diff options
author | A. Unique TensorFlower <gardener@tensorflow.org> | 2018-08-22 15:16:32 -0700 |
---|---|---|
committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-08-22 15:42:20 -0700 |
commit | 8b3e40586af915c4d59cd5233c8f937659a15d37 (patch) | |
tree | 929b1865e22ccea93cf82b3d71da7ec1008cded8 /tensorflow/contrib/distributions | |
parent | b2530e2b40b3c55c7121508b224ee1d9ed1bad27 (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: 209839048
Diffstat (limited to 'tensorflow/contrib/distributions')
24 files changed, 125 insertions, 125 deletions
diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/absolute_value_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/absolute_value_test.py index 042c8ebd51..372b7e37b7 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/absolute_value_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/absolute_value_test.py @@ -31,7 +31,7 @@ class AbsoluteValueTest(test.TestCase): """Tests correctness of the absolute value bijector.""" def testBijectorVersusNumpyRewriteOfBasicFunctionsEventNdims0(self): - with self.test_session() as sess: + with self.cached_session() as sess: bijector = AbsoluteValue(validate_args=True) self.assertEqual("absolute_value", bijector.name) x = array_ops.constant([[0., 1., -1], [0., -5., 3.]]) # Shape [2, 3] @@ -54,13 +54,13 @@ class AbsoluteValueTest(test.TestCase): y, event_ndims=0))) def testNegativeYRaisesForInverseIfValidateArgs(self): - with self.test_session() as sess: + with self.cached_session() as sess: bijector = AbsoluteValue(validate_args=True) with self.assertRaisesOpError("y was negative"): sess.run(bijector.inverse(-1.)) def testNegativeYRaisesForILDJIfValidateArgs(self): - with self.test_session() as sess: + with self.cached_session() as sess: bijector = AbsoluteValue(validate_args=True) with self.assertRaisesOpError("y was negative"): sess.run(bijector.inverse_log_det_jacobian(-1., event_ndims=0)) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_linear_operator_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_linear_operator_test.py index 1e4ad724d0..a7bd51430e 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_linear_operator_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_linear_operator_test.py @@ -28,7 +28,7 @@ from tensorflow.python.platform import test class AffineLinearOperatorTest(test.TestCase): def testIdentity(self): - with self.test_session(): + with self.cached_session(): affine = AffineLinearOperator( validate_args=True) x = np.array([[1, 0, -1], [2, 3, 4]], dtype=np.float32) @@ -45,7 +45,7 @@ class AffineLinearOperatorTest(test.TestCase): affine.forward_log_det_jacobian(x, event_ndims=2).eval()) def testDiag(self): - with self.test_session(): + with self.cached_session(): shift = np.array([-1, 0, 1], dtype=np.float32) diag = np.array([[1, 2, 3], [2, 5, 6]], dtype=np.float32) @@ -67,7 +67,7 @@ class AffineLinearOperatorTest(test.TestCase): affine.forward_log_det_jacobian(x, event_ndims=1).eval()) def testTriL(self): - with self.test_session(): + with self.cached_session(): shift = np.array([-1, 0, 1], dtype=np.float32) tril = np.array([[[3, 0, 0], [2, -1, 0], diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_scalar_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_scalar_test.py index d2533620be..bc6752a69d 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_scalar_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_scalar_test.py @@ -31,14 +31,14 @@ class AffineScalarBijectorTest(test.TestCase): """Tests correctness of the Y = scale @ x + shift transformation.""" def testProperties(self): - with self.test_session(): + with self.cached_session(): mu = -1. # scale corresponds to 1. bijector = AffineScalar(shift=mu) self.assertEqual("affine_scalar", bijector.name) def testNoBatchScalar(self): - with self.test_session() as sess: + with self.cached_session() as sess: def static_run(fun, x, **kwargs): return fun(x, **kwargs).eval() @@ -60,7 +60,7 @@ class AffineScalarBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=0)) def testOneBatchScalarViaIdentityIn64BitUserProvidesShiftOnly(self): - with self.test_session() as sess: + with self.cached_session() as sess: def static_run(fun, x, **kwargs): return fun(x, **kwargs).eval() @@ -83,7 +83,7 @@ class AffineScalarBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=0)) def testOneBatchScalarViaIdentityIn64BitUserProvidesScaleOnly(self): - with self.test_session() as sess: + with self.cached_session() as sess: def static_run(fun, x, **kwargs): return fun(x, **kwargs).eval() @@ -106,7 +106,7 @@ class AffineScalarBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=0)) def testTwoBatchScalarIdentityViaIdentity(self): - with self.test_session() as sess: + with self.cached_session() as sess: def static_run(fun, x, **kwargs): return fun(x, **kwargs).eval() @@ -129,7 +129,7 @@ class AffineScalarBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=0)) def testTwoBatchScalarIdentityViaScale(self): - with self.test_session() as sess: + with self.cached_session() as sess: def static_run(fun, x, **kwargs): return fun(x, **kwargs).eval() @@ -152,7 +152,7 @@ class AffineScalarBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=0)) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): bijector = AffineScalar(shift=3.6, scale=0.42) assert_scalar_congruency(bijector, lower_x=-2., upper_x=2.) