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53 lines
1.9 KiB
53 lines
1.9 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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import paddle
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from deepspeech.modules.mask import make_non_pad_mask
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from deepspeech.modules.mask import make_pad_mask
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class TestU2Model(unittest.TestCase):
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def setUp(self):
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paddle.set_device('cpu')
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self.lengths = paddle.to_tensor([5, 3, 2])
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self.masks = np.array([
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[True, True, True, True, True],
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[True, True, True, False, False],
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[True, True, False, False, False],
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])
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self.pad_masks = np.array([
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[False, False, False, False, False],
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[False, False, False, True, True],
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[False, False, True, True, True],
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])
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def test_make_non_pad_mask(self):
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res = make_non_pad_mask(self.lengths)
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res2 = make_pad_mask(self.lengths).logical_not()
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self.assertSequenceEqual(res.numpy().tolist(), self.masks.tolist())
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self.assertSequenceEqual(res.numpy().tolist(), res2.numpy().tolist())
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def test_make_pad_mask(self):
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res = make_pad_mask(self.lengths)
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res1 = make_non_pad_mask(self.lengths).logical_not()
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self.assertSequenceEqual(res.numpy().tolist(), self.pad_masks.tolist())
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self.assertSequenceEqual(res.numpy().tolist(), res1.tolist())
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if __name__ == '__main__':
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unittest.main()
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