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Update expected output values after #39885 (part 1) (#39990)

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fix

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2025-08-07 16:00:28 +02:00
committed by GitHub
parent d5a0809707
commit 43d3b1931a
29 changed files with 103 additions and 103 deletions
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6
tests/models/beit/test_modeling_beit.py
View File

@@ -517,9 +517,9 @@ class BeitModelIntegrationTest(unittest.TestCase):
expected_slice = torch.tensor(
[
[[-4.8963, -2.3696, -3.0359], [-2.8485, -0.9842, -1.7426], [-2.9453, -1.3338, -2.1463]],
[[-5.8099, -3.4140, -4.1025], [-3.8578, -2.2100, -3.0337], [-3.8383, -2.4615, -3.3681]],
[[-0.0314, 3.9864, 4.0536], [2.9637, 4.6879, 4.9976], [3.2074, 4.7690, 4.9946]],
[[-4.8960, -2.3688, -3.0355], [-2.8479, -0.9836, -1.7418], [-2.9449, -1.3333, -2.1456]],
[[-5.8081, -3.4124, -4.1006], [-3.8561, -2.2081, -3.0323], [-3.8365, -2.4601, -3.3669]],
[[-0.0309, 3.9868, 4.0540], [2.9640, 4.6877, 4.9976], [3.2081, 4.7690, 4.9942]],
],
device=torch_device,
)

2
tests/models/conditional_detr/test_modeling_conditional_detr.py
View File

@@ -622,7 +622,7 @@ class ConditionalDetrModelIntegrationTests(unittest.TestCase):
)[0]
expected_scores = torch.tensor([0.8330, 0.8315, 0.8039, 0.6829, 0.5354]).to(torch_device)
expected_labels = [75, 17, 17, 75, 63]
expected_slice_boxes = torch.tensor([38.3109, 72.1002, 177.6301, 118.4511]).to(torch_device)
expected_slice_boxes = torch.tensor([38.3089, 72.1023, 177.6292, 118.4514]).to(torch_device)
self.assertEqual(len(results["scores"]), 5)
torch.testing.assert_close(results["scores"], expected_scores, rtol=2e-4, atol=2e-4)

16
tests/models/d_fine/test_modeling_d_fine.py
View File

@@ -779,9 +779,9 @@ class DFineModelIntegrationTest(unittest.TestCase):
expected_logits = torch.tensor(
[
[-3.8221, -4.7679, -6.0063],
[-5.2994, -9.5009, -6.1697],
[-5.3103, -3.8005, -6.2972],
[-3.8098, -4.7725, -5.9945],
[-5.2975, -9.4991, -6.1654],
[-5.3502, -3.9532, -6.3631],
]
).to(torch_device)
expected_boxes = torch.tensor(
@@ -803,14 +803,14 @@ class DFineModelIntegrationTest(unittest.TestCase):
outputs, threshold=0.0, target_sizes=[image.size[::-1]]
)[0]
expected_scores = torch.tensor([0.9616, 0.9541, 0.9541, 0.8551], device=torch_device)
expected_scores = torch.tensor([0.9642, 0.9542, 0.9536, 0.8548], device=torch_device)
expected_labels = [15, 65, 15, 57]
expected_slice_boxes = torch.tensor(
[
[1.3358e01, 5.4123e01, 3.1726e02, 4.7222e02],
[4.0274e01, 7.2972e01, 1.7620e02, 1.1777e02],
[3.4270e02, 2.3427e01, 6.3998e02, 3.7476e02],
[5.7796e-01, 1.1773e00, 6.3933e02, 4.7486e02],
[1.3186e01, 5.4130e01, 3.1727e02, 4.7212e02],
[4.0275e01, 7.2975e01, 1.7620e02, 1.1777e02],
[3.4276e02, 2.3428e01, 6.3998e02, 3.7477e02],
[5.8418e-01, 1.1794e00, 6.3933e02, 4.7486e02],
],
device=torch_device,
)

