1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
|
# 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.
# ==============================================================================
"""Tests for Bijector."""
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.exp import Exp
from tensorflow.contrib.distributions.python.ops.bijectors.inline import Inline
from tensorflow.python.framework import tensor_shape
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
class InlineBijectorTest(test.TestCase):
"""Tests correctness of the inline constructed bijector."""
def testBijector(self):
with self.test_session():
exp = Exp(event_ndims=1)
inline = Inline(
forward_fn=math_ops.exp,
inverse_fn=math_ops.log,
inverse_log_det_jacobian_fn=(
lambda y: -math_ops.reduce_sum( # pylint: disable=g-long-lambda
math_ops.log(y), reduction_indices=-1)),
forward_log_det_jacobian_fn=(
lambda x: math_ops.reduce_sum(x, reduction_indices=-1)),
name="exp")
self.assertEqual(exp.name, inline.name)
x = [[[1., 2.], [3., 4.], [5., 6.]]]
y = np.exp(x)
self.assertAllClose(y, inline.forward(x).eval())
self.assertAllClose(x, inline.inverse(y).eval())
self.assertAllClose(
-np.sum(np.log(y), axis=-1),
inline.inverse_log_det_jacobian(y).eval())
self.assertAllClose(-inline.inverse_log_det_jacobian(y).eval(),
inline.forward_log_det_jacobian(x).eval())
def testShapeGetters(self):
with self.test_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],
inverse_event_shape_tensor_fn=lambda x: x[:-1],
inverse_event_shape_fn=lambda x: x[:-1],
name="shape_only")
x = tensor_shape.TensorShape([1, 2, 3])
y = tensor_shape.TensorShape([1, 2, 3, 1])
self.assertAllEqual(y, bijector.forward_event_shape(x))
self.assertAllEqual(
y.as_list(),
bijector.forward_event_shape_tensor(x.as_list()).eval())
self.assertAllEqual(x, bijector.inverse_event_shape(y))
self.assertAllEqual(
x.as_list(),
bijector.inverse_event_shape_tensor(y.as_list()).eval())
if __name__ == "__main__":
test.main()
|
