diff --git a/tutorials/notebook/mindspore_save_model.ipynb b/tutorials/notebook/mindspore_save_model.ipynb
index d7467d4e86dde7ad5743255777a83c2e3a670fab..ce40c37156d5f59b11b8ba1918c04ad3045f7199 100644
--- a/tutorials/notebook/mindspore_save_model.ipynb
+++ b/tutorials/notebook/mindspore_save_model.ipynb
@@ -81,16 +81,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "--2020-11-30 16:14:55--  https://obs.dualstack.cn-north-4.myhuaweicloud.com/mindspore-website/notebook/datasets/MNIST_Data.zip\n",
+      "--2020-11-26 15:50:38--  https://obs.dualstack.cn-north-4.myhuaweicloud.com/mindspore-website/notebook/datasets/MNIST_Data.zip\n",
       "Resolving proxy-notebook.modelarts-dev-proxy.com (proxy-notebook.modelarts-dev-proxy.com)... 192.168.0.172\n",
       "Connecting to proxy-notebook.modelarts-dev-proxy.com (proxy-notebook.modelarts-dev-proxy.com)|192.168.0.172|:8083... connected.\n",
       "Proxy request sent, awaiting response... 200 OK\n",
       "Length: 10754903 (10M) [application/zip]\n",
       "Saving to: ‘MNIST_Data.zip’\n",
       "\n",
-      "MNIST_Data.zip      100%[===================>]  10.26M  64.9MB/s    in 0.2s    \n",
+      "MNIST_Data.zip      100%[===================>]  10.26M  65.1MB/s    in 0.2s    \n",
       "\n",
-      "2020-11-30 16:14:56 (64.9 MB/s) - ‘MNIST_Data.zip’ saved [10754903/10754903]\n",
+      "2020-11-26 15:50:39 (65.1 MB/s) - ‘MNIST_Data.zip’ saved [10754903/10754903]\n",
       "\n",
       "Archive:  MNIST_Data.zip\n",
       "   creating: MNIST_Data/test/\n",
@@ -112,9 +112,11 @@
     }
    ],
    "source": [
-    "!wget -N https://obs.dualstack.cn-north-4.myhuaweicloud.com/mindspore-website/notebook/datasets/MNIST_Data.zip\n",
-    "!unzip -o MNIST_Data.zip -d ./datasets\n",
-    "!tree ./datasets/MNIST_Data/"
+    "! wget https://obs.dualstack.cn-north-4.myhuaweicloud.com/mindspore-website/notebook/datasets/MNIST_Data.zip\n",
+    "! unzip MNIST_Data.zip\n",
+    "! mkdir -p ./datasets/\n",
+    "! mv -f ./MNIST_Data/ ./datasets/\n",
+    "! tree ./datasets/MNIST_Data"
    ]
   },
   {
@@ -300,6 +302,13 @@
     "\n",
     "context.set_context(mode=context.GRAPH_MODE, device_target=\"CPU\")\n",
     "\n",
+    "if os.name == \"nt\":\n",
+    "    # clean up old run files before in Windows\n",
+    "    os.system('del/f/s/q *.ckpt *.meta')\n",
+    "else:\n",
+    "    # clean up old run files before in Linux\n",
+    "    os.system('rm -f *.ckpt *.meta *.pb')\n",
+    "\n",
     "lr = 0.01\n",
     "momentum = 0.9 \n",
     "\n",
@@ -373,14 +382,10 @@
    "source": [
     "from mindspore.train.callback import ModelCheckpoint, CheckpointConfig\n",
     "\n",
-    "model_path = './models/ckpt/mindspore_save_model/'\n",
-    "# clean up old run files before in Linux\n",
-    "os.system('rm -f {}*.ckpt {}*.meta {}*.pb'.format(model_path, model_path, model_path))\n",
-    "\n",
     "# define config_ck for specifying the steps to save the checkpoint and the maximum file numbers\n",
     "config_ck = CheckpointConfig(save_checkpoint_steps=375, keep_checkpoint_max=10)\n",
     "# define ckpoint_cb for specifying the prefix of the file and the saving directory\n",
-    "ckpoint_cb = ModelCheckpoint(prefix='lenet', directory=model_path, config=config_ck)\n",
+    "ckpoint_cb = ModelCheckpoint(prefix='lenet', directory='./models/ckpt/save_model', config=config_ck)\n",
     "#load the training dataset\n",
     "ds_train = create_dataset(os.path.join(mnist_path, \"train\"), 32, repeat_size)\n",
     "print(\"========== The Training is Starting. ==========\")\n",
@@ -425,7 +430,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "./models/ckpt/mindspore_save_model\n",
+      "./models/ckpt/save_model\n",
       "├── lenet-1_1125.ckpt\n",
