state_dict = torch.load(args.eval_poison_path)
poison_tuple_list, base_idx_list = state_dict['poison'], state_dict[
'idx']
print("=" * 100)
print("=" * 100)
print("Poisons loaded")
print("Now evaluating on the target nets")
t = 0
tt = 0
else:
print(args)
print("Path: {}".format(chk_path))
# Otherwise, we craft new poisons
if args.nearest:
base_tensor_list, base_idx_list = fetch_nearest_poison_bases(
sub_net_list, target, args.poison_num, args.poison_label,
args.num_per_class, 'others', args.train_data_path,
transform_test)
else:
# just fetch the first poison_num samples
base_tensor_list, base_idx_list = fetch_poison_bases(
args.poison_label,
args.poison_num,
subset='others',
path=args.train_data_path,
transforms=transform_test)
base_tensor_list = [bt.to('cuda') for bt in base_tensor_list]
print("Selected base image indices: {}".format(base_idx_list))
if args.resume_poison_ite > 0:
state_dict = torch.load(
print("=" * 100)
print("=" * 100)
print("Poisons loaded")
print("Now evaluating on the target nets")
t = 0
tt = 0
assert False, "ToDo: check here!"
else:
print(args)
print("Path: {}".format(chk_path))
# Otherwise, we craft new poisons
if args.nearest:
base_tensor_list, base_idx_list = \
fetch_nearest_poison_bases(sub_net_list, targets, args.poison_num,
args.poison_label, args.num_per_class, subset='others',
train_data_path=args.train_data_path, transforms=transform_test, )
else:
# just fetch the first poison_num samples
base_tensor_list, base_idx_list = fetch_poison_bases(args.poison_label, args.poison_num, subset='others',
path=args.train_data_path, transforms=transform_test)
base_tensor_list = [bt.to(args.device) for bt in base_tensor_list]
print("Selected base image indices: {}".format(base_idx_list))
print("Target indices: {}".format(targets_indices))
print("# Targets: {}, # Poisons: {}".format(len(targets), len(base_tensor_list)))
if args.resume_poison_ite > 0:
state_dict = torch.load(os.path.join(chk_path, "poison_%05d.pth" % args.resume_poison_ite))
poison_tuple_list, base_idx_list = state_dict['poison'], state_dict['idx']
poison_init = [pt.to('cuda') for pt, _ in poison_tuple_list]