code: def postprocess(eval_examples, extra_data, all_results):
      output_dir = "predictions"
      os.makedirs(output_dir, exist_ok=True)
      output_prediction_file = os.path.join(
          output_dir, "predictions.json"
      )
      output_nbest_file = os.path.join(
          output_dir, "nbest_predictions.json"
      )
      write_predictions(
          eval_examples,
          extra_data,
          all_results,
          n_best_size,
          max_answer_length,
          True,
          output_prediction_file,
          output_nbest_file,
      )
  
      # print results
      with open(output_prediction_file) as json_file:
          test_data = json.load(json_file)
          print("The result is:", json.dumps(test_data, indent=2))
  
imports: import os
  import zipfile
  import numpy
  import json
  from singa import device
  from singa import tensor
  from singa import sonnx
  import onnx
  import tokenization
  from run_onnx_squad import read_squad_examples, convert_examples_to_features, RawResult, write_predictions
  import sys
  from utils import download_model, check_exist_or_download
  import logging
label_desc: Use image node_id 3 for calling a global function with example usage: postprocess(eval_examples, extra_data, all_results) without return types