code: def train_dataloader(self):
      dataset = torchaudio.datasets.LibriLightLimited(
          self.dataset_path, self.subset
      )
      lengths = _get_lengths_librilightlimited(
          dataset._fileids_paths, dataset._path, dataset._ext_audio
      )
      sampler = BucketizeBatchSampler(
          lengths,
          num_buckets=100,
          max_token_count=self.seconds_per_batch * 16000,
          shuffle=True,
          seed=self.global_step,
      )
      sampler = DistributedBatchSampler(sampler, shuffle=True)
      sampler.set_epoch(self.global_step)
      dataloader = DataLoader(
          dataset,
          batch_sampler=sampler,
          collate_fn=CollateFnLibriLightLimited(),
          num_workers=10,
      )
      return dataloader
  
imports: import math
  from typing import Optional, Tuple
  import torch
  import torch.nn.functional
  import torchaudio
  import torchaudio.models.wav2vec2.components
  from dataset import _get_lengths_librilightlimited, _get_lengths_librispeech, BucketizeBatchSampler, CollateFnHubert, CollateFnLibriLightLimited, DistributedBatchSampler, HuBERTDataSet
  from lightning.pytorch import LightningModule
  from loss import hubert_loss
  from torch import Tensor
  from torch.optim.optimizer import Optimizer
  from torch.utils.data import DataLoader
label_desc: Use image node_id 7 for calling the HuBERTFineTuneModule obj's underlying member method code with example usage: obj.train_dataloader() and returns: dataloader