def METHOD_NAME():
    device = Device()
    np.random.seed(0)
    dtype = "float32"
    shapes_config = [
        [1, 2, 3, 4],
        [3, 2, 3, 4],
        [2, 2, 3],
        [16, 32, 32],
        [5, 3],
    ]
    axes = [-1, 0, 1, 2]
    for shape in shapes_config:
        for axis in axes:
            if len(shape) == 2 and axis != 0:
                continue
            for center in [False, True]:
                for scale in [False, True]:
                    outputs = []
                    inputs = {
                        "src": tvm.nd.array(np.random.uniform(-128, 127, shape).astype(dtype)),
                    }
                    func, params = _get_model(
                        shape,
                        [shape[axis]],
                        [shape[axis]],
                        dtype,
                        var_names=iter(inputs),
                        axis=axis,
                        center=center,
                        scale=scale,
                    )
                    for enable_bnns in [False, True]:
                        outputs.append(
                            build_and_run(
                                func,
                                inputs,
                                1,
                                params,
                                device,
                                enable_bnns=enable_bnns,
                            )[0]
                        )
                    config = {
                        "dtype": dtype,
                    }
                    verify(outputs, atol=0.001, rtol=0.01, config=config)