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_test.py index 9e14b9a53e..dc18eb3df6 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_test.py @@ -32,14 +32,14 @@ class AffineBijectorTest(test.TestCase): """Tests correctness of the Y = scale @ x + shift transformation.""" def testProperties(self): - with self.test_session(): + with self.cached_session(): mu = -1. # scale corresponds to 1. bijector = Affine(shift=mu) self.assertEqual("affine", bijector.name) def testNoBatchMultivariateIdentity(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -71,7 +71,7 @@ class AffineBijectorTest(test.TestCase): 0., run(bijector.inverse_log_det_jacobian, x, event_ndims=1)) def testNoBatchMultivariateDiag(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -114,7 +114,7 @@ class AffineBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=1)) def testNoBatchMultivariateFullDynamic(self): - with self.test_session() as sess: + with self.cached_session() as sess: x = array_ops.placeholder(dtypes.float32, name="x") mu = array_ops.placeholder(dtypes.float32, name="mu") scale_diag = array_ops.placeholder(dtypes.float32, name="scale_diag") @@ -137,7 +137,7 @@ class AffineBijectorTest(test.TestCase): feed_dict)) def testBatchMultivariateIdentity(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -161,7 +161,7 @@ class AffineBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=1)) def testBatchMultivariateDiag(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -185,7 +185,7 @@ class AffineBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=1)) def testBatchMultivariateFullDynamic(self): - with self.test_session() as sess: + with self.cached_session() as sess: x = array_ops.placeholder(dtypes.float32, name="x") mu = array_ops.placeholder(dtypes.float32, name="mu") scale_diag = array_ops.placeholder(dtypes.float32, name="scale_diag") @@ -209,7 +209,7 @@ class AffineBijectorTest(test.TestCase): x, event_ndims=1), feed_dict)) def testIdentityWithDiagUpdate(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -235,7 +235,7 @@ class AffineBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=1)) def testIdentityWithTriL(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -261,7 +261,7 @@ class AffineBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=1)) def testDiagWithTriL(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -285,7 +285,7 @@ class AffineBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=1)) def testIdentityAndDiagWithTriL(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -312,7 +312,7 @@ class AffineBijectorTest(test.TestCase): run(bijector.inverse_log_det_jacobian, x, event_ndims=1)) def testIdentityWithVDVTUpdate(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -349,7 +349,7 @@ class AffineBijectorTest(test.TestCase): run(bijector_ref.inverse_log_det_jacobian, x, event_ndims=1)) def testDiagWithVDVTUpdate(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -385,7 +385,7 @@ class AffineBijectorTest(test.TestCase): run(bijector_ref.inverse_log_det_jacobian, x, event_ndims=1)) def testTriLWithVDVTUpdate(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -422,7 +422,7 @@ class AffineBijectorTest(test.TestCase): run(bijector_ref.inverse_log_det_jacobian, x, event_ndims=1)) def testTriLWithVDVTUpdateNoDiagonal(self): - with self.test_session() as sess: + with self.cached_session() as sess: placeholder = array_ops.placeholder(dtypes.float32, name="x") def static_run(fun, x, **kwargs): @@ -459,7 +459,7 @@ class AffineBijectorTest(test.TestCase): run(bijector_ref.inverse_log_det_jacobian, x, event_ndims=1)) def testNoBatchMultivariateRaisesWhenSingular(self): - with self.test_session(): + with self.cached_session(): mu = [1., -1] bijector = Affine( shift=mu, @@ -531,7 +531,7 @@ class AffineBijectorTest(test.TestCase): itertools.combinations(s, r) for r in range(len(s) + 1)) for args in _powerset(scale_params.items()): - with self.test_session(): + with self.cached_session(): args = dict(args) scale_args = dict({"x": x}, **args) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/batch_normalization_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/batch_normalization_test.py index c832fcaa68..bf61e9f2fe 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/batch_normalization_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/batch_normalization_test.py @@ -69,7 +69,7 @@ class BatchNormTest(test_util.VectorDistributionTestHelpers, ] for input_shape, event_dims, training in params: x_ = np.arange(5 * 4 * 2).astype(np.float32).reshape(input_shape) - with self.test_session() as sess: + with self.cached_session() as sess: x = constant_op.constant(x_) # When training, memorize the exact mean of the last # minibatch that it normalized (instead of moving average assignment). @@ -145,7 +145,7 @@ class BatchNormTest(test_util.VectorDistributionTestHelpers, def testMaximumLikelihoodTraining(self): # Test Maximum Likelihood training with default bijector. - with self.test_session() as sess: + with self.cached_session() as sess: base_dist = distributions.MultivariateNormalDiag(loc=[0., 0.]) batch_norm = BatchNormalization(training=True) dist = transformed_distribution_lib.TransformedDistribution( @@ -176,7 +176,7 @@ class BatchNormTest(test_util.VectorDistributionTestHelpers, self.assertAllClose([1., 1.], moving_var_, atol=5e-2) def testLogProb(self): - with self.test_session() as sess: + with self.cached_session() as sess: layer = normalization.BatchNormalization(epsilon=0.) batch_norm = BatchNormalization(batchnorm_layer=layer, training=False) base_dist = distributions.MultivariateNormalDiag(loc=[0., 0.]) @@ -196,7 +196,7 @@ class