Unverified Commit c4a17027 authored by jachymuv's avatar jachymuv Committed by GitHub
Browse files

Do not use IO functions in batch consistency test (#1521)

parent ae9560da
...@@ -74,8 +74,7 @@ class TestTransforms(common_utils.TorchaudioTestCase): ...@@ -74,8 +74,7 @@ class TestTransforms(common_utils.TorchaudioTestCase):
self.assertEqual(computed, expected) self.assertEqual(computed, expected)
def test_batch_mulaw(self): def test_batch_mulaw(self):
test_filepath = common_utils.get_asset_path('steam-train-whistle-daniel_simon.wav') waveform = common_utils.get_whitenoise(sample_rate=8000, duration=1, n_channels=2)
waveform, _ = torchaudio.load(test_filepath) # (2, 278756), 44100
# Single then transform then batch # Single then transform then batch
waveform_encoded = torchaudio.transforms.MuLawEncoding()(waveform) waveform_encoded = torchaudio.transforms.MuLawEncoding()(waveform)
...@@ -99,8 +98,7 @@ class TestTransforms(common_utils.TorchaudioTestCase): ...@@ -99,8 +98,7 @@ class TestTransforms(common_utils.TorchaudioTestCase):
self.assertEqual(computed, expected) self.assertEqual(computed, expected)
def test_batch_spectrogram(self): def test_batch_spectrogram(self):
test_filepath = common_utils.get_asset_path('steam-train-whistle-daniel_simon.wav') waveform = common_utils.get_whitenoise(sample_rate=8000, duration=1, n_channels=2)
waveform, _ = torchaudio.load(test_filepath) # (2, 278756), 44100
# Single then transform then batch # Single then transform then batch
expected = torchaudio.transforms.Spectrogram()(waveform).repeat(3, 1, 1, 1) expected = torchaudio.transforms.Spectrogram()(waveform).repeat(3, 1, 1, 1)
...@@ -110,8 +108,7 @@ class TestTransforms(common_utils.TorchaudioTestCase): ...@@ -110,8 +108,7 @@ class TestTransforms(common_utils.TorchaudioTestCase):
self.assertEqual(computed, expected) self.assertEqual(computed, expected)
def test_batch_melspectrogram(self): def test_batch_melspectrogram(self):
test_filepath = common_utils.get_asset_path('steam-train-whistle-daniel_simon.wav') waveform = common_utils.get_whitenoise(sample_rate=8000, duration=1, n_channels=2)
waveform, _ = torchaudio.load(test_filepath) # (2, 278756), 44100
# Single then transform then batch # Single then transform then batch
expected = torchaudio.transforms.MelSpectrogram()(waveform).repeat(3, 1, 1, 1) expected = torchaudio.transforms.MelSpectrogram()(waveform).repeat(3, 1, 1, 1)
...@@ -121,8 +118,7 @@ class TestTransforms(common_utils.TorchaudioTestCase): ...@@ -121,8 +118,7 @@ class TestTransforms(common_utils.TorchaudioTestCase):
self.assertEqual(computed, expected) self.assertEqual(computed, expected)
def test_batch_mfcc(self): def test_batch_mfcc(self):
test_filepath = common_utils.get_asset_path('steam-train-whistle-daniel_simon.wav') waveform = common_utils.get_whitenoise(sample_rate=8000, duration=1, n_channels=2)
waveform, _ = torchaudio.load(test_filepath)
# Single then transform then batch # Single then transform then batch
expected = torchaudio.transforms.MFCC()(waveform).repeat(3, 1, 1, 1) expected = torchaudio.transforms.MFCC()(waveform).repeat(3, 1, 1, 1)
...@@ -160,8 +156,7 @@ class TestTransforms(common_utils.TorchaudioTestCase): ...@@ -160,8 +156,7 @@ class TestTransforms(common_utils.TorchaudioTestCase):
self.assertEqual(computed, expected, atol=1e-5, rtol=1e-5) self.assertEqual(computed, expected, atol=1e-5, rtol=1e-5)
def test_batch_Fade(self): def test_batch_Fade(self):
test_filepath = common_utils.get_asset_path('steam-train-whistle-daniel_simon.wav') waveform = common_utils.get_whitenoise(sample_rate=8000, duration=1, n_channels=2)
waveform, _ = torchaudio.load(test_filepath) # (2, 278756), 44100
fade_in_len = 3000 fade_in_len = 3000
fade_out_len = 3000 fade_out_len = 3000
...@@ -173,8 +168,7 @@ class TestTransforms(common_utils.TorchaudioTestCase): ...@@ -173,8 +168,7 @@ class TestTransforms(common_utils.TorchaudioTestCase):
self.assertEqual(computed, expected) self.assertEqual(computed, expected)
def test_batch_Vol(self): def test_batch_Vol(self):
test_filepath = common_utils.get_asset_path('steam-train-whistle-daniel_simon.wav') waveform = common_utils.get_whitenoise(sample_rate=8000, duration=1, n_channels=2)
waveform, _ = torchaudio.load(test_filepath) # (2, 278756), 44100
# Single then transform then batch # Single then transform then batch
expected = torchaudio.transforms.Vol(gain=1.1)(waveform).repeat(3, 1, 1) expected = torchaudio.transforms.Vol(gain=1.1)(waveform).repeat(3, 1, 1)
......
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