code: def run_and_check(self, args):
      n_gpu = get_gpu_count()
  
      if n_gpu > 1:
          pass
          # XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
          # script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
          # distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
          # cmd = [sys.executable] + distributed_args + args
          # execute_subprocess_async(cmd, env=self.get_env())
          # XXX: test the results - need to save them first into .json file
      else:
          args.insert(0, "run_glue_deebert.py")
          with patch.object(sys, "argv", args):
              result = run_glue_deebert.main()
              for value in result.values():
                  self.assertGreaterEqual(value, 0.666)
  
file_path: transformers/examples/research_projects/deebert/test_glue_deebert.py
imports: import argparse
  import logging
  import sys
  from unittest.mock import patch
  import run_glue_deebert
  from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
label_desc: Use image node_id 2 for calling the DeeBertTests obj's underlying member method code with example usage: obj.run_and_check(args) without return types