-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathenumerate_test.py
75 lines (62 loc) · 2.97 KB
/
enumerate_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
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
# 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.
# ==============================================================================
"""Tests for `tf.data.Dataset.enumerate()`."""
from absl.testing import parameterized
from tensorflow.python.data.kernel_tests import checkpoint_test_base
from tensorflow.python.data.kernel_tests import test_base
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.data.ops import options as options_lib
from tensorflow.python.framework import combinations
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import tensor_shape
from tensorflow.python.platform import test
class EnumerateTest(test_base.DatasetTestBase, parameterized.TestCase):
@combinations.generate(test_base.default_test_combinations())
def testEnumerate(self):
components = (["a", "b"], [1, 2], [37.0, 38])
start = constant_op.constant(20, dtype=dtypes.int64)
dataset = dataset_ops.Dataset.from_tensor_slices(components).enumerate(
start)
self.assertEqual(dtypes.int64,
dataset_ops.get_legacy_output_types(dataset)[0])
dataset_output_shapes = dataset_ops.get_legacy_output_shapes(dataset)
self.assertEqual((), dataset_output_shapes[0])
self.assertEqual([tensor_shape.TensorShape([])] * 3,
[shape for shape in dataset_output_shapes[1]])
self.assertDatasetProduces(dataset, [(20, (b"a", 1, 37.0)),
(21, (b"b", 2, 38.0))])
class EnumerateCheckpointTest(checkpoint_test_base.CheckpointTestBase,
parameterized.TestCase):
def _build_enumerate_dataset(self, start, stop, options=None):
dataset = dataset_ops.Dataset.range(start, stop).enumerate()
if options:
dataset = dataset.with_options(options)
return dataset
@combinations.generate(
combinations.times(
test_base.default_test_combinations(),
checkpoint_test_base.default_test_combinations(),
combinations.combine(symbolic_checkpoint=[False, True])))
def test(self, verify_fn, symbolic_checkpoint):
start = 2
stop = 10
options = options_lib.Options()
options.experimental_symbolic_checkpoint = symbolic_checkpoint
verify_fn(
self, lambda: self._build_enumerate_dataset(
start=start, stop=stop, options=options), stop - start)
if __name__ == "__main__":
test.main()