Fix

lightx2v/models/networks/wan/model.py

@@ -66,9 +66,9 @@ class WanModel:
         use_bfloat16 = self.config.get("use_bfloat16", True)
         with safe_open(file_path, framework="pt") as f:
             if use_bfloat16:
-                tensor_dict = {key: f.get_tensor(key).to(torch.bfloat16).to(self.device) for key in f.keys()}
+                tensor_dict = {key: f.get_tensor(key).pin_memory().to(torch.bfloat16).to(self.device) for key in f.keys()}
             else:
-                tensor_dict = {key: f.get_tensor(key).to(self.device) for key in f.keys()}
+                tensor_dict = {key: f.get_tensor(key).pin_memory().to(self.device) for key in f.keys()}
         return tensor_dict
 
     def _load_ckpt(self):
@@ -107,9 +107,9 @@ class WanModel:
                 with safe_open(safetensor_path, framework="pt", device=str(self.device)) as f:
                     logger.info(f"Loading weights from {safetensor_path}")
                     for k in f.keys():
-                        weight_dict[k] = f.get_tensor(k)
+                        weight_dict[k] = f.get_tensor(k).pin_memory()
                         if weight_dict[k].dtype == torch.float:
-                            weight_dict[k] = weight_dict[k].to(torch.bfloat16)
+                            weight_dict[k] = weight_dict[k].pin_memory().to(torch.bfloat16)
 
         return weight_dict
 
@@ -121,9 +121,9 @@ class WanModel:
         safetensor_path = os.path.join(lazy_load_model_path, "non_block.safetensors")
         with safe_open(safetensor_path, framework="pt", device=str(self.device)) as f:
             for k in f.keys():
-                pre_post_weight_dict[k] = f.get_tensor(k)
+                pre_post_weight_dict[k] = f.get_tensor(k).pin_memory()
                 if pre_post_weight_dict[k].dtype == torch.float:
-                    pre_post_weight_dict[k] = pre_post_weight_dict[k].to(torch.bfloat16)
+                    pre_post_weight_dict[k] = pre_post_weight_dict[k].pin_memory().to(torch.bfloat16)
 
         safetensors_pattern = os.path.join(lazy_load_model_path, "block_*.safetensors")
         safetensors_files = glob.glob(safetensors_pattern)
@@ -134,9 +134,9 @@ class WanModel:
             with safe_open(file_path, framework="pt") as f:
                 for k in f.keys():
                     if "modulation" in k:
-                        transformer_weight_dict[k] = f.get_tensor(k)
+                        transformer_weight_dict[k] = f.get_tensor(k).pin_memory()
                         if transformer_weight_dict[k].dtype == torch.float:
-                            transformer_weight_dict[k] = transformer_weight_dict[k].to(torch.bfloat16)
+                            transformer_weight_dict[k] = transformer_weight_dict[k].pin_memory().to(torch.bfloat16)
 
         return pre_post_weight_dict, transformer_weight_dict