code: def _get_mask_for(
      self,
      tf_batch_data: Dict[Text, Dict[Text, List[tf.Tensor]]],
      key: Text,
      sub_key: Text,
  ) -> Optional[tf.Tensor]:
      if key not in tf_batch_data or sub_key not in tf_batch_data[key]:
          return None
  
      sequence_lengths = tf.cast(
          tf_batch_data[key][sub_key][0], dtype=tf.int32
      )
      return rasa_layers.compute_mask(sequence_lengths)
  
imports: import time
  import random
  import tensorflow
  import numpy
  import logging
  import os
  from collections import defaultdict
  from typing import List, Text, Dict, Tuple, Union, Optional, Any, TYPE_CHECKING
  from keras.utils import tf_utils
  from keras import Model
  from rasa.shared.constants import DIAGNOSTIC_DATA
  from rasa.utils.tensorflow.constants import LABEL, IDS, INTENT_CLASSIFICATION, SENTENCE, SEQUENCE_LENGTH, RANDOM_SEED, EMBEDDING_DIMENSION, REGULARIZATION_CONSTANT, SIMILARITY_TYPE, CONNECTION_DENSITY, NUM_NEG, LOSS_TYPE, MAX_POS_SIM, MAX_NEG_SIM, USE_MAX_NEG_SIM, NEGATIVE_MARGIN_SCALE, SCALE_LOSS, LEARNING_RATE, CONSTRAIN_SIMILARITIES, MODEL_CONFIDENCE, RUN_EAGERLY
  from rasa.utils.tensorflow.model_data import RasaModelData, FeatureSignature, FeatureArray
  import rasa.utils.train_utils
  from rasa.utils.tensorflow import layers
  from rasa.utils.tensorflow import rasa_layers
  from rasa.utils.tensorflow.data_generator import RasaDataGenerator, RasaBatchDataGenerator
  from rasa.shared.nlu.constants import TEXT
  from rasa.shared.exceptions import RasaException
  from rasa.utils.tensorflow.types import BatchData, MaybeNestedBatchData
label_desc: Use image node_id 17 for calling the TransformerRasaModel obj's underlying member method code with example usage: obj._get_mask_for(tf_batch_data, key, sub_key) and returns: rasa_layers, None