class_docstr: Creates features for entity extraction.
class_docstr_tok: ["Creates","features","for","entity","extraction","."]
docstr: Initialize the tokenizer.
docstr_tok: ["Initialize","the","tokenizer","."]
code: def __init__(self, config: Dict[Text, Any]) -> None:
      """Initialize the tokenizer."""
      super().__init__(config)
      self.emoji_pattern = rasa.utils.io.get_emoji_regex()
  
      if "case_sensitive" in self._config:
          rasa.shared.utils.io.raise_warning(
              "The option 'case_sensitive' was moved from the tokenizers to the "
              "featurizers.",
              docs=DOCS_URL_COMPONENTS,
          )
  
imports: from __future__ import annotations
  from typing import Any, Dict, List, Optional, Text
  import regex
  import rasa.shared.utils.io
  import rasa.utils.io
  from rasa.engine.graph import ExecutionContext
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.tokenizers.tokenizer import Token, Tokenizer
  from rasa.shared.constants import DOCS_URL_COMPONENTS
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 3 to create a new WhitespaceTokenizer object from inherited base classes: Tokenizer with example: obj = WhitespaceTokenizer(config)