code: def plot_rdp_curve_per_example(votes, sigmas):
      orders = np.linspace(1.0, 100.0, endpoint=True, num=1000)
      orders[0] = 1.001
      fig, ax = setup_plot()
  
      for i in range(votes.shape[0]):
          for sigma in sigmas:
              logq = pate.compute_logq_gaussian(votes[i,], sigma)
              rdp = pate.rdp_gaussian(logq, sigma, orders)
              ax.plot(
                  orders,
                  rdp,
                  alpha=1.0,
                  label=r"Data-dependent bound, $\sigma$={}".format(
                      int(sigma)
                  ),
                  linewidth=5,
              )
  
      for sigma in sigmas:
          ax.plot(
              orders,
              pate.rdp_data_independent_gaussian(sigma, orders),
              alpha=0.3,
              label=r"Data-independent bound, $\sigma$={}".format(
                  int(sigma)
              ),
              linewidth=10,
          )
  
      plt.xlim(xmin=1, xmax=100)
      plt.ylim(ymin=0)
      plt.xticks([1, 20, 40, 60, 80, 100])
      plt.yticks([0, 0.0025, 0.005, 0.0075, 0.01])
      plt.xlabel(r"Order $\alpha$", fontsize=16)
      plt.ylabel(r"RDP value $\varepsilon$ at $\alpha$", fontsize=16)
      ax.tick_params(labelsize=14)
  
      plt.legend(loc=0, fontsize=13)
      plt.show()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import os
  import sys
  from absl import app
  from absl import flags
  import matplotlib
  import matplotlib.pyplot
  import numpy
  import core
  import random
label_desc: Use image node_id 2 for calling a global function with example usage: plot_rdp_curve_per_example(votes, sigmas) without return types