diff --git a/test/torchaudio_unittest/functional/autograd_impl.py b/test/torchaudio_unittest/functional/autograd_impl.py index 2d9dca76d6..e273369ea6 100644 --- a/test/torchaudio_unittest/functional/autograd_impl.py +++ b/test/torchaudio_unittest/functional/autograd_impl.py @@ -29,7 +29,7 @@ def assert_grad( def test_lfilter_x(self): torch.random.manual_seed(2434) - x = get_whitenoise(sample_rate=22050, duration=0.025, n_channels=2) + x = get_whitenoise(sample_rate=22050, duration=0.01, n_channels=2) a = torch.tensor([0.7, 0.2, 0.6]) b = torch.tensor([0.4, 0.2, 0.9]) x.requires_grad = True @@ -37,7 +37,7 @@ def test_lfilter_x(self): def test_lfilter_a(self): torch.random.manual_seed(2434) - x = get_whitenoise(sample_rate=22050, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=22050, duration=0.01, n_channels=2) a = torch.tensor([0.7, 0.2, 0.6]) b = torch.tensor([0.4, 0.2, 0.9]) a.requires_grad = True @@ -45,7 +45,7 @@ def test_lfilter_a(self): def test_lfilter_b(self): torch.random.manual_seed(2434) - x = get_whitenoise(sample_rate=22050, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=22050, duration=0.01, n_channels=2) a = torch.tensor([0.7, 0.2, 0.6]) b = torch.tensor([0.4, 0.2, 0.9]) b.requires_grad = True @@ -53,14 +53,14 @@ def test_lfilter_b(self): def test_lfilter_all_inputs(self): torch.random.manual_seed(2434) - x = get_whitenoise(sample_rate=22050, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=22050, duration=0.01, n_channels=2) a = torch.tensor([0.7, 0.2, 0.6]) b = torch.tensor([0.4, 0.2, 0.9]) self.assert_grad(F.lfilter, (x, a, b)) def test_biquad(self): torch.random.manual_seed(2434) - x = get_whitenoise(sample_rate=22050, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=22050, duration=0.01, n_channels=1) a = torch.tensor([0.7, 0.2, 0.6]) b = torch.tensor([0.4, 0.2, 0.9]) self.assert_grad(F.biquad, (x, b[0], b[1], b[2], a[0], a[1], a[2])) @@ -72,7 +72,7 @@ def test_biquad(self): def test_band_biquad(self, central_freq, Q, noise): torch.random.manual_seed(2434) sr = 22050 - x = get_whitenoise(sample_rate=sr, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=sr, duration=0.01, n_channels=1) central_freq = torch.tensor(central_freq) Q = torch.tensor(Q) self.assert_grad(F.band_biquad, (x, sr, central_freq, Q, noise)) @@ -84,7 +84,7 @@ def test_band_biquad(self, central_freq, Q, noise): def test_bass_biquad(self, central_freq, Q, gain): torch.random.manual_seed(2434) sr = 22050 - x = get_whitenoise(sample_rate=sr, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=sr, duration=0.01, n_channels=1) central_freq = torch.tensor(central_freq) Q = torch.tensor(Q) gain = torch.tensor(gain) @@ -98,7 +98,7 @@ def test_bass_biquad(self, central_freq, Q, gain): def test_treble_biquad(self, central_freq, Q, gain): torch.random.manual_seed(2434) sr = 22050 - x = get_whitenoise(sample_rate=sr, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=sr, duration=0.01, n_channels=1) central_freq = torch.tensor(central_freq) Q = torch.tensor(Q) gain = torch.tensor(gain) @@ -110,7 +110,7 @@ def test_treble_biquad(self, central_freq, Q, gain): def test_allpass_biquad(self, central_freq, Q): torch.random.manual_seed(2434) sr = 22050 - x = get_whitenoise(sample_rate=sr, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=sr, duration=0.01, n_channels=1) central_freq = torch.tensor(central_freq) Q = torch.tensor(Q) self.assert_grad(F.allpass_biquad, (x, sr, central_freq, Q)) @@ -121,7 +121,7 @@ def test_allpass_biquad(self, central_freq, Q): def test_lowpass_biquad(self, cutoff_freq, Q): torch.random.manual_seed(2434) sr = 22050 - x = get_whitenoise(sample_rate=sr, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=sr, duration=0.01, n_channels=1) cutoff_freq = torch.tensor(cutoff_freq) Q = torch.tensor(Q) self.assert_grad(F.lowpass_biquad, (x, sr, cutoff_freq, Q)) @@ -132,7 +132,7 @@ def test_lowpass_biquad(self, cutoff_freq, Q): def test_highpass_biquad(self, cutoff_freq, Q): torch.random.manual_seed(2434) sr = 22050 - x = get_whitenoise(sample_rate=sr, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=sr, duration=0.01, n_channels=1) cutoff_freq = torch.tensor(cutoff_freq) Q = torch.tensor(Q) self.assert_grad(F.highpass_biquad, (x, sr, cutoff_freq, Q)) @@ -144,7 +144,7 @@ def test_highpass_biquad(self, cutoff_freq, Q): def test_bandpass_biquad(self, central_freq, Q, const_skirt_gain): torch.random.manual_seed(2434) sr = 22050 - x = get_whitenoise(sample_rate=sr, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=sr, duration=0.01, n_channels=1) central_freq = torch.tensor(central_freq) Q = torch.tensor(Q) self.assert_grad(F.bandpass_biquad, (x, sr, central_freq, Q, const_skirt_gain)) @@ -156,7 +156,7 @@ def test_bandpass_biquad(self, central_freq, Q, const_skirt_gain): def test_equalizer_biquad(self, central_freq, Q, gain): torch.random.manual_seed(2434) sr = 22050 - x = get_whitenoise(sample_rate=sr, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=sr, duration=0.01, n_channels=1) central_freq = torch.tensor(central_freq) Q = torch.tensor(Q) gain = torch.tensor(gain) @@ -168,7 +168,7 @@ def test_equalizer_biquad(self, central_freq, Q, gain): def test_bandreject_biquad(self, central_freq, Q): torch.random.manual_seed(2434) sr = 22050 - x = get_whitenoise(sample_rate=sr, duration=0.05, n_channels=2) + x = get_whitenoise(sample_rate=sr, duration=0.01, n_channels=1) central_freq = torch.tensor(central_freq) Q = torch.tensor(Q) self.assert_grad(F.bandreject_biquad, (x, sr, central_freq, Q))