def METHOD_NAME(
    self,
    model: Module,
    layer: Module,
    neuron_selector: Union[int, Tuple[Union[int, slice], ...]],
    test_input: TensorOrTupleOfTensorsGeneric,
    expected: Tuple[torch.Tensor, ...],
    additional_input: Any = None,
) -> None:
    deconv = NeuronDeconvolution(model, layer)
    attributions = deconv.attribute(
        test_input,
        neuron_selector=neuron_selector,
        additional_forward_args=additional_input,
    )
    for i in range(len(test_input)):
        assertTensorAlmostEqual(self, attributions[i], expected[i], delta=0.01)