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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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18
tests/generation/test_logits_process.py
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@@ -166,8 +166,8 @@ class LogitsProcessorTest(unittest.TestCase):
processed_scores = temp_dist_warper_smoother(input_ids, scores)
# uniform distribution stays uniform
self.assertTrue(torch.allclose(probs[0, :], warped_prob_sharp[0, :], atol=1e-3))
self.assertTrue(torch.allclose(probs[0, :], warped_prob_smooth[0, :], atol=1e-3))
torch.testing.assert_close(probs[0, :], warped_prob_sharp[0, :], rtol=1e-3, atol=1e-3)
torch.testing.assert_close(probs[0, :], warped_prob_smooth[0, :], rtol=1e-3, atol=1e-3)
# sharp peaks get higher, valleys get lower
self.assertLess(probs[1, :].max(), warped_prob_sharp[1, :].max())
@@ -288,7 +288,7 @@ class LogitsProcessorTest(unittest.TestCase):
EXPECTED_FILTERED_DIST = torch.tensor(
[[0.3, 0.0, 0.0, 0.5], [0.0, 0.3, 0.3, 0.25]], device=torch_device, dtype=torch.float
)
self.assertTrue(torch.allclose(filtered_dist, EXPECTED_FILTERED_DIST, atol=1e-3))
torch.testing.assert_close(filtered_dist, EXPECTED_FILTERED_DIST, rtol=1e-3, atol=1e-3)
# processor should not change logits in-place
self.assertFalse(torch.all(top_p_warp(input_ids, dist) == dist))
@@ -335,7 +335,7 @@ class LogitsProcessorTest(unittest.TestCase):
device=torch_device,
dtype=torch.float,
)
self.assertTrue(torch.allclose(filtered_dist, EXPECTED_FILTERED_DIST, atol=1e-3))
torch.testing.assert_close(filtered_dist, EXPECTED_FILTERED_DIST, rtol=1e-3, atol=1e-3)
# processor should not change logits in-place
self.assertFalse(torch.all(min_p_warp(input_ids, dist) == dist))
@@ -372,7 +372,7 @@ class LogitsProcessorTest(unittest.TestCase):
EXPECTED_FILTERED_DIST = torch.tensor(
[[0.97, 0.0, 0.0, 0.0], [0.0, 0.2, 0.2, 0.2]], device=torch_device, dtype=torch.float
)
self.assertTrue(torch.allclose(filtered_dist, EXPECTED_FILTERED_DIST, atol=1e-3))
torch.testing.assert_close(filtered_dist, EXPECTED_FILTERED_DIST, rtol=1e-3, atol=1e-3)
# processor should not change logits in-place
self.assertFalse(torch.all(typical_warp(input_ids, dist) == dist))
@@ -422,7 +422,7 @@ class LogitsProcessorTest(unittest.TestCase):
EXPECTED_FILTERED_DIST = torch.tensor(
[[0.87, 0, 0, 0], [0.4, 0.299, 0.101, 0.2]], device=torch_device, dtype=torch.float
)
self.assertTrue(torch.allclose(filtered_dist, EXPECTED_FILTERED_DIST, atol=1e-3))
torch.testing.assert_close(filtered_dist, EXPECTED_FILTERED_DIST, rtol=1e-3, atol=1e-3)
# processor should not change logits in-place
self.assertFalse(torch.all(epsilon_warp(input_ids, dist) == dist))
@@ -462,7 +462,7 @@ class LogitsProcessorTest(unittest.TestCase):
EXPECTED_FILTERED_DIST = torch.tensor(
[[0.0, 0.1, 0.8, 0.1], [0.0, 0.0, 0.9, 0.0]], device=torch_device, dtype=torch.float
)
self.assertTrue(torch.allclose(filtered_dist, EXPECTED_FILTERED_DIST, atol=1e-3))
torch.testing.assert_close(filtered_dist, EXPECTED_FILTERED_DIST, rtol=1e-3, atol=1e-3)
# processor should not change logits in-place
self.assertFalse(torch.all(eta_warp(input_ids, dist) == dist))
@@ -599,7 +599,7 @@ class LogitsProcessorTest(unittest.TestCase):
# check edge case
no_bad_words_dist_proc = NoBadWordsLogitsProcessor(bad_words_ids=[[4]], eos_token_id=eos_token_id)
filtered_scores = no_bad_words_dist_proc(input_ids, scores)
self.assertTrue(torch.allclose(scores, filtered_scores, atol=1e-3))
torch.testing.assert_close(scores, filtered_scores, rtol=1e-3, atol=1e-3)
def test_bias_dist_processor(self):
vocab_size = 5
@@ -674,7 +674,7 @@ class LogitsProcessorTest(unittest.TestCase):
scores_comp = processor(input_ids, scores_comp)
# scores should be equal
self.assertTrue(torch.allclose(scores, scores_comp, atol=1e-3))
torch.testing.assert_close(scores, scores_comp, rtol=1e-3, atol=1e-3)
# input_ids should never be changed
self.assertListEqual(input_ids.tolist(), input_ids_comp.tolist())