diff --git a/docs/mindspore/programming_guide/source_zh_cn/debug_in_pynative_mode.ipynb b/docs/mindspore/programming_guide/source_zh_cn/debug_in_pynative_mode.ipynb
index 3316b3d75d9518dc9aaca0a1d632026987305bb4..2dc4605b2589ac4f33c00571bc82a3be2e3eb940 100644
--- a/docs/mindspore/programming_guide/source_zh_cn/debug_in_pynative_mode.ipynb
+++ b/docs/mindspore/programming_guide/source_zh_cn/debug_in_pynative_mode.ipynb
@@ -2,7 +2,6 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "d8f28388",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:06:23.745016Z",
@@ -37,7 +36,6 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "1f073178",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:15:13.240496Z",
@@ -53,7 +51,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7c2d61c8",
    "metadata": {},
    "source": [
     "## 执行单算子"
@@ -62,7 +59,6 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "02da4fc9",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:08:29.337515Z",
@@ -109,7 +105,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cb199d5a",
    "metadata": {},
    "source": [
     "## 执行函数"
@@ -118,7 +113,6 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "ae94d0c8",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:08:53.065585Z",
@@ -156,7 +150,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4750f0de",
    "metadata": {},
    "source": [
     "## 执行网络\n",
@@ -167,7 +160,6 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "b27a3b82",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:09:16.498705Z",
@@ -208,7 +200,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e8fd0a3f",
    "metadata": {},
    "source": [
     "## 构建网络\n",
@@ -219,7 +210,6 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "587ec18c",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:09:54.055532Z",
@@ -264,7 +254,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "63cd2da8",
    "metadata": {},
    "source": [
     "## 设置Loss函数及优化器\n",
@@ -279,7 +268,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "12463c2b",
    "metadata": {},
    "source": [
     "## 保存模型参数\n",
@@ -297,7 +285,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "efe5d247",
    "metadata": {},
    "source": [
     "## 训练网络\n",
@@ -326,7 +313,6 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "642d8765",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:11:12.072192Z",
@@ -376,7 +362,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d3acddf1",
    "metadata": {},
    "source": [
     "上述示例代码中，在`TensorAddNet`类的`construct`之前加装了`ms_function`装饰器，该装饰器会将`construct`方法编译成计算图，在给定输入之后，以图的形式下发执行，而上一示例代码中的`add`会直接以普通的PyNative的方式执行。\n",
@@ -389,7 +374,6 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "0d5f8edc",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:11:37.208346Z",
@@ -432,7 +416,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "51aba8b2",
    "metadata": {},
    "source": [
     "如果被装饰的函数中包含了需要进行参数训练的算子（如`Convolution`、`BatchNorm`等算子），则这些算子必须在被装饰的函数之外完成实例化操作，如下例所示。\n",
@@ -443,7 +426,6 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "b768cd62",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:12:01.721275Z",
@@ -513,7 +495,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2c22412b",
    "metadata": {},
    "source": [
     "更多ms_function的功能可以参考[ms_function文档](https://mindspore.cn/docs/programming_guide/zh-CN/master/ms_function.html)。\n",
@@ -528,7 +509,6 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "733a67bc",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:12:28.228442Z",
@@ -542,7 +522,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "198071c8",
    "metadata": {},
    "source": [
     "示例代码:\n",
@@ -577,7 +556,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bc31de88",
    "metadata": {},
    "source": [
