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Unverified Commit 84c494dd authored by Bhargav Kathivarapu's avatar Bhargav Kathivarapu Committed by GitHub
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Fix sox tests variable names (#559)

parent b42d6100
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Showing with 44 additions and 44 deletions
test/test_sox_compatibility.py
View file @ 84c494dd
...@@ -78,16 +78,16 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -78,16 +78,16 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad lowpass filter, compare to SoX implementation Test biquad lowpass filter, compare to SoX implementation
""" """
CUTOFF_FREQ = 3000 cutoff_freq = 3000
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("lowpass", [CUTOFF_FREQ]) E.append_effect_to_chain("lowpass", [cutoff_freq])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.lowpass_biquad(waveform, sample_rate, CUTOFF_FREQ) output_waveform = F.lowpass_biquad(waveform, sample_rate, cutoff_freq)
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
...@@ -98,16 +98,16 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -98,16 +98,16 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad highpass filter, compare to SoX implementation Test biquad highpass filter, compare to SoX implementation
""" """
CUTOFF_FREQ = 2000 cutoff_freq = 2000
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("highpass", [CUTOFF_FREQ]) E.append_effect_to_chain("highpass", [cutoff_freq])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.highpass_biquad(waveform, sample_rate, CUTOFF_FREQ) output_waveform = F.highpass_biquad(waveform, sample_rate, cutoff_freq)
# TBD - this fails at the 1e-4 level, debug why # TBD - this fails at the 1e-4 level, debug why
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-3, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-3, rtol=1e-5)
...@@ -119,17 +119,17 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -119,17 +119,17 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad allpass filter, compare to SoX implementation Test biquad allpass filter, compare to SoX implementation
""" """
CENTRAL_FREQ = 1000 central_freq = 1000
Q = 0.707 q = 0.707
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("allpass", [CENTRAL_FREQ, str(Q) + 'q']) E.append_effect_to_chain("allpass", [central_freq, str(q) + 'q'])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.allpass_biquad(waveform, sample_rate, CENTRAL_FREQ, Q) output_waveform = F.allpass_biquad(waveform, sample_rate, central_freq, q)
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
...@@ -140,18 +140,18 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -140,18 +140,18 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad bandpass filter, compare to SoX implementation Test biquad bandpass filter, compare to SoX implementation
""" """
CENTRAL_FREQ = 1000 central_freq = 1000
Q = 0.707 q = 0.707
CONST_SKIRT_GAIN = True const_skirt_gain = True
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("bandpass", ["-c", CENTRAL_FREQ, str(Q) + 'q']) E.append_effect_to_chain("bandpass", ["-c", central_freq, str(q) + 'q'])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.bandpass_biquad(waveform, sample_rate, CENTRAL_FREQ, Q, CONST_SKIRT_GAIN) output_waveform = F.bandpass_biquad(waveform, sample_rate, central_freq, q, const_skirt_gain)
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
...@@ -162,18 +162,18 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -162,18 +162,18 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad bandpass filter, compare to SoX implementation Test biquad bandpass filter, compare to SoX implementation
""" """
CENTRAL_FREQ = 1000 central_freq = 1000
Q = 0.707 q = 0.707
CONST_SKIRT_GAIN = False const_skirt_gain = False
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("bandpass", [CENTRAL_FREQ, str(Q) + 'q']) E.append_effect_to_chain("bandpass", [central_freq, str(q) + 'q'])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.bandpass_biquad(waveform, sample_rate, CENTRAL_FREQ, Q, CONST_SKIRT_GAIN) output_waveform = F.bandpass_biquad(waveform, sample_rate, central_freq, q, const_skirt_gain)
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
...@@ -184,17 +184,17 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -184,17 +184,17 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad bandreject filter, compare to SoX implementation Test biquad bandreject filter, compare to SoX implementation
""" """
CENTRAL_FREQ = 1000 central_freq = 1000
Q = 0.707 q = 0.707
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("bandreject", [CENTRAL_FREQ, str(Q) + 'q']) E.append_effect_to_chain("bandreject", [central_freq, str(q) + 'q'])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.bandreject_biquad(waveform, sample_rate, CENTRAL_FREQ, Q) output_waveform = F.bandreject_biquad(waveform, sample_rate, central_freq, q)
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
...@@ -205,18 +205,18 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -205,18 +205,18 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad band filter with noise mode, compare to SoX implementation Test biquad band filter with noise mode, compare to SoX implementation
""" """
CENTRAL_FREQ = 1000 central_freq = 1000
Q = 0.707 q = 0.707
NOISE = True noise = True
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("band", ["-n", CENTRAL_FREQ, str(Q) + 'q']) E.append_effect_to_chain("band", ["-n", central_freq, str(q) + 'q'])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.band_biquad(waveform, sample_rate, CENTRAL_FREQ, Q, NOISE) output_waveform = F.band_biquad(waveform, sample_rate, central_freq, q, noise)
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
...@@ -227,18 +227,18 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -227,18 +227,18 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad band filter without noise mode, compare to SoX implementation Test biquad band filter without noise mode, compare to SoX implementation
""" """
CENTRAL_FREQ = 1000 central_freq = 1000
Q = 0.707 q = 0.707
NOISE = False noise = False
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("band", [CENTRAL_FREQ, str(Q) + 'q']) E.append_effect_to_chain("band", [central_freq, str(q) + 'q'])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.band_biquad(waveform, sample_rate, CENTRAL_FREQ, Q, NOISE) output_waveform = F.band_biquad(waveform, sample_rate, central_freq, q, noise)
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
...@@ -249,18 +249,18 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -249,18 +249,18 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad treble filter, compare to SoX implementation Test biquad treble filter, compare to SoX implementation
""" """
CENTRAL_FREQ = 1000 central_freq = 1000
Q = 0.707 q = 0.707
GAIN = 40 gain = 40
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("treble", [GAIN, CENTRAL_FREQ, str(Q) + 'q']) E.append_effect_to_chain("treble", [gain, central_freq, str(q) + 'q'])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.treble_biquad(waveform, sample_rate, GAIN, CENTRAL_FREQ, Q) output_waveform = F.treble_biquad(waveform, sample_rate, gain, central_freq, q)
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
...@@ -325,18 +325,18 @@ class TestFunctionalFiltering(unittest.TestCase): ...@@ -325,18 +325,18 @@ class TestFunctionalFiltering(unittest.TestCase):
Test biquad peaking equalizer filter, compare to SoX implementation Test biquad peaking equalizer filter, compare to SoX implementation
""" """
CENTER_FREQ = 300 center_freq = 300
Q = 0.707 q = 0.707
GAIN = 1 gain = 1
noise_filepath = common_utils.get_asset_path('whitenoise.wav') noise_filepath = common_utils.get_asset_path('whitenoise.wav')
E = torchaudio.sox_effects.SoxEffectsChain() E = torchaudio.sox_effects.SoxEffectsChain()
E.set_input_file(noise_filepath) E.set_input_file(noise_filepath)
E.append_effect_to_chain("equalizer", [CENTER_FREQ, Q, GAIN]) E.append_effect_to_chain("equalizer", [center_freq, q, gain])
sox_output_waveform, sr = E.sox_build_flow_effects() sox_output_waveform, sr = E.sox_build_flow_effects()
waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True) waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
output_waveform = F.equalizer_biquad(waveform, sample_rate, CENTER_FREQ, GAIN, Q) output_waveform = F.equalizer_biquad(waveform, sample_rate, center_freq, gain, q)
torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5) torch.testing.assert_allclose(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
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