code: def _assert_shap_ig_comparision(
      self,
      attributions1: Tuple[Tensor, ...],
      attributions2: Tuple[Tensor, ...],
  ) -> None:
      for attribution1, attribution2 in zip(
          attributions1, attributions2
      ):
          for attr_row1, attr_row2 in zip(attribution1, attribution2):
              assertTensorAlmostEqual(
                  self, attr_row1, attr_row2, 0.05, "max"
              )
  
file_path: captum/tests/attr/test_gradient_shap.py
imports: from typing import cast, Tuple, Union
  import numpy
  import torch
  from captum._utils.typing import Tensor
  from captum.attr._core.gradient_shap import GradientShap
  from captum.attr._core.integrated_gradients import IntegratedGradients
  from numpy import ndarray
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicLinearModel, BasicModel2
  from tests.helpers.classification_models import SoftmaxModel
label_desc: Use image node_id 6 for calling the Test obj's underlying member method code with example usage: obj._assert_shap_ig_comparision(attributions1, attributions2) without return types