code: def best_split_for_idx_remote(tree, idx, X, y, num_parent, best_gini):
      return best_split_for_idx(tree, idx, X, y, num_parent, best_gini)
  
imports: import numpy
  import ray
  from sklearn import datasets, metrics
  import time
  import tempfile
  import os
  import json
label_desc: Use image node_id 5 for calling a global function with example usage: best_split_for_idx_remote(tree, idx, X, y, num_parent, best_gini) and returns: best_split_for_idx