diff --git a/docs/apis/datasets.md b/docs/apis/datasets.md
index ae3595be7ece185ce1992d0e5a0c75e2977ef362..3494aaa8a66840cecc16a79454b22bd252ab117b 100644
--- a/docs/apis/datasets.md
+++ b/docs/apis/datasets.md
@@ -7,7 +7,7 @@ paddlex.datasets.ImageNet(data_dir, file_list, label_list, transforms=None, num_
 ```
 读取ImageNet格式的分类数据集，并对样本进行相应的处理。ImageNet数据集格式的介绍可查看文档:[数据集格式说明](../data/format/index.html)  
 
-示例：[代码文件](https://github.com/PaddlePaddle/PaddleX/blob/develop/tutorials/train/classification/mobilenetv2.py#L25)
+示例：[代码文件](https://github.com/PaddlePaddle/PaddleX/blob/develop/tutorials/train/image_classification/mobilenetv2.py)
 
 > **参数**
 
@@ -20,15 +20,15 @@ paddlex.datasets.ImageNet(data_dir, file_list, label_list, transforms=None, num_
 > > * **parallel_method** (str): 数据集中样本在预处理过程中并行处理的方式，支持'thread'线程和'process'进程两种方式。默认为'process'（Windows和Mac下会强制使用thread，该参数无效）。  
 > > * **shuffle** (bool): 是否需要对数据集中样本打乱顺序。默认为False。  
 
-## paddlex.datasets.PascalVOC
+## paddlex.datasets.VOCDetection
 > **用于目标检测模型**  
 ```
-paddlex.datasets.PascalVOC(data_dir, file_list, label_list, transforms=None, num_workers=‘auto’, buffer_size=100, parallel_method='thread', shuffle=False)
+paddlex.datasets.VOCDetection(data_dir, file_list, label_list, transforms=None, num_workers=‘auto’, buffer_size=100, parallel_method='thread', shuffle=False)
 ```
 
 > 读取PascalVOC格式的检测数据集，并对样本进行相应的处理。PascalVOC数据集格式的介绍可查看文档:[数据集格式说明](../data/format/index.html)  
 
-> 示例：[代码文件](https://github.com/PaddlePaddle/PaddleX/blob/develop/tutorials/train/detection/yolov3_darknet53.py#L29)
+> 示例：[代码文件](https://github.com/PaddlePaddle/PaddleX/blob/develop/tutorials/train/object_detection/yolov3_darknet53.py)
 
 > **参数**
 
@@ -41,15 +41,15 @@ paddlex.datasets.PascalVOC(data_dir, file_list, label_list, transforms=None, num
 > > * **parallel_method** (str): 数据集中样本在预处理过程中并行处理的方式，支持'thread'线程和'process'进程两种方式。默认为'process'（Windows和Mac下会强制使用thread，该参数无效）。  
 > > * **shuffle** (bool): 是否需要对数据集中样本打乱顺序。默认为False。  
 
-## paddlex.datasets.MSCOCO
+## paddlex.datasets.CocoDetection
 > **用于实例分割/目标检测模型**  
 ```
-paddlex.datasets.MSCOCO(data_dir, ann_file, transforms=None, num_workers='auto', buffer_size=100, parallel_method='thread', shuffle=False)
+paddlex.datasets.CocoDetection(data_dir, ann_file, transforms=None, num_workers='auto', buffer_size=100, parallel_method='thread', shuffle=False)
 ```
 
 > 读取MSCOCO格式的检测数据集，并对样本进行相应的处理，该格式的数据集同样可以应用到实例分割模型的训练中。MSCOCO数据集格式的介绍可查看文档:[数据集格式说明](../data/format/index.html)  
 
-> 示例：[代码文件](https://github.com/PaddlePaddle/PaddleX/blob/develop/tutorials/train/detection/mask_rcnn_r50_fpn.py#L27)
+> 示例：[代码文件](https://github.com/PaddlePaddle/PaddleX/blob/develop/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py)
 
 > **参数**
 
@@ -69,7 +69,7 @@ paddlex.datasets.SegDataset(data_dir, file_list, label_list, transforms=None, nu
 
 > 读取语义分割任务数据集，并对样本进行相应的处理。语义分割任务数据集格式的介绍可查看文档:[数据集格式说明](../data/format/index.html)  
 
-> 示例：[代码文件](https://github.com/PaddlePaddle/PaddleX/blob/develop/tutorials/train/segmentation/unet.py#L27)
+> 示例：[代码文件](https://github.com/PaddlePaddle/PaddleX/blob/develop/tutorials/train/semantic_segmentation/unet.py)
 
 > **参数**
 
diff --git a/docs/quick_start.md b/docs/quick_start.md
index 760b15bb8cdc3c292d86c7a6d87e5e4b0b8676a1..a91df68373dd1f29faba7d184f93624e24a429db 100644
--- a/docs/quick_start.md
+++ b/docs/quick_start.md
@@ -1,6 +1,8 @@
 # 10分钟快速上手使用
 
-本文档在一个小数据集上展示了如何通过PaddleX进行训练，您可以阅读PaddleX的**使用教程**来了解更多模型任务的训练使用方式。本示例同步在AIStudio上，可直接[在线体验模型训练](https://aistudio.baidu.com/aistudio/projectdetail/439860)
+本文档在一个小数据集上展示了如何通过PaddleX进行训练。本示例同步在AIStudio上，可直接[在线体验模型训练](https://aistudio.baidu.com/aistudio/projectdetail/450220)。  
+
+本示例代码源于Github [tutorials/train/classification/mobilenetv3_small_ssld.py](https://github.com/PaddlePaddle/PaddleX/blob/develop/tutorials/train/image_classification/mobilenetv3_small_ssld.py)，用户可自行下载至本地运行。  
 
