code: def alt_perturb_func(
      original_inp: TensorOrTupleOfTensorsGeneric, **kwargs
  ) -> TensorOrTupleOfTensorsGeneric:
      if isinstance(original_inp, Tensor):
          device = original_inp.device
      else:
          device = original_inp[0].device
  
      feature_mask = kwargs["feature_mask"]
  
      probs = torch.ones(1, kwargs["num_interp_features"]) * 0.5
      curr_sample = torch.bernoulli(probs).to(device=device)
  
      binary_mask: TensorOrTupleOfTensorsGeneric
      if isinstance(original_inp, Tensor):
          binary_mask = curr_sample[0][feature_mask]
          return (
              binary_mask * original_inp
              + (1 - binary_mask) * kwargs["baselines"]
          )
      else:
          binary_mask = tuple(
              curr_sample[0][feature_mask[j]]
              for j in range(len(feature_mask))
          )
          return tuple(
              binary_mask[j] * original_inp[j]
              + (1 - binary_mask[j]) * kwargs["baselines"][j]
              for j in range(len(feature_mask))
          )
  
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 1 for calling a global function with example usage: alt_perturb_func(original_inp) and returns: unknown, tuple