Update `OneFormerModelIntegrationTest` expected values (#21295)

* update values

* update values

* update values

* Update tests/models/oneformer/test_modeling_oneformer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

tests/models/oneformer/test_modeling_oneformer.py

@@ -451,7 +451,7 @@ class OneFormerModelIntegrationTest(unittest.TestCase):
             outputs = model(**inputs)
 
         expected_slice_hidden_state = torch.tensor(
-            [[0.2724, 0.8287, 0.6025], [1.2706, 1.1252, 1.1445], [1.1357, 0.6150, 0.4185]]
+            [[0.2723, 0.8280, 0.6026], [1.2699, 1.1257, 1.1444], [1.1344, 0.6153, 0.4177]]
         ).to(torch_device)
         self.assertTrue(
             torch.allclose(
@@ -460,7 +460,7 @@ class OneFormerModelIntegrationTest(unittest.TestCase):
         )
 
         expected_slice_hidden_state = torch.tensor(
-            [[1.0581, 1.2275, 1.2000], [1.1901, 1.2925, 1.2861], [1.1578, 1.2558, 1.3212]]
+            [[1.0581, 1.2276, 1.2003], [1.1903, 1.2925, 1.2862], [1.158, 1.2559, 1.3216]]
         ).to(torch_device)
         self.assertTrue(
             torch.allclose(
@@ -469,7 +469,7 @@ class OneFormerModelIntegrationTest(unittest.TestCase):
         )
 
         expected_slice_hidden_state = torch.tensor(
-            [[3.0711, -1.1855, -5.1095], [3.5536, -3.2710, -5.2052], [2.6020, -4.3605, -4.1422]]
+            [[3.0668, -1.1833, -5.1103], [3.344, -3.362, -5.1101], [2.6017, -4.3613, -4.1444]]
         ).to(torch_device)
         self.assertTrue(
             torch.allclose(
@@ -495,7 +495,7 @@ class OneFormerModelIntegrationTest(unittest.TestCase):
             masks_queries_logits.shape,
             (1, model.config.num_queries, inputs_shape[-2] // 4, (inputs_shape[-1] + 2) // 4),
         )
-        expected_slice = [[[3.1215, 4.1250, 4.1106], [2.8183, 3.4623, 3.5512], [2.4550, 2.9841, 3.5081]]]
+        expected_slice = [[[3.1848, 4.2141, 4.1993], [2.9000, 3.5721, 3.6603], [2.5358, 3.0883, 3.6168]]]
         expected_slice = torch.tensor(expected_slice).to(torch_device)
         self.assertTrue(torch.allclose(masks_queries_logits[0, 0, :3, :3], expected_slice, atol=TOLERANCE))
         # class_queries_logits
@@ -505,7 +505,7 @@ class OneFormerModelIntegrationTest(unittest.TestCase):
             (1, model.config.num_queries, model.config.num_labels + 1),
         )
         expected_slice = torch.tensor(
-            [[3.0711, -1.1855, -5.1095], [3.5536, -3.2710, -5.2052], [2.6020, -4.3605, -4.1422]]
+            [[3.0668, -1.1833, -5.1103], [3.3440, -3.3620, -5.1101], [2.6017, -4.3613, -4.1444]]
         ).to(torch_device)
         self.assertTrue(torch.allclose(class_queries_logits[0, :3, :3], expected_slice, atol=TOLERANCE))