code: def configure_optimizers(self):
      return (
          [self.optimizer],
          [
              {
                  "scheduler": self.lr_scheduler,
                  "interval": "step",
              },
          ],
      )
  
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 3 for calling the HuBERTPreTrainModule obj's underlying member method code with example usage: obj.configure_optimizers() and returns: list,  list