code: def scatter(dtype, use_mpi=False):
      if dtype in "hH":
          return  # nccl does not support int16
  
      def run_scatter(rank, root, dtype, use_mpi=False):
          dev = cuda.Device(rank)
          dev.use()
          comm = NCCLBackend(N_WORKERS, rank, use_mpi=use_mpi)
          in_array = 1 + cupy.arange(N_WORKERS * 10, dtype="f").reshape(
              N_WORKERS, 10
          )
          out_array = cupy.zeros((10,), dtype="f")
  
          comm.scatter(in_array, out_array, root)
          if rank > 0:
              testing.assert_allclose(out_array, in_array[rank])
  
      if use_mpi:
          from mpi4py import MPI
  
          # This process was run with mpiexec
          run_scatter(MPI.COMM_WORLD.Get_rank(), 0, dtype, True)
          run_scatter(MPI.COMM_WORLD.Get_rank(), 1, dtype, True)
      else:
          _launch_workers(run_scatter, (0, dtype))
          _launch_workers(run_scatter, (1, dtype))
  
imports: import sys
  import time
  import warnings
  import cupy
  from cupy import cuda
  from cupy.cuda import nccl
  from cupy import testing
  from cupyx.distributed import init_process_group
  from cupyx.distributed._nccl_comm import NCCLBackend
  from cupyx.distributed._store import ExceptionAwareProcess
  from cupyx.scipy import sparse
label_desc: Use image node_id 9 for calling a global function with example usage: scatter(dtype, use_mpi) without return types