BatchNormTest(test_util.VectorDistributionTestHelpers, def testMutuallyConsistent(self): # BatchNorm bijector is only mutually consistent when training=False. dims = 4 - with self.test_session() as sess: + with self.cached_session() as sess: layer = normalization.BatchNormalization(epsilon=0.) batch_norm = BatchNormalization(batchnorm_layer=layer, training=False) dist = transformed_distribution_lib.TransformedDistribution( @@ -215,7 +215,7 @@ class BatchNormTest(test_util.VectorDistributionTestHelpers, def testInvertMutuallyConsistent(self): # BatchNorm bijector is only mutually consistent when training=False. dims = 4 - with self.test_session() as sess: + with self.cached_session() as sess: layer = normalization.BatchNormalization(epsilon=0.) batch_norm = Invert( BatchNormalization(batchnorm_layer=layer, training=False)) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/chain_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/chain_test.py index dc45114b1c..ada99ec9c6 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/chain_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/chain_test.py @@ -46,7 +46,7 @@ class ChainBijectorTest(test.TestCase): """Tests the correctness of the Y = Chain(bij1, bij2, bij3) transformation.""" def testBijector(self): - with self.test_session(): + with self.cached_session(): chain = Chain((Exp(), Softplus())) self.assertEqual("chain_of_exp_of_softplus", chain.name) x = np.asarray([[[1., 2.], @@ -61,7 +61,7 @@ class ChainBijectorTest(test.TestCase): chain.forward_log_det_jacobian(x, event_ndims=1).eval()) def testBijectorIdentity(self): - with self.test_session(): + with self.cached_session(): chain = Chain() self.assertEqual("identity", chain.name) x = np.asarray([[[1., 2.], @@ -74,13 +74,13 @@ class ChainBijectorTest(test.TestCase): 0., chain.forward_log_det_jacobian(x, event_ndims=1).eval()) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): chain = Chain((Exp(), Softplus())) assert_scalar_congruency( chain, lower_x=1e-3, upper_x=1.5, rtol=0.05) def testShapeGetters(self): - with self.test_session(): + with self.cached_session(): chain = Chain([ SoftmaxCentered(validate_args=True), SoftmaxCentered(validate_args=True), @@ -195,7 +195,7 @@ class ChainBijectorTest(test.TestCase): dtype=np.float32, shape=[None, 10], name="samples") ildj = chain.inverse_log_det_jacobian(samples, event_ndims=0) self.assertTrue(ildj is not None) - with self.test_session(): + with self.cached_session(): ildj.eval({samples: np.zeros([2, 10], np.float32)}) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/cholesky_outer_product_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/cholesky_outer_product_test.py index d1ce273499..9681b64ced 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/cholesky_outer_product_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/cholesky_outer_product_test.py @@ -30,7 +30,7 @@ class CholeskyOuterProductBijectorTest(test.TestCase): """Tests the correctness of the Y = X @ X.T transformation.""" def testBijectorMatrix(self): - with self.test_session(): + with self.cached_session(): bijector = bijectors.CholeskyOuterProduct(validate_args=True) self.assertEqual("cholesky_outer_product", bijector.name) x = [[[1., 0], [2, 1]], [[np.sqrt(2.), 0], [np.sqrt(8.), 1]]] @@ -75,7 +75,7 @@ class CholeskyOuterProductBijectorTest(test.TestCase): bijector = bijectors.CholeskyOuterProduct() x_pl = array_ops.placeholder(dtypes.float32) - with self.test_session(): + with self.cached_session(): log_det_jacobian = bijector.forward_log_det_jacobian(x_pl, event_ndims=2) # The Jacobian matrix is 2 * tf.eye(2), which has jacobian determinant 4. @@ -86,7 +86,7 @@ class CholeskyOuterProductBijectorTest(test.TestCase): def testNoBatchStatic(self): x = np.array([[1., 0], [2, 1]]) # np.linalg.cholesky(y) y = np.array([[1., 2], [2, 5]]) # np.matmul(x, x.T) - with self.test_session() as sess: + with self.cached_session() as sess: y_actual = bijectors.CholeskyOuterProduct().forward(x=x) x_actual = bijectors.CholeskyOuterProduct().inverse(y=y) [y_actual_, x_actual_] = sess.run([y_actual, x_actual]) @@ -98,7 +98,7 @@ class CholeskyOuterProductBijectorTest(test.TestCase): def testNoBatchDeferred(self): x = np.array([[1., 0], [2, 1]]) # np.linalg.cholesky(y) y = np.array([[1., 2], [2, 5]]) # np.matmul(x, x.T) - with self.test_session() as sess: + with self.cached_session() as sess: x_pl = array_ops.placeholder(dtypes.float32) y_pl = array_ops.placeholder(dtypes.float32) y_actual = bijectors.CholeskyOuterProduct().forward(x=x_pl) @@ -119,7 +119,7 @@ class CholeskyOuterProductBijectorTest(test.TestCase): [2, 5]], [[9., 3], [3, 5]]]) # np.matmul(x, x.T) - with self.test_session() as sess: + with self.cached_session() as sess: y_actual = bijectors.CholeskyOuterProduct().forward(x=x) x_actual = bijectors.CholeskyOuterProduct().inverse(y=y) [y_actual_, x_actual_] = sess.run([y_actual, x_actual]) @@ -137,7 +137,7 @@ class CholeskyOuterProductBijectorTest(test.TestCase): [2, 5]], [[9., 3], [3, 5]]]) # np.matmul(x, x.T) - with self.test_session() as sess: + with self.cached_session() as sess: x_pl = array_ops.placeholder(dtypes.float32) y_pl = array_ops.placeholder(dtypes.float32) y_actual = bijectors.CholeskyOuterProduct().forward(x=x_pl) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/exp_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/exp_test.py index 7be939cd27..d2c00865e7 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/exp_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/exp_test.py @@ -30,7 +30,7 @@ class ExpBijectorTest(test.TestCase): """Tests correctness of the Y = g(X) = exp(X) transformation.""" def testBijector(self): - with self.test_session(): + with self.cached_session(): bijector = Exp() self.assertEqual("exp", bijector.name) x = [[[1.], [2.]]] @@ -48,13 +48,13 @@ class ExpBijectorTest(test.TestCase): x, event_ndims=1).eval()) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): bijector = Exp() assert_scalar_congruency( bijector, lower_x=-2., upper_x=1.5, rtol=0.05) def testBijectiveAndFinite(self): - with self.test_session(): + with self.cached_session(): bijector = Exp() x = np.linspace(-10, 10, num=10).astype(np.float32) y = np.logspace(-10, 10, num=10).astype(np.float32) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/gumbel_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/gumbel_test.py index 54e54c3296..b9cdbfb823 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/gumbel_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/gumbel_test.py @@ -31,7 +31,7 @@ class GumbelBijectorTest(test.TestCase): """Tests correctness of the Gumbel bijector.""" def testBijector(self): - with self.test_session(): + with self.cached_session(): loc = 0.3 scale = 5. bijector = Gumbel(loc=loc, scale=scale, validate_args=True) @@ -52,12 +52,12 @@ class GumbelBijectorTest(test.TestCase): atol=0.) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): assert_scalar_congruency( Gumbel(loc=0.3, scale=20.), lower_x=1., upper_x=100., rtol=0.02) def testBijectiveAndFinite(self): - with self.test_session(): + with self.cached_session(): bijector = Gumbel(loc=0., scale=3.0, validate_args=True) x = np.linspace(-10., 10., num=10).astype(np.float32) y = np.linspace(0.01, 0.99, num=10).astype(np.float32) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/inline_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/inline_test.py index 7d3bd758cd..c9bccb36fc 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/inline_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/inline_test.py @@ -32,7 +32,7 @@ class InlineBijectorTest(test.TestCase): """Tests correctness of the inline constructed bijector.""" def testBijector(self): - with self.test_session(): + with self.cached_session(): exp = Exp() inline = Inline( forward_fn=math_ops.exp, @@ -55,7 +55,7 @@ class InlineBijectorTest(test.TestCase): inline.forward_log_det_jacobian(x, event_ndims=1).eval()) def testShapeGetters(self): - with self.test_session(): + with self.cached_session(): bijector = Inline( forward_event_shape_tensor_fn=lambda x: array_ops.concat((x, [1]), 0), forward_event_shape_fn=lambda x: x.as_list() + [1], diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/invert_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/invert_test.py index 8b14c8327f..7e3340aeb0 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/invert_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/invert_test.py @@ -31,7 +31,7 @@ class InvertBijectorTest(test.TestCase): """Tests the correctness of the Y = Invert(bij) transformation.""" def testBijector(self): - with self.test_session(): + with self.cached_session(): for fwd in [ bijectors.Identity(), bijectors.Exp(), @@ -53,13 +53,13 @@ class InvertBijectorTest(test.TestCase): rev.forward_log_det_jacobian(x, event_ndims=1).eval()) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): bijector = bijectors.Invert(bijectors.Exp()) assert_scalar_congruency( bijector, lower_x=1e-3, upper_x=1.5, rtol=0.05) def testShapeGetters(self): - with self.test_session(): + with self.cached_session(): bijector = bijectors.Invert(bijectors.SoftmaxCentered(validate_args=True)) x = tensor_shape.TensorShape([2]) y = tensor_shape.TensorShape([1]) @@ -73,7 +73,7 @@ class InvertBijectorTest(test.TestCase): bijector.inverse_event_shape_tensor(y.as_list()).eval()) def testDocstringExample(self): - with self.test_session(): + with self.cached_session(): exp_gamma_distribution = ( transformed_distribution_lib.TransformedDistribution( distribution=gamma_lib.Gamma(concentration=1., rate=2.), diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/kumaraswamy_bijector_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/kumaraswamy_bijector_test.py index a8089881f6..b3fb50005e 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/kumaraswamy_bijector_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/kumaraswamy_bijector_test.py @@ -30,7 +30,7 @@ class KumaraswamyBijectorTest(test.TestCase): """Tests correctness of the Kumaraswamy bijector.""" def testBijector(self): - with self.test_session(): + with self.cached_session(): a = 2. b = 0.3 bijector = Kumaraswamy( @@ -54,13 +54,13 @@ class KumaraswamyBijectorTest(test.TestCase): atol=0.) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): assert_scalar_congruency( Kumaraswamy(concentration1=0.5, concentration0=1.1), lower_x=0., upper_x=1., n=int(10e3), rtol=0.02) def testBijectiveAndFinite(self): - with self.test_session(): + with self.cached_session(): concentration1 = 1.2 concentration0 = 2. bijector = Kumaraswamy( diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/masked_autoregressive_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/masked_autoregressive_test.py index 5ba5a2083b..ad4329d425 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/masked_autoregressive_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/masked_autoregressive_test.py @@ -71,7 +71,7 @@ class MaskedAutoregressiveFlowTest(test_util.VectorDistributionTestHelpers, def testBijector(self): x_ = np.arange(3 * 4 * 2).astype(np.float32).reshape(3, 4, 2) - with self.test_session() as sess: + with self.cached_session() as sess: ma = MaskedAutoregressiveFlow( validate_args=True, **self._autoregressive_flow_kwargs) @@ -102,7 +102,7 @@ class MaskedAutoregressiveFlowTest(test_util.VectorDistributionTestHelpers, def testMutuallyConsistent(self): dims = 4 - with self.test_session() as sess: + with self.cached_session() as sess: ma = MaskedAutoregressiveFlow( validate_args=True, **self._autoregressive_flow_kwargs) @@ -121,7 +121,7 @@ class MaskedAutoregressiveFlowTest(test_util.VectorDistributionTestHelpers, def testInvertMutuallyConsistent(self): dims = 4 - with self.test_session() as sess: + with self.cached_session() as sess: ma = Invert(MaskedAutoregressiveFlow( validate_args=True, **self._autoregressive_flow_kwargs)) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ordered_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ordered_test.py index cb42331a21..a188843952 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ordered_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ordered_test.py @@ -38,7 +38,7 @@ class OrderedBijectorTest(test.TestCase): @test_util.run_in_graph_and_eager_modes def testBijectorVector(self): - with self.test_session(): + with self.cached_session(): ordered = Ordered() self.assertEqual("ordered", ordered.name) x = np.asarray([[2., 3, 4], [4., 8, 13]]) @@ -57,7 +57,7 @@ class OrderedBijectorTest(test.TestCase): rtol=1e-7) def testBijectorUnknownShape(self): - with self.test_session(): + with self.cached_session(): ordered = Ordered() self.assertEqual("ordered", ordered.name) x = array_ops.placeholder(shape=[2, None], dtype=dtypes.float32) @@ -84,7 +84,7 @@ class OrderedBijectorTest(test.TestCase): @test_util.run_in_graph_and_eager_modes def testShapeGetters(self): - with self.test_session(): + with self.cached_session(): x = tensor_shape.TensorShape([4]) y = tensor_shape.TensorShape([4]) bijector = Ordered(validate_args=True) @@ -98,7 +98,7 @@ class OrderedBijectorTest(test.TestCase): y.as_list()))) def testBijectiveAndFinite(self): - with self.test_session(): + with self.cached_session(): ordered = Ordered() x = np.sort(self._rng.randn(3, 10), axis=-1).astype(np.float32) y = (self._rng.randn(3, 10)).astype(np.float32) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/permute_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/permute_test.py index 7eef4ab599..e2062ed55d 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/permute_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/permute_test.py @@ -38,7 +38,7 @@ class PermuteBijectorTest(test.TestCase): expected_x = np.random.randn(4, 2, 3) expected_y = expected_x[..., expected_permutation] - with self.test_session() as sess: + with self.cached_session() as sess: permutation_ph = array_ops.placeholder(dtype=dtypes.int32) bijector = Permute( permutation=permutation_ph, @@ -64,7 +64,7 @@ class PermuteBijectorTest(test.TestCase): self.assertAllClose(0., ildj, rtol=1e-6, atol=0) def testRaisesOpError(self): - with self.test_session() as sess: + with self.cached_session() as sess: with self.assertRaisesOpError("Permutation over `d` must contain"): permutation_ph = array_ops.placeholder(dtype=dtypes.int32) bijector = Permute( @@ -77,7 +77,7 @@ class PermuteBijectorTest(test.TestCase): permutation = np.int32([2, 0, 1]) x = np.random.randn(4, 2, 3) y = x[..., permutation] - with self.test_session(): + with self.cached_session(): bijector = Permute(permutation=permutation, validate_args=True) assert_bijective_and_finite( bijector, x, y, event_ndims=1, rtol=1e-6, atol=0) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/power_transform_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/power_transform_test.py index 85d2283013..ef303ab664 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/power_transform_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/power_transform_test.py @@ -30,7 +30,7 @@ class PowerTransformBijectorTest(test.TestCase): """Tests correctness of the power transformation.""" def testBijector(self): - with self.test_session(): + with self.cached_session(): c = 0.2 bijector = PowerTransform(power=c, validate_args=True) self.assertEqual("power_transform", bijector.name) @@ -48,13 +48,13 @@ class PowerTransformBijectorTest(test.TestCase): atol=0.) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): bijector = PowerTransform(power=0.2, validate_args=True) assert_scalar_congruency( bijector, lower_x=-2., upper_x=1.5, rtol=0.05) def testBijectiveAndFinite(self): - with self.test_session(): + with self.cached_session(): bijector = PowerTransform(power=0.2, validate_args=True) x = np.linspace(-4.999, 10, num=10).astype(np.float32) y = np.logspace(0.001, 10, num=10).astype(np.float32) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/real_nvp_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/real_nvp_test.py index 2d52895fbe..b3b7b8535e 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/real_nvp_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/real_nvp_test.py @@ -43,7 +43,7 @@ class RealNVPTest(test_util.VectorDistributionTestHelpers, test.TestCase): def testBijector(self): x_ = np.arange(3 * 4 * 2).astype(np.float32).reshape(3, 4 * 2) - with self.test_session() as sess: + with self.cached_session() as sess: nvp = RealNVP( num_masked=4, validate_args=True, @@ -78,7 +78,7 @@ class RealNVPTest(test_util.VectorDistributionTestHelpers, test.TestCase): def testMutuallyConsistent(self): dims = 4 - with