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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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12
tests/models/clap/test_feature_extraction_clap.py
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@@ -285,8 +285,8 @@ class ClapFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Tes
input_features = feature_extractor(input_speech, return_tensors="pt", padding=padding).input_features
self.assertEqual(input_features.shape, (1, 4, 1001, 64))
self.assertTrue(torch.allclose(input_features[0, 0, idx_in_mel[0]], EXPECTED_VALUES[0], atol=1e-4))
self.assertTrue(torch.allclose(input_features[0, 0, idx_in_mel[1]], EXPECTED_VALUES[1], atol=1e-4))
torch.testing.assert_close(input_features[0, 0, idx_in_mel[0]], EXPECTED_VALUES[0], rtol=1e-4, atol=1e-4)
torch.testing.assert_close(input_features[0, 0, idx_in_mel[1]], EXPECTED_VALUES[1], rtol=1e-4, atol=1e-4)
self.assertTrue(torch.all(input_features[0, 0] == input_features[0, 1]))
self.assertTrue(torch.all(input_features[0, 0] == input_features[0, 2]))
@@ -408,8 +408,8 @@ class ClapFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Tes
input_speech, return_tensors="pt", truncation="rand_trunc", padding=padding
).input_features
self.assertEqual(input_features.shape, (1, 1, 1001, 64))
self.assertTrue(torch.allclose(input_features[0, 0, idx_in_mel[0]], EXPECTED_VALUES[0], atol=1e-4))
self.assertTrue(torch.allclose(input_features[0, 0, idx_in_mel[1]], EXPECTED_VALUES[1], atol=1e-4))
torch.testing.assert_close(input_features[0, 0, idx_in_mel[0]], EXPECTED_VALUES[0], rtol=1e-4, atol=1e-4)
torch.testing.assert_close(input_features[0, 0, idx_in_mel[1]], EXPECTED_VALUES[1], rtol=1e-4, atol=1e-4)
def test_integration_fusion_long_input(self):
# fmt: off
@@ -475,7 +475,7 @@ class ClapFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Tes
set_seed(987654321)
input_features = feature_extractor(input_speech, return_tensors="pt", padding=padding).input_features
self.assertEqual(input_features.shape, (1, 4, 1001, 64))
self.assertTrue(torch.allclose(input_features[0, block_idx, MEL_BIN], EXPECTED_VALUES, atol=1e-3))
torch.testing.assert_close(input_features[0, block_idx, MEL_BIN], EXPECTED_VALUES, rtol=1e-3, atol=1e-3)
def test_integration_rand_trunc_long_input(self):
# fmt: off
@@ -544,4 +544,4 @@ class ClapFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Tes
input_speech, return_tensors="pt", truncation="rand_trunc", padding=padding
).input_features
self.assertEqual(input_features.shape, (1, 1, 1001, 64))
self.assertTrue(torch.allclose(input_features[0, 0, MEL_BIN], EXPECTED_VALUES, atol=1e-4))
torch.testing.assert_close(input_features[0, 0, MEL_BIN], EXPECTED_VALUES, rtol=1e-4, atol=1e-4)