6
tests/models/dab_detr/test_modeling_dab_detr.py
View File

@@ -788,9 +788,9 @@ class DabDetrModelIntegrationTests(unittest.TestCase):
self.assertEqual(outputs.last_hidden_state.shape, expected_shape)
expected_slice = torch.tensor(
[
[-0.4878, -0.2593, 0.4521],
[-0.4999, -0.4257, 0.4326],
[-0.8220, -0.4997, 0.0578],
[-0.4879, -0.2594, 0.4524],
[-0.4997, -0.4258, 0.4329],
[-0.8220, -0.4996, 0.0577],
]
).to(torch_device)
torch.testing.assert_close(outputs.last_hidden_state[0, :3, :3], expected_slice, atol=2e-4, rtol=2e-4)

18
tests/models/deformable_detr/test_modeling_deformable_detr.py
View File

@@ -678,9 +678,9 @@ class DeformableDetrModelIntegrationTests(unittest.TestCase):
expected_logits = torch.tensor(
[
[-9.6644, -4.3434, -5.8707],
[-9.7035, -3.8503, -5.0721],
[-10.5633, -5.3387, -7.5119],
[-9.6645, -4.3449, -5.8705],
[-9.7035, -3.8504, -5.0724],
[-10.5634, -5.3379, -7.5116],
]
).to(torch_device)
expected_boxes = torch.tensor(
@@ -703,7 +703,7 @@ class DeformableDetrModelIntegrationTests(unittest.TestCase):
)[0]
expected_scores = torch.tensor([0.7999, 0.7895, 0.6332, 0.4719, 0.4382]).to(torch_device)
expected_labels = [17, 17, 75, 75, 63]
expected_slice_boxes = torch.tensor([16.4960, 52.8387, 318.2565, 470.7831]).to(torch_device)
expected_slice_boxes = torch.tensor([16.5028, 52.8391, 318.2544, 470.7841]).to(torch_device)
self.assertEqual(len(results["scores"]), 5)
torch.testing.assert_close(results["scores"], expected_scores, rtol=2e-4, atol=2e-4)
@@ -729,15 +729,15 @@ class DeformableDetrModelIntegrationTests(unittest.TestCase):
expected_logits = torch.tensor(
[
[-6.7112, -4.3216, -6.3781],
[-8.9035, -6.1738, -6.7249],
[-6.9314, -4.4736, -6.2303],
[-6.7108, -4.3213, -6.3777],
[-8.9014, -6.1799, -6.7240],
[-6.9315, -4.4735, -6.2298],
]
).to(torch_device)
expected_boxes = torch.tensor(
[
[0.2582, 0.5499, 0.4683],
[0.7652, 0.9084, 0.4884],
[0.2583, 0.5499, 0.4683],
[0.7652, 0.9068, 0.4882],
[0.5490, 0.2763, 0.0564],
]
).to(torch_device)

