code: def test_classification_infidelity_tpl_target(self) -> None:
      model = BasicModel_MultiLayer()
      input = torch.arange(1.0, 13.0).view(4, 3)
      additional_forward_args = (
          torch.arange(1, 13).view(4, 3).float(),
          True,
      )
      targets: List = [(0, 1, 1), (0, 1, 1), (1, 1, 1), (0, 1, 1)]
      sa = Saliency(model)
  
      infid1 = self.infidelity_assert(
          model,
          sa.attribute(
              input,
              target=targets,
              additional_forward_args=additional_forward_args,
          ),
          input,
          torch.zeros(4),
          additional_args=additional_forward_args,
          target=targets,
          multi_input=False,
      )
  
      infid2 = self.infidelity_assert(
          model,
          sa.attribute(
              input,
              target=targets,
              additional_forward_args=additional_forward_args,
          ),
          input,
          torch.zeros(4),
          additional_args=additional_forward_args,
          target=targets,
          max_batch_size=2,
          multi_input=False,
      )
      assertTensorAlmostEqual(
          self, infid1, infid2, delta=1e-05, mode="max"
      )
  
imports: import typing
  from typing import Any, Callable, cast, List, Tuple, Union
  import torch
  from captum._utils.typing import BaselineType, TargetType, TensorOrTupleOfTensorsGeneric
  from captum.attr import Attribution, DeepLift, FeatureAblation, IntegratedGradients, Saliency
  from captum.metrics import infidelity, infidelity_perturb_func_decorator
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel2, BasicModel4_MultiArgs, BasicModel_ConvNet_One_Conv, BasicModel_MultiLayer
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 6 for calling the Test obj's underlying member method code with example usage: obj.test_classification_infidelity_tpl_target() without return types