code: def _flatten_for_scatter_gather(tensor_list, copy=False):
      """Flatten the tensor for gather/scatter operations.
  
      Args:
          tensor_list: the list of tensors to be scattered/gathered.
          copy: whether the copy the tensors in tensor_list into the buffer.
  
      Returns:
          The flattened tensor buffer.
      """
      if not tensor_list:
          raise RuntimeError("Received an empty list.")
      t = tensor_list[0]
      # note we need a cupy dtype here.
      dtype = nccl_util.get_cupy_tensor_dtype(t)
      buffer_shape = [len(tensor_list)] + nccl_util.get_tensor_shape(t)
      device = nccl_util.get_tensor_device(t)
      with nccl_util.Device(device):
          buffer = cupy.empty(buffer_shape, dtype=dtype)
      if copy:
          for i, tensor in enumerate(tensor_list):
              nccl_util.copy_tensor(buffer[i], tensor)
      return buffer
  
imports: import logging
  import datetime
  import time
  import ray
  import cupy
  from ray.util.collective.const import ENV
  from ray.util.collective.collective_group import nccl_util
  from ray.util.collective.collective_group.base_collective_group import BaseGroup
  from ray.util.collective.const import get_store_name
  from ray.util.collective.types import AllReduceOptions, BarrierOptions, Backend, ReduceOptions, BroadcastOptions, AllGatherOptions, ReduceScatterOptions, SendOptions, RecvOptions
  from ray.util.collective.collective_group.cuda_stream import get_stream_pool
label_desc: Use image node_id 1 for calling a global function with example usage: _flatten_for_scatter_gather(tensor_list, copy) and returns: buffer