code: def test_run_clm_adapter(self):
      stream_handler = logging.StreamHandler(sys.stdout)
      logger.addHandler(stream_handler)
  
      tmp_dir = self.get_auto_remove_tmp_dir()
      testargs = f"""
              run_clm.py
              --model_name_or_path gpt2
              --train_file ./tests/fixtures/sample_text.txt
              --validation_file ./tests/fixtures/sample_text.txt
              --do_train
              --do_eval
              --learning_rate 1e-3
              --block_size 128
              --per_device_train_batch_size 5
              --per_device_eval_batch_size 5
              --num_train_epochs 2
              --output_dir {tmp_dir}
              --overwrite_output_dir
              --train_adapter
              --adapter_config=double_seq_bn[reduction_factor=8]
              """.split()
  
      if torch.cuda.device_count() > 1:
          # Skipping because there are not enough batches to train the model + would need a drop_last to work.
          return
  
      if torch_device != "cuda":
          testargs.append("--no_cuda")
  
      with patch.object(sys, "argv", testargs):
          run_clm.main()
          result = get_results(tmp_dir)
          self.assertLess(result["perplexity"], 100)
  
imports: import json
  import logging
  import os
  import sys
  from unittest.mock import patch
  import torch
  from transformers.testing_utils import TestCasePlus, get_gpu_count, slow, torch_device
label_desc: Use image node_id 5 for calling the AdapterExamplesTests obj's underlying member method code with example usage: obj.test_run_clm_adapter() without return types