code: def get_trainer(self):
      if self.trainer is None:
          self.trainer = Trainer(
              model=self.model,
              args=self.training_arguments,
              train_dataset=self.data.train_dl.dataset,
              eval_dataset=self.data.val_dl.dataset,
              compute_metrics=self.compute_metrics,
          )
  
      return self.trainer
  
imports: import os
  import logging
  import torch
  import numpy
  from .data_ner import BertNERDataBunch
  from torch import nn
  from seqeval.metrics import f1_score, precision_score, recall_score
  from typing import Dict, List, Optional, Tuple
  from .learner_util import Learner
  from transformers import AutoConfig, AutoModelForTokenClassification, Trainer, TrainingArguments, EvalPrediction, HfArgumentParser
label_desc: Use image node_id 8 for calling the BertNERLearner obj's underlying member method code with example usage: obj.get_trainer() and returns: self