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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/informer/test_modeling_informer.py
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@@ -504,7 +504,7 @@ class InformerModelIntegrationTests(unittest.TestCase):
[[0.4699, 0.7295, 0.8967], [0.4858, 0.3810, 0.9641], [-0.0233, 0.3608, 1.0303]],
device=torch_device,
)
self.assertTrue(torch.allclose(output[0, :3, :3], expected_slice, atol=TOLERANCE))
torch.testing.assert_close(output[0, :3, :3], expected_slice, rtol=TOLERANCE, atol=TOLERANCE)
def test_inference_head(self):
model = InformerForPrediction.from_pretrained("huggingface/informer-tourism-monthly").to(torch_device)
@@ -527,7 +527,7 @@ class InformerModelIntegrationTests(unittest.TestCase):
expected_slice = torch.tensor(
[[0.4170, 0.9067, 0.8153], [0.3004, 0.7574, 0.7066], [0.6803, -0.6323, 1.2802]], device=torch_device
)
self.assertTrue(torch.allclose(output[0, :3, :3], expected_slice, atol=TOLERANCE))
torch.testing.assert_close(output[0, :3, :3], expected_slice, rtol=TOLERANCE, atol=TOLERANCE)
def test_seq_to_seq_generation(self):
model = InformerForPrediction.from_pretrained("huggingface/informer-tourism-monthly").to(torch_device)
@@ -547,4 +547,4 @@ class InformerModelIntegrationTests(unittest.TestCase):
expected_slice = torch.tensor([3400.8005, 4289.2637, 7101.9209], device=torch_device)
mean_prediction = outputs.sequences.mean(dim=1)
self.assertTrue(torch.allclose(mean_prediction[0, -3:], expected_slice, rtol=1e-1))
torch.testing.assert_close(mean_prediction[0, -3:], expected_slice, rtol=1e-1)