code: def main():
      corpus_folder = "bert-ner/data"
      corpus = TokenClassificationCorpus(corpus_folder)
      tokenizer = AutoTokenizer.from_pretrained(
          BERT_MODEL_NAME, use_fast=False
      )
      datamodule = TokenClassificationDataModule(corpus, tokenizer)
      model = BertForTokenClassification(num_labels=corpus.num_labels)
      logger = WandbLogger(
          project="phobert-token-classification", log_model=False
      )
      trainer = pl.Trainer(
          max_epochs=20,
          checkpoint_callback=False,
          gpus=-1,
          logger=logger,
      )
      trainer.fit(model, datamodule=datamodule)
  
imports: import logging
  from os.path import join
  import pytorch_lightning
  from pytorch_lightning.loggers import WandbLogger
  from torch.optim import AdamW
  import torch.nn
  import torch
  from torchmetrics import F1
  from torch.utils.data import DataLoader, Dataset
  from transformers import AutoTokenizer, AutoModel
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types