class_docstr: A class that featurizes using Mitie.
class_docstr_tok: ["A","class","that","featurizes","using","Mitie","."]
docstr: Instantiates a new `MitieFeaturizer` instance.
docstr_tok: ["Instantiates","a","new","`","MitieFeaturizer","`","instance","."]
code: def __init__(
      self, config: Dict[Text, Any], execution_context: ExecutionContext
  ) -> None:
      """Instantiates a new `MitieFeaturizer` instance."""
      super().__init__(execution_context.node_name, config)
      self.pooling_operation = self._config[POOLING]
  
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 4 to create a new MitieFeaturizer object from inherited base classes: DenseFeaturizer, GraphComponent with example: obj = MitieFeaturizer(config, execution_context)