code: def on_test_end(
      self, trainer: pl.Trainer, pl_module: pl.LightningModule
  ):
      rank_zero_info("***** Test results *****")
      metrics = trainer.callback_metrics
      # Log and save results to file
      output_test_results_file = os.path.join(
          pl_module.hparams.output_dir, "test_results.txt"
      )
      with open(output_test_results_file, "w") as writer:
          for key in sorted(metrics):
              if key not in ["log", "progress_bar"]:
                  rank_zero_info(
                      "{} = {}\n".format(key, str(metrics[key]))
                  )
                  writer.write(
                      "{} = {}\n".format(key, str(metrics[key]))
                  )
  
imports: import argparse
  import logging
  import os
  from pathlib import Path
  from typing import Any, Dict
  import pytorch_lightning
  from pytorch_lightning.utilities import rank_zero_info
  from transformers import AdamW, AutoConfig, AutoModel, AutoModelForPreTraining, AutoModelForQuestionAnswering, AutoModelForSeq2SeqLM, AutoModelForSequenceClassification, AutoModelForTokenClassification, AutoModelWithLMHead, AutoTokenizer, PretrainedConfig, PreTrainedTokenizer
  from transformers.optimization import Adafactor, get_cosine_schedule_with_warmup, get_cosine_with_hard_restarts_schedule_with_warmup, get_linear_schedule_with_warmup, get_polynomial_decay_schedule_with_warmup
  from transformers.utils.versions import require_version
label_desc: Use image node_id 3 for calling the LoggingCallback obj's underlying member method code with example usage: obj.on_test_end(trainer, pl_module) without return types