class_docstr: Base class for all featurizers.
class_docstr_tok: ["Base","class","for","all","featurizers","."]
docstr: Adds sequence and sentence features for the attribute to the given message.
  
  Args:
    sequence: sequence feature matrix
    sentence: sentence feature matrix
    attribute: the attribute which both features describe
    message: the message to which we want to add those features
docstr_tok: ["Adds","sequence","and","sentence","features","for","the","attribute","to","the","given","message",".","Args",":","sequence",":","sequence","feature","matrix","sentence",":","sentence","feature","matrix","attribute",":","the","attribute","which","both","features","describe","message",":","the","message","to","which","we","want","to","add","those","features"]
code: def add_features_to_message(
      self,
      sequence: FeatureType,
      sentence: Optional[FeatureType],
      attribute: Text,
      message: Message,
  ) -> None:
      """Adds sequence and sentence features for the attribute to the given message.
  
      Args:
        sequence: sequence feature matrix
        sentence: sentence feature matrix
        attribute: the attribute which both features describe
        message: the message to which we want to add those features
      """
      for type, features in [
          (FEATURE_TYPE_SEQUENCE, sequence),
          (FEATURE_TYPE_SENTENCE, sentence),
      ]:
          if features is not None:
              wrapped_feature = Features(
                  features, type, attribute, self._identifier
              )
              message.add_features(wrapped_feature)
  
file_path: rasa/rasa/nlu/featurizers/featurizer.py
imports: from __future__ import annotations
  from abc import abstractmethod, ABC
  from collections import Counter
  from typing import Generic, Iterable, Text, Optional, Dict, Any, TypeVar
  from rasa.nlu.constants import FEATURIZER_CLASS_ALIAS
  from rasa.shared.nlu.training_data.features import Features
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.exceptions import InvalidConfigException
  from rasa.shared.nlu.constants import FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE
label_desc: Use image node_id 4 for calling the Featurizer obj's underlying member method code with example usage: obj.add_features_to_message(sequence, sentence, attribute, message) without return types