36
tests/models/detr/test_modeling_detr.py
View File

@@ -589,9 +589,9 @@ class DetrModelIntegrationTestsTimmBackbone(unittest.TestCase):
{
(None, None):
[
[0.0622, -0.5142, -0.4034],
[-0.7628, -0.4935, -1.7153],
[-0.4751, -0.6386, -0.7818],
[0.0616, -0.5146, -0.4032],
[-0.7629, -0.4934, -1.7153],
[-0.4768, -0.6403, -0.7826],
],
("rocm", (9, 5)):
[
@@ -623,9 +623,9 @@ class DetrModelIntegrationTestsTimmBackbone(unittest.TestCase):
{
(None, None):
[
[-19.1211, -0.0881, -11.0188],
[-17.3641, -1.8045, -14.0229],
[-20.0415, -0.5833, -11.1005],
[-19.1194, -0.0893, -11.0154],
[-17.3640, -1.8035, -14.0219],
[-20.0461, -0.5837, -11.1060],
],
("rocm", (9, 5)):
[
@@ -681,9 +681,9 @@ class DetrModelIntegrationTestsTimmBackbone(unittest.TestCase):
{
(None, None):
[
[-18.1523, -1.7592, -13.5019],
[-16.8866, -1.4139, -14.1025],
[-17.5735, -2.5090, -11.8666],
[-18.1565, -1.7568, -13.5029],
[-16.8888, -1.4138, -14.1028],
[-17.5709, -2.5080, -11.8654],
],
("rocm", (9, 5)):
[
@@ -702,9 +702,9 @@ class DetrModelIntegrationTestsTimmBackbone(unittest.TestCase):
{
(None, None):
[
[0.5344, 0.1790, 0.9284],
[0.4421, 0.0571, 0.0875],
[0.6632, 0.6886, 0.1015]
[0.5344, 0.1789, 0.9285],
[0.4420, 0.0572, 0.0875],
[0.6630, 0.6887, 0.1017],
],
("rocm", (9, 5)):
[
@@ -723,9 +723,9 @@ class DetrModelIntegrationTestsTimmBackbone(unittest.TestCase):
{
(None, None):
[
[-7.8408, -11.0104, -12.1279],
[-12.0299, -16.6498, -17.9806],
[-14.8995, -19.9940, -20.5646],
[-7.7557, -10.8788, -11.9797],
[-11.8880, -16.4328, -17.7450],
[-14.7315, -19.7382, -20.3003],
],
("rocm", (9, 5)):
[
@@ -793,9 +793,9 @@ class DetrModelIntegrationTests(unittest.TestCase):
{
(None, None):
[
[0.0622, -0.5142, -0.4034],
[-0.7628, -0.4935, -1.7153],
[-0.4751, -0.6386, -0.7818],
[0.0616, -0.5146, -0.4032],
[-0.7629, -0.4934, -1.7153],
[-0.4768, -0.6403, -0.7826],
],
("rocm", (9, 5)):
[

2
tests/models/dpt/test_modeling_dpt.py
View File

@@ -345,7 +345,7 @@ class DPTModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [[6.3199, 6.3629, 6.4148], [6.3850, 6.3615, 6.4166], [6.3519, 6.3176, 6.3575]],
("cuda", 8): [[6.3215, 6.3635, 6.4155], [6.3863, 6.3622, 6.4174], [6.3530, 6.3184, 6.3583]],
("cuda", 8): [[6.3199, 6.3629, 6.4148], [6.3850, 6.3615, 6.4166], [6.3519, 6.3176, 6.3575]],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

20
tests/models/fastspeech2_conformer/test_modeling_fastspeech2_conformer.py
View File

