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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/led/test_modeling_led.py
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@@ -540,7 +540,7 @@ class LEDModelIntegrationTests(unittest.TestCase):
expected_slice = torch.tensor(
[[2.3050, 2.8279, 0.6531], [-1.8457, -0.1455, -3.5661], [-1.0186, 0.4586, -2.2043]], device=torch_device
)
self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=TOLERANCE))
torch.testing.assert_close(output[:, :3, :3], expected_slice, rtol=TOLERANCE, atol=TOLERANCE)
def test_inference_head(self):
model = LEDForConditionalGeneration.from_pretrained("allenai/led-base-16384").to(torch_device)
@@ -557,7 +557,7 @@ class LEDModelIntegrationTests(unittest.TestCase):
expected_slice = torch.tensor(
[[33.6507, 6.4572, 16.8089], [5.8739, -2.4238, 11.2902], [-3.2139, -4.3149, 4.2783]], device=torch_device
)
self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=TOLERANCE))
torch.testing.assert_close(output[:, :3, :3], expected_slice, rtol=TOLERANCE, atol=TOLERANCE)
def test_seq_to_seq_generation(self):
# this test requires 16GB of RAM