code: def all_reduce(cls, comm, in_array, out_array, op="sum", stream=None):
      # TODO(ecastill) find a way to better determine the root, maybe random?
      # super naive algorithm
      root = 0
      cls.reduce(comm, in_array, out_array, root, op, stream)
      cls.broadcast(comm, 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 5 for calling the _SparseNCCLCommunicator obj's underlying member method code with example usage: obj.all_reduce(cls, comm, in_array, out_array, op, stream) without return types