code: def prepare_dataset_graphs(data_path, k_list, lvl_list):
      with open(data_path, "rb") as f:
          features, labels = pickle.load(f)
      gs = []
      for k, l in zip(k_list, lvl_list):
          dataset = LanderDataset(
              features=features,
              labels=labels,
              k=k,
              levels=l,
              faiss_gpu=args.faiss_gpu,
          )
          gs += [g.to(device) for g in dataset.gs]
      return gs
  
file_path: dgl/examples/pytorch/hilander/train.py
imports: import argparse
  import os
  import pickle
  import time
  import dgl
  import numpy
  import torch
  import torch.optim
  from dataset import LanderDataset
  from models import LANDER
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_dataset_graphs(data_path, k_list, lvl_list) and returns: gs