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test: use temp output folders, pytest.parametrize, fixtures
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import os | ||
import unittest | ||
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from tests import get_tests_input_path, get_tests_output_path, get_tests_path | ||
import pytest | ||
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from tests import get_tests_input_path | ||
from TTS.config import BaseAudioConfig | ||
from TTS.utils.audio.processor import AudioProcessor | ||
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TESTS_PATH = get_tests_path() | ||
OUT_PATH = os.path.join(get_tests_output_path(), "audio_tests") | ||
WAV_FILE = os.path.join(get_tests_input_path(), "example_1.wav") | ||
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os.makedirs(OUT_PATH, exist_ok=True) | ||
conf = BaseAudioConfig(mel_fmax=8000, pitch_fmax=640, pitch_fmin=1) | ||
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# pylint: disable=protected-access | ||
class TestAudio(unittest.TestCase): | ||
def __init__(self, *args, **kwargs): | ||
super().__init__(*args, **kwargs) | ||
self.ap = AudioProcessor(**conf) | ||
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def test_audio_synthesis(self): | ||
"""1. load wav | ||
2. set normalization parameters | ||
3. extract mel-spec | ||
4. invert to wav and save the output | ||
""" | ||
print(" > Sanity check for the process wav -> mel -> wav") | ||
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def _test(max_norm, signal_norm, symmetric_norm, clip_norm): | ||
self.ap.max_norm = max_norm | ||
self.ap.signal_norm = signal_norm | ||
self.ap.symmetric_norm = symmetric_norm | ||
self.ap.clip_norm = clip_norm | ||
wav = self.ap.load_wav(WAV_FILE) | ||
mel = self.ap.melspectrogram(wav) | ||
wav_ = self.ap.inv_melspectrogram(mel) | ||
file_name = "/audio_test-melspec_max_norm_{}-signal_norm_{}-symmetric_{}-clip_norm_{}.wav".format( | ||
max_norm, signal_norm, symmetric_norm, clip_norm | ||
) | ||
print(" | > Creating wav file at : ", file_name) | ||
self.ap.save_wav(wav_, OUT_PATH + file_name) | ||
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# maxnorm = 1.0 | ||
_test(1.0, False, False, False) | ||
_test(1.0, True, False, False) | ||
_test(1.0, True, True, False) | ||
_test(1.0, True, False, True) | ||
_test(1.0, True, True, True) | ||
# maxnorm = 4.0 | ||
_test(4.0, False, False, False) | ||
_test(4.0, True, False, False) | ||
_test(4.0, True, True, False) | ||
_test(4.0, True, False, True) | ||
_test(4.0, True, True, True) | ||
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def test_normalize(self): | ||
"""Check normalization and denormalization for range values and consistency""" | ||
print(" > Testing normalization and denormalization.") | ||
wav = self.ap.load_wav(WAV_FILE) | ||
wav = self.ap.sound_norm(wav) # normalize audio to get abetter normalization range below. | ||
self.ap.signal_norm = False | ||
x = self.ap.melspectrogram(wav) | ||
x_old = x | ||
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self.ap.signal_norm = True | ||
self.ap.symmetric_norm = False | ||
self.ap.clip_norm = False | ||
self.ap.max_norm = 4.0 | ||
x_norm = self.ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
assert (x_old - x).sum() == 0 | ||
# check value range | ||
assert x_norm.max() <= self.ap.max_norm + 1, x_norm.max() | ||
assert x_norm.min() >= 0 - 1, x_norm.min() | ||
# check denorm. | ||
x_ = self.ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3, (x - x_).mean() | ||
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self.ap.signal_norm = True | ||
self.ap.symmetric_norm = False | ||
self.ap.clip_norm = True | ||
self.ap.max_norm = 4.0 | ||
x_norm = self.ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
# check value range | ||
assert x_norm.max() <= self.ap.max_norm, x_norm.max() | ||
assert x_norm.min() >= 0, x_norm.min() | ||
# check denorm. | ||
x_ = self.ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3, (x - x_).mean() | ||
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self.ap.signal_norm = True | ||
self.ap.symmetric_norm = True | ||
self.ap.clip_norm = False | ||
self.ap.max_norm = 4.0 | ||
x_norm = self.ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
# check value range | ||
assert x_norm.max() <= self.ap.max_norm + 1, x_norm.max() | ||
assert x_norm.min() >= -self.ap.max_norm - 2, x_norm.min() # pylint: disable=invalid-unary-operand-type | ||
assert x_norm.min() <= 0, x_norm.min() | ||
# check denorm. | ||
x_ = self.ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3, (x - x_).mean() | ||
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self.ap.signal_norm = True | ||
self.ap.symmetric_norm = True | ||
