move dygraph in tutorials

tutorials/slim/prune/image_classification/mobilenetv2_prune.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -33,17 +33,17 @@ eval_dataset = pdx.datasets.ImageNet(
 model = pdx.load_model('output/mobilenet_v2/best_model')
 
 # Step 1/3: 分析模型各层参数在不同的剪裁比例下的敏感度
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md#analyze_sensitivity
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md#analyze_sensitivity
 model.analyze_sensitivity(
     dataset=eval_dataset, save_dir='output/mobilenet_v2/prune')
 
 # Step 2/3: 根据选择的FLOPs减小比例对模型进行剪裁
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md#prune
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md#prune
 model.prune(pruned_flops=.2)
 
 # Step 3/3: 对剪裁后的模型重新训练
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md#train
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md#train
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/slim/prune/image_classification/mobilenetv2_train.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -34,8 +34,8 @@ eval_dataset = pdx.datasets.ImageNet(
 num_classes = len(train_dataset.labels)
 model = pdx.cls.MobileNetV2(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/slim/prune/object_detection/yolov3_prune.py

@@ -6,7 +6,7 @@ dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.MixupImage(mixup_epoch=250), T.RandomDistort(),
     T.RandomExpand(im_padding_value=[123.675, 116.28, 103.53]), T.RandomCrop(),
@@ -23,7 +23,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -42,19 +42,19 @@ eval_dataset = pdx.datasets.VOCDetection(
 model = pdx.load_model('output/yolov3_darknet53/best_model')
 
 # Step 1/3: 分析模型各层参数在不同的剪裁比例下的敏感度
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md#analyze_sensitivity
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md#analyze_sensitivity
 model.analyze_sensitivity(
     dataset=eval_dataset,
     batch_size=1,
     save_dir='output/yolov3_darknet53/prune')
 
 # Step 2/3: 根据选择的FLOPs减小比例对模型进行剪裁
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md#prune
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md#prune
 model.prune(pruned_flops=.2)
 
 # Step 3/3: 对剪裁后的模型重新训练
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md#train
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md#train
 model.train(
     num_epochs=270,
     train_dataset=train_dataset,

tutorials/slim/prune/object_detection/yolov3_train.py

@@ -6,7 +6,7 @@ dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.MixupImage(mixup_epoch=250), T.RandomDistort(),
     T.RandomExpand(im_padding_value=[123.675, 116.28, 103.53]), T.RandomCrop(),
@@ -23,7 +23,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -43,8 +43,8 @@ eval_dataset = pdx.datasets.VOCDetection(
 num_classes = len(train_dataset.labels)
 model = pdx.det.YOLOv3(num_classes=num_classes, backbone='DarkNet53')
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=270,
     train_dataset=train_dataset,

tutorials/slim/prune/semantic_segmentation/unet_prune.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.Resize(target_size=512),
     T.RandomHorizontalFlip(),
@@ -21,7 +21,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -40,17 +40,17 @@ eval_dataset = pdx.datasets.SegDataset(
 model = pdx.load_model('output/unet/best_model')
 
 # Step 1/3: 分析模型各层参数在不同的剪裁比例下的敏感度
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md#analyze_sensitivity
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md#analyze_sensitivity
 model.analyze_sensitivity(
     dataset=eval_dataset, batch_size=1, save_dir='output/unet/prune')
 
 # Step 2/3: 根据选择的FLOPs减小比例对模型进行剪裁
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md#prune
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md#prune
 model.prune(pruned_flops=.2)
 
 # Step 3/3: 对剪裁后的模型重新训练
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md#train
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md#train
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/slim/prune/semantic_segmentation/unet_train.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.Resize(target_size=512),
     T.RandomHorizontalFlip(),
@@ -21,7 +21,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -41,8 +41,8 @@ eval_dataset = pdx.datasets.SegDataset(
 num_classes = len(train_dataset.labels)
 model = pdx.seg.UNet(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/slim/quantize/instance_segmentation/mask_rcnn_qat.py

@@ -22,7 +22,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/paddlex/cv/datasets/coco.py#L26
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/paddlex/cv/datasets/coco.py#L26
 train_dataset = pdx.datasets.CocoDetection(
     data_dir='xiaoduxiong_ins_det/JPEGImages',
     ann_file='xiaoduxiong_ins_det/train.json',

tutorials/slim/quantize/instance_segmentation/mask_rcnn_train.py

@@ -22,7 +22,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/paddlex/cv/datasets/coco.py#L26
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/paddlex/cv/datasets/coco.py#L26
 train_dataset = pdx.datasets.CocoDetection(
     data_dir='xiaoduxiong_ins_det/JPEGImages',
     ann_file='xiaoduxiong_ins_det/train.json',

tutorials/slim/quantize/semantic_segmentation/unet_qat.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.Resize(target_size=512),
     T.RandomHorizontalFlip(),
@@ -21,7 +21,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -40,7 +40,7 @@ eval_dataset = pdx.datasets.SegDataset(
 model = pdx.load_model('output/unet/best_model')
 
