From 8377eb1dd69f9727d0271d03f3a5209d85e43b44 Mon Sep 17 00:00:00 2001
From: yangxinxian <947098055@qq.com>
Date: Thu, 13 Mar 2025 14:35:25 +0800
Subject: [PATCH 1/8] =?UTF-8?q?=E5=86=92=E7=83=9F?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../data_processor/mindspore_processor.py     | 40 ++++++----
 .../data_processor/pytorch_processor.py       | 43 ++++++----
 .../msprobe/core/data_dump/json_writer.py     | 78 +++++++++++++++++++
 3 files changed, 129 insertions(+), 32 deletions(-)

diff --git a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/mindspore_processor.py b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/mindspore_processor.py
index c6ab0293cf3..125f68643ab 100644
--- a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/mindspore_processor.py
+++ b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/mindspore_processor.py
@@ -43,6 +43,7 @@ class MindsporeDataProcessor(BaseDataProcessor):
         self.mindspore_object_key = {
             "dtype": self.analyze_dtype_in_kwargs
         }
+        self.stat_stack_list = []
         self._async_dump_cache = {}
         self.api_register = get_api_register()
 
@@ -61,11 +62,10 @@ class MindsporeDataProcessor(BaseDataProcessor):
     def get_stat_info_sync(data):
         tensor_stat = TensorStatInfo()
         if data.dtype == ms.bool_:
-            data_np = data.asnumpy()
-            tensor_stat.max = np.max(data_np).item()
-            tensor_stat.min = np.min(data_np).item()
+            tensor_stat.max = mint.any(data)
+            tensor_stat.min = mint.all(data)
         elif not data.shape:
-            tensor_stat.max = tensor_stat.min = tensor_stat.mean = tensor_stat.norm = data.item()
+            tensor_stat.max = tensor_stat.min = tensor_stat.mean = tensor_stat.norm = data
         elif data.dtype == ms.complex64 or data.dtype == ms.complex128:
             data_abs = np.abs(data.asnumpy())
             tensor_stat.max = np.max(data_abs).item()
@@ -76,10 +76,10 @@ class MindsporeDataProcessor(BaseDataProcessor):
             if not ops.is_floating_point(data) or data.dtype == ms.float64:
                 data = data.to(ms.float32)
             get_norm_value = mint.norm if hasattr(mint, "norm") else ops.norm
-            tensor_stat.max = mint.max(data).item()
-            tensor_stat.min = mint.min(data).item()
-            tensor_stat.mean = mint.mean(data).item()
-            tensor_stat.norm = get_norm_value(data).item()
+            tensor_stat.max = mint.max(data)
+            tensor_stat.min = mint.min(data)
+            tensor_stat.mean = mint.mean(data)
+            tensor_stat.norm = get_norm_value(data)
         return tensor_stat
 
     @staticmethod
@@ -147,10 +147,16 @@ class MindsporeDataProcessor(BaseDataProcessor):
         }
 
         if tensor_stat.stack_tensor_stat is None:
-            tensor_json.update({'Max': self.transfer_type(tensor_stat.max)})
-            tensor_json.update({'Min': self.transfer_type(tensor_stat.min)})
-            tensor_json.update({'Mean': self.transfer_type(tensor_stat.mean)})
-            tensor_json.update({'Norm': self.transfer_type(tensor_stat.norm)})
+            stat_values = [
+                tensor_stat.max,
+                tensor_stat.min,
+                tensor_stat.mean,
+                tensor_stat.norm
+            ]
+
+            placeholder_index = self.data_writer.append_stat_to_buffer(stat_values)
+
+            tensor_json.update({"tensor_stat_index": placeholder_index})
         else:
             tensor_json.update({'tensor_stat': tensor_stat.stack_tensor_stat})
         if self.config.summary_mode == Const.MD5 and not self.config.async_dump:
@@ -231,7 +237,7 @@ class OverflowCheckDataProcessor(MindsporeDataProcessor):
         api_info_struct = super().analyze_backward(name, module, module_input_output)
         self.maybe_save_overflow_data()
         return api_info_struct if self.has_overflow else None
-    
+
     def analyze_params(self, name, param_name, grad):
         self.has_overflow = False
         api_info_struct = super().analyze_params(name, param_name, grad)
@@ -249,11 +255,13 @@ class OverflowCheckDataProcessor(MindsporeDataProcessor):
         self.cached_tensors_and_file_paths = {}
 
