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
|
# Copyright 2017 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.
# ==============================================================================
"""Functional tests for XLA Reverse Ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import itertools
import numpy as np
from tensorflow.compiler.tests.xla_test import XLATestCase
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import googletest
class ReverseOpsTest(XLATestCase):
def testReverseOneDim(self):
shape = (7, 5, 9, 11)
for revdim in range(len(shape)):
self._AssertReverseEqual([revdim], shape)
def testReverseMoreThanOneDim(self):
shape = (7, 5, 9, 11)
for revdims in itertools.chain.from_iterable(
itertools.combinations(range(len(shape)), k)
for k in range(2, len(shape)+1)):
self._AssertReverseEqual(revdims, shape)
def _AssertReverseEqual(self, revdims, shape):
np.random.seed(120)
pval = np.random.randint(0, 100, size=shape).astype(float)
with self.test_session():
with self.test_scope():
p = array_ops.placeholder(dtypes.int32, shape=shape)
axis = constant_op.constant(
np.array(revdims, dtype=np.int32),
shape=(len(revdims),), dtype=dtypes.int32)
rval = array_ops.reverse(p, axis).eval({p: pval})
slices = [
slice(-1, None, -1) if d in revdims else slice(None)
for d in range(len(shape))]
self.assertEqual(
pval[slices].flatten().tolist(),
rval.flatten().tolist())
if __name__ == '__main__':
googletest.main()
|
