code: def smooth_probability_distribution(
      set_list, smoothing_weight=0.0, target_sum=1.0
  ):
      """This function smooths the probability distribution in the list"""
      if len(list(set_list)) > 0:
          num_unspecified = 0
          accumulated_prob = 0
          for item in set_list:
              if item.probability is None:
                  num_unspecified += 1
              else:
                  accumulated_prob += item.probability
  
          # Compute the probability for the items without specifying their probability
          uniform_probability = 0
          if num_unspecified > 0 and accumulated_prob < 1:
              uniform_probability = (1 - accumulated_prob) / float(
                  num_unspecified
              )
          elif num_unspecified > 0 and accumulated_prob >= 1:
              warnings.warn(
                  "The sum of probabilities specified by user is larger than or equal to 1. "
                  "The items without probabilities specified will be given zero to their probabilities."
              )
  
          for item in set_list:
              if item.probability is None:
                  item.probability = uniform_probability
              else:
                  # smooth the probability
                  item.probability = (
                      (1 - smoothing_weight) * item.probability
                      + smoothing_weight * uniform_probability
                  )
  
          # Normalize the probability
          sum_p = sum(item.probability for item in set_list)
          for item in set_list:
              item.probability = item.probability / sum_p * target_sum
  
      return set_list
  
imports: import argparse, shlex, glob, math, os, random, sys, warnings, copy, imp, ast
label_desc: Use image node_id 13 for calling a global function with example usage: smooth_probability_distribution(set_list, smoothing_weight, target_sum) and returns: set_list