fix marigold ut case fail on xpu (#12350)

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

Author: yao-matrix

tests/pipelines/marigold/test_marigold_depth.py

@@ -33,6 +33,7 @@
 )
 
 from ...testing_utils import (
+    Expectations,
     backend_empty_cache,
     enable_full_determinism,
     floats_tensor,
@@ -356,7 +357,7 @@ def test_marigold_depth_einstein_f32_cpu_G0_S1_P32_E1_B1_M1(self):
             match_input_resolution=True,
         )
 
-    def test_marigold_depth_einstein_f32_cuda_G0_S1_P768_E1_B1_M1(self):
+    def test_marigold_depth_einstein_f32_accelerator_G0_S1_P768_E1_B1_M1(self):
         self._test_marigold_depth(
             is_fp16=False,
             device=torch_device,
@@ -369,7 +370,7 @@ def test_marigold_depth_einstein_f32_cuda_G0_S1_P768_E1_B1_M1(self):
             match_input_resolution=True,
         )
 
-    def test_marigold_depth_einstein_f16_cuda_G0_S1_P768_E1_B1_M1(self):
+    def test_marigold_depth_einstein_f16_accelerator_G0_S1_P768_E1_B1_M1(self):
         self._test_marigold_depth(
             is_fp16=True,
             device=torch_device,
@@ -382,7 +383,7 @@ def test_marigold_depth_einstein_f16_cuda_G0_S1_P768_E1_B1_M1(self):
             match_input_resolution=True,
         )
 
-    def test_marigold_depth_einstein_f16_cuda_G2024_S1_P768_E1_B1_M1(self):
+    def test_marigold_depth_einstein_f16_accelerator_G2024_S1_P768_E1_B1_M1(self):
         self._test_marigold_depth(
             is_fp16=True,
             device=torch_device,
@@ -395,20 +396,31 @@ def test_marigold_depth_einstein_f16_cuda_G2024_S1_P768_E1_B1_M1(self):
             match_input_resolution=True,
         )
 
-    def test_marigold_depth_einstein_f16_cuda_G0_S2_P768_E1_B1_M1(self):
+    def test_marigold_depth_einstein_f16_accelerator_G0_S2_P768_E1_B1_M1(self):
+        # fmt: off
+        expected_slices = Expectations(
+            {
+                ("cuda", 7): np.array([0.1085, 0.1098, 0.1110, 0.1081, 0.1085, 0.1082, 0.1085, 0.1057, 0.0996]),
+                ("xpu", 3): np.array([0.1084, 0.1096, 0.1108, 0.1080, 0.1083, 0.1080,
+ 0.1085, 0.1057, 0.0996]),
+            }
+        )
+        expected_slice = expected_slices.get_expectation()
+        # fmt: on
+
         self._test_marigold_depth(
             is_fp16=True,
             device=torch_device,
             generator_seed=0,
-            expected_slice=np.array([0.1085, 0.1098, 0.1110, 0.1081, 0.1085, 0.1082, 0.1085, 0.1057, 0.0996]),
+            expected_slice=expected_slice,
             num_inference_steps=2,
             processing_resolution=768,
             ensemble_size=1,
             batch_size=1,
             match_input_resolution=True,
         )
 
-    def test_marigold_depth_einstein_f16_cuda_G0_S1_P512_E1_B1_M1(self):
+    def test_marigold_depth_einstein_f16_accelerator_G0_S1_P512_E1_B1_M1(self):
         self._test_marigold_depth(
             is_fp16=True,
             device=torch_device,
@@ -421,7 +433,7 @@ def test_marigold_depth_einstein_f16_cuda_G0_S1_P512_E1_B1_M1(self):
             match_input_resolution=True,
         )
 
-    def test_marigold_depth_einstein_f16_cuda_G0_S1_P768_E3_B1_M1(self):
+    def test_marigold_depth_einstein_f16_accelerator_G0_S1_P768_E3_B1_M1(self):
         self._test_marigold_depth(
             is_fp16=True,
             device=torch_device,
@@ -435,7 +447,7 @@ def test_marigold_depth_einstein_f16_cuda_G0_S1_P768_E3_B1_M1(self):
             match_input_resolution=True,
         )
 
-    def test_marigold_depth_einstein_f16_cuda_G0_S1_P768_E4_B2_M1(self):
+    def test_marigold_depth_einstein_f16_accelerator_G0_S1_P768_E4_B2_M1(self):
         self._test_marigold_depth(
             is_fp16=True,
             device=torch_device,
@@ -449,7 +461,7 @@ def test_marigold_depth_einstein_f16_cuda_G0_S1_P768_E4_B2_M1(self):
             match_input_resolution=True,
         )
 
-    def test_marigold_depth_einstein_f16_cuda_G0_S1_P512_E1_B1_M0(self):
+    def test_marigold_depth_einstein_f16_accelerator_G0_S1_P512_E1_B1_M0(self):
         self._test_marigold_depth(
             is_fp16=True,
             device=torch_device,