@@ -393,16 +393,16 @@ class FastSpeech2ConformerModelIntegrationTest(unittest.TestCase):
[0.7831, -0.2663, 1.0352, 1.4489, 0.9088, 0.0247, -0.3995, 0.0078, 1.2446, 1.6998],
],
("cuda", 8): [
[-1.2425, -1.7282, -1.6750, -1.7448, -1.6400, -1.5217, -1.4478, -1.3341, -1.4026, -1.4493],
[-0.7858, -1.4967, -1.3601, -1.4875, -1.2950, -1.0725, -1.0021, -0.7553, -0.6522, -0.6929],
[-0.7303, -1.3911, -1.0370, -1.2656, -1.0345, -0.7888, -0.7423, -0.5251, -0.3737, -0.3979],
[-0.4784, -1.3506, -1.1556, -1.4677, -1.2820, -1.0253, -1.0868, -0.9006, -0.8949, -0.8448],
[-0.3968, -1.2896, -1.2811, -1.6145, -1.4660, -1.2564, -1.4135, -1.2652, -1.3258, -1.1716],
[-1.4912, -1.3092, -0.3812, -0.3886, -0.5737, -0.9034, -1.0749, -1.0571, -1.2202, -1.0567],
[0.0200, -0.0577, 0.9151, 1.1516, 1.1656, 0.6628, -0.1012, -0.3086, -0.2283, 0.2658],
[1.1778, 0.1805, 0.7255, 1.5732, 1.6680, 0.4539, -0.1572, -0.1785, 0.0751, 0.8175],
[-0.2088, -0.3212, 1.1101, 1.5085, 1.4625, 0.6293, -0.0522, 0.0587, 0.8615, 1.4432],
[0.7834, -0.2659, 1.0355, 1.4486, 0.9080, 0.0244, -0.3995, 0.0083, 1.2452, 1.6998],
[-1.2426, -1.7286, -1.6754, -1.7451, -1.6402, -1.5219, -1.4480, -1.3345, -1.4030, -1.4497],
[-0.7858, -1.4966, -1.3601, -1.4876, -1.2949, -1.0723, -1.0021, -0.7553, -0.6521, -0.6929],
[-0.7298, -1.3908, -1.0369, -1.2656, -1.0342, -0.7883, -0.7420, -0.5249, -0.3734, -0.3977],
[-0.4784, -1.3508, -1.1558, -1.4678, -1.2820, -1.0252, -1.0868, -0.9006, -0.8947, -0.8448],
[-0.3963, -1.2895, -1.2813, -1.6147, -1.4658, -1.2560, -1.4134, -1.2650, -1.3255, -1.1715],
[-1.4913, -1.3097, -0.3820, -0.3897, -0.5747, -0.9040, -1.0755, -1.0575, -1.2205, -1.0571],
[ 0.0197, -0.0582, 0.9148, 1.1512, 1.1651, 0.6628, -0.1009, -0.3085, -0.2285, 0.2651],
[ 1.1780, 0.1803, 0.7251, 1.5728, 1.6677, 0.4542, -0.1572, -0.1787, 0.0744, 0.8168],
[-0.2078, -0.3211, 1.1096, 1.5085, 1.4631, 0.6299, -0.0515, 0.0589, 0.8609, 1.4429],
[ 0.7831, -0.2663, 1.0352, 1.4488, 0.9087, 0.0247, -0.3995, 0.0079, 1.2447, 1.6998],
],
}
)

2
tests/models/grounding_dino/test_modeling_grounding_dino.py
View File

@@ -692,7 +692,7 @@ class GroundingDinoModelIntegrationTests(unittest.TestCase):
expectations = Expectations(
{
(None, None): [[-4.8913, -0.1900, -0.2161], [-4.9653, -0.3719, -0.3950], [-5.9599, -3.3765, -3.3104]],
("cuda", 8): [[-4.8927, -0.1910, -0.2169], [-4.9657, -0.3748, -0.3980], [-5.9579, -3.3812, -3.3153]],
("cuda", 8): [[-4.8915, -0.1900, -0.2161], [-4.9658, -0.3716, -0.3948], [-5.9596, -3.3763, -3.3103]],
}
)
expected_logits = torch.tensor(expectations.get_expectation()).to(torch_device)

2
tests/models/levit/test_modeling_levit.py
View File

@@ -409,7 +409,7 @@ class LevitModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [1.0448, -0.3745, -1.8317],
("cuda", 8): [1.0453, -0.3739, -1.8314],
("cuda", 8): [1.0448, -0.3745, -1.8317],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

12
tests/models/mask2former/test_modeling_mask2former.py
View File

@@ -512,9 +512,9 @@ class Mask2FormerModelIntegrationTest(unittest.TestCase):
[-6.6105, -6.3427, -6.4675],
],
("cuda", 8): [
[-8.7809, -9.0041, -8.8087],
[-7.4075, -7.0307, -6.5385],
[-6.6088, -6.3417, -6.4627],
[-8.7839, -9.0056, -8.8122],
[-7.4104, -7.0313, -6.5401],
[-6.6105, -6.3428, -6.4675],
],
}
)
@@ -531,9 +531,9 @@ class Mask2FormerModelIntegrationTest(unittest.TestCase):
[0.3045, -7.7293, -3.0275],
],
("cuda", 8): [
[1.8326, -8.0834, -4.1916],
[0.8446, -9.0048, -3.6048],
[0.3042, -7.7296, -3.0277],
[1.8324, -8.0835, -4.1922],
[0.8450, -9.0050, -3.6053],
[0.3045, -7.7293, -3.0275],
],
}
)

