class_docstr: Featurizer using ConveRT model.
  
  Loads the ConveRT(https://github.com/PolyAI-LDN/polyai-models#convert)
  model from TFHub and computes sentence and sequence level feature representations
  for dense featurizable attributes of each message object.
class_docstr_tok: ["Featurizer","using","ConveRT","model",".","Loads","the","ConveRT","(","https",":","\/\/github.com\/PolyAI-LDN\/polyai-models","#","convert",")","model","from","TFHub","and","computes","sentence","and","sequence","level","feature","representations","for","dense","featurizable","attributes","of","each","message","object","."]
docstr: Featurize an incoming message with the ConveRT model.
  
  Args:
      messages: Message to be featurized
docstr_tok: ["Featurize","an","incoming","message","with","the","ConveRT","model",".","Args",":","messages",":","Message","to","be","featurized"]
code: def process(self, messages: List[Message]) -> List[Message]:
      """Featurize an incoming message with the ConveRT model.
  
      Args:
          messages: Message to be featurized
      """
      for message in messages:
          for attribute in {TEXT, ACTION_TEXT}:
              if message.get(attribute):
                  (
                      sequence_features,
                      sentence_features,
                  ) = self._compute_features(
                      [message], attribute=attribute
                  )
  
                  self._set_features(
                      [message],
                      sequence_features,
                      sentence_features,
                      attribute,
                  )
      return messages
  
imports: from __future__ import annotations
  import logging
  import os
  from typing import Any, Dict, List, Optional, Text, Tuple, Type
  import tensorflow
  from tensorflow.python.eager.wrap_function import WrappedFunction
  from tqdm import tqdm
  import numpy
  from rasa.engine.graph import GraphComponent, ExecutionContext
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.storage import ModelStorage
  from rasa.engine.storage.resource import Resource
  import rasa.shared.utils.io
  import rasa.core.utils
  from rasa.nlu.tokenizers.tokenizer import Token, Tokenizer
  from rasa.nlu.featurizers.dense_featurizer.dense_featurizer import DenseFeaturizer
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
  from rasa.nlu.constants import DENSE_FEATURIZABLE_ATTRIBUTES, TOKENS_NAMES, NUMBER_OF_SUB_TOKENS
  from rasa.shared.nlu.constants import TEXT, ACTION_TEXT
  from rasa.exceptions import RasaException
  import rasa.nlu.utils
  import rasa.utils.train_utils
label_desc: Use image node_id 19 for calling the ConveRTFeaturizer obj's underlying member method code with example usage: obj.process(messages) and returns: messages