code: def train_wrapper(config, ray_params):
      train_ray(
          path="/data/classification.parquet",
          num_workers=None,
          num_boost_rounds=100,
          num_files=25,
          regression=False,
          use_gpu=False,
          ray_params=ray_params,
          xgboost_params=config,
      )
  
file_path: ray/release/xgboost_tests/workloads/tune_small.py
imports: from collections import Counter
  import json
  import os
  import time
  import ray
  from ray import tune
  from xgboost_ray import RayParams
  from release_test_util import train_ray
label_desc: Use image node_id 1 for calling a global function with example usage: train_wrapper(config, ray_params) without return types