from textattack.constraints.pre_transformation import (
    InputColumnModification,
    RepeatModification,
    StopwordModification,
)
from textattack.goal_functions import UntargetedClassification
from textattack.search_methods import PSOAlgorithm
from textattack.shared.attack import Attack
from textattack.transformations import WordSwapEmbedding, WordSwapHowNet


def PSOZang2020(model):
    """
        Zang, Y., Yang, C., Qi, F., Liu, Z., Zhang, M., Liu, Q., & Sun, M. (2019).
        
        Word-level Textual Adversarial Attacking as Combinatorial Optimization.
        
        https://www.aclweb.org/anthology/2020.acl-main.540.pdf

        Methodology description quoted from the paper:

        "We propose a novel word substitution-based textual attack model, which reforms
        both the aforementioned two steps. In the first step, we adopt a sememe-based word
        substitution strategy, which can generate more candidate adversarial examples with
        better semantic preservation. In the second step, we utilize particle swarm optimization
        (Eberhart and Kennedy, 1995) as the adversarial example searching algorithm."

        And "Following the settings in Alzantot et al. (2018), we set the max iteration time G to 20."
    """
    #
    # Swap words with their synonyms extracted based on the HowNet.
    #
    transformation = WordSwapHowNet()
    #
    # Don't modify the same word twice or stopwords
    #
    constraints = [RepeatModification(), StopwordModification()]
    #
    #
    # During entailment, we should only edit the hypothesis - keep the premise
    # the same.
    #
    input_column_modification = InputColumnModification(
        ["premise", "hypothesis"], {"premise"}
    )
    constraints.append(input_column_modification)
    #
    # Use untargeted classification for demo, can be switched to targeted one
    #
    goal_function = UntargetedClassification(model)
    #
    # Perform word substitution with a Particle Swarm Optimization (PSO) algorithm.
    #
    search_method = PSOAlgorithm(pop_size=60, max_iters=20)

    return Attack(goal_function, constraints, transformation, search_method)