Axial-DeepLab-SWideRNet / data /preprocessing /autoaugment_policy_test.py
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from https://huggingface.co/spaces/akhaliq/deeplab2
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# coding=utf-8
# Copyright 2021 The Deeplab2 Authors.
#
# 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 autoaugment_policy.py."""
import tensorflow as tf
from deeplab2.data.preprocessing import autoaugment_policy
class AutoaugmentPolicyTest(tf.test.TestCase):
def testConvertPolicy(self):
policy = [5, 1, 10, 5, 3, 4,
6, 3, 7, 3, 3, 9,
2, 2, 8, 8, 2, 8,
1, 4, 9, 4, 5, 7,
6, 4, 1, 1, 3, 4]
expected = [
[('Color', 0.2, 10), ('Color', 0.6, 4)],
[('Contrast', 0.6, 7), ('Posterize', 0.6, 9)],
[('Invert', 0.4, 8), ('Sharpness', 0.4, 8)],
[('Equalize', 0.8, 9), ('Solarize', 1.0, 7)],
[('Contrast', 0.8, 1), ('Equalize', 0.6, 4)],
]
policy_list = autoaugment_policy.convert_policy(policy)
self.assertAllEqual(policy_list, expected)
if __name__ == '__main__':
tf.test.main()