code: def prepare_tokenizer(
      data_folder, save_folder, phonemes, dataset_name
  ):
      """Prepares annotations for the tokenizer
  
      Arguments
      ---------
      dataset_name: str
          the name of the HuggingFace dataset
      data_folder: str
          the path to the dataset
      save_folder: str
          the path to the folder where annotations will be saved
      phonemes: list
          the list of phonemes
      """
      dataset = (
          datasets.load_dataset(dataset_name) if dataset_name else None
      )
      for data_split in DATA_SPLITS:
          destination_file_name = os.path.join(
              save_folder, f"tokenizer_annotation_{data_split}.json"
          )
          if os.path.exists(destination_file_name):
              print(
                  f"Annotation file '{destination_file_name} already exists"
              )
          else:
              print(
                  f"Creating tokenizer annotation '{destination_file_name}' "
                  f"from '{data_split}'"
              )
              prepare_annotation(
                  src=dataset[f"sentence_{data_split}"],
                  destination_file_name=destination_file_name,
                  phonemes=phonemes,
              )
  
imports: import json
  import os
  import re
  import datasets
  from speechbrain.lobes.models.g2p.dataio import build_token_char_map
label_desc: Use image node_id 3 for calling a global function with example usage: prepare_tokenizer(data_folder, save_folder, phonemes, dataset_name) without return types