code: def test_attack_masked_multiinput(self) -> None:
      model = BasicModel2()
      input1 = torch.tensor(
          [[4.0, -1.0], [3.0, 10.0]], requires_grad=True
      )
      input2 = torch.tensor(
          [[2.0, -5.0], [-2.0, 1.0]], requires_grad=True
      )
      mask1 = torch.tensor([[1, 0], [1, 0]])
      mask2 = torch.tensor([[0, 0], [0, 0]])
      self._FGSM_assert(
          model,
          (input1, input2),
          0,
          0.25,
          ([[3.75, -1.0], [2.75, 10.0]], [[2.0, -5.0], [-2.0, 1.0]]),
          mask=(mask1, mask2),
      )
  
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 12 for calling the Test obj's underlying member method code with example usage: obj.test_attack_masked_multiinput() without return types