diff --git a/tutorials/train/image_classification/alexnet.py b/tutorials/train/image_classification/alexnet.py
index 90819a93df0bdb6cb7b413cd1222d28d0d08e3d3..b78f45bbc0f6889452ad0953062b78daca428aa9 100644
--- a/tutorials/train/image_classification/alexnet.py
+++ b/tutorials/train/image_classification/alexnet.py
@@ -7,12 +7,14 @@ pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomCrop(crop_size=224), transforms.RandomHorizontalFlip(),
+    transforms.RandomCrop(crop_size=224), 
+    transforms.RandomHorizontalFlip(),
     transforms.Normalize()
 ])
 eval_transforms = transforms.Compose([
     transforms.ResizeByShort(short_size=256),
-    transforms.CenterCrop(crop_size=224), transforms.Normalize()
+    transforms.CenterCrop(crop_size=224), 
+    transforms.Normalize()
 ])
 
 # 定义训练和验证所用的数据集
diff --git a/tutorials/train/image_classification/mobilenetv2.py b/tutorials/train/image_classification/mobilenetv2.py
index bc30dfdaf93558842712ab863655639b6b99ddfb..5edbf587a2831b1c0118526fe28f6add32df4be8 100644
--- a/tutorials/train/image_classification/mobilenetv2.py
+++ b/tutorials/train/image_classification/mobilenetv2.py
@@ -8,12 +8,14 @@ pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomCrop(crop_size=224), transforms.RandomHorizontalFlip(),
+    transforms.RandomCrop(crop_size=224), 
+    transforms.RandomHorizontalFlip(),
     transforms.Normalize()
 ])
 eval_transforms = transforms.Compose([
     transforms.ResizeByShort(short_size=256),
-    transforms.CenterCrop(crop_size=224), transforms.Normalize()
+    transforms.CenterCrop(crop_size=224), 
+    transforms.Normalize()
 ])
 
 # 定义训练和验证所用的数据集
diff --git a/tutorials/train/image_classification/mobilenetv3_small_ssld.py b/tutorials/train/image_classification/mobilenetv3_small_ssld.py
index b8e5e432b1169a76d1d2ba2206fac77aea074525..6d52775f33987507878ef77b2485ebe3ce2f6881 100644
--- a/tutorials/train/image_classification/mobilenetv3_small_ssld.py
+++ b/tutorials/train/image_classification/mobilenetv3_small_ssld.py
@@ -8,12 +8,14 @@ pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomCrop(crop_size=224), transforms.RandomHorizontalFlip(),
+    transforms.RandomCrop(crop_size=224), 
+    transforms.RandomHorizontalFlip(),
     transforms.Normalize()
 ])
 eval_transforms = transforms.Compose([
     transforms.ResizeByShort(short_size=256),
-    transforms.CenterCrop(crop_size=224), transforms.Normalize()
+    transforms.CenterCrop(crop_size=224), 
+    transforms.Normalize()
 ])
 
 # 定义训练和验证所用的数据集
diff --git a/tutorials/train/image_classification/resnet50_vd_ssld.py b/tutorials/train/image_classification/resnet50_vd_ssld.py
index 97a2e318426e97427a49d7a4d2f188153b98c0ce..ca94f7f19055b67fbfcd0cb29b34cd55b69a90e6 100644
--- a/tutorials/train/image_classification/resnet50_vd_ssld.py
+++ b/tutorials/train/image_classification/resnet50_vd_ssld.py
@@ -8,12 +8,14 @@ pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomCrop(crop_size=224), transforms.RandomHorizontalFlip(),
+    transforms.RandomCrop(crop_size=224), 
+    transforms.RandomHorizontalFlip(),
     transforms.Normalize()
 ])
 eval_transforms = transforms.Compose([
     transforms.ResizeByShort(short_size=256),
-    transforms.CenterCrop(crop_size=224), transforms.Normalize()
+    transforms.CenterCrop(crop_size=224), 
+    transforms.Normalize()
 ])
 
