add VGG-CIFAR10

Image/SwinTransformer/code/train.py

@@ -1,59 +0,0 @@
-import sys
-import os
-sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
-from utils.dataset_utils import get_cifar10_dataloaders
-from utils.train_utils import train_model, train_model_data_augmentation, train_model_backdoor
-from utils.parse_args import parse_args
-from model import SwinTransformer
-
-def main():
-    # 解析命令行参数
-    args = parse_args()
-    
-    # 创建模型
-    model = SwinTransformer()
-    
-    if args.train_type == '0':
-        # 获取数据加载器
-        trainloader, testloader = get_cifar10_dataloaders(batch_size=args.batch_size, local_dataset_path=args.dataset_path)
-        # 训练模型
-        train_model(
-            model=model,
-            trainloader=trainloader,
-            testloader=testloader,
-            epochs=args.epochs,
-            lr=args.lr,
-            device=f'cuda:{args.gpu}',
-            save_dir='../model',
-            model_name='swintransformer',
-            save_type='0'
-        )
-    elif args.train_type == '1':
-        train_model_data_augmentation(
-            model, 
-            epochs=args.epochs, 
-            lr=args.lr, 
-            device=f'cuda:{args.gpu}', 
-            save_dir='../model', 
-            model_name='swintransformer',
-            batch_size=args.batch_size, 
-            num_workers=args.num_workers,
-            local_dataset_path=args.dataset_path
-        )
-    elif args.train_type == '2':
-        train_model_backdoor(
-            model, 
-            poison_ratio=args.poison_ratio, 
-            target_label=args.target_label, 
-            epochs=args.epochs, 
-            lr=args.lr,
-            device=f'cuda:{args.gpu}', 
-            save_dir='../model', 
-            model_name='swintransformer',
-            batch_size=args.batch_size, 
-            num_workers=args.num_workers,
-            local_dataset_path=args.dataset_path
-        )
-
-if __name__ == '__main__':
-    main()

Image/VGG/code/train.py

@@ -1,59 +0,0 @@
-import sys
-import os
-sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
-from utils.dataset_utils import get_cifar10_dataloaders
-from utils.train_utils import train_model, train_model_data_augmentation, train_model_backdoor
-from utils.parse_args import parse_args
-from model import VGG
-
-def main():
-    # 解析命令行参数
-    args = parse_args()
-    
-    # 创建模型
-    model = VGG()
-    
-    if args.train_type == '0':
-        # 获取数据加载器
-        trainloader, testloader = get_cifar10_dataloaders(batch_size=args.batch_size, local_dataset_path=args.dataset_path)
-        # 训练模型
-        train_model(
-            model=model,
-            trainloader=trainloader,
-            testloader=testloader,
-            epochs=args.epochs,
-            lr=args.lr,
-            device=f'cuda:{args.gpu}',
-            save_dir='../model',
-            model_name='vgg',
-            save_type='0'
-        )
-    elif args.train_type == '1':
-        train_model_data_augmentation(
-            model, 
-            epochs=args.epochs, 
-            lr=args.lr, 
-            device=f'cuda:{args.gpu}', 
-            save_dir='../model', 
-            model_name='vgg',
-            batch_size=args.batch_size, 
-            num_workers=args.num_workers,
-            local_dataset_path=args.dataset_path
-        )
-    elif args.train_type == '2':
-        train_model_backdoor(
-            model, 
-            poison_ratio=args.poison_ratio, 
-            target_label=args.target_label, 
-            epochs=args.epochs, 
-            lr=args.lr,
-            device=f'cuda:{args.gpu}', 
-            save_dir='../model', 
-            model_name='vgg',
-            batch_size=args.batch_size, 
-            num_workers=args.num_workers,
-            local_dataset_path=args.dataset_path
-        )
-
-if __name__ == '__main__':
-    main()

SwinTransformer-CIFAR10/Classification-backdoor/dataset/backdoor_index.npy

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SwinTransformer-CIFAR10/Classification-backdoor/dataset/info.json

@@ -0,0 +1,4 @@
+{
+    "model": "SwinTransformer",
+    "classes":["airplane", "automobile", "bird", "cat", "deer", "dog", "frog", "horse", "ship", "truck"]
+}

SwinTransformer-CIFAR10/Classification-backdoor/dataset/labels.npy

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SwinTransformer-CIFAR10/Classification-backdoor/epochs/epoch_1/embeddings.npy

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SwinTransformer-CIFAR10/Classification-backdoor/epochs/epoch_1/model.pth

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SwinTransformer-CIFAR10/Classification-backdoor/epochs/epoch_1/predictions.npy

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SwinTransformer-CIFAR10/Classification-backdoor/epochs/epoch_10/embeddings.npy

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SwinTransformer-CIFAR10/Classification-backdoor/epochs/epoch_10/model.pth

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SwinTransformer-CIFAR10/Classification-backdoor/epochs/epoch_12/embeddings.npy

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SwinTransformer-CIFAR10/Classification-backdoor/epochs/epoch_14/embeddings.npy

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SwinTransformer-CIFAR10/Classification-backdoor/epochs/epoch_16/embeddings.npy

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