     "输出：此时算子为同步执行，当算子执行错误时，可以看到完整的调用栈，找到出错的代码行。\n",
@@ -604,7 +582,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "76c1c4d4",
    "metadata": {},
    "source": [
     "## Hook功能\n",
@@ -621,7 +598,6 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "7c478a5b",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:13:38.660885Z",
@@ -667,7 +643,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7c591014",
    "metadata": {},
    "source": [
     "更多HookBackward算子的说明可以参考[API文档](https://mindspore.cn/docs/api/zh-CN/master/api_python/ops/mindspore.ops.HookBackward.html)。\n",
@@ -691,7 +666,6 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "be24bd1e",
    "metadata": {},
    "outputs": [
     {
@@ -745,7 +719,6 @@
   },
   {
      "cell_type": "markdown",
-     "id": "7c591014",
      "metadata": {},
      "source": [
       "用户如果在Hook函数中直接返回新创建的数据，而不是返回由原始输入数据经过计算后得到的数据，那么梯度的反向传播将会在该Cell对象上截止。\n",
@@ -756,7 +729,6 @@
   {
      "cell_type": "code",
      "execution_count": 12,
-     "id": "ef703b78",
      "metadata": {},
      "outputs": [
       {
@@ -801,7 +773,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7527515d",
    "metadata": {},
    "source": [
     "为了避免脚本在切换到图模式时运行失败，不建议在Cell对象的 `construct` 函数中调用 `register_forward_pre_hook` 函数和 `handle` 对象的 `remove()` 函数。在PyNative模式下，如果在Cell对象的 `construct` 函数中调用 `register_forward_pre_hook` 函数，那么Cell对象每次运行都将新注册一个Hook函数。\n",
@@ -828,7 +799,6 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "bf9a9441",
    "metadata": {},
    "outputs": [
     {
@@ -880,7 +850,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6c43f47d",
    "metadata": {},
    "source": [
     "用户如果在Hook函数中直接返回新创建的数据，而不是将原始的输出数据经过计算后，将得到的新输出数据返回，那么梯度的反向传播将会在该Cell对象上截止。该现象可以参考 `register_forward_pre_hook` 函数的用例说明。\n",
@@ -891,7 +860,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "785b3be4",
    "metadata": {},
    "source": [
     "### Cell对象的register_backward_hook功能\n",
@@ -906,7 +874,6 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "9826935c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -917,7 +884,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "acb32235",
    "metadata": {},
    "source": [
     "这里的 `cell_id` 是Cell对象的名称以及ID信息， `grad_input` 是网络反向传播时，传入到Cell对象的梯度，它对应于正向过程中下一个算子的反向输出梯度； `grad_output` 是Cell对象反向输出的梯度。因此，用户可以使用 `register_backward_hook` 函数来捕获网络中某一个Cell对象的反向传入和反向输出梯度。用户可以在Hook函数中自定义对梯度的操作，比如查看、打印梯度，或者返回新的输出梯度。使用方式上与 `register_forward_pre_hook` 和 `register_forward_hook` 函数类似。\n",
@@ -928,7 +894,6 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "6aed31a5",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:14:26.523389Z",
@@ -994,7 +959,6 @@
   },
   {
      "cell_type": "markdown",
-     "id": "acb32235",
      "metadata": {},
      "source": [
       "当 `register_backward_hook` 函数和 `register_forward_pre_hook` 函数、 `register_forward_hook` 函数同时作用于同一Cell对象时，如果 `register_forward_pre_hook` 和 `register_forward_hook` 函数中有添加其他算子进行数据处理，这些新增算子会在Cell对象执行前或者执行后参与数据的正向计算，但是这些新增算子的反向梯度不在 `register_backward_hook` 函数的捕获范围内。 `register_backward_hook` 中注册的Hook函数仅捕获原始Cell对象的输入、输出梯度。\n",
@@ -1005,7 +969,6 @@
   {
      "cell_type": "code",
      "execution_count": 16,
-     "id": "bf9a9441",
      "metadata": {},
      "outputs": [
       {
@@ -1068,7 +1031,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a0eb08c",
    "metadata": {},
    "source": [
     "这里的 `grad_input` 是梯度反向传播时传入`net.mul`的梯度，而不是传入 `forward_hook_fn` 函数中，新增的 `Add` 算子的梯度。这里的 `grad_output` 是梯度反向传播时 `net.mul` 反向输出的梯度，而不是 `forward_pre_hook_fn` 函数中新增 `Add` 算子的反向输出梯度。 `register_forward_pre_hook` 函数和 `register_forward_hook` 函数是在Cell对象执行前后起作用，不会影响Cell对象上反向Hook函数的梯度捕获范围。\n",
@@ -1086,7 +1048,6 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "342c346e",
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-03-02T09:14:55.896896Z",