Win and linux can run the code

example/export_samples.py

@@ -14,15 +14,16 @@ import torch.nn.functional as F
 
 from data_utils import load_split
 from hybrid_diffusion import HybridDiffusionModel, cosine_beta_schedule
+from platform_utils import resolve_device, safe_path, ensure_dir
 
 
 def load_vocab(path: str) -> Dict[str, Dict[str, int]]:
-    with open(path, "r", encoding="ascii") as f:
+    with open(path, "r", encoding="utf-8") as f:
         return json.load(f)["vocab"]
 
 
 def load_stats(path: str):
-    with open(path, "r", encoding="ascii") as f:
+    with open(path, "r", encoding="utf-8") as f:
         return json.load(f)
 
 
@@ -66,17 +67,7 @@ def parse_args():
     return parser.parse_args()
 
 
-def resolve_device(mode: str) -> str:
-    mode = mode.lower()
-    if mode == "cpu":
-        return "cpu"
-    if mode == "cuda":
-        if not torch.cuda.is_available():
-            raise SystemExit("device set to cuda but CUDA is not available")
-        return "cuda"
-    if torch.cuda.is_available():
-        return "cuda"
-    return "cpu"
+# 使用 platform_utils 中的 resolve_device 函数
 
 
 def main():
@@ -156,7 +147,7 @@ def main():
     out_cols = [c for c in header if c != time_col or args.include_time]
 
     os.makedirs(os.path.dirname(args.out), exist_ok=True)
-    with open(args.out, "w", newline="", encoding="ascii") as f:
+    with open(args.out, "w", newline="", encoding="utf-8") as f:
         writer = csv.DictWriter(f, fieldnames=out_cols)
         writer.writeheader()