self.ap.clip_norm = True | ||
self.ap.max_norm = 4.0 | ||
x_norm = self.ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
# check value range | ||
assert x_norm.max() <= self.ap.max_norm, x_norm.max() | ||
assert x_norm.min() >= -self.ap.max_norm, x_norm.min() # pylint: disable=invalid-unary-operand-type | ||
assert x_norm.min() <= 0, x_norm.min() | ||
# check denorm. | ||
x_ = self.ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3, (x - x_).mean() | ||
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self.ap.signal_norm = True | ||
self.ap.symmetric_norm = False | ||
self.ap.max_norm = 1.0 | ||
x_norm = self.ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
assert x_norm.max() <= self.ap.max_norm, x_norm.max() | ||
assert x_norm.min() >= 0, x_norm.min() | ||
x_ = self.ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3 | ||
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self.ap.signal_norm = True | ||
self.ap.symmetric_norm = True | ||
self.ap.max_norm = 1.0 | ||
x_norm = self.ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
assert x_norm.max() <= self.ap.max_norm, x_norm.max() | ||
assert x_norm.min() >= -self.ap.max_norm, x_norm.min() # pylint: disable=invalid-unary-operand-type | ||
assert x_norm.min() < 0, x_norm.min() | ||
x_ = self.ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3 | ||
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def test_scaler(self): | ||
scaler_stats_path = os.path.join(get_tests_input_path(), "scale_stats.npy") | ||
conf.stats_path = scaler_stats_path | ||
conf.preemphasis = 0.0 | ||
conf.do_trim_silence = True | ||
conf.signal_norm = True | ||
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ap = AudioProcessor(**conf) | ||
mel_mean, mel_std, linear_mean, linear_std, _ = ap.load_stats(scaler_stats_path) | ||
ap.setup_scaler(mel_mean, mel_std, linear_mean, linear_std) | ||
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self.ap.signal_norm = False | ||
self.ap.preemphasis = 0.0 | ||
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# test scaler forward and backward transforms | ||
wav = self.ap.load_wav(WAV_FILE) | ||
mel_reference = self.ap.melspectrogram(wav) | ||
mel_norm = ap.melspectrogram(wav) | ||
mel_denorm = ap.denormalize(mel_norm) | ||
assert abs(mel_reference - mel_denorm).max() < 1e-4 | ||
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def test_compute_f0(self): # pylint: disable=no-self-use | ||
ap = AudioProcessor(**conf) | ||
wav = ap.load_wav(WAV_FILE) | ||
pitch = ap.compute_f0(wav) | ||
mel = ap.melspectrogram(wav) | ||
assert pitch.shape[0] == mel.shape[1] | ||
@pytest.fixture | ||
def ap(): | ||
"""Set up audio processor.""" | ||
return AudioProcessor(**conf) | ||
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norms = [ | ||
# maxnorm = 1.0 | ||
(1.0, False, False, False), | ||
(1.0, True, False, False), | ||
(1.0, True, True, False), | ||
(1.0, True, False, True), | ||
(1.0, True, True, True), | ||
# maxnorm = 4.0 | ||
(4.0, False, False, False), | ||
(4.0, True, False, False), | ||
(4.0, True, True, False), | ||
(4.0, True, False, True), | ||
(4.0, True, True, True), | ||
] | ||
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@pytest.mark.parametrize("norms", norms) | ||
def test_audio_synthesis(tmp_path, ap, norms): | ||
"""1. load wav | ||
2. set normalization parameters | ||
3. extract mel-spec | ||
4. invert to wav and save the output | ||
""" | ||
print(" > Sanity check for the process wav -> mel -> wav") | ||
max_norm, signal_norm, symmetric_norm, clip_norm = norms | ||
ap.max_norm = max_norm | ||
ap.signal_norm = signal_norm | ||
ap.symmetric_norm = symmetric_norm | ||
ap.clip_norm = clip_norm | ||
wav = ap.load_wav(WAV_FILE) | ||
mel = ap.melspectrogram(wav) | ||
wav_ = ap.inv_melspectrogram(mel) | ||
file_name = ( | ||
f"audio_test-melspec_max_norm_{max_norm}-signal_norm_{signal_norm}-" | ||
f"symmetric_{symmetric_norm}-clip_norm_{clip_norm}.wav" | ||
) | ||
print(" | > Creating wav file at : ", file_name) | ||
ap.save_wav(wav_, tmp_path / file_name) | ||
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def test_normalize(ap): | ||
"""Check normalization and denormalization for range values and consistency""" | ||
print(" > Testing normalization and denormalization.") | ||
wav = ap.load_wav(WAV_FILE) | ||
wav = ap.sound_norm(wav) # normalize audio to get abetter normalization range below. | ||
ap.signal_norm = False | ||
x = ap.melspectrogram(wav) | ||
x_old = x | ||
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ap.signal_norm = True | ||
ap.symmetric_norm = False | ||
ap.clip_norm = False | ||
ap.max_norm = 4.0 | ||
x_norm = ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {ap.max_norm}, ClipNorm:{ap.clip_norm}, SymmetricNorm:{ap.symmetric_norm}, SignalNorm:{ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
