code: def sample(self, seeds):
      walks = dgl.sampling.random_walk(
          self.G, seeds, length=self.walk_length - 1
      )[0]
      return walks
  
imports: import os
  import pickle
  import random
  import time
  import dgl
  import numpy
  import scipy.sparse
  import torch
  from dgl.data.utils import _get_dgl_url, download, extract_archive, get_download_dir
  from torch.utils.data import DataLoader
  from utils import shuffle_walks
label_desc: Use image node_id 2 for calling the DeepwalkSampler obj's underlying member method code with example usage: obj.sample(seeds) and returns: walks