Add unittest for feature apis.

pull/1548/head
KP 3 years ago
parent f657ee64dc
commit b24925da7a

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# Copyright (c) 2022 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.

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# Copyright (c) 2022 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 os
import unittest
import numpy as np
import paddle
from paddleaudio import load
file_dir = os.path.dirname(os.path.realpath(__file__))
class FeatTest(unittest.TestCase):
def setUp(self):
self.initParmas()
self.initWavInput()
self.setUpDevice()
def setUpDevice(self, device='cpu'):
paddle.set_device(device)
def initWavInput(self):
self.waveform, self.sr = load(
os.path.abspath(os.path.join(file_dir, '../wav/zh.wav')))
self.waveform = self.waveform.astype(
np.float32
) # paddlespeech.s2t.transform.spectrogram only supports float32
dim = len(self.waveform.shape)
assert dim in [1, 2]
if dim == 1:
self.waveform = np.expand_dims(self.waveform, 0)
def initParmas(self):
raise NotImplementedError

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# Copyright (c) 2022 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 .base import FeatTest
from paddleaudio.functional.window import get_window
from paddlespeech.s2t.transform.spectrogram import IStft
from paddlespeech.s2t.transform.spectrogram import Stft
class ISTFT(FeatTest):
def initParmas(self):
self.n_fft = 512
self.hop_length = 128
self.window_str = 'hann'
def test_istft(self):
ps_stft = Stft(self.n_fft, self.hop_length)
ps_res = ps_stft(
self.waveform.T).squeeze(1).T # (n_fft//2 + 1, n_frmaes)
x = paddle.to_tensor(ps_res)
ps_istft = IStft(self.hop_length)
ps_res = ps_istft(ps_res.T)
window = get_window(
self.window_str, self.n_fft, dtype=self.waveform.dtype)
pd_res = paddle.signal.istft(
x, self.n_fft, self.hop_length, window=window)
np.testing.assert_array_almost_equal(ps_res, pd_res, decimal=5)
if __name__ == '__main__':
unittest.main()

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# Copyright (c) 2022 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
import paddleaudio
from .base import FeatTest
from paddlespeech.s2t.transform.spectrogram import LogMelSpectrogram
class LogMelSpect(FeatTest):
def initParmas(self):
self.n_fft = 512
self.hop_length = 128
self.n_mels = 40
def test_log_melspect(self):
ps_melspect = LogMelSpectrogram(self.sr, self.n_mels, self.n_fft,
self.hop_length)
ps_res = ps_melspect(self.waveform.T).squeeze(1).T
x = paddle.to_tensor(self.waveform)
# paddlespeech.s2t的特征存在幅度谱和功率谱滥用的情况
ps_melspect = paddleaudio.features.LogMelSpectrogram(
self.sr,
self.n_fft,
self.hop_length,
power=1.0,
n_mels=self.n_mels,
f_min=0.0)
pa_res = (ps_melspect(x) / 10.0).squeeze(0).numpy()
np.testing.assert_array_almost_equal(ps_res, pa_res, decimal=5)
if __name__ == '__main__':
unittest.main()

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# Copyright (c) 2022 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
import paddleaudio
from .base import FeatTest
from paddlespeech.s2t.transform.spectrogram import Spectrogram
class Spect(FeatTest):
def initParmas(self):
self.n_fft = 512
self.hop_length = 128
def test_spectrogram(self):
ps_spect = Spectrogram(self.n_fft, self.hop_length)
ps_res = ps_spect(self.waveform.T).squeeze(1).T # Magnitude
x = paddle.to_tensor(self.waveform)
pa_spect = paddleaudio.features.Spectrogram(
self.n_fft, self.hop_length, power=1.0)
pa_res = pa_spect(x).squeeze(0).numpy()
np.testing.assert_array_almost_equal(ps_res, pa_res, decimal=5)
if __name__ == '__main__':
unittest.main()

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# Copyright (c) 2022 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 .base import FeatTest
from paddleaudio.functional.window import get_window
from paddlespeech.s2t.transform.spectrogram import Stft
class STFT(FeatTest):
def initParmas(self):
self.n_fft = 512
self.hop_length = 128
self.window_str = 'hann'
def test_stft(self):
ps_stft = Stft(self.n_fft, self.hop_length)
ps_res = ps_stft(
self.waveform.T).squeeze(1).T # (n_fft//2 + 1, n_frmaes)
x = paddle.to_tensor(self.waveform)
window = get_window(self.window_str, self.n_fft, dtype=x.dtype)
pd_res = paddle.signal.stft(
x, self.n_fft, self.hop_length, window=window).squeeze(0).numpy()
np.testing.assert_array_almost_equal(ps_res, pd_res, decimal=5)
if __name__ == '__main__':
unittest.main()

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