code: def main(argv):
      if len(argv) > 1:
          raise app.UsageError("Too many command-line arguments.")
  
      results = multiprocessing.Queue()
      results_thread = threading.Thread(
          target=result_collector, args=(results,)
      )
      results_thread.start()
  
      model = tflite_model.Model(model_path=FLAGS.model_path)
      overlap_timesteps = 4
      overlap_wav = (
          model.get_hop_size() * overlap_timesteps
          + model.get_window_length()
      )
  
      if FLAGS.wav_file:
          wav_data = open(FLAGS.wav_file, "rb").read()
          samples = audio_recorder.wav_data_to_samples(
              wav_data, model.get_sample_rate()
          )
          samples = samples[
              : model.get_sample_rate() * 10
          ]  # Only the first 10 seconds
          samples = samples.reshape((-1, 1))
          samples_length = samples.shape[0]
          # Extend samples with zeros
          samples = np.pad(
              samples,
              (0, model.get_input_wav_length()),
              mode="constant",
          )
          for i, pos in enumerate(
              range(
                  0,
                  samples_length
                  - model.get_input_wav_length()
                  + overlap_wav,
                  model.get_input_wav_length() - overlap_wav,
              )
          ):
              chunk = samples[pos : pos + model.get_input_wav_length()]
              task = OnsetsTask(AudioChunk(i, chunk))
              task(model)
              results.put(task)
      else:
          tasks = multiprocessing.JoinableQueue()
  
          ## Make and start the workers
          num_workers = 4
          workers = [
              TfLiteWorker(FLAGS.model_path, tasks, results)
              for i in range(num_workers)
          ]
          for w in workers:
              w.start()
  
          audio_feeder = AudioQueue(
              callback=lambda audio_chunk: tasks.put(
                  OnsetsTask(audio_chunk)
              ),
              audio_device_index=FLAGS.mic
              if FLAGS.mic is None
              else int(FLAGS.mic),
              sample_rate_hz=int(FLAGS.sample_rate_hz),
              model_sample_rate=model.get_sample_rate(),
              frame_length=model.get_input_wav_length(),
              overlap=overlap_wav,
          )
  
          audio_feeder.start()
  
imports: import multiprocessing
  import threading
  from absl import app
  from absl import flags
  import attr
  from colorama import Fore
  from colorama import Style
  from magenta.models.onsets_frames_transcription.realtime import audio_recorder
  from magenta.models.onsets_frames_transcription.realtime import tflite_model
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: main(argv) without return types