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badnet folder information about trojanzoo HOT 1 CLOSED

ArshadIram commented on August 14, 2024

badnet folder information

from trojanzoo.

Comments (1)

ain-soph commented on August 14, 2024

trojanzoo/trojanvision/attacks/abstract.py

Lines 188 to 195 in 1a2adf9

    
           def save(self, filename: str = None, **kwargs): 
        
               r"""Save attack results to files.""" 
        
               filename = filename or self.get_filename(**kwargs) 
        
               file_path = os.path.join(self.folder_path, filename) 
        
               np.save(file_path + '.npy', self.mark.mark.detach().cpu().numpy()) 
        
               F.to_pil_image(self.mark.mark).save(file_path + '.png') 
        
               self.model.save(file_path + '.pth') 
        
               print('attack results saved at: ', file_path)

from trojanzoo.

Related Issues (20)

BackdoorAttack class has no argument for source_class HOT 1
Low effective loading in get_class_subset function HOT 1
Install newest version fail HOT 1
Using a custom model HOT 4
RuntimeError: Dataset not found or corrupted. You can use download=True to download it HOT 10
Clean label attack accuracy is wrong HOT 5
In new push model path is not working HOT 1
[Error] When I test Neural Cleanse i got a error HOT 2
Is it possible to apply methods to graph? HOT 6
Input aware dynamic backdoor error HOT 5
trojanvision.datasets.ImageFolder HOT 1
Possible bug: target_class not changed when computing ASR for reversed triggers HOT 2
problem about saving the intermediate results and config problem HOT 6
strange mark saved HOT 2
Hyperparameters for training Resnet18 on CIFAR10? HOT 1
STRIP implementation doesn't match original codebase HOT 1
Attack saving and loading is not working HOT 2
Comp version of networks HOT 2
Unable to Access Triggered Dataset in BadNet Attack HOT 5

badnet folder information about trojanzoo HOT 1 CLOSED

Comments (1)

Related Issues (20)

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	def save(self, filename: str = None, **kwargs):
	r"""Save attack results to files."""
	filename = filename or self.get_filename(**kwargs)
	file_path = os.path.join(self.folder_path, filename)
	np.save(file_path + '.npy', self.mark.mark.detach().cpu().numpy())
	F.to_pil_image(self.mark.mark).save(file_path + '.png')
	self.model.save(file_path + '.pth')
	print('attack results saved at: ', file_path)