def METHOD_NAME(self, input_param, input_shape, expected_shapes):
    dsdepth = input_param.get("dsdepth", 1)
    net = SegResNetDS(**input_param).to(device)
    net.train()
    result = net(torch.randn(input_shape).to(device))
    assert isinstance(result, list)
    self.assertEqual(dsdepth, len(result))
    for i in range(dsdepth):
        self.assertEqual(result[i].shape, expected_shapes[i], msg=str(input_param))