class_docstr: Tokenizer that uses SpaCy.
class_docstr_tok: ["Tokenizer","that","uses","SpaCy","."]
docstr: Tokenizes the text of the provided attribute of the incoming message.
docstr_tok: ["Tokenizes","the","text","of","the","provided","attribute","of","the","incoming","message","."]
code: def tokenize(self, message: Message, attribute: Text) -> List[Token]:
      """Tokenizes the text of the provided attribute of the incoming message."""
      doc = self._get_doc(message, attribute)
      if not doc:
          return []
  
      tokens = [
          Token(
              t.text,
              t.idx,
              lemma=t.lemma_,
              data={POS_TAG_KEY: self._tag_of_token(t)},
          )
          for t in doc
          if t.text and t.text.strip()
      ]
  
      return self._apply_token_pattern(tokens)
  
file_path: rasa/rasa/nlu/tokenizers/spacy_tokenizer.py
imports: import typing
  from typing import Dict, Text, List, Any, Optional, Type
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.nlu.utils.spacy_utils import SpacyNLP
  from rasa.nlu.tokenizers.tokenizer import Token, Tokenizer
  from rasa.nlu.constants import SPACY_DOCS
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 5 for calling the SpacyTokenizer obj's underlying member method code with example usage: obj.tokenize(message, attribute) and returns: self, list