Update legendary_models configs

ppcls/configs/ImageNet/HRNet/HRNet_W18_C.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "HRNet_W18_C"
+  name: HRNet_W18_C
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/HRNet/HRNet_W30_C.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "HRNet_W30_C"
+  name: HRNet_W30_C
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/HRNet/HRNet_W32_C.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "HRNet_W32_C"
+  name: HRNet_W32_C
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/HRNet/HRNet_W40_C.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "HRNet_W40_C"
+  name: HRNet_W40_C
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/HRNet/HRNet_W44_C.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "HRNet_W44_C"
+  name: HRNet_W44_C
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/HRNet/HRNet_W48_C.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "HRNet_W48_C"
+  name: HRNet_W48_C
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/HRNet/HRNet_W64_C.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "HRNet_W64_C"
+  name: HRNet_W64_C
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/Ineption/InceptionV3.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 299, 299]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "InceptionV3"
+  name: InceptionV3
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.045
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 299
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 320
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV1/MobileNetV1.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV1"
+  name: MobileNetV1
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV1/MobileNetV1_x0_25.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV1_x0_25"
+  name: MobileNetV1_x0_25
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV1/MobileNetV1_x0_5.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV1_x0_5"
+  name: MobileNetV1_x0_5
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV1/MobileNetV1_x0_75.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV1_x0_75"
+  name: MobileNetV1_x0_75
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x0_35.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_large_x0_35"
+  name: MobileNetV3_large_x0_35
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x0_5.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_large_x0_5"
+  name: MobileNetV3_large_x0_5
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x0_75.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_large_x0_75"
+  name: MobileNetV3_large_x0_75
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_large_x1_0"
+  name: MobileNetV3_large_x1_0
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_25.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_large_x1_25"
+  name: MobileNetV3_large_x1_25
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x0_35.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_small_x0_35"
+  name: MobileNetV3_small_x0_35
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x0_5.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_small_x0_5"
+  name: MobileNetV3_small_x0_5
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x0_75.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_small_x0_75"
+  name: MobileNetV3_small_x0_75
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x1_0.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_small_x1_0"
+  name: MobileNetV3_small_x1_0
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x1_25.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "MobileNetV3_small_x1_25"
+  name: MobileNetV3_small_x1_25
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 1.3
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -60,7 +60,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 512
       drop_last: False
       shuffle: True
@@ -71,9 +71,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -85,7 +85,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -94,7 +94,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -111,9 +111,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet101.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet101"
+  name: ResNet101
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet101_vd.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet101_vd"
+  name: ResNet101_vd
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.1
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -63,7 +63,7 @@ DataLoader:
             alpha: 0.2
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -74,9 +74,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -88,7 +88,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -97,7 +97,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -114,9 +114,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet152.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet152"
+  name: ResNet152
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet152_vd.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet152_vd"
+  name: ResNet152_vd
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.1
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -63,7 +63,7 @@ DataLoader:
             alpha: 0.2
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -74,9 +74,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -88,7 +88,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -97,7 +97,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -114,9 +114,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet18.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet18"
+  name: ResNet18
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet18_vd.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet18_vd"
+  name: ResNet18_vd
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.1
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -63,7 +63,7 @@ DataLoader:
             alpha: 0.2
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -74,9 +74,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -88,7 +88,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -97,7 +97,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -114,9 +114,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet200_vd.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet200_vd"
+  name: ResNet200_vd
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.1
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -63,7 +63,7 @@ DataLoader:
             alpha: 0.2
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -74,9 +74,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -88,7 +88,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -97,7 +97,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -114,9 +114,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet34.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet34"
+  name: ResNet34
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet34_vd.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet34_vd"
+  name: ResNet34_vd
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.1
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -63,7 +63,7 @@ DataLoader:
             alpha: 0.2
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -74,9 +74,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -88,7 +88,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -97,7 +97,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -114,9 +114,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet50.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet50"
+  name: ResNet50
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Piecewise"
+    name: Piecewise
     learning_rate: 0.1
     decay_epochs: [30, 60, 90]
     values: [0.1, 0.01, 0.001, 0.0001]
@@ -46,9 +46,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -61,7 +61,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -72,9 +72,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -86,7 +86,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -95,7 +95,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -112,9 +112,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "ResNet50_vd"
+  name: ResNet50_vd
  