       "├── lenet-1_1500.ckpt\n",
       "├── lenet-1_1875.ckpt\n",
@@ -438,7 +443,7 @@
     }
    ],
    "source": [
-    "! tree ./models/ckpt/mindspore_save_model"
+    "! tree ./models/ckpt/save_model"
    ]
   },
   {
@@ -481,14 +486,10 @@
    ],
    "source": [
     "from mindspore.train.callback import ModelCheckpoint, CheckpointConfig\n",
-    "import os\n",
-    "\n",
-    "# clean up old run files before in Linux\n",
-    "os.system('rm -f {}lenet_2*.ckpt'.format(model_path))\n",
     "\n",
     "config_ck = CheckpointConfig(save_checkpoint_steps=375, keep_checkpoint_max=10)\n",
     "# Specify that here the script is executed for the second time\n",
-    "ckpoint_cb = ModelCheckpoint(prefix='lenet_2', directory='./models/ckpt/mindspore_save_model', config=config_ck)\n",
+    "ckpoint_cb = ModelCheckpoint(prefix='lenet_2', directory='./models/ckpt/save_model', config=config_ck)\n",
     "ds_train = create_dataset(os.path.join(mnist_path, \"train\"), 32, repeat_size)\n",
     "print(\"========== The Training is Starting. ==========\")\n",
     "model.train(epoch_size, ds_train, callbacks=ckpoint_cb,dataset_sink_mode=False)\n",
@@ -499,7 +500,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "生成的CheckPoint文件（以`lenet-2`为前缀的`.ckpt`文件）如下："
+    "生成的CheckPoint文件如下："
    ]
   },
   {
@@ -511,7 +512,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "./models/ckpt/mindspore_save_model\n",
+      "./models/ckpt/save_model\n",
       "├── lenet-1_1125.ckpt\n",
       "├── lenet-1_1500.ckpt\n",
       "├── lenet-1_1875.ckpt\n",
@@ -530,7 +531,7 @@
     }
    ],
    "source": [
-    "! tree ./models/ckpt/mindspore_save_model"
+    "! tree ./models/ckpt/save_model"
    ]
   },
   {
@@ -587,15 +588,13 @@
    ],
    "source": [
     "from mindspore.train.callback import ModelCheckpoint, CheckpointConfig\n",
-    "import os\n",
     "\n",
-    "os.system('rm -f {}lenet_3*.ckpt'.format(model_path))\n",
     "# define config_ck for specifying the seconds to save the checkpoint and the maximum file numbers\n",
-    "config_ck = CheckpointConfig(save_checkpoint_steps=None, save_checkpoint_seconds=10, keep_checkpoint_max=None, keep_checkpoint_per_n_minutes=1)\n",
+    "config_ck = CheckpointConfig(save_checkpoint_steps=None, save_checkpoint_seconds=30, keep_checkpoint_max=None, keep_checkpoint_per_n_minutes=1)\n",
     "# define ckpoint_cb for specifying the prefix of the file and the saving directory\n",
-    "ckpoint_cb = ModelCheckpoint(prefix='lenet_3', directory='./models/ckpt/mindspore_save_model', config=config_ck)\n",
+    "ckpoint_cb = ModelCheckpoint(prefix='lenet_3', directory='./models/ckpt/save_model', config=config_ck)\n",
     "#load the training dataset\n",
-    "epoch_size = 2\n",
+    "epoch_size = 10\n",
     "ds_train = create_dataset(os.path.join(mnist_path, \"train\"), 32, repeat_size)\n",
     "print(\"========== The Training is Starting. ==========\")\n",
     "model.train(epoch_size, ds_train, callbacks=ckpoint_cb,dataset_sink_mode=False)\n",
@@ -606,8 +605,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "这里`save_checkpoint_seconds`和`keep_checkpoint_per_n_minutes`这两个分别设置为10和1。<br>\n",
-    "意思是每10秒会保存一个CheckPoint文件，每隔1分钟会保留一个CheckPoint文件。假设训练持续了1分钟，那总共会生成7个CheckPoint文件，但是当训练结束后，实际上会看到4个CheckPoint文件（以`lenet-3`为前缀的`.ckpt`文件），即保存下来的3个文件和默认保存最后一个step的CheckPoint文件。"
+    "这里`save_checkpoint_seconds`和`keep_checkpoint_per_n_minutes`这两个分别设置为30和1。<br>\n",
+    "意思是每30秒会保存一个CheckPoint文件，每隔1分钟会保留一个CheckPoint文件。假设训练持续了3分钟，那总共会生成6个CheckPoint文件，但是当训练结束后，实际上会看到4个CheckPoint文件，即保存下来的3个文件和默认保存最后一个step的CheckPoint文件。"
    ]
   },
   {
@@ -626,7 +625,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "./models/ckpt/mindspore_save_model\n",
+      "./models/ckpt/save_model\n",