 # 定义训练和验证所用的数据集
diff --git a/tutorials/train/image_classification/shufflenetv2.py b/tutorials/train/image_classification/shufflenetv2.py
index 244c43419607c78321c3c8243f2e67ca23d2e3d5..29272df3f13bb28524c942c11f6714e459427345 100644
--- a/tutorials/train/image_classification/shufflenetv2.py
+++ b/tutorials/train/image_classification/shufflenetv2.py
@@ -8,12 +8,14 @@ pdx.utils.download_and_decompress(veg_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomCrop(crop_size=224), transforms.RandomHorizontalFlip(),
+    transforms.RandomCrop(crop_size=224), 
+    transforms.RandomHorizontalFlip(),
     transforms.Normalize()
 ])
 eval_transforms = transforms.Compose([
     transforms.ResizeByShort(short_size=256),
-    transforms.CenterCrop(crop_size=224), transforms.Normalize()
+    transforms.CenterCrop(crop_size=224), 
+    transforms.Normalize()
 ])
 
 # 定义训练和验证所用的数据集
diff --git a/tutorials/train/instance_segmentation/mask_rcnn_hrnet_fpn.py b/tutorials/train/instance_segmentation/mask_rcnn_hrnet_fpn.py
index 920c5f27298d49ad3a5ab7288a0ed7dc9f56d8d9..7f8e1eb35ddda3e7f27916e4756e8103f62ee88b 100644
--- a/tutorials/train/instance_segmentation/mask_rcnn_hrnet_fpn.py
+++ b/tutorials/train/instance_segmentation/mask_rcnn_hrnet_fpn.py
@@ -11,15 +11,15 @@ pdx.utils.download_and_decompress(xiaoduxiong_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomHorizontalFlip(), transforms.Normalize(),
-    transforms.ResizeByShort(
-        short_size=800, max_size=1333), transforms.Padding(coarsest_stride=32)
+    transforms.RandomHorizontalFlip(), 
+    transforms.Normalize(),
+    transforms.ResizeByShort(short_size=800, max_size=1333), 
+    transforms.Padding(coarsest_stride=32)
 ])
 
 eval_transforms = transforms.Compose([
     transforms.Normalize(),
-    transforms.ResizeByShort(
-        short_size=800, max_size=1333),
+    transforms.ResizeByShort(short_size=800, max_size=1333),
     transforms.Padding(coarsest_stride=32),
 ])
 
diff --git a/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py b/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py
index bacbe615d0813040f9a34a70c0dcde31c86a54f9..1d9510fd189dd019d35d59918905dd178f2e73ad 100644
--- a/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py
+++ b/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py
@@ -11,16 +11,16 @@ pdx.utils.download_and_decompress(xiaoduxiong_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomHorizontalFlip(), transforms.Normalize(),
-    transforms.ResizeByShort(
-        short_size=800, max_size=1333), transforms.Padding(coarsest_stride=32)
+    transforms.RandomHorizontalFlip(), 
+    transforms.Normalize(),
+    transforms.ResizeByShort(short_size=800, max_size=1333), 
+    transforms.Padding(coarsest_stride=32)
 ])
 
 eval_transforms = transforms.Compose([
-    transforms.Normalize(),
-    transforms.ResizeByShort(
-        short_size=800, max_size=1333),
-    transforms.Padding(coarsest_stride=32),
+    transforms.Normalize(), 
+    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
diff --git a/tutorials/train/object_detection/faster_rcnn_hrnet_fpn.py b/tutorials/train/object_detection/faster_rcnn_hrnet_fpn.py
index 83f9b69c344981fa1de108a9ebe19d2cab5fb686..3d1650f3768a6b0207011aa215596b5c46c8852d 100644
--- a/tutorials/train/object_detection/faster_rcnn_hrnet_fpn.py
+++ b/tutorials/train/object_detection/faster_rcnn_hrnet_fpn.py
@@ -11,16 +11,16 @@ pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomHorizontalFlip(), transforms.Normalize(),
-    transforms.ResizeByShort(
-        short_size=800, max_size=1333), transforms.Padding(coarsest_stride=32)
+    transforms.RandomHorizontalFlip(), 
+    transforms.Normalize(),
+    transforms.ResizeByShort(short_size=800, max_size=1333), 
+    transforms.Padding(coarsest_stride=32)
 ])
 
 eval_transforms = transforms.Compose([
-    transforms.Normalize(),
-    transforms.ResizeByShort(
-        short_size=800, max_size=1333),
-    transforms.Padding(coarsest_stride=32),
+    transforms.Normalize(), 
+    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
diff --git a/tutorials/train/object_detection/faster_rcnn_r50_fpn.py b/tutorials/train/object_detection/faster_rcnn_r50_fpn.py
index 6c7987a74f8216b4a448624096aceb0a7db522f8..ca4105892bcd1294c26f04bfb7fefe6af1a0badc 100644
--- a/tutorials/train/object_detection/faster_rcnn_r50_fpn.py
+++ b/tutorials/train/object_detection/faster_rcnn_r50_fpn.py
@@ -8,15 +8,15 @@ pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomHorizontalFlip(), transforms.Normalize(),
-    transforms.ResizeByShort(
-        short_size=800, max_size=1333), transforms.Padding(coarsest_stride=32)
+    transforms.RandomHorizontalFlip(), 
+    transforms.Normalize(),
+    transforms.ResizeByShort(short_size=800, max_size=1333), 
+    transforms.Padding(coarsest_stride=32)
 ])
 
