SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

use torch.testing.assertclose instead to get more details about error in cis (#35659)

Browse Source 
* 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
Download Patch File Download Diff File Expand all files Collapse all files

6
tests/models/prophetnet/test_modeling_prophetnet.py
View File

@@ -1227,7 +1227,7 @@ class ProphetNetModelIntegrationTest(unittest.TestCase):
expected_slice = torch.tensor(
[[[-7.7729, -8.0343, -8.26001], [-7.74213, -7.8629, -8.6000], [-7.7328, -7.8269, -8.5264]]]
).to(torch_device)
# self.assertTrue(torch.allclose(output_predited_logits[:, :3, :3], expected_slice, atol=1e-4))
# torch.testing.assert_close(output_predited_logits[:, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)
assert torch.allclose(output_predited_logits[:, :3, :3], expected_slice, atol=1e-4)
# encoder outputs
@@ -1237,7 +1237,7 @@ class ProphetNetModelIntegrationTest(unittest.TestCase):
).to(torch_device)
expected_shape_encoder = torch.Size((1, 28, 1024))
self.assertEqual(encoder_outputs.shape, expected_shape_encoder)
# self.assertTrue(torch.allclose(encoder_outputs[:, :3, :3], expected_encoder_outputs_slice, atol=1e-4))
# torch.testing.assert_close(encoder_outputs[:, :3, :3], expected_encoder_outputs_slice, rtol=1e-4, atol=1e-4)
assert torch.allclose(encoder_outputs[:, :3, :3], expected_encoder_outputs_slice, atol=1e-4)
# decoder outputs
@@ -1245,7 +1245,7 @@ class ProphetNetModelIntegrationTest(unittest.TestCase):
predicting_streams = decoder_outputs[1].view(1, model.config.ngram, 12, -1)
predicting_streams_logits = model.lm_head(predicting_streams)
next_first_stream_logits = predicting_streams_logits[:, 0]
# self.assertTrue(torch.allclose(next_first_stream_logits[:, :3, :3], expected_slice, atol=1e-4))
# torch.testing.assert_close(next_first_stream_logits[:, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)
assert torch.allclose(next_first_stream_logits[:, :3, :3], expected_slice, atol=1e-4)
@slow