-
Notifications
You must be signed in to change notification settings - Fork 74k
/
zero_out_2_test.py
49 lines (37 loc) · 1.77 KB
/
zero_out_2_test.py
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
# Copyright 2015 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.
# ==============================================================================
"""Test for version 2 of the zero_out op."""
import tensorflow as tf
from tensorflow.examples.adding_an_op import zero_out_grad_2 # pylint: disable=unused-import
from tensorflow.examples.adding_an_op import zero_out_op_2
class ZeroOut2Test(tf.test.TestCase):
def test(self):
result = zero_out_op_2.zero_out([5, 4, 3, 2, 1])
self.assertAllEqual(result, [5, 0, 0, 0, 0])
def test_2d(self):
result = zero_out_op_2.zero_out([[6, 5, 4], [3, 2, 1]])
self.assertAllEqual(result, [[6, 0, 0], [0, 0, 0]])
def test_grad(self):
x = tf.constant([5, 4, 3, 2, 1], dtype=tf.float32)
theoretical, numerical = tf.test.compute_gradient(zero_out_op_2.zero_out,
tuple([x]))
self.assertAllClose(theoretical, numerical)
def test_grad_2d(self):
x = tf.constant([[6, 5, 4], [3, 2, 1]], dtype=tf.float32)
theoretical, numerical = tf.test.compute_gradient(zero_out_op_2.zero_out,
tuple([x]))
self.assertAllClose(theoretical, numerical)
if __name__ == '__main__':
tf.test.main()