 # loss function config for traing/eval process
 Loss:
@@ -31,10 +31,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.1
   regularizer:
     name: 'L2'
@@ -45,9 +45,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -63,7 +63,7 @@ DataLoader:
             alpha: 0.2
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -74,9 +74,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -88,7 +88,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -97,7 +97,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -114,9 +114,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/VGG/VGG11.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "VGG11"
+  name: VGG11
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.1
   regularizer:
     name: 'L2'
@@ -44,9 +44,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -59,7 +59,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 128
       drop_last: False
       shuffle: True
@@ -70,9 +70,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -84,7 +84,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -93,7 +93,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -110,9 +110,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/VGG/VGG13.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "VGG13"
+  name: VGG13
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.01
   regularizer:
     name: 'L2'
@@ -44,9 +44,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -59,7 +59,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -70,9 +70,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -84,7 +84,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -93,7 +93,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -110,9 +110,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/VGG/VGG16.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "VGG16"
+  name: VGG16
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.01
   regularizer:
     name: 'L2'
@@ -44,9 +44,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -59,7 +59,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -70,9 +70,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -84,7 +84,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -93,7 +93,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -110,9 +110,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/ImageNet/VGG/VGG19.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 1000
   save_interval: 1
   eval_during_train: True
@@ -13,11 +13,11 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
+  save_inference_dir: ./inference
 
 # model architecture
 Arch:
-  name: "VGG19"
+  name: VGG19
  
 # loss function config for traing/eval process
 Loss:
@@ -30,10 +30,10 @@ Loss:
 
 
 Optimizer:
-  name: "Momentum"
+  name: Momentum
   momentum: 0.9
   lr:
-    name: "Cosine"
+    name: Cosine
     learning_rate: 0.01
   regularizer:
     name: 'L2'
@@ -44,9 +44,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/train_list.txt
       transform_ops:
         - RandCropImage:
             size: 224
@@ -59,7 +59,7 @@ DataLoader:
             order: ''
 
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: True
@@ -70,9 +70,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/ILSVRC2012/"
-      cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/ILSVRC2012/
+      cls_label_path: ./dataset/ILSVRC2012/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -84,7 +84,7 @@ DataLoader:
             std: [0.229, 0.224, 0.225]
             order: ''
     sampler:
-      name: "DistributedBatchSampler"
+      name: DistributedBatchSampler
       batch_size: 64
       drop_last: False
       shuffle: False
@@ -93,7 +93,7 @@ DataLoader:
       use_shared_memory: True
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:
@@ -110,9 +110,9 @@ Infer:
         order: ''
     - ToCHWImage:
   PostProcess:
-    name: "Topk"
+    name: Topk
     topk: 5
-    class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
+    class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
 
 Metric:
   Train:

ppcls/configs/Products/ResNet50_vd_Aliproduct.yaml

@@ -2,8 +2,8 @@
 Global:
   checkpoints: null
   pretrained_model: null
-  output_dir: "./output/"
-  device: "gpu"
+  output_dir: ./output/
+  device: gpu
   class_num: 50030
   save_interval: 1
   eval_during_train: True
@@ -13,23 +13,23 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
-  eval_mode: "classification"
+  save_inference_dir: ./inference
+  eval_mode: classification
 
 # model architecture
 Arch:
-  name: "RecModel"
+  name: RecModel
   Backbone: 
-    name: "ResNet50_vd"
+    name: ResNet50_vd
     pretrained: True
   BackboneStopLayer:
-    name: "flatten_0"
+    name: flatten_0
   Neck:
-    name: "FC"
+    name: FC
     embedding_size: 2048
     class_num: 512
   Head:
-    name: "FC"  
+    name: FC  
     embedding_size: 512
     class_num: 50030
  