14
tests/models/maskformer/test_modeling_maskformer.py
View File

@@ -604,9 +604,9 @@ class MaskFormerModelIntegrationTest(unittest.TestCase):
[1.0766e-04, -7.7630e00, -5.1263e00],
],
("cuda", 8): [
[1.6507e00, -5.2568e00, -3.3520e00],
[3.5767e-02, -5.9023e00, -2.9313e00],
[-6.2712e-04, -7.7627e00, -5.1268e00],
[1.6512e00, -5.2572e00, -3.3519e00],
[3.6163e-02, -5.9025e00, -2.9313e00],
[1.1681e-04, -7.7631e00, -5.1263e00],
],
}
)
@@ -641,7 +641,7 @@ class MaskFormerModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [[-0.9046, -2.6366, -4.6062], [-3.4179, -5.7890, -8.8057], [-4.9179, -7.6560, -10.7711]],
("cuda", 8): [[-0.9000, -2.6283, -4.5964], [-3.4123, -5.7789, -8.7919], [-4.9132, -7.6444, -10.7557]],
("cuda", 8): [[-0.9046, -2.6366, -4.6062], [-3.4179, -5.7890, -8.8057], [-4.9179, -7.6560, -10.7711]],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)
@@ -659,9 +659,9 @@ class MaskFormerModelIntegrationTest(unittest.TestCase):
[7.2449, -2.2764, -2.1874],
],
("cuda", 8): [
[4.7177, -3.2586, -2.8853],
[6.6845, -2.9186, -1.2491],
[7.2443, -2.2760, -2.1858],
[4.7188, -3.2585, -2.8857],
[6.6871, -2.9181, -1.2487],
[7.2449, -2.2764, -2.1874],
],
}
)

2
tests/models/mobilenet_v1/test_modeling_mobilenet_v1.py
View File

@@ -249,7 +249,7 @@ class MobileNetV1ModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [-4.1739, -1.1233, 3.1205],
("cuda", 8): [-4.1725, -1.1238, 3.1191],
("cuda", 8): [-4.1739, -1.1233, 3.1205],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

8
tests/models/mobilenet_v2/test_modeling_mobilenet_v2.py
View File

@@ -304,7 +304,7 @@ class MobileNetV2ModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [0.2445, -1.1993, 0.1905],
("cuda", 8): [0.2445, -1.1970, 0.1868],
("cuda", 8): [0.2445, -1.1993, 0.1905],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)
@@ -338,9 +338,9 @@ class MobileNetV2ModelIntegrationTest(unittest.TestCase):
[[4.2058, 4.8317, 4.7638], [4.4136, 5.0361, 4.9383], [4.5028, 4.9644, 4.8734]],
],
("cuda", 8): [
[[17.5809, 17.7571, 18.3341], [18.3240, 18.4216, 18.8974], [18.6174, 18.8662, 19.2177]],
[[-2.1562, -2.0942, -2.3703], [-2.4199, -2.2999, -2.6818], [-2.7800, -2.5944, -2.7678]],
[[4.2092, 4.8356, 4.7694], [4.4181, 5.0401, 4.9409], [4.5089, 4.9700, 4.8802]],
[[17.5790, 17.7581, 18.3355], [18.3257, 18.4230, 18.8973], [18.6169, 18.8650, 19.2187]],
[[-2.1595, -2.0977, -2.3742], [-2.4226, -2.3028, -2.6836], [-2.7820, -2.5991, -2.7706]],
[[4.2058, 4.8317, 4.7638], [4.4136, 5.0361, 4.9383], [4.5028, 4.9645, 4.8734]],
],
}
)

