code: def load_groundtruth_file(data_file):
      with open(data_file, "r") as f:
          nq_examples = json.load(f)
  
      data = []
      for instance in nq_examples:
          if "answers" in instance:
              answers = instance["answers"]
              if len(answers) < 1:
                  answers = [None]
          elif "answer" in instance:
              if type(instance["answer"]) is str:
                  answers = [instance["answer"]]
              elif type(instance["answer"]) is list:
                  answers = instance["answer"]
              else:
                  answers = [str(instance["answer"])]
          else:
              raise ValueError("need to have answer or answers")
          data.append(answers[0])
  
      return data
  
file_path: megatron-lm/tools/retro/text_generation/evaluate.py
imports: import sys
  import os
  from tqdm import tqdm
  import string
  import json
  import regex
  import numpy
  from tools.retro.text_generation.metrics import F1Metric
label_desc: Use image node_id 3 for calling a global function with example usage: load_groundtruth_file(data_file) and returns: data