code: def get_golden_config(model_name, config_class, args):
      """Return a dict with the golden data for throughput and memory usage."""
  
      if model_name == "lm":
          return config_class.get_golden_real_stats()
      else:
          raise RuntimeError(
              "Unrecognized args.model_mame " % args.model_name
          )
  
imports: from collections import defaultdict
  import gc
  import logging
  import math
  import time
  import torch
  import torch.distributed
  from torch.distributed import rpc
  from torch.nn.parallel import DistributedDataParallel
  import utils
  from benchmarks.golden_configs.lm_wikitext2 import Pipe
  from fairscale.fair_dev.testing.testing import dist_init
  from fairscale.nn import Pipe
  from fairscale.nn.model_parallel import initialize_model_parallel
label_desc: Use image node_id 11 for calling a global function with example usage: get_golden_config(model_name, config_class, args) and returns: config_class