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4113c4d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | import torchvision
import torch
from torchvision import datasets
from torchvision import transforms
import os
from deeprobust.image.attack.pgd import PGD
from deeprobust.image.config import attack_params
val_root = '/mnt/home/liyaxin1/Documents/data/ImageNet'
#Imagenet_data = torchvision.datasets.ImageNet(val_root, split = 'val')
test_loader = torch.utils.data.DataLoader(datasets.ImageFolder('~/Documents/data/ImageNet/val', transforms.Compose([
transforms.Scale(256), transforms.CenterCrop(224), transforms.ToTensor(),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])), batch_size=1, shuffle=False)
#import torchvision.models as models
#model = models.resnet50(pretrained=True).to('cuda')
import pretrainedmodels
model = pretrainedmodels.resnet50(num_classes=1000, pretrained='imagenet').to('cuda')
for i, (input, y) in enumerate(test_loader):
import ipdb
ipdb.set_trace()
input, y = input.to('cuda'), y.to('cuda')
pred = model(input)
print(pred.argmax(dim=1, keepdim = True))
adversary = PGD(model)
AdvExArray = adversary.generate(input, y, **attack_params['PGD_CIFAR10']).float()
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