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import itertools
from pathlib import Path
from parameterized import parameterized
from torchaudio import sox_effects
from torchaudio_unittest.common_utils import (
get_sinusoid,
get_wav_data,
load_wav,
PytorchTestCase,
save_wav,
skipIfNoSox,
sox_utils,
TempDirMixin,
)
from .common import load_params, name_func
@skipIfNoSox
class TestSoxEffects(PytorchTestCase):
def test_init(self):
"""Calling init_sox_effects multiple times does not crush"""
for _ in range(3):
sox_effects.init_sox_effects()
@skipIfNoSox
class TestSoxEffectsTensor(TempDirMixin, PytorchTestCase):
"""Test suite for `apply_effects_tensor` function"""
@parameterized.expand(
list(itertools.product(["float32", "int32", "int16", "uint8"], [8000, 16000], [1, 2, 4, 8], [True, False])),
name_func=name_func,
)
def test_apply_no_effect(self, dtype, sample_rate, num_channels, channels_first):
"""`apply_effects_tensor` without effects should return identical data as input"""
original = get_wav_data(dtype, num_channels, channels_first=channels_first)
expected = original.clone()
found, output_sample_rate = sox_effects.apply_effects_tensor(expected, sample_rate, [], channels_first)
assert output_sample_rate == sample_rate
# SoxEffect should not alter the input Tensor object
self.assertEqual(original, expected)
# SoxEffect should not return the same Tensor object
assert expected is not found
# Returned Tensor should equal to the input Tensor
self.assertEqual(expected, found)
@parameterized.expand(
load_params("sox_effect_test_args.jsonl"),
name_func=lambda f, i, p: f'{f.__name__}_{i}_{p.args[0]["effects"][0][0]}',
)
def test_apply_effects(self, args):
"""`apply_effects_tensor` should return identical data as sox command"""
effects = args["effects"]
num_channels = args.get("num_channels", 2)
input_sr = args.get("input_sample_rate", 8000)
output_sr = args.get("output_sample_rate")
input_path = self.get_temp_path("input.wav")
reference_path = self.get_temp_path("reference.wav")
original = get_sinusoid(frequency=800, sample_rate=input_sr, n_channels=num_channels, dtype="float32")
save_wav(input_path, original, input_sr)
sox_utils.run_sox_effect(input_path, reference_path, effects, output_sample_rate=output_sr)
expected, expected_sr = load_wav(reference_path)
found, sr = sox_effects.apply_effects_tensor(original, input_sr, effects)
assert sr == expected_sr
self.assertEqual(expected, found)
@skipIfNoSox
class TestSoxEffectsFile(TempDirMixin, PytorchTestCase):
"""Test suite for `apply_effects_file` function"""
@parameterized.expand(
list(
itertools.product(
["float32", "int32", "int16", "uint8"],
[8000, 16000],
[1, 2, 4, 8],
[False, True],
)
),
name_func=name_func,
)
def test_apply_no_effect(self, dtype, sample_rate, num_channels, channels_first):
"""`apply_effects_file` without effects should return identical data as input"""
path = self.get_temp_path("input.wav")
expected = get_wav_data(dtype, num_channels, channels_first=channels_first)
save_wav(path, expected, sample_rate, channels_first=channels_first)
found, output_sample_rate = sox_effects.apply_effects_file(
path, [], normalize=False, channels_first=channels_first
)
assert output_sample_rate == sample_rate
self.assertEqual(expected, found)
@parameterized.expand(
load_params("sox_effect_test_args.jsonl"),
name_func=lambda f, i, p: f'{f.__name__}_{i}_{p.args[0]["effects"][0][0]}',
)
def test_apply_effects_str(self, args):
"""`apply_effects_file` should return identical data as sox command"""
dtype = "int32"
channels_first = True
effects = args["effects"]
num_channels = args.get("num_channels", 2)
input_sr = args.get("input_sample_rate", 8000)
output_sr = args.get("output_sample_rate")
input_path = self.get_temp_path("input.wav")
reference_path = self.get_temp_path("reference.wav")
data = get_wav_data(dtype, num_channels, channels_first=channels_first)
save_wav(input_path, data, input_sr, channels_first=channels_first)
