class_docstr: A class designed for performing ASR and diarization together.
  
  Attributes:
      cfg_diarizer (OmegaConf):
          Hydra config for diarizer key
      params (OmegaConf):
          Parameters config in diarizer.asr
      ctc_decoder_params (OmegaConf)
          Hydra config for beam search decoder
      realigning_lm_params (OmegaConf):
          Hydra config for realigning language model
      manifest_filepath (str):
          Path to the input manifest path
      nonspeech_threshold (float):
          Threshold for VAD logits that are used for creating speech segments
      fix_word_ts_with_VAD (bool):
          Choose whether to fix word timestamps by using VAD results
      root_path (str):
          Path to the folder where diarization results are saved
      vad_threshold_for_word_ts (float):
          Threshold used for compensating word timestamps with VAD output
      max_word_ts_length_in_sec (float):
          Maximum limit for the duration of each word timestamp
      word_ts_anchor_offset (float):
          Offset for word timestamps from ASR decoders
      run_ASR:
          Placeholder variable for an ASR launcher function
      realigning_lm:
          Placeholder variable for a loaded ARPA Language model
      ctm_exists (bool):
          Boolean that indicates whether all files have the corresponding reference CTM file
      frame_VAD (dict):
          Dictionary containing frame-level VAD logits
      AUDIO_RTTM_MAP:
          Dictionary containing the input manifest information
      color_palette (dict):
          Dictionary containing the ANSI color escape codes for each speaker label (speaker index)
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docstr: Print a slew of error metrics for ASR and Diarization.
  
  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.
docstr_tok: ["Print","a","slew","of","error","metrics","for","ASR","and","Diarization",".","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","."]
code: def print_errors(
      der_results: Dict[str, Dict[str, float]],
      wer_results: Dict[str, Dict[str, float]],
  ):
      """
      Print a slew of error metrics for ASR and Diarization.
  
      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.
      """
      DER_info = f"\nDER                : {der_results['total']['DER']:.4f} \
                       \nFA                 : {der_results['total']['FA']:.4f} \
                       \nMISS               : {der_results['total']['MISS']:.4f} \
                       \nCER                : {der_results['total']['CER']:.4f} \
                       \nSpk. counting acc. : {der_results['total']['spk_counting_acc']:.4f}"
      if wer_results is not None and len(wer_results) > 0:
          logging.info(
              DER_info
              + f"\ncpWER              : {wer_results['total']['average_cpWER']:.4f} \
                       \nWER                : {wer_results['total']['average_WER']:.4f}"
          )
      else:
          logging.info(DER_info)
  
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 26 for calling the OfflineDiarWithASR obj's underlying member method code with example usage: obj.print_errors(der_results, wer_results) without return types