code: def validate_hparams(hparams):
      result = True
      supports_homograph = not (
          (
              hparams.get("char_tokenize")
              and not hparams.get("char_token_wordwise")
          )
          or (
              hparams.get("phn_tokenize")
              and not hparams.get("phn_token_wordwise")
          )
      )
      if (
          not supports_homograph
          and hparams.get("homograph_epochs", 0) > 0
      ):
          logger.error(
              "ERROR: Non-wordwise tokenization is not supported with "
              "homograph disambiguation training"
          )
          result = False
      return result
  
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 4 for calling a global function with example usage: validate_hparams(hparams) and returns: result