class_docstr: Construct a CANINE tokenizer (i.e. a character splitter). It turns text into a sequence of characters, and then
  converts each character into its Unicode code point.
  
  [`CanineTokenizer`] inherits from [`PreTrainedTokenizer`].
  
  Refer to superclass [`PreTrainedTokenizer`] for usage examples and documentation concerning parameters.
  
  Args:
      model_max_length (`int`, *optional*, defaults to 2048):
              The maximum sentence length the model accepts.
code: def vocab_size(self) -> int:
      return self._unicode_vocab_size
  
file_path: transformers/src/transformers/models/canine/tokenization_canine.py
imports: from typing import Dict, List, Optional
  from ...tokenization_utils import AddedToken, PreTrainedTokenizer
  from ...utils import logging
label_desc: Use image node_id 2 for calling the CanineTokenizer obj's underlying member method code with example usage: obj.vocab_size() and returns: self