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import os
from pathlib import Path
from torchaudio.datasets import yesno
from torchaudio_unittest.common_utils import get_whitenoise, normalize_wav, save_wav, TempDirMixin, TorchaudioTestCase
def get_mock_data(root_dir, labels):
"""
root_dir: path
labels: list of labels
"""
mocked_data = []
base_dir = os.path.join(root_dir, "waves_yesno")
os.makedirs(base_dir, exist_ok=True)
for i, label in enumerate(labels):
filename = f'{"_".join(str(l) for l in label)}.wav'
path = os.path.join(base_dir, filename)
data = get_whitenoise(sample_rate=8000, duration=6, n_channels=1, dtype="int16", seed=i)
save_wav(path, data, 8000)
mocked_data.append(normalize_wav(data))
return mocked_data
class TestYesNo(TempDirMixin, TorchaudioTestCase):
backend = "default"
root_dir = None
data = []
labels = [
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 1, 1],
[0, 1, 0, 1, 0, 1, 1, 0],
[1, 1, 1, 1, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1],
]
@classmethod
def setUpClass(cls):
cls.root_dir = cls.get_base_temp_dir()
cls.data = get_mock_data(cls.root_dir, cls.labels)
def _test_yesno(self, dataset):
n_ite = 0
for i, (waveform, sample_rate, label) in enumerate(dataset):
expected_label = self.labels[i]
expected_data = self.data[i]
self.assertEqual(expected_data, waveform, atol=5e-5, rtol=1e-8)
assert sample_rate == 8000
assert label == expected_label
n_ite += 1
assert n_ite == len(self.data)
def test_yesno_str(self):
dataset = yesno.YESNO(self.root_dir)
self._test_yesno(dataset)
def test_yesno_path(self):
dataset = yesno.YESNO(Path(self.root_dir))
self._test_yesno(dataset)
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