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.
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code: def save_vocabulary(
      self, save_directory: str, filename_prefix: Optional[str] = None
  ):
      return ()
  
file_path: H2O/h2o_flexgen/benchmark/third_party/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 10 for calling the CanineTokenizer obj's underlying member method code with example usage: obj.save_vocabulary(save_directory, filename_prefix) and returns: 