code: def _load_indices(indices_path: Path, split: str) -> List[str]:
      with open(indices_path, "r") as f:
          indices = sorted(f.readlines())
  
      image_names = [os.path.splitext(el.rstrip())[0] for el in indices]
      if split == "train":
          image_names = [
              el for el in image_names if el not in _INVALID_IMAGE_NAMES
          ]
  
      return image_names
  
file_path: NeuralCompression/neuralcompression/data/_openimages_v6.py
imports: import os
  from pathlib import Path
  from typing import Callable, List, Optional, Union
  from torch.utils.data import Dataset
  from torchvision.datasets.folder import default_loader
label_desc: Use image node_id 1 for calling a global function with example usage: _load_indices(indices_path, split) and returns: image_names