code: def main(args):
      pipeline = GslmPipeline(args)
  
      audio, sample_rate = torchaudio.load(args.input_file)
  
      if audio.ndim == 2:
          audio = audio.mean(0)
  
      if args.prompt_duration_sec:
          prompt = int(args.prompt_duration_sec * sample_rate)
          audio = audio[:prompt]
  
      generated_audio = pipeline(audio, sample_rate)
  
      torchaudio.save(
          args.output_file,
          generated_audio.cpu().unsqueeze(0),
          pipeline.output_sample_rate,
      )
  
file_path: textlesslib/examples/gslm/sample.py
imports: import logging
  import random
  from typing import Optional
  from fairseq import utils
  import numpy
  import torch
  import torchaudio
  from textless.data.speech_encoder import SpeechEncoder
  from textless.vocoders.tacotron2.vocoder import TacotronVocoder
  from sampler import UnitLanguageModelSampler
label_desc: Use image node_id 1 for calling a global function with example usage: main(args) without return types