code: def _make_train_test_ids(
      rng: np.random.RandomState,
      num_frames: int,
  ) -> Tuple[List[int], List[int]]:
      """Randomly generate train / test ids."""
      all_idx = rng.permutation(num_frames)
  
      boundary = int(num_frames * _TRAIN_TEST_RATIO)
  
      train_ids = all_idx[:boundary]
      test_ids = all_idx[boundary:]
      # np.int64 is not serializable by Json, so need to convert to int first.
      return list(int(x) for x in train_ids), list(
          int(x) for x in test_ids
      )
  
file_path: kubric/challenges/robust_nerf/worker.py
imports: import collections
  import json
  import logging
  from typing import Dict, List, Optional, Tuple
  import kubric
  import kubric.renderer.blender
  import kubric.simulator.pybullet
  import numpy
  import tensorflow
  import bpy
label_desc: Use image node_id 7 for calling a global function with example usage: _make_train_test_ids(rng, num_frames) and returns: list,  list