code: def _update_hparams(hparams, is_training):
      """Update hparams for given is_training option."""
      if not is_training:
          hparams.set_hparam("drop_path_keep_prob", 1.0)
  
file_path: adanet/research/improve_nas/trainer/nasnet.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling a global function with example usage: _update_hparams(hparams, is_training) without return types