code: def generate_dataset(v_min, v_max, n_samples, fname):
      samples = []
      for _ in range(n_samples):
          size = random.randint(v_min, v_max)
          samples.append(get_decision_sequence(size))
  
      with open(fname, "wb") as f:
          pickle.dump(samples, f)
  
imports: import os
  import pickle
  import random
  import matplotlib.pyplot
  import networkx
  from torch.utils.data import Dataset
label_desc: Use image node_id 5 for calling a global function with example usage: generate_dataset(v_min, v_max, n_samples, fname) without return types