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
|
# Copyright 2018 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 utilities for tf.data functionality."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import re
from tensorflow.python.data.util import nest
from tensorflow.python.framework import errors
from tensorflow.python.platform import test
class DatasetTestBase(test.TestCase):
"""Base class for dataset tests."""
def _assert_datasets_equal(self, dataset1, dataset2):
# TODO(rachelim): support sparse tensor outputs
next1 = dataset1.make_one_shot_iterator().get_next()
next2 = dataset2.make_one_shot_iterator().get_next()
with self.test_session() as sess:
while True:
try:
op1 = sess.run(next1)
except errors.OutOfRangeError:
with self.assertRaises(errors.OutOfRangeError):
sess.run(next2)
break
op2 = sess.run(next2)
op1 = nest.flatten(op1)
op2 = nest.flatten(op2)
assert len(op1) == len(op2)
for i in range(len(op1)):
self.assertAllEqual(op1[i], op2[i])
def _assert_datasets_raise_same_error(self,
dataset1,
dataset2,
exception_class,
replacements=None):
next1 = dataset1.make_one_shot_iterator().get_next()
next2 = dataset2.make_one_shot_iterator().get_next()
with self.test_session() as sess:
try:
sess.run(next1)
raise ValueError(
"Expected dataset to raise an error of type %s, but it did not." %
repr(exception_class))
except exception_class as e:
expected_message = e.message
for old, new, count in replacements:
expected_message = expected_message.replace(old, new, count)
# Check that the first segment of the error messages are the same.
with self.assertRaisesRegexp(exception_class,
re.escape(expected_message)):
sess.run(next2)
|
