code: def get_total_result_dict(
      der_results: Dict[str, Dict[str, float]],
      wer_results: Dict[str, Dict[str, float]],
      csv_columns: List[str],
  ):
      """
      Merge WER results and DER results into a single dictionary variable.
  
      Args:
          der_results (dict):
              Dictionary containing FA, MISS, CER and DER values for both aggregated amount and
              each session.
          wer_results (dict):
              Dictionary containing session-by-session WER and cpWER. `wer_results` only
              exists when CTM files are provided.
  
      Returns:
          total_result_dict (dict):
              Dictionary containing both DER and WER results. This dictionary contains unique-IDs of
              each session and `total` key that includes average (cp)WER and DER/CER/Miss/FA values.
      """
      total_result_dict = {}
      for uniq_id in der_results.keys():
          if uniq_id == "total":
              continue
          total_result_dict[uniq_id] = {x: "-" for x in csv_columns}
          total_result_dict[uniq_id]["uniq_id"] = uniq_id
          if uniq_id in der_results:
              total_result_dict[uniq_id].update(der_results[uniq_id])
          if uniq_id in wer_results:
              total_result_dict[uniq_id].update(wer_results[uniq_id])
      total_result_jsons = list(total_result_dict.values())
      return total_result_jsons
  
imports: import copy
  import csv
  import json
  import os
  from collections import OrderedDict
  from datetime import datetime
  from typing import Dict, List, Tuple
  import numpy
  from nemo.collections.asr.metrics.der import concat_perm_word_error_rate
  from nemo.collections.asr.metrics.wer import word_error_rate
  from nemo.collections.asr.models import ClusteringDiarizer
  from nemo.collections.asr.parts.utils.speaker_utils import audio_rttm_map, get_uniqname_from_filepath, labels_to_rttmfile, rttm_to_labels, write_rttm2manifest
  from nemo.utils import logging
label_desc: Use image node_id 6 for calling a global function with example usage: get_total_result_dict(der_results, wer_results, csv_columns) and returns: total_result_jsons