 eval_transforms = transforms.Compose([
     transforms.Normalize(),
-    transforms.ResizeByShort(
-        short_size=800, max_size=1333),
+    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
diff --git a/tutorials/train/object_detection/yolov3_darknet53.py b/tutorials/train/object_detection/yolov3_darknet53.py
index facb3e558b422ac5c73db275eec9efc62de34054..a15e5cbcfd037e75eadc65bfb42320f8c13f8e54 100644
--- a/tutorials/train/object_detection/yolov3_darknet53.py
+++ b/tutorials/train/object_detection/yolov3_darknet53.py
@@ -8,20 +8,18 @@ pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.MixupImage(mixup_epoch=250),
+    transforms.MixupImage(mixup_epoch=250), 
     transforms.RandomDistort(),
-    transforms.RandomExpand(),
-    transforms.RandomCrop(),
-    transforms.Resize(
-        target_size=608, interp='RANDOM'),
+    transforms.RandomExpand(), 
+    transforms.RandomCrop(), 
+    transforms.Resize(target_size=608, interp='RANDOM'), 
     transforms.RandomHorizontalFlip(),
-    transforms.Normalize(),
+    transforms.Normalize()
 ])
 
 eval_transforms = transforms.Compose([
-    transforms.Resize(
-        target_size=608, interp='CUBIC'),
-    transforms.Normalize(),
+    transforms.Resize(target_size=608, interp='CUBIC'), 
+    transforms.Normalize()
 ])
 
 # 定义训练和验证所用的数据集
diff --git a/tutorials/train/object_detection/yolov3_mobilenetv1.py b/tutorials/train/object_detection/yolov3_mobilenetv1.py
index c74572640bc0ceb0f0fcf45180bbdc7a038a317d..9b621851bcc5f0f058129c5ad9a666503cbda667 100644
--- a/tutorials/train/object_detection/yolov3_mobilenetv1.py
+++ b/tutorials/train/object_detection/yolov3_mobilenetv1.py
@@ -12,15 +12,13 @@ train_transforms = transforms.Compose([
     transforms.RandomDistort(),
     transforms.RandomExpand(),
     transforms.RandomCrop(),
-    transforms.Resize(
-        target_size=608, interp='RANDOM'),
+    transforms.Resize(target_size=608, interp='RANDOM'),
     transforms.RandomHorizontalFlip(),
     transforms.Normalize(),
 ])
 
 eval_transforms = transforms.Compose([
-    transforms.Resize(
-        target_size=608, interp='CUBIC'),
+    transforms.Resize(target_size=608, interp='CUBIC'),
     transforms.Normalize(),
 ])
 
diff --git a/tutorials/train/object_detection/yolov3_mobilenetv3.py b/tutorials/train/object_detection/yolov3_mobilenetv3.py
index 3fab5255b9f3a1a8ce537fa5b202916b147f380e..4eb06099e7320655310b77c7166a022b363e4bbe 100644
--- a/tutorials/train/object_detection/yolov3_mobilenetv3.py
+++ b/tutorials/train/object_detection/yolov3_mobilenetv3.py
@@ -8,20 +8,18 @@ pdx.utils.download_and_decompress(insect_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.MixupImage(mixup_epoch=250),
+    transforms.MixupImage(mixup_epoch=250), 
     transforms.RandomDistort(),
-    transforms.RandomExpand(),
-    transforms.RandomCrop(),
-    transforms.Resize(
-        target_size=608, interp='RANDOM'),
+    transforms.RandomExpand(), 
+    transforms.RandomCrop(), 
+    transforms.Resize(target_size=608, interp='RANDOM'), 
     transforms.RandomHorizontalFlip(),
-    transforms.Normalize(),
+    transforms.Normalize()
 ])
 
 eval_transforms = transforms.Compose([
-    transforms.Resize(
-        target_size=608, interp='CUBIC'),
-    transforms.Normalize(),
+    transforms.Resize(target_size=608, interp='CUBIC'), 
+    transforms.Normalize()
 ])
 
