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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/vilt/test_modeling_vilt.py
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@@ -587,7 +587,7 @@ class ViltModelIntegrationTest(unittest.TestCase):
self.assertEqual(outputs.logits.shape, expected_shape)
expected_slice = torch.tensor([-12.5061, -12.5123, -12.5174]).to(torch_device)
self.assertTrue(torch.allclose(outputs.logits[0, 0, :3], expected_slice, atol=1e-4))
torch.testing.assert_close(outputs.logits[0, 0, :3], expected_slice, rtol=1e-4, atol=1e-4)
# verify masked token prediction equals "cats"
predicted_id = outputs.logits[0, 4, :].argmax(-1).item()
@@ -612,7 +612,7 @@ class ViltModelIntegrationTest(unittest.TestCase):
expected_slice = torch.tensor([-15.9495, -18.1472, -10.3041]).to(torch_device)
self.assertTrue(torch.allclose(outputs.logits[0, :3], expected_slice, atol=1e-4))
torch.testing.assert_close(outputs.logits[0, :3], expected_slice, rtol=1e-4, atol=1e-4)
# compute loss
vqa_labels = [[2, 3, 155, 800]]
@@ -673,4 +673,4 @@ class ViltModelIntegrationTest(unittest.TestCase):
device=torch_device,
)
self.assertTrue(torch.allclose(outputs.logits[0, :3], expected_slice, atol=1e-4))
torch.testing.assert_close(outputs.logits[0, :3], expected_slice, rtol=1e-4, atol=1e-4)