src/transformers/models/roberta_prelayernorm/modeling_tf_roberta_prelayernorm.py/TFRobertaPreLayerNormForCausalLM/__init__
class TFRobertaPreLayerNormForCausalLM:    def __init__(self, config: RobertaPreLayerNormConfig, *inputs, **kwargs):
        super().__init__(config, *inputs, **kwargs)

        if not config.is_decoder:
            logger.warning(
                "If you want to use `TFRobertaPreLayerNormLMHeadModel` as a standalone, add `is_decoder=True.`"
            )

        self.roberta_prelayernorm = TFRobertaPreLayerNormMainLayer(
            config, add_pooling_layer=False, name="roberta_prelayernorm"
        )
        self.lm_head = TFRobertaPreLayerNormLMHead(
            config, input_embeddings=self.roberta_prelayernorm.embeddings, name="lm_head"
        )