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Add AMD test expectations to DETR model (#39539)
* Add AMD test expectations to DETR model * Fix baseline expectation * Address review comments * Make formatting a bit more consistent
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‎tests/models/detr/test_modeling_detr.py

Lines changed: 103 additions & 35 deletions
Original file line numberDiff line numberDiff line change
@@ -18,7 +18,7 @@
1818
import unittest
1919

2020
from transformers import DetrConfig, ResNetConfig, is_torch_available, is_vision_available
21-
from transformers.testing_utils import require_timm, require_torch, require_vision, slow, torch_device
21+
from transformers.testing_utils import Expectations, require_timm, require_torch, require_vision, slow, torch_device
2222
from transformers.utils import cached_property
2323

2424
from ...test_configuration_common import ConfigTester
@@ -585,13 +585,23 @@ def test_inference_no_head(self):
585585

586586
expected_shape = torch.Size((1, 100, 256))
587587
assert outputs.last_hidden_state.shape == expected_shape
588-
expected_slice = torch.tensor(
589-
[
590-
[0.0622, -0.5142, -0.4034],
591-
[-0.7628, -0.4935, -1.7153],
592-
[-0.4751, -0.6386, -0.7818],
593-
]
594-
).to(torch_device)
588+
expected_slices = Expectations(
589+
{
590+
(None, None):
591+
[
592+
[0.0622, -0.5142, -0.4034],
593+
[-0.7628, -0.4935, -1.7153],
594+
[-0.4751, -0.6386, -0.7818],
595+
],
596+
("rocm", (9, 5)):
597+
[
598+
[ 0.0616, -0.5146, -0.4032],
599+
[-0.7629, -0.4934, -1.7153],
600+
[-0.4768, -0.6403, -0.7826],
601+
],
602+
}
603+
) # fmt: skip
604+
expected_slice = torch.tensor(expected_slices.get_expectation(), device=torch_device)
595605
torch.testing.assert_close(outputs.last_hidden_state[0, :3, :3], expected_slice, rtol=2e-4, atol=2e-4)
596606

597607
def test_inference_object_detection_head(self):
@@ -609,13 +619,23 @@ def test_inference_object_detection_head(self):
609619
# verify outputs
610620
expected_shape_logits = torch.Size((1, model.config.num_queries, model.config.num_labels + 1))
611621
self.assertEqual(outputs.logits.shape, expected_shape_logits)
612-
expected_slice_logits = torch.tensor(
613-
[
614-
[-19.1211, -0.0881, -11.0188],
615-
[-17.3641, -1.8045, -14.0229],
616-
[-20.0415, -0.5833, -11.1005],
617-
]
618-
).to(torch_device)
622+
expected_slices = Expectations(
623+
{
624+
(None, None):
625+
[
626+
[-19.1211, -0.0881, -11.0188],
627+
[-17.3641, -1.8045, -14.0229],
628+
[-20.0415, -0.5833, -11.1005],
629+
],
630+
("rocm", (9, 5)):
631+
[
632+
[-19.1194, -0.0893, -11.0154],
633+
[-17.3640, -1.8035, -14.0219],
634+
[-20.0461, -0.5837, -11.1060],
635+
],
636+
}
637+
) # fmt: skip
638+
expected_slice_logits = torch.tensor(expected_slices.get_expectation(), device=torch_device)
619639
torch.testing.assert_close(outputs.logits[0, :3, :3], expected_slice_logits, rtol=2e-4, atol=2e-4)
620640

621641
expected_shape_boxes = torch.Size((1, model.config.num_queries, 4))
@@ -657,27 +677,65 @@ def test_inference_panoptic_segmentation_head(self):
657677
# verify outputs
658678
expected_shape_logits = torch.Size((1, model.config.num_queries, model.config.num_labels + 1))
659679
self.assertEqual(outputs.logits.shape, expected_shape_logits)
660-
expected_slice_logits = torch.tensor(
661-
[
662-
[-18.1523, -1.7592, -13.5019],
663-
[-16.8866, -1.4139, -14.1025],
664-
[-17.5735, -2.5090, -11.8666],
665-
]
666-
).to(torch_device)
680+
expected_slices = Expectations(
681+
{
682+
(None, None):
683+
[
684+
[-18.1523, -1.7592, -13.5019],
685+
[-16.8866, -1.4139, -14.1025],
686+
[-17.5735, -2.5090, -11.8666],
687+
],
688+
("rocm", (9, 5)):
689+
[
690+
[-18.1565, -1.7568, -13.5029],
691+
[-16.8888, -1.4138, -14.1028],
692+
[-17.5709, -2.5080, -11.8654],
693+
],
694+
}
695+
) # fmt: skip
696+
expected_slice_logits = torch.tensor(expected_slices.get_expectation(), device=torch_device)
667697
torch.testing.assert_close(outputs.logits[0, :3, :3], expected_slice_logits, rtol=2e-4, atol=2e-4)
668698

669699
expected_shape_boxes = torch.Size((1, model.config.num_queries, 4))
670700
self.assertEqual(outputs.pred_boxes.shape, expected_shape_boxes)
671-
expected_slice_boxes = torch.tensor(
672-
[[0.5344, 0.1790, 0.9284], [0.4421, 0.0571, 0.0875], [0.6632, 0.6886, 0.1015]]
673-
).to(torch_device)
701+
expected_slices = Expectations(
702+
{
703+
(None, None):
704+
[
705+
[0.5344, 0.1790, 0.9284],
706+
[0.4421, 0.0571, 0.0875],
707+
[0.6632, 0.6886, 0.1015]
708+
],
709+
("rocm", (9, 5)):
710+
[
711+
[0.5344, 0.1789, 0.9285],
712+
[0.4420, 0.0572, 0.0875],
713+
[0.6630, 0.6887, 0.1017],
714+
],
715+
}
716+
) # fmt: skip
717+
expected_slice_boxes = torch.tensor(expected_slices.get_expectation(), device=torch_device)
674718
torch.testing.assert_close(outputs.pred_boxes[0, :3, :3], expected_slice_boxes, rtol=2e-4, atol=2e-4)
675719

676720
expected_shape_masks = torch.Size((1, model.config.num_queries, 200, 267))
677721
self.assertEqual(outputs.pred_masks.shape, expected_shape_masks)
678-
expected_slice_masks = torch.tensor(
679-
[[-7.8408, -11.0104, -12.1279], [-12.0299, -16.6498, -17.9806], [-14.8995, -19.9940, -20.5646]]
680-
).to(torch_device)
722+
expected_slices = Expectations(
723+
{
724+
(None, None):
725+
[
726+
[-7.8408, -11.0104, -12.1279],
727+
[-12.0299, -16.6498, -17.9806],
728+
[-14.8995, -19.9940, -20.5646],
729+
],
730+
("rocm", (9, 5)):
731+
[
732+
[ -7.7558, -10.8789, -11.9798],
733+
[-11.8882, -16.4330, -17.7452],
734+
[-14.7317, -19.7384, -20.3005],
735+
],
736+
}
737+
) # fmt: skip
738+
expected_slice_masks = torch.tensor(expected_slices.get_expectation(), device=torch_device)
681739
torch.testing.assert_close(outputs.pred_masks[0, 0, :3, :3], expected_slice_masks, rtol=2e-3, atol=2e-3)
682740

683741
# verify postprocessing
@@ -731,11 +789,21 @@ def test_inference_no_head(self):
731789

732790
expected_shape = torch.Size((1, 100, 256))
733791
assert outputs.last_hidden_state.shape == expected_shape
734-
expected_slice = torch.tensor(
735-
[
736-
[0.0622, -0.5142, -0.4034],
737-
[-0.7628, -0.4935, -1.7153],
738-
[-0.4751, -0.6386, -0.7818],
739-
]
740-
).to(torch_device)
792+
expected_slices = Expectations(
793+
{
794+
(None, None):
795+
[
796+
[0.0622, -0.5142, -0.4034],
797+
[-0.7628, -0.4935, -1.7153],
798+
[-0.4751, -0.6386, -0.7818],
799+
],
800+
("rocm", (9, 5)):
801+
[
802+
[ 0.0616, -0.5146, -0.4032],
803+
[-0.7629, -0.4934, -1.7153],
804+
[-0.4768, -0.6403, -0.7826]
805+
],
806+
}
807+
) # fmt: skip
808+
expected_slice = torch.tensor(expected_slices.get_expectation(), device=torch_device)
741809
torch.testing.assert_close(outputs.last_hidden_state[0, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)

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