class_docstr: Base class of audio datasets, providing common functionality
  for other audio datasets.
  
  Args:
      collection: Collection of audio examples prepared from manifest files.
      audio_processor: Used to process every example from the collection.
                       A callable with `process` method. For reference,
                       please check ASRAudioProcessor.
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docstr: Instantiates an audio dataset.
          
code: def __init__(
      self,
      collection: collections.Audio,
      audio_processor: Callable,
      output_type: Type[namedtuple],
  ):
      """Instantiates an audio dataset."""
      super().__init__()
  
      self.collection = collection
      self.audio_processor = audio_processor
      self.output_type = output_type
  
imports: import abc
  import math
  import random
  from collections import OrderedDict, namedtuple
  from dataclasses import dataclass
  from typing import Callable, Dict, List, Optional, Tuple, Type, Union
  import librosa
  import numpy
  import torch
  from nemo.collections.asr.parts.preprocessing.segment import AudioSegment
  from nemo.collections.asr.parts.utils.audio_utils import ChannelSelectorType
  from nemo.collections.common.parts.preprocessing import collections
  from nemo.collections.common.parts.utils import flatten
  from nemo.core.classes import Dataset
  from nemo.core.neural_types import AudioSignal, EncodedRepresentation, LengthsType, NeuralType
  from nemo.utils import logging
label_desc: Use image node_id 2 to create a new BaseAudioDataset object from inherited base classes: Dataset with example: obj = BaseAudioDataset(collection, audio_processor, output_type)