code: def get_optimizer(args, model):
      optimizer = bmt.optim.AdamOffloadOptimizer(
          model.parameters(), weight_decay=args.weight_decay
      )
      return optimizer
  
imports: import time
  from typing import Dict, List, Union
  import torch
  import bmtrain
  import os
  from opendelta import LoraModel
  from cpm_live.arguments import get_args
  from cpm_live.models import CPMBee, CPMBeeConfig
  from cpm_live.tokenizers import CPMBeeTokenizer
  from cpm_live.utils import allgather_objects
  from cpm_live.training_tasks.bee import FinetuneDataset
label_desc: Use image node_id 3 for calling a global function with example usage: get_optimizer(args, model) and returns: optimizer