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add:resnet-cifar10-classification-noisy

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  1. Image/ResNet/code/train.py +0 -59
  2. Image/ResNet/dataset/.gitkeep +0 -0
  3. Image/ResNet/model/.gitkeep +0 -0
  4. ResNet-CIFAR10/Classification-noisy/dataset/index.json +0 -0
  5. ResNet-CIFAR10/Classification-noisy/dataset/info.json +4 -0
  6. ResNet-CIFAR10/Classification-noisy/dataset/labels.npy +3 -0
  7. ResNet-CIFAR10/Classification-noisy/dataset/noise_index.npy +3 -0
  8. ResNet-CIFAR10/Classification-noisy/epochs/epoch_1/embeddings.npy +3 -0
  9. ResNet-CIFAR10/Classification-noisy/epochs/epoch_1/model.pth +3 -0
  10. ResNet-CIFAR10/Classification-noisy/epochs/epoch_1/predictions.npy +3 -0
  11. ResNet-CIFAR10/Classification-noisy/epochs/epoch_10/embeddings.npy +3 -0
  12. ResNet-CIFAR10/Classification-noisy/epochs/epoch_10/model.pth +3 -0
  13. ResNet-CIFAR10/Classification-noisy/epochs/epoch_10/predictions.npy +3 -0
  14. ResNet-CIFAR10/Classification-noisy/epochs/epoch_12/embeddings.npy +3 -0
  15. ResNet-CIFAR10/Classification-noisy/epochs/epoch_12/model.pth +3 -0
  16. ResNet-CIFAR10/Classification-noisy/epochs/epoch_12/predictions.npy +3 -0
  17. ResNet-CIFAR10/Classification-noisy/epochs/epoch_14/embeddings.npy +3 -0
  18. ResNet-CIFAR10/Classification-noisy/epochs/epoch_14/model.pth +3 -0
  19. ResNet-CIFAR10/Classification-noisy/epochs/epoch_14/predictions.npy +3 -0
  20. ResNet-CIFAR10/Classification-noisy/epochs/epoch_16/embeddings.npy +3 -0
  21. ResNet-CIFAR10/Classification-noisy/epochs/epoch_16/model.pth +3 -0
  22. ResNet-CIFAR10/Classification-noisy/epochs/epoch_16/predictions.npy +3 -0
  23. ResNet-CIFAR10/Classification-noisy/epochs/epoch_18/embeddings.npy +3 -0
  24. ResNet-CIFAR10/Classification-noisy/epochs/epoch_18/model.pth +3 -0
  25. ResNet-CIFAR10/Classification-noisy/epochs/epoch_18/predictions.npy +3 -0
  26. ResNet-CIFAR10/Classification-noisy/epochs/epoch_2/embeddings.npy +3 -0
  27. ResNet-CIFAR10/Classification-noisy/epochs/epoch_2/model.pth +3 -0
  28. ResNet-CIFAR10/Classification-noisy/epochs/epoch_2/predictions.npy +3 -0
  29. ResNet-CIFAR10/Classification-noisy/epochs/epoch_20/embeddings.npy +3 -0
  30. ResNet-CIFAR10/Classification-noisy/epochs/epoch_20/model.pth +3 -0
  31. ResNet-CIFAR10/Classification-noisy/epochs/epoch_20/predictions.npy +3 -0
  32. ResNet-CIFAR10/Classification-noisy/epochs/epoch_22/embeddings.npy +3 -0
  33. ResNet-CIFAR10/Classification-noisy/epochs/epoch_22/model.pth +3 -0
  34. ResNet-CIFAR10/Classification-noisy/epochs/epoch_22/predictions.npy +3 -0
  35. ResNet-CIFAR10/Classification-noisy/epochs/epoch_24/embeddings.npy +3 -0
  36. ResNet-CIFAR10/Classification-noisy/epochs/epoch_24/model.pth +3 -0
  37. ResNet-CIFAR10/Classification-noisy/epochs/epoch_24/predictions.npy +3 -0
  38. ResNet-CIFAR10/Classification-noisy/epochs/epoch_26/embeddings.npy +3 -0
  39. ResNet-CIFAR10/Classification-noisy/epochs/epoch_26/model.pth +3 -0
  40. ResNet-CIFAR10/Classification-noisy/epochs/epoch_26/predictions.npy +3 -0
  41. ResNet-CIFAR10/Classification-noisy/epochs/epoch_28/embeddings.npy +3 -0
  42. ResNet-CIFAR10/Classification-noisy/epochs/epoch_28/model.pth +3 -0
