src/transformers/models/roformer/modeling_tf_roformer.py/TFRoFormerMainLayer/__init__
class TFRoFormerMainLayer:    def __init__(self, config: RoFormerConfig, add_pooling_layer: bool = True, **kwargs):
        super().__init__(**kwargs)

        self.config = config

        self.embeddings = TFRoFormerEmbeddings(config, name="embeddings")
        if config.embedding_size != config.hidden_size:
            self.embeddings_project = tf.keras.layers.Dense(config.hidden_size, name="embeddings_project")

        self.encoder = TFRoFormerEncoder(config, name="encoder")