code: def filter_homograph_positions(dataset):
      """Removes any defective homograph samples
  
      Arguments
      ---------
      data: speechbrain.dataio.dataset.DynamicItemDataset
          the data to be filtered
  
      Results
      -------
      data: speechbrain.dataio.dataset.DynamicItemDataset
          the filtered data
      """
      return dataset.filtered_sorted(
          key_test={
              "homograph_char_end": lambda value: value > 0,
              "homograph_phn_end": lambda value: value > 0,
          }
      )
  
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 3 for calling a global function with example usage: filter_homograph_positions(dataset) and returns: dataset