code: def __init__(self, num_epochs, num_batches):
      super(CyclePrinting, self).__init__()
  
      self.num_epochs = num_epochs
      self.num_batches = num_batches
      self.batch_count = 0
  
imports: import os
  import pickle
  import random
  import matplotlib.pyplot
  import networkx
  from torch.utils.data import Dataset
label_desc: Use image node_id 1 to create a new CyclePrinting object from inherited base classes: object with example: obj = CyclePrinting(num_epochs, num_batches)