code: def change_volume(
      audio: Union[str, np.ndarray],
      sample_rate: int = DEFAULT_SAMPLE_RATE,
      volume_db: float = 0.0,
      output_path: Optional[str] = None,
      metadata: Optional[List[Dict[str, Any]]] = None,
  ) -> Tuple[np.ndarray, int]:
      """
      Changes the volume of the audio
  
      @param audio: the path to the audio or a variable of type np.ndarray that
          will be augmented
  
      @param sample_rate: the audio sample rate of the inputted audio
  
      @param volume_db: the decibel amount by which to either increase
          (positive value) or decrease (negative value) the volume of the audio
  
      @param output_path: the path in which the resulting audio will be stored. If
          None, the resulting np.ndarray will still be returned
  
      @param metadata: if set to be a list, metadata about the function execution
          including its name, the source & dest duration, sample rates, etc. will be
          appended to the inputted list. If set to None, no metadata will be appended
  
      @returns: the augmented audio array and sample rate
      """
      assert isinstance(
          volume_db, (int, float)
      ), "Expected 'volume_db' to be a number"
      audio, sample_rate = audutils.validate_and_load_audio(
          audio, sample_rate
      )
  
      num_channels = 1 if audio.ndim == 1 else audio.shape[0]
      aug_audio = audio.reshape((num_channels, -1))
  
      aug_audio, out_sample_rate = sox_effects.apply_effects_tensor(
          torch.Tensor(aug_audio),
          sample_rate,
          [["vol", str(volume_db), "dB"]],
      )
  
      aug_audio = aug_audio.numpy()
      if num_channels == 1:
          aug_audio = aug_audio.reshape((aug_audio.shape[-1],))
  
      audutils.get_metadata(
          metadata=metadata,
          function_name="change_volume",
          audio=audio,
          sample_rate=sample_rate,
          dst_audio=aug_audio,
          dst_sample_rate=sample_rate,
          volume_db=volume_db,
          output_path=output_path,
      )
  
      return audutils.ret_and_save_audio(
          aug_audio, output_path, sample_rate
      )
  
imports: from copy import deepcopy
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  from augly.audio import utils
  from augly.utils import DEFAULT_SAMPLE_RATE
  from augly.utils.libsndfile import install_libsndfile
  import librosa
  from torchaudio import sox_effects
  from torchaudio.functional import fftconvolve, resample
label_desc: Use image node_id 3 for calling a global function with example usage: change_volume(audio, sample_rate, volume_db, output_path, metadata) and returns: audutils