class_docstr: A class that featurizes using Mitie.
class_docstr_tok: ["A","class","that","featurizes","using","Mitie","."]
code: def _set_features(
      self,
      message: Message,
      sequence_features: np.ndarray,
      sentence_features: np.ndarray,
      attribute: Text,
  ) -> None:
      final_sequence_features = Features(
          sequence_features,
          FEATURE_TYPE_SEQUENCE,
          attribute,
          self._config[FEATURIZER_CLASS_ALIAS],
      )
      message.add_features(final_sequence_features)
  
      final_sentence_features = Features(
          sentence_features,
          FEATURE_TYPE_SENTENCE,
          attribute,
          self._config[FEATURIZER_CLASS_ALIAS],
      )
      message.add_features(final_sentence_features)
  
imports: from __future__ import annotations
  import numpy
  import logging
  import typing
  from typing import Any, List, Text, Dict, Tuple, Type
  from rasa.engine.graph import GraphComponent, 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.featurizers.dense_featurizer.dense_featurizer import DenseFeaturizer
  from rasa.nlu.tokenizers.tokenizer import Token, Tokenizer
  from rasa.nlu.constants import DENSE_FEATURIZABLE_ATTRIBUTES, FEATURIZER_CLASS_ALIAS, TOKENS_NAMES
  from rasa.nlu.utils.mitie_utils import MitieModel, MitieNLP
  from rasa.utils.tensorflow.constants import MEAN_POOLING, POOLING
  from rasa.shared.nlu.training_data.features import Features
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.constants import FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE
  from rasa.shared.nlu.training_data.training_data import TrainingData
label_desc: Use image node_id 12 for calling the MitieFeaturizer obj's underlying member method code with example usage: obj._set_features(message, sequence_features, sentence_features, attribute) without return types