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'])