     def _analyze_maybe_overflow_tensor(self, tensor_json):
-        if tensor_json['Max'] is None:
+        max_tensor = self.data_writer.get_buffer_values_max(tensor_json['tensor_stat_index'])
+        min_tensor = self.data_writer.get_buffer_values_min(tensor_json['tensor_stat_index'])
+        if max_tensor is None or min_tensor is None:
             return
-        if np.isinf(tensor_json['Max']) or np.isnan(tensor_json['Max']):
+        if mint.isinf(max_tensor) or mint.isnan(max_tensor):
             self.has_overflow = True
-        if np.isinf(tensor_json['Min']) or np.isnan(tensor_json['Min']):
+        if mint.isinf(min_tensor) or mint.isnan(min_tensor):
             self.has_overflow = True
 
     def _analyze_tensor(self, tensor, suffix):
diff --git a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py
index 4c56419dcb1..b4e6551ca34 100644
--- a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py
+++ b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py
@@ -126,17 +126,17 @@ class PytorchDataProcessor(BaseDataProcessor):
             tensor_stat.min = np.min(data_abs).item()
             tensor_stat.mean = np.mean(data_abs).item()
         elif data.dtype == torch.bool:
-            tensor_stat.max = torch.any(data).item()
-            tensor_stat.min = torch.all(data).item()
+            tensor_stat.max = torch.any(data)
+            tensor_stat.min = torch.all(data)
         elif not data.shape:
-            tensor_stat.max = tensor_stat.min = tensor_stat.mean = tensor_stat.norm = data.item()
+            tensor_stat.max = tensor_stat.min = tensor_stat.mean = tensor_stat.norm = data
         else:
             if not data.is_floating_point() or data.dtype == torch.float64:
                 data = data.float()
-            tensor_stat.max = torch.max(data).item()
-            tensor_stat.min = torch.min(data).item()
-            tensor_stat.mean = torch.mean(data).item()
-            tensor_stat.norm = torch.norm(data).item()
+            tensor_stat.max = torch.max(data)
+            tensor_stat.min = torch.min(data)
+            tensor_stat.mean = torch.mean(data)
+            tensor_stat.norm = torch.norm(data)
         return tensor_stat
 
     @staticmethod
@@ -271,16 +271,21 @@ class PytorchDataProcessor(BaseDataProcessor):
         tensor_json.update({'dtype': str(tensor.dtype)})
         tensor_json.update({"shape": tensor.shape})
         if tensor_stat.stack_tensor_stat is None:
-            tensor_json.update({"Max": tensor_stat.max})
-            tensor_json.update({"Min": tensor_stat.min})
-            tensor_json.update({"Mean": tensor_stat.mean})
-            tensor_json.update({"Norm": tensor_stat.norm})
+            stat_values = [
+                tensor_stat.max,
+                tensor_stat.min,
+                tensor_stat.mean,
+                tensor_stat.norm
+            ]
+            placeholder_index = self.data_writer.append_stat_to_buffer(stat_values)
+
+            tensor_json.update({"tensor_stat_index": placeholder_index})
             tensor_json.update({"requires_grad": tensor.requires_grad})
             if tensor_stat.max is not None:
-                if np.isinf(tensor_stat.max) or np.isnan(tensor_stat.max):
+                if torch.isinf(tensor_stat.max) or torch.isnan(tensor_stat.max):
                     tensor_json['Max_except_inf_nan'] = self.handle_tensor_extremum_nan_inf(tensor, "max")
             if tensor_stat.min is not None:
-                if np.isinf(tensor_stat.min) or np.isnan(tensor_stat.min):
+                if torch.isinf(tensor_stat.min) or torch.isnan(tensor_stat.min):
                     tensor_json['Min_except_inf_nan'] = self.handle_tensor_extremum_nan_inf(tensor, "min")
 
         else:
@@ -411,10 +416,16 @@ class OverflowCheckDataProcessor(PytorchDataProcessor):
             raise RuntimeError(f"overflow check failed") from e
 
