Fix CUDA device access in T5EncoderModel and add GPU check

app.py

@@ -16,6 +16,15 @@ import torch.distributed as dist
 from PIL import Image
 from huggingface_hub import snapshot_download
 
+# 检查 GPU 可用性（参考 Meigen-MultiTalk）
+is_gpu_available = torch.cuda.is_available()
+if is_gpu_available:
+    # 初始化 CUDA，确保设备可用
+    try:
+        _ = torch.cuda.current_device()
+    except RuntimeError:
+        is_gpu_available = False
+
 # 导入 AnyTalker 相关的模块
 import wan
 from wan.configs import SIZE_CONFIGS, SUPPORTED_SIZES, WAN_CONFIGS, MAX_AREA_CONFIGS

wan/modules/t5.py

@@ -475,11 +475,17 @@ class T5EncoderModel:
         self,
         text_len,
         dtype=torch.bfloat16,
-        device=torch.cuda.current_device(),
+        device=None,
         checkpoint_path=None,
         tokenizer_path=None,
         shard_fn=None,
     ):
+        # 延迟获取 CUDA 设备，避免在导入时访问
+        if device is None:
+            if torch.cuda.is_available():
+                device = torch.cuda.current_device()
+            else:
+                device = torch.device('cpu')
         self.text_len = text_len
         self.dtype = dtype
         self.device = device