def METHOD_NAME(setup_cluster):
    import dask.array as da
    from numpy.core.numeric import array_equal
    x = da.random.random((10000, 10000), chunks=(1000, 1000))
    y = x + x.T
    z = y[::2, 5000:].mean(axis=1)
    dask_res = z.compute()
    assert array_equal(dask_res, z.compute(scheduler=mars_scheduler))
    assert array_equal(dask_res, convert_dask_collection(z).execute().fetch())