add type check and error description

mindspore/train/serialization.py

@@ -148,18 +148,22 @@ def save_checkpoint(save_obj, ckpt_file_name, integrated_save=True, async_save=F
     Args:
         save_obj (nn.Cell or list): The cell object or data list(each element is a dictionary, like
                                     [{"name": param_name, "data": param_data},...], the type of param_name would
-                                    be string, and the type of param_data would be parameter, tensor or numpy).
+                                    be string, and the type of param_data would be parameter or tensor).
         ckpt_file_name (str): Checkpoint file name. If the file name already exists, it will be overwritten.
         integrated_save (bool): Whether to integrated save in automatic model parallel scene. Default: True
         async_save (bool): Whether asynchronous execution saves the checkpoint to a file. Default: False
 
     Raises:
-        TypeError: If the parameter save_obj is not nn.Cell or list type.
-        RuntimeError: Failed to save the Checkpoint file.
+        TypeError: If the parameter save_obj is not nn.Cell or list type.And if the parameter integrated_save and
+                   async_save are not bool type.
     """
 
     if not isinstance(save_obj, nn.Cell) and not isinstance(save_obj, list):
         raise TypeError("The parameter save_obj should be nn.Cell or list, but got {}".format(type(save_obj)))
+    if not isinstance(integrated_save, bool):
+        raise TypeError("The parameter integrated_save should be bool, but got {}".format(type(integrated_save)))
+    if not isinstance(async_save, bool):
+        raise TypeError("The parameter async_save should be bool, but got {}".format(type(async_save)))
 
     logger.info("Execute save checkpoint process.")