def test_dcshift_with_limiter(self):
shift = 0.5
limiter_gain = 0.05
data, path = self.get_whitenoise()
result = F.dcshift(data, shift, limiter_gain)
self.assert_sox_effect(result, path, ['dcshift', shift, limiter_gain])
def test_dcshift_without_limiter(self):
"""
Test dcshift effect, compare to SoX implementation
"""
shift = 0.6
noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath)
E.append_effect_to_chain("dcshift", [shift])
sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, _ = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.dcshift(waveform, shift)
self.assertEqual(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
def test_dcshift_without_limiter(self):
"""
Test dcshift effect, compare to SoX implementation
"""
shift = 0.6
E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(self.noise_filepath)
E.append_effect_to_chain("dcshift", [shift])
sox_output_waveform, sr = E.sox_build_flow_effects()
output_waveform = F.dcshift(self.noise_waveform, shift)
self.assertEqual(output_waveform,
sox_output_waveform,
atol=1e-4,
rtol=1e-5)
def func(tensor):
shift = 0.5
limiter_gain = 0.05
return F.dcshift(tensor, shift, limiter_gain)
def test_dcshift_without_limiter(self):
shift = 0.6
data, path = self.get_whitenoise()
result = F.dcshift(data, shift)
self.assert_sox_effect(result, path, ['dcshift', shift])
