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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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8
tests/models/luke/test_modeling_luke.py
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@@ -909,14 +909,14 @@ class LukeModelIntegrationTests(unittest.TestCase):
expected_slice = torch.tensor(
[[0.0037, 0.1368, -0.0091], [0.1099, 0.3329, -0.1095], [0.0765, 0.5335, 0.1179]]
).to(torch_device)
self.assertTrue(torch.allclose(outputs.last_hidden_state[0, :3, :3], expected_slice, atol=1e-4))
torch.testing.assert_close(outputs.last_hidden_state[0, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)
# Verify entity hidden states
expected_shape = torch.Size((1, 1, 768))
self.assertEqual(outputs.entity_last_hidden_state.shape, expected_shape)
expected_slice = torch.tensor([[0.1457, 0.1044, 0.0174]]).to(torch_device)
self.assertTrue(torch.allclose(outputs.entity_last_hidden_state[0, :3, :3], expected_slice, atol=1e-4))
torch.testing.assert_close(outputs.entity_last_hidden_state[0, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)
@slow
def test_inference_large_model(self):
@@ -944,11 +944,11 @@ class LukeModelIntegrationTests(unittest.TestCase):
expected_slice = torch.tensor(
[[0.0133, 0.0865, 0.0095], [0.3093, -0.2576, -0.7418], [-0.1720, -0.2117, -0.2869]]
).to(torch_device)
self.assertTrue(torch.allclose(outputs.last_hidden_state[0, :3, :3], expected_slice, atol=1e-4))
torch.testing.assert_close(outputs.last_hidden_state[0, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)
# Verify entity hidden states
expected_shape = torch.Size((1, 1, 1024))
self.assertEqual(outputs.entity_last_hidden_state.shape, expected_shape)
expected_slice = torch.tensor([[0.0466, -0.0106, -0.0179]]).to(torch_device)
self.assertTrue(torch.allclose(outputs.entity_last_hidden_state[0, :3, :3], expected_slice, atol=1e-4))
torch.testing.assert_close(outputs.entity_last_hidden_state[0, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)