code: def get_tokenizer(parameters):
      tokenizer = BertTokenizer.from_pretrained(
          parameters["path_to_model"],
          do_lower_case=parameters["lowercase_flag"],
      )
      return tokenizer
  
imports: import torch
  import os
  import numpy
  from pytorch_transformers.modeling_bert import BertPreTrainedModel, BertConfig, BertModel
  from pytorch_transformers.tokenization_bert import BertTokenizer
  from torch.utils.data import DataLoader, SequentialSampler, TensorDataset
  from torch import nn
  from torch.nn import CrossEntropyLoss, MSELoss
  from tqdm import tqdm
  from pytorch_transformers.optimization import AdamW, WarmupLinearSchedule
  from pytorch_transformers.file_utils import PYTORCH_PRETRAINED_BERT_CACHE
label_desc: Use image node_id 5 for calling the BertReranker obj's underlying member method code with example usage: obj.get_tokenizer(parameters) and returns: tokenizer