@@ -56,9 +56,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/Aliproduct/"
-      cls_label_path: "./dataset/Aliproduct/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/Aliproduct/
+      cls_label_path: ./dataset/Aliproduct/train_list.txt
       transform_ops:
         - ResizeImage:
             size: 224
@@ -81,9 +81,9 @@ DataLoader:
   Eval:
     # TOTO: modify to the latest trainer
     dataset: 
-      name: "ImageNetDataset"
-      image_root: "./dataset/Aliproduct/"
-      cls_label_path: "./dataset/Aliproduct/val_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/Aliproduct/
+      cls_label_path: ./dataset/Aliproduct/val_list.txt
       transform_ops:
         - ResizeImage:
             resize_short: 256
@@ -111,7 +111,7 @@ Metric:
         topk: [1, 5]
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:

ppcls/configs/Products/ResNet50_vd_Inshop.yaml

@@ -3,9 +3,9 @@ Global:
   checkpoints: null
 # please download pretrained model via this link:
 # https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/pretrain/product_ResNet50_vd_Aliproduct_v1.0_pretrained.pdparams
-  pretrained_model: "product_ResNet50_vd_Aliproduct_v1.0_pretrained"
-  output_dir: "./output/"
-  device: "gpu"
+  pretrained_model: product_ResNet50_vd_Aliproduct_v1.0_pretrained
+  output_dir: ./output/
+  device: gpu
   class_num: 3997
   save_interval: 10
   eval_during_train: True
@@ -15,26 +15,26 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
-  eval_mode: "retrieval"
+  save_inference_dir: ./inference
+  eval_mode: retrieval
 
 # model architecture
 Arch:
-  name: "RecModel"
-  infer_output_key: "features"
+  name: RecModel
+  infer_output_key: features
   infer_add_softmax: False
   
   Backbone: 
-    name: "ResNet50_vd"
+    name: ResNet50_vd
     pretrained: False
   BackboneStopLayer:
-    name: "flatten_0"
+    name: flatten_0
   Neck:
-    name: "FC"
+    name: FC
     embedding_size: 2048
     class_num: 512
   Head:
-    name: "ArcMargin"  
+    name: ArcMargin  
     embedding_size: 512
     class_num: 3997
     margin: 0.15
@@ -70,9 +70,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/Inshop/"
-      cls_label_path: "./dataset/Inshop/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/Inshop/
+      cls_label_path: ./dataset/Inshop/train_list.txt
       transform_ops:
         - ResizeImage:
             size: 224
@@ -90,7 +90,7 @@ DataLoader:
             r1: 0.3
             mean: [0., 0., 0.]
     sampler:
-      name: "DistributedRandomIdentitySampler"
+      name: DistributedRandomIdentitySampler
       batch_size: 64
       num_instances: 2
       drop_last: False
@@ -102,9 +102,9 @@ DataLoader:
   Eval:
     Query:
       dataset: 
-        name: "ImageNetDataset"
-        image_root: "./dataset/Inshop/"
-        cls_label_path: "./dataset/Inshop/query_list.txt"
+        name: ImageNetDataset
+        image_root: ./dataset/Inshop/
+        cls_label_path: ./dataset/Inshop/query_list.txt
         transform_ops:
           - ResizeImage:
               size: 224
@@ -114,7 +114,7 @@ DataLoader:
               std: [0.229, 0.224, 0.225]
               order: ''
       sampler:
-        name: "DistributedBatchSampler"
+        name: DistributedBatchSampler
         batch_size: 64
         drop_last: False
         shuffle: False
@@ -124,9 +124,9 @@ DataLoader:
 