sox_utils.run_sox_effect(input_path, reference_path, effects, output_sample_rate=output_sr)
expected, expected_sr = load_wav(reference_path)
found, sr = sox_effects.apply_effects_file(input_path, effects, normalize=False, channels_first=channels_first)
assert sr == expected_sr
self.assertEqual(found, expected)
def test_apply_effects_path(self):
"""`apply_effects_file` should return identical data as sox command when file path is given as a Path Object"""
dtype = "int32"
channels_first = True
effects = [["hilbert"]]
num_channels = 2
input_sr = 8000
output_sr = 8000
input_path = self.get_temp_path("input.wav")
reference_path = self.get_temp_path("reference.wav")
data = get_wav_data(dtype, num_channels, channels_first=channels_first)
save_wav(input_path, data, input_sr, channels_first=channels_first)
sox_utils.run_sox_effect(input_path, reference_path, effects, output_sample_rate=output_sr)
expected, expected_sr = load_wav(reference_path)
found, sr = sox_effects.apply_effects_file(
Path(input_path), effects, normalize=False, channels_first=channels_first
)
assert sr == expected_sr
self.assertEqual(found, expected)
@skipIfNoSox
class TestFileFormats(TempDirMixin, PytorchTestCase):
"""`apply_effects_file` gives the same result as sox on various file formats"""
@parameterized.expand(
list(
itertools.product(
["float32", "int32", "int16", "uint8"],
[8000, 16000],
[1, 2],
)
),
name_func=lambda f, _, p: f'{f.__name__}_{"_".join(str(arg) for arg in p.args)}',
)
def test_wav(self, dtype, sample_rate, num_channels):
"""`apply_effects_file` works on various wav format"""
channels_first = True
effects = [["band", "300", "10"]]
input_path = self.get_temp_path("input.wav")
reference_path = self.get_temp_path("reference.wav")
data = get_wav_data(dtype, num_channels, channels_first=channels_first)
save_wav(input_path, data, sample_rate, channels_first=channels_first)
sox_utils.run_sox_effect(input_path, reference_path, effects)
expected, expected_sr = load_wav(reference_path)
found, sr = sox_effects.apply_effects_file(input_path, effects, normalize=False, channels_first=channels_first)
assert sr == expected_sr
self.assertEqual(found, expected)
@parameterized.expand(
list(
itertools.product(
[8000, 16000],
[1, 2],
)
),
name_func=lambda f, _, p: f'{f.__name__}_{"_".join(str(arg) for arg in p.args)}',
)
def test_flac(self, sample_rate, num_channels):
"""`apply_effects_file` works on various flac format"""
channels_first = True
effects = [["band", "300", "10"]]
input_path = self.get_temp_path("input.flac")
reference_path = self.get_temp_path("reference.wav")
sox_utils.gen_audio_file(input_path, sample_rate, num_channels)
sox_utils.run_sox_effect(input_path, reference_path, effects, output_bitdepth=32)
expected, expected_sr = load_wav(reference_path)
found, sr = sox_effects.apply_effects_file(input_path, effects, channels_first=channels_first)
save_wav(self.get_temp_path("result.wav"), found, sr, channels_first=channels_first)
assert sr == expected_sr
self.assertEqual(found, expected)
@parameterized.expand(
list(
itertools.product(
[8000, 16000],
[1, 2],
)
),
name_func=lambda f, _, p: f'{f.__name__}_{"_".join(str(arg) for arg in p.args)}',
)
def test_vorbis(self, sample_rate, num_channels):
"""`apply_effects_file` works on various vorbis format"""
channels_first = True
effects = [["band", "300", "10"]]
input_path = self.get_temp_path("input.vorbis")
reference_path = self.get_temp_path("reference.wav")
sox_utils.gen_audio_file(input_path, sample_rate, num_channels)
sox_utils.run_sox_effect(input_path, reference_path, effects, output_bitdepth=32)
expected, expected_sr = load_wav(reference_path)
found, sr = sox_effects.apply_effects_file(input_path, effects, channels_first=channels_first)
save_wav(self.get_temp_path("result.wav"), found, sr, channels_first=channels_first)
assert sr == expected_sr
self.assertEqual(found, expected)
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