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use torch.testing.assertclose instead to get more details about error in cis (#35659)

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* use torch.testing.assertclose instead to get more details about error in cis

* fix

* style

* test_all

* revert for I bert

* fixes and updates

* more image processing fixes

* more image processors

* fix mamba and co

* style

* less strick

* ok I won't be strict

* skip and be done

* up
This commit is contained in:
Arthur
2025-01-24 16:55:28 +01:00
committed by GitHub
parent 72d1a4cd53
commit b912f5ee43
255 changed files with 1048 additions and 969 deletions
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4
tests/models/univnet/test_feature_extraction_univnet.py
View File

@@ -360,6 +360,6 @@ class UnivNetFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.
EXPECTED_MEAN = torch.tensor(-6.18862009)
EXPECTED_STDDEV = torch.tensor(2.80845642)
torch.testing.assert_close(input_features_mean, EXPECTED_MEAN, atol=5e-5, rtol=5e-6)
torch.testing.assert_close(input_features_mean, EXPECTED_MEAN, rtol=5e-5, atol=5e-5)
torch.testing.assert_close(input_features_stddev, EXPECTED_STDDEV)
torch.testing.assert_close(input_features[0, :30, 0], EXPECTED_INPUT_FEATURES, atol=1e-4, rtol=1e-5)
torch.testing.assert_close(input_features[0, :30, 0], EXPECTED_INPUT_FEATURES, rtol=1e-4, atol=1e-4)

18
tests/models/univnet/test_modeling_univnet.py
View File

@@ -276,9 +276,9 @@ class UnivNetModelIntegrationTests(unittest.TestCase):
EXPECTED_STDDEV = torch.tensor(0.35230172)
EXPECTED_SLICE = torch.tensor([-0.3408, -0.6045, -0.5052, 0.1160, -0.1556, -0.0405, -0.3024, -0.5290, -0.5019])
torch.testing.assert_close(waveform_mean, EXPECTED_MEAN, atol=1e-4, rtol=1e-5)
torch.testing.assert_close(waveform_stddev, EXPECTED_STDDEV, atol=1e-4, rtol=1e-5)
torch.testing.assert_close(waveform_slice, EXPECTED_SLICE, atol=5e-4, rtol=1e-5)
torch.testing.assert_close(waveform_mean, EXPECTED_MEAN, rtol=1e-4, atol=1e-4)
torch.testing.assert_close(waveform_stddev, EXPECTED_STDDEV, rtol=1e-4, atol=1e-4)
torch.testing.assert_close(waveform_slice, EXPECTED_SLICE, rtol=5e-4, atol=5e-4)
def test_model_inference_unbatched(self):
# Load sample checkpoint from Tortoise TTS
@@ -300,9 +300,9 @@ class UnivNetModelIntegrationTests(unittest.TestCase):
EXPECTED_STDDEV = torch.tensor(0.33986747)
EXPECTED_SLICE = torch.tensor([-0.3276, -0.5504, -0.3484, 0.3574, -0.0373, -0.1826, -0.4880, -0.6431, -0.5162])
torch.testing.assert_close(waveform_mean, EXPECTED_MEAN, atol=1e-4, rtol=1e-5)
torch.testing.assert_close(waveform_stddev, EXPECTED_STDDEV, atol=1e-4, rtol=1e-5)
torch.testing.assert_close(waveform_slice, EXPECTED_SLICE, atol=1e-3, rtol=1e-5)
torch.testing.assert_close(waveform_mean, EXPECTED_MEAN, rtol=1e-4, atol=1e-4)
torch.testing.assert_close(waveform_stddev, EXPECTED_STDDEV, rtol=1e-4, atol=1e-4)
torch.testing.assert_close(waveform_slice, EXPECTED_SLICE, rtol=1e-3, atol=1e-3)
def test_integration(self):
feature_extractor = UnivNetFeatureExtractor.from_pretrained("dg845/univnet-dev")
@@ -331,6 +331,6 @@ class UnivNetModelIntegrationTests(unittest.TestCase):
EXPECTED_SLICE = torch.tensor([-4.3934e-04, -1.8203e-04, -3.3033e-04, -3.8716e-04, -1.6125e-04, 3.5389e-06, -3.3149e-04, -3.7613e-04, -2.3331e-04])
# fmt: on
torch.testing.assert_close(waveform_mean, EXPECTED_MEAN, atol=5e-6, rtol=1e-5)
torch.testing.assert_close(waveform_stddev, EXPECTED_STDDEV, atol=1e-4, rtol=1e-5)
torch.testing.assert_close(waveform_slice, EXPECTED_SLICE, atol=5e-6, rtol=1e-5)
torch.testing.assert_close(waveform_mean, EXPECTED_MEAN, rtol=5e-6, atol=5e-6)
torch.testing.assert_close(waveform_stddev, EXPECTED_STDDEV, rtol=1e-4, atol=1e-4)
torch.testing.assert_close(waveform_slice, EXPECTED_SLICE, rtol=5e-6, atol=5e-6)