assert (x_old - x).sum() == 0 | ||
# check value range | ||
assert x_norm.max() <= ap.max_norm + 1, x_norm.max() | ||
assert x_norm.min() >= 0 - 1, x_norm.min() | ||
# check denorm. | ||
x_ = ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3, (x - x_).mean() | ||
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ap.signal_norm = True | ||
ap.symmetric_norm = False | ||
ap.clip_norm = True | ||
ap.max_norm = 4.0 | ||
x_norm = ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {ap.max_norm}, ClipNorm:{ap.clip_norm}, SymmetricNorm:{ap.symmetric_norm}, SignalNorm:{ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
# check value range | ||
assert x_norm.max() <= ap.max_norm, x_norm.max() | ||
assert x_norm.min() >= 0, x_norm.min() | ||
# check denorm. | ||
x_ = ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3, (x - x_).mean() | ||
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ap.signal_norm = True | ||
ap.symmetric_norm = True | ||
ap.clip_norm = False | ||
ap.max_norm = 4.0 | ||
x_norm = ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {ap.max_norm}, ClipNorm:{ap.clip_norm}, SymmetricNorm:{ap.symmetric_norm}, SignalNorm:{ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
# check value range | ||
assert x_norm.max() <= ap.max_norm + 1, x_norm.max() | ||
assert x_norm.min() >= -ap.max_norm - 2, x_norm.min() # pylint: disable=invalid-unary-operand-type | ||
assert x_norm.min() <= 0, x_norm.min() | ||
# check denorm. | ||
x_ = ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3, (x - x_).mean() | ||
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ap.signal_norm = True | ||
ap.symmetric_norm = True | ||
ap.clip_norm = True | ||
ap.max_norm = 4.0 | ||
x_norm = ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {ap.max_norm}, ClipNorm:{ap.clip_norm}, SymmetricNorm:{ap.symmetric_norm}, SignalNorm:{ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
# check value range | ||
assert x_norm.max() <= ap.max_norm, x_norm.max() | ||
assert x_norm.min() >= -ap.max_norm, x_norm.min() # pylint: disable=invalid-unary-operand-type | ||
assert x_norm.min() <= 0, x_norm.min() | ||
# check denorm. | ||
x_ = ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3, (x - x_).mean() | ||
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ap.signal_norm = True | ||
ap.symmetric_norm = False | ||
ap.max_norm = 1.0 | ||
x_norm = ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {ap.max_norm}, ClipNorm:{ap.clip_norm}, SymmetricNorm:{ap.symmetric_norm}, SignalNorm:{ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
assert x_norm.max() <= ap.max_norm, x_norm.max() | ||
assert x_norm.min() >= 0, x_norm.min() | ||
x_ = ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3 | ||
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ap.signal_norm = True | ||
ap.symmetric_norm = True | ||
ap.max_norm = 1.0 | ||
x_norm = ap.normalize(x) | ||
print( | ||
f" > MaxNorm: {ap.max_norm}, ClipNorm:{ap.clip_norm}, SymmetricNorm:{ap.symmetric_norm}, SignalNorm:{ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}" | ||
) | ||
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assert (x_old - x).sum() == 0 | ||
assert x_norm.max() <= ap.max_norm, x_norm.max() | ||
assert x_norm.min() >= -ap.max_norm, x_norm.min() # pylint: disable=invalid-unary-operand-type | ||
assert x_norm.min() < 0, x_norm.min() | ||
x_ = ap.denormalize(x_norm) | ||
assert (x - x_).sum() < 1e-3 | ||
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def test_scaler(ap): | ||
scaler_stats_path = os.path.join(get_tests_input_path(), "scale_stats.npy") | ||
conf.stats_path = scaler_stats_path | ||
conf.preemphasis = 0.0 | ||
conf.do_trim_silence = True | ||
conf.signal_norm = True | ||
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ap = AudioProcessor(**conf) | ||
mel_mean, mel_std, linear_mean, linear_std, _ = ap.load_stats(scaler_stats_path) | ||
ap.setup_scaler(mel_mean, mel_std, linear_mean, linear_std) | ||
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ap.signal_norm = False | ||
ap.preemphasis = 0.0 | ||
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# test scaler forward and backward transforms | ||
wav = ap.load_wav(WAV_FILE) | ||
mel_reference = ap.melspectrogram(wav) | ||
mel_norm = ap.melspectrogram(wav) | ||
mel_denorm = ap.denormalize(mel_norm) | ||
assert abs(mel_reference - mel_denorm).max() < 1e-4 | ||
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def test_compute_f0(ap): | ||
wav = ap.load_wav(WAV_FILE) | ||
pitch = ap.compute_f0(wav) | ||
mel = ap.melspectrogram(wav) | ||
assert pitch.shape[0] == mel.shape[1] |
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