docstr: Outputs all reports for a given epoch
  
  Arguments
  ---------
  epoch: int
      the epoch number
  
  final: bool
      whether or not the reports are final (i.e.
      after the final epoch)
  
  Returns
  -------
  file_name: str
      the report file name
docstr_tok: ["Outputs","all","reports","for","a","given","epoch","Arguments","--","--","--","--","-","epoch",":","int","the","epoch","number","final",":","bool","whether","or","not","the","reports","are","final","(","i.e",".","after","the","final","epoch",")","Returns","--","--","--","-","file_name",":","str","the","report","file","name"]
code: def _write_reports(self, epoch, final=True):
      """Outputs all reports for a given epoch
  
      Arguments
      ---------
      epoch: int
          the epoch number
  
      final: bool
          whether or not the reports are final (i.e.
          after the final epoch)
  
      Returns
      -------
      file_name: str
          the report file name
      """
      wer_file_name = self._get_report_path(epoch, "wer_file", final)
      self._write_wer_file(wer_file_name)
      if self.mode == TrainMode.HOMOGRAPH:
          homograph_stats_file_name = self._get_report_path(
              epoch, "homograph_stats_file", final
          )
          self._write_homograph_file(homograph_stats_file_name)
  
imports: from speechbrain.dataio.dataset import FilteredSortedDynamicItemDataset, DynamicItemDataset
  from speechbrain.dataio.sampler import BalancingDataSampler
  from speechbrain.utils.data_utils import undo_padding
  import datasets
  import logging
  import os
  import random
  import speechbrain
  import sys
  from enum import Enum
  from collections import namedtuple
  from hyperpyyaml import load_hyperpyyaml
  from functools import partial
  from speechbrain.utils.distributed import run_on_main
  from speechbrain.utils.pretrained import save_for_pretrained
  from speechbrain.lobes.models.g2p.dataio import enable_eos_bos, grapheme_pipeline, phoneme_pipeline, tokenizer_encode_pipeline, add_bos_eos, get_sequence_key, phonemes_to_label
  from speechbrain.dataio.wer import print_alignments
  from speechbrain.wordemb.util import expand_to_chars
  from io import StringIO
  from speechbrain.utils import hpopt
  import numpy
label_desc: Use image node_id 16 for calling the G2PBrain obj's underlying member method code with example usage: obj._write_reports(epoch, final) without return types