     def _analyze_maybe_overflow_tensor(self, tensor_json):
-        if tensor_json['Max'] is None or tensor_json['Min'] is None:
+        max_tensor = self.data_writer.get_buffer_values_max(tensor_json['tensor_stat_index'])
+        min_tensor = self.data_writer.get_buffer_values_min(tensor_json['tensor_stat_index'])
+
+        if max_tensor is None or min_tensor is None :
             return
-        self.has_overflow = np.isinf(tensor_json['Max']) or np.isnan(tensor_json['Max']) or \
-                            np.isinf(tensor_json['Min']) or np.isnan(tensor_json['Min'])
+        if torch.isinf(max_tensor) or torch.isnan(max_tensor):
+            self.has_overflow = True
+
+        if torch.isinf(min_tensor) or torch.isnan(min_tensor):
+            self.has_overflow = True
 
     def _analyze_tensor(self, tensor, suffix):
         dump_data_name, file_path = self.get_save_file_path(suffix)
diff --git a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
index b1e26d16f97..33c95d686b4 100644
--- a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
+++ b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
@@ -38,6 +38,7 @@ class DataWriter:
         self.cache_stack = {}
         self.cache_construct = {}
         self.cache_debug = {}
+        self.stat_stack_list = []
 
     @staticmethod
     def write_data_to_csv(result: list, result_header: tuple, file_path: str):
@@ -126,7 +127,47 @@ class DataWriter:
     def write_debug_info_json(self, file_path):
         save_json(file_path, self.cache_debug, indent=1)
 
+    def append_stat_to_buffer(self, stat_vector):
+        """
+        直接使用 Python list 存储 stat_vector,
+        将 stat_vector 存入 self.stat_stack_list 的方式
+        """
+        self.stat_stack_list.append(stat_vector)
+        return len(self.stat_stack_list) - 1
+
+    def get_buffer_values_max(self, index):
+        return self.stat_stack_list[index][0]
+
+    def get_buffer_values_min(self, index):
+        print(f"self.stat_stack_list[index]:{self.stat_stack_list[index]}")
+        return self.stat_stack_list[index][1]
+
+    def flush_stat_stack(self):
+        """
+        在 flush 阶段，将所有存储的统计值从设备搬到 CPU，
+        这里返回一个列表，每个元素是 [Max, Min, Mean, Norm] 的数值列表
+        """
+        if not self.stat_stack_list:
+            return []
+        result = [
+            [
+                x.cpu().detach().numpy().tolist() if hasattr(x, "cpu") else
+                x.asnumpy().tolist() if hasattr(x, "asnumpy") else x
+                for x in stat_values
+            ]
+            for stat_values in self.stat_stack_list
+        ]
+        self.stat_stack_list = []
+        return result
+
     def write_json(self):
+        # 在写 JSON 前，统一获取统计值
+        stat_result = self.flush_stat_stack()
+        print(f"before:{self.cache_data}")
+        # 遍历 cache_data，将占位符替换为最终统计值
+        if stat_result:
+            self._replace_stat_placeholders(self.cache_data, stat_result)
+        print(f"after:{self.cache_data}")
         if self.cache_data:
             self.write_data_json(self.dump_file_path)
         if self.cache_stack:
@@ -136,6 +177,43 @@ class DataWriter:
         if self.cache_debug:
             self.write_debug_info_json(self.debug_file_path)
 
+    def _replace_stat_placeholders(self, data, stat_result):
+        if isinstance(data, dict):
+            keys = list(data.keys())  # 获取当前所有键
+            for key in keys:  # 避免遍历时修改字典
+                value = data[key]
+                if key == "tensor_stat_index" and isinstance(value, int):
+                    idx = value
+                    stat_values = stat_result[idx] if idx < len(stat_result) else [None] * 4
+
+                    # 构建新字段并删除旧键
+                    new_entries = {
+                        "type": data["type"],
+                        "dtype": data["dtype"],
+                        "shape": data["shape"],
+                        "Max": stat_values[0],
+                        "Min": stat_values[1],
+                        "Mean": stat_values[2],
+                        "Norm": stat_values[3]
+                    }
+                    del data[key]
+
+                    # 重构字典顺序
+                    updated_dict = {}
+                    # 先插入统计字段
+                    updated_dict.update(new_entries)
+                    # 保留原字典其他字段（排除已删除的tensor_stat_index）
+                    for k in data:
+                        if k not in new_entries:
+                            updated_dict[k] = data[k]
+                    data.clear()
+                    data.update(updated_dict)
+                else:
+                    self._replace_stat_placeholders(value, stat_result)
+        elif isinstance(data, list):
+            for item in data:
+                self._replace_stat_placeholders(item, stat_result)
+
     def fill_stack_tensor_data(self):
         self.process_stat_data_recursive(self.cache_data)
 
-- 
Gitee


From e1c00fb30760f29271a0527c8a5aefb4318a8f85 Mon Sep 17 00:00:00 2001
From: yangxinxian <947098055@qq.com>
Date: Thu, 13 Mar 2025 14:41:34 +0800
Subject: [PATCH 2/8] =?UTF-8?q?=E5=86=92=E7=83=9F?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py b/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py
index a9a543a8fac..48fac8d1317 100644
--- a/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py
+++ b/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py
@@ -102,7 +102,7 @@ class JitDump(_MindsporeFunctionExecutor):
             return False
         return True
 
-    def grad(self, obj, grad, weights, grad_position, *args, **kwargs):
+    def grad(self, obj, grad, weights, grad_position, False, *args, **kwargs):
         if JitDump.jit_dump_switch and JitDump.jit_enable:
             _api_register.restore_all_api()
         output = self._executor.grad(grad, obj, weights, grad_position, *args, *(kwargs.values()))
-- 
Gitee


From 90a10b47f0bb2ba920e260dfa65d4b9824dfc191 Mon Sep 17 00:00:00 2001
From: yangxinxian <947098055@qq.com>
Date: Thu, 13 Mar 2025 14:45:18 +0800
Subject: [PATCH 3/8] Update jit_dump.py

---
 debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py b/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py
index 48fac8d1317..715a06a1e96 100644
--- a/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py
+++ b/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py
@@ -102,10 +102,10 @@ class JitDump(_MindsporeFunctionExecutor):
             return False
         return True
 
-    def grad(self, obj, grad, weights, grad_position, False, *args, **kwargs):
+    def grad(self, obj, grad, weights, grad_position, *args, **kwargs):
         if JitDump.jit_dump_switch and JitDump.jit_enable:
             _api_register.restore_all_api()
-        output = self._executor.grad(grad, obj, weights, grad_position, *args, *(kwargs.values()))
+        output = self._executor.grad(grad, obj, weights, grad_position, False, *args, *(kwargs.values()))
         if JitDump.jit_dump_switch and JitDump.jit_enable:
             dump_jit(obj, args, None, False)
             _api_register.register_all_api()
-- 
Gitee


From 42ae4f5d87f34d6954a1dba78c1ae43029ee1e5d Mon Sep 17 00:00:00 2001
From: yangxinxian <947098055@qq.com>
Date: Thu, 13 Mar 2025 16:32:15 +0800
Subject: [PATCH 4/8] Update jit_dump.py

---
 debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py b/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py
index 715a06a1e96..a9a543a8fac 100644
--- a/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py
+++ b/debug/accuracy_tools/msprobe/mindspore/dump/jit_dump.py
@@ -105,7 +105,7 @@ class JitDump(_MindsporeFunctionExecutor):
     def grad(self, obj, grad, weights, grad_position, *args, **kwargs):
         if JitDump.jit_dump_switch and JitDump.jit_enable:
             _api_register.restore_all_api()
-        output = self._executor.grad(grad, obj, weights, grad_position, False, *args, *(kwargs.values()))
+        output = self._executor.grad(grad, obj, weights, grad_position, *args, *(kwargs.values()))
         if JitDump.jit_dump_switch and JitDump.jit_enable:
             dump_jit(obj, args, None, False)
             _api_register.register_all_api()
-- 
Gitee


From 61143517e1a4da742c5a61e30d6433e260662f0d Mon Sep 17 00:00:00 2001
From: yangxinxian <947098055@qq.com>
Date: Mon, 17 Mar 2025 17:28:29 +0800
Subject: [PATCH 5/8] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E6=A3=80=E8=A7=86?=
 =?UTF-8?q?=E6=84=8F=E8=A7=81?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../core/data_dump/data_processor/pytorch_processor.py     | 7 -------
 debug/accuracy_tools/msprobe/core/data_dump/json_writer.py | 3 +--
 2 files changed, 1 insertion(+), 9 deletions(-)

