code: def test_run_glue_no_trainer(self):
      tmp_dir = self.get_auto_remove_tmp_dir()
      testargs = f"""
              {self.examples_dir}/pytorch/text-classification/run_glue_no_trainer.py
              --model_name_or_path distilbert-base-uncased
              --output_dir {tmp_dir}
              --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
              --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
              --per_device_train_batch_size=2
              --per_device_eval_batch_size=1
              --learning_rate=1e-4
              --seed=42
              --checkpointing_steps epoch
              --with_tracking
          """.split()
  
      if is_cuda_and_apex_available():
          testargs.append("--fp16")
  
      run_command(self._launch_args + testargs)
      result = get_results(tmp_dir)
      self.assertGreaterEqual(result["eval_accuracy"], 0.75)
      self.assertTrue(os.path.exists(os.path.join(tmp_dir, "epoch_0")))
      self.assertTrue(
          os.path.exists(os.path.join(tmp_dir, "glue_no_trainer"))
      )
  
imports: import argparse
  import json
  import logging
  import os
  import shutil
  import sys
  import tempfile
  from unittest import mock
  import torch
  from accelerate.utils import write_basic_config
  from transformers.testing_utils import TestCasePlus, get_gpu_count, is_flaky, run_command, slow, torch_device
  from transformers.utils import is_apex_available
label_desc: Use image node_id 3 for calling the ExamplesTestsNoTrainer obj's underlying member method code with example usage: obj.test_run_glue_no_trainer() without return types