attacks/privacy_attacks.py [572:584]:
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            images=torch.stack([dataset[i][0] for i in ids])
            images=images.cuda()

            log_softmax = torch.nn.LogSoftmax(dim=1)
        
            output=private_model(images)
            attack_output=attack_model(images)
        
            log_output=log_softmax(output)
            log_attack_output=log_softmax(attack_output)
        
            private_confidences,_=torch.max(log_output,dim=1)
            attack_confidences,_=torch.max(log_attack_output,dim=1)
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attacks/privacy_attacks.py [599:611]:
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        images=torch.stack([dataset[i][0] for i in ids])
        images=images.cuda()

        log_softmax = torch.nn.LogSoftmax(dim=1)
    
        output=private_model(images)
        attack_output=attack_model(images)
    
        log_output=log_softmax(output)
        log_attack_output=log_softmax(attack_output)
    
        private_confidences,_=torch.max(log_output,dim=1)
        attack_confidences,_=torch.max(log_attack_output,dim=1)
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