code: def worker(
      num_epochs: int = 4,
      num_workers: int = 4,
      rank: int = 0,
      worker_ip_ports: str = "",
      batch_size: int = 64,
      use_gpu: bool = False,
  ):
      config = CONFIG.copy()
      config["epochs"] = num_epochs
      config["batch_size"] = batch_size
  
      # Parse worker ip ports
      worker_ip_port_list = worker_ip_ports.split(",")
  
      # Then we kick off the training function on every worker.
      return train_tf_vanilla_worker(
          config=config,
          rank=rank,
          world_size=num_workers,
          worker_ip_port_list=worker_ip_port_list,
          use_gpu=use_gpu,
      )
  
file_path: ray/release/air_tests/air_benchmarks/workloads/tensorflow_benchmark.py
imports: import json
  import os
  import time
  from pathlib import Path
  import click
  import numpy
  import tensorflow
  from typing import List, Tuple
label_desc: Use image node_id 9 for calling a global function with example usage: worker(num_epochs, num_workers, rank, worker_ip_ports, batch_size, use_gpu) and returns: train_tf_vanilla_worker