self.test_session() as sess: + with self.cached_session() as sess: nvp = RealNVP( num_masked=3, validate_args=True, @@ -98,7 +98,7 @@ class RealNVPTest(test_util.VectorDistributionTestHelpers, test.TestCase): def testInvertMutuallyConsistent(self): dims = 4 - with self.test_session() as sess: + with self.cached_session() as sess: nvp = Invert(RealNVP( num_masked=3, validate_args=True, diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/reshape_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/reshape_test.py index d44e49b487..79eadf524b 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/reshape_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/reshape_test.py @@ -50,7 +50,7 @@ class _ReshapeBijectorTest(object): expected_x = np.random.randn(4, 3, 2) expected_y = np.reshape(expected_x, [4, 6]) - with self.test_session() as sess: + with self.cached_session() as sess: shape_in, shape_out, feed_dict = self.build_shapes([3, 2], [6,]) bijector = Reshape( event_shape_out=shape_out, @@ -84,7 +84,7 @@ class _ReshapeBijectorTest(object): # using the _tensor methods, we should always get a fully-specified # result since these are evaluated at graph runtime. - with self.test_session() as sess: + with self.cached_session() as sess: (shape_out_, shape_in_) = sess.run(( bijector.forward_event_shape_tensor(shape_in), @@ -103,7 +103,7 @@ class _ReshapeBijectorTest(object): expected_y_scalar = expected_x_scalar[0] shape_in, shape_out, feed_dict = self.build_shapes([], [1,]) - with self.test_session() as sess: + with self.cached_session() as sess: bijector = Reshape( event_shape_out=shape_in, event_shape_in=shape_out, validate_args=True) @@ -124,7 +124,7 @@ class _ReshapeBijectorTest(object): def testMultipleUnspecifiedDimensionsOpError(self): - with self.test_session() as sess: + with self.cached_session() as sess: shape_in, shape_out, feed_dict = self.build_shapes([2, 3], [4, -1, -1,]) bijector = Reshape( event_shape_out=shape_out, @@ -139,7 +139,7 @@ class _ReshapeBijectorTest(object): # pylint: disable=invalid-name def _testInvalidDimensionsOpError(self, expected_error_message): - with self.test_session() as sess: + with self.cached_session() as sess: shape_in, shape_out, feed_dict = self.build_shapes([2, 3], [1, 2, -2,]) bijector = Reshape( @@ -155,7 +155,7 @@ class _ReshapeBijectorTest(object): def testValidButNonMatchingInputOpError(self): x = np.random.randn(4, 3, 2) - with self.test_session() as sess: + with self.cached_session() as sess: shape_in, shape_out, feed_dict = self.build_shapes([2, 3], [1, 6, 1,]) bijector = Reshape( event_shape_out=shape_out, @@ -173,7 +173,7 @@ class _ReshapeBijectorTest(object): def testValidButNonMatchingInputPartiallySpecifiedOpError(self): x = np.random.randn(4, 3, 2) - with self.test_session() as sess: + with self.cached_session() as sess: shape_in, shape_out, feed_dict = self.build_shapes([2, -1], [1, 6, 1,]) bijector = Reshape( event_shape_out=shape_out, @@ -190,7 +190,7 @@ class _ReshapeBijectorTest(object): x1 = np.random.randn(4, 2, 3) x2 = np.random.randn(4, 1, 1, 5) - with self.test_session() as sess: + with self.cached_session() as sess: shape_in, shape_out, fd_mismatched = self.build_shapes([2, 3], [1, 1, 5]) bijector = Reshape( @@ -208,7 +208,7 @@ class _ReshapeBijectorTest(object): expected_x = np.random.randn(4, 6) expected_y = np.reshape(expected_x, [4, 2, 3]) - with self.test_session() as sess: + with self.cached_session() as sess: # one of input/output shapes is partially specified shape_in, shape_out, feed_dict = self.build_shapes([-1,], [2, 3]) bijector = Reshape( @@ -227,7 +227,7 @@ class _ReshapeBijectorTest(object): def testBothShapesPartiallySpecified(self): expected_x = np.random.randn(4, 2, 3) expected_y = np.reshape(expected_x, [4, 3, 2]) - with self.test_session() as sess: + with self.cached_session() as sess: shape_in, shape_out, feed_dict = self.build_shapes([-1, 3], [-1, 2]) bijector = Reshape( event_shape_out=shape_out, @@ -245,7 +245,7 @@ class _ReshapeBijectorTest(object): def testDefaultVectorShape(self): expected_x = np.random.randn(4, 4) expected_y = np.reshape(expected_x, [4, 2, 2]) - with self.test_session() as sess: + with self.cached_session() as sess: _, shape_out, feed_dict = self.build_shapes([-1,], [-1, 2]) bijector = Reshape(shape_out, validate_args=True) @@ -292,7 +292,7 @@ class ReshapeBijectorTestStatic(test.TestCase, _ReshapeBijectorTest): def testBijectiveAndFinite(self): x = np.random.randn(4, 2, 3) y = np.reshape(x, [4, 1, 2, 3]) - with self.test_session(): + with self.cached_session(): bijector = Reshape( event_shape_in=[2, 3], event_shape_out=[1, 2, 3], diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/sigmoid_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/sigmoid_test.py index cea4a62c22..a6d432753d 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/sigmoid_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/sigmoid_test.py @@ -31,7 +31,7 @@ class SigmoidBijectorTest(test.TestCase): """Tests correctness of the Y = g(X) = (1 + exp(-X))^-1 transformation.""" def testBijector(self): - with self.test_session(): + with self.cached_session(): self.assertEqual("sigmoid", Sigmoid().name) x = np.linspace(-10., 10., 100).reshape([2, 5, 10]).astype(np.float32) y = special.expit(x) @@ -45,11 +45,11 @@ class SigmoidBijectorTest(test.TestCase): x, event_ndims=0).eval(), atol=0., rtol=1e-4) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): assert_scalar_congruency(Sigmoid(), lower_x=-7., upper_x=7.) def testBijectiveAndFinite(self): - with