def METHOD_NAME(self) -> None:
    model = BasicModel_MultiLayer()
    add_input = torch.tensor([[-1.0, 2.0, 2.0]])
    input = torch.tensor([[1.0, 6.0, -3.0]])
    labels = torch.tensor([0])
    mask = torch.tensor([[0, 0, 1]])
    loss_func = CrossEntropyLoss(reduction="none")
    adv = FGSM(model, loss_func)
    perturbed_input = adv.perturb(
        input, 0.2, labels, additional_forward_args=(add_input,), mask=mask
    )
    assertTensorAlmostEqual(
        self, perturbed_input, [[1.0, 6.0, -3.0]], delta=0.01, mode="max"
    )