code: def ap_qnormal_sampler(
      obs, prior_weight, mu, sigma, q, size=(), rng=None
  ):
      weights, mus, sigmas = scope.adaptive_parzen_normal(
          obs, prior_weight, mu, sigma
      )
      return scope.GMM1(weights, mus, sigmas, q=q, size=size, rng=rng)
  
imports: from __future__ import print_function
  from __future__ import absolute_import
  from __future__ import division
  from builtins import str
  from builtins import map
  from builtins import zip
  from builtins import range
  from past.utils import old_div
  import logging
  import time
  import numpy
  from scipy.special import erf
  from .None import pyll
  from .pyll import scope
  from .pyll.stochastic import implicit_stochastic
  from .base import miscs_to_idxs_vals
  from .base import miscs_update_idxs_vals
  from .None import rand
label_desc: Use image node_id 20 for calling a global function with example usage: ap_qnormal_sampler(obs, prior_weight, mu, sigma, q, size, rng) and returns: scope