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absolute_value_test.py
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absolute_value_test.py
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# Copyright 2018 The TensorFlow Probability Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Tests for AbsoluteValue Bijector."""
import tensorflow.compat.v2 as tf
from tensorflow_probability.python.bijectors import absolute_value
from tensorflow_probability.python.internal import test_util
@test_util.test_all_tf_execution_regimes
class AbsoluteValueTest(test_util.TestCase):
"""Tests correctness of the absolute value bijector."""
def testBijectorVersusNumpyRewriteOfBasicFunctionsEventNdims0(self):
bijector = absolute_value.AbsoluteValue(validate_args=True)
self.assertStartsWith(bijector.name, "absolute_value")
x = tf.constant([[0., 1., -1], [0., -5., 3.]]) # Shape [2, 3]
y = tf.math.abs(x)
y_ = self.evaluate(y)
self.assertAllClose(y_, self.evaluate(bijector.forward(x)))
self.assertAllClose((-y_, y_), self.evaluate(bijector.inverse(y)))
self.assertAllClose((0., 0.),
self.evaluate(bijector.inverse_log_det_jacobian(
y, event_ndims=0)))
# Run things twice to make sure there are no issues in caching the tuples
# returned by .inverse*
self.assertAllClose(y_, self.evaluate(bijector.forward(x)))
self.assertAllClose((-y_, y_), self.evaluate(bijector.inverse(y)))
self.assertAllClose((0., 0.),
self.evaluate(bijector.inverse_log_det_jacobian(
y, event_ndims=0)))
def testNegativeYRaisesForInverseIfValidateArgs(self):
bijector = absolute_value.AbsoluteValue(validate_args=True)
with self.assertRaisesOpError("y was negative"):
self.evaluate(bijector.inverse(-1.))
def testNegativeYRaisesForILDJIfValidateArgs(self):
bijector = absolute_value.AbsoluteValue(validate_args=True)
with self.assertRaisesOpError("y was negative"):
self.evaluate(bijector.inverse_log_det_jacobian(-1., event_ndims=0))
def testCompositeTensor(self):
bijector = absolute_value.AbsoluteValue(validate_args=True)
flat = tf.nest.flatten(bijector, expand_composites=True)
unflat = tf.nest.pack_sequence_as(bijector, flat, expand_composites=True)
x = tf.convert_to_tensor([0., 1., -1.])
self.assertAllClose(
bijector.forward(x),
tf.function(lambda b_: b_.forward(x))(unflat))
if __name__ == "__main__":
test_util.main()