def test_batch_Fade(self):
waveform, sample_rate = torchaudio.load(self.test_filepath)
fade_in_len = 3000
fade_out_len = 3000
# Single then transform then batch
expected = transforms.Fade(fade_in_len, fade_out_len)(waveform).repeat(3, 1, 1)
# Batch then transform
computed = transforms.Fade(fade_in_len, fade_out_len)(waveform.repeat(3, 1, 1))
self.assertTrue(computed.shape == expected.shape, (computed.shape, expected.shape))
self.assertTrue(torch.allclose(computed, expected))
def test_Fade(self):
test_filepath = common_utils.get_asset_path(
'steam-train-whistle-daniel_simon.wav')
waveform, _ = torchaudio.load(test_filepath)
fade_in_len = 3000
fade_out_len = 3000
self._assert_consistency(T.Fade(fade_in_len, fade_out_len), waveform)
def test_Fade(self):
test_filepath = os.path.join(common_utils.TEST_DIR_PATH, 'assets',
'steam-train-whistle-daniel_simon.wav')
waveform, _ = torchaudio.load(test_filepath)
fade_in_len = 3000
fade_out_len = 3000
self._assert_consistency(T.Fade(fade_in_len, fade_out_len), waveform)
def test_fade(self, fade_shape):
transform = T.Fade(fade_shape=fade_shape)
waveform = get_whitenoise(sample_rate=8000, duration=0.05, n_channels=2)
self.assert_grad(transform, [waveform], nondet_tol=1e-10)
def test_Fade(self):
waveform = common_utils.get_whitenoise()
fade_in_len = 3000
fade_out_len = 3000
self._assert_consistency(T.Fade(fade_in_len, fade_out_len), waveform)
def test_fade(self, fade_shape_sox, fade_shape):
fade_in_len, fade_out_len = 44100, 44100
data, path = self.get_whitenoise(sample_rate=44100)
result = T.Fade(fade_in_len, fade_out_len, fade_shape)(data)
self.assert_sox_effect(result, path,
['fade', fade_shape_sox, '1', '0', '1'])
