code: def test_simple_batch_lime_with_mask(self) -> None:
      net = BasicModel_MultiLayer()
      inp = torch.tensor(
          [[20.0, 50.0, 30.0], [10.0, 14.0, 4.0]], requires_grad=True
      )
      self._lime_test_assert(
          net,
          inp,
          [[271.0, 271.0, 111.0], [32.11, 48.00, 11.00]],
          feature_mask=torch.tensor([[0, 0, 1], [0, 1, 2]]),
          perturbations_per_eval=(1, 2, 3),
          n_samples=600,
          expected_coefs_only=[
              [271.0, 111.0, 0.0],
              [32.11, 48.00, 11.00],
          ],
          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 10 for calling the Test obj's underlying member method code with example usage: obj.test_simple_batch_lime_with_mask() without return types