code: def get_binary_mask(total_size, indices):
      mask = torch.zeros(total_size)
      mask[indices] = 1
      return mask.byte()
  
file_path: AutoGL/test/performance/heterogeneous/dgl/train_hgt.py
imports: import os
  import numpy
  from tqdm import tqdm
  import torch
  from autogl.module.train import NodeClassificationHetTrainer
  from autogl.solver.utils import set_seed
  import logging
  import argparse
  from autogl.datasets import build_dataset_from_name
label_desc: Use image node_id 1 for calling a global function with example usage: get_binary_mask(total_size, indices) and returns: mask