code: def __init__(self, dataset_name, min_size=5, max_size=20):
      self.min_size = min_size
      self.max_size = max_size
      self.train, self.test, _ = load_dataset(dataset_name)
  
imports: import os
  import pickle
  import random
  from deepsnap.batch import Batch
  from deepsnap.dataset import GraphDataset
  import networkx
  import numpy
  from sklearn.manifold import TSNE
  import torch
  import torch.multiprocessing
  import torch.nn.functional
  import torch.optim
  from torch_geometric.data import DataLoader
  from torch.utils.data import DataLoader
  from torch_geometric.datasets import TUDataset, PPI, QM9
  import torch_geometric.utils
  import torch_geometric.nn
  from tqdm import tqdm
  import queue
  import utils
label_desc: Use image node_id 1 to create a new DataSource object  with example: obj = DataSource(dataset_name, min_size, max_size)