fix: update `llm_config` and `vision_config` Initialization in Config

configuration_eagle_chat.py

@@ -40,7 +40,7 @@ class Eagle2ChatConfig(PretrainedConfig):
         super().__init__(**kwargs)
 
         if vision_config is None:
-            vision_config = {}
+            self.vision_config = {}
             logger.info('vision_config is None. Initializing Vision Encoders with default values.')
         else:
             if vision_config['model_type'] == 'siglip_vision_model':
@@ -49,7 +49,7 @@ class Eagle2ChatConfig(PretrainedConfig):
                 raise ValueError('Unsupported model_type: {}'.format(vision_config['model_type']))
 
         if llm_config is None:
-            llm_config = {}
+            self.llm_config = {}
             logger.info('llm_config is None. Initializing the LLM config with default values')
         else:
             if llm_config['architectures'][0] == 'LlamaBidirectionalModel':
@@ -83,8 +83,14 @@ class Eagle2ChatConfig(PretrainedConfig):
             `Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
         """
         output = copy.deepcopy(self.__dict__)
-        output['vision_config'] = self.vision_config.to_dict()
-        output['llm_config'] = self.llm_config.to_dict()
+        if self.vision_config and hasattr(self.vision_config, 'to_dict'):
+            output['vision_config'] = self.vision_config.to_dict()
+        else:
+            output['vision_config'] = self.vision_config
+        if self.llm_config and hasattr(self.llm_config, 'to_dict'):
+            output['llm_config'] = self.llm_config.to_dict()
+        else:
+            output['llm_config'] = self.llm_config
         output['model_type'] = self.__class__.model_type
         output['use_backbone_lora'] = self.use_backbone_lora
         output['use_llm_lora'] = self.use_llm_lora