code: def __init__(self, data_file: str, bert_version: str):
      super().__init__(data_file=data_file)
      self.tokenizer = BertTokenizer.from_pretrained(bert_version)
      df = pd.read_csv(data_file)
      self.target_vocab = Vocabulary(add_unk=False)
      self.target_vocab.add_many(set(df.category))
  
file_path: transfer-nlp/experiments/bert/bert.py
imports: import logging
  from pathlib import Path
  from typing import Tuple
  import numpy
  import pandas
  from pytorch_pretrained_bert import BertTokenizer, BertForSequenceClassification, BertAdam
  from tqdm import tqdm
  from transfer_nlp.loaders.loaders import DatasetSplits, DataFrameDataset
  from transfer_nlp.loaders.vectorizers import Vectorizer
  from transfer_nlp.loaders.vocabulary import Vocabulary
  from transfer_nlp.plugins.config import register_plugin, ExperimentConfig
label_desc: Use image node_id 1 to create a new BertVectorizer object from inherited base classes: Vectorizer with example: obj = BertVectorizer(data_file, bert_version)