src/transformers/models/roformer/modeling_tf_roformer.py/TFRoFormerLMPredictionHead/__init__
class TFRoFormerLMPredictionHead:    def __init__(self, config: RoFormerConfig, input_embeddings: tf.keras.layers.Layer, **kwargs):
        super().__init__(**kwargs)

        self.config = config
        self.embedding_size = config.embedding_size

        self.transform = TFRoFormerPredictionHeadTransform(config, name="transform")

        # The output weights are the same as the input embeddings, but there is
        # an output-only bias for each token.
        self.input_embeddings = input_embeddings