code: def get_model_and_optimizer(
      args, device, benchmark_config, model_config
  ):
      """Return instantiated model and optimizer function."""
  
      if args.model_name == "lm":
          model = get_lm_model(args, device, model_config)
  
      lr = benchmark_config["lr"]
  
      def make_adam(params):
          return Adam(params, lr=lr)
  
      optimizer = make_adam
      return model, optimizer
  
file_path: fairscale/benchmarks/utils.py
imports: import argparse
  from functools import reduce
  import logging
  import operator
  import datasets.wikitext2_data
  from models import transformer_lm
  import numpy
  import torch
  from torch.optim import Adam
label_desc: Use image node_id 6 for calling a global function with example usage: get_model_and_optimizer(args, device, benchmark_config, model_config) and returns: model,  optimizer, Adam