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# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
"""Exp Tests."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.contrib.distributions.python.ops.bijectors import bijector_test_util
from tensorflow.contrib.distributions.python.ops.bijectors import exp as exp_lib
from tensorflow.python.platform import test
class ExpBijectorTest(test.TestCase):
"""Tests correctness of the Y = g(X) = exp(X) transformation."""
def testBijector(self):
with self.test_session():
bijector = exp_lib.Exp(event_ndims=1)
self.assertEqual("exp", bijector.name)
x = [[[1.], [2.]]]
y = np.exp(x)
self.assertAllClose(y, bijector.forward(x).eval())
self.assertAllClose(x, bijector.inverse(y).eval())
self.assertAllClose(
-np.sum(np.log(y), axis=-1),
bijector.inverse_log_det_jacobian(y).eval())
self.assertAllClose(-bijector.inverse_log_det_jacobian(np.exp(x)).eval(),
bijector.forward_log_det_jacobian(x).eval())
def testScalarCongruency(self):
with self.test_session():
bijector = exp_lib.Exp()
bijector_test_util.assert_scalar_congruency(
bijector, lower_x=-2., upper_x=1.5, rtol=0.05)
def testBijectiveAndFinite(self):
with self.test_session():
bijector = exp_lib.Exp(event_ndims=0)
x = np.linspace(-10, 10, num=10).astype(np.float32)
y = np.logspace(-10, 10, num=10).astype(np.float32)
bijector_test_util.assert_bijective_and_finite(bijector, x, y)
if __name__ == "__main__":
test.main()
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