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# Copyright (c) 2022 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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# Copyright (c) 2022 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 os
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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 paddleaudio import load
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file_dir = os.path.dirname(os.path.realpath(__file__))
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class FeatTest(unittest.TestCase):
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def setUp(self):
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self.initParmas()
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self.initWavInput()
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self.setUpDevice()
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def setUpDevice(self, device='cpu'):
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paddle.set_device(device)
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def initWavInput(self):
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self.waveform, self.sr = load(
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os.path.abspath(os.path.join(file_dir, '../wav/zh.wav')))
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self.waveform = self.waveform.astype(
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np.float32
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) # paddlespeech.s2t.transform.spectrogram only supports float32
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dim = len(self.waveform.shape)
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assert dim in [1, 2]
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if dim == 1:
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self.waveform = np.expand_dims(self.waveform, 0)
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def initParmas(self):
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raise NotImplementedError
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# Copyright (c) 2022 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 .base import FeatTest
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from paddleaudio.functional.window import get_window
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from paddlespeech.s2t.transform.spectrogram import IStft
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from paddlespeech.s2t.transform.spectrogram import Stft
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class ISTFT(FeatTest):
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def initParmas(self):
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self.n_fft = 512
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self.hop_length = 128
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self.window_str = 'hann'
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def test_istft(self):
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ps_stft = Stft(self.n_fft, self.hop_length)
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ps_res = ps_stft(
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self.waveform.T).squeeze(1).T # (n_fft//2 + 1, n_frmaes)
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x = paddle.to_tensor(ps_res)
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ps_istft = IStft(self.hop_length)
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ps_res = ps_istft(ps_res.T)
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window = get_window(
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self.window_str, self.n_fft, dtype=self.waveform.dtype)
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pd_res = paddle.signal.istft(
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x, self.n_fft, self.hop_length, window=window)
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np.testing.assert_array_almost_equal(ps_res, pd_res, decimal=5)
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if __name__ == '__main__':
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unittest.main()
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# Copyright (c) 2022 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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import paddleaudio
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from .base import FeatTest
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from paddlespeech.s2t.transform.spectrogram import LogMelSpectrogram
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class LogMelSpect(FeatTest):
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def initParmas(self):
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self.n_fft = 512
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self.hop_length = 128
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self.n_mels = 40
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def test_log_melspect(self):
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ps_melspect = LogMelSpectrogram(self.sr, self.n_mels, self.n_fft,
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self.hop_length)
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ps_res = ps_melspect(self.waveform.T).squeeze(1).T
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x = paddle.to_tensor(self.waveform)
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# paddlespeech.s2t的特征存在幅度谱和功率谱滥用的情况
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ps_melspect = paddleaudio.features.LogMelSpectrogram(
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self.sr,
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self.n_fft,
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self.hop_length,
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power=1.0,
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n_mels=self.n_mels,
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f_min=0.0)
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pa_res = (ps_melspect(x) / 10.0).squeeze(0).numpy()
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np.testing.assert_array_almost_equal(ps_res, pa_res, decimal=5)
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if __name__ == '__main__':
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unittest.main()
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# Copyright (c) 2022 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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import paddleaudio
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from .base import FeatTest
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from paddlespeech.s2t.transform.spectrogram import Spectrogram
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class Spect(FeatTest):
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def initParmas(self):
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self.n_fft = 512
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self.hop_length = 128
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def test_spectrogram(self):
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ps_spect = Spectrogram(self.n_fft, self.hop_length)
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ps_res = ps_spect(self.waveform.T).squeeze(1).T # Magnitude
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x = paddle.to_tensor(self.waveform)
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pa_spect = paddleaudio.features.Spectrogram(
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self.n_fft, self.hop_length, power=1.0)
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pa_res = pa_spect(x).squeeze(0).numpy()
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np.testing.assert_array_almost_equal(ps_res, pa_res, decimal=5)
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if __name__ == '__main__':
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unittest.main()
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# Copyright (c) 2022 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 .base import FeatTest
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from paddleaudio.functional.window import get_window
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from paddlespeech.s2t.transform.spectrogram import Stft
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class STFT(FeatTest):
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def initParmas(self):
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self.n_fft = 512
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self.hop_length = 128
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self.window_str = 'hann'
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def test_stft(self):
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ps_stft = Stft(self.n_fft, self.hop_length)
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ps_res = ps_stft(
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self.waveform.T).squeeze(1).T # (n_fft//2 + 1, n_frmaes)
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x = paddle.to_tensor(self.waveform)
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window = get_window(self.window_str, self.n_fft, dtype=x.dtype)
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pd_res = paddle.signal.stft(
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x, self.n_fft, self.hop_length, window=window).squeeze(0).numpy()
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np.testing.assert_array_almost_equal(ps_res, pd_res, decimal=5)
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if __name__ == '__main__':
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unittest.main()
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