code: def gmm1(args, rng, weights, mus, sigmas, clip=None):
      """
      Gaussian Mixture Model 1D.
      """
      ret = np.asarray([])
      while len(ret) < args.n_ei_candidates:
          n = args.n_ei_candidates - len(ret)
          active = np.argmax(rng.multinomial(1, weights, n), axis=1)
          samples = rng.normal(mus[active], sigmas[active])
          if clip:
              samples = samples[
                  (clip[0] <= samples) & (samples <= clip[1])
              ]
          ret = np.concatenate([ret, samples])
      return ret
  
imports: from __future__ import annotations
  from collections import defaultdict
  import logging
  import math
  from typing import Any, NamedTuple
  import numpy
  from scipy.special import erf
  from typing_extensions import Literal
  import nni
  from nni.common.hpo_utils import Deduplicator, OptimizeMode, format_search_space, deformat_parameters, format_parameters
  from nni.tuner import Tuner
  from nni.utils import extract_scalar_reward
  from .None import random_tuner
label_desc: Use image node_id 9 for calling a global function with example usage: gmm1(args, rng, weights, mus, sigmas, clip) and returns: ret