code: def test_run_glue(self):
      import xla_spawn
  
      tmp_dir = self.get_auto_remove_tmp_dir()
      testargs = f"""
              ./examples/pytorch/text-classification/run_glue.py
              --num_cores=8
              ./examples/pytorch/text-classification/run_glue.py
              --model_name_or_path distilbert-base-uncased
              --output_dir {tmp_dir}
              --overwrite_output_dir
              --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
              --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
              --do_train
              --do_eval
              --debug tpu_metrics_debug
              --per_device_train_batch_size=2
              --per_device_eval_batch_size=1
              --learning_rate=1e-4
              --max_steps=10
              --warmup_steps=2
              --seed=42
              --max_seq_length=128
              """.split()
  
      with patch.object(sys, "argv", testargs):
          start = time()
          xla_spawn.main()
          end = time()
  
          result = get_results(tmp_dir)
          self.assertGreaterEqual(result["eval_accuracy"], 0.75)
  
          # Assert that the script takes less than 500 seconds to make sure it doesn't hang.
          self.assertLess(end - start, 500)
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/examples/pytorch/test_xla_examples.py
imports: import json
  import logging
  import os
  import sys
  from time import time
  from unittest.mock import patch
  from transformers.testing_utils import TestCasePlus, require_torch_tpu
label_desc: Use image node_id 1 for calling the TorchXLAExamplesTests obj's underlying member method code with example usage: obj.test_run_glue() without return types