code: def test_run_image_classification_no_trainer(self):
      tmp_dir = self.get_auto_remove_tmp_dir()
      testargs = f"""
              {self.examples_dir}/pytorch/image-classification/run_image_classification_no_trainer.py
              --model_name_or_path google/vit-base-patch16-224-in21k
              --dataset_name hf-internal-testing/cats_vs_dogs_sample
              --learning_rate 1e-4
              --per_device_train_batch_size 2
              --per_device_eval_batch_size 1
              --max_train_steps 2
              --train_val_split 0.1
              --seed 42
              --output_dir {tmp_dir}
              --with_tracking
              --checkpointing_steps 1
              --label_column_name labels
          """.split()
  
      run_command(self._launch_args + testargs)
      result = get_results(tmp_dir)
      # The base model scores a 25%
      self.assertGreaterEqual(result["eval_accuracy"], 0.4)
      self.assertTrue(os.path.exists(os.path.join(tmp_dir, "step_1")))
      self.assertTrue(
          os.path.exists(
              os.path.join(tmp_dir, "image_classification_no_trainer")
          )
      )
  
imports: import argparse
  import json
  import logging
  import os
  import shutil
  import sys
  import tempfile
  import unittest
  from unittest import mock
  from accelerate.utils import write_basic_config
  from transformers.testing_utils import TestCasePlus, backend_device_count, run_command, slow, torch_device
label_desc: Use image node_id 12 for calling the ExamplesTestsNoTrainer obj's underlying member method code with example usage: obj.test_run_image_classification_no_trainer() without return types