code: def load_best_model(best_logdir):
      import xgboost as xgb
      import os
  
      best_bst = xgb.Booster()
      best_bst.load_model(os.path.join(best_logdir, "model.xgb"))
      return best_bst
  
imports: import argparse
  from sklearn import datasets
  from sklearn.model_selection import train_test_split
  from xgboost_ray import RayDMatrix, RayParams, train
label_desc: Use image node_id 2 for calling a global function with example usage: load_best_model(best_logdir) and returns: best_bst