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import os
from collections import defaultdict
from pathlib import Path
from parameterized import parameterized
from torchaudio.datasets import quesst14
from torchaudio_unittest.common_utils import get_whitenoise, save_wav, TempDirMixin, TorchaudioTestCase
def _get_filename(folder, index):
if folder == "Audio":
return f"quesst14_{index:05d}.wav"
elif folder == "dev_queries":
return f"quesst14_dev_{index:04d}.wav"
elif folder == "eval_queries":
return f"quesst14_eval_{index:04d}.wav"
return
def _get_key(folder):
folder_key_mapping = {
"Audio": "utterances",
"dev_queries": "dev",
"eval_queries": "eval",
}
return folder_key_mapping[folder]
def _save_sample(dataset_dir, folder, language, index, sample_rate, seed):
# create and save audio samples to corresponding files
path = os.path.join(dataset_dir, folder)
os.makedirs(path, exist_ok=True)
filename = _get_filename(folder, index)
file_path = os.path.join(path, filename)
data = get_whitenoise(
sample_rate=sample_rate,
duration=0.01,
n_channels=1,
seed=seed,
)
save_wav(file_path, data, sample_rate)
sample = (data, sample_rate, Path(file_path).with_suffix("").name)
# add audio files and language data to language key files
scoring_path = os.path.join(dataset_dir, "scoring")
os.makedirs(scoring_path, exist_ok=True)
wav_file = f"quesst14Database/{folder}/{filename}"
line = f"{wav_file} {language}"
key = _get_key(folder)
language_key_file = f"language_key_{key}.lst"
language_key_file = os.path.join(scoring_path, language_key_file)
with open(language_key_file, "a") as f:
f.write(line + "\n")
return sample
def _get_mocked_samples(dataset_dir, folder, sample_rate, seed):
samples_per_language = 2
samples_map = defaultdict(list)
samples_all = []
curr_idx = 0
for language in quesst14._LANGUAGES:
for _ in range(samples_per_language):
sample = _save_sample(dataset_dir, folder, language, curr_idx, sample_rate, seed)
samples_map[language].append(sample)
samples_all.append(sample)
curr_idx += 1
return samples_map, samples_all
def get_mock_dataset(dataset_dir):
"""
dataset_dir: directory to the mocked dataset
"""
os.makedirs(dataset_dir, exist_ok=True)
sample_rate = 8000
audio_seed = 0
dev_seed = 1
eval_seed = 2
mocked_utterances, mocked_utterances_all = _get_mocked_samples(dataset_dir, "Audio", sample_rate, audio_seed)
mocked_dev_samples, mocked_dev_samples_all = _get_mocked_samples(dataset_dir, "dev_queries", sample_rate, dev_seed)
mocked_eval_samples, mocked_eval_samples_all = _get_mocked_samples(
dataset_dir, "eval_queries", sample_rate, eval_seed
)
return (
mocked_utterances,
mocked_dev_samples,
mocked_eval_samples,
mocked_utterances_all,
mocked_dev_samples_all,
mocked_eval_samples_all,
)
class TestQuesst14(TempDirMixin, TorchaudioTestCase):
root_dir = None
utterances = {}
dev_samples = {}
eval_samples = {}
utterances_all = []
dev_samples_all = []
eval_samples_all = []
@classmethod
def setUpClass(cls):
cls.root_dir = cls.get_base_temp_dir()
dataset_dir = os.path.join(cls.root_dir, "quesst14Database")
(
cls.utterances,
cls.dev_samples,
cls.eval_samples,
cls.utterances_all,
cls.dev_samples_all,
cls.eval_samples_all,
) = get_mock_dataset(dataset_dir)
def _testQuesst14(self, dataset, data_samples):
num_samples = 0
for i, (data, sample_rate, name) in enumerate(dataset):
self.assertEqual(data, data_samples[i][0])
assert sample_rate == data_samples[i][1]
assert name == data_samples[i][2]
num_samples += 1
assert num_samples == len(data_samples)
def testQuesst14SubsetDocs(self):
dataset = quesst14.QUESST14(self.root_dir, language=None, subset="docs")
self._testQuesst14(dataset, self.utterances_all)
def testQuesst14SubsetDev(self):
dataset = quesst14.QUESST14(self.root_dir, language=None, subset="dev")
self._testQuesst14(dataset, self.dev_samples_all)
def testQuesst14SubsetEval(self):
dataset = quesst14.QUESST14(self.root_dir, language=None, subset="eval")
self._testQuesst14(dataset, self.eval_samples_all)
@parameterized.expand(quesst14._LANGUAGES)
def testQuesst14DocsSingleLanguage(self, language):
dataset = quesst14.QUESST14(self.root_dir, language=language, subset="docs")
self._testQuesst14(dataset, self.utterances[language])
@parameterized.expand(quesst14._LANGUAGES)
def testQuesst14DevSingleLanguage(self, language):
dataset = quesst14.QUESST14(self.root_dir, language=language, subset="dev")
self._testQuesst14(dataset, self.dev_samples[language])
@parameterized.expand(quesst14._LANGUAGES)
def testQuesst14EvalSingleLanguage(self, language):
dataset = quesst14.QUESST14(self.root_dir, language=language, subset="eval")
self._testQuesst14(dataset, self.eval_samples[language])
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