code: def function_trainable(config):
      with create_dict_checkpoint({"checkpoint_data": 5}) as checkpoint:
          train.report({"metric": 4}, checkpoint=checkpoint)
  
imports: import json
  import os
  from typing import Dict, Union
  import pytest
  import ray
  from ray import train, tune
  from ray.train._internal.storage import StorageContext
  from ray.tune.trainable import wrap_function
  from ray.train.tests.util import create_dict_checkpoint
label_desc: Use image node_id 2 for calling a global function with example usage: function_trainable(config) without return types