     Gallery:
       dataset: 
-        name: "ImageNetDataset"
-        image_root: "./dataset/Inshop/"
-        cls_label_path: "./dataset/Inshop/gallery_list.txt"
+        name: ImageNetDataset
+        image_root: ./dataset/Inshop/
+        cls_label_path: ./dataset/Inshop/gallery_list.txt
         transform_ops:
           - ResizeImage:
               size: 224
@@ -136,7 +136,7 @@ DataLoader:
               std: [0.229, 0.224, 0.225]
               order: ''
       sampler:
-        name: "DistributedBatchSampler"
+        name: DistributedBatchSampler
         batch_size: 64
         drop_last: False
         shuffle: False
@@ -150,7 +150,7 @@ Metric:
         topk: [1, 5]
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage:

ppcls/configs/Products/ResNet50_vd_SOP.yaml

@@ -3,9 +3,9 @@ Global:
   checkpoints: null
 # please download pretrained model via this link:
 # https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/pretrain/product_ResNet50_vd_Aliproduct_v1.0_pretrained.pdparams
-  pretrained_model: "product_ResNet50_vd_Aliproduct_v1.0_pretrained"
-  output_dir: "./output/"
-  device: "gpu"
+  pretrained_model: product_ResNet50_vd_Aliproduct_v1.0_pretrained
+  output_dir: ./output/
+  device: gpu
   class_num: 11319
   save_interval: 10
   eval_during_train: True
@@ -15,28 +15,28 @@ Global:
   use_visualdl: False
   # used for static mode and model export
   image_shape: [3, 224, 224]
-  save_inference_dir: "./inference"
-  eval_mode: "retrieval"
+  save_inference_dir: ./inference
+  eval_mode: retrieval
 
 # model architecture
 Arch:
-  name: "RecModel"
+  name: RecModel
   Backbone: 
-    name: "ResNet50_vd"
+    name: ResNet50_vd
     pretrained: False
   BackboneStopLayer:
-    name: "flatten_0"
+    name: flatten_0
   Neck:
-    name: "FC"
+    name: FC
     embedding_size: 2048
     class_num: 512
   Head:
-    name: "ArcMargin"  
+    name: ArcMargin  
     embedding_size: 512
     class_num: 11319
     margin: 0.15
     scale: 30
-  infer_output_key: "features"
+  infer_output_key: features
   infer_add_softmax: False
 
 # loss function config for traing/eval process
@@ -69,9 +69,9 @@ Optimizer:
 DataLoader:
   Train:
     dataset:
-      name: "ImageNetDataset"
-      image_root: "./dataset/Stanford_Online_Products/"
-      cls_label_path: "./dataset/Stanford_Online_Products/train_list.txt"
+      name: ImageNetDataset
+      image_root: ./dataset/Stanford_Online_Products/
+      cls_label_path: ./dataset/Stanford_Online_Products/train_list.txt
       transform_ops:
         - ResizeImage:
             size: 224
@@ -101,9 +101,9 @@ DataLoader:
   Eval:
     Query:
       dataset: 
-        name: "ImageNetDataset"
-        image_root: "./dataset/Stanford_Online_Products/"
-        cls_label_path: "./dataset/Stanford_Online_Products/test_list.txt"
+        name: ImageNetDataset
+        image_root: ./dataset/Stanford_Online_Products/
+        cls_label_path: ./dataset/Stanford_Online_Products/test_list.txt
         transform_ops:
           - ResizeImage:
               size: 224
@@ -123,9 +123,9 @@ DataLoader:
 
     Gallery:
       dataset: 
-        name: "ImageNetDataset"
-        image_root: "./dataset/Stanford_Online_Products/"
-        cls_label_path: "./dataset/Stanford_Online_Products/test_list.txt"
+        name: ImageNetDataset
+        image_root: ./dataset/Stanford_Online_Products/
+        cls_label_path: ./dataset/Stanford_Online_Products/test_list.txt
         transform_ops:
           - ResizeImage:
               size: 224
@@ -149,7 +149,7 @@ Metric:
         topk: [1, 5]
 
 Infer:
-  infer_imgs: "docs/images/whl/demo.jpg"
+  infer_imgs: docs/images/whl/demo.jpg
   batch_size: 10
   transforms:
     - DecodeImage: