code: def binarize_text_file(
      text_file: str,
      dictionary: Dictionary,
      output_path: str,
      append_eos: bool,
      reverse_order: bool,
      embed_bytes: bool = False,
      char_dictionary: Optional[Dictionary] = None,
      already_numberized: bool = False,
  ) -> str:
      output_path = maybe_generate_temp_file_path(output_path)
      if char_dictionary is not None:
          dataset = char_data.InMemoryNumpyWordCharDataset()
          dataset.parse(
              path=text_file,
              word_dict=dictionary,
              char_dict=char_dictionary,
              embed_bytes=embed_bytes,
              reverse_order=reverse_order,
              append_eos=append_eos,
          )
      else:
          dataset = pytorch_translate_data.InMemoryIndexedDataset()
          dataset.parse(
              path=text_file,
              dictionary=dictionary,
              reverse_order=reverse_order,
              append_eos=append_eos,
              already_numberized=already_numberized,
          )
      dataset.save(output_path)
      return output_path
  
imports: import argparse
  import os
  import tempfile
  from typing import Dict, List, Optional
  from pytorch_translate import constants, multilingual_utils, options, utils
  from pytorch_translate.data import char_data, data
  from pytorch_translate.data.dictionary import Dictionary
label_desc: Use image node_id 2 for calling a global function with example usage: binarize_text_file(text_file, dictionary, output_path, append_eos, reverse_order, embed_bytes, char_dictionary, already_numberized) and returns: output_path