code: def stochastically_convert_to_three_level_categorical(x):
      p = sigmoid(x)
      return choice([0, 1, 2], 1, p=[0.8 * (1 - p), 0.8 * p, 0.2])
  
imports: import math
  import string
  import networkx
  import numpy
  import pandas
  import scipy.stats
  from numpy.random import choice
  from scipy.stats import bernoulli, halfnorm, poisson, uniform
  from sklearn.neural_network import MLPRegressor
  from dowhy.utils.graph_operations import add_edge, del_edge, get_random_node_pair, get_simple_ordered_tree
label_desc: Use image node_id 3 for calling a global function with example usage: stochastically_convert_to_three_level_categorical(x) and returns: choice