code: def gen_execute_single_async_special(special_f):
      def execute_single_async_special(self, i, f, *args, **kwargs):
          assert len(self.workers) == 2
          if (
              i == 0
              and hasattr(self, "should_fail")
              and self.should_fail
          ):
              kwargs["train_func"] = special_f
          return (
              self.workers[i]
              .actor._RayTrainWorker__execute.options(name=f.__name__)
              .remote(f, *args, **kwargs)
          )
  
      return execute_single_async_special
  
imports: import os
  import time
  from unittest.mock import patch
  import pytest
  import ray
  from ray import train, tune
  from ray.train import RunConfig, ScalingConfig
  from ray.train._internal.backend_executor import BackendExecutor
  from ray.train._internal.worker_group import WorkerGroup
  from ray.train.backend import Backend, BackendConfig
  from ray.train.data_parallel_trainer import DataParallelTrainer
  from ray.train.tests.util import create_dict_checkpoint, load_dict_checkpoint
  from ray.tune.callback import Callback
  from ray.tune.tune_config import TuneConfig
  from ray.tune.tuner import Tuner
label_desc: Use image node_id 3 for calling a global function with example usage: gen_execute_single_async_special(special_f) and returns: execute_single_async_special, self