables()), 2) def testFunctionalConv2DTransposeInitializerFromScope(self): - with self.test_session() as sess: + with self.cached_session() as sess: with variable_scope.variable_scope( 'scope', initializer=init_ops.ones_initializer()): height, width = 7, 9 @@ -1061,7 +1061,7 @@ class Conv3DTransposeTest(test.TestCase): self.assertEqual(len(variables.trainable_variables()), 2) def testFunctionalConv3DTransposeInitializerFromScope(self): - with self.test_session() as sess: + with self.cached_session() as sess: with variable_scope.variable_scope( 'scope', initializer=init_ops.ones_initializer()): depth, height, width = 5, 7, 9 diff --git a/tensorflow/python/layers/core_test.py b/tensorflow/python/layers/core_test.py index 040c1cddc0..46009a30ac 100644 --- a/tensorflow/python/layers/core_test.py +++ b/tensorflow/python/layers/core_test.py @@ -60,7 +60,7 @@ class DenseTest(test.TestCase): self.assertEqual(dense.name, 'dense_2') def testVariableInput(self): - with self.test_session(): + with self.cached_session(): v = variable_scope.get_variable( 'X', initializer=init_ops.zeros_initializer(), shape=(1, 1)) x = core_layers.Dense(1)(v) @@ -221,7 +221,7 @@ class DenseTest(test.TestCase): self.assertListEqual(dense.losses, loss_keys) def testFunctionalDense(self): - with self.test_session(): + with self.cached_session(): inputs = random_ops.random_uniform((5, 3), seed=1) outputs = core_layers.dense( inputs, 2, activation=nn_ops.relu, name='my_dense') @@ -240,7 +240,7 @@ class DenseTest(test.TestCase): # TODO(alive): get this to work in eager mode. def testFunctionalDenseTwiceReuse(self): - with self.test_session(): + with self.cached_session(): inputs = random_ops.random_uniform((5, 3), seed=1) core_layers.dense(inputs, 2, name='my_dense') vars1 = variables.trainable_variables() @@ -250,7 +250,7 @@ class DenseTest(test.TestCase): # TODO(alive): get this to work in eager mode. def testFunctionalDenseTwiceReuseFromScope(self): - with self.test_session(): + with self.cached_session(): with variable_scope.variable_scope('scope'): inputs = random_ops.random_uniform((5, 3), seed=1) core_layers.dense(inputs, 2, name='my_dense') @@ -262,7 +262,8 @@ class DenseTest(test.TestCase): def testFunctionalDenseInitializerFromScope(self): with variable_scope.variable_scope( - 'scope', initializer=init_ops.ones_initializer()), self.test_session(): + 'scope', + initializer=init_ops.ones_initializer()), self.cached_session(): inputs = random_ops.random_uniform((5, 3), seed=1) core_layers.dense(inputs, 2) variables.global_variables_initializer().run() @@ -305,7 +306,7 @@ class DenseTest(test.TestCase): self.assertEqual(called[0], 2) def testFunctionalDenseInScope(self): - with self.test_session(): + with self.cached_session(): with variable_scope.variable_scope('test'): inputs = random_ops.random_uniform((5, 3), seed=1) core_layers.dense(inputs, 2, name='my_dense') @@ -391,7 +392,7 @@ class DropoutTest(test.TestCase): self.assertAllClose(np.ones((5, 3)), np_output) def testDynamicLearningPhase(self): - with self.test_session() as sess: + with self.cached_session() as sess: dp = core_layers.Dropout(0.5, seed=1) inputs = array_ops.ones((5, 5)) training = array_ops.placeholder(dtype='bool') @@ -424,7 +425,7 @@ class DropoutTest(test.TestCase): self.assertAllClose(np_output[:, 0, :], np_output[:, 1, :]) def testFunctionalDropout(self): - with self.test_session(): + with self.cached_session(): inputs = array_ops.ones((5, 5)) dropped = core_layers.dropout(inputs, 0.5, training=True, seed=1) variables.global_variables_initializer().run() @@ -435,7 +436,7 @@ class DropoutTest(test.TestCase): self.assertAllClose(np.ones((5, 5)), np_output) def