File size: 1,819 Bytes
f4bee9e | 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 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | """
Attack wrapper utilities for compatibility
"""
import torch
import torch.nn as nn
from typing import Dict, Any
def create_fgsm_attack(model: nn.Module, epsilon: float = 0.3, **kwargs):
"""Create FGSM attack with flexible parameters"""
from attacks.fgsm import FGSMAttack
try:
# Try with config dict
config = {'epsilon': epsilon, **kwargs}
return FGSMAttack(model, config)
except TypeError:
try:
# Try without config
return FGSMAttack(model)
except Exception as e:
print(f"Failed to create FGSM attack: {e}")
return None
def create_fast_cw_attack(model: nn.Module, const: float = 1.0, iterations: int = 50, **kwargs):
"""Create fast C&W attack with flexible parameters"""
from attacks.cw import FastCarliniWagnerL2
try:
# Try with config dict
config = {'const': const, 'iterations': iterations, **kwargs}
return FastCarliniWagnerL2(model, config)
except TypeError:
try:
# Try without parameters
return FastCarliniWagnerL2(model)
except Exception as e:
print(f"Failed to create C&W attack: {e}")
return None
def create_pgd_attack(model: nn.Module, epsilon: float = 0.3, alpha: float = 0.01, steps: int = 40, **kwargs):
"""Create PGD attack with flexible parameters"""
from attacks.pgd import PGDAttack
try:
# Try with config dict
config = {'epsilon': epsilon, 'alpha': alpha, 'steps': steps, **kwargs}
return PGDAttack(model, config)
except TypeError:
try:
# Try without parameters
return PGDAttack(model)
except Exception as e:
print(f"Failed to create PGD attack: {e}")
return None
|