code: def _deconv_test_assert(
      self,
      model: Module,
      test_input: TensorOrTupleOfTensorsGeneric,
      expected: Tuple[torch.Tensor, ...],
      additional_input: Any = None,
  ) -> None:
      deconv = Deconvolution(model)
      attributions = deconv.attribute(
          test_input, target=0, additional_forward_args=additional_input
      )
      for i in range(len(test_input)):
          assertTensorAlmostEqual(
              self, attributions[i], expected[i], delta=0.01
          )
  
imports: from __future__ import print_function
  import unittest
  from typing import Any, Tuple, Union
  import torch
  from captum._utils.typing import TensorOrTupleOfTensorsGeneric
  from captum.attr._core.guided_backprop_deconvnet import Deconvolution
  from captum.attr._core.neuron.neuron_guided_backprop_deconvnet import NeuronDeconvolution
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet_One_Conv
  from torch.nn import Module
label_desc: Use image node_id 7 for calling the Test obj's underlying member method code with example usage: obj._deconv_test_assert(model, test_input, expected, additional_input) without return types