 PaddleX中的所有模型训练跟随以下3个步骤，即可快速完成训练代码开发！
 
@@ -35,7 +37,7 @@ tar xzvf vegetables_cls.tar.gz
 <a name="定义训练验证图像处理流程transforms"></a>
 **3. 定义训练/验证图像处理流程transforms**  
 
-由于训练时数据增强操作的加入，因此模型在训练和验证过程中，数据处理流程需要分别进行定义。如下所示，代码在`train_transforms`中加入了[RandomCrop](apis/transforms/cls_transforms.html#RandomCrop)和[RandomHorizontalFlip](apis/transforms/cls_transforms.html#RandomHorizontalFlip)两种数据增强方式, 更多方法可以参考[数据增强文档](apis/transforms/augment.md)。
+由于训练时数据增强操作的加入，因此模型在训练和验证过程中，数据处理流程需要分别进行定义。如下所示，代码在`train_transforms`中加入了[RandomCrop](apis/transforms/cls_transforms.html#randomcrop)和[RandomHorizontalFlip](apis/transforms/cls_transforms.html#randomhorizontalflip)两种数据增强方式, 更多方法可以参考[数据增强文档](apis/transforms/augment.md)。
 ```
 from paddlex.cls import transforms
 train_transforms = transforms.Compose([
@@ -54,7 +56,7 @@ eval_transforms = transforms.Compose([
 **4. 定义`dataset`加载图像分类数据集**  
 
 定义数据集，`pdx.datasets.ImageNet`表示读取ImageNet格式的分类数据集
-- [paddlex.datasets.ImageNet接口说明](apis/datasets/classification.md)
+- [paddlex.datasets.ImageNet接口说明](apis/datasets.md)
 - [ImageNet数据格式说明](data/format/classification.md)
 
 ```
@@ -118,7 +120,7 @@ Predict Result: Predict Result: [{'score': 0.9999393, 'category': 'bocai', 'cate
 
 <a name="更多使用教程"></a>
 **更多使用教程**
-- 1.[目标检测模型训练](tutorials/train/detection.md)
-- 2.[语义分割模型训练](tutorials/train/segmentation.md)
-- 3.[实例分割模型训练](tutorials/train/instance_segmentation.md)
-- 4.[模型太大，想要更小的模型，试试模型裁剪吧!](tutorials/compress/classification.md)
+- 1.[目标检测模型训练](train/object_detection.md)
+- 2.[语义分割模型训练](train/semantic_segmentation.md)
+- 3.[实例分割模型训练](train/instance_segmentation.md)
+- 4.[模型太大，想要更小的模型，试试模型裁剪吧!](https://github.com/PaddlePaddle/PaddleX/tree/develop/tutorials/compress)
diff --git a/tutorials/train/image_classification/alexnet.py b/tutorials/train/image_classification/alexnet.py
index b78f45bbc0f6889452ad0953062b78daca428aa9..bec066962abd8955f6021c8d578e6543eefa0a70 100644
--- a/tutorials/train/image_classification/alexnet.py
+++ b/tutorials/train/image_classification/alexnet.py
@@ -1,3 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
+import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.cls import transforms
 import paddlex as pdx
 
@@ -6,6 +11,7 @@ veg_dataset = 'https://bj.bcebos.com/paddlex/datasets/vegetables_cls.tar.gz'
 pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/cls_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomCrop(crop_size=224), 
     transforms.RandomHorizontalFlip(),
@@ -18,6 +24,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-imagenet
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -33,11 +40,14 @@ eval_dataset = pdx.datasets.ImageNet(
 # 初始化模型，并进行训练
 # 可使用VisualDL查看训练指标
 # VisualDL启动方式: visualdl --logdir output/mobilenetv2/vdl_log --port 8001
-# 浏览器打开 https://0.0.0.0:8001即可
+# 浏览器打开 https://0.0.0.0:8001或https://localhost:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 model = pdx.cls.AlexNet(num_classes=len(train_dataset.labels))
 # AlexNet需要指定确定的input_shape
 model.fixed_input_shape = [224, 224]
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/classification.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,
diff --git a/tutorials/train/image_classification/mobilenetv2.py b/tutorials/train/image_classification/mobilenetv2.py
index 5edbf587a2831b1c0118526fe28f6add32df4be8..7533aab7bc0fc2498d17fd1bd554f595253c05b8 100644
--- a/tutorials/train/image_classification/mobilenetv2.py
+++ b/tutorials/train/image_classification/mobilenetv2.py
@@ -1,4 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.cls import transforms
 import paddlex as pdx
 
@@ -7,6 +11,7 @@ veg_dataset = 'https://bj.bcebos.com/paddlex/datasets/vegetables_cls.tar.gz'
 pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/cls_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomCrop(crop_size=224), 
     transforms.RandomHorizontalFlip(),
@@ -19,6 +24,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-imagenet
