def _prepare_layers(self) -> None:
    self.text_name = TEXT
    self._tf_layers[f'sequence_layer.{self.text_name}'] = rasa_layers.RasaSequenceLayer(self.text_name, self.data_signature[self.text_name], self.config)
    if self.config[MASKED_LM]:
        self._prepare_mask_lm_loss(self.text_name)
    if self.config[INTENT_CLASSIFICATION]:
        self.label_name = (TEXT if self.config[SHARE_HIDDEN_LAYERS] else LABEL)
        label_config = self.config.copy()
        label_config.update({SPARSE_INPUT_DROPOUT: False, DENSE_INPUT_DROPOUT: False})
        self._tf_layers[f'feature_combining_layer.{self.label_name}'] = rasa_layers.RasaFeatureCombiningLayer(self.label_name, self.label_signature[self.label_name], label_config)
        self._prepare_ffnn_layer(self.label_name, self.config[HIDDEN_LAYERS_SIZES][self.label_name], self.config[DROP_RATE])
        self._prepare_label_classification_layers(predictor_attribute=TEXT)
    if self.config[ENTITY_RECOGNITION]:
        self._prepare_entity_recognition_layers()
def _prepare_layers(self) -> None:
    self.text_name = TEXT
    self._tf_layers[f'sequence_layer.{self.text_name}'] = rasa_layers.RasaSequenceLayer(self.text_name, self.data_signature[self.text_name], self.config)
    if self.config[MASKED_LM]:
        self._prepare_mask_lm_loss(self.text_name)
    if self.config[INTENT_CLASSIFICATION]:
        self.label_name = (TEXT if self.config[SHARE_HIDDEN_LAYERS] else LABEL)
        label_config = self.config.copy()
        label_config.update({SPARSE_INPUT_DROPOUT: False, DENSE_INPUT_DROPOUT: False})
        self._tf_layers[f'feature_combining_layer.{self.label_name}'] = rasa_layers.RasaFeatureCombiningLayer(self.label_name, self.label_signature[self.label_name], label_config)
        self._prepare_ffnn_layer(self.label_name, self.config[HIDDEN_LAYERS_SIZES][self.label_name], self.config[DROP_RATE])
        self._prepare_label_classification_layers(predictor_attribute=TEXT)
    if self.config[ENTITY_RECOGNITION]:
        self._prepare_entity_recognition_layers()