self.test_session(): + with self.cached_session(): x = np.linspace(-7., 7., 100).astype(np.float32) eps = 1e-3 y = np.linspace(eps, 1. - eps, 100).astype(np.float32) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/sinh_arcsinh_bijector_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/sinh_arcsinh_bijector_test.py index 795f1993ba..282619a73b 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/sinh_arcsinh_bijector_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/sinh_arcsinh_bijector_test.py @@ -33,7 +33,7 @@ class SinhArcsinhBijectorTest(test.TestCase): """Tests correctness of the power transformation.""" def testBijectorVersusNumpyRewriteOfBasicFunctions(self): - with self.test_session(): + with self.cached_session(): skewness = 0.2 tailweight = 2.0 bijector = SinhArcsinh( @@ -58,7 +58,7 @@ class SinhArcsinhBijectorTest(test.TestCase): atol=0.) def testLargerTailWeightPutsMoreWeightInTails(self): - with self.test_session(): + with self.cached_session(): # Will broadcast together to shape [3, 2]. x = [-1., 1.] tailweight = [[0.5], [1.0], [2.0]] @@ -75,7 +75,7 @@ class SinhArcsinhBijectorTest(test.TestCase): self.assertLess(forward_1[1], forward_1[2]) def testSkew(self): - with self.test_session(): + with self.cached_session(): # Will broadcast together to shape [3, 2]. x = [-1., 1.] skewness = [[-1.], [0.], [1.]] @@ -92,24 +92,24 @@ class SinhArcsinhBijectorTest(test.TestCase): self.assertLess(np.abs(y[2, 0]), np.abs(y[2, 1])) def testScalarCongruencySkewness1Tailweight0p5(self): - with self.test_session(): + with self.cached_session(): bijector = SinhArcsinh(skewness=1.0, tailweight=0.5, validate_args=True) assert_scalar_congruency(bijector, lower_x=-2., upper_x=2.0, rtol=0.05) def testScalarCongruencySkewnessNeg1Tailweight1p5(self): - with self.test_session(): + with self.cached_session(): bijector = SinhArcsinh(skewness=-1.0, tailweight=1.5, validate_args=True) assert_scalar_congruency(bijector, lower_x=-2., upper_x=2.0, rtol=0.05) def testBijectiveAndFiniteSkewnessNeg1Tailweight0p5(self): - with self.test_session(): + with self.cached_session(): bijector = SinhArcsinh(skewness=-1., tailweight=0.5, validate_args=True) x = np.concatenate((-np.logspace(-2, 10, 1000), [0], np.logspace( -2, 10, 1000))).astype(np.float32) assert_bijective_and_finite(bijector, x, x, event_ndims=0, rtol=1e-3) def testBijectiveAndFiniteSkewness1Tailweight3(self): - with self.test_session(): + with self.cached_session(): bijector = SinhArcsinh(skewness=1., tailweight=3., validate_args=True) x = np.concatenate((-np.logspace(-2, 5, 1000), [0], np.logspace( -2, 5, 1000))).astype(np.float32) @@ -117,7 +117,7 @@ class SinhArcsinhBijectorTest(test.TestCase): bijector, x, x, event_ndims=0, rtol=1e-3) def testBijectorEndpoints(self): - with self.test_session(): + with self.cached_session(): for dtype in (np.float32, np.float64): bijector = SinhArcsinh( skewness=dtype(0.), tailweight=dtype(1.), validate_args=True) @@ -129,7 +129,7 @@ class SinhArcsinhBijectorTest(test.TestCase): bijector, bounds, bounds, event_ndims=0, atol=2e-6) def testBijectorOverRange(self): - with self.test_session(): + with self.cached_session(): for dtype in (np.float32, np.float64): skewness = np.array([1.2, 5.], dtype=dtype) tailweight = np.array([2., 10.], dtype=dtype) @@ -176,12 +176,12 @@ class SinhArcsinhBijectorTest(test.TestCase): atol=0.) def testZeroTailweightRaises(self): - with self.test_session(): + with self.cached_session(): with self.assertRaisesOpError("not positive"): SinhArcsinh(tailweight=0., validate_args=True).forward(1.0).eval() def testDefaultDtypeIsFloat32(self): - with self.test_session(): + with self.cached_session(): bijector = SinhArcsinh() self.assertEqual(bijector.tailweight.dtype, np.float32) self.assertEqual(bijector.skewness.dtype, np.float32) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/softmax_centered_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/softmax_centered_test.py index 0f0a2fa531..8d18400487 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/softmax_centered_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/softmax_centered_test.py @@ -35,7 +35,7 @@ class SoftmaxCenteredBijectorTest(test.TestCase): """Tests correctness of the Y = g(X) = exp(X) / sum(exp(X)) transformation.""" def testBijectorVector(self): - with self.test_session(): + with self.cached_session(): softmax = SoftmaxCentered() self.assertEqual("softmax_centered", softmax.name) x = np.log([[2., 3, 4], [4., 8, 12]]) @@ -54,7 +54,7 @@ class SoftmaxCenteredBijectorTest(test.TestCase): rtol=1e-7) def testBijectorUnknownShape(self): - with self.test_session(): + with self.cached_session(): softmax = SoftmaxCentered() self.assertEqual("softmax_centered", softmax.name) x = array_ops.placeholder(shape=[2, None], dtype=dtypes.float32) @@ -80,7 +80,7 @@ class SoftmaxCenteredBijectorTest(test.TestCase): rtol=1e-7) def testShapeGetters(self): - with self.test_session(): + with self.cached_session(): x = tensor_shape.TensorShape([4]) y = tensor_shape.TensorShape([5]) bijector = SoftmaxCentered(validate_args=True) @@ -94,7 +94,7 @@ class SoftmaxCenteredBijectorTest(test.TestCase): y.as_list()).eval()) def testBijectiveAndFinite(self): - with self.test_session(): + with self.cached_session(): softmax = SoftmaxCentered() x = np.linspace(-50, 50, num=10).reshape(5, 2).astype(np.float32) # Make y values on the simplex with a wide range. diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/softplus_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/softplus_test.py