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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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52
tests/models/omdet_turbo/test_modeling_omdet_turbo.py
View File

@@ -701,8 +701,8 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
[[[0.2550, 0.5501, 0.4738, 0.8745], [0.7695, 0.4121, 0.4603, 0.7244], [0.7691, 0.4117, 0.4603, 0.7214]]]
).to(torch_device)
self.assertTrue(torch.allclose(outputs.decoder_class_logits[:3, :3], expected_class_logits, atol=1e-1))
self.assertTrue(torch.allclose(outputs.decoder_coord_logits[:3, :3], expected_coord_logits, atol=1e-3))
torch.testing.assert_close(outputs.decoder_class_logits[:3, :3], expected_class_logits, rtol=1e-1, atol=1e-1)
torch.testing.assert_close(outputs.decoder_coord_logits[:3, :3], expected_coord_logits, rtol=1e-3, atol=1e-3)
# verify grounded postprocessing
results = processor.post_process_grounded_object_detection(
@@ -712,8 +712,8 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
expected_slice_boxes = torch.tensor([39.8870, 70.3522, 176.7424, 118.0354]).to(torch_device)
self.assertEqual(len(results["scores"]), 4)
self.assertTrue(torch.allclose(results["scores"], expected_scores, atol=1e-2))
self.assertTrue(torch.allclose(results["boxes"][0, :], expected_slice_boxes, atol=1e-2))
torch.testing.assert_close(results["scores"], expected_scores, rtol=1e-2, atol=1e-2)
torch.testing.assert_close(results["boxes"][0, :], expected_slice_boxes, rtol=1e-2, atol=1e-2)
expected_text_labels = ["remote", "cat", "remote", "cat"]
self.assertListEqual(results["text_labels"], expected_text_labels)
@@ -745,8 +745,8 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
[[[0.2550, 0.5501, 0.4738, 0.8745], [0.7695, 0.4121, 0.4603, 0.7244], [0.7691, 0.4117, 0.4603, 0.7214]]]
).to(torch_device, dtype=torch.float16)
self.assertTrue(torch.allclose(outputs.decoder_class_logits[:3, :3], expected_class_logits, atol=1e-1))
self.assertTrue(torch.allclose(outputs.decoder_coord_logits[:3, :3], expected_coord_logits, atol=1e-3))
torch.testing.assert_close(outputs.decoder_class_logits[:3, :3], expected_class_logits, rtol=1e-1, atol=1e-1)
torch.testing.assert_close(outputs.decoder_coord_logits[:3, :3], expected_coord_logits, rtol=1e-3, atol=1e-3)
# verify grounded postprocessing
results = processor.post_process_grounded_object_detection(
@@ -758,8 +758,8 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
)
self.assertEqual(len(results["scores"]), 4)
self.assertTrue(torch.allclose(results["scores"], expected_scores, atol=1e-2))
self.assertTrue(torch.allclose(results["boxes"][0, :], expected_slice_boxes, atol=1e-1))
torch.testing.assert_close(results["scores"], expected_scores, rtol=1e-2, atol=1e-2)
torch.testing.assert_close(results["boxes"][0, :], expected_slice_boxes, rtol=1e-1, atol=1e-1)
expected_text_labels = ["remote", "cat", "remote", "cat"]
self.assertListEqual(results["text_labels"], expected_text_labels)
@@ -787,8 +787,8 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
[[[0.2550, 0.5501, 0.4738, 0.8745], [0.7695, 0.4121, 0.4603, 0.7244], [0.7691, 0.4117, 0.4603, 0.7214]]]
).to(torch_device)
self.assertTrue(torch.allclose(outputs.decoder_class_logits[:3, :3], expected_class_logits, atol=1e-1))
self.assertTrue(torch.allclose(outputs.decoder_coord_logits[:3, :3], expected_coord_logits, atol=1e-3))
torch.testing.assert_close(outputs.decoder_class_logits[:3, :3], expected_class_logits, rtol=1e-1, atol=1e-1)
torch.testing.assert_close(outputs.decoder_coord_logits[:3, :3], expected_coord_logits, rtol=1e-3, atol=1e-3)
# verify grounded postprocessing
results = processor.post_process_grounded_object_detection(
@@ -798,8 +798,8 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
expected_slice_boxes = torch.tensor([39.8870, 70.3522, 176.7424, 118.0354]).to(torch_device)
self.assertEqual(len(results["scores"]), 4)
self.assertTrue(torch.allclose(results["scores"], expected_scores, atol=1e-2))
self.assertTrue(torch.allclose(results["boxes"][0, :], expected_slice_boxes, atol=1e-2))
