code: def test_pytorch2_hf_language_modeling_distributed() -> None:
      test_dir = "hf_language_modeling"
  
      config = conf.load_config(
          conf.hf_trainer_examples_path(f"{test_dir}/distributed.yaml")
      )
      config = conf.set_pt2_image(config)
      config = conf.set_slots_per_trial(config, 4)
      config["searcher"]["max_length"]["batches"] = 50
  
      # Our hardware GPUs have only 16gb memory, lower memory use with smaller batches.
      config = conf.set_entrypoint(
          config,
          config["entrypoint"]
          .replace(
              "--per_device_train_batch_size 8",
              "--per_device_train_batch_size 2",
          )
          .replace(
              "--per_device_eval_batch_size 8",
              "--per_device_eval_batch_size 2",
          ),
      )
  
      exp.run_basic_test_with_temp_config(
          config, conf.hf_trainer_examples_path(test_dir), 1
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_pytorch2_hf_language_modeling_distributed() without return types