code: def prepare_sentences(
      dump_text_paths: Union[str, Path],
      output_path: Union[str, Path],
      remove_characters="",
  ):
      """Create train.txt file for sentencepiece training from the given dump file.
  
      Args:
          dump_text_paths (Union[str, Path]): Dump text file path.
          output_path (Union[str, Path]): Output directory for train.txt file.
      """
      # Please join the dump set before running this function.
      if not os.path.exists(output_path):
          os.makedirs(output_path)
  
      lines = []
      for dump_text_path in dump_text_paths:
          with open(dump_text_path, "r") as f:
              lines += f.readlines()
  
      # normalize text
      # remove unrequired characters
      lines = [
          line.translate(str.maketrans("", "", remove_characters))
          for line in lines
      ]
      texts = "\n".join(
          [
              line.split(" ", maxsplit=1)[1].replace("\n", "")
              for line in lines
          ]
      )
  
      with open(os.path.join(output_path, "train.txt"), "w") as f:
          f.write(texts)
  
imports: import os
  import shutil
  from pathlib import Path
  from typing import Union
  import sentencepiece
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_sentences(dump_text_paths, output_path, remove_characters) without return types