code: def __init__(self, *, pad_to_max: bool = True):
      if self.base is None:
          raise ValueError(
              "`transformers` is needed for `ICLIPTokenizer`"
          )
      self.tokenizer = self.base.from_pretrained(self.tag)
      self.bos_token_id = self.tokenizer.bos_token_id
      self.eos_token_id = self.tokenizer.eos_token_id
      self.comma_token_id = self.tokenizer.get_vocab().get(",</w>")
      self.pad_to_max = pad_to_max
  
file_path: carefree-learn/cflearn/models/nlp/tokenizers/clip.py
imports: import numpy
  from typing import Any
  from typing import List
  from typing import Type
  from typing import Union
  from .schema import ITokenizer
label_desc: Use image node_id 1 to create a new ICLIPTokenizer object from inherited base classes: ITokenizer with example: obj = ICLIPTokenizer()