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","."]
code: def _compute_sentence_encodings(
      self, batch_examples: List[Message], attribute: Text = TEXT
  ) -> np.ndarray:
      # Get text for attribute of each example
      batch_attribute_text = [
          ex.get(attribute) for ex in batch_examples
      ]
      sentence_encodings = self._sentence_encoding_of_text(
          batch_attribute_text
      )
  
      # convert them to a sequence of 1
      return np.reshape(
          sentence_encodings, (len(batch_examples), 1, -1)
      )
  
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 12 for calling the ConveRTFeaturizer obj's underlying member method code with example usage: obj._compute_sentence_encodings(batch_examples, attribute) and returns: np