def METHOD_NAME(
    self,
    model: Module,
    target_layer: Module,
    test_input: TensorOrTupleOfTensorsGeneric,
    test_neuron: Union[int, Tuple[Union[int, slice], ...], Callable],
    expected_input_ig: Union[TensorLikeList, Tuple[TensorLikeList, ...]],
    additional_input: Any = None,
    multiply_by_inputs: bool = True,
) -> None:
    for internal_batch_size in [None, 5, 20]:
        grad = NeuronIntegratedGradients(
            model, target_layer, multiply_by_inputs=multiply_by_inputs
        )
        self.assertEquals(grad.multiplies_by_inputs, multiply_by_inputs)
        attributions = grad.attribute(
            test_input,
            test_neuron,
            n_steps=200,
            method="gausslegendre",
            additional_forward_args=additional_input,
            internal_batch_size=internal_batch_size,
        )
        assertTensorTuplesAlmostEqual(
            self, attributions, expected_input_ig, delta=0.1
        )