 # 在线量化
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md#quant_aware_train
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md#quant_aware_train
 model.quant_aware_train(
     num_epochs=5,
     train_dataset=train_dataset,

tutorials/slim/quantize/semantic_segmentation/unet_train.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.Resize(target_size=512),
     T.RandomHorizontalFlip(),
@@ -21,7 +21,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -41,8 +41,8 @@ eval_dataset = pdx.datasets.SegDataset(
 num_classes = len(train_dataset.labels)
 model = pdx.seg.UNet(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/image_classification/alexnet.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -34,8 +34,8 @@ eval_dataset = pdx.datasets.ImageNet(
 num_classes = len(train_dataset.labels)
 model = pdx.cls.AlexNet(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/image_classification/darknet53.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -34,8 +34,8 @@ eval_dataset = pdx.datasets.ImageNet(
 num_classes = len(train_dataset.labels)
 model = pdx.cls.DarkNet53(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/image_classification/densenet121.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -34,8 +34,8 @@ eval_dataset = pdx.datasets.ImageNet(
 num_classes = len(train_dataset.labels)
 model = pdx.cls.DenseNet121(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/image_classification/hrnet_w18_c.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -34,8 +34,8 @@ eval_dataset = pdx.datasets.ImageNet(
 num_classes = len(train_dataset.labels)
 model = pdx.cls.HRNet_W18_C(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/image_classification/mobilenetv3_large_w_custom_optimizer.py

@@ -7,7 +7,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -16,7 +16,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',

tutorials/train/image_classification/mobilenetv3_small.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -34,8 +34,8 @@ eval_dataset = pdx.datasets.ImageNet(
 num_classes = len(train_dataset.labels)
 model = pdx.cls.MobileNetV3_small(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/image_classification/resnet50_vd_ssld.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -34,8 +34,8 @@ eval_dataset = pdx.datasets.ImageNet(
 num_classes = len(train_dataset.labels)
 model = pdx.cls.ResNet50_vd_ssld(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/image_classification/shufflenetv2.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -34,8 +34,8 @@ eval_dataset = pdx.datasets.ImageNet(
 num_classes = len(train_dataset.labels)
 model = pdx.cls.ShuffleNetV2(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/image_classification/xception41.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose(
     [T.RandomCrop(crop_size=224), T.RandomHorizontalFlip(), T.Normalize()])
 
@@ -15,7 +15,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.ImageNet(
     data_dir='vegetables_cls',
     file_list='vegetables_cls/train_list.txt',
@@ -34,8 +34,8 @@ eval_dataset = pdx.datasets.ImageNet(
 num_classes = len(train_dataset.labels)
 model = pdx.cls.Xception41(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/classification.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/classification.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/tree/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py

@@ -6,7 +6,7 @@ dataset = 'https://bj.bcebos.com/paddlex/datasets/xiaoduxiong_ins_det.tar.gz'
 pdx.utils.download_and_decompress(dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.RandomResizeByShort(
         short_sizes=[640, 672, 704, 736, 768, 800],
@@ -22,7 +22,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.CocoDetection(
     data_dir='xiaoduxiong_ins_det/JPEGImages',
     ann_file='xiaoduxiong_ins_det/train.json',
@@ -39,8 +39,8 @@ num_classes = len(train_dataset.labels)
 model = pdx.det.MaskRCNN(
     num_classes=num_classes, backbone='ResNet50', with_fpn=True)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/instance_segmentation.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/instance_segmentation.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=12,
     train_dataset=train_dataset,

tutorials/train/object_detection/faster_rcnn_hrnet_w18.py

@@ -6,7 +6,7 @@ dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.RandomResizeByShort(
         short_sizes=[640, 672, 704, 736, 768, 800],
@@ -22,7 +22,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -42,8 +42,8 @@ eval_dataset = pdx.datasets.VOCDetection(
 num_classes = len(train_dataset.labels)
 model = pdx.det.FasterRCNN(num_classes=num_classes, backbone='HRNet_W18')
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=24,
     train_dataset=train_dataset,

tutorials/train/object_detection/faster_rcnn_r50_fpn.py

@@ -6,7 +6,7 @@ dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.RandomResizeByShort(
         short_sizes=[640, 672, 704, 736, 768, 800],
@@ -22,7 +22,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -43,8 +43,8 @@ num_classes = len(train_dataset.labels)
 model = pdx.det.FasterRCNN(
     num_classes=num_classes, backbone='ResNet50', with_fpn=True)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=12,
     train_dataset=train_dataset,

tutorials/train/object_detection/ppyolo.py

@@ -6,7 +6,7 @@ dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.MixupImage(mixup_epoch=-1), T.RandomDistort(),
     T.RandomExpand(im_padding_value=[123.675, 116.28, 103.53]), T.RandomCrop(),
@@ -23,7 +23,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -43,8 +43,8 @@ eval_dataset = pdx.datasets.VOCDetection(
 num_classes = len(train_dataset.labels)
 model = pdx.det.PPYOLO(num_classes=num_classes, backbone='ResNet50_vd_dcn')
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=200,
     train_dataset=train_dataset,

tutorials/train/object_detection/ppyolotiny.py

@@ -6,7 +6,7 @@ dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.MixupImage(mixup_epoch=-1), T.RandomDistort(),
     T.RandomExpand(im_padding_value=[123.675, 116.28, 103.53]), T.RandomCrop(),
@@ -23,7 +23,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -43,8 +43,8 @@ eval_dataset = pdx.datasets.VOCDetection(
 num_classes = len(train_dataset.labels)
 model = pdx.det.PPYOLOTiny(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=550,
     train_dataset=train_dataset,

tutorials/train/object_detection/ppyolov2.py

@@ -6,7 +6,7 @@ dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.MixupImage(mixup_epoch=-1), T.RandomDistort(),
     T.RandomExpand(im_padding_value=[123.675, 116.28, 103.53]), T.RandomCrop(),
@@ -26,7 +26,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -46,8 +46,8 @@ eval_dataset = pdx.datasets.VOCDetection(
 num_classes = len(train_dataset.labels)
 model = pdx.det.PPYOLOv2(num_classes=num_classes, backbone='ResNet50_vd_dcn')
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=170,
     train_dataset=train_dataset,

tutorials/train/object_detection/yolov3_darknet53.py

@@ -6,7 +6,7 @@ dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
 pdx.utils.download_and_decompress(dataset, path='./')
 
 # 定义训练和验证时的transforms
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.MixupImage(mixup_epoch=250), T.RandomDistort(),
     T.RandomExpand(im_padding_value=[123.675, 116.28, 103.53]), T.RandomCrop(),
@@ -23,7 +23,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.VOCDetection(
     data_dir='insect_det',
     file_list='insect_det/train_list.txt',
@@ -43,8 +43,8 @@ eval_dataset = pdx.datasets.VOCDetection(
 num_classes = len(train_dataset.labels)
 model = pdx.det.YOLOv3(num_classes=num_classes, backbone='DarkNet53')
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/detection.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop//docs/apis/models/detection.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop//docs/parameters.md
 model.train(
     num_epochs=270,
     train_dataset=train_dataset,

tutorials/train/semantic_segmentation/bisenetv2.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.Resize(target_size=512),
     T.RandomHorizontalFlip(),
@@ -21,7 +21,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -41,8 +41,8 @@ eval_dataset = pdx.datasets.SegDataset(
 num_classes = len(train_dataset.labels)
 model = pdx.seg.BiSeNetV2(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/semantic_segmentation/deeplabv3p_resnet50_vd.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.Resize(target_size=512),
     T.RandomHorizontalFlip(),
@@ -21,7 +21,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -41,8 +41,8 @@ eval_dataset = pdx.datasets.SegDataset(
 num_classes = len(train_dataset.labels)
 model = pdx.seg.DeepLabV3P(num_classes=num_classes, backbone='ResNet50_vd')
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/semantic_segmentation/fastscnn.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.Resize(target_size=512),
     T.RandomHorizontalFlip(),
@@ -21,7 +21,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -41,8 +41,8 @@ eval_dataset = pdx.datasets.SegDataset(
 num_classes = len(train_dataset.labels)
 model = pdx.seg.FastSCNN(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/semantic_segmentation/hrnet.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.Resize(target_size=512),
     T.RandomHorizontalFlip(),
@@ -21,7 +21,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -41,8 +41,8 @@ eval_dataset = pdx.datasets.SegDataset(
 num_classes = len(train_dataset.labels)
 model = pdx.seg.HRNet(num_classes=num_classes, width=48)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,

tutorials/train/semantic_segmentation/unet.py

@@ -6,7 +6,7 @@ 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://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/transforms/transforms.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
 train_transforms = T.Compose([
     T.Resize(target_size=512),
     T.RandomHorizontalFlip(),
@@ -21,7 +21,7 @@ eval_transforms = T.Compose([
 ])
 
 # 定义训练和验证所用的数据集
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/datasets.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
 train_dataset = pdx.datasets.SegDataset(
     data_dir='optic_disc_seg',
     file_list='optic_disc_seg/train_list.txt',
@@ -41,8 +41,8 @@ eval_dataset = pdx.datasets.SegDataset(
 num_classes = len(train_dataset.labels)
 model = pdx.seg.UNet(num_classes=num_classes)
 
-# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/apis/models/semantic_segmentation.md
-# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/dygraph/docs/parameters.md
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/semantic_segmentation.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
 model.train(
     num_epochs=10,
     train_dataset=train_dataset,