Add XPU sdpa Support

demo/vibevoice_asr_inference_from_file.py

@@ -37,7 +37,7 @@ class VibeVoiceASRBatchInference:
         
         Args:
             model_path: Path to the pretrained model
-            device: Device to run inference on (cuda, mps, cpu, auto)
+            device: Device to run inference on (cuda, mps, xpu, cpu, auto)
             dtype: Data type for model weights
             attn_implementation: Attention implementation to use ('flash_attention_2', 'sdpa', 'eager')
         """
@@ -442,8 +442,8 @@ def main():
     parser.add_argument(
         "--device", 
         type=str, 
-        default="cuda" if torch.cuda.is_available() else ("mps" if torch.backends.mps.is_available() else "cpu"),
-        choices=["cuda", "cpu", "mps", "auto"],
+        default="cuda" if torch.cuda.is_available() else ("xpu" if torch.backends.xpu.is_available() else ("mps" if torch.backends.mps.is_available() else "cpu") ),
+        choices=["cuda", "cpu", "mps","xpu", "auto"],
         help="Device to run inference on"
     )
     parser.add_argument(
@@ -475,7 +475,7 @@ def main():
         type=str,
         default="auto",
         choices=["flash_attention_2", "sdpa", "eager", "auto"],
-        help="Attention implementation to use. 'auto' will select the best available for your device (flash_attention_2 for CUDA, sdpa for MPS/CPU)"
+        help="Attention implementation to use. 'auto' will select the best available for your device (flash_attention_2 for CUDA, sdpa for MPS/CPU/XPU)"
     )
     
     args = parser.parse_args()
@@ -490,7 +490,7 @@ def main():
                 print("flash_attn not installed, falling back to sdpa")
                 args.attn_implementation = "sdpa"
         else:
-            # MPS and CPU don't support flash_attention_2
+            # MPS/XPU/CPU don't support flash_attention_2
             args.attn_implementation = "sdpa"
         print(f"Auto-detected attention implementation: {args.attn_implementation}")
     
@@ -532,6 +532,8 @@ def main():
     # Handle MPS device and dtype
     if args.device == "mps":
         model_dtype = torch.float32  # MPS works better with float32
+    elif args.device == "xpu":
+        model_dtype = torch.float32
     elif args.device == "cpu":
         model_dtype = torch.float32
     else: