code: def test_attack_loss_defined(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])
      loss_func = CrossEntropyLoss(reduction="none")
      adv = FGSM(model, loss_func)
      perturbed_input = adv.perturb(
          input, 0.2, labels, additional_forward_args=(add_input,)
      )
      assertTensorAlmostEqual(
          self,
          perturbed_input,
          [[1.0, 6.0, -3.0]],
          delta=0.01,
          mode="max",
      )
  
imports: from typing import Any, Callable, List, Optional, Tuple, Union
  import torch
  from captum._utils.typing import TensorLikeList, TensorOrTupleOfTensorsGeneric
  from captum.robust import FGSM
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel, BasicModel2, BasicModel_MultiLayer
  from torch import Tensor
  from torch.nn import CrossEntropyLoss
label_desc: Use image node_id 9 for calling the Test obj's underlying member method code with example usage: obj.test_attack_loss_defined() without return types