       "├── lenet-1_1125.ckpt\n",
       "├── lenet-1_1500.ckpt\n",
       "├── lenet-1_1875.ckpt\n",
@@ -638,19 +637,23 @@
       "├── lenet_2-1_375.ckpt\n",
       "├── lenet_2-1_750.ckpt\n",
       "├── lenet_2-graph.meta\n",
-      "├── lenet_3-1_1023.ckpt\n",
-      "├── lenet_3-2_1254.ckpt\n",
-      "├── lenet_3-2_1875.ckpt\n",
-      "├── lenet_3-2_194.ckpt\n",
+      "├── lenet_3-10_1875.ckpt\n",
+      "├── lenet_3-10_1.ckpt\n",
+      "├── lenet_3-2_452.ckpt\n",
+      "├── lenet_3-3_1029.ckpt\n",
+      "├── lenet_3-4_1581.ckpt\n",
+      "├── lenet_3-6_188.ckpt\n",
+      "├── lenet_3-7_758.ckpt\n",
+      "├── lenet_3-8_1331.ckpt\n",
       "├── lenet_3-graph.meta\n",
       "└── lenet-graph.meta\n",
       "\n",
-      "0 directories, 17 files\n"
+      "0 directories, 21 files\n"
      ]
     }
    ],
    "source": [
-    "! tree ./models/ckpt/mindspore_save_model"
+    "! tree ./models/ckpt/save_model"
    ]
   },
   {
@@ -680,13 +683,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from mindspore import export, load_checkpoint, load_param_into_net\n",
+    "from mindspore.train.serialization import export, load_checkpoint, load_param_into_net\n",
     "from mindspore import Tensor\n",
     "import numpy as np\n",
     "\n",
     "lenet = LeNet5()\n",
     "# return a parameter dict for model\n",
-    "param_dict = load_checkpoint(\"./models/ckpt/mindspore_save_model/lenet-1_1875.ckpt\")\n",
+    "param_dict = load_checkpoint(\"./models/ckpt/save_model/lenet-1_1875.ckpt\")\n",
     "# load the parameter into net\n",
     "load_param_into_net(lenet, param_dict)\n",
     "input = np.random.uniform(0.0, 1.0, size=[32, 1, 32, 32]).astype(np.float32)\n",
@@ -726,7 +729,7 @@
     "import numpy as np\n",
     "lenet = LeNet5()\n",
     "# return a parameter dict for model\n",
-    "param_dict = load_checkpoint(\"./models/ckpt/mindspore_save_model/lenet-1_1875.ckpt\")\n",
+    "param_dict = load_checkpoint(\"./models/ckpt/save_model/lenet-1_1875.ckpt\")\n",
     "# load the parameter into net\n",
     "load_param_into_net(lenet, param_dict)\n",
     "input = np.random.uniform(0.0, 1.0, size=[32, 1, 32, 32]).astype(np.float32)\n",
diff --git a/tutorials/training/source_en/advanced_use/custom_debugging_info.md b/tutorials/training/source_en/advanced_use/custom_debugging_info.md
index 30fa019a5fed8eed8cfb6bc87be39f5f8dc62980..8f01a9fc36db3f514bc2d0cb2f7f68e9136bbcc2 100644
--- a/tutorials/training/source_en/advanced_use/custom_debugging_info.md
+++ b/tutorials/training/source_en/advanced_use/custom_debugging_info.md
@@ -429,7 +429,7 @@ Sub modules of MindSpore grouped by source directory:
 | mindspore/ccsrc/pybind_api | COMMON |
 | mindspore/ccsrc/runtime/device | DEVICE |
 | mindspore/ccsrc/transform/graph_ir | GE_ADPT |
-| mindspore/ccsrc/transform/onnx | ONNX |
+| mindspore/ccsrc/transform/express_ir | EXPRESS |
 | mindspore/ccsrc/utils | UTILS |
 | mindspore/ccsrc/vm | VM |
 | mindspore/ccsrc | ME |
diff --git a/tutorials/training/source_zh_cn/advanced_use/custom_debugging_info.md b/tutorials/training/source_zh_cn/advanced_use/custom_debugging_info.md
index ff75859da4a09eaaf12017dfd318b20a4b6cd135..aac4e00000f236dbcb5881818b56cf3299b6bc8f 100644
--- a/tutorials/training/source_zh_cn/advanced_use/custom_debugging_info.md
+++ b/tutorials/training/source_zh_cn/advanced_use/custom_debugging_info.md
@@ -434,7 +434,7 @@ MindSpore子模块按照目录划分如下：
 | mindspore/ccsrc/pybind_api | COMMON |
 | mindspore/ccsrc/runtime/device | DEVICE |
 | mindspore/ccsrc/transform/graph_ir | GE_ADPT |
-| mindspore/ccsrc/transform/onnx | ONNX |
+| mindspore/ccsrc/transform/express_ir | EXPRESS |
 | mindspore/ccsrc/utils | UTILS |
 | mindspore/ccsrc/vm | VM |
 | mindspore/ccsrc | ME |