code: def test_audio_save(
      format, encoding_dtype, num_samples, expected_length
  ) -> None:
      opts = argparse.Namespace()
      setattr(
          opts,
          "audio_augmentation.torchaudio_save.encoding_dtype",
          encoding_dtype,
      )
      setattr(opts, "audio_augmentation.torchaudio_save.format", format)
      t = audio_bytes.TorchaudioSave(opts)
  
      x = {
          "samples": {"audio": torch.randn([2, num_samples])},
          "metadata": {"audio_fps": 16},
      }
  
      outputs = t(x)["samples"]["audio"]
      assert torch.all(0 <= outputs)
      assert torch.all(outputs <= 255)
      assert outputs.shape == (expected_length,)
  
imports: import argparse
  import pytest
  import torch
  from data.transforms import audio_bytes
label_desc: Use image node_id 1 for calling a global function with example usage: test_audio_save(format, encoding_dtype, num_samples, expected_length) without return types