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, 1], [0, 0]])
      mask2 = torch.tensor([[0, 1], [0, 1]])
      adv = PGD(model)
      perturbed_input = adv.perturb(
          (input1, input2),
          0.25,
          0.1,
          3,
          0,
          norm="L2",
          mask=(mask1, mask2),
      )
      answer = ([[3.75, -1.0], [3.0, 10.0]], [[2.0, -5.0], [-2.0, 1.0]])
      for i in range(len(perturbed_input)):
          assertTensorAlmostEqual(
              self,
              perturbed_input[i],
              answer[i],
              delta=0.01,
              mode="max",
          )
  
file_path: captum/tests/robust/test_PGD.py
imports: import torch
  from captum.robust import PGD
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel, BasicModel2, BasicModel_MultiLayer
  from torch.nn import CrossEntropyLoss
label_desc: Use image node_id 10 for calling the Test obj's underlying member method code with example usage: obj.test_attack_masked_multiinput() without return types