torch.testing.assert_close(results["scores"], expected_scores, rtol=1e-2, atol=1e-2)
torch.testing.assert_close(results["boxes"][0, :], expected_slice_boxes, rtol=1e-2, atol=1e-2)
expected_text_labels = ["remote", "cat", "remote", "cat"]
self.assertListEqual(results["text_labels"], expected_text_labels)
@@ -831,8 +831,12 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
[[[0.2550, 0.5501, 0.4738]], [[0.2535, 0.6006, 0.0353]], [[0.3742, 0.3337, 0.0666]]]
).to(torch_device)
self.assertTrue(torch.allclose(outputs.decoder_class_logits[:, :1, :3], expected_class_logits, atol=1e-1))
self.assertTrue(torch.allclose(outputs.decoder_coord_logits[:, :1, :3], expected_coord_logits, atol=1e-3))
torch.testing.assert_close(
outputs.decoder_class_logits[:, :1, :3], expected_class_logits, rtol=1e-1, atol=1e-1
)
torch.testing.assert_close(
outputs.decoder_coord_logits[:, :1, :3], expected_coord_logits, rtol=1e-3, atol=1e-3
)
# verify grounded postprocessing
results = processor.post_process_grounded_object_detection(
@@ -851,11 +855,11 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
).to(torch_device)
self.assertListEqual([len(result["scores"]) for result in results], [4, 4, 6])
self.assertTrue(
torch.allclose(torch.stack([result["scores"][0] for result in results]), expected_scores, atol=1e-2)
torch.testing.assert_close(
torch.stack([result["scores"][0] for result in results]), expected_scores, rtol=1e-2, atol=1e-2
)
self.assertTrue(
torch.allclose(torch.stack([result["boxes"][0, :] for result in results]), expected_slice_boxes, atol=1e-2)
torch.testing.assert_close(
torch.stack([result["boxes"][0, :] for result in results]), expected_slice_boxes, rtol=1e-2, atol=1e-2
)
expected_text_labels = [
@@ -889,8 +893,12 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
[[[0.2550, 0.5501, 0.4738, 0.8745], [0.7695, 0.4121, 0.4603, 0.7244], [0.7691, 0.4117, 0.4603, 0.7214]]]
)
self.assertTrue(torch.allclose(cpu_outputs.decoder_class_logits[:3, :3], expected_class_logits, atol=1e-1))
self.assertTrue(torch.allclose(cpu_outputs.decoder_coord_logits[:3, :3], expected_coord_logits, atol=1e-3))
torch.testing.assert_close(
cpu_outputs.decoder_class_logits[:3, :3], expected_class_logits, rtol=1e-1, atol=1e-1
)
torch.testing.assert_close(
cpu_outputs.decoder_coord_logits[:3, :3], expected_coord_logits, rtol=1e-3, atol=1e-3
)
# verify grounded postprocessing
results_cpu = processor.post_process_grounded_object_detection(
@@ -900,5 +908,5 @@ class OmDetTurboModelIntegrationTests(unittest.TestCase):
gpu_outputs, text_labels=[text_labels], target_sizes=[image.size[::-1]]
)[0]
self.assertTrue(torch.allclose(results_cpu["scores"], result_gpu["scores"].cpu(), atol=1e-2))
self.assertTrue(torch.allclose(results_cpu["boxes"][0, :], result_gpu["boxes"][0, :].cpu(), atol=1e-2))
torch.testing.assert_close(results_cpu["scores"], result_gpu["scores"].cpu(), rtol=1e-2, atol=1e-2)
torch.testing.assert_close(results_cpu["boxes"][0, :], result_gpu["boxes"][0, :].cpu(), rtol=1e-2, atol=1e-2)

4
tests/models/omdet_turbo/test_processor_omdet_turbo.py
View File

@@ -106,10 +106,10 @@ class OmDetTurboProcessorTest(ProcessorTesterMixin, unittest.TestCase):
self.assertEqual(post_processed[0]["boxes"].shape, (self.num_queries, 4))
self.assertEqual(post_processed[0]["scores"].shape, (self.num_queries,))
expected_scores = torch.tensor([0.7310, 0.6579, 0.6513, 0.6444, 0.6252])
self.assertTrue(torch.allclose(post_processed[0]["scores"], expected_scores, atol=1e-4))
torch.testing.assert_close(post_processed[0]["scores"], expected_scores, rtol=1e-4, atol=1e-4)
expected_box_slice = torch.tensor([14.9657, 141.2052, 30.0000, 312.9670])
self.assertTrue(torch.allclose(post_processed[0]["boxes"][0], expected_box_slice, atol=1e-4))
torch.testing.assert_close(post_processed[0]["boxes"][0], expected_box_slice, rtol=1e-4, atol=1e-4)
def test_save_load_pretrained_additional_features(self):
processor = OmDetTurboProcessor(tokenizer=self.get_tokenizer(), image_processor=self.get_image_processor())