code: def __init__(self, url=None):
      from transformers import (
          DistilBertTokenizer,
          DistilBertForMaskedLM,
      )
      import torch
  
      self.torch = torch
      self.url = url
      if url is None:
          self.device = torch.device(
              "cuda" if torch.cuda.is_available() else "cpu"
          )
          self.bert_tokenizer = DistilBertTokenizer.from_pretrained(
              "distilbert-base-cased"
          )
          self.bert = DistilBertForMaskedLM.from_pretrained(
              "distilbert-base-cased"
          )
          self.bert.to(self.device)
          self.bert.eval()
  
imports: from .None import utils
  from .None import anchor_base
  from .None import anchor_explanation
  import numpy
  import json
  import os
  import string
  import sys
  from io import open
  import numpy
label_desc: Use image node_id 1 to create a new TextGenerator object from inherited base classes: object with example: obj = TextGenerator(url)