code: def test_cpu_gpu_loading_random_device_map(self):
      from transformers import AutoConfig, AutoModelForCausalLM
  
      r"""
          A test to check is dispatching a model on cpu & gpu works correctly using a random `device_map`.
          """
      device_map = {
          "transformer.word_embeddings": "cpu",
          "transformer.word_embeddings_layernorm": 0,
          "lm_head": "cpu",
          "transformer.h.0": 0,
          "transformer.h.1": 0,
          "transformer.h.2": 0,
          "transformer.h.3": 0,
          "transformer.h.4": 0,
          "transformer.h.5": 0,
          "transformer.h.6": 0,
          "transformer.h.7": 0,
          "transformer.h.8": 0,
          "transformer.h.9": 1,
          "transformer.h.10": 0,
          "transformer.h.11": 1,
          "transformer.h.12": 0,
          "transformer.h.13": 0,
          "transformer.h.14": 1,
          "transformer.h.15": 0,
          "transformer.h.16": 0,
          "transformer.h.17": 1,
          "transformer.h.18": 1,
          "transformer.h.19": 0,
          "transformer.h.20": 1,
          "transformer.h.21": 1,
          "transformer.h.22": 0,
          "transformer.h.23": 0,
          "transformer.ln_f": 1,
      }
  
      bnb_quantization_config = BnbQuantizationConfig(load_in_4bit=True)
  
      with init_empty_weights():
          model_4bit = AutoModelForCausalLM.from_config(
              AutoConfig.from_pretrained(self.model_name)
          )
  
      model_4bit.tie_weights()
      model_4bit = load_and_quantize_model(
          model_4bit,
          bnb_quantization_config,
          weights_location=self.weights_location,
          device_map=device_map,
          no_split_module_classes=["BloomBlock"],
      )
      self.check_inference_correctness(model_4bit)
  
imports: import gc
  import tempfile
  import unittest
  import torch
  import torch.nn
  from accelerate import Accelerator, init_empty_weights
  from accelerate.test_utils import require_bnb, require_cuda, require_huggingface_suite, require_multi_gpu, slow
  from accelerate.utils.bnb import load_and_quantize_model
  from accelerate.utils.dataclasses import BnbQuantizationConfig
label_desc: Use image node_id 8 for calling the Bnb4BitEmptyModelTest obj's underlying member method code with example usage: obj.test_cpu_gpu_loading_random_device_map() without return types