  43. ResNet-CIFAR10/Classification-noisy/epochs/epoch_28/predictions.npy +3 -0
  44. ResNet-CIFAR10/Classification-noisy/epochs/epoch_30/embeddings.npy +3 -0
  45. ResNet-CIFAR10/Classification-noisy/epochs/epoch_30/model.pth +3 -0
  46. ResNet-CIFAR10/Classification-noisy/epochs/epoch_30/predictions.npy +3 -0
  47. ResNet-CIFAR10/Classification-noisy/epochs/epoch_32/embeddings.npy +3 -0
  48. ResNet-CIFAR10/Classification-noisy/epochs/epoch_32/model.pth +3 -0
  49. ResNet-CIFAR10/Classification-noisy/epochs/epoch_32/predictions.npy +3 -0
  50. ResNet-CIFAR10/Classification-noisy/epochs/epoch_34/embeddings.npy +3 -0
Image/ResNet/code/train.py DELETED
@@ -1,59 +0,0 @@
1
- import sys
2
- import os
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- sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
4
- from utils.dataset_utils import get_cifar10_dataloaders
5
- from utils.train_utils import train_model, train_model_data_augmentation, train_model_backdoor
6
- from utils.parse_args import parse_args
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- from model import ResNet34
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-
9
- def main():
10
- # 解析命令行参数
11
- args = parse_args()
12
-
13
- # 创建模型
14
- model = ResNet34()
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-
16
- if args.train_type == '0':
17
- # 获取数据加载器
18
- trainloader, testloader = get_cifar10_dataloaders(batch_size=args.batch_size, local_dataset_path=args.dataset_path)
19
- # 训练模型
20
- train_model(
21
- model=model,
22
- trainloader=trainloader,
23
- testloader=testloader,
24
- epochs=args.epochs,
25
- lr=args.lr,
26
- device=f'cuda:{args.gpu}',
27
- save_dir='../model',
28
- model_name='resnet',
29
- save_type='0'
30
- )
31
- elif args.train_type == '1':
32
- train_model_data_augmentation(
33
- model,
34
- epochs=args.epochs,
35
- lr=args.lr,
36
- device=f'cuda:{args.gpu}',
37
- save_dir='../model',
38
- model_name='resnet',
39
- batch_size=args.batch_size,
40
- num_workers=args.num_workers,
41
- local_dataset_path=args.dataset_path
42
- )
43
- elif args.train_type == '2':
44
- train_model_backdoor(
45
- model,
46
- poison_ratio=args.poison_ratio,
47
- target_label=args.target_label,
48
- epochs=args.epochs,
49
- lr=args.lr,
50
- device=f'cuda:{args.gpu}',
51
- save_dir='../model',
52
- model_name='resnet',
53
- batch_size=args.batch_size,
54
- num_workers=args.num_workers,
55
- local_dataset_path=args.dataset_path
56
- )
57
-
58
- if __name__ == '__main__':
59
- main()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Image/ResNet/dataset/.gitkeep DELETED
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Image/ResNet/model/.gitkeep DELETED
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ResNet-CIFAR10/Classification-noisy/dataset/index.json ADDED
The diff for this file is too large to render. See raw diff
 
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+ "model": "ResNet18",
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+ "classes":["airplane", "automobile", "bird", "cat", "deer", "dog", "frog", "horse", "ship", "truck"]
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+ }
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