class_docstr: Function caller to be used in the MLP experiments. 
class_docstr_tok: ["Function","caller","to","be","used","in","the","MLP","experiments","."]
docstr: Evaluates the validation score. 
docstr_tok: ["Evaluates","the","validation","score","."]
code: def _eval_validation_score(self, raw_fidel, raw_point, qinfo):
      """Evaluates the validation score."""
      # pylint: disable=unused-argument
      # pylint: disable=bare-except
      # Extract out the arguments
      nn = raw_point[0]
      learning_rate = 10 ** raw_point[1]
      num_loops = raw_fidel[0]
      curr_tf_params = deepcopy(self.train_params.tf_params)
      curr_tf_params["learningRate"] = learning_rate
      curr_tf_params["numLoops"] = num_loops
      #     self.reporter.writeln('Eval: %s, %0.8f, %0d.'%(str(nn), learning_rate, num_loops))
      # Set up
      os.environ["CUDA_VISIBLE_DEVICES"] = str(qinfo.worker_id)
      num_tries = 0
      succ_eval = False
      while num_tries < _MAX_TRIES and not succ_eval:
          try:
              tmp_dir = tempfile.mkdtemp(dir=self.root_tmp_dir)
              vali_error = (
                  run_tensorflow_cifar.compute_validation_error(
                      nn,
                      self.data_file_str,
                      qinfo.worker_id,
                      curr_tf_params,
                      tmp_dir,
                  )
              )
              succ_eval = True
          except Exception as e:
              sleep(_SLEEP_BETWEEN_TRIES_SECS)
              num_tries += 1
              self.reporter.writeln(
                  " -- Failed on try %d with gpu %d: %s."
                  % (num_tries, qinfo.worker_id, e)
              )
      self._clean_up(tmp_dir)
      return vali_error
  
file_path: dragonfly/examples/nas/cnn_function_caller.py
imports: from copy import deepcopy
  import os
  import shutil
  import tempfile
  from time import sleep
  from nn_function_caller import NNFunctionCaller
  from cg.cifar import run_tensorflow_cifar
label_desc: Use image node_id 2 for calling the CNNFunctionCaller obj's underlying member method code with example usage: obj._eval_validation_score(raw_fidel, raw_point, qinfo) and returns: vali_error