code: def convert_to_distributed_tensor(
      tensor: torch.Tensor,
  ) -> Tuple[torch.Tensor, str]:
      """
      For some backends, such as NCCL, communication only works if the
      tensor is on the GPU. This helper function converts to the correct
      device and returns the tensor + original device.
      """
      orig_device = "cpu" if not tensor.is_cuda else "gpu"
      if (
          torch.distributed.is_available()
          and torch.distributed.get_backend()
          == torch.distributed.Backend.NCCL
          and not tensor.is_cuda
      ):
          tensor = tensor.cuda()
      return (tensor, orig_device)
  
imports: import io
  import tempfile
  from typing import Any, Callable, List, Tuple
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: convert_to_distributed_tensor(tensor) and returns: tensor,  orig_device