class_docstr: Similar to @torchvision.transforms.Lambda, applies a user-defined lambda on the
  audio samples as a transform.
code: def __init__(
      self,
      opts: argparse.Namespace,
      func: Callable[[torch.Tensor], torch.Tensor],
      *args,
      **kwargs,
  ) -> None:
      self.func = func
      super(LambdaAudio, self).__init__(opts, *args, **kwargs)
  
imports: import argparse
  import math
  import pathlib
  import random
  from typing import Callable, Dict, List, Optional, Union
  import torch
  import torchaudio
  from data.transforms import TRANSFORMATIONS_REGISTRY, BaseTransformation
  from data.transforms.audio_aux import mfccs
label_desc: Use image node_id 1 to create a new LambdaAudio object from inherited base classes: BaseTransformation with example: obj = LambdaAudio(opts, func)