code: def broadcast_best(samples, below_llik, above_llik):
      if len(samples):
          score = below_llik - above_llik
          if len(samples) != len(score):
              raise ValueError()
          best = np.argmax(score)
          return [samples[best]] * len(samples)
      else:
          return []
  
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 29 for calling a global function with example usage: broadcast_best(samples, below_llik, above_llik) and returns: unknown, list