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/han_main.py
imports: import os
  import numpy
  from tqdm import tqdm
  import torch
  from autogl.module.model.dgl import AutoHAN
  from helper import EarlyStopping
  import argparse
  import random
  from sklearn.metrics import f1_score
  from autogl.datasets import build_dataset_from_name
label_desc: Use image node_id 2 for calling a global function with example usage: get_binary_mask(total_size, indices) and returns: mask