code: def test_literal_device():
      model = OneLayerNet(128, 128)
  
      os.environ["RANK"] = "0"
      os.environ["WORLD_SIZE"] = "1"
      os.environ["MASTER_ADDR"] = "127.0.0.1"
      os.environ["MASTER_PORT"] = "8088"
      os.environ["LOCAL_RANK"] = "0"
      deepspeed.init_distributed(
          get_accelerator().communication_backend_name()
      )
      deepspeed.initialize(model=model, config="ds_config.json")
      string = get_accelerator().device_name()  #'xpu' or 'cuda'
      string0 = get_accelerator().device_name(0)  #'xpu:0' or 'cuda:0'
      string1 = get_accelerator().device_name(1)  #'xpu:1' or 'cuda:1'
      assert string == "xpu" or string == "cuda"
      assert string0 == "xpu:0" or string0 == "cuda:0"
      assert string1 == "xpu:1" or string1 == "cuda:1"
  
file_path: deepspeed/tests/accelerator/test_ds_init.py
imports: import os
  import torch
  import deepspeed
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 1 for calling a global function with example usage: test_literal_device() without return types