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -37,6 +43,9 @@ eval_dataset = pdx.datasets.ImageNet(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 model = pdx.cls.MobileNetV2(num_classes=len(train_dataset.labels))
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/classification.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,
diff --git a/tutorials/train/image_classification/mobilenetv3_small_ssld.py b/tutorials/train/image_classification/mobilenetv3_small_ssld.py
index 6d52775f33987507878ef77b2485ebe3ce2f6881..8f13312d835b582ec673635f11b4c3fff1c95dda 100644
--- a/tutorials/train/image_classification/mobilenetv3_small_ssld.py
+++ b/tutorials/train/image_classification/mobilenetv3_small_ssld.py
@@ -1,4 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.cls import transforms
 import paddlex as pdx
 
@@ -7,6 +11,7 @@ veg_dataset = 'https://bj.bcebos.com/paddlex/datasets/vegetables_cls.tar.gz'
 pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/cls_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomCrop(crop_size=224), 
     transforms.RandomHorizontalFlip(),
@@ -19,6 +24,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-imagenet
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -37,6 +43,9 @@ eval_dataset = pdx.datasets.ImageNet(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 model = pdx.cls.MobileNetV3_small_ssld(num_classes=len(train_dataset.labels))
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-imagenet
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,
diff --git a/tutorials/train/image_classification/resnet50_vd_ssld.py b/tutorials/train/image_classification/resnet50_vd_ssld.py
index ca94f7f19055b67fbfcd0cb29b34cd55b69a90e6..b72ebc52d74f6a0023b830c33f5afc31fb4b7196 100644
--- a/tutorials/train/image_classification/resnet50_vd_ssld.py
+++ b/tutorials/train/image_classification/resnet50_vd_ssld.py
@@ -1,4 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.cls import transforms
 import paddlex as pdx
 
@@ -7,6 +11,7 @@ veg_dataset = 'https://bj.bcebos.com/paddlex/datasets/vegetables_cls.tar.gz'
 pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/cls_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomCrop(crop_size=224), 
     transforms.RandomHorizontalFlip(),
@@ -19,6 +24,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-imagenet
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -37,6 +43,9 @@ eval_dataset = pdx.datasets.ImageNet(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 model = pdx.cls.ResNet50_vd_ssld(num_classes=len(train_dataset.labels))
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/classification.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,
diff --git a/tutorials/train/image_classification/shufflenetv2.py b/tutorials/train/image_classification/shufflenetv2.py
index 29272df3f13bb28524c942c11f6714e459427345..cdfa1889ba926f4728277929b76536ddaea75c04 100644
--- a/tutorials/train/image_classification/shufflenetv2.py
+++ b/tutorials/train/image_classification/shufflenetv2.py
@@ -1,4 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.cls import transforms
 import paddlex as pdx
 
@@ -7,6 +11,7 @@ veg_dataset = 'https://bj.bcebos.com/paddlex/datasets/vegetables_cls.tar.gz'
 pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/cls_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomCrop(crop_size=224), 
     transforms.RandomHorizontalFlip(),
@@ -19,6 +24,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-imagenet
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -37,6 +43,9 @@ eval_dataset = pdx.datasets.ImageNet(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 model = pdx.cls.ShuffleNetV2(num_classes=len(train_dataset.labels))
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/classification.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,
