use torch.testing.assertclose instead to get more details about error in cis (#35659)

* 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

tests/models/data2vec/test_modeling_data2vec_text.py

@@ -527,7 +527,7 @@ class Data2VecTextModelIntegrationTest(TestCasePlus):
         # compare the actual values for a slice.
         expected_slice = torch.tensor([[[0.2328, 0.0000, 1.1710], [2.2525, 0.0000, 1.9937], [2.1280, 0.0000, 1.8691]]])
 
-        self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4))
+        torch.testing.assert_close(output[:, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)
 
     @slow
     def test_inference_no_head(self):
@@ -541,4 +541,4 @@ class Data2VecTextModelIntegrationTest(TestCasePlus):
             [[[0.1998, -0.0379, 0.0024], [-0.0971, -0.2214, -0.1798], [-0.0789, -0.2400, -0.1898]]]
         )
 
-        self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4))
+        torch.testing.assert_close(output[:, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)

tests/models/data2vec/test_modeling_data2vec_vision.py

@@ -548,7 +548,7 @@ class Data2VecVisionModelIntegrationTest(unittest.TestCase):
 
         expected_slice = torch.tensor([0.3277, -0.1395, 0.0911]).to(torch_device)
 
-        self.assertTrue(torch.allclose(logits[0, :3], expected_slice, atol=1e-4))
+        torch.testing.assert_close(logits[0, :3], expected_slice, rtol=1e-4, atol=1e-4)
 
         expected_top2 = [model.config.label2id[i] for i in ["remote control, remote", "tabby, tabby cat"]]
         self.assertEqual(logits[0].topk(2).indices.cpu().tolist(), expected_top2)