code: def reduce_scatter(
      cls, comm, in_array, out_array, count, op="sum", stream=None
  ):
      # We need a LIST of sparse in_arrays and perform a reduction for each
      # of the entries, then we will scatter that result
      root = 0
      reduce_out_arrays = []
      if not isinstance(in_array, (list, tuple)):
          raise ValueError(
              "in_array must be a list or a tuple of sparse matrices"
          )
      for s_m in in_array:
          partial_out_array = _make_sparse_empty(
              s_m.dtype, _get_sparse_type(s_m)
          )
          cls.reduce(comm, s_m, partial_out_array, root, op, stream)
          reduce_out_arrays.append(partial_out_array)
      cls.scatter(comm, reduce_out_arrays, out_array, root, stream)
  
imports: import numpy
  import warnings
  import cupy
  from cupy.cuda import nccl
  from cupyx.distributed import _store
  from cupyx.distributed._comm import _Backend
  from cupyx.scipy import sparse
label_desc: Use image node_id 8 for calling the _SparseNCCLCommunicator obj's underlying member method code with example usage: obj.reduce_scatter(cls, comm, in_array, out_array, count, op, stream) without return types