code: def test_run_summarization_adapter(self):
      stream_handler = logging.StreamHandler(sys.stdout)
      logger.addHandler(stream_handler)
  
      tmp_dir = self.get_auto_remove_tmp_dir()
      testargs = f"""
                  run_summarization.py
                  --model_name_or_path facebook/bart-base
                  --train_file ./tests/fixtures/samples/xsum/sample.json
                  --validation_file ./tests/fixtures/samples/xsum/sample.json
                  --output_dir {tmp_dir}
                  --overwrite_output_dir
                  --max_steps=50
                  --warmup_steps=8
                  --do_train
                  --do_eval
                  --learning_rate=2e-4
                  --per_device_train_batch_size=2
                  --per_device_eval_batch_size=1
                  --predict_with_generate
                  --train_adapter
                  --adapter_config=double_seq_bn[reduction_factor=8]
              """.split()
  
      with patch.object(sys, "argv", testargs):
          run_summarization.main()
          result = get_results(tmp_dir)
          self.assertGreaterEqual(result["eval_rouge1"], 10)
          self.assertGreaterEqual(result["eval_rouge2"], 2)
          self.assertGreaterEqual(result["eval_rougeL"], 7)
          self.assertGreaterEqual(result["eval_rougeLsum"], 7)
  
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 7 for calling the AdapterExamplesTests obj's underlying member method code with example usage: obj.test_run_summarization_adapter() without return types