code: def __init__(self, G, seeds):
      self.G = G
      self.seeds = seeds
      self.edges = torch.cat(
          (
              self.G.edges()[0].unsqueeze(0),
              self.G.edges()[1].unsqueeze(0),
          ),
          0,
      ).t()
  
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
label_desc: Use image node_id 1 to create a new EdgeSampler object from inherited base classes: object with example: obj = EdgeSampler(G, seeds)