src/transformers/models/roformer/modeling_tf_roformer.py/TFRoFormerForMaskedLM/__init__
class TFRoFormerForMaskedLM:    def __init__(self, config: RoFormerConfig, *inputs, **kwargs):
        super().__init__(config, *inputs, **kwargs)

        if config.is_decoder:
            logger.warning(
                "If you want to use `TFRoFormerForMaskedLM` make sure `config.is_decoder=False` for "
                "bi-directional self-attention."
            )

        self.roformer = TFRoFormerMainLayer(config, name="roformer")
        self.mlm = TFRoFormerMLMHead(config, input_embeddings=self.roformer.embeddings, name="mlm___cls")