code: def transcribe_stream(
      g2p, text_file, output_file, batch_size=64, total=None
  ):
      """
      Transcribes a file stream
  
      Arguments
      ---------
      g2p: speechbrain.inference.text.GrpahemeToPhoneme
          a pretrained G2P model instance
      text_file: file
          a file object from which text samples will be read
      output_file: file
          the file object to which phonemes will be output
      batch_size: 64
          the size of the batch passed to the model
      total: int
          the total number of examples (used for the progress bar)
      """
      batch_count = math.ceil(total // batch_size)
      for batch in tqdm(
          chunked(text_file, batch_size), total=batch_count
      ):
          phoneme_results = g2p(batch)
          for result in phoneme_results:
              line = " ".join(
                  _substitutions.get(phoneme, phoneme)
                  for phoneme in result
              )
              print(line, file=output_file)
              output_file.flush()
  
imports: import itertools
  import math
  import os
  import speechbrain
  import sys
  import traceback
  from cmd import Cmd
  from argparse import ArgumentParser
  from hyperpyyaml import load_hyperpyyaml
  from speechbrain.inference.text import GraphemeToPhoneme
  from tqdm.auto import tqdm
label_desc: Use image node_id 4 for calling a global function with example usage: transcribe_stream(g2p, text_file, output_file, batch_size, total) without return types