xpu enabling for 4 cases (#12345)

Signed-off-by: Yao, Matrix <matrix.yao@intel.com>

src/diffusers/modular_pipelines/components_manager.py

@@ -25,6 +25,7 @@ from ..utils import (
     is_accelerate_available,
     logging,
 )
+from ..utils.torch_utils import get_device
 
 
 if is_accelerate_available():
@@ -161,7 +162,9 @@ class AutoOffloadStrategy:
 
         current_module_size = model.get_memory_footprint()
 
-        mem_on_device = torch.cuda.mem_get_info(execution_device.index)[0]
+        device_type = execution_device.type
+        device_module = getattr(torch, device_type, torch.cuda)
+        mem_on_device = device_module.mem_get_info(execution_device.index)[0]
         mem_on_device = mem_on_device - self.memory_reserve_margin
         if current_module_size < mem_on_device:
             return []
@@ -301,7 +304,7 @@ class ComponentsManager:
         cm.add("vae", vae_model, collection="sdxl")
 
         # Enable auto offloading
-        cm.enable_auto_cpu_offload(device="cuda")
+        cm.enable_auto_cpu_offload()
 
         # Retrieve components
         unet = cm.get_one(name="unet", collection="sdxl")
@@ -490,6 +493,8 @@ class ComponentsManager:
             gc.collect()
             if torch.cuda.is_available():
                 torch.cuda.empty_cache()
+            if torch.xpu.is_available():
+                torch.xpu.empty_cache()
 
     # YiYi TODO: rename to search_components for now, may remove this method
     def search_components(
@@ -678,7 +683,7 @@ class ComponentsManager:
 
         return get_return_dict(matches, return_dict_with_names)
 
-    def enable_auto_cpu_offload(self, device: Union[str, int, torch.device] = "cuda", memory_reserve_margin="3GB"):
+    def enable_auto_cpu_offload(self, device: Union[str, int, torch.device] = None, memory_reserve_margin="3GB"):
         """
         Enable automatic CPU offloading for all components.
 
@@ -704,6 +709,8 @@ class ComponentsManager:
 
         self.disable_auto_cpu_offload()
         offload_strategy = AutoOffloadStrategy(memory_reserve_margin=memory_reserve_margin)
+        if device is None:
+            device = get_device()
         device = torch.device(device)
         if device.index is None:
             device = torch.device(f"{device.type}:{0}")

tests/lora/test_lora_layers_hunyuanvideo.py

@@ -253,6 +253,7 @@ class HunyuanVideoLoRAIntegrationTests(unittest.TestCase):
         expected_slices = Expectations(
             {
                 ("cuda", 7): np.array([0.1013, 0.1924, 0.0078, 0.1021, 0.1929, 0.0078, 0.1023, 0.1919, 0.7402, 0.104, 0.4482, 0.7354, 0.0925, 0.4382, 0.7275, 0.0815]),
+                ("xpu", 3): np.array([0.1013, 0.1924, 0.0078, 0.1021, 0.1929, 0.0078, 0.1023, 0.1919, 0.7402, 0.104, 0.4482, 0.7354, 0.0925, 0.4382, 0.7275, 0.0815]),
             }
         )
         # fmt: on