diff --git a/tutorials/train/instance_segmentation/mask_rcnn_hrnet_fpn.py b/tutorials/train/instance_segmentation/mask_rcnn_hrnet_fpn.py
index 7f8e1eb35ddda3e7f27916e4756e8103f62ee88b..f78446546cd793f96cb074f0a1701a718f7d84b4 100644
--- a/tutorials/train/instance_segmentation/mask_rcnn_hrnet_fpn.py
+++ b/tutorials/train/instance_segmentation/mask_rcnn_hrnet_fpn.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 from paddlex.det import transforms
@@ -10,6 +11,7 @@ xiaoduxiong_dataset = 'https://bj.bcebos.com/paddlex/datasets/xiaoduxiong_ins_de
 pdx.utils.download_and_decompress(xiaoduxiong_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.Normalize(),
@@ -24,6 +26,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-cocodetection
 train_dataset = pdx.datasets.CocoDetection(
     data_dir='xiaoduxiong_ins_det/JPEGImages',
     ann_file='xiaoduxiong_ins_det/train.json',
@@ -41,7 +44,12 @@ eval_dataset = pdx.datasets.CocoDetection(
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 # num_classes 需要设置为包含背景类的类别数，即: 目标类别数量 + 1
 num_classes = len(train_dataset.labels) + 1
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/instance_segmentation.html#maskrcnn
 model = pdx.det.MaskRCNN(num_classes=num_classes, backbone='HRNet_W18')
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/instance_segmentation.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=12,
     train_dataset=train_dataset,
diff --git a/tutorials/train/instance_segmentation/mask_rcnn_r18_fpn.py b/tutorials/train/instance_segmentation/mask_rcnn_r18_fpn.py
index a4105159e633e67f63fcd5ee0354599cf994263d..dc16b66b3941e0d639fd45dbaa691ec51bc5cfbd 100644
--- a/tutorials/train/instance_segmentation/mask_rcnn_r18_fpn.py
+++ b/tutorials/train/instance_segmentation/mask_rcnn_r18_fpn.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 from paddlex.det import transforms
@@ -10,6 +11,7 @@ xiaoduxiong_dataset = 'https://bj.bcebos.com/paddlex/datasets/xiaoduxiong_ins_de
 pdx.utils.download_and_decompress(xiaoduxiong_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.Normalize(),
@@ -24,6 +26,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-cocodetection
 train_dataset = pdx.datasets.CocoDetection(
     data_dir='xiaoduxiong_ins_det/JPEGImages',
     ann_file='xiaoduxiong_ins_det/train.json',
@@ -41,7 +44,12 @@ eval_dataset = pdx.datasets.CocoDetection(
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 # num_classes 需要设置为包含背景类的类别数，即: 目标类别数量 + 1
 num_classes = len(train_dataset.labels) + 1
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/instance_segmentation.html#maskrcnn
 model = pdx.det.MaskRCNN(num_classes=num_classes, backbone='ResNet18')
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/instance_segmentation.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=12,
     train_dataset=train_dataset,
diff --git a/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py b/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py
index 817499815979cbadfe9c3a1b80bc94dc00cb53a0..e87c88e5d8feba36df1bd65430058a4f413ba73c 100644
--- a/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py
+++ b/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 from paddlex.det import transforms
@@ -10,6 +11,7 @@ xiaoduxiong_dataset = 'https://bj.bcebos.com/paddlex/datasets/xiaoduxiong_ins_de
 pdx.utils.download_and_decompress(xiaoduxiong_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.Normalize(),
@@ -24,6 +26,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-cocodetection
 train_dataset = pdx.datasets.CocoDetection(
     data_dir='xiaoduxiong_ins_det/JPEGImages',
     ann_file='xiaoduxiong_ins_det/train.json',
@@ -41,7 +44,12 @@ eval_dataset = pdx.datasets.CocoDetection(
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 # num_classes 需要设置为包含背景类的类别数，即: 目标类别数量 + 1
 num_classes = len(train_dataset.labels) + 1
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/instance_segmentation.html#maskrcnn
 model = pdx.det.MaskRCNN(num_classes=num_classes, backbone='ResNet50')
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/instance_segmentation.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=12,
     train_dataset=train_dataset,
diff --git a/tutorials/train/object_detection/faster_rcnn_hrnet_fpn.py b/tutorials/train/object_detection/faster_rcnn_hrnet_fpn.py
index 3d1650f3768a6b0207011aa215596b5c46c8852d..e46d3ae56b57aa90cdcecdcce3ad3ee1ad67d098 100644
--- a/tutorials/train/object_detection/faster_rcnn_hrnet_fpn.py
+++ b/tutorials/train/object_detection/faster_rcnn_hrnet_fpn.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 from paddlex.det import transforms
@@ -10,6 +11,7 @@ insect_dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.Normalize(),
@@ -24,6 +26,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-vocdetection
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -43,7 +46,12 @@ eval_dataset = pdx.datasets.VOCDetection(
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 # num_classes 需要设置为包含背景类的类别数，即: 目标类别数量 + 1
 num_classes = len(train_dataset.labels) + 1
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#paddlex-det-fasterrcnn
 model = pdx.det.FasterRCNN(num_classes=num_classes, backbone='HRNet_W18')
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#id1
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=12,
     train_dataset=train_dataset,
diff --git a/tutorials/train/object_detection/faster_rcnn_r18_fpn.py b/tutorials/train/object_detection/faster_rcnn_r18_fpn.py
index cd8928ad48dae42e134607cf84332fa51467b464..0ae82d3ec8166159649f09d33b3f2ad094c3c6ee 100644
--- a/tutorials/train/object_detection/faster_rcnn_r18_fpn.py
+++ b/tutorials/train/object_detection/faster_rcnn_r18_fpn.py
@@ -1,4 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.det import transforms
 import paddlex as pdx
 
@@ -7,6 +11,7 @@ insect_dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.Normalize(),
@@ -19,7 +24,9 @@ eval_transforms = transforms.Compose([
     transforms.ResizeByShort(short_size=800, max_size=1333),
     transforms.Padding(coarsest_stride=32),
 ])
+
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-vocdetection
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -39,7 +46,12 @@ eval_dataset = pdx.datasets.VOCDetection(
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 # num_classes 需要设置为包含背景类的类别数，即: 目标类别数量 + 1
 num_classes = len(train_dataset.labels) + 1
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#paddlex-det-fasterrcnn
 model = pdx.det.FasterRCNN(num_classes=num_classes, backbone='ResNet18')
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#id1
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=12,
     train_dataset=train_dataset,
diff --git a/tutorials/train/object_detection/faster_rcnn_r50_fpn.py b/tutorials/train/object_detection/faster_rcnn_r50_fpn.py
index 350c40fd12651e3dfe155b0b95cc702e741e1de4..0f26bfa9a5c571419c5b4b2f6e553f383d011399 100644
--- a/tutorials/train/object_detection/faster_rcnn_r50_fpn.py
+++ b/tutorials/train/object_detection/faster_rcnn_r50_fpn.py
@@ -1,4 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.det import transforms
 import paddlex as pdx
 
@@ -7,6 +11,7 @@ insect_dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.Normalize(),
@@ -19,7 +24,9 @@ eval_transforms = transforms.Compose([
     transforms.ResizeByShort(short_size=800, max_size=1333),
     transforms.Padding(coarsest_stride=32),
 ])
+
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-vocdetection
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -39,7 +46,12 @@ eval_dataset = pdx.datasets.VOCDetection(
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 # num_classes 需要设置为包含背景类的类别数，即: 目标类别数量 + 1
 num_classes = len(train_dataset.labels) + 1
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#paddlex-det-fasterrcnn
 model = pdx.det.FasterRCNN(num_classes=num_classes, backbone='ResNet50')
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#id1
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=12,
     train_dataset=train_dataset,
diff --git a/tutorials/train/object_detection/yolov3_darknet53.py b/tutorials/train/object_detection/yolov3_darknet53.py
index a15e5cbcfd037e75eadc65bfb42320f8c13f8e54..085be4bf7ffa3f9eca31f3b2807d83f00544b455 100644
--- a/tutorials/train/object_detection/yolov3_darknet53.py
+++ b/tutorials/train/object_detection/yolov3_darknet53.py
@@ -1,4 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.det import transforms
 import paddlex as pdx
 
@@ -7,6 +11,7 @@ insect_dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
 train_transforms = transforms.Compose([
     transforms.MixupImage(mixup_epoch=250), 
     transforms.RandomDistort(),
@@ -23,6 +28,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-vocdetection
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -41,7 +47,12 @@ eval_dataset = pdx.datasets.VOCDetection(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 num_classes = len(train_dataset.labels)
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#paddlex-det-yolov3
 model = pdx.det.YOLOv3(num_classes=num_classes, backbone='DarkNet53')
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=270,
     train_dataset=train_dataset,
diff --git a/tutorials/train/object_detection/yolov3_mobilenetv1.py b/tutorials/train/object_detection/yolov3_mobilenetv1.py
index 9b621851bcc5f0f058129c5ad9a666503cbda667..bfc2bea0716c1bc0b7c27cb8014d6215eed8306c 100644
--- a/tutorials/train/object_detection/yolov3_mobilenetv1.py
+++ b/tutorials/train/object_detection/yolov3_mobilenetv1.py
@@ -1,4 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.det import transforms
 import paddlex as pdx
 
@@ -7,6 +11,7 @@ insect_dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
 train_transforms = transforms.Compose([
     transforms.MixupImage(mixup_epoch=250),
     transforms.RandomDistort(),
@@ -23,6 +28,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-vocdetection
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -41,7 +47,12 @@ eval_dataset = pdx.datasets.VOCDetection(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 num_classes = len(train_dataset.labels)
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#paddlex-det-yolov3
 model = pdx.det.YOLOv3(num_classes=num_classes, backbone='MobileNetV1')
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=270,
     train_dataset=train_dataset,
diff --git a/tutorials/train/object_detection/yolov3_mobilenetv3.py b/tutorials/train/object_detection/yolov3_mobilenetv3.py
index 4eb06099e7320655310b77c7166a022b363e4bbe..85570781851665a9ab28a718ecf85a0b078508a3 100644
--- a/tutorials/train/object_detection/yolov3_mobilenetv3.py
+++ b/tutorials/train/object_detection/yolov3_mobilenetv3.py
@@ -1,4 +1,8 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
 from paddlex.det import transforms
 import paddlex as pdx
 
@@ -7,6 +11,7 @@ insect_dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
 train_transforms = transforms.Compose([
     transforms.MixupImage(mixup_epoch=250), 
     transforms.RandomDistort(),
@@ -23,6 +28,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-vocdetection
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -41,7 +47,12 @@ eval_dataset = pdx.datasets.VOCDetection(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 num_classes = len(train_dataset.labels)
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#paddlex-det-yolov3
 model = pdx.det.YOLOv3(num_classes=num_classes, backbone='MobileNetV3_large')
+
+# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=270,
     train_dataset=train_dataset,
diff --git a/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2.py b/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2.py
index 28931a67da2df3e8c6a3975aa7eb9de542ba6e40..fc5b738a0641604f28fd83a47b795313c13bcd39 100644
