def METHOD_NAME(test_case):
    x_list = []
    local_np = np.arange(4 * 8, dtype=float).reshape(4, 8)
    P1d = flow.placement("cuda", ranks=[0, 1, 2, 3])
    B = flow.sbp.broadcast()
    S0 = flow.sbp.split(0)
    S1 = flow.sbp.split(1)
    P = flow.sbp.partial_sum()
    in_0 = (
        flow.tensor(local_np / 4.0)
        .to(flow.device("cuda"))
        .to_global(sbp=P, placement=P1d)
    )
    flow.boxing.nccl.enable_use_compute_stream(True)
    class TestNcclFusion1DGraph(flow.nn.Graph):
        def __init__(self):
            super().__init__()
        def build(self, x):
            # fuse group 0:
            x0 = x * 0.5
            y0 = x0.to_global(sbp=B, placement=P1d)  # P->B
            x1 = x * 1.0
            y1 = x1.to_global(sbp=S0, placement=P1d)  # P->S0
            x2 = x * 2.0
            y2 = x2.to_global(sbp=S1, placement=P1d)  # P->S1
            x3 = x * 3.0
            y3 = x3.to_global(sbp=S1, placement=P1d)  # P->S1
            x4 = x * 4.0
            y4 = x4.to_global(sbp=S0, placement=P1d)  # P->S0
            # fuse group 1:
            x5 = y1 * 5.0
            y5 = x5.to_global(sbp=B, placement=P1d)  # S0->B
            x6 = y2 * (6.0 / 2.0)
            y6 = x6.to_global(sbp=B, placement=P1d)  # S1->B
            x7 = y3 * (9.0 / 3.0)
            y7 = x7.to_global(sbp=S0, placement=P1d)  # S1->S0
            x8 = y4 * (8.0 / 4.0)
            y8 = x8.to_global(sbp=S1, placement=P1d)  # S0->S1
            y = y0 + y1 + y2 + y3 + y4 + y5 + y6 + y7 + y8
            return y, y0, y1, y2, y3, y4, y5, y6, y7, y8
    graph = TestNcclFusion1DGraph()
    out, out_0, out_1, out_2, out_3, out_4, out_5, out_6, out_7, out_8 = graph(in_0)
    test_case.assertTrue(np.array_equal(out_0.numpy(), local_np * 0.5))
    test_case.assertTrue(np.array_equal(out_1.numpy(), local_np * 1.0))
    test_case.assertTrue(np.array_equal(out_2.numpy(), local_np * 2.0))
    test_case.assertTrue(np.array_equal(out_3.numpy(), local_np * 3.0))
    test_case.assertTrue(np.array_equal(out_4.numpy(), local_np * 4.0))
    test_case.assertTrue(np.array_equal(out_5.numpy(), local_np * 5.0))
    test_case.assertTrue(np.array_equal(out_6.numpy(), local_np * 6.0))
    test_case.assertTrue(np.array_equal(out_7.numpy(), local_np * 9.0))
    test_case.assertTrue(np.array_equal(out_8.numpy(), local_np * 8.0))
    flow.boxing.nccl.enable_use_compute_stream(False)