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support for ssld

pull/39/head
WuHaobo 2020-04-16 03:47:00 +00:00
parent 1151bcff84
commit 174d723ceb
92 changed files with 276 additions and 92 deletions
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4
configs/AlexNet/AlexNet.yaml
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mode: 'train'
architecture: "AlexNet"
ARCHITECTURE:
name: "AlexNet"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DPN/DPN107.yaml
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mode: 'train'
architecture: 'DPN107'
ARCHITECTURE:
name: 'DPN107'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DPN/DPN131.yaml
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mode: 'train'
architecture: 'DPN131'
ARCHITECTURE:
name: 'DPN131'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DPN/DPN68.yaml
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mode: 'train'
architecture: 'DPN68'
ARCHITECTURE:
name: 'DPN68'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DPN/DPN92.yaml
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mode: 'train'
architecture: 'DPN92'
ARCHITECTURE:
name: 'DPN92'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DPN/DPN98.yaml
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mode: 'train'
architecture: 'DPN98'
ARCHITECTURE:
name: 'DPN98'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DarkNet/DarkNet53.yaml
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mode: 'train'
architecture: "DarkNet53"
ARCHITECTURE:
name: "DarkNet53"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DenseNet/DenseNet121.yaml
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mode: 'train'
architecture: 'DenseNet121'
ARCHITECTURE:
name: 'DenseNet121'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DenseNet/DenseNet161.yaml
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mode: 'train'
architecture: 'DenseNet161'
ARCHITECTURE:
name: 'DenseNet161'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DenseNet/DenseNet169.yaml
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mode: 'train'
architecture: 'DenseNet169'
ARCHITECTURE:
name: 'DenseNet169'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DenseNet/DenseNet201.yaml
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mode: 'train'
architecture: 'DenseNet201'
ARCHITECTURE:
name: 'DenseNet201'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/DenseNet/DenseNet264.yaml
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mode: 'train'
architecture: 'DenseNet264'
ARCHITECTURE:
name: 'DenseNet264'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/HRNet/HRNet_W18_C.yaml
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mode: 'train'
architecture: 'HRNet_W18_C'
ARCHITECTURE:
name: 'HRNet_W18_C'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/HRNet/HRNet_W30_C.yaml
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mode: 'train'
architecture: 'HRNet_W30_C'
ARCHITECTURE:
name: 'HRNet_W30_C'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/HRNet/HRNet_W32_C.yaml
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mode: 'train'
architecture: 'HRNet_W32_C'
ARCHITECTURE:
name: 'HRNet_W32_C'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/HRNet/HRNet_W40_C.yaml
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mode: 'train'
architecture: 'HRNet_W40_C'
ARCHITECTURE:
name: 'HRNet_W40_C'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/HRNet/HRNet_W44_C.yaml
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mode: 'train'
architecture: 'HRNet_W44_C'
ARCHITECTURE:
name: 'HRNet_W44_C'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/HRNet/HRNet_W48_C.yaml
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mode: 'train'
architecture: 'HRNet_W48_C'
ARCHITECTURE:
name: 'HRNet_W48_C'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/HRNet/HRNet_W64_C.yaml
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mode: 'train'
architecture: 'HRNet_W64_C'
ARCHITECTURE:
name: 'HRNet_W64_C'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/Inception/GoogLeNet.yaml
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mode: 'train'
architecture: "GoogLeNet"
ARCHITECTURE:
name: "GoogLeNet"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/Inception/InceptionV4.yaml
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mode: 'train'
architecture: 'InceptionV4'
ARCHITECTURE:
name: 'InceptionV4'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV1/MobileNetV1.yaml
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mode: 'train'
architecture: "MobileNetV1"
ARCHITECTURE:
name: "MobileNetV1"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV1/MobileNetV1_x0_25.yaml
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mode: 'train'
architecture: "MobileNetV1_x0_25"
ARCHITECTURE:
name: "MobileNetV1_x0_25"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV1/MobileNetV1_x0_5.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV1_x0_5"
ARCHITECTURE:
name: "MobileNetV1_x0_5"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV1/MobileNetV1_x0_75.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV1_x0_75"
ARCHITECTURE:
name: "MobileNetV1_x0_75"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV2/MobileNetV2.yaml
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mode: 'train'
architecture: "MobileNetV2"
ARCHITECTURE:
name: "MobileNetV2"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV2/MobileNetV2_x0_25.yaml
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mode: 'train'
architecture: "MobileNetV2_x0_25"
ARCHITECTURE:
name: "MobileNetV2_x0_25"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV2/MobileNetV2_x0_5.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV2_x0_5"
ARCHITECTURE:
name: "MobileNetV2_x0_5"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV2/MobileNetV2_x0_75.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV2_x0_75"
ARCHITECTURE:
name: "MobileNetV2_x0_75"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV2/MobileNetV2_x1_5.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV2_x1_5"
ARCHITECTURE:
name: "MobileNetV2_x1_5"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV2/MobileNetV2_x2_0.yaml
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mode: 'train'
architecture: "MobileNetV2_x2_0"
ARCHITECTURE:
name: "MobileNetV2_x2_0"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_large_x0_35.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_large_x0_35"
ARCHITECTURE:
name: "MobileNetV3_large_x0_35"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_large_x0_5.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_large_x0_5"
ARCHITECTURE:
name: "MobileNetV3_large_x0_5"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_large_x0_75.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_large_x0_75"
ARCHITECTURE:
name: "MobileNetV3_large_x0_75"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_large_x1_0.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_large_x1_0"
ARCHITECTURE:
name: "MobileNetV3_large_x1_0"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_large_x1_25.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_large_x1_25"
ARCHITECTURE:
name: "MobileNetV3_large_x1_25"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_small_x0_35.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_small_x0_35"
ARCHITECTURE:
name: "MobileNetV3_small_x0_35"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_small_x0_5.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_small_x0_5"
ARCHITECTURE:
name: "MobileNetV3_small_x0_5"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_small_x0_75.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_small_x0_75"
ARCHITECTURE:
name: "MobileNetV3_small_x0_75"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_small_x1_0.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_small_x1_0"
ARCHITECTURE:
name: "MobileNetV3_small_x1_0"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/MobileNetV3/MobileNetV3_small_x1_25.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "MobileNetV3_small_x1_25"
ARCHITECTURE:
name: "MobileNetV3_small_x1_25"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/Res2Net/Res2Net101_vd_26w_4s.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'Res2Net101_vd_26w_4s'
ARCHITECTURE:
name: 'Res2Net101_vd_26w_4s'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/Res2Net/Res2Net200_vd_26w_4s.yaml
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mode: 'train'
architecture: 'Res2Net200_vd_26w_4s'
ARCHITECTURE:
name: 'Res2Net200_vd_26w_4s'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/Res2Net/Res2Net50_14w_8s.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'Res2Net50_14w_8s'
ARCHITECTURE:
name: 'Res2Net50_14w_8s'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/Res2Net/Res2Net50_26w_4s.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'Res2Net50_26w_4s'
ARCHITECTURE:
name: 'Res2Net50_26w_4s'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/Res2Net/Res2Net50_vd_26w_4s.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'Res2Net50_vd_26w_4s'
ARCHITECTURE:
name: 'Res2Net50_vd_26w_4s'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt101_32x4d.yaml
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mode: 'train'
architecture: 'ResNeXt101_32x4d'
ARCHITECTURE:
name: 'ResNeXt101_32x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt101_64x4d.yaml
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mode: 'train'
architecture: 'ResNeXt101_64x4d'
ARCHITECTURE:
name: 'ResNeXt101_64x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt101_vd_32x4d.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'ResNeXt101_vd_32x4d'
ARCHITECTURE:
name: 'ResNeXt101_vd_32x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt101_vd_64x4d.yaml
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mode: 'train'
architecture: 'ResNeXt101_vd_64x4d'
ARCHITECTURE:
name: 'ResNeXt101_vd_64x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt152_32x4d.yaml
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mode: 'train'
architecture: 'ResNeXt152_32x4d'
ARCHITECTURE:
name: 'ResNeXt152_32x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt152_64x4d.yaml
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mode: 'train'
architecture: 'ResNeXt152_64x4d'
ARCHITECTURE:
name: 'ResNeXt152_64x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt152_vd_32x4d.yaml
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mode: 'train'
architecture: 'ResNeXt152_vd_32x4d'
ARCHITECTURE:
name: 'ResNeXt152_vd_32x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt152_vd_64x4d.yaml
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mode: 'train'
architecture: 'ResNeXt152_vd_64x4d'
ARCHITECTURE:
name: 'ResNeXt152_vd_64x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt50_32x4d.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'ResNeXt50_32x4d'
ARCHITECTURE:
name: 'ResNeXt50_32x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt50_64x4d.yaml
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mode: 'train'
architecture: "ResNeXt50_64x4d"
ARCHITECTURE:
name: "ResNeXt50_64x4d"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt50_vd_32x4d.yaml
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mode: 'train'
architecture: "ResNeXt50_vd_32x4d"
ARCHITECTURE:
name: "ResNeXt50_vd_32x4d"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNeXt/ResNeXt50_vd_64x4d.yaml
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mode: 'train'
architecture: 'ResNeXt50_vd_64x4d'
ARCHITECTURE:
name: 'ResNeXt50_vd_64x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet101.yaml
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mode: 'train'
architecture: 'ResNet101'
ARCHITECTURE:
name: 'ResNet101'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet101_vd.yaml
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mode: 'train'
architecture: 'ResNet101_vd'
ARCHITECTURE:
name: 'ResNet101_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet152.yaml
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mode: 'train'
architecture: 'ResNet152'
ARCHITECTURE:
name: 'ResNet152'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet152_vd.yaml