diff --git a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py
index b4e6551ca34..6b146203c4f 100644
--- a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py
+++ b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/pytorch_processor.py
@@ -281,13 +281,6 @@ class PytorchDataProcessor(BaseDataProcessor):
 
             tensor_json.update({"tensor_stat_index": placeholder_index})
             tensor_json.update({"requires_grad": tensor.requires_grad})
-            if tensor_stat.max is not None:
-                if torch.isinf(tensor_stat.max) or torch.isnan(tensor_stat.max):
-                    tensor_json['Max_except_inf_nan'] = self.handle_tensor_extremum_nan_inf(tensor, "max")
-            if tensor_stat.min is not None:
-                if torch.isinf(tensor_stat.min) or torch.isnan(tensor_stat.min):
-                    tensor_json['Min_except_inf_nan'] = self.handle_tensor_extremum_nan_inf(tensor, "min")
-
         else:
             tensor_json.update({"requires_grad": tensor.requires_grad})
             tensor_json.update({"tensor_stat": tensor_stat.stack_tensor_stat})
diff --git a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
index 33c95d686b4..c4af30fe933 100644
--- a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
+++ b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
@@ -151,8 +151,7 @@ class DataWriter:
             return []
         result = [
             [
-                x.cpu().detach().numpy().tolist() if hasattr(x, "cpu") else
-                x.asnumpy().tolist() if hasattr(x, "asnumpy") else x
+                x.item() if hasattr(x, "item") else x
                 for x in stat_values
             ]
             for stat_values in self.stat_stack_list
-- 
Gitee


From d676820b179c743ce02400fa3b3c58ef57489b3b Mon Sep 17 00:00:00 2001
From: yangxinxian <947098055@qq.com>
Date: Mon, 17 Mar 2025 19:13:39 +0800
Subject: [PATCH 6/8] Update json_writer.py

---
 debug/accuracy_tools/msprobe/core/data_dump/json_writer.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
index c4af30fe933..96d79de2787 100644
--- a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
+++ b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
@@ -162,11 +162,9 @@ class DataWriter:
     def write_json(self):
         # 在写 JSON 前，统一获取统计值
         stat_result = self.flush_stat_stack()
-        print(f"before:{self.cache_data}")
         # 遍历 cache_data，将占位符替换为最终统计值
         if stat_result:
             self._replace_stat_placeholders(self.cache_data, stat_result)
-        print(f"after:{self.cache_data}")
         if self.cache_data:
             self.write_data_json(self.dump_file_path)
         if self.cache_stack:
-- 
Gitee


From 714d9d5c7823cb92d2201809554588680ffd8403 Mon Sep 17 00:00:00 2001
From: yangxinxian <947098055@qq.com>
Date: Tue, 18 Mar 2025 15:28:01 +0800
Subject: [PATCH 7/8] Update mindspore_processor.py

---
 .../msprobe/core/data_dump/data_processor/mindspore_processor.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/mindspore_processor.py b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/mindspore_processor.py
index 125f68643ab..7b71e97c78d 100644
--- a/debug/accuracy_tools/msprobe/core/data_dump/data_processor/mindspore_processor.py
+++ b/debug/accuracy_tools/msprobe/core/data_dump/data_processor/mindspore_processor.py
@@ -43,7 +43,6 @@ class MindsporeDataProcessor(BaseDataProcessor):
         self.mindspore_object_key = {
             "dtype": self.analyze_dtype_in_kwargs
         }
-        self.stat_stack_list = []
         self._async_dump_cache = {}
         self.api_register = get_api_register()
 
-- 
Gitee


From 715447d24685741aba12bf1087381bbb4e0fe5ed Mon Sep 17 00:00:00 2001
From: yangxinxian <947098055@qq.com>
Date: Tue, 18 Mar 2025 15:44:12 +0800
Subject: [PATCH 8/8] Update json_writer.py

---
 debug/accuracy_tools/msprobe/core/data_dump/json_writer.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
index 96d79de2787..364237fd3c9 100644
--- a/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
+++ b/debug/accuracy_tools/msprobe/core/data_dump/json_writer.py
@@ -139,7 +139,6 @@ class DataWriter:
         return self.stat_stack_list[index][0]
 
     def get_buffer_values_min(self, index):
-        print(f"self.stat_stack_list[index]:{self.stat_stack_list[index]}")
         return self.stat_stack_list[index][1]
 
     def flush_stat_stack(self):
-- 
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