diff --git a/tutorials/source_en/debug/dump.md b/tutorials/source_en/debug/dump.md
index cabe663f95d17f776c63c3fb8dda16dd488fa83e..109361a70888b43294608f2371ba3b949b19a32f 100644
--- a/tutorials/source_en/debug/dump.md
+++ b/tutorials/source_en/debug/dump.md
@@ -155,7 +155,7 @@ MindSpore supports different Dump functionalities under various modes, as shown
             - "negative inf count": represents the number of `-Inf` elements in the tensor;
             - "positive inf count": represents the number of `+Inf` elements in the tensor;
             - "zero count": represents the number of zero elements in the tensor;
-            - "md5": represents the MD5 value of the tensor;
+            - "hash": represents the hash feature value of the tensor, currently using the SHA1 algorithm by default, so it can also be written as "hash:sha1", SHA1 algorithm is recommended for its faster；"hash:md5" represents the MD5 value of the tensor, which yields the same result as the "md5" configuration item in previous versions;
             - "l2norm": represents L2Norm value of the tensor, supporting both device and host statistics.
 
             Except for those marked as supporting device statistics, other statistics can be collected only on the host.
@@ -168,7 +168,7 @@ MindSpore supports different Dump functionalities under various modes, as shown
 
         - `enable`: When set to `true`, enable Synchronous Dump. When set to false or not set, Asynchronous Dump will be used on Ascend. The main difference between the two is that Asynchronous Dump has less impact on the original code execution order.
         - `trans_flag`: Enable trans flag. Transform the device data format into NCHW. If it is `true`, the data will be saved in the 4D format (NCHW) format on the Host side; if it is `false`, the data format on the Device side will be retained. Default: `true`.
-        - `stat_calc_mode`: Select the backend for statistical calculations. Options are "host" and "device". Choosing "device" enables device computation of statistics, currently only effective on Ascend, and supports only min/max/avg/l2norm statistics. When `op_debug_mode` is set to 3, only `stat_calc_mode` set to "host" is supported.
+        - `stat_calc_mode`: Select the backend for statistical calculations. Options are "host" and "device". Choosing "device" enables device computation of statistics, currently only effective on Ascend, and supports only min/max/avg/l2norm statistics. When `op_debug_mode` is set to 3, only `stat_calc_mode` set to "host" is supported. Default: "host".
         - `device_stat_precision_mode`(Optional): Precision mode of device statistics, and the value can be "high" or "low". When "high" is selected, avg/l2norm statistics will be calculated using float32, which will increase device memory usage and have higher precision; when "low" is selected, the same type as the original data will be used for calculation, which will occupy less device memory, but statistics overflow may be caused when processing large values. The default value is "high".
         - `sample_mode`(Optional): Setting it to 0 means the sample dump function is not enabled. Enable the sampling dump feature during graph compilation using the ms_backend backend. This field is effective only when "op_debug_mode" is set to `0`, sample dump cannot be enabled in other scene.
         - `sample_num`(Optional): Used to control the size of sample in sample dump. The default value is 100.
diff --git a/tutorials/source_zh_cn/debug/dump.md b/tutorials/source_zh_cn/debug/dump.md
index 444a145e262989c41b3d6a681b3c581062725eb6..1077c97419d2c7735e3de20738a275e61758102d 100644
--- a/tutorials/source_zh_cn/debug/dump.md
+++ b/tutorials/source_zh_cn/debug/dump.md
@@ -155,7 +155,7 @@ MindSpore在不同后端下支持的Dump功能如下表所示：
             - "negative inf count": 表示Tensor中`-Inf`元素的个数；
             - "positive inf count": 表示Tensor中`+Inf`元素的个数；
             - "zero count": 表示Tensor中元素`0`的个数；
-            - "md5": 表示Tensor的MD5值；
+            - "hash": 表示Tensor的哈希特征值，默认使用SHA1算法，也可写作"hash:sha1"，该算法计算更快，推荐优先使用；"hash:md5"表示Tensor的MD5值，与先前版本的"md5"配置项结果相同。
             - "l2norm": 表示Tensor的L2Norm值，支持在device统计和在host统计。
 
             以上除了标记了支持device统计的，其他都仅支持在host统计。
@@ -168,7 +168,7 @@ MindSpore在不同后端下支持的Dump功能如下表所示：
 
         - `enable`：设置成true，表示开启同步Dump；设置成false时，采用异步Dump。不设置该字段时默认值为false，开启异步Dump。两者的区别是异步Dump对原本代码执行过程的影响更小。
         - `trans_flag`：开启格式转换，将设备上的数据格式转换成NCHW格式。若为`true`，则数据会以Host侧的4D格式（NCHW）格式保存；若为`false`，则保留Device侧的数据格式。该配置参数在CPU上无效，因为CPU上没有format转换。默认值：true。
-        - `stat_calc_mode`：选择统计信息计算后端，可选"host"和"device"。选择"device"后可以使能device计算统计信息，当前只在Ascend生效，只支持`min/max/avg/l2norm`统计量。在op_debug_mode设置为3时，仅支持将`stat_calc_mode`设置为"host"。
+        - `stat_calc_mode`：选择统计信息计算后端，可选"host"和"device"。选择"device"后可以使能device计算统计信息，当前只在Ascend生效，只支持`min/max/avg/l2norm`统计量。在op_debug_mode设置为3时，仅支持将`stat_calc_mode`设置为"host"。默认值："host"。
         - `device_stat_precision_mode`（可选）：device统计信息精度模式，可选"high"和"low"。选择"high"时，`avg/l2norm`统计量使用float32进行计算，会增加device内存占用，精度更高；为"low"时使用与原始数据相同的类型进行计算，device内存占用较少，但在处理较大数值时可能会导致统计量溢出。默认值为"high"。
         - `sample_mode`（可选）：设置成0，表示不开启切片dump功能；设置成1时，在图编译后端为ms_backend的情况下开启切片dump功能。仅在op_debug_mode设置为0时生效，其他场景不会开启切片dump功能。
         - `sample_num`（可选）：用于控制切片dump中切片的大小。默认值为100。