index 3d8a0a32bb..e805619041 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/softplus_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/softplus_test.py @@ -42,13 +42,13 @@ class SoftplusBijectorTest(test.TestCase): return -np.log(1 - np.exp(-y)) def testHingeSoftnessZeroRaises(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus(hinge_softness=0., validate_args=True) with self.assertRaisesOpError("must be non-zero"): bijector.forward([1., 1.]).eval() def testBijectorForwardInverseEventDimsZero(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus() self.assertEqual("softplus", bijector.name) x = 2 * rng.randn(2, 10) @@ -58,7 +58,7 @@ class SoftplusBijectorTest(test.TestCase): self.assertAllClose(x, bijector.inverse(y).eval()) def testBijectorForwardInverseWithHingeSoftnessEventDimsZero(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus(hinge_softness=1.5) x = 2 * rng.randn(2, 10) y = 1.5 * self._softplus(x / 1.5) @@ -67,7 +67,7 @@ class SoftplusBijectorTest(test.TestCase): self.assertAllClose(x, bijector.inverse(y).eval()) def testBijectorLogDetJacobianEventDimsZero(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus() y = 2 * rng.rand(2, 10) # No reduction needed if event_dims = 0. @@ -77,7 +77,7 @@ class SoftplusBijectorTest(test.TestCase): y, event_ndims=0).eval()) def testBijectorForwardInverseEventDimsOne(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus() self.assertEqual("softplus", bijector.name) x = 2 * rng.randn(2, 10) @@ -87,7 +87,7 @@ class SoftplusBijectorTest(test.TestCase): self.assertAllClose(x, bijector.inverse(y).eval()) def testBijectorLogDetJacobianEventDimsOne(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus() y = 2 * rng.rand(2, 10) ildj_before = self._softplus_ildj_before_reduction(y) @@ -97,25 +97,25 @@ class SoftplusBijectorTest(test.TestCase): y, event_ndims=1).eval()) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus() assert_scalar_congruency( bijector, lower_x=-2., upper_x=2.) def testScalarCongruencyWithPositiveHingeSoftness(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus(hinge_softness=1.3) assert_scalar_congruency( bijector, lower_x=-2., upper_x=2.) def testScalarCongruencyWithNegativeHingeSoftness(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus(hinge_softness=-1.3) assert_scalar_congruency( bijector, lower_x=-2., upper_x=2.) def testBijectiveAndFinite32bit(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus() x = np.linspace(-20., 20., 100).astype(np.float32) y = np.logspace(-10, 10, 100).astype(np.float32) @@ -123,7 +123,7 @@ class SoftplusBijectorTest(test.TestCase): bijector, x, y, event_ndims=0, rtol=1e-2, atol=1e-2) def testBijectiveAndFiniteWithPositiveHingeSoftness32Bit(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus(hinge_softness=1.23) x = np.linspace(-20., 20., 100).astype(np.float32) y = np.logspace(-10, 10, 100).astype(np.float32) @@ -131,7 +131,7 @@ class SoftplusBijectorTest(test.TestCase): bijector, x, y, event_ndims=0, rtol=1e-2, atol=1e-2) def testBijectiveAndFiniteWithNegativeHingeSoftness32Bit(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus(hinge_softness=-0.7) x = np.linspace(-20., 20., 100).astype(np.float32) y = -np.logspace(-10, 10, 100).astype(np.float32) @@ -139,7 +139,7 @@ class SoftplusBijectorTest(test.TestCase): bijector, x, y, event_ndims=0, rtol=1e-2, atol=1e-2) def testBijectiveAndFinite16bit(self): - with self.test_session(): + with self.cached_session(): bijector = Softplus() # softplus(-20) is zero, so we can't use such a large range as in 32bit. x = np.linspace(-10., 20., 100).astype(np.float16) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/square_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/square_test.py index 30c7a738c3..e5550cc830 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/square_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/square_test.py @@ -29,7 +29,7 @@ class SquareBijectorTest(test.TestCase): """Tests the correctness of the Y = X ** 2 transformation.""" def testBijectorScalar(self): - with self.test_session(): + with self.cached_session(): bijector = bijectors.Square(validate_args=True) self.assertEqual("square", bijector.name) x = [[[1., 5], @@ -50,7 +50,7 @@ class SquareBijectorTest(test.TestCase): rtol=1e-7) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): bijector = bijectors.Square(validate_args=True) assert_scalar_congruency(bijector, lower_x=1e-3, upper_x=1.5, rtol=0.05) diff --git a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/weibull_test.py b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/weibull_test.py index f57adcda89..424eb58fa0 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/weibull_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/weibull_test.py @@ -31,7 +31,7 @@ class WeibullBijectorTest(test.TestCase): """Tests correctness of the weibull bijector.""" def testBijector(self): - with self.test_session(): + with self.cached_session(): scale = 5. concentration = 0.3 bijector = Weibull( @@ -54,13 +54,13 @@ class WeibullBijectorTest(test.TestCase): atol=0.) def testScalarCongruency(self): - with self.test_session(): + with self.cached_session(): assert_scalar_congruency( Weibull(scale=20., concentration=0.3), lower_x=1., upper_x=100., rtol=0.02) def testBijectiveAndFinite(self): - with self.test_session(): + with self.cached_session(): bijector = Weibull( scale=20., concentration=2., validate_args=True) x = np.linspace(1., 8., num=10).astype(np.float32) |