code: def suggest_batch(new_ids, domain, trials, seed, *args, **kwargs):
      return AnnealingAlgo(domain, trials, seed, *args, **kwargs).batch(
          new_ids
      )
  
imports: from __future__ import print_function
  from __future__ import absolute_import
  from __future__ import division
  from builtins import zip
  from past.utils import old_div
  import logging
  import numpy
  from .pyll.stochastic import categorical, normal, lognormal, qnormal, qlognormal, uniform, loguniform, quniform, qloguniform
  from .base import miscs_to_idxs_vals
  from .algobase import SuggestAlgo, ExprEvaluator
label_desc: Use image node_id 2 for calling a global function with example usage: suggest_batch(new_ids, domain, trials, seed) and returns: AnnealingAlgo