code: def evaluate(data_file, pred_file):
      """
      Evaluate.
      """
      expected_version = "1.1"
      with open(data_file) as dataset_file:
          dataset_json = json.load(dataset_file)
          if dataset_json["version"] != expected_version:
              print(
                  "Evaluation expects v-"
                  + expected_version
                  + ", but got dataset with v-"
                  + dataset_json["version"],
                  file=sys.stderr,
              )
          dataset = dataset_json["data"]
      with open(pred_file) as prediction_file:
          predictions = json.load(prediction_file)
      # print(json.dumps(evaluate(dataset, predictions)))
      result = _evaluate(dataset, predictions)
      # print('em:', result['exact_match'], 'f1:', result['f1'])
      return result["exact_match"]
  
file_path: nni/examples/trials/ga_squad/evaluate.py
imports: from __future__ import print_function
  from collections import Counter
  import string
  import re
  import argparse
  import json
  import sys
label_desc: Use image node_id 6 for calling a global function with example usage: evaluate(data_file, pred_file) and returns: result