src/transformers/models/roberta_prelayernorm/modeling_tf_roberta_prelayernorm.py/TFRobertaPreLayerNormMainLayer/__init__
class TFRobertaPreLayerNormMainLayer:    def __init__(self, config, add_pooling_layer=True, **kwargs):
        super().__init__(**kwargs)

        self.config = config
        self.is_decoder = config.is_decoder

        self.num_hidden_layers = config.num_hidden_layers
        self.initializer_range = config.initializer_range
        self.output_attentions = config.output_attentions
        self.output_hidden_states = config.output_hidden_states
        self.return_dict = config.use_return_dict
        self.encoder = TFRobertaPreLayerNormEncoder(config, name="encoder")
        self.LayerNorm = tf.keras.layers.LayerNormalization(epsilon=config.layer_norm_eps, name="LayerNorm")
        self.pooler = TFRobertaPreLayerNormPooler(config, name="pooler") if add_pooling_layer else None
        # The embeddings must be the last declaration in order to follow the weights order
        self.embeddings = TFRobertaPreLayerNormEmbeddings(config, name="embeddings")