src/transformers/models/deberta/modeling_tf_deberta.py/TFDebertaLMPredictionHead/__init__
class TFDebertaLMPredictionHead:    def __init__(self, config: DebertaConfig, input_embeddings: tf.keras.layers.Layer, **kwargs):
        super().__init__(**kwargs)

        self.vocab_size = config.vocab_size
        self.hidden_size = config.hidden_size

        self.transform = TFDebertaPredictionHeadTransform(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