8
tests/models/mobilevit/test_modeling_mobilevit.py
View File

@@ -307,7 +307,7 @@ class MobileViTModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [-1.9364, -1.2327, -0.4653],
("cuda", 8): [-1.9401, -1.2384, -0.4702],
("cuda", 8): [-1.9364, -1.2327, -0.4653],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)
@@ -341,9 +341,9 @@ class MobileViTModelIntegrationTest(unittest.TestCase):
[[-3.3089, -2.8539, -2.6740], [-3.2706, -2.5621, -2.5108], [-3.2534, -2.6615, -2.6651]],
],
("cuda", 8): [
[[6.9661, 6.9753, 7.2386], [7.2864, 7.2785, 7.4429], [7.6577, 7.8770, 7.9387]],
[[-10.7046, -10.3411, -10.3641], [-10.4402, -10.0004, -9.7269], [-11.0579, -11.0358, -10.7459]],
[[-3.3022, -2.8465, -2.6661], [-3.2654, -2.5542, -2.5055], [-3.2477, -2.6544, -2.6562]],
[[6.9713, 6.9786, 7.2422], [7.2893, 7.2825, 7.4446], [7.6580, 7.8797, 7.9420]],
[[-10.6869, -10.3250, -10.3471], [-10.4229, -9.9868, -9.7132], [-11.0405, -11.0221, -10.7318]],
[[-3.3089, -2.8539, -2.6739], [-3.2706, -2.5621, -2.5108], [-3.2534, -2.6615, -2.6651]],
],
}
)

8
tests/models/mobilevitv2/test_modeling_mobilevitv2.py
View File

@@ -327,7 +327,7 @@ class MobileViTV2ModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [-1.6336e00, -7.3204e-02, -5.1883e-01],
("cuda", 8): [-1.6341, -0.0665, -0.5158],
("cuda", 8): [-1.6336, -0.0732, -0.5188],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)
@@ -361,9 +361,9 @@ class MobileViTV2ModelIntegrationTest(unittest.TestCase):
[[-2.9329, -2.8003, -2.7369], [-3.0564, -2.4780, -2.0207], [-2.6889, -1.9298, -1.7640]],
],
("cuda", 8): [
[[7.0866, 7.1509, 6.8188], [6.6935, 6.8757, 6.8927], [6.2988, 7.0365, 6.9631]],
[[-3.7113, -3.6686, -3.6643], [-3.5801, -3.3516, -3.4739], [-3.3432, -3.3966, -3.2832]],
[[-2.9359, -2.8037, -2.7387], [-3.0595, -2.4798, -2.0222], [-2.6901, -1.9306, -1.7659]],
[[7.0863, 7.1525, 6.8201], [6.6931, 6.8770, 6.8933], [6.2978, 7.0366, 6.9636]],
[[-3.7134, -3.6712, -3.6675], [-3.5825, -3.3549, -3.4777], [-3.3435, -3.3979, -3.2857]],
[[-2.9329, -2.8003, -2.7369], [-3.0564, -2.4780, -2.0207], [-2.6889, -1.9298, -1.7640]],
],
}
)

8
tests/models/moonshine/test_modeling_moonshine.py
View File

@@ -496,10 +496,10 @@ class MoonshineModelIntegrationTests(unittest.TestCase):
# fmt: off
EXPECTED_LOGITS = torch.tensor(
[
[-8.5966, 4.8608, 5.8849, -6.6183, -7.0378, -7.7121, -7.0640, -7.3839, -7.8330, -7.6116],
[-4.3147, -2.4953, 8.4924, -6.4803, -7.0949, -6.7498, -6.1081, -6.6481, -6.9866, -6.5916],
[-10.0088, 3.2862, 0.7342, -6.5559, -6.8514, -6.5309, -6.4173, -6.9485, -6.6215, -6.6230],
[-11.1002, 3.9398, 0.6674, -5.0146, -5.3936, -5.4099, -5.2236, -5.4404, -5.2200, -5.2702],
[-8.5973, 4.8608, 5.8845, -6.6182, -7.0376, -7.7120, -7.0638, -7.3837, -7.8328, -7.6114],
[-4.3157, -2.4944, 8.4917, -6.4806, -7.0952, -6.7500, -6.1084, -6.6484, -6.9868, -6.5919],
[-10.0086, 3.2859, 0.7345, -6.5557, -6.8514, -6.5308, -6.4172, -6.9484, -6.6214, -6.6229],
[-11.1003, 3.9395, 0.6672, -5.0150, -5.3939, -5.4103, -5.2240, -5.4407, -5.2204, -5.2706],
],
)
# fmt: on

