# Copyright (c) 2021 PaddlePaddle 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. import unittest import numpy as np import paddle from deepspeech.modules.mask import make_non_pad_mask from deepspeech.modules.mask import make_pad_mask from deepspeech.modules.mask import sequence_mask class TestU2Model(unittest.TestCase): def setUp(self): paddle.set_device('cpu') self.lengths = paddle.to_tensor([5, 3, 2]) self.masks = np.array([ [True, True, True, True, True], [True, True, True, False, False], [True, True, False, False, False], ]) self.pad_masks = np.array([ [False, False, False, False, False], [False, False, False, True, True], [False, False, True, True, True], ]) def test_sequence_mask(self): res = sequence_mask(self.lengths, dtype='bool') self.assertSequenceEqual(res.numpy().tolist(), self.masks.tolist()) def test_make_non_pad_mask(self): res = make_non_pad_mask(self.lengths) res1 = sequence_mask(self.lengths, dtype='bool') res2 = make_pad_mask(self.lengths).logical_not() self.assertSequenceEqual(res.numpy().tolist(), self.masks.tolist()) self.assertSequenceEqual(res.numpy().tolist(), res1.numpy().tolist()) self.assertSequenceEqual(res.numpy().tolist(), res2.numpy().tolist()) def test_make_pad_mask(self): res = make_pad_mask(self.lengths) res1 = make_non_pad_mask(self.lengths).logical_not() self.assertSequenceEqual(res.numpy().tolist(), self.pad_masks.tolist()) self.assertSequenceEqual(res.numpy().tolist(), res1.tolist()) if __name__ == '__main__': unittest.main()