fix: Add weight whitelist support for torch 2.6 (#110)

configs/config.py

@@ -22,18 +22,16 @@ version_config_list = [
 ]
 
 
-def singleton_variable(func):
-    def wrapper(*args, **kwargs):
-        if wrapper.instance is None:
-            wrapper.instance = func(*args, **kwargs)
-        return wrapper.instance
+class Singleton(type):
+    _instances = {}
 
-    wrapper.instance = None
-    return wrapper
+    def __call__(cls, *args, **kwargs):
+        if cls not in cls._instances:
+            cls._instances[cls] = super(Singleton, cls).__call__(*args, **kwargs)
+        return cls._instances[cls]
 
 
-@singleton_variable
-class Config:
+class Config(metaclass=Singleton):
     def __init__(self):
         self.device = "cuda:0"
         self.is_half = True
@@ -129,6 +127,16 @@ class Config:
         else:
             return False
 
+    @staticmethod
+    def use_insecure_load():
+        try:
+            from fairseq.data.dictionary import Dictionary
+
+            torch.serialization.add_safe_globals([Dictionary])
+            logging.warning("Using insecure weight loading for fairseq dictionary")
+        except AttributeError:
+            pass
+
     def use_fp32_config(self):
         for config_file in version_config_list:
             self.json_config[config_file]["train"]["fp16_run"] = False
@@ -210,15 +218,20 @@ class Config:
         else:
             if self.instead:
                 logger.info(f"Use {self.instead} instead")
+
         logger.info(
             "Half-precision floating-point: %s, device: %s"
             % (self.is_half, self.device)
         )
+
+        # Check if the pytorch is 2.6 or higher
+        if tuple(map(int, torch.__version__.split("+")[0].split("."))) >= (2, 6, 0):
+            self.use_insecure_load()
+
         return x_pad, x_query, x_center, x_max
 
 
-@singleton_variable
-class CPUConfig:
+class CPUConfig(metaclass=Singleton):
     def __init__(self):
         self.device = "cpu"
         self.is_half = False