6
tests/models/oneformer/test_modeling_oneformer.py
View File

@@ -578,7 +578,7 @@ class OneFormerModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [[3.0668, -1.1833, -5.1103], [3.344, -3.362, -5.1101], [2.6017, -4.3613, -4.1444]],
("cuda", 8): [[3.0590, -1.1903, -5.1119], [3.3919, -3.3547, -5.1469], [2.6041, -4.3592, -4.1406]],
("cuda", 8): [[3.0668, -1.1833, -5.1103], [3.3440, -3.3620, -5.1101], [2.6017, -4.3613, -4.1444]],
}
)
expected_slice_hidden_state = torch.tensor(expectations.get_expectation()).to(torch_device)
@@ -606,7 +606,7 @@ class OneFormerModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [[3.1848, 4.2141, 4.1993], [2.9000, 3.5721, 3.6603], [2.5358, 3.0883, 3.6168]],
("cuda", 8): [[3.1687, 4.1893, 4.1742], [2.8768, 3.5380, 3.6257], [2.5121, 3.0552, 3.5822]],
("cuda", 8): [[3.1848, 4.2141, 4.1993], [2.9000, 3.5721, 3.6603], [2.5358, 3.0883, 3.6168]],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)
@@ -621,7 +621,7 @@ class OneFormerModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [[3.0668, -1.1833, -5.1103], [3.3440, -3.3620, -5.1101], [2.6017, -4.3613, -4.1444]],
("cuda", 8): [[3.0590, -1.1903, -5.1119], [3.3919, -3.3547, -5.1469], [2.6041, -4.3592, -4.1406]],
("cuda", 8): [[3.0668, -1.1833, -5.1103], [3.3440, -3.3620, -5.1101], [2.6017, -4.3613, -4.1444]],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

2
tests/models/poolformer/test_modeling_poolformer.py
View File

@@ -241,7 +241,7 @@ class PoolFormerModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [-0.6113, 0.1685, -0.0492],
("cuda", 8): [-0.6112, 0.1690, -0.0481],
("cuda", 8): [-0.6113, 0.1685, -0.0492],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

2
tests/models/pvt/test_modeling_pvt.py
View File

@@ -291,7 +291,7 @@ class PvtModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [[-0.3086, 1.0402, 1.1816], [-0.2880, 0.5781, 0.6124], [0.1480, 0.6129, -0.0590]],
("cuda", 8): [[-0.3084, 1.0402, 1.1816], [-0.2883, 0.5781, 0.6123], [0.1487, 0.6119, -0.0584]],
("cuda", 8): [[-0.3086, 1.0402, 1.1816], [-0.2880, 0.5781, 0.6124], [0.1480, 0.6129, -0.0590]],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

2
tests/models/regnet/test_modeling_regnet.py
View File

@@ -255,7 +255,7 @@ class RegNetModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [-0.4180, -1.5051, -3.4836],
("cuda", 8): [-0.4168, -1.5056, -3.4836],
("cuda", 8): [-0.4180, -1.5051, -3.4836],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

2
tests/models/resnet/test_modeling_resnet.py
View File

@@ -304,7 +304,7 @@ class ResNetModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [-11.1069, -9.7877, -8.3777],
("cuda", 8): [-11.1112, -9.7916, -8.3788],
("cuda", 8): [-11.1069, -9.7877, -8.3777],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

