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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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6
tests/models/roberta/test_modeling_roberta.py
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@@ -541,7 +541,7 @@ class RobertaModelIntegrationTest(TestCasePlus):
# roberta.eval()
# expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()
self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4))
torch.testing.assert_close(output[:, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)
@slow
def test_inference_no_head(self):
@@ -559,7 +559,7 @@ class RobertaModelIntegrationTest(TestCasePlus):
# roberta.eval()
# expected_slice = roberta.extract_features(input_ids)[:, :3, :3].detach()
self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4))
torch.testing.assert_close(output[:, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)
@slow
def test_inference_classification_head(self):
@@ -576,7 +576,7 @@ class RobertaModelIntegrationTest(TestCasePlus):
# roberta.eval()
# expected_tensor = roberta.predict("mnli", input_ids, return_logits=True).detach()
self.assertTrue(torch.allclose(output, expected_tensor, atol=1e-4))
torch.testing.assert_close(output, expected_tensor, rtol=1e-4, atol=1e-4)
@slow
def test_export(self):