class_docstr: Base class for all featurizers.
class_docstr_tok: ["Base","class","for","all","featurizers","."]
docstr: Instantiates a new featurizer.
  
  Args:
    config: configuration
    name: a name that can be used as identifier, in case the configuration does
      not specify an `alias` (or this `alias` is None)
docstr_tok: ["Instantiates","a","new","featurizer",".","Args",":","config",":","configuration","name",":","a","name","that","can","be","used","as","identifier",",","in","case","the","configuration","does","not","specify","an","`","alias","`","(","or","this","`","alias","`","is","None",")"]
code: def __init__(self, name: Text, config: Dict[Text, Any]) -> None:
      """Instantiates a new featurizer.
  
      Args:
        config: configuration
        name: a name that can be used as identifier, in case the configuration does
          not specify an `alias` (or this `alias` is None)
      """
      super().__init__()
      self.validate_config(config)
      self._config = config
      self._identifier = self._config[FEATURIZER_CLASS_ALIAS] or name
  
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 2 to create a new Featurizer object from inherited base classes: Generic, ABC with example: obj = Featurizer(name, config)