code: def __init__(
      self,
      *,
      dataset_path,
      seconds_per_batch,
      train_shuffle=True,
      num_workers=10,
  ):
      super().__init__()
      self.dataset_path = dataset_path
      self.seconds_per_batch = seconds_per_batch
      self.train_shuffle = train_shuffle
      self.num_workers = num_workers
  
file_path: audio/examples/self_supervised_learning/data_modules/_wav2vec2_datamodule.py
imports: import torch
  from pytorch_lightning import LightningDataModule
  from torchaudio.datasets.librispeech import LIBRISPEECH
  from ._utils import BucketizeBatchSampler, CollateFnWav2Vec2, DistributedBatchSampler
label_desc: Use image node_id 1 to create a new Wav2Vec2DataModule object from inherited base classes: LightningDataModule with example: obj = Wav2Vec2DataModule()