src/transformers/models/albert/modeling_tf_albert.py/TFAlbertEmbeddings/__init__
class TFAlbertEmbeddings:    def __init__(self, config: AlbertConfig, **kwargs):
        super().__init__(**kwargs)

        self.vocab_size = config.vocab_size
        self.type_vocab_size = config.type_vocab_size
        self.embedding_size = config.embedding_size
        self.max_position_embeddings = config.max_position_embeddings
        self.initializer_range = config.initializer_range
        self.embeddings_sum = tf.keras.layers.Add()
        self.LayerNorm = tf.keras.layers.LayerNormalization(epsilon=config.layer_norm_eps, name="LayerNorm")
        self.dropout = tf.keras.layers.Dropout(rate=config.hidden_dropout_prob)