def METHOD_NAME(self) -> None:
    input = 100 * torch.randn(2, 1, 10, 10, 10, requires_grad=True)
    baseline = 600 * torch.randn(2, 1, 10, 10, 10)
    model = BasicModel_ConvNet_MaxPool3d()
    dl = DeepLift(model)
    self.softmax_classification(model, dl, input, baseline, torch.tensor(2))