Fix CUDA device fallback in WanVAE and WanAF2V

wan/audio2video_multiID.py

@@ -67,7 +67,11 @@ class WanAF2V:
             use_half (`bool`, *optional*, defaults to False):
                 Whether to use half precision (float16/bfloat16) for model inference. Reduces memory usage.
         """
-        self.device = torch.device(f"cuda:{device_id}")
+        # 如果 CUDA 不可用，自动回退到 CPU
+        if torch.cuda.is_available():
+            self.device = torch.device(f"cuda:{device_id}")
+        else:
+            self.device = torch.device("cpu")
         self.config = config
         self.rank = rank
         self.t5_cpu = t5_cpu

wan/modules/vae.py

@@ -624,6 +624,12 @@ class WanVAE:
                  dtype=torch.float,
                  device="cuda"):
         self.dtype = dtype
+        # 如果 device 是 "cuda" 但 CUDA 不可用，自动回退到 CPU
+        if device == "cuda" and not torch.cuda.is_available():
+            device = "cpu"
+        elif isinstance(device, str) and device.startswith("cuda"):
+            if not torch.cuda.is_available():
+                device = "cpu"
         self.device = device
 
         mean = [