 # 定义训练和验证所用的数据集
diff --git a/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2.py b/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2.py
index 9e3a7d5d438373d4d58c0301ab9329847b450980..d7a2f6371796f763be9181c3ec431bf986621198 100644
--- a/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2.py
+++ b/tutorials/train/semantic_segmentation/deeplabv3p_mobilenetv2.py
@@ -11,12 +11,15 @@ pdx.utils.download_and_decompress(optic_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomHorizontalFlip(), transforms.ResizeRangeScaling(),
-    transforms.RandomPaddingCrop(crop_size=512), transforms.Normalize()
+    transforms.RandomHorizontalFlip(), 
+    transforms.ResizeRangeScaling(),
+    transforms.RandomPaddingCrop(crop_size=512), 
+    transforms.Normalize()
 ])
 
 eval_transforms = transforms.Compose([
-    transforms.ResizeByLong(long_size=512), transforms.Padding(target_size=512),
+    transforms.ResizeByLong(long_size=512), 
+    transforms.Padding(target_size=512),
     transforms.Normalize()
 ])
 
diff --git a/tutorials/train/semantic_segmentation/fast_scnn.py b/tutorials/train/semantic_segmentation/fast_scnn.py
index a2fdfa40dd94e145c6142b215908e731ec40d3c3..af041cacb95e49170be3af61078b8ea3399145fb 100644
--- a/tutorials/train/semantic_segmentation/fast_scnn.py
+++ b/tutorials/train/semantic_segmentation/fast_scnn.py
@@ -12,12 +12,15 @@ 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
 train_transforms = transforms.Compose([
-    transforms.RandomHorizontalFlip(), transforms.ResizeRangeScaling(),
-    transforms.RandomPaddingCrop(crop_size=512), transforms.Normalize()
+    transforms.RandomHorizontalFlip(), 
+    transforms.ResizeRangeScaling(),
+    transforms.RandomPaddingCrop(crop_size=512), 
+    transforms.Normalize()
 ])
 
 eval_transforms = transforms.Compose([
-    transforms.ResizeByLong(long_size=512), transforms.Padding(target_size=512),
+    transforms.ResizeByLong(long_size=512), 
+    transforms.Padding(target_size=512),
     transforms.Normalize()
 ])
 
diff --git a/tutorials/train/semantic_segmentation/hrnet.py b/tutorials/train/semantic_segmentation/hrnet.py
index 682ce82da4495c80cf504d17477d9ef9e750b963..330a107714ee5fbe7e6e3a021b5afa5737fdd779 100644
--- a/tutorials/train/semantic_segmentation/hrnet.py
+++ b/tutorials/train/semantic_segmentation/hrnet.py
@@ -11,12 +11,15 @@ pdx.utils.download_and_decompress(optic_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomHorizontalFlip(), transforms.ResizeRangeScaling(),
-    transforms.RandomPaddingCrop(crop_size=512), transforms.Normalize()
+    transforms.RandomHorizontalFlip(), 
+    transforms.ResizeRangeScaling(),
+    transforms.RandomPaddingCrop(crop_size=512), 
+    transforms.Normalize()
 ])
 
 eval_transforms = transforms.Compose([
-    transforms.ResizeByLong(long_size=512), transforms.Padding(target_size=512),
+    transforms.ResizeByLong(long_size=512), 
+    transforms.Padding(target_size=512),
     transforms.Normalize()
 ])
 
diff --git a/tutorials/train/semantic_segmentation/unet.py b/tutorials/train/semantic_segmentation/unet.py
index 327a6ce648c14604fe2861be20af23c4d59089e9..46e93b8c217d11bfa9aa7c003ea28fd1041092ba 100644
--- a/tutorials/train/semantic_segmentation/unet.py
+++ b/tutorials/train/semantic_segmentation/unet.py
@@ -11,8 +11,10 @@ pdx.utils.download_and_decompress(optic_dataset, path='./')
 
 # 定义训练和验证时的transforms
 train_transforms = transforms.Compose([
-    transforms.RandomHorizontalFlip(), transforms.ResizeRangeScaling(),
-    transforms.RandomPaddingCrop(crop_size=512), transforms.Normalize()
+    transforms.RandomHorizontalFlip(), 
+    transforms.ResizeRangeScaling(),
+    transforms.RandomPaddingCrop(crop_size=512), 
+    transforms.Normalize()
 ])
 
 eval_transforms = transforms.Compose([