code: def test_run_ner_no_trainer(self):
      # with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
      epochs = 7 if get_gpu_count() > 1 else 2
  
      tmp_dir = self.get_auto_remove_tmp_dir()
      testargs = f"""
              {self.examples_dir}/pytorch/token-classification/run_ner_no_trainer.py
              --model_name_or_path bert-base-uncased
              --train_file tests/fixtures/tests_samples/conll/sample.json
              --validation_file tests/fixtures/tests_samples/conll/sample.json
              --output_dir {tmp_dir}
              --learning_rate=2e-4
              --per_device_train_batch_size=2
              --per_device_eval_batch_size=2
              --num_train_epochs={epochs}
              --seed 7
              --checkpointing_steps epoch
              --with_tracking
          """.split()
  
      run_command(self._launch_args + testargs)
      result = get_results(tmp_dir)
      self.assertGreaterEqual(result["eval_accuracy"], 0.75)
      self.assertLess(result["train_loss"], 0.5)
      self.assertTrue(os.path.exists(os.path.join(tmp_dir, "epoch_0")))
      self.assertTrue(
          os.path.exists(os.path.join(tmp_dir, "ner_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 6 for calling the ExamplesTestsNoTrainer obj's underlying member method code with example usage: obj.test_run_ner_no_trainer() without return types