class_docstr: A training module for NER. See BaseTransformer for the core options.
code: def forward(self, **inputs):
      return self.model(**inputs)
  
imports: import argparse
  import glob
  import logging
  import os
  from argparse import Namespace
  from importlib import import_module
  import numpy
  import torch
  from seqeval.metrics import accuracy_score, f1_score, precision_score, recall_score
  from torch.nn import CrossEntropyLoss
  from torch.utils.data import DataLoader, TensorDataset
  from lightning_base import BaseTransformer, add_generic_args, generic_train
  from utils_ner import TokenClassificationTask
label_desc: Use image node_id 2 for calling the NERTransformer obj's underlying member method code with example usage: obj.forward() and returns: self