code: def __init__(self, dataset, transforms):
      self.dataset = dataset
      self.transforms = transforms
  
file_path: audio/examples/pipeline_wavernn/datasets.py
imports: import random
  import torch
  from processing import bits_to_normalized_waveform, normalized_waveform_to_bits
  from torch.utils.data.dataset import random_split
  from torchaudio.datasets import LIBRITTS, LJSPEECH
  from torchaudio.transforms import MuLawEncoding
label_desc: Use image node_id 1 to create a new Processed object from inherited base classes: torch.utils.data with example: obj = Processed(dataset, transforms)