code: def benchmark_single_process(config_class, args):
      """Benchmark a given model using a single process and multiple devices."""
  
      init_method_pgroup = "tcp://localhost:{}".format(MPI_PORT)
      torch.distributed.init_process_group(
          backend="gloo",
          rank=0,
          world_size=1,
          init_method=init_method_pgroup,
      )
  
      num_devices = (
          torch.cuda.device_count() if torch.cuda.is_available() else 1
      )
      assert num_devices > 0
      utils.init_random_seed(0)
  
      benchmark_config = utils.create_benchmark_config(
          args.model_name, config_class
      )
      model_specs = utils.get_model_specs(args.model_name, config_class)
      model_config = utils.create_model_config(
          args,
          benchmark_config=benchmark_config,
          model_specs=model_specs,
      )
      model = model_config["model"]
  
      balance = generate_balance(min(num_devices, 4), len(model))
      pipe_model = Pipe(
          model, balance, chunks=args.chunks, checkpoint=args.checkpoint
      )
      del model
      del model_config["model"]
  
      if args.dry_run:
          train(
              model_config,
              pipe_model,
              benchmark_config,
              model_specs,
              args,
          )
      else:
          benchmark_language_model(
              model_config,
              pipe_model,
              benchmark_config,
              model_specs,
              config_class,
              args,
          )
  
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 12 for calling a global function with example usage: benchmark_single_process(config_class, args) without return types