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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/patchtsmixer/test_modeling_patchtsmixer.py
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@@ -483,7 +483,7 @@ class PatchTSMixerModelIntegrationTests(unittest.TestCase):
self.assertEqual(output.shape, expected_shape)
expected_slice = torch.tensor([[[[-0.9106]],[[1.5326]],[[-0.8245]],[[0.7439]],[[-0.7830]],[[2.6256]],[[-0.6485]],]],device=torch_device) # fmt: skip
self.assertTrue(torch.allclose(output[0, :7, :1, :1], expected_slice, atol=TOLERANCE))
torch.testing.assert_close(output[0, :7, :1, :1], expected_slice, rtol=TOLERANCE, atol=TOLERANCE)
def test_forecasting_head(self):
model = PatchTSMixerForPrediction.from_pretrained("ibm/patchtsmixer-etth1-forecasting").to(torch_device)
@@ -504,7 +504,7 @@ class PatchTSMixerModelIntegrationTests(unittest.TestCase):
[[0.2471, 0.5036, 0.3596, 0.5401, -0.0985, 0.3423, -0.8439]],
device=torch_device,
)
self.assertTrue(torch.allclose(output[0, :1, :7], expected_slice, atol=TOLERANCE))
torch.testing.assert_close(output[0, :1, :7], expected_slice, rtol=TOLERANCE, atol=TOLERANCE)
def test_prediction_generation(self):
model = PatchTSMixerForPrediction.from_pretrained("ibm/patchtsmixer-etth1-generate").to(torch_device)
@@ -526,7 +526,7 @@ class PatchTSMixerModelIntegrationTests(unittest.TestCase):
mean_prediction = outputs.sequences.mean(dim=1)
self.assertTrue(torch.allclose(mean_prediction[0, -1:], expected_slice, atol=TOLERANCE))
torch.testing.assert_close(mean_prediction[0, -1:], expected_slice, rtol=TOLERANCE, atol=TOLERANCE)
@require_torch