code: def logmgf_from_counts(counts, noise_eps, l):
      """
      ReportNoisyMax mechanism with noise_eps with 2*noise_eps-DP
      in our setting where one count can go up by one and another
      can go down by 1.
      """
  
      q = compute_q_noisy_max(counts, noise_eps)
      return logmgf_exact(q, 2.0 * noise_eps, l)
  
file_path: privacy/research/pate_2017/analysis.py
imports: import os
  import math
  import numpy
  from six.moves import xrange
  import tensorflow.compat.v1
  import maybe_download
label_desc: Use image node_id 4 for calling a global function with example usage: logmgf_from_counts(counts, noise_eps, l) and returns: logmgf_exact