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mode: 'train'
architecture: 'ResNet152_vd'
ARCHITECTURE:
name: 'ResNet152_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet18.yaml
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mode: 'train'
architecture: 'ResNet18'
ARCHITECTURE:
name: 'ResNet18'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet18_vd.yaml
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mode: 'train'
architecture: 'ResNet18_vd'
ARCHITECTURE:
name: 'ResNet18_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet200_vd.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'ResNet200_vd'
ARCHITECTURE:
name: 'ResNet200_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet34.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'ResNet34'
ARCHITECTURE:
name: 'ResNet34'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet34_vd.yaml
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mode: 'train'
architecture: 'ResNet34_vd'
ARCHITECTURE:
name: 'ResNet34_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet50.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'ResNet50'
ARCHITECTURE:
name: 'ResNet50'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet50_vc.yaml
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mode: 'train'
architecture: 'ResNet50_vc'
ARCHITECTURE:
name: 'ResNet50_vc'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet/ResNet50_vd.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'ResNet50_vd'
ARCHITECTURE:
name: 'ResNet50_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ResNet_ACNet/ResNet_ACNet.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: "ResNet_ACNet"
ARCHITECTURE:
name: "ResNet_ACNet"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/SENet/SENet154_vd.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'SENet154_vd'
ARCHITECTURE:
name: 'SENet154_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/SENet/SE_ResNeXt101_32x4d.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'SE_ResNeXt101_32x4d'
ARCHITECTURE:
name: 'SE_ResNeXt101_32x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/SENet/SE_ResNeXt50_32x4d.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'SE_ResNeXt50_32x4d'
ARCHITECTURE:
name: 'SE_ResNeXt50_32x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/SENet/SE_ResNeXt50_vd_32x4d.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'SE_ResNeXt50_vd_32x4d'
ARCHITECTURE:
name: 'SE_ResNeXt50_vd_32x4d'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/SENet/SE_ResNet18_vd.yaml
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@ -1,5 +1,7 @@
mode: 'train'
architecture: 'SE_ResNet18_vd'
ARCHITECTURE:
name: 'SE_ResNet18_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/SENet/SE_ResNet34_vd.yaml
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mode: 'train'
architecture: 'SE_ResNet34_vd'
ARCHITECTURE:
name: 'SE_ResNet34_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/SENet/SE_ResNet50_vd.yaml
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mode: 'train'
architecture: 'SE_ResNet50_vd'
ARCHITECTURE:
name: 'SE_ResNet50_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ShuffleNet/ShuffleNetV2.yaml
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mode: 'train'
architecture: "ShuffleNetV2"
ARCHITECTURE:
name: "ShuffleNetV2"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ShuffleNet/ShuffleNetV2_swish.yaml
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mode: 'train'
architecture: "ShuffleNetV2_swish"
ARCHITECTURE:
name: "ShuffleNetV2_swish"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ShuffleNet/ShuffleNetV2_x0_25.yaml
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mode: 'train'
architecture: "ShuffleNetV2_x0_25"
ARCHITECTURE:
name: "ShuffleNetV2_x0_25"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ShuffleNet/ShuffleNetV2_x0_33.yaml
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mode: 'train'
architecture: "ShuffleNetV2_x0_33"
ARCHITECTURE:
name: "ShuffleNetV2_x0_33"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ShuffleNet/ShuffleNetV2_x0_5.yaml
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mode: 'train'
architecture: "ShuffleNetV2_x0_5"
ARCHITECTURE:
name: "ShuffleNetV2_x0_5"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ShuffleNet/ShuffleNetV2_x1_5.yaml
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mode: 'train'
architecture: "ShuffleNetV2_x1_5"
ARCHITECTURE:
name: "ShuffleNetV2_x1_5"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/ShuffleNet/ShuffleNetV2_x2_0.yaml
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mode: 'train'
architecture: "ShuffleNetV2_x2_0"
ARCHITECTURE:
name: "ShuffleNetV2_x2_0"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/SqueezeNet/SqueezeNet1_0.yaml
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mode: 'train'
architecture: "SqueezeNet1_0"
ARCHITECTURE:
name: "SqueezeNet1_0"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/SqueezeNet/SqueezeNet1_1.yaml
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mode: 'train'
architecture: "SqueezeNet1_1"
ARCHITECTURE:
name: "SqueezeNet1_1"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/VGG/VGG11.yaml
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mode: 'train'
architecture: "VGG11"
ARCHITECTURE:
name: "VGG11"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/VGG/VGG13.yaml
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mode: 'train'
architecture: "VGG13"
ARCHITECTURE:
name: "VGG13"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/VGG/VGG16.yaml
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mode: 'train'
architecture: "VGG16"
ARCHITECTURE:
name: "VGG16"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/VGG/VGG19.yaml
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mode: 'train'
architecture: "VGG19"
ARCHITECTURE:
name: "VGG19"
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 1000

4
configs/eval.yaml
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mode: 'valid'
architecture: ""
ARCHITECTURE:
name: ""
pretrained_model: ""
classes_num: 1000
total_images: 1281167