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

        self.attention = TFAlbertAttention(config, name="attention")
        self.ffn = tf.keras.layers.Dense(
            units=config.intermediate_size, kernel_initializer=get_initializer(config.initializer_range), name="ffn"
        )

        if isinstance(config.hidden_act, str):
            self.activation = get_tf_activation(config.hidden_act)
        else:
            self.activation = config.hidden_act

        self.ffn_output = tf.keras.layers.Dense(
            units=config.hidden_size, kernel_initializer=get_initializer(config.initializer_range), name="ffn_output"
        )
        self.full_layer_layer_norm = tf.keras.layers.LayerNormalization(
            epsilon=config.layer_norm_eps, name="full_layer_layer_norm"
        )
        self.dropout = tf.keras.layers.Dropout(rate=config.hidden_dropout_prob)