code: def _tf_device(device_option):
      """
      Handle the devices.
  
      Args:
          device_option (caffe2_pb2.DeviceOption): DeviceOption protobuf,
              associated to an operator, that contains information such as
              device_type (optional), cuda_gpu_id (optional), node_name (optional,
              tells which node the operator should execute on). See caffe2.proto
              in caffe2/proto for the full list.
  
      Returns:
          Formatted string representing device information contained in
              device_option.
      """
      if not device_option.HasField("device_type"):
          return ""
      if (
          device_option.device_type == caffe2_pb2.CPU
          or device_option.device_type == caffe2_pb2.MKLDNN
      ):
          return "/cpu:*"
      if device_option.device_type == caffe2_pb2.CUDA:
          return f"/gpu:{device_option.device_id}"
      raise Exception("Unhandled device", device_option)
  
imports: import copy
  import logging
  import os
  import re
  from tensorboard.compat.proto.graph_pb2 import GraphDef
  from tensorboard.compat.proto.node_def_pb2 import NodeDef
  from tensorboard.compat.proto.tensor_shape_pb2 import TensorShapeProto
  from caffe2.proto import caffe2_pb2
  from caffe2.python import core, workspace
  from typing import Set, Dict, Tuple, List
label_desc: Use image node_id 10 for calling a global function with example usage: _tf_device(device_option) and returns: str, str, str, device_option