code: def test_multi_input_batch_lime(self) -> None:
      net = BasicModel_MultiLayer_MultiInput()
      inp1 = torch.tensor([[23.0, 100.0, 0.0], [20.0, 50.0, 30.0]])
      inp2 = torch.tensor([[20.0, 50.0, 30.0], [0.0, 100.0, 0.0]])
      inp3 = torch.tensor([[0.0, 100.0, 10.0], [2.0, 10.0, 3.0]])
      mask1 = torch.tensor([[1, 1, 1], [0, 1, 0]])
      mask2 = torch.tensor([[0, 1, 2]])
      mask3 = torch.tensor([[0, 1, 2], [0, 0, 0]])
      expected = (
          [
              [1086.2802, 1086.2802, 1086.2802],
              [250.8907, 590.9789, 250.8907],
          ],
          [
              [73.2166, 1086.2802, 152.6888],
              [250.8907, 590.9789, 0.0000],
          ],
          [
              [73.2166, 1086.2802, 152.6888],
              [250.8907, 250.8907, 250.8907],
          ],
      )
      self._lime_test_assert(
          net,
          (inp1, inp2, inp3),
          expected,
          additional_input=(1,),
          feature_mask=(mask1, mask2, mask3),
      )
      expected_with_baseline = (
          [
              [1036.4233, 1036.4233, 1036.4233],
              [180.3035, 575.8969, 180.3035],
          ],
          [
              [48.2441, 1036.4233, 128.3161],
              [180.3035, 575.8969, -8.3229],
          ],
          [
              [48.2441, 1036.4233, 128.3161],
              [180.3035, 180.3035, 180.3035],
          ],
      )
      self._lime_test_assert(
          net,
          (inp1, inp2, inp3),
          expected_with_baseline,
          additional_input=(1,),
          feature_mask=(mask1, mask2, mask3),
          baselines=(2, 3.0, 4),
          perturbations_per_eval=(1, 2, 3),
          expected_coefs_only=[
              [48.2441, 1036.4233, 128.3161],
              [180.3035, 575.8969, -8.3229],
          ],
          n_samples=500,
          test_generator=True,
      )
  
imports: import io
  import unittest
  import unittest.mock
  from functools import partial
  from typing import Any, Callable, Generator, List, Optional, Tuple, Union
  import torch
  from captum._utils.models.linear_model import SGDLasso, SkLearnLasso
  from captum._utils.models.model import Model
  from captum._utils.typing import BaselineType, TensorOrTupleOfTensorsGeneric
  from captum.attr._core.lime import get_exp_kernel_similarity_function, Lime, LimeBase
  from captum.attr._utils.batching import _batch_example_iterator
  from captum.attr._utils.common import _construct_default_feature_mask, _format_input_baseline, _format_tensor_into_tuples
  from tests.helpers.basic import assertTensorAlmostEqual, assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicLinearModel, BasicModel_MultiLayer, BasicModel_MultiLayer_MultiInput, BasicModelBoolInput
  from torch import Tensor
label_desc: Use image node_id 15 for calling the Test obj's underlying member method code with example usage: obj.test_multi_input_batch_lime() without return types