diff options
Diffstat (limited to 'tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_test.py')
| -rw-r--r-- | tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_test.py | 74 |
1 files changed, 37 insertions, 37 deletions
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 295e64a0d8..71460a1769 100644 --- a/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_test.py +++ b/tensorflow/contrib/distributions/python/kernel_tests/bijectors/affine_test.py @@ -22,8 +22,8 @@ import itertools import numpy as np -from tensorflow.contrib.distributions.python.ops.bijectors.affine import Affine -from tensorflow.contrib.distributions.python.ops.bijectors.bijector_test_util import assert_scalar_congruency +from tensorflow.contrib.distributions.python.ops.bijectors import affine as affine_lib +from tensorflow.contrib.distributions.python.ops.bijectors import bijector_test_util from tensorflow.python.framework import dtypes from tensorflow.python.ops import array_ops from tensorflow.python.platform import test @@ -36,7 +36,7 @@ class AffineBijectorTest(test.TestCase): with self.test_session(): mu = -1. # scale corresponds to 1. - bijector = Affine(shift=mu, event_ndims=0) + bijector = affine_lib.Affine(shift=mu, event_ndims=0) self.assertEqual("affine", bijector.name) def testNoBatchScalarViaIdentity(self): @@ -53,7 +53,7 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # Corresponds to scale = 2 - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_identity_multiplier=2., event_ndims=0) self.assertEqual(0, bijector.event_ndims.eval()) # "is scalar" x = [1., 2, 3] # Three scalar samples (no batches). @@ -76,7 +76,7 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # Corresponds to scale = 2 - bijector = Affine(shift=mu, scale_diag=[2.], event_ndims=0) + bijector = affine_lib.Affine(shift=mu, scale_diag=[2.], event_ndims=0) self.assertEqual(0, bijector.event_ndims.eval()) # "is scalar" x = [1., 2, 3] # Three scalar samples (no batches). self.assertAllClose([1., 3, 5], run(bijector.forward, x)) @@ -98,7 +98,7 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # Corresponds to scale = 2. - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_identity_multiplier=2., event_ndims=0) self.assertEqual(0, bijector.event_ndims.eval()) # "is scalar" x = [[1., 2, 3], [4, 5, 6]] # Weird sample shape. @@ -126,7 +126,7 @@ class AffineBijectorTest(test.TestCase): mu = [1.] # One batch, scalar. # Corresponds to scale = 1. - bijector = Affine(shift=mu, event_ndims=0) + bijector = affine_lib.Affine(shift=mu, event_ndims=0) self.assertEqual(0, bijector.event_ndims.eval()) # "is scalar" x = [1.] # One sample from one batches. self.assertAllClose([2.], run(bijector.forward, x)) @@ -148,7 +148,7 @@ class AffineBijectorTest(test.TestCase): mu = [1.] # One batch, scalar. # Corresponds to scale = 1. - bijector = Affine(shift=mu, scale_diag=[1.], event_ndims=0) + bijector = affine_lib.Affine(shift=mu, scale_diag=[1.], event_ndims=0) self.assertEqual(0, bijector.event_ndims.eval()) # "is scalar" x = [1.] # One sample from one batches. self.assertAllClose([2.], run(bijector.forward, x)) @@ -170,7 +170,7 @@ class AffineBijectorTest(test.TestCase): mu = [1., -1] # Univariate, two batches. # Corresponds to scale = 1. - bijector = Affine(shift=mu, event_ndims=0) + bijector = affine_lib.Affine(shift=mu, event_ndims=0) self.assertEqual(0, bijector.event_ndims.eval()) # "is scalar" x = [1., 1] # One sample from each of two batches. self.assertAllClose([2., 0], run(bijector.forward, x)) @@ -192,7 +192,7 @@ class AffineBijectorTest(test.TestCase): mu = [1., -1] # Univariate, two batches. # Corresponds to scale = 1. - bijector = Affine(shift=mu, scale_diag=[1.], event_ndims=0) + bijector = affine_lib.Affine(shift=mu, scale_diag=[1.], event_ndims=0) self.assertEqual(0, bijector.event_ndims.eval()) # "is scalar" x = [1., 1] # One sample from each of two batches. self.assertAllClose([2., 0], run(bijector.forward, x)) @@ -214,7 +214,7 @@ class AffineBijectorTest(test.TestCase): mu = [1., -1] # Multivariate # Corresponds to scale = [[1., 0], [0, 1.]] - bijector = Affine(shift=mu) + bijector = affine_lib.Affine(shift=mu) self.assertEqual(1, bijector.event_ndims.eval()) # "is vector" x = [1., 1] # matmul(sigma, x) + shift @@ -245,7 +245,7 @@ class AffineBijectorTest(test.TestCase): mu = [1., -1] # Multivariate # Corresponds to scale = [[2., 0], [0, 1.]] - bijector = Affine(shift=mu, scale_diag=[2., 1]) + bijector = affine_lib.Affine(shift=mu, scale_diag=[2., 1]) self.assertEqual(1, bijector.event_ndims.eval()) # "is vector" x = [1., 1] # matmul(sigma, x) + shift @@ -287,7 +287,7 @@ class AffineBijectorTest(test.TestCase): event_ndims: event_ndims_value } - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_diag=scale_diag, event_ndims=event_ndims) self.assertEqual(1, sess.run(bijector.event_ndims, feed_dict)) self.assertAllClose([[3., 1]], sess.run(bijector.forward(x), feed_dict)) @@ -311,7 +311,7 @@ class AffineBijectorTest(test.TestCase): mu = [[1., -1]] # Corresponds to 1 2x2 matrix, with twos on the diagonal. scale = 2. - bijector = Affine(shift=mu, scale_identity_multiplier=scale) + bijector = affine_lib.Affine(shift=mu, scale_identity_multiplier=scale) self.assertEqual(1, bijector.event_ndims.eval()) # "is vector" x = [[[1., 1]]] self.assertAllClose([[[3., 1]]], run(bijector.forward, x)) @@ -334,7 +334,7 @@ class AffineBijectorTest(test.TestCase): mu = [[1., -1]] # Corresponds to 1 2x2 matrix, with twos on the diagonal. scale_diag = [[2., 2]] - bijector = Affine(shift=mu, scale_diag=scale_diag) + bijector = affine_lib.Affine(shift=mu, scale_diag=scale_diag) self.assertEqual(1, bijector.event_ndims.eval()) # "is vector" x = [[[1., 1]]] self.assertAllClose([[[3., 1]]], run(bijector.forward, x)) @@ -361,7 +361,7 @@ class AffineBijectorTest(test.TestCase): event_ndims: event_ndims_value } - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_diag=scale_diag, event_ndims=event_ndims) self.assertEqual(1, sess.run(bijector.event_ndims, feed_dict)) self.assertAllClose([[[3., 1]]], sess.run(bijector.forward(x), feed_dict)) @@ -384,7 +384,7 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # Corresponds to scale = 2 - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_identity_multiplier=1., scale_diag=[1.], @@ -410,7 +410,7 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # scale = [[2., 0], [2, 2]] - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_identity_multiplier=1., scale_tril=[[1., 0], [2., 1]]) @@ -435,7 +435,7 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # scale = [[2., 0], [2, 3]] - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_diag=[1., 2.], scale_tril=[[1., 0], [2., 1]]) self.assertEqual(1, bijector.event_ndims.eval()) # "is vector" x = [[1., 2]] # One multivariate sample. @@ -458,7 +458,7 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # scale = [[3., 0], [2, 4]] - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_identity_multiplier=1.0, scale_diag=[1., 2.], @@ -484,14 +484,14 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # Corresponds to scale = [[10, 0, 0], [0, 2, 0], [0, 0, 3]] - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_identity_multiplier=2., scale_perturb_diag=[2., 1], scale_perturb_factor=[[2., 0], [0., 0], [0, 1]]) - bijector_ref = Affine(shift=mu, scale_diag=[10., 2, 3]) + bijector_ref = affine_lib.Affine(shift=mu, scale_diag=[10., 2, 3]) self.assertEqual(1, bijector.event_ndims.eval()) # "is vector" x = [1., 2, 3] # Vector. @@ -522,14 +522,14 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # Corresponds to scale = [[10, 0, 0], [0, 3, 0], [0, 0, 5]] - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_diag=[2., 3, 4], scale_perturb_diag=[2., 1], scale_perturb_factor=[[2., 0], [0., 0], [0, 1]]) - bijector_ref = Affine(shift=mu, scale_diag=[10., 3, 5]) + bijector_ref = affine_lib.Affine(shift=mu, scale_diag=[10., 3, 5]) self.assertEqual(1, bijector.event_ndims.eval()) # "is vector" x = [1., 2, 3] # Vector. @@ -559,7 +559,7 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # Corresponds to scale = [[10, 0, 0], [1, 3, 0], [2, 3, 5]] - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_tril=[[2., 0, 0], [1, 3, 0], @@ -568,7 +568,7 @@ class AffineBijectorTest(test.TestCase): scale_perturb_factor=[[2., 0], [0., 0], [0, 1]]) - bijector_ref = Affine( + bijector_ref = affine_lib.Affine( shift=mu, scale_tril=[[10., 0, 0], [1, 3, 0], [2, 3, 5]]) @@ -601,12 +601,12 @@ class AffineBijectorTest(test.TestCase): for run in (static_run, dynamic_run): mu = -1. # Corresponds to scale = [[6, 0, 0], [1, 3, 0], [2, 3, 5]] - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_tril=[[2., 0, 0], [1, 3, 0], [2, 3, 4]], scale_perturb_diag=None, scale_perturb_factor=[[2., 0], [0., 0], [0, 1]]) - bijector_ref = Affine( + bijector_ref = affine_lib.Affine( shift=mu, scale_tril=[[6., 0, 0], [1, 3, 0], [2, 3, 5]]) self.assertEqual(1, bijector.event_ndims.eval()) # "is vector" @@ -626,7 +626,7 @@ class AffineBijectorTest(test.TestCase): def testNoBatchMultivariateRaisesWhenSingular(self): with self.test_session(): mu = [1., -1] - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, # Has zero on the diagonal. scale_diag=[0., 1], @@ -638,14 +638,14 @@ class AffineBijectorTest(test.TestCase): with self.test_session(): mu = [1., -1] # Scale corresponds to 2x2 identity matrix. - bijector = Affine(shift=mu, event_ndims=2, validate_args=True) + bijector = affine_lib.Affine(shift=mu, event_ndims=2, validate_args=True) bijector.forward([1., 1.]).eval() def testScaleZeroScalarRaises(self): with self.test_session(): mu = -1. # Check Identity matrix with zero scaling. - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_identity_multiplier=0.0, event_ndims=0, @@ -654,16 +654,16 @@ class AffineBijectorTest(test.TestCase): bijector.forward(1.).eval() # Check Diag matrix with zero scaling. - bijector = Affine( + bijector = affine_lib.Affine( shift=mu, scale_diag=[0.0], event_ndims=0, validate_args=True) with self.assertRaisesOpError("Condition x > 0"): bijector.forward(1.).eval() def testScalarCongruency(self): with self.test_session(): - bijector = Affine( + bijector = affine_lib.Affine( shift=3.6, scale_identity_multiplier=0.42, event_ndims=0) - assert_scalar_congruency( + bijector_test_util.assert_scalar_congruency( bijector, lower_x=-2., upper_x=2.) def _makeScale(self, @@ -743,9 +743,9 @@ class AffineBijectorTest(test.TestCase): # We haven't specified enough information for the scale. if scale is None: with self.assertRaisesRegexp(ValueError, ("must be specified.")): - bijector = Affine(shift=shift, **bijector_args) + bijector = affine_lib.Affine(shift=shift, **bijector_args) else: - bijector = Affine(shift=shift, **bijector_args) + bijector = affine_lib.Affine(shift=shift, **bijector_args) np_x = x # For the case a vector is passed in, we need to make the shape # match the matrix for matmul to work. @@ -823,7 +823,7 @@ class AffineBijectorTest(test.TestCase): def testScalePropertyAssertsCorrectly(self): with self.test_session(): with self.assertRaises(NotImplementedError): - scale = Affine( # pylint:disable=unused-variable + scale = affine_lib.Affine( # pylint:disable=unused-variable scale_tril=[[1., 0], [2, 1]], scale_perturb_factor=[2., 1.]).scale |