6
tests/models/rt_detr/test_modeling_rt_detr.py
View File

@@ -787,9 +787,9 @@ class RTDetrModelIntegrationTest(unittest.TestCase):
[40.114475, 73.44104, 175.9573, 118.48469],
],
("cuda", 8): [
[1.4183e-01, 3.8063e-01, 6.4013e02, 4.7621e02],
[3.4338e02, 2.4275e01, 6.4014e02, 3.7150e02],
[1.3236e01, 5.4179e01, 3.1899e02, 4.7222e02],
[1.3775e-01, 3.7821e-01, 6.4013e02, 4.7621e02],
[3.4338e02, 2.4277e01, 6.4014e02, 3.7150e02],
[1.3225e01, 5.4179e01, 3.1898e02, 4.7222e02],
[4.0114e01, 7.3441e01, 1.7596e02, 1.1848e02],
],
}

6
tests/models/rt_detr_v2/test_modeling_rt_detr_v2.py
View File

@@ -782,10 +782,10 @@ class RTDetrV2ModelIntegrationTest(unittest.TestCase):
[-1.0521e-01, 2.9717e00, 6.3989e02, 4.7362e02],
],
("cuda", 8): [
[3.4115e02, 2.5109e01, 6.3997e02, 3.7290e02],
[1.2785e01, 5.6350e01, 3.1767e02, 4.7134e02],
[3.4114e02, 2.5111e01, 6.3998e02, 3.7289e02],
[1.2779e01, 5.6347e01, 3.1767e02, 4.7134e02],
[3.9959e01, 7.3117e01, 1.7565e02, 1.1744e02],
[-1.0471e-01, 2.9680e00, 6.3989e02, 4.7362e02],
[-1.0502e-01, 2.9707e00, 6.3989e02, 4.7362e02],
],
}
)

2
tests/models/sam/test_modeling_sam.py
View File

@@ -779,7 +779,7 @@ class SamModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [-12.7729, -12.3665, -12.6061],
("cuda", 8): [-12.7657, -12.3683, -12.5983],
("cuda", 8): [-12.7731, -12.3667, -12.6063],
}
)
expected_masks = torch.tensor(expectations.get_expectation()).to(torch_device)

2
tests/models/timesformer/test_modeling_timesformer.py
View File

@@ -353,7 +353,7 @@ class TimesformerModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [-0.3016, -0.7713, -0.4205],
("cuda", 8): [-0.3004, -0.7708, -0.4205],
("cuda", 8): [-0.3016, -0.7713, -0.4205],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

2
tests/models/upernet/test_modeling_upernet.py
View File

@@ -297,7 +297,7 @@ class UperNetModelIntegrationTest(unittest.TestCase):
self.assertEqual(outputs.logits.shape, expected_shape)
expected_slice = torch.tensor(
[[-7.5969, -7.5969, -7.4313], [-7.5969, -7.5969, -7.4313], [-7.4808, -7.4808, -7.3080]]
[[-7.5958, -7.5958, -7.4302], [-7.5958, -7.5958, -7.4302], [-7.4797, -7.4797, -7.3068]]
).to(torch_device)
torch.testing.assert_close(outputs.logits[0, 0, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)

2
tests/models/vivit/test_modeling_vivit.py
View File

@@ -358,7 +358,7 @@ class VivitModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [-0.9498, 2.7971, -1.4049, 0.1024, -1.8353],
("cuda", 8): [-0.9502, 2.7967, -1.4046, 0.1027, -1.8345],
("cuda", 8): [-0.9498, 2.7971, -1.4049, 0.1025, -1.8353],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)

2
tests/models/x_clip/test_modeling_x_clip.py
View File

@@ -761,7 +761,7 @@ class XCLIPModelIntegrationTest(unittest.TestCase):
expectations = Expectations(
{
(None, None): [[0.0126, 0.2109, 0.0609], [0.0448, 0.5862, -0.1688], [-0.0881, 0.8525, -0.3044]],
("cuda", 8): [[0.0141, 0.2114, 0.0599], [0.0446, 0.5866, -0.1674], [-0.0876, 0.8592, -0.3025]],
("cuda", 8): [[0.0126, 0.2109, 0.0609], [0.0448, 0.5862, -0.1688], [-0.0881, 0.8525, -0.3044]],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)