--- a/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2.py
+++ b/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 import paddlex as pdx
@@ -10,6 +11,7 @@ optic_dataset = 'https://bj.bcebos.com/paddlex/datasets/optic_disc_seg.tar.gz'
 pdx.utils.download_and_decompress(optic_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/seg_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.ResizeRangeScaling(),
@@ -24,6 +26,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-segdataset
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -42,7 +45,13 @@ eval_dataset = pdx.datasets.SegDataset(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 num_classes = len(train_dataset.labels)
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#paddlex-seg-deeplabv3p
 model = pdx.seg.DeepLabv3p(num_classes=num_classes, backbone='MobileNetV2_x1.0')
+
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=40,
     train_dataset=train_dataset,
diff --git a/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2_x0.25.py b/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2_x0.25.py
index 04553e3b07e72a9cb7939bdd00e1b8321fbad04c..51bdb3ded85453fd48cce0b4845742421b949f06 100644
--- a/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2_x0.25.py
+++ b/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2_x0.25.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 import paddlex as pdx
@@ -10,6 +11,7 @@ optic_dataset = 'https://bj.bcebos.com/paddlex/datasets/optic_disc_seg.tar.gz'
 pdx.utils.download_and_decompress(optic_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/seg_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.ResizeRangeScaling(),
@@ -24,6 +26,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-segdataset
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -42,7 +45,12 @@ eval_dataset = pdx.datasets.SegDataset(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 num_classes = len(train_dataset.labels)
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#paddlex-seg-deeplabv3p
 model = pdx.seg.DeepLabv3p(num_classes=num_classes, backbone='MobileNetV2_x0.25')
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=40,
     train_dataset=train_dataset,
diff --git a/tutorials/train/semantic_segmentation/deeplabv3p_xception65.py b/tutorials/train/semantic_segmentation/deeplabv3p_xception65.py
index 70167ff05d280d6ab96c42e080ca132ac17e39ef..4101c98f7d0e4f61dd0709d608e052615560fffc 100644
--- a/tutorials/train/semantic_segmentation/deeplabv3p_xception65.py
+++ b/tutorials/train/semantic_segmentation/deeplabv3p_xception65.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 import paddlex as pdx
@@ -10,6 +11,7 @@ optic_dataset = 'https://bj.bcebos.com/paddlex/datasets/optic_disc_seg.tar.gz'
 pdx.utils.download_and_decompress(optic_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/seg_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.ResizeRangeScaling(),
@@ -24,6 +26,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-segdataset
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -42,7 +45,12 @@ eval_dataset = pdx.datasets.SegDataset(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 num_classes = len(train_dataset.labels)
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#paddlex-seg-deeplabv3p
 model = pdx.seg.DeepLabv3p(num_classes=num_classes, backbone='Xception65')
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=40,
     train_dataset=train_dataset,
diff --git a/tutorials/train/semantic_segmentation/fast_scnn.py b/tutorials/train/semantic_segmentation/fast_scnn.py
index af041cacb95e49170be3af61078b8ea3399145fb..38fa51a7ab6242795dfd16c322d004b733e62a74 100644
--- a/tutorials/train/semantic_segmentation/fast_scnn.py
+++ b/tutorials/train/semantic_segmentation/fast_scnn.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 import paddlex as pdx
