diff --git a/debug/accuracy_tools/atat/pytorch/compare/acc_compare.py b/debug/accuracy_tools/atat/pytorch/compare/acc_compare.py
index b6a06ede3a2684294ab27d99d3897eba384cfa7f..0fd0082a1109b470db9ea5c9b1ef1fd1bf437b0f 100644
--- a/debug/accuracy_tools/atat/pytorch/compare/acc_compare.py
+++ b/debug/accuracy_tools/atat/pytorch/compare/acc_compare.py
@@ -712,7 +712,7 @@ def op_item_parse(item, op_name, index, item_list=[], top_bool=True):
             parsed_item = item
             parsed_item['full_op_name'] = full_op_name
             item_list.append(parsed_item)
-        else:
+        elif 'type' in item:
             parsed_item = {}
             if item['type'] == 'slice':
                 parsed_item['full_op_name'] = full_op_name
@@ -736,12 +736,45 @@ def op_item_parse(item, op_name, index, item_list=[], top_bool=True):
                 parsed_item['Norm'] = item['value']
                 parsed_item['data_name'] = '-1'
                 item_list.append(parsed_item)
+        else:
+            resolve_api_special_parameters(item, full_op_name, item_list)
     else:
         for j in range(len(item)):
             op_item_parse(item[j], full_op_name, j, top_bool=False)
     return item_list
 
 
+def resolve_api_special_parameters(data_dict, full_op_name, item_list):
+    """
+    Function Description:
+        解析下面格式的数据, 是api参数的一种特殊格式
+        {
+         "last_hidden_state": {
+          "type": "torch.Tensor",
+          "dtype": "torch.bfloat16",
+          ...
+         },
+         "loss": {
+          "type": "torch.Tensor",
+          "dtype": "torch.float32",
+          ...
+         }
+        }
+    Parameter:
+        data_dict: 字典格式的数据
+        full_op_name: 参数的全名字符串
+        item_list: 参数信息集合        
+    """
+    for key, value in data_dict.items():
+        if isinstance(value, dict):
+            parsed_item = value
+            parts = full_op_name.split(".")
+            parts.insert(-1, key)
+            full_op_name_new = ".".join(parts)
+            parsed_item['full_op_name'] = full_op_name_new
+            item_list.append(parsed_item)
+
+
 def read_op(op_data, op_name):
     op_parsed_list = []
     if 'forward' in op_name:
diff --git a/debug/accuracy_tools/atat/pytorch/module_processer.py b/debug/accuracy_tools/atat/pytorch/module_processer.py
index 434f95910dafd57587d93ad22cb0a0c825083aba..b2d3d798f622336a17c6336c62f5731353a8eeea 100644
--- a/debug/accuracy_tools/atat/pytorch/module_processer.py
+++ b/debug/accuracy_tools/atat/pytorch/module_processer.py
@@ -18,8 +18,21 @@ class ModuleProcesser:
             self.scope = None
         BackwardHook.setup_input_hook = ModuleProcesser.clone_return_value(BackwardHook.setup_input_hook)
         BackwardHook.setup_output_hook = ModuleProcesser.clone_return_value(BackwardHook.setup_output_hook)
+        BackwardHook.setup_output_hook = ModuleProcesser.filter_tensor_and_tuple(BackwardHook.setup_output_hook)
         self.module_count = {}
 
+    @staticmethod
+    def filter_tensor_and_tuple(func):
+        @wraps(func)
+        def wrap_by_filter_tensor_and_tuple(*args, **kwargs):
+            # setup_output_hook传入非tensor数据，工具后续dump会报错，处理方式是非tensor数据不传入
+            # setup_output_hook定义为setup_output_hook(self, args)，因此处理第二个位置参数，即*args[1]
+            if not isinstance(args[1], (torch.Tensor, tuple)):
+                return args[1]
+            return func(*args, **kwargs)
+
+        return wrap_by_filter_tensor_and_tuple
+
     @staticmethod
     def clone_return_value(func):
         @wraps(func)