class_docstr: This is a dummy audio transform.
  
  It ignores actual audio data, and returns an empty tensor. It is useful when
  actual audio data is raw waveform and has a varying number of waveform samples
  which makes minibatch assembling impossible
class_docstr_tok: ["This","is","a","dummy","audio","transform",".","It","ignores","actual","audio","data",",","and","returns","an","empty","tensor",".","It","is","useful","when","actual","audio","data","is","raw","waveform","and","has","a","varying","number","of","waveform","samples","which","makes","minibatch","assembling","impossible"]
docstr: The constructor method of DummyAudioTransform class.
docstr_tok: ["The","constructor","method","of","DummyAudioTransform","class","."]
code: def __init__(self):
      """The constructor method of DummyAudioTransform class."""
  
      pass
  
imports: import random
  from typing import Any, Callable, Dict, List, Optional, Union
  import torch
  import torchvision.transforms
  import torchvision.transforms._transforms_video
  from .None import build_transforms, ClassyTransform, register_transform
  from .util import ApplyTransformToKey, ImagenetConstants, TupleToMapTransform
label_desc: Use image node_id 1 to create a new DummyAudioTransform object from inherited base classes: ClassyTransform with example: obj = DummyAudioTransform()