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])