testDynamicRate(self): - with self.test_session() as sess: + with self.cached_session() as sess: rate = array_ops.placeholder(dtype='float32', name='rate') dp = core_layers.Dropout(rate, name='dropout') inputs = array_ops.ones((5, 5)) @@ -450,7 +451,7 @@ class DropoutTest(test.TestCase): class FlattenTest(test.TestCase): def testCreateFlatten(self): - with self.test_session() as sess: + with self.cached_session() as sess: x = array_ops.placeholder(shape=(None, 2, 3), dtype='float32') y = core_layers.Flatten()(x) np_output = sess.run(y, feed_dict={x: np.zeros((3, 2, 3))}) @@ -484,7 +485,7 @@ class FlattenTest(test.TestCase): core_layers.Flatten()(x) def testFlattenUnknownAxes(self): - with self.test_session() as sess: + with self.cached_session() as sess: x = array_ops.placeholder(shape=(5, None, None), dtype='float32') y = core_layers.Flatten()(x) np_output = sess.run(y, feed_dict={x: np.zeros((5, 2, 3))}) diff --git a/tensorflow/python/layers/normalization_test.py b/tensorflow/python/layers/normalization_test.py index 57394f29d7..a72d147a0b 100644 --- a/tensorflow/python/layers/normalization_test.py +++ b/tensorflow/python/layers/normalization_test.py @@ -319,7 +319,7 @@ class BNTest(test.TestCase): training = array_ops.placeholder(dtype='bool') outputs = bn.apply(inputs, training=training) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) @@ -361,7 +361,7 @@ class BNTest(test.TestCase): training = array_ops.placeholder(dtype='bool') outputs = bn.apply(inputs, training=training) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) @@ -442,7 +442,7 @@ class BNTest(test.TestCase): training = array_ops.placeholder(dtype='bool') outputs = bn.apply(inputs, training=training) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) @@ -482,7 +482,7 @@ class BNTest(test.TestCase): training = array_ops.placeholder(dtype='bool') outputs = bn.apply(inputs, training=training) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) @@ -522,7 +522,7 @@ class BNTest(test.TestCase): training = array_ops.placeholder(dtype='bool') outputs = bn.apply(inputs, training=training) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) @@ -563,7 +563,7 @@ class BNTest(test.TestCase): training = array_ops.placeholder(dtype='bool') outputs = bn.apply(inputs, training=training) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) @@ -603,7 +603,7 @@ class BNTest(test.TestCase): training = array_ops.placeholder(dtype='bool') outputs = bn.apply(inputs, training=training) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) @@ -644,7 +644,7 @@ class BNTest(test.TestCase): outputs_training = bn.apply(inputs, training=True) outputs_infer = bn.apply(inputs, training=False) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([bn.gamma, bn.beta]) @@ -694,7 +694,7 @@ class BNTest(test.TestCase): beta = all_vars['bn/beta:0'] gamma = all_vars['bn/gamma:0'] - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) np_gamma, np_beta = sess.run([gamma, beta]) @@ -756,7 +756,7 @@ class BNTest(test.TestCase): beta = all_vars['bn/beta:0'] gamma = all_vars['bn/gamma:0'] - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) for _ in range(100): @@ -1254,7 +1254,7 @@ class BNTest(test.TestCase): training = array_ops.placeholder(dtype='bool') outputs = bn.apply(inputs, training=training) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) @@ -1294,7 +1294,7 @@ class BNTest(test.TestCase): training = array_ops.placeholder(dtype='bool') outputs = bn.apply(inputs, training=training) - with self.test_session() as sess: + with self.cached_session() as sess: # Test training with placeholder learning phase. sess.run(variables.global_variables_initializer()) -- cgit v1.2.3