@@ -10,7 +11,7 @@ optic_dataset = 'https://bj.bcebos.com/paddlex/datasets/optic_disc_seg.tar.gz'
 pdx.utils.download_and_decompress(optic_dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明: https://paddlex.readthedocs.io/zh_CN/latest/apis/transforms/seg_transforms.html#composedsegtransforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/seg_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.ResizeRangeScaling(),
@@ -25,7 +26,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明: https://paddlex.readthedocs.io/zh_CN/latest/apis/datasets/semantic_segmentation.html#segdataset
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-segdataset
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -44,9 +45,13 @@ eval_dataset = pdx.datasets.SegDataset(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 
-# https://paddlex.readthedocs.io/zh_CN/latest/apis/models/semantic_segmentation.html#fastscnn
 num_classes = len(train_dataset.labels)
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#paddlex-seg-fastscnn
 model = pdx.seg.FastSCNN(num_classes=num_classes)
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=20,
     train_dataset=train_dataset,
diff --git a/tutorials/train/semantic_segmentation/hrnet.py b/tutorials/train/semantic_segmentation/hrnet.py
index 330a107714ee5fbe7e6e3a021b5afa5737fdd779..9526e99b352eee73ca3ee4d308ec9fe36250f7d1 100644
--- a/tutorials/train/semantic_segmentation/hrnet.py
+++ b/tutorials/train/semantic_segmentation/hrnet.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 import paddlex as pdx
@@ -10,6 +11,7 @@ optic_dataset = 'https://bj.bcebos.com/paddlex/datasets/optic_disc_seg.tar.gz'
 pdx.utils.download_and_decompress(optic_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/seg_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.ResizeRangeScaling(),
@@ -24,6 +26,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-segdataset
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -42,7 +45,12 @@ eval_dataset = pdx.datasets.SegDataset(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 num_classes = len(train_dataset.labels)
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#paddlex-seg-hrnet
 model = pdx.seg.HRNet(num_classes=num_classes)
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=20,
     train_dataset=train_dataset,
diff --git a/tutorials/train/semantic_segmentation/unet.py b/tutorials/train/semantic_segmentation/unet.py
index 46e93b8c217d11bfa9aa7c003ea28fd1041092ba..c0ba72666d4b386667cc747077916eaf251675a9 100644
--- a/tutorials/train/semantic_segmentation/unet.py
+++ b/tutorials/train/semantic_segmentation/unet.py
@@ -1,5 +1,6 @@
+# 环境变量配置，用于控制是否使用GPU
+# 说明文档：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html#gpu
 import os
-# 选择使用0号卡
 os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
 import paddlex as pdx
@@ -10,6 +11,7 @@ optic_dataset = 'https://bj.bcebos.com/paddlex/datasets/optic_disc_seg.tar.gz'
 pdx.utils.download_and_decompress(optic_dataset, path='./')
 
 # 定义训练和验证时的transforms
+# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/seg_transforms.html
 train_transforms = transforms.Compose([
     transforms.RandomHorizontalFlip(), 
     transforms.ResizeRangeScaling(),
@@ -23,6 +25,7 @@ eval_transforms = transforms.Compose([
 ])
 
 # 定义训练和验证所用的数据集
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-segdataset
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -41,7 +44,12 @@ eval_dataset = pdx.datasets.SegDataset(
 # 浏览器打开 https://0.0.0.0:8001即可
 # 其中0.0.0.0为本机访问，如为远程服务, 改成相应机器IP
 num_classes = len(train_dataset.labels)
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#paddlex-seg-deeplabv3p
 model = pdx.seg.UNet(num_classes=num_classes)
+
+# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/models/semantic_segmentation.html#train
+# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
 model.train(
     num_epochs=20,
     train_dataset=train_dataset,