code: def do_broadcast_multigpu(
      self, group_name="default", src_rank=0, src_gpu_index=0
  ):
      col.broadcast_multigpu(
          [self.buffer0, self.buffer1],
          src_rank,
          src_gpu_index,
          group_name,
      )
      return self.buffer0, self.buffer1
  
imports: import cupy
  import logging
  import ray
  import ray.util.collective
  from ray.util.collective.types import Backend, ReduceOp
  from ray.util.collective.collective_group.nccl_util import get_num_gpus
  import torch
label_desc: Use image node_id 10 for calling the MultiGPUWorker obj's underlying member method code with example usage: obj.do_broadcast_multigpu(group_name, src_rank, src_gpu_index) and returns: self,  self