make test_instant_style_multiple_masks pass on XPU (huggingface#11266)

Signed-off-by: Matrix Yao <[email protected]>

Author: yao-matrix

tests/pipelines/ip_adapters/test_ip_adapter_stable_diffusion.py

@@ -34,6 +34,7 @@
 from diffusers.image_processor import IPAdapterMaskProcessor
 from diffusers.utils import load_image
 from diffusers.utils.testing_utils import (
+    Expectations,
     backend_empty_cache,
     enable_full_determinism,
     is_flaky,
@@ -664,7 +665,50 @@ def test_instant_style_multiple_masks(self):
         images = pipeline(**inputs).images
         image_slice = images[0, :3, :3, -1].flatten()
 
-        expected_slice = np.array([0.2323, 0.1026, 0.1338, 0.0638, 0.0662, 0.0000, 0.0000, 0.0000, 0.0199])
+        expected_slices = Expectations(
+            {
+                ("xpu", 3): np.array(
+                    [
+                        0.2520,
+                        0.1050,
+                        0.1510,
+                        0.0997,
+                        0.0893,
+                        0.0019,
+                        0.0000,
+                        0.0000,
+                        0.0210,
+                    ]
+                ),
+                ("cuda", 7): np.array(
+                    [
+                        0.2323,
+                        0.1026,
+                        0.1338,
+                        0.0638,
+                        0.0662,
+                        0.0000,
+                        0.0000,
+                        0.0000,
+                        0.0199,
+                    ]
+                ),
+                ("cuda", 8): np.array(
+                    [
+                        0.2518,
+                        0.1059,
+                        0.1553,
+                        0.0977,
+                        0.0852,
+                        0.0000,
+                        0.0000,
+                        0.0000,
+                        0.0220,
+                    ]
+                ),
+            }
+        )
+        expected_slice = expected_slices.get_expectation()
 
         max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice)
         assert max_diff < 5e-4