code: def get_batch(num_samples):
      points, _ = make_circles(
          n_samples=num_samples, noise=0.06, factor=0.5
      )
      x = torch.tensor(points).type(torch.float32).to(device)
      logp_diff_t1 = (
          torch.zeros(num_samples, 1).type(torch.float32).to(device)
      )
  
      return (x, logp_diff_t1)
  
imports: import os
  import argparse
  import glob
  from PIL import Image
  import numpy
  import matplotlib
  import matplotlib.pyplot
  from sklearn.datasets import make_circles
  import torch
  import torch.nn
  import torch.optim
label_desc: Use image node_id 2 for calling a global function with example usage: get_batch(num_samples) and returns: x,  logp_diff_t1