code: def configure_optimizers(self):
      self.warmup_lr_scheduler = WarmupCosineScheduler(
          self.optimizer,
          10,
          self.args.epochs,
          len(self.trainer.datamodule.train_dataloader())
          / self.trainer.num_devices
          / self.trainer.num_nodes,
      )
      self.lr_scheduler_interval = "step"
      return (
          [self.optimizer],
          [
              {
                  "scheduler": self.warmup_lr_scheduler,
                  "interval": self.lr_scheduler_interval,
              }
          ],
      )
  
imports: import itertools
  import math
  from collections import namedtuple
  from typing import List, Tuple
  import sentencepiece
  import torch
  import torchaudio
  from models.conformer_rnnt import conformer_rnnt
  from models.emformer_rnnt import emformer_rnnt
  from models.fusion import fusion_module
  from models.resnet import video_resnet
  from models.resnet1d import audio_resnet
  from pytorch_lightning import LightningModule
  from schedulers import WarmupCosineScheduler
  from torchaudio.models import Hypothesis, RNNTBeamSearch
label_desc: Use image node_id 3 for calling the AVConformerRNNTModule obj's underlying member method code with example usage: obj.configure_optimizers() and returns: list,  list