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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/time_series_transformer/test_modeling_time_series_transformer.py
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@@ -512,7 +512,7 @@ class TimeSeriesTransformerModelIntegrationTests(unittest.TestCase):
expected_slice = torch.tensor(
[[0.8196, -1.5131, 1.4620], [1.1268, -1.3238, 1.5997], [1.5098, -1.0715, 1.7359]], 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 = TimeSeriesTransformerForPrediction.from_pretrained(
@@ -534,7 +534,7 @@ class TimeSeriesTransformerModelIntegrationTests(unittest.TestCase):
expected_slice = torch.tensor(
[[-1.2957, -1.0280, -0.6045], [-0.7017, -0.8193, -0.3717], [-1.0449, -0.8149, 0.1405]], 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 = TimeSeriesTransformerForPrediction.from_pretrained(
@@ -555,4 +555,4 @@ class TimeSeriesTransformerModelIntegrationTests(unittest.TestCase):
expected_slice = torch.tensor([2825.2749, 3584.9207, 6763.9951], 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)