164 lines
5.7 KiB
Python
164 lines
5.7 KiB
Python
# 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 soundfile
|
|
|
|
import paddle.audio
|
|
|
|
|
|
class TestAudioBackends(unittest.TestCase):
|
|
def setUp(self):
|
|
self.initParams()
|
|
|
|
def initParams(self):
|
|
def get_wav_data(dtype: str, num_channels: int, num_frames: int):
|
|
dtype_ = getattr(paddle, dtype)
|
|
base = paddle.linspace(-1.0, 1.0, num_frames, dtype=dtype_) * 0.1
|
|
data = base.tile([num_channels, 1])
|
|
return data
|
|
|
|
self.duration = 0.5
|
|
self.num_channels = 1
|
|
self.sr = 16000
|
|
self.dtype = "float32"
|
|
self.window_size = 1024
|
|
waveform_tensor = get_wav_data(
|
|
self.dtype, self.num_channels, num_frames=self.duration * self.sr
|
|
)
|
|
# shape (1, 8000)
|
|
self.waveform = waveform_tensor.numpy()
|
|
|
|
def test_backend(self):
|
|
base_dir = os.getcwd()
|
|
wave_wav_path = os.path.join(base_dir, "wave_test.wav")
|
|
paddle.audio.save(
|
|
wave_wav_path,
|
|
paddle.to_tensor(self.waveform),
|
|
self.sr,
|
|
channels_first=True,
|
|
)
|
|
|
|
# test backends(wave)(wave_backend) info
|
|
wav_info = paddle.audio.info(wave_wav_path)
|
|
self.assertTrue(wav_info.sample_rate, self.sr)
|
|
self.assertTrue(wav_info.num_channels, self.num_channels)
|
|
self.assertTrue(wav_info.bits_per_sample, 16)
|
|
|
|
with open(wave_wav_path, 'rb') as file_:
|
|
wav_info = paddle.audio.info(file_)
|
|
self.assertTrue(wav_info.sample_rate, self.sr)
|
|
self.assertTrue(wav_info.num_channels, self.num_channels)
|
|
self.assertTrue(wav_info.bits_per_sample, 16)
|
|
|
|
# test backends(wave_backend) load & save
|
|
wav_data, sr = paddle.audio.load(wave_wav_path)
|
|
np.testing.assert_array_almost_equal(wav_data, self.waveform, decimal=4)
|
|
with soundfile.SoundFile(wave_wav_path, "r") as file_:
|
|
dtype = "float32"
|
|
frames = file_._prepare_read(0, None, -1)
|
|
waveform = file_.read(frames, dtype, always_2d=True)
|
|
waveform = waveform.T
|
|
np.testing.assert_array_almost_equal(wav_data, waveform)
|
|
|
|
with open(wave_wav_path, 'rb') as file_:
|
|
wav_data, sr = paddle.audio.load(
|
|
file_, normalize=False, num_frames=10000
|
|
)
|
|
with soundfile.SoundFile(wave_wav_path, "r") as file_:
|
|
dtype = "int16"
|
|
frames = file_._prepare_read(0, None, -1)
|
|
waveform = file_.read(frames, dtype, always_2d=True)
|
|
waveform = waveform.T
|
|
np.testing.assert_array_almost_equal(wav_data, waveform)
|
|
|
|
current_backend = paddle.audio.backends.get_current_backend()
|
|
self.assertTrue(
|
|
current_backend in ["wave_backend", "soundfile", "sox_io"]
|
|
)
|
|
|
|
paddle.audio.backends.set_backend("wave_backend")
|
|
|
|
backends = paddle.audio.backends.list_available_backends()
|
|
for backend in backends:
|
|
self.assertTrue(backend in ["wave_backend", "soundfile", "sox_io"])
|
|
|
|
# Test error
|
|
try:
|
|
paddle.audio.backends.set_backend("jfiji")
|
|
except NotImplementedError:
|
|
pass
|
|
|
|
try:
|
|
import paddleaudio
|
|
|
|
backends = paddle.audio.backends.list_available_backends()
|
|
for backend in backends:
|
|
self.assertTrue(
|
|
backend in ["wave_backend", "soundfile", "sox_io"]
|
|
)
|
|
current_backend = paddle.audio.backends.get_current_backend()
|
|
self.assertTrue(current_backend, "wave_backend")
|
|
paddleaudio.backends.set_audio_backend("soundfile")
|
|
paddle.audio.backends.set_backend("soundfile")
|
|
current_backend = paddle.audio.backends.get_current_backend()
|
|
self.assertTrue(current_backend, "soundfile")
|
|
wav_info = paddle.audio.info(wave_wav_path)
|
|
self.assertTrue(wav_info.sample_rate, self.sr)
|
|
self.assertTrue(wav_info.num_channels, self.num_channels)
|
|
self.assertTrue(wav_info.bits_per_sample, 16)
|
|
paddle.audio.backends.set_backend("wave_backend")
|
|
except ImportError:
|
|
pass
|
|
|
|
try:
|
|
paddle.audio.save(
|
|
wave_wav_path,
|
|
paddle.to_tensor(self.waveform),
|
|
self.sr,
|
|
bits_per_sample=24,
|
|
channels_first=True,
|
|
)
|
|
except ValueError:
|
|
pass
|
|
|
|
try:
|
|
paddle.audio.save(
|
|
wave_wav_path,
|
|
paddle.to_tensor(self.waveform).unsqueeze(0),
|
|
self.sr,
|
|
)
|
|
except AssertionError:
|
|
pass
|
|
|
|
fake_data = np.array([0, 1, 2, 3, 4, 6], np.float32)
|
|
soundfile.write(wave_wav_path, fake_data, 1, subtype="DOUBLE")
|
|
try:
|
|
wav_info = paddle.audio.info(wave_wav_path)
|
|
except NotImplementedError:
|
|
pass
|
|
try:
|
|
wav_data = paddle.audio.load(wave_wav_path)
|
|
except NotImplementedError:
|
|
pass
|
|
|
|
if os.path.exists(wave_wav_path):
|
|
os.remove(wave_wav_path)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|