OpenBackdoor

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from typing import *
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from openbackdoor.victims import Victim
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from openbackdoor.data import get_dataloader, wrap_dataset
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from .poisoners import load_poisoner
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from openbackdoor.trainers import load_trainer
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from openbackdoor.utils import evaluate_classification
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from openbackdoor.defenders import Defender
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from .attacker import Attacker
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import torch
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import torch.nn as nn
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class SOSAttacker(Attacker):
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    r"""
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        Attacker for `SOS <https://aclanthology.org/2021.acl-long.431>`_
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    """
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    def __init__(self, **kwargs):
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        super().__init__(**kwargs)
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    def attack(self, victim: Victim, dataset: List, config: Optional[dict] = None, defender: Optional[Defender] = None):
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        clean_model = self.train(victim, dataset)
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        poison_dataset = self.poison(clean_model, dataset, "train")
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        if defender is not None and defender.pre is True:
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            # pre tune defense
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            poison_dataset = defender.defend(data=poison_dataset)
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        backdoored_model = self.sos_train(clean_model, poison_dataset)
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        return backdoored_model
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    def sos_train(self, victim: Victim, dataset: List):
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        """
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        sos training
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        """
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        return self.poison_trainer.sos_train(victim, dataset, self.metrics)
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